This presentation illustrates how we can extract data from twitter with R programming language that can be any tweets i.e. sarcastic tweets, today's most prevalent tweets etc...
This document provides an overview of analyzing social media data from Twitter using R. It discusses the following:
- Introduction to the Twitter APIs, including the Stream and REST APIs and how they are used to capture live and archived Twitter data.
- The process for authenticating with the Twitter APIs using authentication keys and accessing Twitter data through API calls in R.
- Examples of capturing Twitter user data through API calls, including timelines, followers, locations.
- Integrating other APIs like Google Maps to visualize Twitter data on maps.
- Performing analysis on Twitter data like sentiment analysis using word clouds and visualizing trends over time through diagrams.
The document discusses Twitter's data APIs, including the Streaming API which provides a 1% sample of all tweets or tracks keywords in real-time, and the REST API which accesses past tweet data. It recommends creating a Twitter app, using optimized calls to the REST API to avoid errors, and leveraging open source libraries rather than re-inventing the wheel.
Tweepy is an open source Python package that gives you a very convenient way to access the Twitter API with Python. Tweepy includes a set of classes and methods that represent Twitter's models and API endpoints, and it transparently handles various implementation details, such as: Data encoding and decoding.
Five steps to get tweets sent by a list of usersWeiai Wayne Xu
In this episode of Python tutorial, we teach you how to gather tweets sent by a list of Twitter users. Download the script at https://drive.google.com/file/d/0Bwwg6GLCW_IPVmNBMUV4bVhUU0U/edit?usp=sharing
How to get data from twitter (by hnnrrhm)Hani Nurrahmi
This document discusses how to get data from Twitter using their API. It explains that Twitter provides an API that allows developers to access Twitter data programmatically. It then outlines the steps to get Twitter API access keys, including registering a developer application on their website. Finally, it provides a code example in PHP of how to connect to the Twitter API using a PHP wrapper library, make a request to get a user's timeline, and output the tweets.
Openpicus Flyport interfaces the cloud servicesIonela
This document provides an overview of using ThingSpeak and parse libraries with an Openpicus Flyport device. It describes creating a public ThingSpeak channel to store sensor data from the Flyport's analog and digital inputs. The document also explains how to use the ThingSpeak APIs to post to Twitter and call external web APIs, retrieving Rome's temperature from Google Weather. Finally, it summarizes the Flyport firmware code for writing data to the channel and calling the ThingSpeak APIs.
This document provides an overview of analyzing social media data from Twitter using R. It discusses the following:
- Introduction to the Twitter APIs, including the Stream and REST APIs and how they are used to capture live and archived Twitter data.
- The process for authenticating with the Twitter APIs using authentication keys and accessing Twitter data through API calls in R.
- Examples of capturing Twitter user data through API calls, including timelines, followers, locations.
- Integrating other APIs like Google Maps to visualize Twitter data on maps.
- Performing analysis on Twitter data like sentiment analysis using word clouds and visualizing trends over time through diagrams.
The document discusses Twitter's data APIs, including the Streaming API which provides a 1% sample of all tweets or tracks keywords in real-time, and the REST API which accesses past tweet data. It recommends creating a Twitter app, using optimized calls to the REST API to avoid errors, and leveraging open source libraries rather than re-inventing the wheel.
Tweepy is an open source Python package that gives you a very convenient way to access the Twitter API with Python. Tweepy includes a set of classes and methods that represent Twitter's models and API endpoints, and it transparently handles various implementation details, such as: Data encoding and decoding.
Five steps to get tweets sent by a list of usersWeiai Wayne Xu
In this episode of Python tutorial, we teach you how to gather tweets sent by a list of Twitter users. Download the script at https://drive.google.com/file/d/0Bwwg6GLCW_IPVmNBMUV4bVhUU0U/edit?usp=sharing
How to get data from twitter (by hnnrrhm)Hani Nurrahmi
This document discusses how to get data from Twitter using their API. It explains that Twitter provides an API that allows developers to access Twitter data programmatically. It then outlines the steps to get Twitter API access keys, including registering a developer application on their website. Finally, it provides a code example in PHP of how to connect to the Twitter API using a PHP wrapper library, make a request to get a user's timeline, and output the tweets.
Openpicus Flyport interfaces the cloud servicesIonela
This document provides an overview of using ThingSpeak and parse libraries with an Openpicus Flyport device. It describes creating a public ThingSpeak channel to store sensor data from the Flyport's analog and digital inputs. The document also explains how to use the ThingSpeak APIs to post to Twitter and call external web APIs, retrieving Rome's temperature from Google Weather. Finally, it summarizes the Flyport firmware code for writing data to the channel and calling the ThingSpeak APIs.
Why "Hello World" is a Massive Operation - From Python code to Stack Virtual ...Richard Rowland
Presented at PyCascades 2023.
What happens on the computer when you run print(“Hello world”)? This talk attempts to dissect how Python code gets translated for execution. While many programmers can live without interacting with compiler internals, a stronger understanding of CPython can help make us better programmers.
This document describes a Twitter analysis project performed in RStudio using R programming. The analysis included collecting tweets containing the hashtag "#Kejriwal", performing sentiment analysis to score the tweets as positive, negative or neutral, and visualizing the results. Text mining was also conducted on the tweets. The sentiment analysis found most tweets had a negative sentiment towards Kejriwal, while text mining showed the most common words in tweets were "Kejriwal", "power", "cut" and "Modi".
Ikai Lan gave a talk about building cloud applications using Google App Engine. They demonstrated TweetEngine, an open source Twitter application built on App Engine, to explain key concepts. These included OAuth for secure authentication, internationalization (i18n) for localized versions, AppStats for application profiling, and Task Queues for background processing. The talk aimed to show how App Engine handles infrastructure concerns so developers can focus on code, and whet the audience's appetite for building cloud applications.
This document provides an overview of exploring art through RESTful APIs. It discusses what APIs are and how they allow communication between systems. It then covers querying two museum APIs - the Metropolitan Museum API and the Cooper Hewitt API. It demonstrates how to authenticate, make requests, and handle responses for each API. Key learnings include understanding authentication strategies like API keys and OAuth tokens, as well as common HTTP status codes.
Curiosity Bits Tutorial: Mining Twitter User Profile on Python V2Weiai Wayne Xu
This document provides instructions for mining Twitter user profile data using Python. It discusses setting up API keys, installing necessary Python libraries like Twython and SQLite, creating a list of Twitter screennames, setting up a SQLite database to store Twitter data, and analyzing the Python code to extract and store Twitter user profile information from the Twitter API based on the screenname list. The code extracts profile fields like screenname, followers count, location, bio and stores it in the SQLite database. Rate limits from the Twitter API require running the code multiple times to get all user profile data.
This article is about using Serverless platform OpenWhisk. The example shows how to do auto retweeting in Python to illustrate an application of serverless approach. Originally published in October 2017 edition of Open Source For You magazine - shared under CC BY SA-3.0 License.
This content shows how to get Twitter geo-located data using QGIS (1. Installation of QGIS and Plugin 2. Twitter API application, and 3. Example of getting data from Twitter API).
Twet is a search tool that combines results from Twitter and Flickr. It searches for tweets and photos related to a search term. It uses WordNet to include synonyms in the search. Search results include tweets displayed on a Yahoo Maps overlay and relevant Flickr photos. The Twet application and Twet-Twitter and Twet-WordNet services work together to provide this mashup of social media search results.
ASFWS 2013 Rump Session - Abusing Twitter API One year later… Nicolas SeriotCyber Security Alliance
This document summarizes Nicolas Seriot's presentation on abusing the Twitter API. It discusses how consumer secrets that control third-party clients can be easily extracted, leading to API abuses, denial of service attacks, and session fixation attacks. It provides examples of how extracted consumer secrets can be used to make unlimited requests to exhaust API limits and perform denial of service attacks against applications. The document warns that leaked consumer secrets can have serious security consequences.
Mining Social Web APIs with IPython Notebook (PyCon 2014)Matthew Russell
From the tutorial description at https://us.pycon.org/2014/schedule/presentation/134/ -
Description
Social websites such as Twitter, Facebook, LinkedIn, Google+, and GitHub have vast amounts of valuable insights lurking just beneath the surface, and this workshop minimizes the barriers to exploring and mining this valuable data by presenting turn-key examples from the thoroughly revised 2nd Edition of Mining the Social Web.
Abstract
This workshop teaches you fundamental data mining techniques as applied to popular social websites by adapting example code from Mining the Social Web (2nd Edition, O'Reilly 2013) in a tutorial-style step-by-step manner that is designed specifically to accommodate attendees with very little programming or domain experience. This workshop's extensive use of IPython Notebook facilitates interactive learning with turn-key examples against a Vagrant-based virtual machine that takes care of installing all 3rd party dependencies that are needed. The barriers to entry are truly minimal, which allows maximal use of the time to be spent on interactive learning.
The workshop is somewhat broadly designed and acclimates you to mining social data from Twitter, Facebook, LinkedIn, Google+, and GitHub APIs in five corresponding modules with the following memorable approach for each of them:
* Aspire - Set out to answer a question or test a hypothesis as part of a data science experiment
* Acquire - Collect and store the data that you need to answer the question or test the hypothesis
* Analyze - Use fundamental data mining techniques to explore and exploit the data
* Summarize - Present analytical findings in a compact and meaningful way
Each module consists of a brief period in which each attendee will customize the corresponding notebook for the module with their own account credentials with the remainder of the module devoted to learning what data is available from the API and exercises demonstrating analysis of the data—all from a pre-populated IPython Notebook. Time will be set aside at the end of each module for attendees to hack on the code, discuss examples, and ask any lingering questions.
Embedded Tweets, Timelines and Twitter Cards - Social Developers London 09 Ja...Angus Fox
This document summarizes Angus Fox's talk on building with Twitter APIs. It provides information on embedding timelines and tweets, implementing Twitter cards, and retiring deprecated APIs. The talk demonstrates how to generate embed codes to display tweets and timelines on other sites and add metadata to pages to create Twitter cards that enrich tweets linking to those pages. It also notes upcoming changes to Twitter APIs.
This document provides an overview of the Python programming language, including its history, features, applications, and how to get started with Python. It discusses that Python was created by Guido van Rossum in 1991 and is an easy to learn, interpreted, high-level programming language that supports object-oriented programming. The document also outlines where Python can be learned, popular Python IDEs like IDLE and PyCharm, and gives examples of using basic Python constructs and Tkinter for GUI applications.
This document provides instructions for building a basic Twitter bot using Python. It outlines setting up a Twitter developer account to get API keys, installing Python and relevant libraries like Tweepy, and writing a Python script to search for tweets containing a phrase and reply to each with a predefined message. The goal is to create a functional Twitter bot as an educational project without needing advanced Python knowledge. Various Python concepts used in the bot like dictionaries, functions, loops, and exception handling are also explained.
So, you heard "the Web is Programmable, Internet of Things, Digitalization", but have NO to little programming skills. Nevertheless, this is 2016, and you want to get enough about Web Programming to be part of the some fun and exciting Web challenge, participate in an Hackathon may be …
Well, I am happy we meet. I suggest you take the tour “from ZERO to REST in a hour”: we’ll teach you to forge your own HTTP requests against the Github API. After this tour, you’ll know enough to interact with any RESTful Web APIs. Worth mentionning this presentation is entirely scripted: so give attention to each slide comments.
Did you enjoy the tour ? look forward to learn more ?
Post your comments below about enhancements, and for any subjects you’d like to see covered.
2. Join the Cisco developers community : https://developer.cisco.com/
3. Take a free online Coding Lab (REST, Python, Parsing JSON, RAML, Git…)
https://learninglabs.cisco.com/labs/tags/Coding
4. Meet DevNet teams at a physical event: conferences, hackathons
https://developer.cisco.com/site/devnet/events-contests/events/
API Documentation Workshop tcworld India 2015Tom Johnson
This is a workshop I gave on API documentation at tcworld India 2015. The workshop covers 3 main areas:
- General overview of API documentation
- Deep dive into REST API documentation
- Deep dive into Javadoc documentation
The document provides instructions for collecting Twitter data using Python. It outlines 5 steps: 1) Set up Twitter API keys, 2) Prepare a list of Twitter handles in a CSV file, 3) Create a SQLite database and import the Twitter handle list, 4) Install required Python libraries, and 5) Modify and run a Python script to retrieve tweets and store results in the SQLite database. The document also discusses Twitter API rate limits and provides a similar process for searching and storing tweets by keywords.
ASFWS 2012 - Contourner les conditions d’utilisation et l’API du service Twit...Cyber Security Alliance
The document discusses abusing the Twitter API by ripping consumer tokens from official Twitter clients on iOS and OS X, which allows accessing a user's Twitter account without their authorization since the tokens can be extracted from the applications. It argues that OAuth is not effective at preventing this on desktop platforms since consumer tokens cannot be reliably kept secret. The document also questions Twitter's motivations for pushing developers towards OAuth, speculating it has more to do with controlling third-party clients than security concerns.
The document provides instructions for collecting Twitter data using Python by having users set up Twitter API keys, prepare a list of Twitter handles in a CSV file, create a SQLite database to store the Twitter data, install necessary Python libraries, modify a Python script to retrieve tweets from the Twitter handles list, and run the script to collect and save the Twitter data in the SQLite database. The results obtained will include various metadata for each tweet such as the language, retweets, user details, hashtags, URLs, and more.
Applications of artificial Intelligence in Mechanical Engineering.pdfAtif Razi
Historically, mechanical engineering has relied heavily on human expertise and empirical methods to solve complex problems. With the introduction of computer-aided design (CAD) and finite element analysis (FEA), the field took its first steps towards digitization. These tools allowed engineers to simulate and analyze mechanical systems with greater accuracy and efficiency. However, the sheer volume of data generated by modern engineering systems and the increasing complexity of these systems have necessitated more advanced analytical tools, paving the way for AI.
AI offers the capability to process vast amounts of data, identify patterns, and make predictions with a level of speed and accuracy unattainable by traditional methods. This has profound implications for mechanical engineering, enabling more efficient design processes, predictive maintenance strategies, and optimized manufacturing operations. AI-driven tools can learn from historical data, adapt to new information, and continuously improve their performance, making them invaluable in tackling the multifaceted challenges of modern mechanical engineering.
Why "Hello World" is a Massive Operation - From Python code to Stack Virtual ...Richard Rowland
Presented at PyCascades 2023.
What happens on the computer when you run print(“Hello world”)? This talk attempts to dissect how Python code gets translated for execution. While many programmers can live without interacting with compiler internals, a stronger understanding of CPython can help make us better programmers.
This document describes a Twitter analysis project performed in RStudio using R programming. The analysis included collecting tweets containing the hashtag "#Kejriwal", performing sentiment analysis to score the tweets as positive, negative or neutral, and visualizing the results. Text mining was also conducted on the tweets. The sentiment analysis found most tweets had a negative sentiment towards Kejriwal, while text mining showed the most common words in tweets were "Kejriwal", "power", "cut" and "Modi".
Ikai Lan gave a talk about building cloud applications using Google App Engine. They demonstrated TweetEngine, an open source Twitter application built on App Engine, to explain key concepts. These included OAuth for secure authentication, internationalization (i18n) for localized versions, AppStats for application profiling, and Task Queues for background processing. The talk aimed to show how App Engine handles infrastructure concerns so developers can focus on code, and whet the audience's appetite for building cloud applications.
This document provides an overview of exploring art through RESTful APIs. It discusses what APIs are and how they allow communication between systems. It then covers querying two museum APIs - the Metropolitan Museum API and the Cooper Hewitt API. It demonstrates how to authenticate, make requests, and handle responses for each API. Key learnings include understanding authentication strategies like API keys and OAuth tokens, as well as common HTTP status codes.
Curiosity Bits Tutorial: Mining Twitter User Profile on Python V2Weiai Wayne Xu
This document provides instructions for mining Twitter user profile data using Python. It discusses setting up API keys, installing necessary Python libraries like Twython and SQLite, creating a list of Twitter screennames, setting up a SQLite database to store Twitter data, and analyzing the Python code to extract and store Twitter user profile information from the Twitter API based on the screenname list. The code extracts profile fields like screenname, followers count, location, bio and stores it in the SQLite database. Rate limits from the Twitter API require running the code multiple times to get all user profile data.
This article is about using Serverless platform OpenWhisk. The example shows how to do auto retweeting in Python to illustrate an application of serverless approach. Originally published in October 2017 edition of Open Source For You magazine - shared under CC BY SA-3.0 License.
This content shows how to get Twitter geo-located data using QGIS (1. Installation of QGIS and Plugin 2. Twitter API application, and 3. Example of getting data from Twitter API).
Twet is a search tool that combines results from Twitter and Flickr. It searches for tweets and photos related to a search term. It uses WordNet to include synonyms in the search. Search results include tweets displayed on a Yahoo Maps overlay and relevant Flickr photos. The Twet application and Twet-Twitter and Twet-WordNet services work together to provide this mashup of social media search results.
ASFWS 2013 Rump Session - Abusing Twitter API One year later… Nicolas SeriotCyber Security Alliance
This document summarizes Nicolas Seriot's presentation on abusing the Twitter API. It discusses how consumer secrets that control third-party clients can be easily extracted, leading to API abuses, denial of service attacks, and session fixation attacks. It provides examples of how extracted consumer secrets can be used to make unlimited requests to exhaust API limits and perform denial of service attacks against applications. The document warns that leaked consumer secrets can have serious security consequences.
Mining Social Web APIs with IPython Notebook (PyCon 2014)Matthew Russell
From the tutorial description at https://us.pycon.org/2014/schedule/presentation/134/ -
Description
Social websites such as Twitter, Facebook, LinkedIn, Google+, and GitHub have vast amounts of valuable insights lurking just beneath the surface, and this workshop minimizes the barriers to exploring and mining this valuable data by presenting turn-key examples from the thoroughly revised 2nd Edition of Mining the Social Web.
Abstract
This workshop teaches you fundamental data mining techniques as applied to popular social websites by adapting example code from Mining the Social Web (2nd Edition, O'Reilly 2013) in a tutorial-style step-by-step manner that is designed specifically to accommodate attendees with very little programming or domain experience. This workshop's extensive use of IPython Notebook facilitates interactive learning with turn-key examples against a Vagrant-based virtual machine that takes care of installing all 3rd party dependencies that are needed. The barriers to entry are truly minimal, which allows maximal use of the time to be spent on interactive learning.
The workshop is somewhat broadly designed and acclimates you to mining social data from Twitter, Facebook, LinkedIn, Google+, and GitHub APIs in five corresponding modules with the following memorable approach for each of them:
* Aspire - Set out to answer a question or test a hypothesis as part of a data science experiment
* Acquire - Collect and store the data that you need to answer the question or test the hypothesis
* Analyze - Use fundamental data mining techniques to explore and exploit the data
* Summarize - Present analytical findings in a compact and meaningful way
Each module consists of a brief period in which each attendee will customize the corresponding notebook for the module with their own account credentials with the remainder of the module devoted to learning what data is available from the API and exercises demonstrating analysis of the data—all from a pre-populated IPython Notebook. Time will be set aside at the end of each module for attendees to hack on the code, discuss examples, and ask any lingering questions.
Embedded Tweets, Timelines and Twitter Cards - Social Developers London 09 Ja...Angus Fox
This document summarizes Angus Fox's talk on building with Twitter APIs. It provides information on embedding timelines and tweets, implementing Twitter cards, and retiring deprecated APIs. The talk demonstrates how to generate embed codes to display tweets and timelines on other sites and add metadata to pages to create Twitter cards that enrich tweets linking to those pages. It also notes upcoming changes to Twitter APIs.
This document provides an overview of the Python programming language, including its history, features, applications, and how to get started with Python. It discusses that Python was created by Guido van Rossum in 1991 and is an easy to learn, interpreted, high-level programming language that supports object-oriented programming. The document also outlines where Python can be learned, popular Python IDEs like IDLE and PyCharm, and gives examples of using basic Python constructs and Tkinter for GUI applications.
This document provides instructions for building a basic Twitter bot using Python. It outlines setting up a Twitter developer account to get API keys, installing Python and relevant libraries like Tweepy, and writing a Python script to search for tweets containing a phrase and reply to each with a predefined message. The goal is to create a functional Twitter bot as an educational project without needing advanced Python knowledge. Various Python concepts used in the bot like dictionaries, functions, loops, and exception handling are also explained.
So, you heard "the Web is Programmable, Internet of Things, Digitalization", but have NO to little programming skills. Nevertheless, this is 2016, and you want to get enough about Web Programming to be part of the some fun and exciting Web challenge, participate in an Hackathon may be …
Well, I am happy we meet. I suggest you take the tour “from ZERO to REST in a hour”: we’ll teach you to forge your own HTTP requests against the Github API. After this tour, you’ll know enough to interact with any RESTful Web APIs. Worth mentionning this presentation is entirely scripted: so give attention to each slide comments.
Did you enjoy the tour ? look forward to learn more ?
Post your comments below about enhancements, and for any subjects you’d like to see covered.
2. Join the Cisco developers community : https://developer.cisco.com/
3. Take a free online Coding Lab (REST, Python, Parsing JSON, RAML, Git…)
https://learninglabs.cisco.com/labs/tags/Coding
4. Meet DevNet teams at a physical event: conferences, hackathons
https://developer.cisco.com/site/devnet/events-contests/events/
API Documentation Workshop tcworld India 2015Tom Johnson
This is a workshop I gave on API documentation at tcworld India 2015. The workshop covers 3 main areas:
- General overview of API documentation
- Deep dive into REST API documentation
- Deep dive into Javadoc documentation
The document provides instructions for collecting Twitter data using Python. It outlines 5 steps: 1) Set up Twitter API keys, 2) Prepare a list of Twitter handles in a CSV file, 3) Create a SQLite database and import the Twitter handle list, 4) Install required Python libraries, and 5) Modify and run a Python script to retrieve tweets and store results in the SQLite database. The document also discusses Twitter API rate limits and provides a similar process for searching and storing tweets by keywords.
ASFWS 2012 - Contourner les conditions d’utilisation et l’API du service Twit...Cyber Security Alliance
The document discusses abusing the Twitter API by ripping consumer tokens from official Twitter clients on iOS and OS X, which allows accessing a user's Twitter account without their authorization since the tokens can be extracted from the applications. It argues that OAuth is not effective at preventing this on desktop platforms since consumer tokens cannot be reliably kept secret. The document also questions Twitter's motivations for pushing developers towards OAuth, speculating it has more to do with controlling third-party clients than security concerns.
The document provides instructions for collecting Twitter data using Python by having users set up Twitter API keys, prepare a list of Twitter handles in a CSV file, create a SQLite database to store the Twitter data, install necessary Python libraries, modify a Python script to retrieve tweets from the Twitter handles list, and run the script to collect and save the Twitter data in the SQLite database. The results obtained will include various metadata for each tweet such as the language, retweets, user details, hashtags, URLs, and more.
Applications of artificial Intelligence in Mechanical Engineering.pdfAtif Razi
Historically, mechanical engineering has relied heavily on human expertise and empirical methods to solve complex problems. With the introduction of computer-aided design (CAD) and finite element analysis (FEA), the field took its first steps towards digitization. These tools allowed engineers to simulate and analyze mechanical systems with greater accuracy and efficiency. However, the sheer volume of data generated by modern engineering systems and the increasing complexity of these systems have necessitated more advanced analytical tools, paving the way for AI.
AI offers the capability to process vast amounts of data, identify patterns, and make predictions with a level of speed and accuracy unattainable by traditional methods. This has profound implications for mechanical engineering, enabling more efficient design processes, predictive maintenance strategies, and optimized manufacturing operations. AI-driven tools can learn from historical data, adapt to new information, and continuously improve their performance, making them invaluable in tackling the multifaceted challenges of modern mechanical engineering.
Sri Guru Hargobind Ji - Bandi Chor Guru.pdfBalvir Singh
Sri Guru Hargobind Ji (19 June 1595 - 3 March 1644) is revered as the Sixth Nanak.
• On 25 May 1606 Guru Arjan nominated his son Sri Hargobind Ji as his successor. Shortly
afterwards, Guru Arjan was arrested, tortured and killed by order of the Mogul Emperor
Jahangir.
• Guru Hargobind's succession ceremony took place on 24 June 1606. He was barely
eleven years old when he became 6th Guru.
• As ordered by Guru Arjan Dev Ji, he put on two swords, one indicated his spiritual
authority (PIRI) and the other, his temporal authority (MIRI). He thus for the first time
initiated military tradition in the Sikh faith to resist religious persecution, protect
people’s freedom and independence to practice religion by choice. He transformed
Sikhs to be Saints and Soldier.
• He had a long tenure as Guru, lasting 37 years, 9 months and 3 days
This study Examines the Effectiveness of Talent Procurement through the Imple...DharmaBanothu
In the world with high technology and fast
forward mindset recruiters are walking/showing interest
towards E-Recruitment. Present most of the HRs of
many companies are choosing E-Recruitment as the best
choice for recruitment. E-Recruitment is being done
through many online platforms like Linkedin, Naukri,
Instagram , Facebook etc. Now with high technology E-
Recruitment has gone through next level by using
Artificial Intelligence too.
Key Words : Talent Management, Talent Acquisition , E-
Recruitment , Artificial Intelligence Introduction
Effectiveness of Talent Acquisition through E-
Recruitment in this topic we will discuss about 4important
and interlinked topics which are
Tools & Techniques for Commissioning and Maintaining PV Systems W-Animations ...Transcat
Join us for this solutions-based webinar on the tools and techniques for commissioning and maintaining PV Systems. In this session, we'll review the process of building and maintaining a solar array, starting with installation and commissioning, then reviewing operations and maintenance of the system. This course will review insulation resistance testing, I-V curve testing, earth-bond continuity, ground resistance testing, performance tests, visual inspections, ground and arc fault testing procedures, and power quality analysis.
Fluke Solar Application Specialist Will White is presenting on this engaging topic:
Will has worked in the renewable energy industry since 2005, first as an installer for a small east coast solar integrator before adding sales, design, and project management to his skillset. In 2022, Will joined Fluke as a solar application specialist, where he supports their renewable energy testing equipment like IV-curve tracers, electrical meters, and thermal imaging cameras. Experienced in wind power, solar thermal, energy storage, and all scales of PV, Will has primarily focused on residential and small commercial systems. He is passionate about implementing high-quality, code-compliant installation techniques.
Prediction of Electrical Energy Efficiency Using Information on Consumer's Ac...PriyankaKilaniya
Energy efficiency has been important since the latter part of the last century. The main object of this survey is to determine the energy efficiency knowledge among consumers. Two separate districts in Bangladesh are selected to conduct the survey on households and showrooms about the energy and seller also. The survey uses the data to find some regression equations from which it is easy to predict energy efficiency knowledge. The data is analyzed and calculated based on five important criteria. The initial target was to find some factors that help predict a person's energy efficiency knowledge. From the survey, it is found that the energy efficiency awareness among the people of our country is very low. Relationships between household energy use behaviors are estimated using a unique dataset of about 40 households and 20 showrooms in Bangladesh's Chapainawabganj and Bagerhat districts. Knowledge of energy consumption and energy efficiency technology options is found to be associated with household use of energy conservation practices. Household characteristics also influence household energy use behavior. Younger household cohorts are more likely to adopt energy-efficient technologies and energy conservation practices and place primary importance on energy saving for environmental reasons. Education also influences attitudes toward energy conservation in Bangladesh. Low-education households indicate they primarily save electricity for the environment while high-education households indicate they are motivated by environmental concerns.
We have designed & manufacture the Lubi Valves LBF series type of Butterfly Valves for General Utility Water applications as well as for HVAC applications.
Impartiality as per ISO /IEC 17025:2017 StandardMuhammadJazib15
This document provides basic guidelines for imparitallity requirement of ISO 17025. It defines in detial how it is met and wiudhwdih jdhsjdhwudjwkdbjwkdddddddddddkkkkkkkkkkkkkkkkkkkkkkkwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwioiiiiiiiiiiiii uwwwwwwwwwwwwwwwwhe wiqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqq gbbbbbbbbbbbbb owdjjjjjjjjjjjjjjjjjjjj widhi owqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqq uwdhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhwqiiiiiiiiiiiiiiiiiiiiiiiiiiiiw0pooooojjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjj whhhhhhhhhhh wheeeeeeee wihieiiiiii wihe
e qqqqqqqqqqeuwiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiqw dddddddddd cccccccccccccccv s w c r
cdf cb bicbsad ishd d qwkbdwiur e wetwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwww w
dddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffw
uuuuhhhhhhhhhhhhhhhhhhhhhhhhe qiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiii iqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqq eeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeee qqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc ccccccccccccccccccccccccccccccccccc bbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbu uuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuum
m
m mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm m i
g i dijsd sjdnsjd ndjajsdnnsa adjdnawddddddddddddd uw
A high-Speed Communication System is based on the Design of a Bi-NoC Router, ...DharmaBanothu
The Network on Chip (NoC) has emerged as an effective
solution for intercommunication infrastructure within System on
Chip (SoC) designs, overcoming the limitations of traditional
methods that face significant bottlenecks. However, the complexity
of NoC design presents numerous challenges related to
performance metrics such as scalability, latency, power
consumption, and signal integrity. This project addresses the
issues within the router's memory unit and proposes an enhanced
memory structure. To achieve efficient data transfer, FIFO buffers
are implemented in distributed RAM and virtual channels for
FPGA-based NoC. The project introduces advanced FIFO-based
memory units within the NoC router, assessing their performance
in a Bi-directional NoC (Bi-NoC) configuration. The primary
objective is to reduce the router's workload while enhancing the
FIFO internal structure. To further improve data transfer speed,
a Bi-NoC with a self-configurable intercommunication channel is
suggested. Simulation and synthesis results demonstrate
guaranteed throughput, predictable latency, and equitable
network access, showing significant improvement over previous
designs
2. Requirements
Library: twitteR
o Provides an interface to the Twitter web API.
R is an open source programming language and
software environment for statistical computing and
graphics
RStudio:RStudio is a free and open source
integrated development environment (IDE) for R
3. Steps
1. Signup in twitter
2. Go to apps.twitter.com and register Application
Program Interface(API) using twitter account
3. Get API Key, API Secret, Access Token, Access
Token Secret
1. API KEY:JfpQuWXgr9YVhi1TeYzGLagKy
2. API Secret:
Ao8afu033PQMslxsLvKMdgVhIFRMiV9Ie2ppXg3oB
eIvF0ZnZz
3. Access Token: 927320525285634049-
dOhOiQFH708QVJeslJfqVnYgKxxe5mu
4. Access Token Secret:
JYQKFhsMjlI8xid8ozVerRfHSq8KrpZFky5m9vFh3ox
4. 4. Install Twitter Library
1. install. packages("twitteR") or
5. Set twitteR library
1. Load: library(twitteR)
2. setup_twitter_oauth(api_key,api_secret,access_toke
n,access_token_secret)
5. Demo1: Text Mining with WordCloud
install. Packages(“tm”)
install. packages(“wordcloud”)
library(“twitteR”)
library(“tm”)
library(“ROAuth”)
library(“wordcloud”)
8. Demo2:Text Mining with R – an Analysis of Twitter Data
>unstructured data
>text categorization
text clustering
entity extraction
Text Mining process
extract data from Twitter
clean extracted data and build a document-term matrix
find frequent words and associations
create a word cloud to visualize important words
text clustering