+documentroot /var/www/html/me
+servername url
+serveralias mydomain.se
+ elements to a light blue */
+p {
+color: #c0ffee;
+}
+/* set the color of #sidebar to a light red */
+#sidebar {
+color: #c55;
+}
+/*
elements inside #sidebar inherit their parent's color (#c55) */
+#sidebar p {
+color: inherit;
+}
+/* you may also override inherited styles using the !important annotation */
+#sidebar p:first-of-type {
+color: orange !important;
+}
+important notice:
+for questions related to css, try to demonstrate your code in a reproducible manner using either stack exchange's stack snippets or alternatively any online editor that allows running and sharing code such as js bin, jsfiddle or codepen (though be sure to always include relevant code in the question). "
+0,"this tag is for questions relating to development on a local server, and generally also involves deployment to a remote server. "
+0,did you come right with this function?
+0,i checked the /usr/lib/mono/gac/system.xml.linq directory and only the directory 3.5.0.0__b77a5c561934e089 was present.
+0,"i am developing metro style app which should read data from external device using serial communication but unfortunately metro apps does not support ""serial and parallel port api ""."
+0,opentk will automaticaly detect linux console environment if program is launched from a console.
+0,i am new to python so please forgive me in advance ;-) i am trying parse a log file for a name that always occurs after a known word and print that name to an lcd using the gpio library.
+0,"useful links
+
+wikipedia reference
+native javascript equivalents of jquery methods
+mdn javascript reference
+w3c dom core, html, events and css compatibility tables from url
+jslint code quality tool by douglas crockford (and jshint, a community-driven branch of the original)
+code minifiers/obfuscators: /packer/, yui compressor, google closure compiler, uglifyjs
+code formatter/deobfuscator: jsbeautifier
+idioms and gotchas: rounding, date object, number object, scope chain
+javascript garden
+comp.lang.javascript faq: very extensive guide on javascript quirks created by usenet's comp.lang.javascript
+ecma 262-5 online: html version of the ecmascript 5 specification. "
+0,"to assign values to an array:
+
+
+or
+
+
+
+
+
+to assign values to an associativearray or ""aa"":
+ smith"",address:""1023 west alameda"",telephone:""415-555-1212""}
+
+or
+
+ smith""
+ west alameda""
+
+
+a mode which allows almost any ascii character to be used as a key, or, using dot notation:
+
+ smith""
+ west alameda""
+
+
+aside from the usual text and numeric manipulation functions, brightscript also has specialized objects that can be created, such as ""roaudioplayer"", ""rovideoplayer"" and many different display screen types, the most commonly used are ""roposterscreen"" and ""rogridscreen"". "
+0,"it may also work on windows 2000, but this is not supported. "
+0,"i am trying to install google assistant on my pi 3. follwing the instructions on the assistant sdk page i had this error:
+""google_assistant_library-0.0.2-py2.py3-none-linux_armv71.whl"" not a supported wheel on this platform""
+on cmd: python -m pip install --upgrade url
+please help. "
+0,eddie
+0,"any type of help is very appreciated, thank you in advanced for the effort placed to answer these questions! "
+0,"if this was your project, how would you program your drone to fly by a quadrant photodiode sensor's data? "
+0,given just a single image this is off course impossible without knowing the size of the objects i want to know the distance too and defining what this means in pixels..
+0,media->open network stream.
+0,the settings for the mac and linux machine are identical.
+0,"use this tag for any programming-related question concerning the creation of pdf files, be it with a 3rd-party library or tools like pdf printers or pdf converters, or pdf authoring applications. "
+0,"i've also tried to change the command to espconn_sendto instead of espconn_send, but it makes no difference and somewhere else in this forum someone said espconn_sendto has a bug. "
+0,"this allows us to control different routes, data and the components that render the data (as well as many additional features). "
+0,"meaning one clap turns led1, then a second one the second one and so on. "
+0,"i propose you have a look at this code which should be placed in your loop() function:
+
+i am using your parameters[0] field to keep track of the time in your syste, in milliseconds units. "
+0,"just because you are using this version, doesn't mean you need this tag. "
+0,i will be back with actual script.
+0,but you can use python to make a graphical user interface that receive all the information from the arduino using pyserial library.
+0,"searching for a number of questions/answers, i could not find a solution for my application:
+i wrote a web application (html/javascript and some php) to read and control an apparatus through rs232. "
+0,rmi/iiop is an implementation of java rmi over the corba iiop protocol.
+1,telegram open network (ton) is a blockchain platform of telegram instant messaging system from the team of pavel durov.
+0,"the following example use a floatlayout without reducing the size of the labels (""2"" - size_hint: 1, 0.83) and (""1"" - size_hint: 1, 0.17). "
+0,this package provides dynamic (i.e.
+0,i assume the file type isn't right although it's .raw.
+0,"if the librdkafka is not light enough for using in your microcontroller, another way is using an intermediate server which handles received data from microcontrollers (e.g. "
+0,"yes, i know it is a trivial query, but if i can't get that simple one to work on the rpi, how can i get my complex queries to work? "
+0,does using this motor shield restrict arduino's pin usage?
+0,"importerror no module named video
+
+the error is on this line
+
+is there any solution or alternative? "
+0,"i am using this shift register, in order to control 32 individual leds. "
+0,call its generated shared objects with a python caller script.
+0,"in the easiest case you have a few sensors right near your ""central unit"" which have an i2c interface or something similar (easy because you don't need to design an analog circuit)."
+0,thanks in advance.
+0,"this data is usually presented in a consistent format, allowing for easy comparison of two different records and tracking progress over time; the practice of recording timestamps in a consistent manner along with the actual data is called timestamping. "
+0,"i get the following error:
+> http.get(""url"", nil, function(code, data)
+>> if (code < 0) then
+>> print(""http request failed"")
+>> else
+>> print(code, data)
+>> end
+>> end)
+> client handshake start. "
+0,this bundle allows you to schedule symfony2 console commands as server-side jobs.
+0,sizzle is a javascript css selector engine.
+0,ubuntu 13.04 was released on schedule on 25 april 2013.
+0,"in arduino:
+string a;
+
+void setup() {
+
+serial.begin(9600); // opens serial port, sets data rate to 9600 bps
+
+}
+
+void loop() {
+
+while(serial.available()) {
+
+ serial.readstringuntil('\n'); //read until new line
+x serial.parseint(); //this is your integer value
+
+}
+
+} "
+0,documentation & repo
+0,"google apis client library for javascript
+description
+written by google, this compact and efficient client library provides access to any of google's restful apis. "
+0,"so i got a program, that must turn on/off the light by a press of a button, but it just doesn't work. "
+0,"arduino code:
+
+processing code:
+
+the accelerometer values print perfectly, but temperature just returns a 0. "
+0,"the (current) documentation
+url
+states
+
+4.2.14. "
+1,"features:
+
+execution of ssh command using both synchronous and asynchronous methods
+return command execution exit status and other information
+provide sftp functionality for both synchronous and asynchronous operations. "
+0,the ttl argument represents the number of seconds before the function can be called again.
+0,"new apis for iot devices
+turnkey hardware solutions
+low barrier to entry
+build products at scale
+build connected devices for a wide variety of consumer, retail, and industrial applications. "
+0,"you create figures explicitly with the figure function, and implicitly whenever you plot graphics and no figure is active."" "
+0,"the wifi and eithernet shields are more expensive than the esp8266, but the esp8266 is not comparable with existing arduino boards. "
+1,"the eic has the format of a regular bankcard, with printed identity information on the surface (such as personal details and a photograph) as well as an embedded microchip. "
+0,gnu-efi is a set of libraries and scripts used to build uefi applications in a linux environment.
+0,i need to figure out how to set better tolerances.
+0,i'm trying to get data from current sensor 'ina219' with raspberry pi.
+0,"the output is available through stdout,stderr variables in the callback. "
+0,this problem is really a spot the difference.
+0,i want to calculate rpm of a spinning object from nodemcu with the help of hall effect sensor.
+0,"if the code object has been compiled with 'exec'
+as the mode argument, eval()s return value will be none. "
+1,"the steps given in the official github readme file are correct but you need to consider some options below in case you encounter errors:
+
+don't use the default value of keystore credentials as written in the readme file. "
+0,e.g.
+0,v8.net is a free open-source c# .net wrapper for google's v8 engine.
+0,latent semantic indexing is an indexing and retrieval method.
+0,"for authoring, testing, and debugging aws sambased serverless applications, you can use the aws cloud9 ide. "
+0,i use one transistor to enable interrupt to reset after esp wakeup from deepsleep.
+0,"what is the alternative of innerhtml in riotjs
+like
+
+asdfghjkl
+
+in js
+we write
+var
+but for the same html tag we have to get that value in riotjs
+like
+riot.id will return value ""one""
+what function will retun value ""asdfghjkl"" instead of . "
+0,"url
+the messages that i am sending from my device to my iot hub are being received by stream analytics, is it possible that stream analytics is stopping the messages from being fed to the service bus? "
+0,"url
+the sample uses a shell script, not python to control bluez to do the detecting. "
+0,when i mount the sd card and check if user-data is copied and valid yaml - then indeed it is.
+0,well.. not sure i understand your problem exactly but i try to give you the best possible answer i can.
+0,if i close and open the file again then i get new data but this is a very slow process (i only get about 10-12 samples/sec).
+0,"bluetooth connection from android to raspberry pi (python & android code)
+dealing with starting such a service on a raspberry pi can be found using this python example: url. "
+0,learn more about square's offerings for developers at url
+0,in java the keyword final is roughly equivalent to const in c++.
+0,if that's an excuse).
+0,"my goal is to activate an electric lock that works with 10-24v ac and dc, for this i have placed a transistor 2n2222 and a resistance of 330 ohms. "
+0,"whenever we want to shift color over the spectrum and trasition the colors in a circular and smooth motion, what we are really doing is shifting light using hue in the hsi/hsv (hue, saturation, intensity/value) color space. "
+1,sending downstream messages (messages to devices) requires that you specify the fcm server key.
+0,"when i pushed the button, called btn_up_pushed(). "
+0,tinyxml is designed to be easy and fast to learn.
+0,can someone help and share with me how to do that ?
+1,"when the pi boots, it looks for
+this file; if it finds it, it enables ssh and then deletes the file. "
+0,do not use this tag if d code simply instantiates a template but where that usage isn't relevant to the problem or question.
+0,am i doing something wrong?
+0,this is most likely a serial communication reset issue as eran w pointed out.
+0,i've decided to use an external interrupt to trigger the proper behavior for the latch pulse and each clock pulse.
+0,it simplifies the use of common interprocess communication and synchronization mechanisms.
+0,the gateway uses raspberry pi units to do the communication.
+0,the iterator variable occurs three times in each loop: that is two chances to get it wrong.
+0,makes arduino write through its serial ports (i.e.
+0,"it is designed to be fast, simple, and memory efficient. "
+0,"(with a arduino bluetooth module) but i also don't know if bluetooth is capable of this multiple connections, i don't want the need of a router or a domestic wifi network to do these communications. "
+0,"the array indexing operator never does bit-level access, c doesn't work like that. "
+0,"i am currently trying read files from a teensy 3.5 using the standard arduino sd card library, and the file fails to open whenever i use longer file names. "
+0,"if there were more, your code would always get the last row of the table, because it doesn't check the identifier of the row and so will repeatedly assign values to the same variables until it runs out of data. "
+0,"whenever i compile it, there's this error ""expected primary-expression before '.' "
+0,a class encapsulates data for the object.
+0,"a minion might send one (or a handful) of broadcasts upon power-on, to encourage an immediate reply from master. "
+0,the code for both master and slave are below.
+0,it was issue in url.
+0,"a compiler allows us to take programs written in a special programming language, called oampl, and transform them into oam assembly. "
+0,"the gpio module spins up a single polling thread to monitor gpio events, and will wait for one callback to return before calling another, regardless of the number of gpio events you are watching. "
+0,use this tag to ask any nemesis platform related questions.
+0,its telling you the truth.
+0,"in python, this function produces a value between 0 and 1023 (when adjusting a potentiometer). "
+0,the select2-rails gem integrates the select2 jquery plugin with the rails asset pipeline.
+0,made by akveo.
+0,created by telerik.
+0,i'm trying to display text in a file stored in a sd card.
+0,"i have successfully implemented the following solutions
+solution 1 :
+using google messaging service
+using cloud based server :
+by sending data through api to a cloud based server which will send the data using pushy but that is also similar process as above. "
+0,a well known protocol is the smb/cfs stack.
+0,sometimes you find that both readings (tempser and doser) are completed and that's why you find two readings in a line in your file.
+0,"both have been used for behavior recognition, and certain conditional independence properties between different levels of abstraction in the model allow for faster learning and inference. "
+0,all i am doing in my arduino program is check for 1 or 0 from the serial port and transferring this over the serial port.
+0,it is a good starting point for your problem.
+0,using
+0,"i don't know the accelstepper library, so i can be wrong, but this should do what you requested:
+
+ is the ""almost"" in your sentence: when it is nearer than this value it will start moving the other motor. "
+0,but can't translate any of them to code.
+0,you need to tell qemu to emulate a 64-bit capable board that matches what your bare-metal code is expecting to run on.
+0,"this may be because you are using the built in dns resolver in go, rather than delegating to the system name resolver. "
+0,please be descriptive because i'm new to coding.
+0,eventprocessorhost - here you will have to write your own implementation of getting data and storing it.
+0,chose python and pycrypto because the os comes with python 3.2.3 pre-installed.
+0,you just have to read it and the idea was that the serialevent function would be called every loop but it doesn't seem to work that way.
+0,i have an 32gb raspberry pi image.
+0,pipes).
+0,general apt-get support is off-topic.
+0,i want sample python code to make two xbees to communicate with each other in windows.
+0,i am trying to implement my code on a raspberry pi and performance is an issue for me.
+1,jdks provide a utility named keytool to manipulate the keystore and the cryptographic assets that it contains.
+0,the emftext getting started screencast demonstrates how to create a small example language with emftext.
+0,i recently bought an arduino with an lcd screen.
+0,"i have raspberry pi 2 model b , windows 10 iot core and programming in c#. "
+1,"enroll call to rest api works fine but register call fails with error
+
+""""authorization required, resend request using supplied key""""
+
+
+gives me keyname and authenticationkey in error response. "
+0,applications are usually developed in html/css/javascript and are following the trend of internet services integration with traditional broadcast (dvb).
+0,"the server will close the connection, if you don't send anything in more than one minute. "
+0,this was the consensus of a meta question.
+0,"on simple low-cost processors, typically, bitwise operations are substantially faster than division, several times faster than multiplication, and sometimes significantly faster than addition. "
+0,decision has to be taken at runtime .
+0,see documentation.
+0,"history
+the twitter gem previously contained a command-line interface, up until
+version 0.5.0, when it was removed. "
+0,(i think different types of beacons send packets in different formats.
+0,"use this tag if your question is specific to ada 95, and you can't use a more recent version of the ada standard. "
+0,"formats: dynamically load amd, commonjs and global scripts (as well as es6 modules) - detecting the format automatically, or with format hints. "
+0,"when a heap has multiple partitions, each partition has a heap structure that contains the data for that specific partition. "
+0,"an invoice or bill is a commercial document issued by a seller to the buyer, indicating the products, quantities, and agreed prices for products or services the seller has provided the buyer. "
+0,colly provides an api for performing network requests and for handling the received content (e.g.
+0,and hw answers with all you need to know.
+0,"the first time i installed opencv, openmp wasn't enabled. "
+0,is there any special trick to make the code run every minute on the raspberry pi?
+0,why is this needed?
+0,--i'm using the raspbian wheezy debian distro and i don't think that comes with a firewall.
+0,"also you should get v4l2_streamparm structure:
+struct v4l2_streamparm streamparm;
+memset(&streamparm, 0, sizeof(streamparm));
+streamparm.type v4l2_buf_type_video_capture;
+if (v4l2_ioctl(m_fd, vidioc_g_parm, &streamparm) 0)
+{
+// error
+}
+streamparm.parm.capture.capturemode v4l2_cap_timeperframe;
+streamparm.timeperframe.numerator x;
+streamparm.timeperframe.denominator y;
+if(v4l2_ioctl(descriptor,video_s_parm, &s) {
+cout<< ""failed to set frame rate ""<getmessage();
+ }
+
+$conn null;
+?> "
+0,represents a class that is used to send json-formatted content to the response.
+0,i have some raspberry pi's from previous projects/learning and i would like to pool their resources to make adifferential drive robot.
+1,when implemented with iclientvalidatable and unobtrusive-validation also adds client side validation logic.
+0,"by default the protobufdata is datatypes are: int64, float, bool. "
+0,"tasks can be schedualed with usage of ""crontab"" command."
+0,this is the code i am attempting to use now:
+0,you need to connect the dots:
+0,"the exception that is thrown when an android application attempts to perform a networking operation on its main thread, i.e ui thread. "
+0,"a professional & principled disambiguation between and [concurrent] is needed, as true parallel code-execution requires much more than just having a few cores and a fan-out of a hord of (uncoordinated) threads, hunting for time-sharing access to a pool of system-reserved resources. "
+0,i have a microcontroller (arduino uno) running nanopb that is sending protobuf messages over the wire.
+0,"url
+
+perhaps there is in future driver updates in windows updates and we no longer have such problems. "
+0,i just got a dragino yun shield.
+0,"but when i initialize the rfid and lcd shield, the lcd is not working. "
+0,you might be interested reading this question and aswers.
+0,here is an example of how to do error checking in cuda programs.
+0,thanks for the responses!
+0,"an optional argument is an argument which can be omitted, eventually being replaced by a default value, where an argument is an actual value passed to a function, procedure, or command line program. "
+0,"usually on debian systems this is done using the update-rc.d tool:
+update-rc.d name_of_init_script remove
+
+you should also have a look at the file /etc/rc.local "
+0,it enables you to add globalization support to your javascript applications.
+1,"you can use direct method invocation from the cloud (ms tutorial) - calling a method on your simulated device and waiting for a response, but this will only work for small payloads (up to 8kb, i think)
+for larger payloads, i'd suggest sending a cloud to device message containing a guid that identifies the message, then sending a file back to blob storage (see this microsoft tutorial), using the guid as a filename, and then having the iot hub send a notification event to your cloud code when the file is delivered. "
+0,here is a working configuration which allows pi3 to use wireless connection automatically if a wired one is not available:
+0,wysihtml5 is an inline html5 editor which creates semantic code.
+0,can someone kindly tell me how to get query id on click using the module chip and not wifishield?
+0,but intel edison has an integrated wifi module and i really can't understand why it is not able to establish an internet connection anymore without the help of the usb connection with my laptop.
+0,"since i can send a string from android app to arduino, i am trying to send a video file like that. "
+0,i picked charts.js as chart drawing library.
+0,is there anyway i can reduce the time taken to perform serial read?
+0,"so far there have been three iterations of the tegra family, named numerically. "
+0,onsubmit is the html event called when a submit button is pressed on a html form.
+0,documentation: url
+1,"it should not be used for general-purpose email validation; instead, use [email-validation]. "
+0,i am running c# application that sends telemetry messages from devices to iot-hub account in azure portal.
+0,javafx application icon
+0,there will be documented ways to do so in any reasonable crypto library.
+0,"on many platforms ""the default charset"" means utf-8, and in utf-8 most bytes of the ""extended ascii"", i.e. "
+0,each item's flags can be changed by calling setflags().
+0,the tool includes both script editors and graphical tools which work with objects and features of the server.
+0,i have also checked the wiring.
+0,"the issue here is that i don't know how to pass video data from socket into mplayer via c#, because i guess it is not done via stdin (already tried that). "
+0,this calibration is needed to understand how to interprete imu measurements and camera features and translate them into translation and rotation
+0,"you will not get a - sign, if you did expect one. "
+0,"for y in range(-10, 12, 2):
+ glvertex3f(-2, y/10., 1)
+ glvertex3f( 2, y/10., 1)
+
+ for y in range(-10, 12, 2):
+ glvertex3f(-2, y/10., 1)
+ glvertex3f(-2, y/10., -1)
+
+ for y in range(-10, 12, 2):
+ glvertex3f(2, y/10., 1)
+ glvertex3f(2, y/10., -1)
+
+ glend()
+ glpushmatrix()
+ glrotate(float(x_angle), 1, 0, 0)
+ glrotate(-float(y_angle), 0, 0, 1)
+ cube.render()
+ glpopmatrix()
+ pygame.display.flip()
+
+class cube(object):
+
+ def __init__(self, position, color):
+ self.position position
+ self.color color
+
+ # cube information
+ num_faces 6
+
+ vertices [ (-1.0, -0.05, 0.5),
+ (1.0, -0.05, 0.5),
+ (1.0, 0.05, 0.5),
+ (-1.0, 0.05, 0.5),
+ (-1.0, -0.05, -0.5),
+ (1.0, -0.05, -0.5),
+ (1.0, 0.05, -0.5),
+ (-1.0, 0.05, -0.5) ]
+
+ normals [ (0.0, 0.0, +1.0), # front
+ (0.0, 0.0, -1.0), # back
+ (+1.0, 0.0, 0.0), # right
+ (-1.0, 0.0, 0.0), # left
+ (0.0, +1.0, 0.0), # top
+ (0.0, -1.0, 0.0) ] # bottom
+
+ vertex_indices [ (0, 1, 2, 3), # front
+ (4, 5, 6, 7), # back
+ (1, 5, 6, 2), # right
+ (0, 4, 7, 3), # left
+ (3, 2, 6, 7), # top
+ (0, 1, 5, 4) ] # bottom
+
+ def render(self):
+ then pygame.time.get_ticks()
+ glcolor(self.color)
+
+ vertices self.vertices
+
+ # draw all 6 faces of the cube
+ glbegin(gl_quads)
+
+ for face_no in xrange(self.num_faces):
+ glnormal3dv(self.normals[face_no])
+ v1, v2, v3, v4 self.vertex_indices[face_no]
+ glvertex(vertices[v1])
+ glvertex(vertices[v2])
+ glvertex(vertices[v3])
+ glvertex(vertices[v4])
+ glend()
+
+if __name__ ""__main__"":
+ run()
+
+this is the code i modified to display only the gyro readings (run from the raspberry pi) which gives me the error in the windows command prompt:
+#!/usr/bin/python
+import web
+import smbus
+import math
+
+urls (
+ '/', 'index'
+)
+
+# power management registers
+power_mgmt_1 0x6b
+power_mgmt_2 0x6c
+
+bus smbus.smbus(1) # or bus smbus.smbus(1) for revision 2 boards
+address 0x68 # this is the address value read via the i2cdetect command
+
+
+def read_byte(adr):
+ return bus.read_byte_data(address, adr)
+
+def read_word(adr):
+ high bus.read_byte_data(address, adr)
+ low bus.read_byte_data(address, adr+1)
+ val (high << 8) + low
+ return val
+
+def read_word_2c(adr):
+ val read_word(adr)
+ if (val 0x8000):
+ return -((65535 - val) + 1)
+ else:
+ return val
+
+class index:
+ def get(self):
+
+ gyro_xout read_word_2c(0x43)
+ gyro_yout read_word_2c(0x45)
+ gyro_zout read_word_2c(0x47)
+
+ gyro_xout_scaled gyro_xout / 131
+ gyro_yout_scaled gyro_yout / 131
+ gyro_zout_scaled gyro_zout / 131
+
+ return gyro_xout_scaled, gyro_yout_scaled, gyro_zout_scaled
+
+
+if __name__ ""__main__"":
+
+ # now wake the 6050 up as it starts in sleep mode
+ bus.write_byte_data(address, power_mgmt_1, 0)
+
+ app web.application(urls, globals())
+ app.run()
+
+i haven't changed anything in the code i run on the laptop, just the script i run on the pi. "
+0,but i have to enter this command everytime i restart my rpi.
+0,i'll leave that as an exercise for you.
+0,"there are two free apps and one is the ""pro"" version of one of the free ones; search slick usb in google play."
+0,bunch of weather sensors like wind/air/hum/temp) and this device needs to report it's state to aws iot.
+0,"use this tag only for rspec 2-specific questions, and tag those questions with [rspec] too. "
+0,each model contains all the data required to render it and is responsible for declaring itself valid or invalid.
+0,must include the javascript file with the name of the map you want.
+0,i can not test it out.
+0,try as specified here
+0,this is termed a logical view of the call because it ignores the details provided by the terminal and terminalconnection objects which are also associated with a call.
+0,stopped node-red graphical event wiring tool..
+0,i expect to be able to move the bird using the ultrasonic sensor as a controller.
+0,thanks for your help.
+0,"for fixed-point arithmetic, use [fixed-point] instead. "
+0,"so i attempted this method:
+
+but the above results in the following:
+
+note that the latter two print out wrong; i'm guessing this is due to floating point precision issues. "
+0,i was using node-red in my raspberry pi normally until get the brillant idea to install new nodes.
+0,"use this tag specifically for questions related to ssms version 18
+
+microsoft sql server management studio 18 is a graphical tool for configuring, managing, and administering all components within microsoft sql server. "
+0,"external links
+
+official website
+community site "
+0,this tag relates to the 2.2.x branch of the cakephp mvc framework.
+0,"questions about primeng's turbotable for displaying data in a table, and how to use turbotable's api. "
+0,you could also use a max7219 chip...
+1,i want to send commands to my raspberry pi via ssh from iphone app.
+0,can someone please explain this?
+0,"depending on the actual shields and their revision, it might indeed be possible to hack a pin here and there to map ss to a different pin on the arduino. "
+0,"the microsoft azure portal is a central place where you can create, manage, and monitor your azure resources. "
+0,i have an imx7 board from technexion.
+0,url
+0,i want when i run the program that the camera fix a area on the floor and stay on this area.
+0,the source code of the library is distributed under very permissive mit license.
+0,in this link it explains you examples on how tu use the frame and where should you redirect the output.
+0,i cant setup a custom keyboard layout to do what i want without having a scancode coming in for the tablet to see.
+0,you also may need to increase the time interval on your timer.
+0,many character encodings are based on ucs.
+0,"i invoked the crontab manager using sudo crontab -e.
+
+for the moment, i can execute the gui by invoking it directly via the pi's command line. "
+0,hi i am trying to write a systemd service to launch a simple hello world program at bootup.
+0,"ideally i'd want to keep lag low, but i'll sacrifice low lag for an easy solution. "
+0,citrix netscaler is an all-in-one web application delivery controller
+0,"in theoretical computer science, correctness of an algorithm is asserted when it is said that the algorithm is correct with respect to a specification. "
+0,"in the arduino ide try:
+tools | board | arduino uno "
+0,"if you see this message again, go to the ibm cloud status page to check whether a service or component has an issue. "
+0,each entry consists of one object that represents the key and a second object that is that keys value.
+0,error compiling.
+0,my os has two users - admin and standard user.
+0,objectmapper is a library for simple json object mapping in swift.
+0,i really hope to learn something useful from this project.
+0,in the setup routine i load the credentials and try to connect to wifi.
+0,i got some problem about reading from mpu6050 and then write to sd card.
+0,"i re-read the tutorial and realised that i didn't do the first step, because the drive is already hfs+. "
+0,here is my python code.
+0,this is what i need to accomplish.
+0,the comprehensive camera module for react native.
+0,frege is a haskell for the jvm.
+0,if you start playing it at 96000 it will be speeded up and higher pitched.
+0,"im new to stackoverflow, writing questions that is) "
+0,so clearly my android code is doing something weird.
+0,hopefully one of you can help me with this problem.
+0,"and in certain situations, it is. "
+0,vs2017 has default linux include files in c:\program files (x86)\microsoft visual studio\2017\community\common7\ide\vc\linux\include.
+0,"note: this tag should not, as a rule, be used for virtual machines (vms). "
+0,"i, i'm programming an attiny85. "
+0,its purpose is to provide a more traditional way to perform logging in an erlang application that plays nicely with traditional unix logging tools like logrotate and syslog.
+0,any idea?
+0,"| california west 23,667,902 210,864 |
+ +---------------------------------------------+
+
+alternatively, you can directly download an online example dataset with the use command:
+clear
+use url
+
+list district votea expenda sharea in 1 / 5
+
+ +-------------------------------------+
+ | district votea expenda sharea |
+ |-------------------------------------|
+1. "
+0,"when i compile it using the gcc and g++ compilers for linux, everything works perfectly. "
+0,"the streaming of the image is not working, and also when obtaining the bitmap from the camera using method, as in the example, the resulting bitmap is a corrupted version on the original map, with wrong size and colors. "
+0,"yes you need the arm port of java8, where fx renders directly into the framebuffer. "
+0,is a program used to control the creation and termination of linux system-level processes (daemons).
+0,two usb devices can't communicate this way.
+0,please let me know from where does qt get the path of odbc drivers?
+0,i set below code in my service.
+0,"if you are on 1000s of guilds but there is never more than one guild using the music command at a time, then you should still be fine with any of them. "
+0,the script works fine on laptops.
+0,this will fix your problem and make your brown-out voltage correct!
+0,when it sees i portd; is loads the value from the portd register and stored it in the variable i.
+0,reference: url
+0,so you need to remember that using hardware serial always is a better choice.
+0,"not sure that examples for any arm processor would help, since the bcm2837 does not seem to be using a standard arm gic acording to bcm2837.dtsi. "
+0,questions related to gdb's python api.
+0,"the question:
+would the application performance optimisations on a raspberry pi allow me to achieve better results on a multi-code multi-socket xeon server later? "
+0,"it should display the actual time for example, "
+0,"on most devices it works fine, but on the samsung galaxy s3 and samsung galaxy tab, some users report extremely slow audio playback. "
+0,it's the continuation of **the little schemer**
+0,"however, by having this much user-defined data in progmem, some internal arduino functionality is also pushed past the 64k mark, and those do not use 4-byte pointers. "
+0,"zookeeper is a centralized service for maintaining configuration information, naming, providing distributed synchronization, and providing group services. "
+0,"to download this plugin you can go here: url
+
+this project development has been suspended. "
+0,ssis is a platform for data integration and workflow applications.
+0,good morning everyone!
+0,try committing your changes:
+0,later i want to get data from a database but that's another story to tell.
+0,"for example, if 1 arduino has to communicate with pi, it sends interrupt and then pi asks the arduino to send data. "
+0,i have been using esp32 and writing code in arduino.
+0,"however if i run this as service i get the following output in /var/log/syslog:
+
+jul 30 16:21:10 raspberrypi2 index.js[11406]: child process exited with error code errorcommand failed: iwgetid
+ jul 30 16:21:10 raspberrypi2 index.js[11406]: /bin/sh: 1: iwgetid: not found "
+0,as the slave devices are of the same kind creating a 'class device' is an obvious solution.
+0,"they're all synced to the exact same time (as i've had each device reply with their current time and they're identical, to the second) and they're all on identical hardware so any latency due to hardware should be identical. "
+0,"currently, im struggling with capturing multiple images quickly and i've tried software such as fswebcam, motion , pygame.camera and all have a delay of roughly 1 sec resulting in "
+0,"jspon is convention for using json for persistent object storage, as opposed to transient object transmission. "
+0,"i don't have the correct answer for your questions, but imho it should be possible. "
+0,"so it turned out, that the php version used by apache is different from the one i got from the console. "
+0,i was hoping someone could help explain this better to me and also hopefully help walk me through my bigger issue which is to write data to the bluetooth device.
+0,asp.net is a server-side web application framework designed for web development to produce dynamic web pages.
+0,"sorry if i sound ""noobish"" i'm a mechanical engineer student who took one java class."
+0,"i want to send a broadcast message from my computer and then reply it from the esp32
+i'm managing to receive the broadcast message but i can't send the reply message (i don't see it in the computer's wireshark)
+i used a popular version from the internet so the code should be fine but i don't understand what's wrong. "
+0,then the computer can find this 0xdeadbeef and know where the next message is going to start.
+0,"where the practicality of not knowing what is in the client buffer and what its length is as to read it, may be the preventative reason i don't see any examples of it being used on tcp. "
+0,"what's puzzling me is that over the course of many, many hours of debugging, i feel i've managed to code out any bug that the script would ever encounter. "
+0,"pega prpc(pega rules process commander) also known as bpm(business process management) tool is a proprietary bpms suite, a market leader for many years, according to gartner. "
+0,i'd say this code works 50% of the time right now.
+1,"tizen sdk for wearable (gear widget development kit)
+samsung accessory sdk
+
+certification guide
+secure your app to upload to samsung gear apps
+
+getting the gear certificate
+
+testing
+if you have no gear device, use gear emulator & rtl
+
+gear emulator
+rtl service
+
+technical resources
+
+gear app development - technical documentation, sample applications, video "
+0,"if so, how? "
+0,line 78: the indentation is incorrect.
+0,thanks for all the advice guys!
+0,is there a way to get the sounds to work from the command line?
+0,productbuild is a utility to build a product archive (pkg file).
+0,"but after, if the server is in discovery mode (if the server is an android phone), the connection succeeds every time! "
+0,"in programming, a needle in a haystack is also something that could be difficult to find (manually), that's why you can find functions that can do the dirty work for you simply by taking as argument a needle, and a haystack "
+0,"i've resolved the problem - the print() function casts all the values as their ascii numbers, so it would make sense that all numbers are preceded by 3s, because ascii numbers are in the 30s range. "
+0,"javaquery is a port of jquery to java that is designed to provide the same functionality, and an as-close-to-possible syntax. "
+0,consider using serial.parseint() instead of that bulky construction in waitformn() function of arduino sketch.
+0,an official derivative of ubuntu linux that uses kde as the default desktop environment.
+0,"disassembly of section .reset:
+
+0000000000080000 :
+ 80000: d53800a1 mrs x1, mpidr_el1
+ 80004: 92400421 and x1, x1, #0x3
+ 80008: f100003f cmp x1, #0x0
+ 8000c: 54001481 b.ne 8029c // b.any
+ 80010: b26d03ff mov sp, #0x80000 // #524288
+ 80014: 1400008d b 80248
+ 80018: d65f03c0 ret
+ 8001c: 00000000 .inst 0x00000000 ; undefined "
+0,"also, this program does not work correctly in the python idle (selecting random devices on the multiplexer). "
+0,"write sketch which do:
+
+read t (temperature). "
+0,some background: i am using an arduino uno with a pn532 shield to send commands to an android phone running an hce app.
+0,"this is the following command i want to execute:
+
+i get the following output when i run the command directly on the raspberry pi terminal :
+model name : armv7 processor rev 4 (v7l)
+hardware : bcm2835
+serial : 0000000083a747d7
+
+which is what i expect as well. "
+0,this seems to be another way i will test.
+0,see c++builder for more information.
+0,from man xxd
+0,"to debug failed tests, you can go to the build directory and run the test with the harness, or without for more details. "
+0,how is the ftdi-chip called which is on the arduino uno?
+0,"the counter of function starts from the start of your program, that means from the start of void setup() function. "
+0,using only information known at compile-time and not performing a run-time check.
+0,i focusing in arduino platform (xbee modules).
+0,"if your application is tolerant of low-timing resolution and high
+ jitter then you could use a software or dma assisted timing loop. "
+0,it is available in ios 3.1 and later.
+0,"it works very well, for now i am testing my code using proteus. "
+0,you need to decode that to if you want string.
+0,"i've done some research but have a few questions i can't seem to find answers to, and wonder if people here might know. "
+0,but i'm not sure.
+0,"1:
+
+prog. "
+1,"assuming that your rfid reader interfaces with raspberry-pi via serial port, the best approach would be to write a simple c program that received data from rfid reader via serial port and send it to your windows server via tcp/udp connection. "
+0,is there an easy way to playback video data stored in a stream-object (url) (e.g.
+0,"url
+here is something i found about the commands but still not what i am looking for. "
+0,"resources
+
+svk documentation
+svk eol announcement "
+0,mysql fabric is a system for managing a farm of mysql servers.
+0,"as a result of that, i see a 'new factory' as one of the factories and i can see the values of the nodes configured on the opc publisher (on the edge). "
+0,how can i execute it when raspberry start?
+0,"it currently supports the following chart types:
+
+line chart
+interpolated line chart
+area chart
+scatter chart
+time chart
+bar chart
+pie chart
+bubble chart
+doughnut chart
+range (high-low) bar chart, including support for gradient colored bars
+dial chart / gauge
+
+all the above supported chart types can contain multiple series, can be displayed with the x-axis horizontally (default) or vertically and support many other custom features (labeling, colors, zoom & pan, pinch zoom,...). "
+0,performs a principal components analysis on the given data matrix and returns the results as an object of class prcomp.
+0,"however, 2.8.0 hangs on boot after the message:
+console: switching to colour frame buffer device 100x30
+
+this goes to show how unstable -m raspi2 still is. "
+0,the viewholder pattern is often used in android applications to improve performances of view access.
+0,"you can use:
+
+rxtx url
+jarduino url
+ardulink url "
+0,"what is the right way to do this, and why isn't the above working? "
+0,express gateway is a microservices api gateway built on express.js.
+0,so using ef.core in uwp will cause you lot of headache; but it is possible.
+0,to achieve this and learn something new i am trying to configure an apache server running on my raspberry pi.
+0,"outside of stack overflow, i am active on dba.se
+
+while i don't spend as much time in the review queues as i used to (i flag more), i still actively work to improve the site by editing, voting and commenting to get users to improve their questions and answers. "
+0,"this includes networking functions, support for distributed and multicore processing, and bayesian statistics. "
+0,"if you need this file too, comment and i will provide it, but i am sure it is not the problem here. "
+0,(or written correctly).
+0,all the information you can find in the linked manual.
+0,"but now, i can't directly connect thermocouples to 74hc4067. "
+0,it is intended for os x and linux but it will give you a good idea of what you need to do.
+0,usually an arduino does not receive any integers or floats at all.
+0,i though that there '<' was used for sending commands and '>' was use for requesting data.
+0,use scala in addition to or instead of this tag.
+0,"some docs on device twins that can help make all this clearer:
+device twin description
+iot hub endpoints "
+0,"they behaved like this:
+
+are there equivalent c functions? "
+0,so is it because i use picture too large ?
+0,"net, register the asp.net version that is coupled with the tool, create client-script directories, and perform other configuration operations. "
+0,other than that i just changed my board to uno and then changed it back to 2560 mega and compiled the sketch and it works now.
+0,"as shown above, yes. "
+0,": flash hw ver:00.01.00.00, bm ver:00.01.05.04 [y/n] n
+update aborted : update was aborted upon user request
++++++++++++++++++++++
+time elapsed : 10 ms for downloading and starting eci firmware
+controller count : 0
+opening board 1 of type ""usb-to-can v2"" failed with error code 0xe0fe000e
+devadminrun -> exited with error code 0xe0fe001a
+
+the second option still not works. "
+0,it currently supports the windows and android platforms.
+0,"are you in the ""audio"" group?"
+1,a cross-site scripting vulnerability may be used by attackers to bypass access controls such as the same origin policy.
+0,"you need to be patient for a while and consider compiling/building every module and helper by yourself from the source codes, especially for the arm side. "
+0,"there is no need to understand complex consistency models, with poorly articulated edge-cases. "
+0,"error when trying to run on iot core:
+c:\program files\docker\docker.exe: error response from daemon: container
+e9da3baa806f161153fdb7f60a9401a5ff46c32a959499cbe0bd822b1fc0dda3 encountered an error during start: failure in a
+windows system call: the compute system exited unexpectedly. "
+0,"i edited the code called ""cordova-plugin-ble-central made by don coleman on github) to reach this goal."
+0,"now i want to be able to get an email reporting the actual status at the moment whenever i am interested, triggering this by an email from my mobile. "
+0,a user role is a group of users that share the same privileges or permissions on a system.
+0,"a) for running the script continuously, you can use tools like forever or pm2, otherwise you can also make the app a debian daemon on raspian you can run with (if you're running arch linux, this is handled differently i guess). "
+0,"so i have a beaglebone black board, and i want to be able to set some pin from a low value to a high value. "
+0,"i've already paired the device with my computer and am currently following this tutorial:
+url
+i am able to add a serial port with:
+
+but when i run rfcomm to watch to port using:
+
+i receive this:
+rfcomm tty layer initialized
+rfcomm socket layer initialized
+rfcomm ver 1.11
+waiting for connection on channel 1
+
+from there i return to my pc's bluetooth settings and traverse to com ports (none show up). "
+0,"this is true for any node.js program controlling an arduino, whether with cylon.js or johnny-five. "
+0,"depending on the current time, it will also upload the temperature to 3 different web services (at 5, 10 ,15 mins past the hour etc) and tweets it (on the hour)
+a long running ruby script which runs at reboot and watches for files being created by the motion detection software, then uploads them to dropbox
+motion - the motion detection software
+
+the scripts are launched in the root users crontab like so:
+
+what i have noticed recently is that within seconds of motion being detected the pi becomes unresponsive and after reboot the cron_shed_watcher.log log file contains entries such as:
+
+to recover from whatever is happening during the killed phase, i need to reboot. "
+0,time and attendance systems are those that keep track of people's comings and goings.
+0,furthermore its opensource and therefore free to use
+0,thanks in advance for your cooperation
+0,"in this link, another user has the same problem as you and he has been suggested to use delegate. "
+0,"once you disrupt connection(incorrect disconnection), which is very easy to do, you will block your port and you will end up with infamous 'address already in use' error. "
+0,if you want to do real complicated things i suggest that you take a look at firmata
+0,"per a suggestion posted, i read on github the following:
+no pre-processing is done to files in a sketch with any extension other than .ino. "
+0,"in general it would look like:
+
+so i thought of using fork(), but this creates zombies when the main process exit. "
+0,as of today you can't install the official package provided for debian for its mismatching the hardware platform.
+0,"i searched a lot for troubles with character set (ascii vs utf), but without any results. "
+0,"inner classes are another, more general way to handle events from user interfaces. "
+0,"the command should be
+
+if you don't know the ip address and you're on the same network, you can use its host name. "
+0,esp8266wifi.h is part of the esp8266 core for arduino.
+0,workers can include other scripts using the method.
+0,"the project aims to provide a consistent and complete set of interactions with openstack's many services, along with complete documentation, examples, and tools. "
+0,"post body
+the post body should provide as much background information as possible to help the other contributors answer your questions. "
+0,you have chip-select conflicts with all of the spi devices you're using.
+0,"var riot require('riot'),
+blogview require('./views/blog.tag');
+riot.mount(blogview);
+i'm just confused with the error and what is going wrong. "
+0,primarily used for creating microsoft windows installer (msi installer).
+0,i flashed 17763 build using dashboard.
+0,"update
+as discussed in comments, there seems to be a problem with the event handling. "
+0,"i really do not understand what you mean:
+""i want to stop the distance sensor measurement when e.g. "
+0,"not
+with npm itself. "
+0,", -classpath, ...)
+options that begin with -x which are non-standard (not guaranteed to be supported on all vm implementations) and are subject to change without notice in subsequent releases of the jdk (e.g. "
+0,i have tried checking whether the 1883 port is open or if there is any issues on rpi mqtt broker.
+0,i would like to develop a python opencv script to duplicate/improve on a gimp procedure i have developed.
+0,"from: url
+
+the jack toolchain is deprecated, as per this announcement. "
+0,whenever i try this both the app i use as remote (flex remote - ios) and the mouse connected to the raspberry won't work.
+0,"in my setup i put that pin as input_analog, do i need to do something else in order to get the reading? "
+0,"i have a digital display connected to my arduino and its supposed to show the number 5 and once i click on the button the number should increment by 5, but when i click it keeps adding 5 until i let go, so a single click goes from 5 to 155 instead of 10. "
+0,"besides the ""helpful flags"" count i try to flag cases i spot where flags are clearly wrong."
+0,"it has a config file that can adjust the period as to be more lossy, but be more tolerant of delayed interrupts. "
+0,i just need to somehow get the times into that.
+0,"on your mobile app, you should initiate a service discovery phase when your ble device is connected. "
+0,"the simulink model contains a constant the is set to 0, and this constant value is displayed in the display block on the right. "
+0,"if i request data from an api using a raspberry pi in a while/for loop in python and append data to csv and one iteration fails due to something like faulty wifi connection that comes and goes, what is a foolproof method of having an indication that an error occurred and have it keep trying again either immediately or after some rest period? "
+0,"for windows, i tried doing this
+
+in powershell, run . "
+0,"include tags to mention if the question relates to format conversion, processing, etc. "
+0,it is highly possible about sample rate.
+0,"worked pretty fine by the normal setup instructions if i recall correctly though it took ages to build (like, half a week). "
+0,i just setup a raspberry pi machine and tried reverse engineering the following piece of code.
+0,"if that doesn't work, /var/log/apache2/error.log can tell you more about the error. "
+0,a driver typically communicates with the device through the computer bus or communications subsystem to which the hardware connects.
+1,"the most proper way is to use in the directory : /etc/apache2/sites-available/
+the default is pointing to /var/www/
+i'm always creating a user for a project and then i point the virtual host and i use suphp for the security. "
+0,the appmaker tag should be used for questions about [google app maker](url).
+0,essentially what i need to learn how to do is have the pi listen for this request and run a script (setting gpio pin 17 to high for a half second).
+1,you could buy antenna which meets requirement of your gateway and lorawan specification.
+0,"if you need that, use mono.data.sqlite or csharp-sqlite. "
+0,source: url
+0,"i am developing a thermostat firmware that handles different states, an oled, and reacts to some push buttons, among other tasks. "
+0,"then you would swap the buffers, and repeat. "
+0,can someone please help me out?
+0,"in software engineering, multi-tier architecture (often referred to as n-tier architecture) is a clientserver architecture in which presentation, application processing and data management functions are physically separated "
+0,sfml (simple fast multimedia library) is a portable and easy to use multimedia api written in c++.
+0,i bought a uno r3 and i don't have this problem anymore.
+0,i am using
+0,use for azure oms\log analytics questions
+0,"if you have a raspberry pi with a revision 2.0 board, you need to use ic bus 1, not bus 0, so you will need to change the bus number used. "
+0,"additionally, all of this is heavily hardware dependent, both on the central and the peripheral, so it's difficult to even ballpark expected performance. "
+0,onreceive callback will define what kind of data should be send back to the raspberry.
+0,arduinos serial monitor is very simple and very limited in functionality.
+0,"as a sanity check i have tried the code against a different mqtt service (adafruit io) and the results are as to be expected (here the message is 'on' or 'off'):
+
+the azure mqtt service must be doing something different when it sends the messages to the device, what i needs to know is what it does differently. "
+0,the community has made available a tools to simplify the creation.
+0,this is not the best solution.
+0,"the one saved in the xml file is actually a kind of hash and if you don't set the correct value you'll have an error like
+
+
+add profile failure: invalid profile xml. "
+0,ilink64 is the linker for c++ 64-bit windows applications.
+0,"in follow up to the loopback test, you can do this with a few tricks from the command line. "
+0,"i need it to count down starting at 45 minutes and 00 seconds
+i don't see you set this anywhere. "
+1,"it is not intended to replace proper security measures, and should never be used in place of proper encryption. "
+0,".net core is compatible with .net framework, xamarin and mono, via the .net standard library. "
+0,"installation
+the imputets package can be found on cran. "
+0,"here is the same, unrolled:
+
+this code too works great, and produces the desired results. "
+0,i have made the dio following the instructions on the oracle page and copied the build folder onto by development pc.
+0,i tried to have the start button trigger a flag that starts a timer.
+0,inside an organisation's firewall as opposed to on the internet.
+0,"therefore, if this is a raspberry pi 3 model b or b+, then it has bluetooth v4.1 or v4.2 (respectively) built-in and it should be capable of acting as both central and peripheral. "
+0,"other patterns that might appear during a failed boot mean:
+
+firmware before 20th october 2012 required loader.bin, and the meaning of the flashes was slightly different: "
+0,"i have a serial com gui and i need to have text displayed in a box based on what the serial port's existing data is, but not exactly what the serial port data is. "
+0,you create subclasses for any custom protocols or url schemes that your app supports.
+0,making the scene brighter will shorten exposure and so improve the sharpness - although in the end you are using a cheap camera with a small sensor so it isn't exactly ideal for this application.
+0,"""arab standard time"", ""arabian standard time"", and ""arabic standard time"" are three completely different time zones with similar names. "
+0,"for more information, see the apple documentation for the uiappfonts key. "
+0,is jtag the normal method (i think that is what my research has indicated ...)?
+0,related to html/css/javascript code created by adobe edge applications.
+0,however it doesn't seem to work with the esp.
+0,"err: you must give at least one requirement to install (see ""pip help install"")
+you need to run this on the raspberry pi:
+sudo pip install twilio
+if you don't have pip installed then run:
+sudo apt-get install python3-pip
+and then again: sudo pip install twilio
+for 2. "
+0,"here are my questions:
+
+where are the requests saved? "
+0,"when not to normalize your sql database
+maybe normalizing isn't normal
+the mother of all database normalization debates on coding horror
+
+the trouble with following advice to ""denormalize"" is that it doesn't tell you what to do. "
+0,"the first statement:
+sets the pointer variable equal to the value of gpio_base, and also casts the latter to a pointer type. "
+0,qttest is a qt module for unit testing qt applications and libraries.
+0,the softwareserial library of arduino don't work with clones made of atmega32 as this do not have pcint feature.
+0,"an yes, i'm new to python. "
+0,"on other systems, it is available through libbsd. "
+0,yes.
+0,it has a synonym with more questions.
+0,good luck.
+0,"here is my solution of wiring:
+
+and:
+you need to choose the right settings in the arduino ide. "
+0,"when i insert it to raspberry pi, it is displaying ""digital input - cannot display this video mode"" on the monitor. "
+0,then you replace your pointer with the pointer to the data of opencv.
+0,"opencart supports multi-channel ecommerce with availability for multi currecy, language, template, domain and device (tablet, web and mobile). "
+0,both cases involve disturbing noise.
+0,"before changing the include path, if you haven't already, first set the ""compiler path"" to point at your c/c++ compiler, and set ""intellisense mode"" to match the compiler as closely as possible. "
+0,when running in a non gui mode?
+0,so after fixing one light blinks and one light continuously stays on but i need both to blink i shall look further.
+0,"you can use its native compilers for raspberry pi(can be used along with old & slow 6.3.0 gcc), or use the cross-compiler in any linux machine(tested on latest ubuntu/bionic x64) to compile programs for your raspberry pi. "
+0,the interpolated surface is smoother than corresponding surfaces obtained by bilinear interpolation or nearest-neighbor interpolation.
+0,"written in php and mysql, virtuemart is an extension that allows administrators running the joomla! "
+0,just use the .toint() function.
+0,the windows client is automatically attempt to enrich the minwinpc:8080 to become minwinpc.local:8080.
+0,and it definitely isn't what you want.
+0,valve !
+0,occasionally scanning will hang on storing a bit and i'll have to fob the reader a second time to get it to finish.
+0,fastmm is the default memory manager for delphi win32 and win64 bit applications.
+0,the following image is showing the memory usage of my raspberry pi.
+1,"this procedure is very well documented in authorizing from a companion app check ""procedure for obtaining refresh and access tokens"" section."
+0,you can also add custom include search paths for your compiler.
+0,it is written in php and primarily uses mysql as a database management system.
+0,this is the place to ask questions about the angular-tree-component npm package.
+0,"that way you can create an array with elements of type sensor and call this method on each element, which then calls the implemented method of the child classes. "
+0,servicenow uses several unique indexes out-of-box to protect certain tables from duplicate record confusion.
+0,"some tool uses this specification to generate code to cover basic crud (cread read, update, delete) functionality, effectively treating the template as a scaffold on which to build a more powerful application. "
+0,"note: i'm already familiar with some programming languages like c and python3, 3d programs like blender and 3dsmax(just the basics),and i have experience with robotics, single board computers(rpi) and microcontrollers(arduino). "
+0,"you usually want this as you don't want
+any of the special terminal handling options. "
+0,ok one approach is to use the function for this.
+0,so each time after certificate created i need to manually attach policy with certificate.
+0,"until today, the access point worked. "
+0,"which solution is the best, we can't say but it works now... "
+0,old question but it came up first in a google search so here is my understanding.
+0,"(simple alsa example have failed because capturing audio buffer is already used by hotword detection engine)
+i am new to linux and some methods like jackaudio, ladspa seem so sophisticated to me. "
+0,thanks
+0,intercom.getinstance(): returns an instance of intercom.
+0,"this is quite an interesting problem, in the normal world of computers we would solve this via threading. "
+0,and some hints for this project.
+0,"open tools > serial monitor, set the serial monitor to the correct serial port and set the baud rate to 38400. "
+0,"serialgps.begin returns the error
+
+if remove * when setting the variable
+softwareserial serialgps(10,11); // rx, tx
+
+result error on the variable
+arduino_sketch:21: error: expected identifier before numeric constant
+arduino_sketch:21: error: expected ',' or '...' before numeric constant
+
+this issue is on all kind of classes that needs values as initialisations. "
+0,now jtidy is maintained by a group of volunteers.
+0,"installing the software you are really going to use into a raspberry pi compatible distro seems far more effective to me, and probably it would also help you better use the available resources. "
+0,"when i put things 1.0 back on the card, it doesn't boot again. "
+0,i am doing some attendance related project.
+0,i want to save settings between two sessions.
+1,libssh is a c library that enables you to write a program that uses the ssh protocol.
+0,"i tried blink led sample it's working fine on board, as led blinking but no ui visible(add ui in code). "
+1,"if the server is configured to use ltpa, the server first checks for a valid ltpa token for the sso domain the server has been configured for. "
+0,this is my code.
+0,"also know that your process may be put to sleep anyhow once the os ""ticks"" in to schedule work."
+0,i've tried doing so with and .exit() but neither seem to work.
+1,"130|shell@test_ref:/sys/class/gpio/gpio218 $ ll
+-rw-r--r-- root root 4096 2009-09-01 01:56 active_low lrwxrwxrwx root root 2009-09-01 01:56 device ->
+../../../0-0022
+-rw-r--r-- root root 4096 2009-09-01 01:56 direction
+-rw-r--r-- root root 4096 2009-09-01 00:30 edge drwxr-xr-x root root 2009-09-01 00:00 power lrwxrwxrwx root root 2009-09-01 01:56 subsystem ->
+../../../../../../../class/gpio
+-rw-r--r-- root root 4096 2009-09-01 00:00 uevent
+-rw-r--r-- root root 4096 2009-09-01 00:00 value
+as above, the write permission of gpio/edge has been denied...
+how can i permit the write authority of gpio/edge, in the linux kernel? "
+0,"to update the web page contents, the same method applies than the previous possibility. "
+0,the 2.0 version of the .net framework.
+0,iotivity which is in the docker hub is the iotivity cloud.
+0,i had the same issue and removing the lock file /var/lib/mongodb/mongod.lock worked for me
+0,to instantiate deviceclient.
+0,forgive my ignorance as i am a complete novice in lua and the nodemcu api.
+0,there is also many points of analytic data that can be acquired via the plan including things such as estimated and actual number of rows.
+0,sharp.xmpp is a multiplatform .net assembly for communicating with an xmpp server.
+0,click on menu tools --> board and check if the correct board is select.
+0,i thank you for and advice you can add towards this project i am doing.
+0,use a different max31855 library that does not bit bang it.
+0,"update: working code for main:
+def connect_socket():
+socketio socketio('10.0.0.4',8080,namespace)
+socketio.wait()
+if __name__ '__main__':
+mykeyboardlistener() #keyboard listener, works fine
+socketthread threading.thread(target connect_socket) #creat thread for socket
+socketthread.daemon true #set daemon flag
+socketthread.start()
+snakeapp().run "
+0,it needs to issue a 'params' key pair if it is to work with the wrapper.
+0,"to support traditional settings.app panes, the app must include a settings.bundle with at least a root.plist to specify the connection of settings ui elements with nsuserdefaults keys. "
+0,"resources:
+jaws - url
+wordnet - url "
+0,i want to print the frequency.
+0,i want 5v voltage from any of the digital pins of arduino uno board but i am getting less than 2v.
+0,"one of the problems is here:
+you are not binding your handler to the event. "
+0,"height, width & depth). "
+0,"however, serieshelper not working for some reason. "
+0,"if you don't want your program to be killed, handle or block sigpipe yourself. "
+0,a nested type is a type that is defined inside another type and is typically accessed by dot notation on the parent type.
+0,i'am dealing exactly with the same issue right now.
+0,some things to ask.. do you continue to print debug messages?
+0,"project homepage
+url "
+0,ember model (em) is a simple and lightweight model library for ember.
+0,i don't want to use another ftdi chip while arduino already have it.
+0,"for example, on the arduino:
+
+and then in the python code:
+
+
+
+
+
+ser serial.serial(port_name,
+
+also, if you can send data from the arduino to the python host, then you know that your communication set up is correct. "
+0,so basically my bell program has to work on a mac computer now.
+0,but the summoners names i get are different from other running sites like url and url (both these sites have the same data but mine is different).
+0,zoneedit provides both free and paid dns services including dynamic dns and dns load balancing as well as web and mail forwarding and parking services.
+0,emf.edit - the emf.edit framework includes generic reusable classes for building editors for emf models.
+0,i restarted my computer and then opened the ide again and it worked while none of the above did.
+0,were i am going wrong?
+0,some of the unit tests require a sql database.
+0,the compiler says it: you cannot use to concatenate c strings (i.e.
+0,i then looked again at the original log and saw that it said it was an 8m (512k+512k) and then dumped a 2nd chip again as 8m.
+0,can anyone assist?
+0,"i hope that someone here can help me, i want to control my arduino uno by sending it commands from a c++ program that performs some basic face recognition. "
+0,"lapply is a function in r that returns a list of the same length as given argument x, each element of which is the result of applying given function to the corresponding element of x "
+1,"the intuit customer account data api provides developers access to end-user financial account and transactional information from nearly 19,000 financial institutions, giving developers the ability to create custom financial applications that can range from analyzing consumer behavior to credit checks to innovative new small business solutions. "
+0,it might be the case that you can look at how they set up their ap and web server as it is all open source.
+0,"radio.stoplistening()
+# take the time, and send it. "
+0,see copy-elision.
+0,"facebook's graph api allows websites to draw information about more objects than simply people, including photos, events, and pages, and their relationships between each other. "
+0,"see here for an example: url
+other providers may also offer such services. "
+0,framework for creating command-line interfaces from docstrings.
+0,i want to understand whole architecture to proceed on this.
+0,"heres what it looks like now:
+char pieces[27][6]
+{
+{""n"", ""n"", ""n"", ""n"", ""n"", ""n""},
+{""n"", ""n"", ""n"", ""n"", ""n"", ""n""},
+...
+{""t"", ""t"", ""t"", ""t"", ""t"", ""t""}
+};
+and heres the error its giving me:
+error: too many initializers for 'char [6]'
+could someone help me to initialize it properly? "
+0,"so valgrind will still have
+decoding failures from time to time. "
+0,i am using a raspberry pi 3 that's running windows 10 iot core.
+0,when i try to import flask i get more syntax errors.
+0,idls offer a bridge between the two different systems.
+0,`context-param` tag is used in the web application configuration file `web.xml` to set a context parameter to the application context.
+0,"that would normally work just nice, if your machines clocks are in sync and the file modification timestamps are ok. "
+0,available in ios 7.0 and later.
+0,"my budget is not large, and would prefer to keep this cheaper than $1000-$1500 excluding the mounted tool on top. "
+0,"im trying to get any version of android running on my raspberry pie 3 b. ive followed the instructions here and used these build settings
+
+oem partition size: 512mb
+using google play services
+empty bundle
+os build: oir1.170720.017
+
+im able to successfully flash the image onto a 64gb micro sd (with etcher) card but when i insert it into the pi and power it on i see a rainbow screen flash a couple times and then it goes completely black. "
+0,how to send alerts from iot hub back to devices only the messages filtered by stream analytic job?
+0,"similar to cilk, hopac runs parallel jobs using a work distributing scheduler in a non-preemptive fashion. "
+0,"the zope.interface module provides an implementation of ""object interfaces"" for python."
+0,keil (my flavor of cortex-m3) mentions that the exti (external interrupt controller) handles gpio pin interrupts.
+0,just because you are using 4.2.1 doesn't mean you need to use this tag.
+0,i have a raspberry pi v2 running windows 10 iot and am trying to run a dotnet 2.0 console application on it.
+0,"i can open the .jar-file with a program like winrar and see that in directory foo/bar/ there is the file main.class and in directory meta-inf/ there is a file called manifest.mf with content:
+
+i am using some libraries in the application, for example com.google.gson, but in the .jar there is the directory com/google/gson/ with the corresponding .class-files. "
+0,programmatically controlled http protocol listener for use in the .net framework.
+0,does anyone have any suggestions on how i can turn this data into a jpeg?
+0,"since it uses canvas, you have to include a polyfill to support older browsers. "
+0,"i want to do this:
+if i type this at the .h file everything are almost perfect but i can not make a method that will return a gsensitivity type.it does not recognize it. "
+0,although standard specifies minimal connection interval of 7.5ms apple documentation says recommendation is 30ms :-d what i have experienced using bunch of different chips and ios devices is that you will be capable to transmit 20bytes every 20-30ms.
+0,"the aws sdk for php enables php developers to easily work with amazon web services and build scalable solutions with amazon s3, amazon dynamodb, amazon glacier, and more. "
+0,replace with pip3.
+0,that's because the test condition your while loop will never become false.
+1,"products include:
+
+iar embedded workbench: c/c++ compiler and debugger tool suite for applications based on 8-, 16-, and 32-bit mcus
+c-run: runtime analysis tool for detecting data type casting, integer overflow and memory management errors
+c-stat: static analysis tool with support for misra-c, cwe and cert rules
+iar visualstate: tools for designing, testing and implementing embedded applications based on state machines. "
+0,"links
+google code link
+github fork link "
+0,i'm trying to send a variable to .
+0,"links
+
+github "
+0,"you can find a fairly easy to follow example on the arm site (but your hardware may differ from the controller discussed here): url
+the setup in the example is discussed in the readme in the .zip archive. "
+0,could you just return a 404 header when you want the server disabled?
+0,would this even be possible?
+0,update: i plugged it into my main home router instead of a switch and it worked immediately there.
+0,using recursion is making it more complicated than necessary.
+0,it scans your cloudant database and intuits the implicit structures in your data.
+0,"i have this function and i need to close the file before exiting the function say(""some text"")."
+0,kill {process number}) but if i send the shutdown command (i.e.
+0,i am writing code that will let arduino sent http posts to a iot cloud service (thethings.io).
+0,"for generic use, just use signalr "
+0,"the ethernet shield does not use the rx and tx pins (0,1) and i have personally used serial communication with the shield before. "
+0,"i'm new to python and i'm trying to produce sound after pushing a button on a raspberry pi 3 using offline tts, my push button is connected to pin 16 (bcm). "
+0,"common causes of unexpected behavior
+
+check your whitespace. "
+0,"i can tell that the problem is in this script because i have tried other scripts with infinite loops, and the ctrl-c works for those. "
+0,just install it in your pcl project and you are good to go.
+0,"however, microsoft, being a major player in the software development tools space, has introduced the term ""assembly"" to mean ""any set of files that are described by manifest file"", where ""manifest"" is also a microsoft term. "
+0,the certificates created are for testing purposes only.
+0,indicative is a simple yet powerful data validator for node.js and browsers.
+0,surfaceflinger is android's window compositor.
+0,we're trying to make something that'll continuously take pictures when its thrown off a building.
+0,"i'm aware i could use system.management and wmi queries, but
+these are not available on linux and macos, which is why i'm using
+libusbdotnet instead. "
+0,"since were are talking about an open source software, i believe there should be people who got wine (installed from jessie-backports) working on rpi3 without buying some extra patch. "
+0,at the very least you will need to install i2c tools and ensure your kernel has i2c support in it.
+0,"healthshare includes health information exchange, data aggregation,
+workflow, text analysis, and analytics technology. "
+0,"ucsr2c (1 << umsel21) | (1 << umsel20); // |(0 << ucpha2) | (0 << ucpol2);
+// enable receiver and transmitter. "
+0,"if it's incorrectly installed, remove it:
+apt-get remove --purge nodejs
+then install it again
+
+if it's correctly installed you should have the binaries for node and npm. "
+1,"i want to install open jdk 8 on my rarpberry pi 3 running ubuntu mate 16.04
+i've an internet connection using corporate proxy that requires a certificate for https connection. "
+0,"description
+remedy refers to the bmc remedy action request system (ars) which was orignally designed to be a platform to build help desk systems on. "
+0,"update:
+for deleting a existing device identity, please see the rest api reference and see the code below. "
+0,"the problem is when i try to run the output:
+/home/pi/spi_slave# ./build/output.elf
+segmentation fault
+/home/pi/spi_slave# ./build/kernel.img
+bash: ./build/kernel.img: cannot execute binary file
+tried to download the arm-none-eabi compiler from cambridge but it wont run:
+/home/pi/spi_slave# ../arm-2008q3/bin/arm-none-eabi-gcc
+bash: ../arm-2008q3/bin/arm-none-eabi-gcc: cannot execute binary file
+sourcecode
+the code we are trying to compile is: url
+the only change we did was in the makefile, added a # in front of the armgnu var
+
+environement
+
+what am i doing wrong? "
+0,"for questions about user-mode linux, use the [user-mode-linux] tag. "
+0,db2 is a family of database servers developed by ibm.
+0,and you'll have whole and thorough control of your code.
+0,#pragmas are often nonportable.
+0,"related links:
+
+home page
+tutorial
+blog link
+download page "
+0,webassembly aims to execute at native speed by taking advantage of common hardware capabilities available on a wide range of platforms.
+0,pdf can contain interactive forms that allow users to enter information to be stored in the pdf.
+0,"heroku-toolbelt install:
+
+heroku command fails with "
+0,requirejs is a javascript file and module loader.
+0,deploying applications native to the system for which they are developed
+0,you need to ensure that your frame rate is fast enough to get a decent still of the moving car.
+0,maybe some one can point me in the right direction.
+0,"while accessing the devicemgt i just keep getting below errors
+
+
+
+please any one help me on this, i have been working on this for about a week. "
+0,however i am having trouble running thermostat.py from my local machine (mac).
+0,this function never returns.
+0,"you need to grab the armv6 tar.gz here: url
+and do:
+
+and then:
+rm your-tar-file.tar.gz
+
+when you get to the part about setting up nginx make sure that you do not use port 8080 because unicorn uses it and gitlab will throw an error page when you try to access it. "
+0,here is a link to an in depth look at boot time optimizations.
+0,also refer write and print on manual.
+0,here is an example of the code on the arduino side
+0,the code doesn't measure the distance.
+0,"watch out for the first case its fine, but for the second one you would have to change the second filter sting to ""#."" "
+0,itemalias - item alias (form name redefenition) formatdatafunction - function to modify the request body.
+0,"if you are looking to configure rpi, you need to go google assistant's sdk site - url
+if it's the latter, you may want to check the google actions
+url "
+0,you can actually to it all with the raspberry pi.
+0,this code runs on an atmega328p using the arduino bootloader.
+0,"visualization features
+
+useful default settings make it easy to inspect data, with minimal code. "
+0,"organizations
+
+
+are group of users that share resources of an application (roles and permissions). "
+0,i guess you miss setting the for the page to bind the model.
+0,"this eliminates the need to use the xna 4 content pipeline, which is not available for all platforms. "
+0,you can't access from a constructor of a static object because there's no guarantee that serial will be set up.
+0,as this doesn't seem to be a commonly available library it's probably a custom module in your system.
+0,"based on the concept of a project object model: builds, dependency management, documentation creation, site publication, and distribution publication are all controlled from the declarative file. "
+0,more here.
+0,because after 30 seconds i want to repeat the same thing and change the image in the window.
+0,roles represent groupings of users for the purposes of granting permissions (e.g.
+0,"here is my qt code:
+
+my source code consists of two parts,
+1- serialportinfolist .... which works just fine
+2- opening and writing data... "
+0,how to solve this?
+0,"i considered the ds2401 approach; however, i couldn't justify the extra hardware. "
+0,same i have another xbee as coordinator which is accepting values from xbee sensing node.
+0,"i am developing a remote desktop application, rendering video and audio and sending data separately trying to sync using audio queue services, achieved the result too, but it gave glitches in sound, used audioqueuereset for syncing sound with video but getting glitches. "
+0,this question has been asked before but the solution did not solve my problem.
+0,"if you've already developed your firmware, switching to 30-pin may introduce problems. "
+0,start multiple server processes and spread the load with a load-balancer.
+0,i am doing a simple tcp communication from an arduino to raspberry-pi wirelessly with an esp8266 wifi module on arduino uno.the tcp server is running on the raspberry-pi.i am able to do tcp communication with the following at commands in arduino serial monitor at a baudrate of 9600.
+0,you can take your existing c knowledge when using arduino.
+1,i have configured a mastercard debit card in passbook.
+0,i think this and this issues are worth looking at.
+0,videos (of slides + audio) are archived.
+0,"@lxpanel --profile lxde-pi
+@pcmanfm --desktop --profile lxde-pi
+@lxterminal
+@xscreensaver -no-splash
+point-rpi
+
+note: in some places, it is suggested to use the -e flag instead of --command parameter in lxterminal, however that did not work for me. "
+0,"for example, querying 5tb on a 100-node system will take the same time as querying 50tb on a 1000-node system. "
+0,"you can use raw sockets, or some high level library such as zmq. "
+0,and prints out the data.
+0,"when i compile,the receiver led on arduino blinks.however i want to cross check if the integer is received by arduino. "
+0,heterogeneous multi-processing
+0,here's my code.
+0,"jquery also has capabilities to manage things like sending a request for a data update to the server, and updating based on the response when it comes back. "
+0,"it will look like this (i imagine):
+arduino (post) --> django server (localhost) --> postgresql database
+so i have 2 questions:
+1) in order to successfully send a post to my local django server, should my host be my public router ip and the port be the same as that which i am running my server on? "
+0,shake is a haskell library for writing build systems - designed as a replacement for make.
+0,spin is a multitasking high-level computer programming language created by parallax for their line of propeller microcontrollers.
+1,"tried adding the cert (in all formats .cer, .pem, .crt) using the certutil command as below. "
+0,maybe you should have a look at samsung artik cloud.
+0,very powerful.
+0,"when i send ""hello arduino!"
+0,"features
+
+fine-grained selection of synchronization operations to perform
+synchronizes single mailboxes or entire mailbox collections
+partial mirrors possible: keep only the latest messages locally
+trash functionality: backup messages before removing them
+imap features:
+
+
+links
+
+website "
+0,"edit: here's part of the cmakelist.txt file i updated on the rpi
+
+edit 2:
+proj a rtl-sdr
+proj b gpu_fft "
+0,"print 2 values separating them with ("","") or any other symbol. "
+0,"thus, the first 9 characters must be the digits 0 through 9, and the 10th must be either one of those digits or an x. "
+0,drawimage is often optimized with hardware operations while the single fill and stroke may not.
+0,i'm a new programmer for devices
+0,i'm currently running the followin in terminal to send a command over usb serial.
+0,"`numberformat` refers to formatting numbers by specifying decimal precision, decimal and thousand separator characters, currency sign, etc. "
+0,with that said i believe you want to move the contents of ser serial.serial() into the main() function just before the while loop.
+0,"the term was coined by manfred von thun to describe his language joy, but some consider forth as the first concatenative language. "
+0,team foundation server 11 was the codename for the product that is now known as visual studio team foundation server 2012.
+0,the power() function would return this respose back to salesforce.
+0,hinstance is a name given to a handler instance in window application
+0,i want this to be built in as a widget within the gui.
+0,more information can be found in the user guide.
+0,"it is commonly used to automate system maintenance or administration, though its general-purpose nature means that it can be used for other purposes, such as connecting to the internet and downloading emails. "
+0,you can easily check it with this code:
+0,javascript intersectionobserver is an api for finding intersections of dom elements.
+0,eventmachine based websocket server
+0,it all really depends on what you want to measure.
+0,"i am having similar issue with wso2 iot 3.3.0:
+1. "
+0,"wrought with the possibility of failure, but is definitely a learn by example approach. "
+0,"when i place an rfid tag in front of the rfid, the arduino board does receive data. "
+0,"here is my code in arduino
+server side code
+
+client side code
+
+can any one suggest me how to transfer data from client to server "
+0,i've tried running visual studio 2017 with administrative privileges.
+0,"i'm running the following command in /home/pi/.config/lxsession/lxde-pi/autostart:
+the midori browser is starting up automatically and going to the website i want it to go, but it won't show any popups. "
+0,"thanks to @dirk, who correctly diagnosed this as a problem of running r headless on the pi, i found a solution by mixing answers from previous posts:
+
+i start r by calling
+i installed the cairo package in r and save plots using code i adapted from this blog post
+
+i also found this site helpful. "
+0,it is able to establish relationships between items based on similarity and usage patterns.
+0,any idea why it returns before the full response is received (well within the timeout period)?
+0,this issue maybe can be solved by software but then i would recommend to bit-bang the whole i2c interface so you do not have to mix existing twi hardware handling with additional software components but have everything under control by software.
+0,"i do seem to recall, however, that there was a __int128_t def before that. "
+0,but it seems i am unable to retrieve the bytes on the arduino.
+0,i'm just learning to program gui's with pyqt.
+0,"because the pia is signed by its
+publisher and labeled with the primaryinteropassembly attribute, it
+can be differentiated from other interop assemblies that define the
+same types. "
+0,"performs application-defined tasks associated with freeing, releasing, or resetting unmanaged resources "
+0,it could be a good idea to look into that.
+0,"in order to program a cpld device (xc2c32a) when the file (.jed) is located on a raspberry pi 3b+ (raspbian lite) and the connection between the raspberry and the cpld device is with a jtag hs3 cable, the software adept 2 can be used. "
+0,"spatial operators for determining geospatial measurements like area, distance, length and perimeter. "
+0,"i pretty quickly see the following errors on console after starting chromium:
+
+after asking on the raspberrypi.org forum, it was suggested that i wait for the next version of chromium. "
+0,is there an option that i have put it in some mode that it can't respond anymore ?
+0,"it was a powerful high-level-language-based, processor-independent, multiprocessing, multiuser operating system with features comparable to unix. "
+0,i built from source on raspbian stretch.
+0,robert-orr has already answered your question but i think you are confused about the naming.
+0,then i tried with the nodemcu-flasher - windows.
+0,"i am able to connect an android device and windows os and read data, but for some reason linux is giving me a problem
+thank you "
+1,promela is a verification modeling language.
+0,i'm getting a compiler error when i try and compile the hellokeypad demo sketch.
+0,check your power supply (external power is most suitable) and send an close-command.
+0,openexr is used by ilm on all motion pictures currently in production.
+0,"2) i also ran all the combinations with/without and and these are the errors
+
+3) i also copied the sysroot from the raspberry-gcc8.3.0.exe install on win10 over to rpi-4 and passed that to gcc as its --sysroot location - which also fails with the ~basic_string() unresolver error. "
+0,"colour sensor code
+movement code in an other file i have these functions def listen():
+print(""listening to commands"")
+while true:
+msg socket.receive()
+print(""received: "" + msg)
+try: if(msg something):
+movement.forward() #ect
+except:
+print(msg)
+listening
+listening.start()
+i let the code for the color sensor run in the main thread
+i expect that everything works as it should and the car drives forward and the colour sensor reads the right values "
+0,thanks in advance for all help and suggestions.
+0,hopefully this will help you.
+0,"sybase was acquired by sap, inc. in august of 2011, as of version 3.0, the name has changed to sap mobile platform. "
+0,try changing the minimum api to 18.
+0,i truly believe that you can just install python3.5 from the source repos.
+0,"so basically i've been struggling with the issue that i can send a message to the leonardo with qt c++ however when i try to send another message it just doesn't arrives for some reason, while it worked with autoit (so i'm 100% confident that the code i used on the leonardo works flawless, and i'm still a big noob at c++)
+
+is there anyone who can point me out where i'd made the mistake and/or how to solve this? "
+0,an easier way might be to keep a buffer of that last 20 characters or so.
+0,"i am trying to boot my raspberry pi and the first light is green, the second red and the other ones are not on. "
+0,"instructions and data are stored in memory together, both of which are sent along the same bus. "
+0,i do not understand why this doesn't work.
+0,i want to send a grayscale image file from server to nodemcu as a response to an http request.
+0,"a component-based, event-driven programming and asp.net syntax similar framework for developing web applications in php 5. "
+0,"now engine temperature sensor, sends data to engine twin, and i want this data to be automatically updated in vehicle twin. "
+1,"here is my code right now:
+while searching for a solution i tried eliminating the part of the code that says:
+from google.cloud import speech
+from google.cloud.speech import enums
+from google.cloud.speech import types
+to what i get:
+traceback (most recent call last):
+file ""/home/pi/documents/pythonprograms/googlespeech.py"", line 12, in
+client speech.speechclient()
+nameerror: name 'speech' is not defined
+thus, i suppose the problem is within the way that i imported that, and not in the credential itself. "
+0,this is what i get in the terminal window.
+1,usb raw hid with hacked 8khz poll rate (125us poll interval) combined with teensy 3.2 (or above).
+0,"however on desktop, both nvidia and ati support opengl and opengles. "
+0,"* connection #0 to host github.com left intact | 2.47 mib/s remote: total 2610 (delta 245), reused 1412 (delta 149), pack-reused 0
+receiving objects: 100% (2610/2610), 14.26 mib | 2.34 mib/s, done. "
+0,is that statement true or false?
+0,i also have no idea on how can i do the android coding in eclipse that can make the arduino read/recognise the button click on the android device.
+0,"in response to a user command, commands and responses are effectively independent. "
+0,"mathjax is an open-source javascript engine that makes it easy to embed mathematical equations, symbols, and formulae on a web page. "
+0,"it has a difference by 1,7pa or 0,85%. "
+0,"here is my code:
+
+does anyone know something about this issue? "
+0,"my code for sms alerting,
+
+this code works for the very first outage but after power up also it send power down. "
+0,"you just need to connect the arduino's gnd to the controller's gnd, choose an arduino pin to be the tx line, and connect that pin to the controller's rx line. "
+0,i am very confused.
+1,"list of features:
+
+works out of the box, with full multimedia support and is extremely easy to use;
+both free of cost and open-source;
+community-driven;
+based on debian and ubuntu, it provides about 30,000 packages and one of the best software managers;
+safe and reliable. "
+0,you could take places as an integer parameter if you wanted to vary the precision.
+0,starting with version 2.3 this plugin uses the maven filtering shared component for filtering resources.
+0,"firefly also includes several filtering, graphic effects, and compositing tools to manipulate live image data. "
+0,"you will find the config.txt file in efiesp drive like this:
+
+
+reference: ""r-pi configuration file"" and ""config.txt""
+update: building iot core image with the modified config.txt file. "
+0,is there a standard way of unit testing code for architectures other than the development machine?
+0,i found the problem.
+0,the system needs to be able to pass data from one device to another.
+0,here is described an implementation of the [chap] (url) for arduino/avr devices.
+0,"let's suppose we have a riot spa like this:
+index.html:
+
+my-tag.riot:
+
+i would like to call myfunction() from index.html. "
+0,is an r package providing bindings to the geospatial data abstraction library (gdal) and access to projection/transformation operations from the proj library.
+0,you should handle data to meet this target.
+0,"look at the muxing bits:
+
+you were entering echo 7 which is --> 0 0 0111 and it means: bit 0,1 and 2 is 1, so the mode is set. "
+0,workers can include other scripts using the method.
+0,"note: tasks which performed all
+ their iterations remain active. "
+1,"response to http: is
+
+and https is:
+ * rebuilt url to: url. "
+0,i've looked into whether to use a simple loop or a deamon for this but i don't understand how to both run a script continuously and receive the new commands.
+0,"it is commonly used for weather forecast broadcasts, wherein a news presenter is usually seen standing in front of a large cgi map during live television newscasts, though in actuality it is a large blue or green background. "
+0,the webpages work except for the php portion of my code on my php page.
+0,"in an hyper threaded environment, for each processor core that is physically present, the operating system addresses two virtual or logical cores, and shares the workload between them when possible. "
+0,"the 9th edition or es9, officially known as ecmascript 2018, was finalized in june 2018. "
+0,phrets open source php library for using rets.
+0,i fail to do so.
+0,"as far as i can tell, they should be equivalent. "
+0,i'm writing this code for arduino.
+0,i have a sensor that has 3.3v output.
+0,"it is looking for concatcpu defined here:
+url
+
+so there may be something wrong with your bazelrc. "
+0,for timer0 set bit wgm01 of tccr0a port:
+0,i feel i am very close to the answer but can't see what i am missing.
+0,this will give you a sampling rate of ~3khz (depending on alot of factors)...
+0,"when x arrives, it's converted into fixed-point and you then you calculate its deviation from the current running average. "
+0,if someone has a microphone that works with speechrecognizer and windows iot 10.0.10586 please post it.
+0,"for whatever reason, esplorer is not designed to read nodemcu version. "
+0,but i know that's the way to do it.
+0,"can be assigned to a variable like light1on gpio.output(18,high) in python? "
+0,i've followed this guide to install/configure scanbd.
+0,"i cannot seem to find it in the bluetooth specifications, even though i imagined it would be under environmental sensing? "
+0,you can also set it to inherit or none to set all three properties to inherit or none.
+0,maybe this is the issue you're facing?
+0,or you could just not call the decode on line and keep it as bytes.
+0,the issue we currently face is that we cannot interface the spectroscopy unit and the raspberry pi in order to collect data.
+0,twig is a modern template engine for php.
+0,"here's my python code:
+
+my settings are:
+
+and i've updated the arduino code to reflect that. "
+0,"by default, the split bars between the views are horizontal, so the views are one on top of the other. "
+0,"is there a way to reverse the situation, like in asp or asp.net, where the file is expecting html, and i can escape using to write c# code. "
+0,is it possible to have multiple writers and readers if they are coordinated not to act at the same time?
+0,~/.bashrc) will no longer be valid or will point to a different file with the same filename if it exists.
+0,software collections (or scl) is a packaging technology to install multiple versions of software on the same system.
+0,"set up a cron job to call the php script:
+url
+alternatively you can use kermit to automate ftp as well:
+url "
+0,make this the most extensible version yet.
+0,the eeprom library for esp8266 only stores one byte.
+0,"this works well for the first connection i make, the second request to the streamsocketlistener destroys the wifi-direct session and it disconnects. "
+0,"traceur allows you to try out new and proposed language features today, helping you say what you mean in your code while informing the standards process. "
+0,"mobility: if you need you arduino to be on the move, buy the wifi shield. "
+0,"i'm trying to send a dm from a raspberry pi connected to the internet to a specific user, but i also want to attach a photo to said dm. "
+0,google cloud messaging for android (gcm) is a service that allows you to send data from your server to your users' android-powered devices.
+0,"this is the following code i used:
+
+i tested the code first with only 2 boards and it worked fine no problems no errors and it printed the printf statement in the code. "
+0,the 'trick' is getting your galileo exposed to the internet in such a way that it works like a proper http server.
+0,i want a completely black screen.
+0,"approach using pseudoterminals and good-old select to read file descriptors
+
+each of the approaches is bundled in a try_[some approach] function. "
+0,please comment if you need more information.
+0,"also known as 'tvs', template varaibles are customisable fields that can be associated to a template. "
+0,"
+the cmake-gui executable is the cmake gui. "
+0,"in haskell, ""bind"" often refers to the operator. "
+0,i am able to connect by .
+0,im trying to do an application to communicate with a microcontroller using the serial com port of my pc.
+0,"it keeps as close as possible to the semantics of the original javascript code, but its design is more in line with cocoa and objective-c conventions (although it is perfectly usable from swift). "
+0,i couldn't tell from any of the documentation that i saw which is better in this case.
+0,i am using build 16299 at the moment.
+0,"on iphone and ipod touch, the presented view is always full screen. "
+0,"now i just started playing around with arduino, and made a simple button class. "
+0,"in my file at url
+the first few two labels work, but not the latitude label. "
+1,"how can i make openvpn connect first, then send the notification after that? "
+0,"before jsf 2.2, the namespace url should be used instead. "
+0,i will up load the project on git when done
+0,the jquery ui droppable plugin makes selected elements droppable so they accept being dropped on by draggables.
+0,"i wrote some arduino code to write data to itself and echo it back, and that is correct. "
+0,"now, the reason i am doing this is to have a trigger-system to synchronize two different data streams (the arduino creates a 5v signal that is converted into a digital value and sent to the pc. "
+0,"but due to unavailability of resources in my country, i had to use this sensor. "
+0,the playground lets you experiment with how content is displayed on glass.
+0,wndproc is a .net method that process windows messages.
+0,i was wondering if it's possible to configure monoremotedebugger to place the app in a specified folder.
+0,checking if the location isvalid() always returns not to be true.
+1,"basically, you just need to include these lines:
+
+all x10 devices have two identifying attributes: a house code and unit code. "
+0,"official website: url
+useful links:
+
+source code repository on github
+google groups discussion forum "
+0,"i can connect to the internet just fine and also receive text messages (sms)
+however when i try connecting it to my raspberry pi (with raspbian os) then it doesn't work. "
+0,does anyone know how i may resolve my uploading issue?
+0,the use of multiple event threads increases the risk of deadlock.
+0,use this tag only for questions related to the universal transversal mercator coordinates system.
+0,code butchered a bit to get the appropriate bits here.
+0,"they are reliable, very well tested and mostly lightweight and sometimes just a wrapper around kernel or other modules function. "
+0,i am trying to implement a simple code to read the data from the ultrasonic and send it to a server by using californium.
+0,still i am getting this error.
+0,"to help with the time, i read the pot every pass through the main loop and save each value in a circular buffer. "
+0,"mainly from wikipedia:
+in computer science, the boolean satisfiability problem (sometimes called propositional satisfiability problem and abbreviated as satisfiability or sat) is the problem of determining if there exists an interpretation that satisfies a given boolean formula. "
+0,4.results will be displayed in the bottom panel.
+0,"if i've done something wrong, i'll be the first to admit to it, but please do provide helpful feedback. "
+0,"dhcp: start
+ dhcp in 1234ms,
+
+
+
+
+
+ listen on 2000
+you are now connected to your network. "
+0,"for doing self testing of the device, you can use the sample and do the following two tests :
+
+first, shorten tx and rx of the usb-to-ttl cable to test it on pc. "
+0,the third major release of the jquery library ([jquery]) has been worked on for a long time and contains some major changes.
+0,"can not make arbitrary instance or static method calls - only the
+public static methods of com.sun.btrace.btraceutils class or methods
+declared in the same program may be called from a btrace program. "
+0,"virtual filesystems
+lucee supports multiple virtual file systems -- built-in abstractions of various local and remote resources -- including zip, http, ftp, s3, and ram. "
+0,"see also:
+
+data migration wikipedia article "
+0,it looks to me that you should be cross compiling the python sdk for your target machine.
+0,"however, i noticed that after writing 20-30 times i get the following exception:
+
+here is the thread which is called from the main activity to send data over tcp:
+
+any help with this will be highly appreciated. "
+0,"a key-value pair is a set of two linked data items: a key which uniquely identifies some item of data, and the value, which is either the data that is identified or a pointer to the location of that data. "
+0,"since stx does not require the construction of an in-memory tree, it is suitable for use in resource constrained scenarios. "
+0,"rename it to supervisord and copy it to your /etc/init.d/ then run:
+
+i believe that init script has supervisord run as root as default. "
+0,"otherwise if you execute it at each iteration, it will delete the pin configuration and your scrip will not work properly. "
+0,really happy for any ideas.
+0,"after googling i found that this issue had actually been solved quite sometime ago, but the official version of mono installed using is too old. "
+0,"just 4 line
+enter image description here "
+0,"i'm not talking about a try/finally, or an unhandled exception handler. "
+0,this step might not be necessary.
+0,"we have automation cmdlets like select-window, select-control, send-keys, send-click, get-windowposition, set-windowposition, set-windowactive, remove-window ... etc. "
+0,"using hyperterminal on the com port associated with the hc-05 and the arduino serial console, i can send messages bidirectionally. "
+0,i'm trying to learn how to get an arduino to talk to an xbee pro s3b module via spi.
+0,nhapi was ported from the original hapi java project.
+0,"links
+
+introduction at beckhoff site
+
+related tags
+
+twincat-ads
+twincat "
+0,common containers are arrays or array-based objects.
+0,"to get your ip you could use something like this
+
+this outputs following in my case
+
+ethernet is what you want simply extract the ip part of the string
+now you need this part of ip 192.168.0.
+var ping require (""net-ping"");
+var ipstring '192.168.0. "
+0,i am able to communicate between 2 of them.
+0,cpuid is an intel x86 and x86_64 processor instruction that returns the processor type and the presence of particular features.
+0,you should not perform the earlier xor operation and instead should just and it with the complement.
+0,"if you want to play two square wave tones simultaneously, or even to control the volume of a single square wave tone, you need to be able to output more values than just ""on"" and ""off"". "
+0,basically serialport package in johnny five need to rebuild itself for the operating system so it needs the run the nodegyp package which will look for msbuild
+0,thanks for your time!
+0,"
+for primitives zero-initialization creates them with a value-initialization of 0
+for objects all of the primitives they are made up of are zero-initialized followed by default intialization
+for arrays zero-initialization occurs using the rules above, based on whether the array elements are primitives or objects
+
+for more information see: url "
+0,"first you should not use a0, a1, a2 but digital pins. "
+0,"millis() will drift against the gps interval, depending on how accurate your crystal is. "
+0,i have created a test enivornment for test automation in canoe by using vector software and for most of test cases i need to transmit continuous messages.
+0,"for instance, it can be used as a disassembler to view executable in assembly form. "
+1,in the typical case the operating system tries to handle the page fault by making the required page accessible at a location in physical memory or terminates the program in the case of an illegal access.
+0,the grouping type for the media query determines the arrangement of the media items you obtain.
+0,"i have tried the pexpect module for python, but i think it is not so good for me because i do not expect any particular output; i just want to get anything the shell gives me. "
+0,"in c++, the standard std::string class interoperates with c strings via the .c_str() method, though beware that std::strings can contain embedded 0-bytes. "
+0,globalize3 is the successor of globalize for rails and is targeted at activerecord version 3.x.
+0,translates most data types and indexes.
+0,templatepower offers you the ability to separate your php code and your (html) layoutfile.
+0,"i'm not clear on why i can declare and use a variable of that structure, however i can use the structure as a parameter type. "
+0,"it would appear that on your particular embedded system, a call to corresponds to a transmitted packet, with the beginpacket / endpacket merely establishing and nullifying the context necessary to transmit one, rather than actually delineating boundaries. "
+0,"once installed, i tried with g++-4.9 -wall -pthread -o ""main"" ""main.cpp"" and i got the following result:
+
+in file included from /usr/include/c++/4.9/thread:39:0,
+ from main.cpp:2: /usr/include/c++/4.9/functional: in instantiation of 'struct std::_bind_simple':
+ /usr/include/c++/4.9/thread:140:47: required from
+ 'std::thread::thread(_callable&&, _args&& ...) [with _callable int;
+ _args {}]' main.cpp:79:29: required from here /usr/include/c++/4.9/functional:1665:61: error: no type named 'type'
+ in 'class std::result_of'
+ typedef typename result_of<_callable(_args...)>::type result_type;
+ ^ /usr/include/c++/4.9/functional:1695:9: error: no type named 'type' in
+ 'class std::result_of'
+ _m_invoke(_index_tuple<_indices...>)
+ ^ compilation failed. "
+0,"for many developers, this is desirable because it allows developers to build their applications and trust that the proper amount of memory will be allocated when needed and released when not. "
+0,"now i want to choose the number of spins, but i haven't been able to. "
+0,"i guess i could trip the task
+ even more but i haven't tried further. "
+1,"cannot authenticate card
+void loop() {
+ // look for new cards
+ if ( ! "
+0,i also don't think that comparing a cpu-bound application with your perl script which is more likely bound by memory or disk overheads exhibits anything very much.
+0,i was able to do a workaround for this issue while there's no beautiful way.
+0,"using the http protocol, is it possible to leverage of http compression (i.e. ) "
+1,credentials in cryptography establish the identity of a party to communication.
+0,the standard linux command line tool will do this for you.
+0,"here is the arduino code:
+
+no matter which button i press on or off, the value of int data will remain same (255). "
+0,"easier to develop applications saves development costs and time because the developers can use a tested api for communications rather than have to design, develop, implement, test, and maintain their own infrastructure code. "
+0,"i want to add support for nextion displays in marlin firmware, but i get an error while compiling. "
+0,"in my main app.js, in the callback function of $(document).ready, i execute the current route and also register a route change handler function. "
+0,i found another.
+0,the output buffer can only be drained if the other end (i.e.
+0,"developer resources
+
+official website
+getting started documentation
+api reference guide
+libraries
+developer tools
+code samples
+stripe on github
+support
+
+products
+stripe payments: advanced processing capabilities and support for over 135 currencies. "
+1,since may 2018 both the endpoint and the certificates for aws's iot core has changed.
+0,"they're not defined because they're in the esp32 sdk, which is completely separate (different cpu, different instruction set, different os) from the esp8266. "
+0,in general controls are interactive elements of the user interface.
+0,i've a rspi 3 with stretch.
+0,it was burninated during last year's cleanup.
+0,"but if your software is not able to read from a serial com port, there are many other applications such as teraterm to store received data to a file. "
+0,"i was added permission
+in manifest file. "
+0,"furthermore, the code from the official webiopi from raspberrypi doesn't work either for me. "
+0,"found another post on here which was very helpful
+
+there are a whole slew of arduino simulators out there, many free, and
+ some paid products as well. "
+0,"code:
+serialcomm.h:
+
+serialcomm.cpp
+
+main.ccp
+int main(int argc, char* argv[])
+{
+
+ serialcomm serial;
+
+ serial.begin(""/dev/ttyacm0"", b115200);
+
+ for(auto i 0; i < 100; ++i)
+ {
+ cout << serial.read_data() << endl;
+ }
+}
+
+serial.ino:
+double sinal 0;
+
+void setup()
+{
+ serial.begin( 115200 );
+}
+
+void loop()
+{
+ sinal analogread( a0 ) * ( 5.0 / 1024.0 );
+ serial.print( ""$"" );
+ serial.print( sinal, 5 );
+ serial.print( "","" );
+ serial.print( sinal, 5 );
+ serial.print( "","" );
+ serial.print( sinal, 5 );
+ serial.print( ""#\n"" );
+}
+
+arduino ide output:
+$2.24121,2.24121,2.24121#
+$2.24609,2.24609,2.24609#
+$2.24121,2.24121,2.24121#
+$2.24121,2.24121,2.24121#
+$2.24609,2.24609,2.24609#
+
+computer output:
+$2.24609,2.24?m#
+$2. "
+0,"so i would re-write your python code with some calls:
+
+
+as for the arduino side, i think you have a mis-understanding of how the digitalwrite function works. "
+0,"organizational units are generaly the immediate superior of entries of object class user, inetorgperson, group or groupofnames. "
+0,i have a small device that operates using the smartphones audio jack.
+0,"archived documentation for prior versions (only available to licensed users)
+
+informative links that show up quite often in answers
+
+release notes for all versions. "
+0,"official release statement
+release date : 28 june 2016
+the main component of zend framework 3 remains the mvc components, which now is composed of many separeted components. "
+0,"the latest released version is sql server 2017 which was released on october 2nd, 2017. "
+0,"resources:
+
+bonecp home page,
+bonecp github repository. "
+0,"utf-8 is a variable-length encoding, so some characters take only one byte while others take several. "
+0,sanctuary makes it possible to write safe code without null checks.
+0,"r news, 1/2, 811. "
+0,"
+spoon is the graphical transformation and job designer associated with the pentaho data integration suite also known as the kettle project. "
+0,i suspect that can be a problem of definition order: you first use and then you define it; you first use pulsedown() and then you define it.
+0,lets create a sample a mvce.
+0,"processing events
+you are making two somewhat common mistakes: you shouldn't do , and you shouldn't call sleep. "
+0,the fact is that after a few minutes there is a delay between the joystick and circle.
+0,"by following these naming conventions, you will make it easier for others to understand your code and help you. "
+0,struts provides its own controller component and integrates with other technologies to provide the model and the view.
+0,livereload applies css/js changes to safari or chrome w/o reloading the page (and autoreloads the page when html changes)
+0,i went back to compile src/tacho.c which uses the function analogread and that compiled fine every time i tried (the preprocessor didn't see the need to complain about my include).
+0,i am very curious to find a workaround!
+0,you can easily modify the decisions without having code changes in the iot application.
+0,armory is an open source wallet management platform for the bitcoin network.
+0,"this worked, but it's more of a very quiet click rather than a loud beep. "
+0,since you act as a device you can power your board directly from the usb cable (the android device will power itself and your baord).
+0,i am stuck in a logical decision.
+0,"anyway, everything seems to be working fine now on the pi. "
+0,i'm using the latest and raspberry pi 1 model b (512 mb).
+0,then you attach the newly created function to the interrupt pin.
+0,what's the solution for the above problem?
+0,my battery is lifepo4 3.32v currently.
+0,"this is the error that i get:
+
+when i run this script i get the error message:
+var ardrone require('ar-drone');
+var gpio require('rpi-gpio');
+
+// pin setup - start
+gpio.setup(29, gpio.dir_in, readinput_flightfront);
+gpio.setup(31, gpio.dir_in, readinput_flightback); // typical setup
+gpio.setup(33, gpio.dir_in, readinput_flightleft);
+gpio.setup(35, gpio.dir_in, readinput_flightright);
+gpio.setup(36, gpio.dir_in, readinput_flightdown);
+gpio.setup(37, gpio.dir_in, readinput_flightup);
+gpio.setup(38, gpio.dir_in, readinput_flighttakeoff);
+gpio.setup(40, gpio.dir_in, readinput_flightland);
+// pin setup - stop
+
+
+// function setup - start
+function flightfunctakeoff(){
+// function that makes the drone take off
+ var client ardrone.createclient();
+ client.disableemergency();
+
+ client.takeoff();
+ client.stop();
+}
+
+function flightfuncland(){
+// function that makes the drone stop it's movement and land
+ var client ardrone.createclient();
+ client.disableemergency();
+
+ client.stop();
+ client.land();
+}
+
+function flightfuncfront(){
+// function that makes the drone fly forwards
+ var client ardrone.createclient();
+ client.disableemergency();
+
+ client
+ .after(500, function() {
+ this.front(0.5);
+ })
+ .after(1000, function() {
+ this.stop();
+ })
+}
+
+function flightfuncback(){
+// function that makes the drone fly backwards
+ var client ardrone.createclient();
+ client.disableemergency();
+
+ client
+ .after(500, function() {
+ this.back(0.5);
+ })
+ .after(1000, function() {
+ this.stop();
+ })
+}
+
+function flightfuncleft(){
+// function that makes the drone fly to the left
+ var client ardrone.createclient();
+ client.disableemergency();
+
+ client
+ .after(500, function() {
+ this.left(0.5);
+ })
+ .after(1000, function() {
+ this.stop();
+ })
+}
+
+function flightfuncright(){
+// function that makes the drone fly to the right
+ var client ardrone.createclient();
+ client.disableemergency();
+
+ client
+ .after(500, function() {
+ this.right(0.5);
+ })
+ .after(1000, function() {
+ this.stop();
+ })
+}
+
+function flightfuncup(){
+// function that makes the drone fly upwards
+ var client ardrone.createclient();
+ client.disableemergency();
+
+ client
+ .after(500, function() {
+ this.up(0.5);
+ })
+ .after(1000, function() {
+ this.stop();
+ })
+}
+
+function flightfuncdown(){
+// function that makes the drone fly downwards
+ var client ardrone.createclient();
+ client.disableemergency();
+
+ client
+ .after(500, function() {
+ this.down(0.5);
+ })
+ .after(1000, function() {
+ this.stop();
+ })
+}
+// function setup - stop
+
+
+
+// special function - start
+function readinput_flighttakeoff() {
+// readinput from pin 38
+ gpio.read(38, function(err, value) {
+ if(value false){
+ flightfunctakeoff(); // run the function
+ } else {
+ process.stdout.write(""""); // will print out an error message.
+ } "
+0,"there are 3 ways to handle this, 2 with a timer, one without, it also depends on the api you are using:
+1) add a variable to store when the event was last fired. "
+0,"typically, the user knows regular expressions, but is not really aware of the limitations, so it asks the so community. "
+0,"so suppose pin 5 gets an analog value of 256 which as i am using a particle photon board comes in a 12bit format text as 000100000000. so does payload[0] get the last eight bits ie 00000000, or does it get value after shifting ie, 00000001? "
+0,"extract, transform and load data. "
+0,"this is relative to the root directory of the jail environment, and may vary a lot, depending on the type of the specific jail environment. "
+0,see also the git man page for git gc.
+0,"however, bash doesn't do word splitting and globbing on quoted variables:
+
+results in:
+quoted: /etc/*tab
+unquoted: /etc/crontab /etc/fstab /etc/inittab /etc/mtab
+
+you don't normally want bash to mess around with your variables, which is why quoting is so important and kudos for doing it. "
+0,"since then, it encouraged students and enthusiasts from backgrounds other than sciences and mathematics to create their own programs and many microcomputers of the 1980s came pre-loaded with basic. "
+0,android adapter method notifies observers attached to the adapter that the underlying data has changed and any views reflecting the data should be refreshed.
+0,"your issue is not that the button is not changing the value, but rather your code has no exit point if it does; the button will change the value, but nothing in tells it to stop. "
+0,this is very useful during development but can also be used in server based applications.
+0,"i have installed tesseract 3,opencv3 and openalpr. "
+0,"you use one timer, the chip wakes up and does work when the time is reached. "
+0,the current production release series of mongodb 4.0.
+0,so i need a command that would do the same as cd /home/pi/pi_video_looper so i can execute install.sh directly.
+0,"1) i get a direct method request:
+
+2) for some reasons i do not send the response in
+
+3) instead i send at once a twin update. "
+0,"answered my own question in perhaps the most noobiest way:
+
+came out looking like: "
+0,my name is eric (aka rocket hazmat).
+0,"you can read more about wxpython and threading at the following:
+
+url
+url
+
+if you do attempt to call a wxpython method from a thread, the behavior will be undefined and you may or may not have immediate issues. "
+0,"we have replicated a project that was on hackster.io:
+url
+it's working great but every night at 03:26gmt +2 we get a amqp error and loose connection and the sensor stops sending data. "
+0,github page: url
+0,"just imagine your program running: the instructions are being executed one after the other in the order in which they are written, according to the execution flow that they define with the exception of which is asynchronously executed (maybe). "
+0,send the data as json.
+0,i would like to save a lua program on nodemcu memory.
+0,why can't i access the 'hex' string outside the while loop?
+0,miva script is often described as 'xml-like' although this is something of a misnomer.
+0,"all versions of the archicad contain their own default libraries, also objects like furniture, windows, doors, trees, people, cars, construction elements, etc. "
+0,a proper way to this problem is to receive the whole message inside a buffer first and then process it only when a end-of-message marker is received.
+0,spidermonkey is also the first javascript engine ever made.
+0,"for instance with turbopower async, you could setup tapddatapacket component this way:
+
+and in its onstringpacket event process the received text somehow: "
+0,"here is the python script to change my wallpaper on raspberry pi:
+
+here is the crontab line i added:
+
+when the script runs as sudo or called by cron every minute it gives me a weird error in terminal:
+** message: 08:41:35.152: x-terminal-emulator has very limited support, consider choose another terminal
+
+what could be the problem is it the path of the program ""pcmanfm"" (the default file/window manager of raspberry pi) cant be found when run as sudo/cron? "
+0,this is the c# code.
+0,"modern web development architecture based on client-side javascript, reusable apis, and prebuilt markup. "
+0,"webstorm is a commercial ide built by jetbrains for editing javascript, html, and css. "
+0,i need help with parsing the hours and minutes from both the current time and alarm time and converting them to seconds so that i can subtract current time from alarm time.
+0,"// file node.h
+class node {
+ public:
+ node(boolean isbase, int *channellist);
+ ~node(); // destructor (called at object destruction)
+ boolean isbase();
+ int* getchannellist();
+
+ private:
+ int *_channellist;
+};
+
+// file node.cpp
+include ""arduino.h""
+#include ""node.h""
+#include
+#include
+
+node::node(boolean isbase, int *channellist)
+{
+ _isbase isbase;
+ int channellistlength;
+ // get channel list lenght
+ for (channellistlength 0; channellist[channellistlength] 0; channellistlength++);
+
+ _channellist (int*)malloc((channellistlength+1)*sizeof(int));
+ if (_channellist null)
+ {
+ int i;
+ for (i 0; i channellistlength; i++)
+ _channellist[i] channellist[i];
+ // no need to enforce the last one to be a 0
+ }
+}
+
+~node()
+{
+ free(_channellist);
+}
+
+boolean node::isbase(){
+ return _isbase;
+}
+
+int* node::getchannellist(){
+ return _channellist;
+}
+
+note, however, that if the malloc fails you will have a null pointer. "
+0,i've been working on a simple xbee/arduino/python transfer system.
+0,i designed an app for ios 7 but the xcode showed the 'isconnected' in the tableviewcontroller.h is deprecated.
+0,"if not, please do and reply. "
+0,"now i'm getting the following error when i try to compile - does anyone have any suggestions, please? "
+0,many projects support interaction with a relational database.
+0,i am using my mobile as hotspot to connect to both my pc and raspberry pi.
+0,i use the first option above so that i can terminal (bluetooth) from my phone to the hc05 and switch on a led/relay etc (ie bring up pin 2 to high) on the hc05.
+0,fully modularized sound drivers.
+0,int.
+0,all lan ports on a port channel must be the same speed and must all be configured as either layer 2 or layer 3 lan ports.
+0,"however, when the board is powered by the computer via usb cable (usb-to-serial to be exact), rx0 receives data from the computer instead of the bluetooth even when it's connected. "
+0,"i don't need this, but i don't know how to disable it. "
+0,i am passing this string to a function i wrote which requires const char str[] as an input parameter.
+0,"but when it's linking, they show me the following error. "
+0,"0x40234d6d: udp_bind at
+/users/igrokhotkov/espressif/arduino/tools/sdk/lwip/src/core/udp.c line 787
+0x401060f4: igmp_timer at
+/users/igrokhotkov/espressif/arduino/tools/sdk/lwip/src/core/timers.c line 217
+0x4021fdb4: system_get_os_print at ?? "
+0,"check type and id""}
+
+i checked the log and it says: starting transaction to url;
+is this url even valid??? "
+0,"use your delegate to provide appropriate
+ behavior when these transitions occur. "
+0,did i mix up my pointers somewhere?
+0,"the python script that i want to use:
+
+every time i want to run this, i just get the error:
+
+what should i do to solve this? "
+0,"
+ejabberd provides an event mechanism. "
+0,i used the sketch from url
+0,"this is the error when i compiled my program
+
+that all thank you for your concern "
+0,"in computing, signedness is a property of data types representing numbers in computer programs. "
+0,"ibm mobile test workbench for worklight automates the creation, execution, and analysis of functional tests for ibm worklight native and hybrid applications on android and ios devices. "
+0,i would like to be able to parse a string separated by commas on my arduino.
+0,"i'm attempting this with this line:
+
+the problem is that adjusting 0 adjusts every input coming into the mixer, not just the one bus like i'm expecting it to. "
+0,"with the servo and sensor using the same power source, the voltage would drop below 5 v when the servo was running. "
+1,"run ;
+scroll down to boot options and press enter;
+select desktop/cli;
+you should see the options for desktop autologin or console autologin. "
+0,how can i take the pixels of the penny only and average those?
+0,"delay(100);
+ digitalwrite(13,high);//turn on led.
+ } "
+0,network getaddrinfo enotfound npm err!
+0,"it provides tools for teams to manage data, automate infrastructure, orchestrate workflows, and collaborate with others in a unified workspace. "
+0,"root is the base framework for the roofit and roostat projects, devoted to statistical analysis, and for tmva for multivariate analysis (machine learning). "
+0,"this preserves the same navigation left, actions right structure present in the action bar and elsewhere. "
+0,"
+make sure your file has execution permission
+instead you could call /usr/bin/python /var/www/photoburst.py and see if that works
+
+what linux are you running? "
+0,"when i want to implement a simple driver module on my raspberry pi, however, that i found in this example the request of ports is implemented by gpio_request() function. "
+0,i have done the same setup in my laptop it is working fine and i am able to see the view using chrome vnc viewer.
+0,see url
+0,"python code
+
+node code
+var serialport require('serialport'); // npm i serialport
+
+var port new serialport('com6', {
+ baudrate: 9600
+});
+
+setinterval(function() {
+ port.write('0 0 0 0');
+ if (port) {
+ let s port.read();
+ if(s) {
+ console.log(s.tostring());
+ }
+ }
+ console.log(""sent"");
+}, 100); // this number works if it's >0.8
+
+arduino code
+void setup() {
+ serial.begin(9600);
+}
+
+void loop() {
+ serial.read();
+ serial.println(""blah"");
+} "
+0,avdec_h264 !
+0,this will also then exist in other/updated ides that you can run.
+0,i'm trying to make a contraption where you press a button on one board and it moves the servo either to 90 degrees or 180 degrees on the other board.
+0,"unsigned long prevmillis 0;
+unsigned long progcycles 0;
+int serialbyte 0;
+int lastserial 0;
+int smallblink 0;
+bool dostatus false; // determine whether to send sys status. "
+0,"if your question applies to onset detection of audio more generally, use this tag only. "
+0,"maybe you can use a postdelay handler
+
+the handler is not blocking, but maybe it can help
+excuse me for my bad english, good luck! "
+0,my http.get() using the esp8266httpclient.h header is returning -1 which means that it fails to connect at some point (httpc_error_connection_refused).
+0,"i have written a simple program, that outputs 0-9 to the uart. "
+0,"compiler doesnt even ""care"" about progmem type, in .h file? "
+0,it is using microsoft.azure.devices.client to create device messages and send them to the iothub which then routes them to an event hub where azure stream analytics has it as an input.
+0,best-first search is a graph search which orders all partial solutions (states) according to some heuristic which attempts to predict how close a partial solution is to a complete solution (goal state).
+0,see the license here.
+0,not sure about this.
+0,it is similar in functionality to bsd editline and gnu readline.
+0,it indicates whether the audio chip should be enabled (true) or disabled (false).
+0,"these differences are articulated above in the meet couchdb section, and other portions of this wiki. "
+0,"
+
+# enable skip-init on the uart interfaces, so u-boot doesn't attempt to
+# re-initialize them. "
+0,i can probably do a lot better by reusing objects but i'm putting this attempt in hold for now.
+0,i have connected my arduino code serially to processing.
+0,"for that purpose punbb supports mysql, postgresql and sqlite. "
+0,"but if i leave the function as is, and only changing this:
+
+
+to this:
+ // skip the 2 stop bits
+ tuneddelay(_rx_delay_stopbit*2);
+ debugpulse(_debug_pin2, 1);
+
+i can upload the sketch and even start receiving true and correct data on my serial. "
+0,it is also because my security camera is hooked up to a battery and i am trying to lower the pi's usage hence why i am dedicating a main hub for the heavy operations.
+0,"with clients written in python, ruby, node.js, elixir, java, nginx, c, and c#, and more. "
+0,"
+website
+github repository "
+0,i successfully run my app for two days.
+0,since your lora::message function returns nothing (void) you'll get another error here.
+0,"this m3-model is the language used by mof to build metamodels, called m2-models. "
+0,"the software consists of three components:
+
+a server
+a client
+a deployer agent
+
+using the client, you connect to your release management server and configure what applications you're deploying, how they should be deployed, and what servers they should be deployed to. "
+0,"libmemcache is the c api for memcached, a high-performance, distributed memory object caching system. "
+0,what do you mean by that?
+0,source: url
+0,"javascript is client-side, phyton is server side, so you need to send a form every time you want to communicate the data. "
+0,note that a port to javascript is also available in the yui compressor repository.
+0,so is impossible auto detect arduino using serial port technology.
+0,"the official raspberry pi 7"" touchscreen display (url) works really well with windows 10 iot core running on my raspberry pi 2 b since support was added back in an insider preview (display and touch are functional)."
+0,"3) i am trying to create ml datasource from the s3 bucket, but get the error below when amazon ml tries to create schema:
+
+""amazon ml can't retrieve the schema. "
+0,"i dont really like the way it uses globes, but it still looks pretty clean. "
+0,"at a glance
+
+server side - extremely fast c# implementation (typically 15x faster than markdownsharp). "
+0,i'm hoping that you can give me direction on this one.
+0,"i used ""status"" because it is in the topic: ""iot-2/cmd/status/fmt/json"" is that correct?)"
+1,"overall my question would be, is the certificate i was using for trying to connect (the baltimore cybertrust root) the right certificate to use, and is there any obvious settings in mbedtls that i didn't set? "
+0,i don't understand a thing about makefile or why it even exists.
+0,"the repetitions allow minimum distances to accurately propagate throughout the graph, since, in the absence of negative cycles, the shortest path can only visit each node at most once. "
+0,the tex.se website has a [sagetex] tag for sagetex questions.
+0,not sure what i might be doing wrong.
+0,bit has changed.
+0,general linux questions should be tagged linux.
+0,the engine uses a custom programming language called gdscript.
+0,"in several languages, the keyword is used to identify methods which will be used in operator-overloading. "
+0,a collection containing unique entries - a treeset sorts its entries either by their natural order if they are comparable or by an explicit comparator provided as a constructor parameter.
+0,i'm trying to make a brainfuck interpreter for an arduino.
+0,what am i overlooking?
+0,"on pin 3 works, but not on pin 5. "
+0,"this could occur as a result of many different actions, such as...
+
+you are calling a method that accepts a low-level object type for an argument (such as ) but you're passing an object that is not one of the types expected by the method. "
+0,"i ran ./change-ip.sh with exemple.com
+2. "
+0,"in fact, there are no arithmetic instructions that perform on more than one register at once, so i'm really not sure what the compiler is doing! "
+0,"electron builder provides these services:
+
+management of npm packages:
+
+
+native application dependencies compilation
+development dependencies are never excluded
+
+management of build versions
+code signing (ci server, development machine)
+auto update support
+multiple target platforms and distribution formats:
+
+
+all platforms: 7z, zip, tar.gz, tar.xz, tar.lz, tar.bz2
+macos: dmg, mas
+linux: appimage, deb, rpm, apk, freebsd, pacman, p5p
+windows: nsis, squirrel.windows
+
+github releases integration for artifacts
+
+electron-packager and appdmg are used under the hood. "
+0,thank you!
+0,"the implementations declared by hook_theme() have two purposes: either they specify how a particular render array is to be rendered as html (this is usually the case if the theme function is assigned to the render array's #theme property), or they return the html that should be returned by an invocation of theme(). "
+1,so in otherwords i can manually open the file on my mac so its not an access issue.
+0,"but now, i am not getting any error message. "
+0,what i'd like to do is to create a simple gui on windows forms and control a arduino.
+0,"by taking care of the infrastructure, it helps clients focus on building the core of their product's end-user value. "
+0,"or use some other tricks, or rearange this procedure somewhat, or ensure that tty1 runs everything in jobs with nohup, then logs out etc, etc. "
+1,"whmcs features automated signups for web hosting customers, automatic invoicing and payment processing in multiple currencies, account provisioning, domain registration and management, as well as a fully featured web ticketing and support system for end users. "
+0,my idea is to try to multiplex these sensors to the rpi via arduino mega.
+0,sometimes it gets called very early and sometimes too late.
+0,"mobile sdk for reading id cards, payment slips, invoices, iban, receipts and more. "
+0,this variable holds the amount of milliseconds since the device is running (it's an arduino).
+0,in my case i want to know for which pin the interrupt came.
+1,"the documentation about run_command states that:
+
+function will return after connection and authentication establishment and after commands have been sent to successfully established ssh channels. "
+0,the gdb makefile settings have pthread pocofoundation pocodata pocodatad pocodatasqlite pocodatasqlited libraries listed.
+0,is implemented in libemqtt and you could try to maintain the connection with a regular ping and try to reconnect if it fails.
+0,"in your case, it would look like this:
+
+now you can use the function in this way: lib_aci_send_data(pipe_air_quality_sensor_relative_humidity_tx, q.s, 4);
+i cannot test this as of now since i'm on a different machine, please let me know if this was successful, i'm willing to add edits if necessary. "
+0,"in my current scenario, i'm using netlight pin (pin no. "
+0,"more info
+
+gwt maven plugin official site
+list of goals supplied by the gwt maven plugin "
+0,"i am wondering why this code
+
+works, but when written like this
+
+it fails with the message
+unable to send the email. "
+0,"would it be possible to
+
+and then
+
+and use a central (admin-type node) soc / computer on wifi to:
+$ curl $esp8266_ip "
+0,i'm struggling making the right piece of code with jquery.
+0,"what i'm noticing is that while i debug the code and step through it, if i trigger the external interrupt manually then it doesn't jump to the isr straight away. "
+0,this led to decent accuracy in my moderator actions in the past.
+0,"in object-oriented programming, a constructor (sometimes shortened to ctor) in a class is a special type of subroutine called at the creation of an object. "
+0,the result is a real-time tracking that typically improves over time.
+0,"you can use the cool new web technologies like web components, model driven views and dart today. "
+0,send this number to the receiver.
+0,"a query that is nested inside a select, insert, etc. "
+0,"it seems to loose functionality to control the gpio pins, and crashes silently without any error. "
+0,"(cla/ins/p1/p2/len)
+with regard to the error: it seams that your messages are routed to the uicc. "
+0,thanks!
+0,"i am decoding audio using , mediacodec, and audiotrack. "
+0,"i've already been messing around with the frequencies with the pygame.mixer.pre_init(), and pygame.mixer.init()commands. "
+0,i had this great idea to turn it into a visual equalizer and lo and behold there were people already doing it here.
+0,why would i use one over the other?
+0,i'm in doubt between: mysystem/slaveid/res/masterid or simply mysystem/slaveid/res.
+0,here's what i have so far as it's just displaying the rfid tag once swiped.
+0,typically a hyperlink is a anchor tag in html and is followed by clicking on it.
+0,i am searching for why this doesn't work on docker for windows running on nano server for windows 2016 and your findings match mine.
+0,i have an arduino connected over usb with a raspberry pi.
+0,"list commits that are reachable by following the parent links from the given commit(s), but exclude commits that are reachable from the one(s) given with a ^ in front of them. "
+0,"now i want to test this, therefore i have to run
+
+my idea was to write a program in c to make this test automatic, and use fork to run access concurrently. "
+0,time information is discarded.
+0,other linkers (e.g.
+0,"all assume headers missing, but none specifically point to how to get headers - only advise installing dev package to get them, which i have done. "
+0,a recording of the announcement presentation can be viewed on infoq and the slides (pdf) have been published.
+0,"a world class user experience the most robust, comprehensive ppm tool available. "
+0,i have been searching for the answer but i'm not really sure what to look for.
+0,but it seems to require that you define your callbacks as non-anonymous functions so that you can refer to them for removal.
+0,win32com is a python module to interact with windows com components.
+0,"the asyncio package provides asynchronous i/o, event loop, coroutines and tasks beginning with python 3.4. "
+0,"my cameras are unknown brands but exposes ""video capture"" as device caps."
+0,"java gridlayout supports cell padding and may have unspecified number of rows (there are enough rows to place all elements using the specified number of columns, new rows are added as required). "
+0,`managementeventwatcher` class is from `system.management` namespace.
+0,i study a project about controlling a robot with visual studio c#.
+0,you are reading the state of the button by calling .
+0,"in addition, you have access to all of the information in the help documentation even if youre working without an internet connection. "
+0,"definition:
+match is a microsoft excel function which searches for the from the lookup_array (a range of cells) based on the match_type. "
+0,"the problem wasn't with the binder, i had forgotten to instantiate esp8266webserver. "
+0,sandcastle helpfilebuilder
+0,"related questions:
+
+where is visual web editor for javaserver faces on netbeans
+
+related tag info pages
+
+jsf tag info page "
+0,"object files in this format usually have the extension "".obj""."
+0,i have been able to access the raw serial data but am at odds with an effective means of parsing the data into a usable format.
+0,"then, on your arduino, you can check its dsr pin (assuming null-modem wiring with handshaking, where the pc dtr pin is wired to dsr+cd on the arduino) at regular intervals, and handle the 'nobody connected' scenario in any way you see fit. "
+0,git-remote is a command used to manage the set of tracked remote repositories for a git repository.
+0,"a light
+web server will be running on the module. "
+0,"hebrew is a language of the semitic branch of the afro-asiatic languages that, in modern and ancient forms, is an official language of israel and a language in which much of the scriptures of jews and christians are written in. "
+0,the .net framework also supports custom formatting.
+0,it was burninated during the 2012 cleanup.
+0,use this tag for a question specifically for version 2.2.
+0,windows xp does not support directx 10 and above.
+0,it should do this with a timeout.
+0,"it can be solved with few patterns in place, depending upon code complexity, outer dependencies, number of use cases and many other factors. "
+0,"for example, gagawa is perfect when a developer needs to return a small chunk of well-formed html in an ajax response. "
+0,"so before the javascript the page source looks empty:
+
+for reference, the site i am referring to is: url "
+0,you should review this article (url) to determine which option is most appropriate for your scenario.
+0,so that you know which part is causing the issue.
+0,here is how i am attempting to receive the list from the api.
+0,could anyone please guide me to send the data.
+0,is there something i might have missed with how nvm behaves that might affect this?
+0,"references
+msdn - wcf test client "
+0,"hy community, i'm writing a program with arduino. "
+0,"also, kognitio can be reconfigured in size to help respond to the requirements of a data analytics project
+ultra-high performance get fast results. "
+0,computer graphics uses blending concept to achieve transparency with image.
+0,you cannot convert int implicitly to anonymous enum.
+0,!pycmd in windbg starts an interactive console and !py
+ 0 0 0111 and it means: bit 0,1 and 2 is 1, so the mode is set. "
+0,"google+ hangouts also offers a ""hangouts on air"" feature for broadcasting live video conversations that are accessible to anyone with a web browser."
+0,i am using 1.6.5 of the ide.
+0,"i installed python 3.5 to raspberry pi 3
+what i want to know is how to use raspberry pi and iot hub to tutn on led and turn off already on led.please if you have any idea,tell me "
+0,network framework in the core services for ios & mac os x
+0,"for more info, see : url "
+0,"i have had some experience replacing arduino ide with just a makefile, but it gets hairy when you need to use different boards and perhaps several connected at the same time. "
+0,"i am trying to program some software for my arduino to read data from an ir fire detector module, i know the module works but i just cannot get the arduino to read from it and carry out a function correctly. "
+0,i have two embedded machines(same manufacture).
+0,"amazon marketplace web service (amazon mws) is an integrated web service api that helps amazon sellers to programmatically exchange data on listings, orders, payments, reports, and more. "
+0,the code you processing code you posted seems to do mostly what you intended it to do.
+0,"if the web application uses servlets, then the servlet container uses web.xml to ascertain to which servlet a url request will be routed to. "
+0,"a monoid is a set that is closed under an associative binary operation and has an identity element i such that for all a s, ia ai a. "
+0,halp?
+0,"the project: url
+some system / ide specs in case that is relevant:
+
+microsoft visual studio community 2015 version 14.0.23107.0 d14rel
+microsoft .net framework version 4.6.00079
+installed version: community
+visual basic 2015 00322-20000-00000-aa366
+visual c# 2015 00322-20000-00000-aa366
+visual c++ 2015 00322-20000-00000-aa366
+windows phone sdk 8.0 - enu 00322-20000-00000-aa366
+application insights tools for visual studio package 1.0
+jetbrains resharper ultimate 2015.2 build 103.0.20150818.200216
+microsoft azure mobile services tools 1.4
+nuget package manager 3.2.0
+preemptive analytics visualizer 1.2
+sql server compact &sqlite toolbox 4.3.0
+visual studio tools for universal windows apps 14.0.23309.00 d14oob "
+0,"mixins
+interfaces but with implementation. "
+0,"silverlight is microsoft's cross-browser, cross platform plug-in for media experiences and rich interactive applications. "
+0,an online demo for mathics can be found on mathics.net.
+0,you should switch the container to linux container(right click the docker icon in task bar -> switch to linux containers).
+0,i am trying to communicate with a cbc autoanaylyser machine which sends data across rs232 serial port.
+0,"microsoft sql server 2008 r2 reporting services provides a complete, server-based platform designed to support a wide variety of reporting needs enabling organizations to deliver relevant information where needed across the entire enterprise. "
+0,"if, for some reasons, you want to exclude some pins (e.g. "
+0,"take a simple case:
+void foo()
+{
+}
+
+int (*fp)(int x) foo;
+
+should result in the same compiler error because you are trying to initialize a variable of type int (*)(int) using foo, whose type is void (*)(). "
+0,cakephp is a web framework written in php.
+0,i want to send commands to an arduino and i want to get the answers with serial readline().
+0,it is currently running raspbian.
+0,ok.
+0,"but before i can actually connect it to an app, i need my code to work with just the serial monitor. "
+0,any pointers would be appreciated.
+0,"if you want a really simple multi-node container cluster, i'd say that docker swarm is a reasonable choice. "
+0,"i have created a data logger using a microcontroller and 3 potentiometers (x,y,z). "
+0,"questions specific to ehcache version 2, for general question about ehcache use ehcache tag "
+0,i do not know how i would store the result.
+0,"this paper describes a simple yet novel method for constructing sets of 50-best parses based on a coarse-to-fine generative parser (charniak, 2000). "
+0,the string given is one of the services listed in the jtapipeer.getservices().
+1,"this is the result on my linux(ip address is 135.251.247.21):
+sdn@sdn-kvm:~$ docker ps -a container id image
+command created status
+ports
+names
+be8c8289fe20 135.249.45.113:9005/onos:1.7.004
+""./bin/onos-service"" 3 weeks ago up 7 hours
+0.0.0.0:6633->6633/tcp, 6653/tcp, 0.0.0.0:8101->8101/tcp, 9876/tcp, 0.0.0.0:9191->8181/tcp onos-docker
+i can access this container from remote machine via ssh: ""ssh -p 8101 karaf@135.251.247.21""
+if you can not access from remote, you can try to access on your local machine, ""docker exec -it xxx bash"", xxx is the container name. "
+1,"the topic is not valid: use-token-auth the topic does not match an allowed rule 07.02.2017 11:58:16
+closed connection from 93.231.145.115. "
+0,it's new life of bootstrap-editable plugin that was strongly refactored and improved.
+0,please use backbone.js instead of this tag.
+0,"otherwise, you'll get a warning next time toy
+# configure the pins. "
+0,thank you very much
+0,"quoting the overview from the jpa 2.0 specification:
+6.1 overview
+the java persistence criteria api,
+like the java persistence query
+language is based on the abstract
+persistence schema of entities, their
+embedded objects, and their
+relationships as its data model. "
+0,google query language allow developers to perform various data manipulations using a syntax very similar to the sql syntax.
+0,"a lot of modbus programs let you specify if you want to do a write, or a write with a readback. "
+0,"supports traceur, babel and typescript for compiling es6 modules and syntax into es5 in the browser with source map support. "
+0,ql used for my purpose:
+0,"if ubuntu is offline, rpi itself can handle the request as well. "
+0,i use mfrc522 library for raspberry pi 3 b+ and i have a problem with readblock method.
+0,learn more about quotas and limits in the official docs
+0,"(however the esp could send more with multiple sockets)
+however, i am finding it hard to get something reliable. "
+0,"it will create archive files in the directory ($home/.unison in unix, $userprofile\.unison in windows) to store the structure of the sync directories and make future syncs much quicker. "
+0,"yes, windows.devices.gpio is able to used in unity app running on a raspberry pi. "
+0,"can i install pygame 1.9.1 in my raspberry, running jessie? "
+0,"my lua code
+
+here it is easy for me to send parameters, but when i want to send a request body i cant, i tried to add this code to send the request body
+
+but it is not working and i get this message:
+
+
+
+so can any one provide any help for me please? "
+0,"if ""temporarily allow"" is selected, then scripts are enabled for that site until the browser session is closed. "
+0,"why there is a difference between ubuntu and raspi, i can only guess that the version is not exactly the same. "
+0,"see also:
+ bitwiseoperators "
+0,"documentation:
+
+tutorial - begin with a background of the project, go through installation and start by writing a simple hello, world! "
+0,"), i.e. "
+0,from: url
+0,"there's good documentation on timers you might want to read (beware the headaches, though):
+
+url
+
+here's how to put the arduino to sleep for long delays:
+
+url
+
+hth "
+0,i presume that main of the bootloader is the entry point into software after a reset of the chip.
+0,this is a bug in the ide that happens in connection with the prototype generation.
+0,try a database)
+0,thanks in advance!
+0,but if i try to fetch json data from my web api i am getting errors.
+1,authorization determines whether an identity should be granted access to a specific resource.
+0,a detailed readme is also available on the sourceforge page.
+0,"aesthetically, windows mobile 6 was meant to be similar in design to the then newly released windows vista. "
+0,what do you thing would be the best approach to skip re-doing everything before calling sdl_gl_swapwindow() ?
+1,"the internet content adaptation protocol (icap) is a lightweight http-like protocol used to extend transparent proxy servers that are focused on a specific function (ad insertion, virus scanning, content translation, content filtering, etc.). "
+0,serious problems with this interface are unlikely.
+0,pebl (psychology experiment building language is an open source software program that allows researchers to design and run psychological experiments.
+0,update: based on the feedback i'm posting some code that i've used but is not returning what i need.
+0,"even the above still has a variation on ""the most common novice error i've seen in any context"": while it does use the return value from the read operation, it does not do everything with it that it should. "
+0,"as processors, graphics cards, ram and other components in computers have increased in speed and power consumption, the amount of heat produced by these components as a side-effect of normal operation has also increased. "
+0,"i think you need some c ported modules to control the hardware, but i don't know
+if there is any. "
+0,"quite often, we are more concerned by a change in state of an input than it's value. "
+0,provides a hash table / dictionary implementation that contains wpf resources(e.g.
+0,geofire is a library for storing and querying geographic locations and receiving realtime updates when location data changes.
+0,"for a full analysis of this topic, check out this techrepublic article, this huffington post article, or one of the many other articles comparing the two approaches "
+0,"(also, the spi object was created with parameter.) "
+0,"do not forget to select ""remote machine"" as the debug target to let visual studio deploy and start the application on the iot board."
+0,"you would certainly be making my life easier, and may help others who are getting started with android/bluetooth development. "
+0,the nstextfindbarcontainer protocol provides a container in which the find bar is displayed.
+0,i asked another similar question here but i dont think i asked the correct question.
+0,"if you use the eeprom library, make sure you call or eeprom.end() after you write your data to make sure it's actually stored in the flash. "
+0,butterknife is open sourced under apache 2.0 license.
+0,for questions about azure functions that do operations in an asynchronous manner.
+0,"the font-weight css property, and the font-weight attribute on svg objects specifies the weight (or boldness) of the font being displayed. "
+0,sensu is an open source monitoring framework written in ruby.
+0,"you can actually vote this feature up on uservoice here, as we are using this to help prioritize the upcoming features of the service. "
+0,"some examples are:
+
+ - vba
+exec() - php
+system() - c, ruby
+
+
+related topics
+for other topics related to ""calling"", please use a more specific tag:
+
+phone-call - for making and managing real-time two-way voice communication "
+0,"then you still have things nicely tied together and not just all loosely floating around in global space, but you aren't wasting memory. "
+0,"update 2:
+this is what a problem area looks like up close. "
+0,what i want to do is basically showcase the patterns and colors that i have without having to send the commands individually.
+0,something like the following.
+0,"references:
+
+git hug repository
+q-io "
+0,"like this:
+
+for systems that require an even higher degree of fault tolerance, for instance aerospace applications, triple redundant or triple modular redundant architectures are used. "
+0,there is full guidance available here.
+0,then you can do whatever you want with it.
+0,this maven 2 plugin wraps the jaxb 2.x xjc compiler and provides the capability to generate java sources from schemas.
+0,"textwrangler 4.0 system requirements
+
+mac os x 10.6 or later (10.6.8, 10.7.3 or later recommended)
+intel macs only
+
+what about bbedit lite? "
+0,"toasts are added to an application's windowmanager and are not bound to an activity's ui; therefore, a toast can remain visible after an activity is navigated away from. "
+0,"i have tried executing this node script on an x64 computer, and it appears to work fine. "
+0,consider the tags 'slider' and 'thumbnails' for other meanings of 'thumb'.
+0,also led 13 doesnt light up.
+0,"moreover, the developers can easily manipulate the appearance of the generated barcodes such as background color, bar color, image quality, rotation angle, x-dimension, captions, size, resolution and much more. "
+0,"the execution result is segmentation fault, can you help me please? "
+0,"however, typical android device (virtually every mobile phone) is only equipped with usb device interface, for connecting to pc or another usb host. "
+0,also connect your arduino gnd to the sim800 gnd unless you are sure they share their ground through the power supply.
+0,download and unzip the latest version of control center.
+0,"cordova version 3 introduces:
+light weight core
+cordova 3 introduces a new unified project structure and ships with a very limited api surface. "
+0,"but transitions on x and y axes give a few degrees of difference, depending on the direction. "
+0,"you got several options, for example a bjt is a current amplifier but it complicates the design and needs some background in electrical engineering. "
+0,can this be achieved without having to manually cast everything?
+0,"i have number of deluge packages on my raspberry pi 3
+
+however my torrent server accept only deluge client form version 1.3.12. "
+0,"add the libxml2.2.dylib framework to your project and search paths as described at cocoa with love
+more documentation and short screencast coming soon...
+usage
+see tfhpplehtmltest.m in the hpple project for samples. "
+0,"(169.254.55.233) at a1:cf:c8:c0:a8:a5 on en0 [ethernet]
+? "
+0,i am trying to send some data by an xbee from pc to arduino.
+0,hope it helps you!
+0,thanks in advance
+1,"best to literally say namenode, data{1,2,3}, yarn-rm, and so on
+regarding permissions issues, you could run everything as root, but that's insecure outside a homelab, so you'd want to run a few adduser commands for at least hduser (as documented elsewhere, but can be anything else), and yarn, then run commands as those users, after chown -r the data and log directories to be owned by these users and unix groups they belong to "
+0,the entire project is based on java for high accessibility.
+0,"use
+
+to get the payload printed as hexadecimal characters. "
+0,i get the following warning message which cause the application to crash.
+0,all permissions are still the same.
+0,this way the change only concerns the respective parts of the xml files.
+0,the uisegmentedcontrol object automatically resizes segments to fit proportionally within their superview unless they have a specific width set.
+0,"in order to accept a tcp connection, send ""hello, client! "
+0,"this is what worked for me (vs2017):
+mainpage.xaml
+
+mainpage.xaml.cs
+
+url "
+0,"it works fine if i connect the fan to vcc +5v (64ma) or +3.3v(46ma) but if i connect my fan to a random gpio set as an output, i got just a twitch. "
+0,does however go from preparing to ready state.
+0,edit i gave my computer and pi to my cousin to fix.
+0,i have pi's deployed around the city that i live in.
+0,"you can check this for yourself by altering the code as follows:
+
+you will observe, that, while the data is indeed only printed up to the first zero byte (by the -function), the whole data is present in the lua-string data and you can process it properly with 8-bit-safe (and zerobyte-safe) methods. "
+0,"my /home/pi/kiosk.sh
+
+the service i configured for daemonization (/lib/systemd/system/kiosk.service)
+
+and lastly my /home/pi/.xinitrc
+. "
+0,you would be advised to find the kernel tree into which your soc's changes are integrated and get a tagged version such as 3.2 rather than head.
+0,many other constraints float elsewhere in the diagram and are joined by dotted lines to the roles they apply to.
+0,the site will be deployed on a local computer
+0,"please set a utf-8 locale (e.g., en_us.utf-8) or set pythonioencoding to utf-8. "
+0,same results on both.
+0,or you can add url into additional board manager and update the board.
+0,please read more at: url
+0,you can access these introductory manuals by typing from stata's command prompt.
+0,note that i'm not using digitalwrite because it disables interrupts which might throw the timing off.
+0,openwebkitsharp is a .net wrapper for the webkit browser engine.
+0,"sorry about all these answers, i'm thinking hard about your problem. "
+0,benchmarking is the process of comparing two or more systems or processes under controlled circumstances in order to have a quantitative measure with which to compare or rank them.
+0,"simple datasets can be entered with the edit command, which opens the
+variables editor and allows the user to manually type or paste data. "
+0,or might it be better to learn c?
+0,"if its 1 i a 1, else 0. "
+0,"it should be possible to achieve latencies on the order of a few hundred micro seconds, although obviously the kernel can interrupt your process mid-way if it needs to serve something with a higher priority. "
+0,i try to control two motors via website.
+0,"assuming you can do a non-blocking read on the serial port, you can write a function that reads the serial port, and then schedules itself to be called again after a delay. "
+0,the solution for the producer is to either go to sleep or discard data if the buffer is full.
+0,no problem!
+0,"i wanted to be able to activate the script from a web browser through the site hosted by my pi, so i have /var/wwww/test/lights.php containing this code:
+
+simple, no? "
+0,"the popupextender is part of the ajax control toolkit for asp.net
+
+popupcontrol is an asp.net ajax extender that can be attached to any control in order to open a popup window that displays additional content. "
+0,"if the data is stored or synchronized with a remote database, this can also slow the app and waste the user's data plan while existing android apis allowed for paging in content, they came with significant constraints and drawbacks:
+cursoradapter makes it easier to map database query results to listview items. "
+0,do not use if you're already using a servlet to process the model.
+0,"it can be used as a standalone script, as a plugin for blosxom or movable type, or as a text filter for bbedit. "
+0,you want to execute some offloaded work and you don't need to get result back.
+0,asking for software recommendation is off-topic on stack overflow.
+0,maybe sender address?
+0,"android provides a straightforward xml vocabulary that corresponds to the view classes and subclasses, such as those for widgets and layouts. "
+0,what is paytrail?
+0,"if the database does not exist on the server, the publish operation will create it. "
+0,any changes required in python code to record right channel mono audio?
+0,this means i need to support to ability to plug/unplug the usb connector while the application on the tablet is running.
+0,"that doesn't get into the requirements of the internal logic of alexa/siri/cortana, which i imagine are similarly astronomical. "
+0,"here is the details:
+url
+end of update
+i hope this would help other people that might have the same problem "
+0,but first of all you have to know timers ability and capacity.
+0,maybe i'm doing something wrong?
+0,"it was first released when c++11 was still called c++0x, so it supports switch rather than "
+0,found the bug!
+0,"as a novice coder myself, i'm not sure what i could try next. "
+0,in my system i got an arduino that sends data via i2c to my raspberrypi.
+0,"when i search online for emg sensors, i often see these sensors are just made of a few transistors, resistors and sometimes diodes. "
+1,see the hid usage tables v1.12 document for more information about hid usage values.
+0,is this a memory limitation?
+0,lean more at url
+0,"the current release, pyx 0.14, is available at the download section of the sourceforge project page. "
+0,i wanted to make a system in which we give something to be search onto the terminal of a raspberry pi and the pi gives a voice output.
+0,"i have seen references to using mingw-w64 and/or cmake but before i just start throwing installs at my machine, i'd like some idea of what i should be doing, and why. "
+0,gcsfuse is a user-space file system for interacting with google cloud storage.
+1,"running this jar on the raspy do not cause any problems, it opens the browser and let me authentificate. "
+0,"i've already searched through this site and on google, but i couldn't find anything helping me. "
+0,"i want all files associated to adm/root, so that i can add a read-only samba user to the group adm, so that the logfiles may be copied on a windows system. "
+0,"if you want to follow an in-depth tutorial on how to use another hardware device such as a raspberry pi or intel edison with azure iot hub, then take a look at the collection of iot hub tutorials in the get started folder here. "
+0,this tag is for questions related to the heuristic search algorithm beam search.
+0,etsy is an e-commerce website focused on handmade or vintage items as well as art and craft supplies.
+0,"this is great if you need a quick reaction, but it uses quite a bit of the computers processing power. "
+0,"however, downloads and issue tracking are still handled on drupal.org through the drupal commerce project page. "
+0,"asp.net core is a cross-platform, high-performance, open-source framework for building modern, cloud-based, internet-connected applications. "
+0,doesn't matter if you build large enterprise apps or small restful apis.
+0,"cloud sdk also contains tools and libraries to create and manage app engine, compute engine, cloud storage, cloud sql, and bigquery resources. "
+0,can i send a text in my phone?
+0,"i typed this command suggested by someone:
+ps -ax | grep 'remote_function.py'
+
+and got this response:
+875 ? "
+0,don't even think of using this tag!
+0,"if a period of 100 is required 99
+should be written to the systick reload value register. "
+0,here is the traceback.
+0,the library is simple in design and is meant to take make certain low level tasks that students encounter easier to handle.
+0,bastyen's idea of using a timer is quite good and makes the code much easier.
+0,excitedly i did a port forward on my adsl router and asked friends to connect to see my hello world response.
+0,now i'm using spi full-duplex mode and 2 dma channels for both the transmitter and the receiver.
+0,i am trying to build azure iot sdk for arduino yun on ubuntu 14.04 and getting the following error while running .\build.sh script.
+0,"nobackend is an approach to decouple apps from backends, by abstracting backend tasks with frontend code (dreamcode). "
+0,"im not sure if this takes the load off your pi, but you might as well give it a try. "
+0,"you could, for example, put your sets of widgets in different tkinter frames and show/hide them on demand as you select different radio buttons. "
+0,"now that i think of it, i have built a new version of g++ recently, but i am not using it, continuting to use 4.6.3. "
+0,"but the problem is , how can i debug the program by setting break-points, do i need to use any debugger like stk500 to debug
+any thoughts? "
+0,"html5
+if you can, use html5. "
+0,"cran documentation
+main website "
+0,zen grids is a responsive grid system built with sass.
+0,what makes this pro micro so different from the other micro-controllers i've used?
+0,i have to record my audio in mp3 format because i need it for third-party server that it just accepts mp3 formats.
+0,not sure what the .
+0,"also after my first encounter i started over completely doing fresh install of raspbian, update, upgrade, and installed apache, php and sql because i wasnt sure what was happening behind the scenes. "
+0,"apollo server is a graphql server for express, connect, hapi and koa, written in typescript "
+0,the request is badly formed.
+0,"the visual output from the editor is sent to the devices screen, and the live inputs are sent back to the running project in unity. "
+0,"from the osc home page at the cnmat, uc berkeley
+bringing the benefits of modern networking technology to the world of electronic musical instruments, osc's advantages include interoperability, accuracy, flexibility, and enhanced organization and documentation. "
+0,that opened up the finder inside the arduino application.
+0,"all the how_to's i found regarding that topic suggest the following approach:
+
+but regardless which way i follow, when i get to the make part, i get:
+
+what's the matter? "
+0,one is for transmitting and other recieving.
+0,installation procedure (x86_64 linux):
+0,"i have question in the following link
+url
+a partial text from above link
+
+as expected i got error in this step. "
+0,"i have an arduino which collects temperature data using dht11, the data must be read on an android app using a wifi module (esp8266). "
+0,it appears that i only need to ask the question before i finally find the answer on my own after days of searching.
+0,no need to join mfi program.
+0,any help would be very much appreciated.
+0,"you don't have to use ""actions on google"" stuff described by @ayoub above."
+0,ibm containers helps you build and deploy containers where you can package your apps and services.
+0,"first of all here is arduino sketch:
+
+ok. "
+0,"also, i can run curl fine from the command line on my raspberry pi. "
+0,"here is my code executed when you click the button:
+my decode()-function (based on this tutorial) with jlayer 1.0.1:
+public static byte[] decode(string path, int startms, int maxms)
+throws ioexception {
+bytearrayoutputstream outstream new bytearrayoutputstream(1024);
+float totalms 0;
+boolean seeking true;
+file file new file(path);
+inputstream inputstream new bufferedinputstream(new fileinputstream(file), 8 * 1024);
+try {
+bitstream bitstream new bitstream(inputstream);
+decoder decoder new decoder();
+boolean done false;
+while (! "
+0,the data i want to get from database are configuration parameters for the sensors.
+0,a poset is just a set with a partial order.
+0,"i have a sample sketch like the following, but i can't figure out how to compare the ""readstring"" to process something on the arduino. "
+0,do you have an idea how i can reset this pins for spi usage without restart?
+0,hp business service management is a suite of service management software tools developed and marketed by the hp software division for end-to-end monitoring of services in the data center and the underlying infrastructure.
+0,vb.net can be viewed as an evolution of microsoft's visual basic 6 (vb6) but implemented on the microsoft .net framework.
+0,"so xbee output for i 4 though 11 should look like this:
+
+0,19,162,0,64,121,230,206 (this is the xbee address converted from hex). "
+0,"however, if you have a problem with something else and just happen to be using intellij, please don't use this tag. "
+0,it is a mathematical concept.
+0,"you can use (if you expect text):
+
+or you can work on bytes (look at b before "". "
+0,i am using windows insider build 14342 windows 10 os.
+0,"the code you see is this switch as gui
+
+
+
+main program works
+gpio works
+switch from hw to sw doesn't work well "
+0,"when i run it now, i get a different error. "
+0,in case it is powered just with a battery the servos just rotates ccw or cw very fast and never stop.
+1,"executing pybeacon -i 321654987654321a321654a456b54699 command, for example, and using the google app called ""beacon tools"" to register the eddystone-uid beacon (ok detected into unregistered layer), when i try to register, the app tell me ""failed to connect"". "
+0,"thanks in advance
+i can get the data to print, but i do not know how to tell it to stop. "
+0,"applications created with lightswitch can be deployed as windows desktop applications, in a 3-tiered lan configuration, as web applications hosted on iis 7, or using the microsoft azure platform. "
+0,"resources:
+
+hpcc systems official website. "
+0,precompiles your server-side webpack bundles before running mocha.
+0,the weaveworks/weave-kube image on dockerhub is only built for x64.
+0,the product was originally developed by metrowerks.
+0,"use, e.g. "
+0,"to
+ensure the coordinator starts on a
+good channel and unused pan id, the
+coordinator performs a series of scans
+to discover any rf activity on
+different channels (energy scan) and
+to discover any nearby operating pans
+(pan scan). "
+0,"htmlspecialchars($_post[""data""]) ."
+0,"but i can't get gui
+arduino code give output as 'e' and 'd'. "
+0,one option is to use a soft serial library.
+0,an ajax request is an asynchronous call initiated by the browser that does not directly result in a page transition.
+0,after that i can read it in trigger.
+0,upgrade firefox version to firefox v59.0.2 levels.
+0,"it provides a single data type: the promise, which is a value that will become determined in the future. "
+0,do not confuse this tag with 'pdf': adobe's file format.
+0,10-15 minutes.
+0,i don't see this as much with the raspi b3+ as with the zero h. the last was plug in both monitor and mouse and that for sure fixes the vnc issues but defeats the headless connection.
+0,an is an abstract object that is triggered when a particular event occurs in the application or system.
+0,if you can't connect to the sinkservice from doubletwist after building see this page.
+0,"if you insist, you could go to launchpad and find the package you need, download it and istall it through: "
+0,"conceptually, i have a camera and encoder component. "
+0,"i am trying to execute the at commands in java, i have done it in matlab, but i found it a bit difficult in java. "
+0,"in your web page:
+
+demo
+check the demo here "
+0,finalbuilder is a build and distribution automation product by vsoft technologies.
+0,"this is evident, both with the ""boinccmd --get_tasks"" command which returns two current tasks, and the ""top"" command also shows two boinc threads processes 100%. "
+0,jackson is a java library for handling tasks like reading and writing (parsing / generating) and data binding to/from java objects.
+0,"currently coding the gui, and when i call the countdown, the program takes three pictures before running the countdown, despite me calling countdown() before capturing the pictures. "
+1,"instead of running as a separate service and configuring security, one can just start up an instance of a new localdb runtime as needed. "
+0,try to use your script with php-cli and put this line at the beginning to see what is happening.
+0,"so, if the parameter is a local variable, you shouldn't free the memory. "
+0,"what way is better, or is it just a matter of taste? "
+0,"there is only ever one of these threads, no matter how many callbacks are registered:
+
+[t]he callback functions are run sequentially, not concurrently. "
+0,"this seems consistent with the description in the /boot/overlays/readme file which states:
+name: uart1
+info: enable uart1 in place of uart0
+
+i did find a limited driver for the mini-uart which is fixed at 115200 baud, which seems like a driver to use the mini-uart instead of the full uart. "
+0,serial.read() can be defined anywhere in your loop() function.
+0,"update
+after digging deeper into the problem, it seems like the executables link for some reason against two different versions of qt. "
+0,in order to play 3d sounds you also need to have an audiolistener.
+0,look-up table of a sine wave where the pointer moves according to the phase modulation?
+0,"please note that the use of just /10 to find the tens and %10 to find the ones assumes that number is in [0..99], (which it should be since you asked about [0..64]) "
+0,finally assign the annotation to the annotationview.
+0,"i don't have an username/password kind of thing, nor a ip address and a port. "
+0,here is a code to exemplify the context.
+0,"you tell it what to read or write, and it handles everything for you. "
+0,their updates will appear in your home tab.
+0,"in maven, xcode, gradle, etc. "
+0,i would have to come to each raspberry again and re enter these strings if i am to reinstall it completely.
+0,this solution is tested and working with versions indicated below.
+0,"haml (html abstraction markup language) is an indentation based, terse page description markup. "
+1,"apps have expanded scaling head-room with new compute resources and gain secure, direct access over virtual networks to corporate resources connected via site-to-site or expressroute connections. "
+0,knowing the amount of steps for the wheel to make a full turn gives you a math formula to calculate the distance.
+0,pure is ridiculously tiny.
+0,rsa purchased archer technologies in early 2010 for an undisclosed amount.
+0,i was wondering if someone could help me out?
+0,"my raspberry pi 2 is configured as access point, working with the following settings:
+i'm using the python binding of the libnetfilter_queue library. "
+0,this extremely old qa is rater out of date now.
+0,the question is: is there a way to debug such a giant library fast knowing it's a realtime application ?
+0,you may solve the problem using a capturing group:
+0,"the reason it is not working could be many, i would do the following:
+
+set the execution bit? "
+0,"what i'd like is for the entire buffer captured from my recording callback to be encoded, decoded, and sent back to the playback loop. "
+0,trigonometry is a branch of mathematics that studies triangles and the relationships between their sides and the angles between sides
+0,treeset implements interface navigableset which is a sub-interface of sortedset.
+0,"e/zygote: iswhitelistprocess -
+process is whitelisted 2019-02-07 19:03:46.036 18008-18008/? "
+0,therefore you will have to find an alternative.
+0,"resources
+
+github
+documetation
+npm modules "
+0,thanks.
+0,it then returns the results to your browser.
+0,com1).
+0,too high baud rates will require very exact timing to not miss a single bit and the hardware is not powerful enough to do serial traffic in software without problems.
+1,he goes beyond ssl to establishing trust.
+0,i connected the ble modules to my ftdi cable and set them as master and slave.
+0,"i'd like to be a janitor for the site, and be able to do more to help. "
+0,i believe something like this addresses your 10 second delay issue.
+0,"can not assign to static or instance fields of target program's
+classes and objects. "
+0,klv is an abbreviation for key-length-value.
+0,"where the names of the variables you use are not self-explanatory, please provide comments. "
+0,"i am having trouble sending data with termios libary
+
+on reciving side i get complete garbage. "
+0,"anyway, it seems like i need a bluetooth expert (which i am not) to explain what's going on and why my connection's not working. "
+0,"this is my code:
+
+can anybody tell me why this isn't working? "
+0,asgard has now been deprecated in favor of spinnaker.
+0,"so for example, whenever a button is pressed (that is connected to an arduino for example) the paired cell phone calls a certain person. "
+0,is it possible to read qr code using windows 10 iot?
+0,how can i solve this but nevertheless calculate the difference after that?
+0,any help is appreciated and i'm sure it's something small.
+0,new to esp8266 and nodemcu.
+0,73246 in ns ns-fr.1and1-dns.fr.
+0,"for debug script, first stop asterisk
+after that start it in your console
+and call "
+0,"i wrote aplication based on:
+usb serial for android
+my main application is here: url
+android project is here: url
+if i connect arduino to my computer, and monitor serial port (by arduino ide), it's working (i receive data, and tx led blinks), but when i connect arduino to my phone, only rx led blinks when i open the connection. "
+0,i don't necessarily have access to a router since i'm working of my apartment building's wifi.
+0,"i have a feeling that the section of code in the arduino bit in run_loop(): with the return, in order to have the function not run if it does not hold all of the data. "
+0,"in the same way, we keep any local images that was created in that corresponding fiware lab node. "
+0,there is no justification for it here; it's considered bad programming practice and shouldn't be used unless you know exactly what you're doing.
+0,"or, refer the following changes in linux kernel and device tree. "
+0,"frankly, i haven't the foggiest idea what could suddenly be wrong (the pi is in headed mode, if you were wondering), so i suppose my best course of action would be to publish my code and see if anyone else can replicate the issues. "
+0,i found a library (named: fauxmoesp).
+0,"make an account, copy the example code, and get started with the blynk app! "
+0,if anyone could help me with this that would be much appreciated.
+0,"use
+#include
+#include
+#include
+#include
+#include ""serial_port.h""
+
+void read_serial_port(const char* device_port)
+{
+ int file;
+ struct termios options;
+ char message[100];
+ unsigned int ncountmax 60;
+ bool b;
+
+ file open(device_port, o_rdonly | o_noctty | o_ndelay);
+
+ if(file -1){perror(""unable to open the serial port\n"");}
+ printf(""serial port open successful\n"");
+
+ tcgetattr(file, &options);
+ cfsetispeed(&options, b9600);
+ cfsetospeed(&options, b9600);
+ options.c_cflag (clocal | cread);
+ options.c_cflag parenb; //no parity
+ options.c_cflag parodd;
+ options.c_cflag ~cstopb;
+ options.c_cflag ~csize;
+ options.c_cflag cs8; //8 bits
+ options.c_iflag (inpck | istrip);
+ tcsetattr(file, tcsanow, &options);
+ fcntl(file, f_setfl, fndelay);
+
+ printf(""reading serial port ...\n\n"");
+ b readmessage(file, message, ncountmax);
+ if (b 0){printf(""error while reading serial port\n"");}
+ else printf(""serial port read successful\n"");
+ close(file);
+ printf(""serial port closed\n"");
+};
+
+bool readmessage(int file, char *message, unsigned int ncountmax)
+{
+ int nbchartoread;
+ char data[100];
+ int i;
+
+ if (file 0)
+ {
+ i 0;
+ while (i
+
+/etc/apache2/sites-available/custom-config:
+
+ documentroot /var/www/html/me
+ servername url
+ serveralias mydomain.se
+
+ . "
+0,"here is the python code i am using
+
+here is the arduino code i used "
+0,"first of all sorry for the long title, i hope it is descriptive enough. "
+0,"it is statically-typed, with a syntax loosely derived from c, adding automatic memory management, type safety, some dynamic typing capabilities, additional built-in types such as variable-length arrays and key-value maps, and a large standard library. "
+0,"obviously if notepad was opened with a file, it would have a different title such as test.txt - notepad. "
+0,"when running the script, the loop prints ""now heating..."" and ""now cooling..."" in accordance to temperature changes but the gpio pins don't seem to be following their assigned true/false configurations. "
+0,"i am active mainly in drupal (and related tags) questions, but my activity is not limited to answering; i review low quality posts, and flag posts that need moderation attention. "
+0,"this tag was previously used for the google documents list api, which was sunset in 2015. "
+0,"i'm trying to install the johnny five library for node.js on windows 7 but keep getting an error:
+
+i had the same problem on mac, but solved it by installing xcode command line components as suggested in a previous post, but don't know how to solve this for windows. "
+0,"new to c and arduino programming, my issue, how to split char c into two separate integer variables? "
+0,part of the reason for this is that we dont have a shell like explorer that is there helping control what app is running or providing other services such as sip / osk as is handled on the desktop.
+0,tortoisegit is an open-source windows-based application that allows the git distributed revision control system to be used directly from windows explorer (using context menus).
+0,"google cloud dataproc is a managed hadoop mapreduce, spark, pig and hive service on google cloud platform. "
+0,i was not able to find any way around this sleep issue.
+0,the stackoverflow use of this tag is for questions related to any dialect or superset implementation of modula-2.
+0,an affine transformation is a special type of mapping that preserves parallel lines in a path but does not necessarily preserve lengths or angles.
+0,"with that information i would also like to find the corners of the shape and crop it, but i get an error related to the convexhull function which i have not used in the code. "
+0,"gyro in degrees per seconds, and accelerometer in range 2g "
+1,a guid (globally unique identifier) is a unique reference number used as an identifier in computer software.
+0,"i am trying to get the following basic python script to work on my raspberry pi:
+
+this is, of course, the basic pyaudio example script. "
+0,"i have something like this:
+
+this code is placed in my custom player created as asynctask. "
+0,please help guys......
+0,"the following is what i've been working with thus far:
+
+edit:
+i've added the output from the arduino serial port
+
+adafruit bluefruit at command example
+ ------------------------------------- initialising the bluefruit le module: ok! "
+0,mezzanine is an open source content management platform built using the django framework.
+0,this will cause the calling block to stop and wait for the thread to terminate.
+0,"
+worked for me. "
+0,your client requests and reads it from the server.
+0,"supported browsers:
+
+internet explorer 8+ [1]
+chrome 4+
+safari 4+
+firefox 4+
+opera 9+ [2] "
+0,i have found what seems like a thousand dead ends searching the web.
+0,"this is simply a function created using javascript, css and html so provide the rich ui to user. "
+0,"i basically just want to know how to ""call"" the state of an led."
+0,but pi3 it is not transmitting data on serial port.
+0,"one minor point, in you're removing an event listener from the stage which you never registered for. "
+0,this error message kept coming even when i changed the code.
+0,"here is my code, simplified:
+
+my cursor will not move past the:
+
+line. "
+0,"the arduino accepts strings in the format :data; like:
+
+2,250;
+5,800;
+
+i'm trying to use a python script to send that message when an ""info"" message is received (i.e. "
+0,you can specify the point to use for the center of scaling.
+0,"some important peps are:
+
+pep 0 index of python enhancement proposals
+pep 1 pep purpose and guidelines
+pep 8 style guide for python code
+pep 20 the zen of python
+pep 404 python 2.8 un-release schedule
+
+at a given moment, the status of a pep can be any one of draft, deferred, accepted, rejected, withdrawn, accepted, final or replaced. "
+0,i am currently attempting to use a raspi 3 to connect to a mysql server and send data.
+0,"that is only when the program is ran by cron, not when i call it from the commandline. "
+0,it can also yield the derivatives of any expression.
+0,our modules are currently written in python 2.7 and ds18b20 is written in python 3.3.
+0,for a project i am making a program controlled completely by the number pad.
+0,"zerobrane studio is a lightweight lua ide with code completion, syntax highlighting, remote debugger, code analyzer, live coding, and debugging support for several lua engines. "
+0,i'm newbie for raspberry pi and python coding.
+0,"zbar is an open source software suite for reading bar codes from various sources, such as video streams, image files and raw intensity sensors. "
+0,"do it twice using strtoul(), once for the lower four bytes, once for the rest and add the two results, multiplying the latter by 0x100000000llu beforehand. "
+0,url
+0,"written by siemens, exificient is a java library for for reading and writing exi (efficient xml interchange) files which are binary representations of xml. "
+0,"i am getting them both to execute at the same time but the communication is only happening if i change the state of virtual pin ""v0""."
+1,"the valgrind team doesn't support freebsd at all, and the people who maintain the freebsd port have restricted it to i386 and amd64 because these are the current tier 1 architectures. "
+0,many thanks.
+0,i been working on a project where i had to make a gui that can control cooling modules base off temperature that is set from the user and sensors that are all being controlled by a raspberry pi.
+0,why does buffer have a fill method?
+0,"my only thought now is to scrap mqtt and create a rest server, which i don't want to do as mqtt is a lot faster in my experience.. "
+0,"here's an example:
+both of the devices are now paired, both bluetooth device and arduino. "
+0,so how can i change the tx power of my ble?
+0,"espresso tests state expectations, interactions, and assertions clearly without the distraction of boilerplate content, custom infrastructure, or messy implementation details getting in the way. "
+0,"cool tip
+if you want to shift the pitch of your voice, or make a voice changer app, all you got to do is increase/decrease the value of writeint(output, 44100); // sample rate in your code. "
+0,"example if i say vs esp8266.ping(""google.ca/"") there is a problem."
+0,it was originally developed by altsys but is now owned by fontlab ltd.
+0,is it possible?
+0,"so i recommend creating a own thread for reading the serial port and filling an internal buffer, that get's rendered by the gtk mainthread, if you send an update request:
+url "
+0,gulp-shell is a handy command line interface for gulp developed by sun zheng'an.
+0,"i want to ask about i beacon advertising, especially tx power. "
+0,agatha is a request/response service layer for .net.
+0,i have an arduino sketch that will be working on an arduino uno and i am trying to get uno to communicate over the i2c connection with a raspberry pi.
+0,"after that all i have tested every command with the phantomjs absolute path:
+/usr/local/bin/phantomjs /home/pi/desktop/testjs.js > /home/pi/desktop/testjs.txt
+
+but nothing works... "
+0,outside you can use gps and inside you will have a hard time figuring out the position.
+0,the filetable feature builds on top of sql server filestream technology.
+1,both are configured with samba and both share just fine on my windows 10 machine with the correct user/password combinations.
+0,"you can also try implementing another ibeacon raspberry pi scanning script, written in python, that can be found here. "
+0,"the servo is brand new, i followed this tutorial and set duty cycle values between 0 and 100. "
+0,"i have set up cross-compilation for the rpi, and everything works great. "
+0,another way to do this is with a pointer-to-function based state machine.
+0,"also, pin setup was changed from out as 22 to 4 for the 4th button to solve the continuous on situation. "
+0,"in the client code in the if statement i used
+
+and
+
+as far as i know it must have been due to a variable type thing and they didn't match. "
+0,that made the server timeout while waiting for a second message ...
+0,2.)
+0,it also includes enhancements to the cdi programming model under trial for cdi 1.1.
+0,"but when sending it to my pi, nothing gets sent over the socket. "
+0,you can access this setting by running .
+0,your timing after power-on might be too fast.
+0,two possible mechanisms are as follows.
+0,"so, just for testing i used two led one for temperate( it will stay on for 10 min) sms and another for motion (it will blink once) and commented function call statement i.e. "
+0,the okhttp3 based app still sends no data.
+0,at-least i been able to start working reading this when i started first time.
+0,how can this problem be solved?
+0,object lifetimes are handled by the container instead of by the consuming object.
+0,"windows script files have the extension "".wsf""."
+0,"see wikipedia on:
+
+convex and concave shapes;
+convex sets. "
+0,"note: this guide is only one potential solution, and there are many ways to configure a highly available cluster. "
+0,"roxy can then remotely create, update, and remove those settings from the command line. "
+0,"because the connection is made to the ip, the server does not know what domain name was looked up by the client. "
+0,i've figured out the problem.
+0,i have made a java gui application with netbeans.
+0,but after some time it gives me following error.
+0,"with createml module developers are able to train a model to recognize people's faces, for example, by feeding it lots of images of different faces. "
+0,the latest version of ios 4 is 4.3.5.
+0,"when you call in python, it converts the numpy array to an array of bytes. "
+0,"i know this is an old thread, but i just came by it having my own problems. "
+0,after that i check it manually to see if everything is correct.
+0,however this approach always led to a core panic and reset of the chip.
+0,i am stucked.
+0,problem is controling by keyboard letter.
+0,any help is much appreciated.
+0,"with the new resource manager, you can click on the ""automation script"" and it will build out the arm template that can be used to recreate the resources / settings as needed. "
+1,the google drive api allows you to develop applications that access google drive accounts.
+0,"ical.net is an icalendar (rfc 5545) class library for .net, formerly known as dday.ical and originally developed by douglas day. "
+0,"here is my code:
+main.c:
+
+gpio.h:
+
+gpio.c:
+#include ""gpio.h""
+/* docs: the pi has 54 gpio pins and 6 function selec registers (fsr). "
+0,"personally, i was never able to get it working, as i was trying to send video out the transmitter, and couldn't get the initialization right. "
+0,"if so, the other solution is to read from the sd card 512 bytes each and store them into a buf array with the help of a struct according to that. "
+0,"but when i remove the usb and connect external power to the arduino , the tx and rx on arduino does not work and it just uses the previous distance . "
+0,audit4j is more focussed on business audit events however it also can be used to capture system audit events through extensions.
+0,to further clarify this only seems to affect an instance of visual studio that was previously connected to the device or previously involved in a remote deployment.
+0,"ps: i started learning to program recently, so i hope this might excuse to a degree possible stupid mistakes or missing stuff. "
+0,w/serialinputoutputmanager( 3010): run ending due to exception: error queueing request.
+0,the apache server is running on port 80.
+0,"in a class i have the following enum ad operator overloads, as show in how to use enums as flags in c++?. "
+0,i have a board with an esp8266 chip running micropython firmware v1.8.7.
+0,"i had pretty much the same problem, and i have fixed it by changing the auto-mount settings for my flash drive and that line of code looks something like this:
+
+i'm not shure about that fat because i can't access my raspberry at the moment, but i guess that since you're already using a flash drive you know the right file system to use in your case. "
+0,"however, all instruction sets have some obscure, rarely
+ used instructions. "
+0,"for further references, see the sourceforge site. "
+0,anything i can do to make it work remotely?
+0,webcal was initiated for use with the apple ical application and has become a common de facto standard for accessing icalendar formatted files via webdav.
+0,""", """");
+ } else if (temp 34 && temp < 35)
+ {
+ displaymessage("" room warm! "
+0,"you can install and compile ffmpeg by following the instructions given in this link:
+url
+once it is installed, you can change your code like so:
+
+no need to change any other thing on the raspberry pi side script. "
+0,then do i really have to have three different gprsmodule||mqttclients so i can send three different topics?
+0,"instead, please use [opencv] and [.net] or [c#] tags, and mention the opencv .net/c# wrapper you're working with (e.g. "
+0,"if i try to upload sketch directly i get a timout error,
+if i try to upload sketch via arduino as isp it is the same error. "
+0,wso2 governance registry is an enterprise-ready open-source product for governing soa deployments.
+0,i have been fiddling with the constructor and trying to use references instead of pointers but i couldn't get it to work properly.
+0,for some reason the connection to the icecast drops.
+0,now could you please suggest me which framework to use which do recording changes pitch and can play and most importent which will work on all iphones.
+0,"gy86(hmc5883l,ms5611,mpu6050) and bmp085 or any other i2c module. "
+0,"when you run it from the console, whatever the barcode scanner outputs will go to your program as it is the one currently reading on stdin for the console. "
+0,so i figured out something on this issue.
+0,i'm having problems with avaudiosession using the avaudiorecorder in a cocos2d game that i'm working on.
+0,"beautifully designed
+simple and functional. "
+0,"my question:
+
+why am i not able to handle the stdin and stdout by using the yowsup application and how i can make it work? "
+0,google apps script is a cloud based scripting language for light-weight application development in the google apps platform.
+0,i'm trying to control (enable/disable) the buzzer of my uhf rfid reader (ct-i809) by rs-232 serial port in raspberry pi with python.
+0,"questions not related to programming are off-topic
+
+related tags
+magento-2.0magento2.2magento2.1magento-1.4magento-1.5magento-1.6magento-1.8magento-1.9 "
+0,they must be all connected together for any of this stuff to work.
+0,thanks to its pluggable architecture it can be extended without limits to support more platforms and languages.
+0,"i would also add the compliment to the dtr for the arduino's with avr's using built-in usb, such as the leonoardo, esplora and alike. "
+0,"if you're not scripting for photoshop, then your question belongs on super user, photography, or graphic design. "
+0,hope this helps.
+0,"you probably want to extract as many bytes as possible for use as storage, so a format well-designed for your application will probably help. "
+0,"i get the outputs:
+connect
+startjobnotifications completed for thing: thing-name
+
+but then the program just sits there. "
+0,"introduction
+the vimeo api uses standard http requests to interact with vimeo.com. "
+0,can't seem to find anything newbie-friendly online.
+0,a cartogram is a map where surfaces are proportional to a given statistical variable.
+0,"by just simply trying to compile the code, the following error is given:
+
+well, most of those functions have being declared in the other files in the same folder of the this main code, but, i have tried making a header (.h) to each of the files, just declaring the functions, it didn't work, i have tried including the files as they are, didn't work, tried to change them to .cpp and including, didn't work. "
+0,"it supports some of the most popular instant messaging and telephony protocols such as sip, jabber/xmpp (and hence facebook and google talk), aim, icq, msn, yahoo! "
+0,i'm having difficulties in configuring existing either processing or standard firmata code to be able to forward signal via xbee to another arduino.
+1,the keychain class provides access to private keys and their corresponding certificate chains in credential storage.
+0,"word/_rels/document.xml.rels
+defines an internal identifier and type with all external content items (images, links, etc). "
+0,"i use this command:
+sudo uv4l -f -k --sched-fifo --mem-lock --driver raspicam --auto-video_nr --encoding h264 --width 1080 --height 720 --enable-server on
+i'm able to access this stream on a web browser by looking at the pi's ip address. "
+0,a library is a collection of software functions and/or data prepared so as to be conveniently linked with application programs to form executables.
+0,the video in the window is extremely slow and also the captured file shows only 1 frame for the whole time of video.
+0,glassfish 4.1.1 is a java ee application server
+0,"i have the following class:
+
+then, in my main .py i have:
+
+i get the error:
+ traceback (most recent call last):
+ file ""pythonhelloworld.py"", line 8, in
+ test distancesensor2(gpio_mode, gpio_trigger, gpio_echo)
+ file ""/home/pi/pythonhelloworld/pythonhelloworld/distancesensor2.py"", line 31, in __init__
+ gpio.add_event_detect(self.gpio_echo, gpio.rising, callback set_times)
+ runtimeerror: failed to add edge detection
+
+when i use the code below directly in my main .py, it works. "
+0,"the google play games services sdk provides cross-platform game services that lets you easily integrate popular gaming features such as achievements, leaderboards, and cloud save in your web-based games. "
+0,i'm using an arduino to access the twitter search api 1.1.
+0,some don't support a bootloader at all.
+0,"the open graph viz platform
+gephi is a tool for people that have to explore and understand graphs. "
+0,the qwebview class is the main widget component of the qt webkit web browsing module.
+0,"boot up w/o errors) and flash size and heap size look ok.
+next, if you use a recent nodemcu firmware from the branch you can skip the byte-107-dance because you can set it in lua. "
+0,url
+0,it is a bsd licensed project that brings together a variety of features that allow you to use websockets seamlessly with any django project.
+0,"fwiw i have written a utility that reports the configuration of the pins for one specific soc, but that only reads the registers and never modifies any setting. "
+0,"on out-of-order x86 cpus, only amd recognizes sbb eax, eax as being independent of the old value of eax, and depending only on flags. "
+0,before doing this you would connect your raspberry pi3 with wlan.
+0,sending user data is done via a corresponding xbee api-command which allows to send user-defined data with a maximum payload of 72 bytes.
+1,"on android, linux and osx, you can see all ibeacon transmissions regardless of the proximityuuid, so you have a total of 20 bytes to work with. "
+0,if you would use modern opengl the you could use the format gl_red for the bitmap format and the internal texture image format.
+0,the analog read works on 10 bits from 0 to 1023 (1024 possible values).
+0,"please do not use this tag, this is a misspelled version of . "
+1,first of all it would allow you to keep using your service when you want to replace your key.
+0,"instead, you could move the logic code to within the if(serial.available()>0) statement so that it only gets called when the key is pressed. "
+0,less writing or less instructions.
+0,official site: url
+0,this is the cpanel xmlapi client class.
+0,"you don't need to change your html, and if you are writing a new one, a simple, commonly-used convention can be implemented to quickly translate your pages. "
+0,"joram is shipped with multiples transport implementations: an invm transport implementation for when both the client(s) and server are in the same java virtual machine, and also a tcp based implementation when clients and server are remote. "
+0,"im trying to make system with collects data, stores it to a database and create a wep page that could show the data that ive gathered. "
+0,"it all seems good, but when i reconnect it to my computer (on linux), i can't upload any program. "
+0,"i've tried
+
+but this seems to only work with windows and will return a with linux. "
+0,"url and url
+i don't want the url to change so the post method is suggested with form element using action and name in button. "
+0,the rel attribute specifies the relationship between the current document and the linked document
+0,in the documentation for the sensor it states that the high nibble in the first byte is the checksum (calculated xhigh+xlow+yhigh+ylow+zhigh+zlow) but also the identification of the packet start.
+0,unfortunately because of the library i've got errors .
+0,the robot still misbehave/randomly move after few data is send to the servo.
+0,i hope this will help people in the same (unusual) situation.
+0,that aside i agree with @hlovdal.
+0,"emerald has no ruby (or php, or java, or whatever...) code embeeded at html;
+create independent applications, i.e., the application is not the framework, like it happens in rails;
+help to integrate your development activities with many useful services, like trello, sandcage, github, slack and others;
+be able to deal with many different programming languages. "
+0,i know it's now a bit late but i recently run into this issue.
+0,no configuration is required.
+0,but the motor moves only once.
+0,i have a hex file that is to be flashed onto an atmel chip running on an arduino device.
+0,"in development, it is easy because i tell my server to listen to outside requests and the arduinos ping localhost:3000. "
+0,thanks for reading :d
+0,i would like to avoid using ready-made flight controllers.
+0,(i don't know why the computer takes 20 seconds to restart anyway.
+0,"as the name implies, rapidjson is inspired by rapidxml. "
+0,"home page: url
+the information on codecentral describes the general architecture:
+
+it is a port of the log4j java package to delphi runtime configurable logging with a hierarchy of categories, each individually controllable. "
+1,mhash is a free (under gnu lesser gpl) library which provides a uniform interface to a large number of hash algorithms.
+0,you may wish to rely on status objects in contexts other than logging.
+0,first way.
+0,so far there is no easy way (rpm package).
+0,sidekiq is a background processing framework for ruby.
+0,"but when i run my program i get the the message: ./tes02.sh: not found
+here is the program:
+
+the directory of my script is: /home/pi
+should i enter the directory ? "
+0,you can write native apps in html and javascript with node-webkit.
+0,i hope this is clear.
+0,"examples
+
+references
+
+background-position - w3c specification
+background-position - mdn link "
+0,"resources:
+
+download microsoft speech sdk 5.1. "
+0,but in the general case it starts to become likely at some point that you'll get corrupt data.
+0,qprintpreviewwidget is a qt framework class providing a widget embedding a preview page layouts for printer output.
+0,for an application i'm developing we're working with the genuino 101.
+0,"in the arduino ide, i compile and verify my sketch, and then attempt an upload. "
+0,"those who will face this problem in future, actually my program memory was fine. "
+0,i've done some research and found out about .
+0,"the administrator can create client and site templates, which predetermine resource-allocation parameters for the domains and/or clients. "
+0,use stackframe for questions related to debugging unterminated function calls.
+0,readline will block until a carriage return is received.
+0,my setup works fine as i'm getting correct values on my pi.
+0,i don't know why (abc) won't go low as well.
+0,restxq maps http requests to xquery functions by using a pre-defined set of xquery 3.0 annotations.
+0,create full resources using a single command with migration or from existing database.
+0,i appreciate any help from you..
+0,i mainly need help on the receiving end where the raspberry pi receives the audio but it wold also be good if you gave me some tips about how to code the android app.
+0,is it possible to receive and play a rtsp stream on the raspberry pi using gstreamer1.0 (with omx plugin in order to use hardware acceleration) and resend another rtsp stream with lower resolution and lower fps rate?
+0,object oriented techniques such as mixins (multiple inheritance) can be used to factor code into reusable components.
+0,"edit: if there isn't a way to do c++17 in arduino, then can someone link a tutorial to code arduino boards using c++ "
+0,"at the time of writing, the latest version of pynfc is 0.0.7, which works perfectly with libnfc 1.5.1. "
+0,"every arduino programm needs the functions and loop(), you have neither of them. "
+0,"so in order to deploy mpu6050 sensor as a module, i am stuck up with the following doubts. "
+0,i know this is an old question.
+0,"the seasoned schemer is a book by daniel p. friedman and matthias felleisen, it's the continuation of the little schemer, introducing more advanced concepts of recursive programming to an audience which may have no prior experience with programming or mathematics. "
+0,100 other times.
+0,doing that i also got a connection timeout.
+0,"i want to create a string like the one below-
+""x value(accelerometer), y value(accelerometer),light-sensor value""
+but the problem is i can't get two value arrays from the same sensorevent. "
+0,suitecrm is a crm application written in php and is a fork of the popular sugarcrm community edition project.
+0,what is actually the cmd?
+0,"although you can implement the features equivalent to the thing-if sdk with the kii cloud sdk, it will require a ton of implementations and thus will be very inefficient. "
+0,"on the linux machine, i use the following shell script, that collects the data:
+
+the main problem with this is that the sleep (delay) has to be quite large; if i use sleep 1;, the computer can not receive any data. "
+0,"ignite realtime smack
+developer guide
+javadoc
+
+note: for linux smack (simplified mandatory access control kernel) see linux-smack. "
+0,"this is a good starting point for your arduino uno wifi:
+url
+the next important point is, that you need to use arduino 1.7 (from arduino.org) especially for ota programming. "
+0,the bully algorithm is a method in distributed computing for dynamically electing a coordinator by process id number.
+0,"however, it did not solve my problem. "
+0,long story short: call it from a different thread.
+0,it works well on the matlab environment.
+0,"it does a lot more, but that is the part i'm having trouble with. "
+0,i am working on a project and ideally i would like to start and stop the loop of an arduino with a raspberru pi.
+0,"i have the latest version of openocd installed (0.9.0), i have my bus pirate v4 hardware upgraded to firmware v6.1 r1676 and bootloader v4.4. "
diff --git a/stack_overflow_security_questions_analysis/app.py b/stack_overflow_security_questions_analysis/app.py
new file mode 100644
index 0000000..ee3d2d3
--- /dev/null
+++ b/stack_overflow_security_questions_analysis/app.py
@@ -0,0 +1,48 @@
+import streamlit as st
+import pandas as pd
+import joblib
+import re
+from sklearn.feature_extraction.text import TfidfVectorizer
+
+# Load the dataset
+df = pd.read_csv('IoT-Security-Dataset.csv')
+
+# Load the saved Random Forest model
+rf_model_loaded = joblib.load('random_forest_model.pkl')
+
+# Load and fit the TF-IDF vectorizer on the dataset
+tfidf_vectorizer = TfidfVectorizer(max_features=5000)
+tfidf_vectorizer.fit(df['Cleaned Sentence'])
+
+# Function to preprocess the input text
+def preprocess_text(text):
+ text = text.lower()
+ text = re.sub(r'\W', ' ', text)
+ text = re.sub(r'\d', ' ', text)
+ text = re.sub(r'\s+[a-z]\s+', ' ', text)
+ text = re.sub(r'\s+', ' ', text).strip()
+ return text
+
+# Function to predict if a question is security-related
+def predict_security(question, model, vectorizer):
+ clean_question = preprocess_text(question)
+ question_tfidf = vectorizer.transform([clean_question])
+ prediction = model.predict(question_tfidf)
+ return prediction[0]
+
+# Streamlit app
+st.title("Security text Predictor")
+
+st.write("Enter your question below to determine if it is related to security.")
+
+user_question = st.text_area("Your Question")
+
+if st.button("Predict"):
+ if user_question.strip() != "":
+ prediction = predict_security(user_question, rf_model_loaded, tfidf_vectorizer)
+ if prediction == 0:
+ st.success("This question is security-related.")
+ else:
+ st.info("This question is not security-related.")
+ else:
+ st.error("Please enter a question.")
diff --git a/stack_overflow_security_questions_analysis/images/correlation_matrix.png b/stack_overflow_security_questions_analysis/images/correlation_matrix.png
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diff --git a/stack_overflow_security_questions_analysis/images/tf-idf_score.png b/stack_overflow_security_questions_analysis/images/tf-idf_score.png
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diff --git a/stack_overflow_security_questions_analysis/images/top_20_words.png b/stack_overflow_security_questions_analysis/images/top_20_words.png
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diff --git a/stack_overflow_security_questions_analysis/images/wordcloud.png b/stack_overflow_security_questions_analysis/images/wordcloud.png
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diff --git a/stack_overflow_security_questions_analysis/readme.md b/stack_overflow_security_questions_analysis/readme.md
new file mode 100644
index 0000000..8d09fe2
--- /dev/null
+++ b/stack_overflow_security_questions_analysis/readme.md
@@ -0,0 +1,42 @@
+# Stack Overflow iot security question analysis and predictor
+
+## Models used
+
+- logistic regression
+- Random Forest
+- SVM
+- GBM
+
+## Libraries Used
+
+1. **joblib**: To dowload and laod the model
+2. **plotly**: For plotting zooming and 3d visualizations
+3. **Matplotlib**: For plotting and visualizing the detection results.
+4. **Pandas**: For image manipulation.
+5. **NumPy**: For efficient numerical operations.
+6. **Streamlit** : for building web app gui.
+
+## dowload model from drive
+
+https://drive.google.com/file/d/12h_fU5WI3KQvXH_qG7RoIKnteceb2fLw/view?usp=sharing
+
+## How to Use
+
+1. **Clone the Repository**:
+ ```sh
+ git clone url_to_this_repository
+ ```
+
+2. **Install Dependencies**:
+ ```sh
+ pip install -r requirements.txt
+ ```
+
+3. **Run the Model**:
+ ```python
+ python main.py
+ ```
+
+4. **View Results**: The script will allow you to predict the text or question from stack overflow is security based or not.
+
+
diff --git a/stack_overflow_security_questions_analysis/stack_overflow_iot_security.ipynb b/stack_overflow_security_questions_analysis/stack_overflow_iot_security.ipynb
new file mode 100644
index 0000000..3ecd74e
--- /dev/null
+++ b/stack_overflow_security_questions_analysis/stack_overflow_iot_security.ipynb
@@ -0,0 +1,1965 @@
+{
+ "nbformat": 4,
+ "nbformat_minor": 0,
+ "metadata": {
+ "colab": {
+ "provenance": []
+ },
+ "kernelspec": {
+ "name": "python3",
+ "display_name": "Python 3"
+ },
+ "language_info": {
+ "name": "python"
+ }
+ },
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "id": "fgopYIPj-dR3"
+ },
+ "outputs": [],
+ "source": [
+ "import pandas as pd\n",
+ "import numpy as np\n",
+ "import seaborn as sns\n",
+ "import matplotlib.pyplot as plt\n",
+ "import warnings\n",
+ "warnings.filterwarnings('ignore')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "df = pd.read_csv('/content/IoT-Security-Dataset.csv')"
+ ],
+ "metadata": {
+ "id": "AfPGq2T9-qS1"
+ },
+ "execution_count": 4,
+ "outputs": []
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "df.head()"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 206
+ },
+ "id": "vGahKAcT-6XI",
+ "outputId": "578816a9-2e11-4c96-c9e0-eebbb1f00de9"
+ },
+ "execution_count": 5,
+ "outputs": [
+ {
+ "output_type": "execute_result",
+ "data": {
+ "text/plain": [
+ " PostId Sentence Security \\\n",
+ "0 53090037 It seems that nothing that I do allows buildro... 0 \n",
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+ "2 56452069 So I'm following this custom module guide to d... 0 \n",
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+ " Cleaned Sentence \n",
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+ " 3 \n",
+ " 0 \n",
+ " how can i solve these problems? \n",
+ " \n",
+ " \n",
+ " 4 \n",
+ " 0 \n",
+ " in all cases check out compiler availability (... \n",
+ " \n",
+ " \n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
"
+ ],
+ "image/png": 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\n"
+ },
+ "metadata": {}
+ }
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "# **Random Forest**"
+ ],
+ "metadata": {
+ "id": "tdvFTUQiDAHa"
+ }
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "# Initialize and train Random Forest model\n",
+ "rf_model = RandomForestClassifier()\n",
+ "rf_model.fit(X_train, y_train)\n",
+ "\n",
+ "# Make predictions\n",
+ "rf_y_pred = rf_model.predict(X_test)\n",
+ "\n",
+ "# Evaluate the model\n",
+ "print(\"Random Forest:\")\n",
+ "print(classification_report(y_test, rf_y_pred))\n",
+ "\n",
+ "# Plot confusion matrix\n",
+ "cm = confusion_matrix(y_test, rf_y_pred)\n",
+ "disp = ConfusionMatrixDisplay(confusion_matrix=cm)\n",
+ "disp.plot()\n",
+ "plt.title('Random Forest Confusion Matrix')\n",
+ "plt.show()"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 654
+ },
+ "id": "KZZXkBPsC3Fq",
+ "outputId": "3240b106-3d7d-457f-c721-c953fc3bd8b9"
+ },
+ "execution_count": 27,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "Random Forest:\n",
+ " precision recall f1-score support\n",
+ "\n",
+ " 0 0.99 1.00 1.00 1382\n",
+ " 1 1.00 0.99 1.00 1368\n",
+ "\n",
+ " accuracy 1.00 2750\n",
+ " macro avg 1.00 1.00 1.00 2750\n",
+ "weighted avg 1.00 1.00 1.00 2750\n",
+ "\n"
+ ]
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ ""
+ ],
+ "image/png": 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\n"
+ },
+ "metadata": {}
+ }
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "# **Gradient Boosting Machine**"
+ ],
+ "metadata": {
+ "id": "xbAG_HNjDDuO"
+ }
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "# Initialize and train Gradient Boosting model\n",
+ "gb_model = GradientBoostingClassifier()\n",
+ "gb_model.fit(X_train, y_train)\n",
+ "\n",
+ "# Make predictions\n",
+ "gb_y_pred = gb_model.predict(X_test)\n",
+ "\n",
+ "# Evaluate the model\n",
+ "print(\"Gradient Boosting:\")\n",
+ "print(classification_report(y_test, gb_y_pred))\n",
+ "\n",
+ "# Plot confusion matrix\n",
+ "cm = confusion_matrix(y_test, gb_y_pred)\n",
+ "disp = ConfusionMatrixDisplay(confusion_matrix=cm)\n",
+ "disp.plot()\n",
+ "plt.title('Gradient Boosting Confusion Matrix')\n",
+ "plt.show()\n"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 646
+ },
+ "id": "8y6btTloDHZ2",
+ "outputId": "d95a0375-204b-4adb-eb26-3ed291fa0b24"
+ },
+ "execution_count": 16,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "Gradient Boosting:\n",
+ " precision recall f1-score support\n",
+ "\n",
+ " 0 0.90 0.99 0.94 1382\n",
+ " 1 0.98 0.88 0.93 1368\n",
+ "\n",
+ " accuracy 0.94 2750\n",
+ " macro avg 0.94 0.94 0.94 2750\n",
+ "weighted avg 0.94 0.94 0.94 2750\n",
+ "\n"
+ ]
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ ""
+ ],
+ "image/png": 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\n"
+ },
+ "metadata": {}
+ }
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "# **Support Vector Machine (SVM)**"
+ ],
+ "metadata": {
+ "id": "OBgc831XDLGW"
+ }
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "# Initialize and train SVM model\n",
+ "svm_model = SVC()\n",
+ "svm_model.fit(X_train, y_train)\n",
+ "\n",
+ "# Make predictions\n",
+ "svm_y_pred = svm_model.predict(X_test)\n",
+ "\n",
+ "# Evaluate the model\n",
+ "print(\"Support Vector Machine (SVM):\")\n",
+ "print(classification_report(y_test, svm_y_pred))\n",
+ "\n",
+ "# Plot confusion matrix\n",
+ "cm = confusion_matrix(y_test, svm_y_pred)\n",
+ "disp = ConfusionMatrixDisplay(confusion_matrix=cm)\n",
+ "disp.plot()\n",
+ "plt.title('SVM Confusion Matrix')\n",
+ "plt.show()\n"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 646
+ },
+ "id": "4QFs55DeDPad",
+ "outputId": "58a31e74-2f66-486b-8607-0116c6bc792f"
+ },
+ "execution_count": 17,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "Support Vector Machine (SVM):\n",
+ " precision recall f1-score support\n",
+ "\n",
+ " 0 1.00 1.00 1.00 1382\n",
+ " 1 1.00 1.00 1.00 1368\n",
+ "\n",
+ " accuracy 1.00 2750\n",
+ " macro avg 1.00 1.00 1.00 2750\n",
+ "weighted avg 1.00 1.00 1.00 2750\n",
+ "\n"
+ ]
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ ""
+ ],
+ "image/png": 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\n"
+ },
+ "metadata": {}
+ }
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "# **Model Comparison**"
+ ],
+ "metadata": {
+ "id": "cnj-akpqJt1j"
+ }
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score\n",
+ "\n",
+ "# Dictionary to store the metrics for each model\n",
+ "metrics = {\n",
+ " 'Model': ['Logistic Regression', 'Random Forest', 'Gradient Boosting', 'SVM'],\n",
+ " 'Accuracy': [],\n",
+ " 'Precision': [],\n",
+ " 'Recall': [],\n",
+ " 'F1 Score': []\n",
+ "}\n",
+ "\n",
+ "# Logistic Regression\n",
+ "log_model = LogisticRegression()\n",
+ "log_model.fit(X_train, y_train)\n",
+ "log_y_pred = log_model.predict(X_test)\n",
+ "\n",
+ "metrics['Accuracy'].append(accuracy_score(y_test, log_y_pred))\n",
+ "metrics['Precision'].append(precision_score(y_test, log_y_pred))\n",
+ "metrics['Recall'].append(recall_score(y_test, log_y_pred))\n",
+ "metrics['F1 Score'].append(f1_score(y_test, log_y_pred))\n",
+ "\n",
+ "# Random Forest\n",
+ "rf_model = RandomForestClassifier()\n",
+ "rf_model.fit(X_train, y_train)\n",
+ "rf_y_pred = rf_model.predict(X_test)\n",
+ "\n",
+ "metrics['Accuracy'].append(accuracy_score(y_test, rf_y_pred))\n",
+ "metrics['Precision'].append(precision_score(y_test, rf_y_pred))\n",
+ "metrics['Recall'].append(recall_score(y_test, rf_y_pred))\n",
+ "metrics['F1 Score'].append(f1_score(y_test, rf_y_pred))\n",
+ "\n",
+ "# Gradient Boosting\n",
+ "gb_model = GradientBoostingClassifier()\n",
+ "gb_model.fit(X_train, y_train)\n",
+ "gb_y_pred = gb_model.predict(X_test)\n",
+ "\n",
+ "metrics['Accuracy'].append(accuracy_score(y_test, gb_y_pred))\n",
+ "metrics['Precision'].append(precision_score(y_test, gb_y_pred))\n",
+ "metrics['Recall'].append(recall_score(y_test, gb_y_pred))\n",
+ "metrics['F1 Score'].append(f1_score(y_test, gb_y_pred))\n",
+ "\n",
+ "# Support Vector Machine (SVM)\n",
+ "svm_model = SVC()\n",
+ "svm_model.fit(X_train, y_train)\n",
+ "svm_y_pred = svm_model.predict(X_test)\n",
+ "\n",
+ "metrics['Accuracy'].append(accuracy_score(y_test, svm_y_pred))\n",
+ "metrics['Precision'].append(precision_score(y_test, svm_y_pred))\n",
+ "metrics['Recall'].append(recall_score(y_test, svm_y_pred))\n",
+ "metrics['F1 Score'].append(f1_score(y_test, svm_y_pred))\n",
+ "\n",
+ "# Convert the metrics dictionary to a DataFrame\n",
+ "metrics_df = pd.DataFrame(metrics)\n"
+ ],
+ "metadata": {
+ "id": "cVknDK7dDg2A"
+ },
+ "execution_count": 18,
+ "outputs": []
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "# Set the style\n",
+ "sns.set(style=\"whitegrid\")\n",
+ "\n",
+ "# Plot Accuracy\n",
+ "plt.figure(figsize=(10, 6))\n",
+ "sns.barplot(x='Model', y='Accuracy', data=metrics_df)\n",
+ "plt.title('Accuracy of Different Models')\n",
+ "plt.ylim(0, 1)\n",
+ "plt.show()\n",
+ "\n",
+ "# Plot Precision\n",
+ "plt.figure(figsize=(10, 6))\n",
+ "sns.barplot(x='Model', y='Precision', data=metrics_df)\n",
+ "plt.title('Precision of Different Models')\n",
+ "plt.ylim(0, 1)\n",
+ "plt.show()\n",
+ "\n",
+ "# Plot Recall\n",
+ "plt.figure(figsize=(10, 6))\n",
+ "sns.barplot(x='Model', y='Recall', data=metrics_df)\n",
+ "plt.title('Recall of Different Models')\n",
+ "plt.ylim(0, 1)\n",
+ "plt.show()\n",
+ "\n",
+ "# Plot F1 Score\n",
+ "plt.figure(figsize=(10, 6))\n",
+ "sns.barplot(x='Model', y='F1 Score', data=metrics_df)\n",
+ "plt.title('F1 Score of Different Models')\n",
+ "plt.ylim(0, 1)\n",
+ "plt.show()\n"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 1000
+ },
+ "id": "2C-g7VSIDiz5",
+ "outputId": "a9ec9595-34d1-4f26-a9e8-0d65ca6bd32d"
+ },
+ "execution_count": 19,
+ "outputs": [
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ ""
+ ],
+ "image/png": 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\n"
+ },
+ "metadata": {}
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ ""
+ ],
+ "image/png": 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\n"
+ },
+ "metadata": {}
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ ""
+ ],
+ "image/png": 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\n"
+ },
+ "metadata": {}
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ ""
+ ],
+ "image/png": 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\n"
+ },
+ "metadata": {}
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "from sklearn.metrics import roc_curve, auc\n",
+ "import matplotlib.pyplot as plt\n",
+ "\n",
+ "# Function to plot ROC Curve\n",
+ "def plot_roc_curve(models, X_test, y_test):\n",
+ " plt.figure(figsize=(10, 6))\n",
+ "\n",
+ " for model_name, model in models.items():\n",
+ " if hasattr(model, \"predict_proba\"):\n",
+ " y_pred_proba = model.predict_proba(X_test)[:, 1]\n",
+ " else: # for models without predict_proba\n",
+ " y_pred_proba = model.decision_function(X_test)\n",
+ " y_pred_proba = (y_pred_proba - y_pred_proba.min()) / (y_pred_proba.max() - y_pred_proba.min())\n",
+ "\n",
+ " fpr, tpr, _ = roc_curve(y_test, y_pred_proba)\n",
+ " roc_auc = auc(fpr, tpr)\n",
+ " plt.plot(fpr, tpr, label=f'{model_name} (AUC = {roc_auc:.2f})')\n",
+ "\n",
+ " plt.plot([0, 1], [0, 1], color='navy', linestyle='--')\n",
+ " plt.xlim([0.0, 1.0])\n",
+ " plt.ylim([0.0, 1.05])\n",
+ " plt.xlabel('False Positive Rate')\n",
+ " plt.ylabel('True Positive Rate')\n",
+ " plt.title('Receiver Operating Characteristic (ROC) Curve')\n",
+ " plt.legend(loc=\"lower right\")\n",
+ " plt.show()\n",
+ "\n",
+ "# Define models\n",
+ "models = {\n",
+ " 'Logistic Regression': LogisticRegression(),\n",
+ " 'Random Forest': RandomForestClassifier(),\n",
+ " 'Gradient Boosting': GradientBoostingClassifier(),\n",
+ " 'SVM': SVC(probability=True)\n",
+ "}\n",
+ "\n",
+ "# Train models and plot ROC curves\n",
+ "for model_name, model in models.items():\n",
+ " model.fit(X_train, y_train)\n",
+ "\n",
+ "plot_roc_curve(models, X_test, y_test)\n"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 573
+ },
+ "id": "VHZDcfbrE5TE",
+ "outputId": "221cb6bd-55a4-4faf-8ec3-03c3803b1ac5"
+ },
+ "execution_count": 20,
+ "outputs": [
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ ""
+ ],
+ "image/png": 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\n"
+ },
+ "metadata": {}
+ }
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "# **ANALYSIS**"
+ ],
+ "metadata": {
+ "id": "InW_SBDkIyx6"
+ }
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "from wordcloud import WordCloud\n",
+ "from collections import Counter\n",
+ "# Get the feature names (words) from the TF-IDF vectorizer\n",
+ "words = tfidf.get_feature_names_out()\n",
+ "\n",
+ "# Sum the TF-IDF scores for each word across all documents\n",
+ "word_scores = np.array(X.sum(axis=0)).flatten()\n",
+ "\n",
+ "# Create a DataFrame for word scores\n",
+ "word_scores_df = pd.DataFrame({'word': words, 'score': word_scores})\n",
+ "\n",
+ "# Get the top 20 most frequent words\n",
+ "top_words_df = word_scores_df.sort_values(by='score', ascending=False).head(20)\n",
+ "\n",
+ "# Plot the count plot\n",
+ "plt.figure(figsize=(12, 6))\n",
+ "sns.barplot(x='score', y='word', data=top_words_df, palette=\"viridis\")\n",
+ "plt.title('Most Used Security-Related Words')\n",
+ "plt.xlabel('TF-IDF Score')\n",
+ "plt.ylabel('Word')\n",
+ "plt.show()\n"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 544
+ },
+ "id": "pJ_8cszmIgn4",
+ "outputId": "87290dc0-6881-4f8b-c1a0-3fc410a5baf8"
+ },
+ "execution_count": 22,
+ "outputs": [
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ ""
+ ],
+ "image/png": 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\n"
+ },
+ "metadata": {}
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "# Join all sentences into a single string\n",
+ "all_text = ' '.join(df['Cleaned Sentence'])\n",
+ "\n",
+ "# Create a wordcloud\n",
+ "wordcloud = WordCloud(width=800, height=400, background_color='white').generate(all_text)\n",
+ "\n",
+ "# Plot the wordcloud\n",
+ "plt.figure(figsize=(10, 6))\n",
+ "plt.imshow(wordcloud, interpolation='bilinear')\n",
+ "plt.axis('off')\n",
+ "plt.title('Wordcloud of Cleaned Sentences')\n",
+ "plt.show()\n"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 446
+ },
+ "id": "K61GELmPIlAy",
+ "outputId": "637ecc34-f08c-4f32-9c13-f6a1d044042a"
+ },
+ "execution_count": 23,
+ "outputs": [
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ ""
+ ],
+ "image/png": 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\n"
+ },
+ "metadata": {}
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "# Calculate the length of each sentence\n",
+ "df['Sentence Length'] = df['Cleaned Sentence'].apply(lambda x: len(x.split()))\n",
+ "\n",
+ "# Plot the distribution of sentence lengths\n",
+ "plt.figure(figsize=(12, 6))\n",
+ "sns.histplot(df['Sentence Length'], bins=30, kde=True, color='blue')\n",
+ "plt.title('Distribution of Sentence Lengths')\n",
+ "plt.xlabel('Sentence Length')\n",
+ "plt.ylabel('Frequency')\n",
+ "plt.show()\n"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 563
+ },
+ "id": "ZvMzyY-QIpSE",
+ "outputId": "334d9986-399f-4217-917a-4b9587dfde8b"
+ },
+ "execution_count": 24,
+ "outputs": [
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ ""
+ ],
+ "image/png": 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+ },
+ "metadata": {}
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "# Get the average TF-IDF score for each word\n",
+ "avg_word_scores_df = word_scores_df.copy()\n",
+ "avg_word_scores_df['avg_score'] = avg_word_scores_df['score'] / X.shape[0]\n",
+ "\n",
+ "# Get the top 20 words by average score\n",
+ "top_avg_words_df = avg_word_scores_df.sort_values(by='avg_score', ascending=False).head(20)\n",
+ "\n",
+ "# Plot the bar plot\n",
+ "plt.figure(figsize=(12, 6))\n",
+ "sns.barplot(x='avg_score', y='word', data=top_avg_words_df, palette=\"magma\")\n",
+ "plt.title('Top 20 Words by Average TF-IDF Score')\n",
+ "plt.xlabel('Average TF-IDF Score')\n",
+ "plt.ylabel('Word')\n",
+ "plt.show()"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 544
+ },
+ "id": "RL8C-NzaIr78",
+ "outputId": "6f47a99e-3b1b-4135-8d33-cc85edce4f98"
+ },
+ "execution_count": 25,
+ "outputs": [
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ ""
+ ],
+ "image/png": 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\n"
+ },
+ "metadata": {}
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "# Example: Assuming the dataset has some numerical features\n",
+ "# Add a small random numerical feature for demonstration\n",
+ "df['Random_Feature'] = np.random.rand(len(df))\n",
+ "\n",
+ "# Calculate the correlation matrix\n",
+ "correlation_matrix = df[['Sentence Length', 'Random_Feature', 'Security']].corr()\n",
+ "\n",
+ "# Plot the heatmap\n",
+ "plt.figure(figsize=(10, 8))\n",
+ "sns.heatmap(correlation_matrix, annot=True, cmap='coolwarm', linewidths=0.5)\n",
+ "plt.title('Correlation Matrix Heatmap')\n",
+ "plt.show()"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 704
+ },
+ "id": "A3cG3mWbIuza",
+ "outputId": "e2e12039-5a9e-41ab-992b-c8b27c0f333d"
+ },
+ "execution_count": 26,
+ "outputs": [
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ ""
+ ],
+ "image/png": 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\n"
+ },
+ "metadata": {}
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "import joblib\n",
+ "joblib.dump(rf_model, 'random_forest_model.pkl')"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "5tQhHGPMKLLT",
+ "outputId": "26dd3eea-da71-484e-ab7f-2616631afefb"
+ },
+ "execution_count": 28,
+ "outputs": [
+ {
+ "output_type": "execute_result",
+ "data": {
+ "text/plain": [
+ "['random_forest_model.pkl']"
+ ]
+ },
+ "metadata": {},
+ "execution_count": 28
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "import re\n",
+ "from sklearn.feature_extraction.text import TfidfVectorizer\n",
+ "rf_model_loaded = joblib.load('random_forest_model.pkl')\n",
+ "# Define a function to preprocess the input text\n",
+ "def preprocess_text(text):\n",
+ " # Convert to lowercase\n",
+ " text = text.lower()\n",
+ " # Remove special characters and numbers\n",
+ " text = re.sub(r'\\W', ' ', text)\n",
+ " text = re.sub(r'\\d', ' ', text)\n",
+ " # Remove single characters\n",
+ " text = re.sub(r'\\s+[a-z]\\s+', ' ', text)\n",
+ " # Remove extra spaces\n",
+ " text = re.sub(r'\\s+', ' ', text).strip()\n",
+ " return text\n",
+ "\n",
+ "# Define a function to predict if a question is security-related\n",
+ "def predict_security(question, model, vectorizer):\n",
+ " # Preprocess the question\n",
+ " clean_question = preprocess_text(question)\n",
+ " # Transform the question using the vectorizer\n",
+ " question_tfidf = vectorizer.transform([clean_question])\n",
+ " # Make the prediction\n",
+ " prediction = model.predict(question_tfidf)\n",
+ " return prediction[0]\n",
+ "\n",
+ "# Load the TF-IDF vectorizer (it should be saved during model training)\n",
+ "tfidf_vectorizer = TfidfVectorizer(max_features=5000)\n",
+ "tfidf_vectorizer.fit(df['Cleaned Sentence'])\n",
+ "\n",
+ "# Example usage\n",
+ "user_question = \"How to secure apps and webs from cyber attack using Iot ?\"\n",
+ "prediction = predict_security(user_question, rf_model_loaded, tfidf_vectorizer)\n",
+ "print(\"Prediction (0 for security-related, 1 for not):\", prediction)\n"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "nGYCm41uKNr3",
+ "outputId": "53ebeb4e-186b-4873-ddac-4261160ab8d8"
+ },
+ "execution_count": 31,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "Prediction (0 for security-related, 1 for not): 0\n"
+ ]
+ }
+ ]
+ }
+ ]
+}
\ No newline at end of file
diff --git a/stack_overflow_security_questions_analysis/webapp.mp4 b/stack_overflow_security_questions_analysis/webapp.mp4
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