This document discusses improving the feature development process for the open-source PyQtGraph library. It first provides background on PyQtGraph and open-source development practices. It then analyzes PyQtGraph's current process through case studies and identifies areas for improvement, such as needing a collaboration tool to better coordinate contributions. The document proposes extending the "Pirate Metrics" framework to better measure community interactions during feature development. The conclusions note this study could help developers, maintainers, and users better understand open-source processes.
This document describes a project called Git-Influencer that aims to discover influential GitHub users by language. It does this by mapping users to languages they contribute to, building networks for each language, and running PageRank algorithms on these networks to score user importance. Several challenges are outlined such as dealing with data volume, accounting for inactive users, and handling users with no followers. Potential improvements discussed include using different data storage, classification metrics, and graph algorithms.
Experienced Software Engineer with a demonstrated history of working in the computer software industry. Skilled in Java, Python, Javascript(ES6), Flask, React and Databases. Strong engineering professional with B.Tech in Computer Engineering from Thapar University, Patiala.
FME-Based Tool for Automatic Updating of Geographical Git Repositories (Pushi...Safe Software
Safe Software's Ken Bragg discusses a project that uses FME and Git to create an open data repository of GeoJSON files on Github that also serves as a collaborative mapping framework.
The document summarizes the progress of a team developing an RSS reader Android application. It groups coding and testing under the same task. It adds research papers referenced. New Gantt and Pert charts are included with proposed task names. The team added internet permissions, optimized code, and enabled reading Atom feeds. Their agenda for the next month is to implement a content panel, add a database instead of file system, and implement localization.
SRDS2019: Abeona: an Architecture for Energy-Aware Task Migrations from the E...LEGATO project
This paper presents our preliminary results with ABEONA, an edge-to-cloud architecture that allows migrating tasks from low-energy, resource-constrained devices on the edge up to the cloud. Our preliminary results on artificial and real world datasets show that it is possible to execute workloads in a more efficient manner energy-wise by scaling horizontally at the edge, without negatively affecting the execution runtime.
This document discusses improving the feature development process for the open-source PyQtGraph library. It first provides background on PyQtGraph and open-source development practices. It then analyzes PyQtGraph's current process through case studies and identifies areas for improvement, such as needing a collaboration tool to better coordinate contributions. The document proposes extending the "Pirate Metrics" framework to better measure community interactions during feature development. The conclusions note this study could help developers, maintainers, and users better understand open-source processes.
This document describes a project called Git-Influencer that aims to discover influential GitHub users by language. It does this by mapping users to languages they contribute to, building networks for each language, and running PageRank algorithms on these networks to score user importance. Several challenges are outlined such as dealing with data volume, accounting for inactive users, and handling users with no followers. Potential improvements discussed include using different data storage, classification metrics, and graph algorithms.
Experienced Software Engineer with a demonstrated history of working in the computer software industry. Skilled in Java, Python, Javascript(ES6), Flask, React and Databases. Strong engineering professional with B.Tech in Computer Engineering from Thapar University, Patiala.
FME-Based Tool for Automatic Updating of Geographical Git Repositories (Pushi...Safe Software
Safe Software's Ken Bragg discusses a project that uses FME and Git to create an open data repository of GeoJSON files on Github that also serves as a collaborative mapping framework.
The document summarizes the progress of a team developing an RSS reader Android application. It groups coding and testing under the same task. It adds research papers referenced. New Gantt and Pert charts are included with proposed task names. The team added internet permissions, optimized code, and enabled reading Atom feeds. Their agenda for the next month is to implement a content panel, add a database instead of file system, and implement localization.
SRDS2019: Abeona: an Architecture for Energy-Aware Task Migrations from the E...LEGATO project
This paper presents our preliminary results with ABEONA, an edge-to-cloud architecture that allows migrating tasks from low-energy, resource-constrained devices on the edge up to the cloud. Our preliminary results on artificial and real world datasets show that it is possible to execute workloads in a more efficient manner energy-wise by scaling horizontally at the edge, without negatively affecting the execution runtime.
Big Data LDN 2018: ENABLING DATA-DRIVEN DECISIONS WITH AUTOMATED INSIGHTSMatt Stubbs
Date: 13th November 2018
Location: Customer Experience Theatre
Time: 11:50 - 12:20
Speaker: Charlotte Emms
Organisation: seenit
About: How do you get your colleagues interested in the power of data? Taking you through Seenit’s journey using Couchbase's NoSQL database to create a regular, fully automated update in an easily digestible format.
This document discusses forecasting the number of daily issues on GitHub repositories to help foundations efficiently manage resources. The authors collected daily issue and commit data from 5 large GitHub repositories over the past year. They used time series forecasting techniques to forecast the number of daily issues for each repository over the next 3 weeks. By evaluating forecast accuracy, they selected the best technique for each repository and generated ensemble forecasts. On average, their forecasts were 16% more accurate than the benchmark. This approach could help foundations allocate programmers in advance to repositories expected to have higher issue volumes.
Data Sharing, Distribution and Updating Using Social Coding Community Github ...Universität Salzburg
This document provides a summary of a presentation about using GitHub and LATEX for graduate research projects. It discusses the benefits of GitHub for collaborative work and version control. It also highlights some advantages of LATEX over traditional text editors for writing theses. The presentation includes steps for creating a personal GitHub repository and maintaining a project. It provides an example of using GitHub and LATEX for an MSc thesis on seagrass mapping. Overall, the presentation aims to demonstrate how these tools can facilitate writing, editing, and managing research projects in an academic setting.
ChatGPT
The Big Data projects course includes five projects:
Data Engineering with PDF Summary Tool: Create a Streamlit app to summarize PDFs, comparing nougat and PyPDF libraries, and integrate architectural diagrams.
Large Language Models for SEC Document Summarization: Develop a tool for summarizing PDF documents, evaluating different libraries, and creating Jupyter notebooks and APIs for Streamlit integration.
Document Summarization with LLMs and RAG: Focus on automating embedding creation, data processing, and developing a client-facing application with secure login and search functionalities.
Data Engineering with Snowpark Python: Reproduce data pipeline steps, analyze datasets, design architectural diagrams, and integrate Streamlit with OpenAI for SQL query generation using natural language.
Project Redesign and Rearchitecture: Review existing architecture and redesign using open-source components and enterprise alternatives, focusing on flexible, scalable, and cost-effective solutions.
1. The document describes a demonstration of the Readium JS software using the IMS Caliper sensor API and LTI integration to capture learning analytics data from a digital textbook.
2. The demo aims to capture events like page views, annotations, bookmarks and logins/logouts and transmit the data in JSON format to be stored and analyzed on a pseudo platform with MongoDB databases.
3. Next steps discussed are evaluating the developed code, contributing it to the Readium project on GitHub, revising the LTI integration, and supporting EPUB for Education standards in Readium. Guidelines for learning data interoperability in ISO/IEC JTC1 SC36 WG8 are also summarized.
Presentation of the paper "Primers or Reminders? The Effects of Existing Review Comments on Code Review" published at ICSE 2020.
Authors:
Davide Spadini, Gül Calikli, Alberto Bacchelli
Link to the paper: https://research.tudelft.nl/en/publications/primers-or-reminders-the-effects-of-existing-review-comments-on-c
Maruti Gollapudi has over 17 years of experience as a principal architect, specializing in digital customer experience. Some of his significant contributions include developing a data aggregation and analytics platform hosted on AWS that enables capabilities like social analytics, text analytics using NLP and machine learning, and enterprise search. He has experience building solutions leveraging technologies such as Java, JBoss, Kafka, MongoDB, Solr, Watson, and various analytics and social APIs. Recent projects include developing a headless CMS for page building and dynamic content modification for CNBC, and architecting a middleware for CNBC's integration with Uber to dynamically serve ride-related content.
London atlassian meetup 31 jan 2016 jira metrics-extract slidesRudiger Wolf
Slides for talk given to London Atlassian User Group Jan 2017. How to get started with Python to extract data from Jira and produce charts for your Agile team.
This document describes a project to analyze GitHub data and develop visualizations and recommendations. The project will have two parts: 1) A visualization part that analyzes metrics like programming languages used, active users, geographic distribution of users, and popular repositories, and 2) A recommendation system that suggests potential contributors or repositories for a given user based on their activity history. The project aims to provide insights into active areas on GitHub and which languages are most widely used. It will also help increase collaboration by recommending potential collaborators and interesting repositories for users. The document outlines the project timeline and division of labor across gathering requirements, design, implementation, and developing the user interface.
The document discusses the evolution of continuous integration and delivery workflows at Red Hat's Fabric8 project. It describes how the workflows have scaled from initially having 4 main Java repositories and 15 Jenkins jobs to now having over 80 repositories and 143 Jenkins jobs. The document outlines the key tools used in their workflows including Jenkins, Kubernetes, Kibana, Grafana and others and demonstrates how automation is applied across the entire software development lifecycle from app creation to continuous improvement. It encourages adopting similar practices to help deliver value to customers faster.
Git and GitHub are open source version control systems. Git is a decentralized version control system, while GitHub is a web-based hosting service for Git repositories that offers additional collaboration features. GitHub allows users to fork repositories to propose and contribute changes. Key features include wikis, task management, bug tracking, and pull requests to merge changes. GitHub is a powerful collaboration tool for software developers and other users due to its features for forking, pulling, and merging code changes.
This document outlines the objectives and content of a course on software development practices and web development. The course covers agile software development methods like Scrum, setting up GitHub repositories, developing static and dynamic web pages using HTML, CSS, and JavaScript, and implementing mini projects like online assessment or ticket reservation systems using these technologies. The course has 5 units covering agile development, Git and GitHub, HTML, CSS, JavaScript basics, and JavaScript objects. Students will learn to apply agile methods, create GitHub repositories, develop web pages with HTML, design pages with CSS, add interactivity with JavaScript, and handle events.
Research data spring: streamlining depositJisc RDM
The research data spring project "Streamlining deposit: an OJS to repository plugin" slides for the third sandpit workshop. Project led by Ernesto Priego of City University London.
Efficient GitHub Crawling using the GraphQL APIMatthias Trapp
This document discusses efficient crawling of GitHub data using the GraphQL API compared to traditional REST APIs. It presents the Prometheus system, which uses a microservices architecture and event-driven approach to split GraphQL queries and import response data into a database. An experiment shows the Prometheus system is over 3 times faster than an existing crawler when retrieving issues data from GitHub repositories. The document concludes the GraphQL API enables better performance for crawling but query structure also impacts efficiency.
Software development projects are notoriously complex and difficult to deal with. Several support tools such as issue tracking, code review and Source Control Management (SCM) systems have been introduced in the past decades to
ease development activities. While such tools efficiently track the evolution of a given aspect of the project (e.g., bug reports), they provide just a partial view of the project and often lack of advanced querying mechanisms limiting themselves to command line or simple GUI support. This is particularly true for projects that rely on Git, the most popular SCM system today.
In this paper, we propose a conceptual schema for Git and an approach that, given a Git repository, exports its data to a relational database in order to (1) promote data integration with other existing SCM tools and (2) enable writing queries on Git data using standard SQL syntax. To ensure efficiency, our approach comes with an incremental propagation mechanism that refreshes the database content with the latest modifications. We have implemented our approach in Gitana, an open-source tool available on GitHub (https://github.com/SOM-Research/Gitana).
Building Reactive Real-time Data PipelineTrieu Nguyen
Topic: Building reactive real-time data pipeline at FPT ?
1) What is “Data Pipeline” ?
2) Big Data Problems at FPT
+ VnExpress: pageview and heat-map
+ eClick: real-time reactive advertising
3) Solutions and Patterns
4) Fast Data Architecture at FPT
5) Wrap up
Crunching the numbers: Open Source Community Metrics at OSCONDawn Foster
Co-presented with Dave Neary at OSCON 2011.
Every community manager knows that community metrics are important, but how do you come up with a plan and figure out what you want to measure? Most community managers have their own set of hacky scripts for extracting data from various sources after they decide what metrics to track. There is no standardised Community Software Dashboard you can use to generate near-real-time stats on your community growth.
Like most open source projects, we have diverse community infrastructure for MeeGo, including Mailman, Drupal, Mediawiki, IRC, git, OpenSuse Build Service, Transifex and vBulletin. We wanted to unify these sources together, extract meaningful statistics from the data we had available to us, and present it to the user in a way that made it easy to see if the community was developing nicely or not.
Building on the work of Pentaho, Talend, MLStats, gitdm and a host of others, we built a generic and open source community dashboard for the MeeGo project, and integrated it into the website. The project was run in the open at http://wiki.meego.com/Metrics/Dashboard and all products of the project are available for reuse.
This presentation will cover the various metrics we wanted to measure, how we extracted the data from a diverse set of services to do it, and more importantly, how you can do it too.
Crunching the numbers: Open Source Community MetricsDawn Foster
Every community manager knows that community metrics are important, but how do you come up with a plan and figure out what you want to measure? Most community managers have their own set of hacky scripts for extracting data from various sources after they decide what metrics to track. There is no standardised Community Software Dashboard you can use to generate near-real-time stats on your community growth.
Like most open source projects, we have diverse community infrastructure for MeeGo, including Mailman, Drupal, Mediawiki, IRC, git, OpenSuse Build Service, Transifex and vBulletin. We wanted to unify these sources together, extract meaningful statistics from the data we had available to us, and present it to the user in a way that made it easy to see if the community was developing nicely or not.
Building on the work of Pentaho, Talend, MLStats, gitdm and a host of others, we built a generic and open source community dashboard for the MeeGo project, and integrated it into the website. The project was run in the open at http://wiki.meego.com/Metrics/Dashboard and all products of the project are available for reuse.
This presentation will cover the various metrics we wanted to measure, how we extracted the data from a diverse set of services to do it, and more importantly, how you can do it too.
Discover the latest insights on Data Driven Maintenance with our comprehensive webinar presentation. Learn about traditional maintenance challenges, the right approach to utilizing data, and the benefits of adopting a Data Driven Maintenance strategy. Explore real-world examples, industry best practices, and innovative solutions like FMECA and the D3M model. This presentation, led by expert Jules Oudmans, is essential for asset owners looking to optimize their maintenance processes and leverage digital technologies for improved efficiency and performance. Download now to stay ahead in the evolving maintenance landscape.
Big Data LDN 2018: ENABLING DATA-DRIVEN DECISIONS WITH AUTOMATED INSIGHTSMatt Stubbs
Date: 13th November 2018
Location: Customer Experience Theatre
Time: 11:50 - 12:20
Speaker: Charlotte Emms
Organisation: seenit
About: How do you get your colleagues interested in the power of data? Taking you through Seenit’s journey using Couchbase's NoSQL database to create a regular, fully automated update in an easily digestible format.
This document discusses forecasting the number of daily issues on GitHub repositories to help foundations efficiently manage resources. The authors collected daily issue and commit data from 5 large GitHub repositories over the past year. They used time series forecasting techniques to forecast the number of daily issues for each repository over the next 3 weeks. By evaluating forecast accuracy, they selected the best technique for each repository and generated ensemble forecasts. On average, their forecasts were 16% more accurate than the benchmark. This approach could help foundations allocate programmers in advance to repositories expected to have higher issue volumes.
Data Sharing, Distribution and Updating Using Social Coding Community Github ...Universität Salzburg
This document provides a summary of a presentation about using GitHub and LATEX for graduate research projects. It discusses the benefits of GitHub for collaborative work and version control. It also highlights some advantages of LATEX over traditional text editors for writing theses. The presentation includes steps for creating a personal GitHub repository and maintaining a project. It provides an example of using GitHub and LATEX for an MSc thesis on seagrass mapping. Overall, the presentation aims to demonstrate how these tools can facilitate writing, editing, and managing research projects in an academic setting.
ChatGPT
The Big Data projects course includes five projects:
Data Engineering with PDF Summary Tool: Create a Streamlit app to summarize PDFs, comparing nougat and PyPDF libraries, and integrate architectural diagrams.
Large Language Models for SEC Document Summarization: Develop a tool for summarizing PDF documents, evaluating different libraries, and creating Jupyter notebooks and APIs for Streamlit integration.
Document Summarization with LLMs and RAG: Focus on automating embedding creation, data processing, and developing a client-facing application with secure login and search functionalities.
Data Engineering with Snowpark Python: Reproduce data pipeline steps, analyze datasets, design architectural diagrams, and integrate Streamlit with OpenAI for SQL query generation using natural language.
Project Redesign and Rearchitecture: Review existing architecture and redesign using open-source components and enterprise alternatives, focusing on flexible, scalable, and cost-effective solutions.
1. The document describes a demonstration of the Readium JS software using the IMS Caliper sensor API and LTI integration to capture learning analytics data from a digital textbook.
2. The demo aims to capture events like page views, annotations, bookmarks and logins/logouts and transmit the data in JSON format to be stored and analyzed on a pseudo platform with MongoDB databases.
3. Next steps discussed are evaluating the developed code, contributing it to the Readium project on GitHub, revising the LTI integration, and supporting EPUB for Education standards in Readium. Guidelines for learning data interoperability in ISO/IEC JTC1 SC36 WG8 are also summarized.
Presentation of the paper "Primers or Reminders? The Effects of Existing Review Comments on Code Review" published at ICSE 2020.
Authors:
Davide Spadini, Gül Calikli, Alberto Bacchelli
Link to the paper: https://research.tudelft.nl/en/publications/primers-or-reminders-the-effects-of-existing-review-comments-on-c
Maruti Gollapudi has over 17 years of experience as a principal architect, specializing in digital customer experience. Some of his significant contributions include developing a data aggregation and analytics platform hosted on AWS that enables capabilities like social analytics, text analytics using NLP and machine learning, and enterprise search. He has experience building solutions leveraging technologies such as Java, JBoss, Kafka, MongoDB, Solr, Watson, and various analytics and social APIs. Recent projects include developing a headless CMS for page building and dynamic content modification for CNBC, and architecting a middleware for CNBC's integration with Uber to dynamically serve ride-related content.
London atlassian meetup 31 jan 2016 jira metrics-extract slidesRudiger Wolf
Slides for talk given to London Atlassian User Group Jan 2017. How to get started with Python to extract data from Jira and produce charts for your Agile team.
This document describes a project to analyze GitHub data and develop visualizations and recommendations. The project will have two parts: 1) A visualization part that analyzes metrics like programming languages used, active users, geographic distribution of users, and popular repositories, and 2) A recommendation system that suggests potential contributors or repositories for a given user based on their activity history. The project aims to provide insights into active areas on GitHub and which languages are most widely used. It will also help increase collaboration by recommending potential collaborators and interesting repositories for users. The document outlines the project timeline and division of labor across gathering requirements, design, implementation, and developing the user interface.
The document discusses the evolution of continuous integration and delivery workflows at Red Hat's Fabric8 project. It describes how the workflows have scaled from initially having 4 main Java repositories and 15 Jenkins jobs to now having over 80 repositories and 143 Jenkins jobs. The document outlines the key tools used in their workflows including Jenkins, Kubernetes, Kibana, Grafana and others and demonstrates how automation is applied across the entire software development lifecycle from app creation to continuous improvement. It encourages adopting similar practices to help deliver value to customers faster.
Git and GitHub are open source version control systems. Git is a decentralized version control system, while GitHub is a web-based hosting service for Git repositories that offers additional collaboration features. GitHub allows users to fork repositories to propose and contribute changes. Key features include wikis, task management, bug tracking, and pull requests to merge changes. GitHub is a powerful collaboration tool for software developers and other users due to its features for forking, pulling, and merging code changes.
This document outlines the objectives and content of a course on software development practices and web development. The course covers agile software development methods like Scrum, setting up GitHub repositories, developing static and dynamic web pages using HTML, CSS, and JavaScript, and implementing mini projects like online assessment or ticket reservation systems using these technologies. The course has 5 units covering agile development, Git and GitHub, HTML, CSS, JavaScript basics, and JavaScript objects. Students will learn to apply agile methods, create GitHub repositories, develop web pages with HTML, design pages with CSS, add interactivity with JavaScript, and handle events.
Research data spring: streamlining depositJisc RDM
The research data spring project "Streamlining deposit: an OJS to repository plugin" slides for the third sandpit workshop. Project led by Ernesto Priego of City University London.
Efficient GitHub Crawling using the GraphQL APIMatthias Trapp
This document discusses efficient crawling of GitHub data using the GraphQL API compared to traditional REST APIs. It presents the Prometheus system, which uses a microservices architecture and event-driven approach to split GraphQL queries and import response data into a database. An experiment shows the Prometheus system is over 3 times faster than an existing crawler when retrieving issues data from GitHub repositories. The document concludes the GraphQL API enables better performance for crawling but query structure also impacts efficiency.
Software development projects are notoriously complex and difficult to deal with. Several support tools such as issue tracking, code review and Source Control Management (SCM) systems have been introduced in the past decades to
ease development activities. While such tools efficiently track the evolution of a given aspect of the project (e.g., bug reports), they provide just a partial view of the project and often lack of advanced querying mechanisms limiting themselves to command line or simple GUI support. This is particularly true for projects that rely on Git, the most popular SCM system today.
In this paper, we propose a conceptual schema for Git and an approach that, given a Git repository, exports its data to a relational database in order to (1) promote data integration with other existing SCM tools and (2) enable writing queries on Git data using standard SQL syntax. To ensure efficiency, our approach comes with an incremental propagation mechanism that refreshes the database content with the latest modifications. We have implemented our approach in Gitana, an open-source tool available on GitHub (https://github.com/SOM-Research/Gitana).
Building Reactive Real-time Data PipelineTrieu Nguyen
Topic: Building reactive real-time data pipeline at FPT ?
1) What is “Data Pipeline” ?
2) Big Data Problems at FPT
+ VnExpress: pageview and heat-map
+ eClick: real-time reactive advertising
3) Solutions and Patterns
4) Fast Data Architecture at FPT
5) Wrap up
Crunching the numbers: Open Source Community Metrics at OSCONDawn Foster
Co-presented with Dave Neary at OSCON 2011.
Every community manager knows that community metrics are important, but how do you come up with a plan and figure out what you want to measure? Most community managers have their own set of hacky scripts for extracting data from various sources after they decide what metrics to track. There is no standardised Community Software Dashboard you can use to generate near-real-time stats on your community growth.
Like most open source projects, we have diverse community infrastructure for MeeGo, including Mailman, Drupal, Mediawiki, IRC, git, OpenSuse Build Service, Transifex and vBulletin. We wanted to unify these sources together, extract meaningful statistics from the data we had available to us, and present it to the user in a way that made it easy to see if the community was developing nicely or not.
Building on the work of Pentaho, Talend, MLStats, gitdm and a host of others, we built a generic and open source community dashboard for the MeeGo project, and integrated it into the website. The project was run in the open at http://wiki.meego.com/Metrics/Dashboard and all products of the project are available for reuse.
This presentation will cover the various metrics we wanted to measure, how we extracted the data from a diverse set of services to do it, and more importantly, how you can do it too.
Crunching the numbers: Open Source Community MetricsDawn Foster
Every community manager knows that community metrics are important, but how do you come up with a plan and figure out what you want to measure? Most community managers have their own set of hacky scripts for extracting data from various sources after they decide what metrics to track. There is no standardised Community Software Dashboard you can use to generate near-real-time stats on your community growth.
Like most open source projects, we have diverse community infrastructure for MeeGo, including Mailman, Drupal, Mediawiki, IRC, git, OpenSuse Build Service, Transifex and vBulletin. We wanted to unify these sources together, extract meaningful statistics from the data we had available to us, and present it to the user in a way that made it easy to see if the community was developing nicely or not.
Building on the work of Pentaho, Talend, MLStats, gitdm and a host of others, we built a generic and open source community dashboard for the MeeGo project, and integrated it into the website. The project was run in the open at http://wiki.meego.com/Metrics/Dashboard and all products of the project are available for reuse.
This presentation will cover the various metrics we wanted to measure, how we extracted the data from a diverse set of services to do it, and more importantly, how you can do it too.
Discover the latest insights on Data Driven Maintenance with our comprehensive webinar presentation. Learn about traditional maintenance challenges, the right approach to utilizing data, and the benefits of adopting a Data Driven Maintenance strategy. Explore real-world examples, industry best practices, and innovative solutions like FMECA and the D3M model. This presentation, led by expert Jules Oudmans, is essential for asset owners looking to optimize their maintenance processes and leverage digital technologies for improved efficiency and performance. Download now to stay ahead in the evolving maintenance landscape.
Null Bangalore | Pentesters Approach to AWS IAMDivyanshu
#Abstract:
- Learn more about the real-world methods for auditing AWS IAM (Identity and Access Management) as a pentester. So let us proceed with a brief discussion of IAM as well as some typical misconfigurations and their potential exploits in order to reinforce the understanding of IAM security best practices.
- Gain actionable insights into AWS IAM policies and roles, using hands on approach.
#Prerequisites:
- Basic understanding of AWS services and architecture
- Familiarity with cloud security concepts
- Experience using the AWS Management Console or AWS CLI.
- For hands on lab create account on [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
# Scenario Covered:
- Basics of IAM in AWS
- Implementing IAM Policies with Least Privilege to Manage S3 Bucket
- Objective: Create an S3 bucket with least privilege IAM policy and validate access.
- Steps:
- Create S3 bucket.
- Attach least privilege policy to IAM user.
- Validate access.
- Exploiting IAM PassRole Misconfiguration
-Allows a user to pass a specific IAM role to an AWS service (ec2), typically used for service access delegation. Then exploit PassRole Misconfiguration granting unauthorized access to sensitive resources.
- Objective: Demonstrate how a PassRole misconfiguration can grant unauthorized access.
- Steps:
- Allow user to pass IAM role to EC2.
- Exploit misconfiguration for unauthorized access.
- Access sensitive resources.
- Exploiting IAM AssumeRole Misconfiguration with Overly Permissive Role
- An overly permissive IAM role configuration can lead to privilege escalation by creating a role with administrative privileges and allow a user to assume this role.
- Objective: Show how overly permissive IAM roles can lead to privilege escalation.
- Steps:
- Create role with administrative privileges.
- Allow user to assume the role.
- Perform administrative actions.
- Differentiation between PassRole vs AssumeRole
Try at [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
Digital Twins Computer Networking Paper Presentation.pptxaryanpankaj78
A Digital Twin in computer networking is a virtual representation of a physical network, used to simulate, analyze, and optimize network performance and reliability. It leverages real-time data to enhance network management, predict issues, and improve decision-making processes.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
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.
Design and optimization of ion propulsion dronebjmsejournal
Electric propulsion technology is widely used in many kinds of vehicles in recent years, and aircrafts are no exception. Technically, UAVs are electrically propelled but tend to produce a significant amount of noise and vibrations. Ion propulsion technology for drones is a potential solution to this problem. Ion propulsion technology is proven to be feasible in the earth’s atmosphere. The study presented in this article shows the design of EHD thrusters and power supply for ion propulsion drones along with performance optimization of high-voltage power supply for endurance in earth’s atmosphere.
Generative AI Use cases applications solutions and implementation.pdfmahaffeycheryld
Generative AI solutions encompass a range of capabilities from content creation to complex problem-solving across industries. Implementing generative AI involves identifying specific business needs, developing tailored AI models using techniques like GANs and VAEs, and integrating these models into existing workflows. Data quality and continuous model refinement are crucial for effective implementation. Businesses must also consider ethical implications and ensure transparency in AI decision-making. Generative AI's implementation aims to enhance efficiency, creativity, and innovation by leveraging autonomous generation and sophisticated learning algorithms to meet diverse business challenges.
https://www.leewayhertz.com/generative-ai-use-cases-and-applications/
Rainfall intensity duration frequency curve statistical analysis and modeling...bijceesjournal
Using data from 41 years in Patna’ India’ the study’s goal is to analyze the trends of how often it rains on a weekly, seasonal, and annual basis (1981−2020). First, utilizing the intensity-duration-frequency (IDF) curve and the relationship by statistically analyzing rainfall’ the historical rainfall data set for Patna’ India’ during a 41 year period (1981−2020), was evaluated for its quality. Changes in the hydrologic cycle as a result of increased greenhouse gas emissions are expected to induce variations in the intensity, length, and frequency of precipitation events. One strategy to lessen vulnerability is to quantify probable changes and adapt to them. Techniques such as log-normal, normal, and Gumbel are used (EV-I). Distributions were created with durations of 1, 2, 3, 6, and 24 h and return times of 2, 5, 10, 25, and 100 years. There were also mathematical correlations discovered between rainfall and recurrence interval.
Findings: Based on findings, the Gumbel approach produced the highest intensity values, whereas the other approaches produced values that were close to each other. The data indicates that 461.9 mm of rain fell during the monsoon season’s 301st week. However, it was found that the 29th week had the greatest average rainfall, 92.6 mm. With 952.6 mm on average, the monsoon season saw the highest rainfall. Calculations revealed that the yearly rainfall averaged 1171.1 mm. Using Weibull’s method, the study was subsequently expanded to examine rainfall distribution at different recurrence intervals of 2, 5, 10, and 25 years. Rainfall and recurrence interval mathematical correlations were also developed. Further regression analysis revealed that short wave irrigation, wind direction, wind speed, pressure, relative humidity, and temperature all had a substantial influence on rainfall.
Originality and value: The results of the rainfall IDF curves can provide useful information to policymakers in making appropriate decisions in managing and minimizing floods in the study area.
2. -
– Let’s spare a moment to think about
what is happening with a giant open-
source software project….
At a well-known open-source project
3.
4. Source: Linux Kernel Report 2017, Linux Foundation
Figure 1:
Top companies
contributing to
the Linux kernel,
4.8– 4.13 in 2017
Linux Kernel Contributors
5. Table of Contents
– 1. What is PyQtGraph and where does it come from?
– 2. Open Source Feature Development: Known Facts
– 3. Analysis of PyQtGraph’s Feature Development Process
– 4. Guidelines for PyQtGraph’s Feature Process
Improvements
– 5. Conclusions
6. PyQtGraph: A graphic library
Functionalities:
– Basic 2D plotting
– Image display with interactive
lookup tables
– 3D graphics system
– Library of widgets and modules
useful for science/engineering
applications
Source: www.pyqtgraph.orgFigure 2: Histogram drawn with
PyQtGraph
8. Feature Development in Open-Soure Software
– Iterative process with a public repository
– Mailing list, Forum Boards
– Small, frequent changes to code repository
– Few key developers (that is, limited resources)
– Atleast one maintainer
9.
10. Applying Pirate Metrics to
PyQtGraph Project
Figure 4: The
AARRR! Metrics
for PyQtGraph
Source:
Pirate Metrics: A new
way to measure open
source community
success by Gaby Fachler
11. To Accept or Not to Accept?
– A dilemma often presenting itself to the maintainer:
– One side:
– Accepting (new) code appeases the feature contributor; (possibly also) other
users
– Other side:
– New code becomes the responsibility of the maintainer
12. PyQtGraph’s Code Development
– Bug Reports and New Feature Proposals on GitHub Issues, GitHub Pull Request
and PyQtGraph GoogleGroups pages
– Maintainer of the GitHub (and also founder): Luke Campagnola
– 8-10 user queries/feature proposals every month
– 60 percent of user queries/feature proposals are answered
– About 40 ‘listed’ contributors
– All development is voluntary-based
– FAQ for prospective contributors is available
13. PyQtGraph Google Group Statistics
Figure 5: Data Related to Number of Posts on PyQtGraph ’Google
Group’ Forum site
14. Analysing the Library Forum Posts
– Only posts where the maintainer had commented were analysed
– Corresponding changes in code in Github were studied
– A list of observations was created
– 3 cases of feature development were studied
– The 3 cases represented different feature development outcomes
15. A Successful Development Cycle
aa
Figure 6: Timeline
of events for a
typical successful
feature-addition
process.
16. Case of Unsuccessful Feature
Development
Figure 7:
Timeline of
interactions for
the “New Time
Axis” proposed
feature
17. Suggested Improvements for Feature
Development Process
– Need for a Collaboration Tool.
(Objective: focus the current development resources towards feature completion)
– A new metric to assign collaboration level for new feature code posts
– Visibility of across GithHub and Google Groups forum
– While feature development in progress: correction list auto-tracking features
21. Conclusions: Beneficiaries &
Limitiations of Scope
– This study could aid:
• a developer wishing to contribute to the PyQtGraph project code
• maintainer of the PyQtGraph project
• User studying the open-source process
- Limitations:
Research based only on one open-source library
Each open-source project may have its own dynamics
22. References:
– 1. Luke Campagnola. PyQtGraph Project Home page:
http://www.pyqtgraph.org/ [Internet] [cited 24 April 2018]
– 2. Luke Campagnola. PyQtGraph Project Official Documentation page:
http://www.pyqtgraph.org/documentation/installation.html [Internet] [cited 24
April 2018]
– 3. Pirate Metrics: A new way to measure open source community success.
https://opensource.com/business/16/6/pirate-metrics [Internet] [cited 24 April
2018]
24. Plotting a Graph
–Imagine an Apple Tree that grows
uniformly at the rate of 1 meter per
year. It was planted in 2010. Can you
show how it has grown?