Simulink® is a block diagram environment for multi-domain simulation and Model-Based Design. It supports simulation, automatic code generation, and continuous test and verification of embedded systems.
This document provides an introduction to Simulink, which is an extension of MATLAB that allows engineers to model dynamic physical systems using block diagrams. It defines key concepts like systems, block diagrams, and modeling approaches. The document explains that Simulink uses block diagram representations of mathematical models to simulate and analyze dynamic systems. It provides examples of modeling spring-mass systems in Simulink and discusses how Simulink can be used for rapid prototyping and application development.
A Powerpoint Presentation designed to provide beginners to MATLAB an introduction to the MATLAB environment and introduce them to the fundamentals of MATLAB including matrix generation and manipulation, Arrays, MATLAB Graphics, Data Import and Export, etc
Introduction to matlab_application_to_electrical_engineeringzulfikar37
This document provides an introduction to using MATLAB. It covers starting and quitting MATLAB, the MATLAB desktop interface and tools, performing basic calculations in MATLAB, creating variables, plotting functions, and debugging M-files. The overall aim is to help students become familiar with MATLAB through examples and exercises.
Simulink is a graphical modeling environment used to model and simulate dynamic systems. It allows users to model systems using block diagrams by dragging blocks from various libraries and connecting them to represent signal flows. Common block types include sources, sinks, continuous, and discrete blocks. Models can be run by selecting Simulation-Start which performs the dynamic simulation. Results can be viewed by double clicking blocks like scopes. Simulink provides an easy to use interface for building and simulating systems without needing to write code.
This document provides information about a textbook titled "Introduction to Simulink with Engineering Applications, Second Edition" by Steven T. Karris. It is published by Orchard Publications and is an introduction to using Simulink for modeling and simulation. The textbook covers all of the block libraries in Simulink Version 7.1 and provides examples of applications in mathematics and engineering. It is intended for students and professionals as a reference guide for using Simulink.
Simulink is a tool for modeling and simulating dynamic systems. It uses block diagrams where blocks represent system components and signals flow between blocks. Common uses include modeling control systems and signal processing. A Simulink model contains sources that generate signals, sinks that terminate signals, and blocks in between that are connected to represent the system. Models can be run to simulate the system and view results. Integrators, derivatives, and other blocks are available to represent system dynamics. Control design tools can also linearize models around operating points.
This document provides an introduction to Simulink, which is an extension of MATLAB that allows engineers to model dynamic physical systems using block diagrams. It defines key concepts like systems, block diagrams, and modeling approaches. The document explains that Simulink uses block diagram representations of mathematical models to simulate and analyze dynamic systems. It provides examples of modeling spring-mass systems in Simulink and discusses how Simulink can be used for rapid prototyping and application development.
A Powerpoint Presentation designed to provide beginners to MATLAB an introduction to the MATLAB environment and introduce them to the fundamentals of MATLAB including matrix generation and manipulation, Arrays, MATLAB Graphics, Data Import and Export, etc
Introduction to matlab_application_to_electrical_engineeringzulfikar37
This document provides an introduction to using MATLAB. It covers starting and quitting MATLAB, the MATLAB desktop interface and tools, performing basic calculations in MATLAB, creating variables, plotting functions, and debugging M-files. The overall aim is to help students become familiar with MATLAB through examples and exercises.
Simulink is a graphical modeling environment used to model and simulate dynamic systems. It allows users to model systems using block diagrams by dragging blocks from various libraries and connecting them to represent signal flows. Common block types include sources, sinks, continuous, and discrete blocks. Models can be run by selecting Simulation-Start which performs the dynamic simulation. Results can be viewed by double clicking blocks like scopes. Simulink provides an easy to use interface for building and simulating systems without needing to write code.
This document provides information about a textbook titled "Introduction to Simulink with Engineering Applications, Second Edition" by Steven T. Karris. It is published by Orchard Publications and is an introduction to using Simulink for modeling and simulation. The textbook covers all of the block libraries in Simulink Version 7.1 and provides examples of applications in mathematics and engineering. It is intended for students and professionals as a reference guide for using Simulink.
Simulink is a tool for modeling and simulating dynamic systems. It uses block diagrams where blocks represent system components and signals flow between blocks. Common uses include modeling control systems and signal processing. A Simulink model contains sources that generate signals, sinks that terminate signals, and blocks in between that are connected to represent the system. Models can be run to simulate the system and view results. Integrators, derivatives, and other blocks are available to represent system dynamics. Control design tools can also linearize models around operating points.
MATLAB Programs For Beginners. | Abhi SharmaAbee Sharma
This is MATLAB's 10 most easy & most basic programs that I's supposed to submit in my practicals. In this document I've complied 10 MATLAB programs from basic to advanced through intermediate levels, But overall they are for beginners only. It's only a 26 pages doc. for academic purposes. well, What else a student can offer you, huh? LOLz
This document discusses parallel computing with MATLAB. It introduces MATLAB and parallel computing concepts. It then covers how MATLAB can be used for parallel computing on multi-core systems and distributed computing servers. It discusses parallel commands in MATLAB like matlabpool, parfor, pmode, and spmd. It also demonstrates how to test the efficiency of parallel code and provides an example comparing the execution times of serial and parallel prime number calculation codes.
MATLAB is a numerical computing environment and programming language developed in the 1970s. It was originally designed for matrix computations but has grown to include tools for data analysis, visualization, and GUI design. MATLAB allows both numeric calculations and programming and is commonly used in engineering, science, and mathematics applications. It includes toolboxes for tasks like signal processing, control systems, and computer vision.
Here are the key points about scalar-matrix addition in MATLAB:
- a is a scalar (single value)
- b is a matrix (2D array)
- To add a scalar to a matrix, MATLAB adds the scalar to each element of the matrix
- c = b + a performs element-wise addition, adding the value of a (which is 3) to each element of b
- The result c is the matrix b with 3 added to each element
So c would be:
c =
4 5 6
7 8 9
Scalar-matrix operations in MATLAB perform the operation on each element of the matrix.
MATLAB is a matrix-based programming language used for numerical computations, data analysis, and visualization. It allows matrix manipulations, functions for computation and visualization, toolboxes for different applications, and integrated development environment for programming. MATLAB can be used for engineering and scientific calculations with graphical output. It has built-in functions, user-defined functions, 2D and 3D graphics capabilities, GUI tools, and interfaces with other languages like C and Fortran.
131010 jim cordy - submodel pattern extraction for simulink modelsPtidej Team
This document discusses submodel pattern extraction for Simulink models. It introduces Model Pattern Engineering (MPE) which aims to discover, catalogue and formalize submodel patterns. MPE is inspired by prior work on detecting near-miss clones in code. The document outlines challenges in adapting near-miss clone detection techniques from code to models. It describes the Simone tool, which uses techniques from the NiCad near-miss clone detector adapted to work on Simulink models. Simone addresses challenges through agile parsing, filtering irrelevant elements, and topological sorting of model elements.
This document discusses integrating C/C++ code with MATLAB using MEX files. MEX files allow calling C/C++ functions from MATLAB for increased computation speed compared to MATLAB code. MEX files contain a gateway routine called mexFunction that interacts with MATLAB and subroutines containing the C/C++ code. The document explains how to write MEX files, use MATLAB data structures like mxArrays, call built-in MATLAB functions, and compile and use the resulting MEX binary file.
1. This document describes the modeling of a quarter-car suspension system using Simulink to analyze the system's response.
2. Key parameters of the suspension system are provided, including spring and damping constants for the suspension and tire.
3. The Simulink model sums the forces on the body and suspension masses based on Newton's laws, and integrates the accelerations to obtain velocities and positions over time.
This document presents a simulation and validation of a cascade refrigeration system. It consists of two conventional vapor compression systems coupled through a cascade condenser. One uses CO2 as the refrigerant for low temperatures around -30C, while the other uses R404A at higher temperatures. The document describes simulating each system individually and comparing the heat loads calculated when each is run as an evaporator or condenser. It also describes an experimental analysis using a high temperature system with variable capacity compressors and primary/secondary condensers. The simulation tool predicted the COP with an average error of 4.4% compared to experimental results, validating the simulation approach.
This document discusses using MATLAB to generate a sine wave with minimal computational complexity. It shows that a sine wave can be generated with just three lines of code by plotting x values from 0.1 to 10 against sine of x. This demonstrates MATLAB's simplicity and power as an engineering tool.
This document discusses MATLAB and provides an introduction for non-technical audiences. It covers MATLAB's history, strengths, and weaknesses. MATLAB was developed in the 1970s to provide access to linear algebra subroutines without requiring Fortran knowledge. It has since grown to be useful for students, engineers, and scientists by allowing easy analysis of systems, solving of complex equations, and multi-disciplinary research through its built-in toolboxes and simulation capabilities. However, it is not a general purpose language and is slower than compiled languages.
SIMULATION OF THERMODYNAMIC ANALYSIS OF CASCADE REFRIGERATION SYSTEM WITH ALT...IAEME Publication
This document summarizes a study that analyzes the thermodynamic performance of a cascade refrigeration system using various alternative refrigerant pairs. The study evaluates 15 different refrigerant pairs for the higher and lower temperature circuits. It assumes 5°C subcooling and 10°C superheating, varies the higher circuit condenser temperature from 30-50°C and lower circuit evaporator from -70 to -50°C. The analysis finds that COP increases with higher evaporator temperature but decreases with higher condenser temperature for all pairs. It also finds that mass flow and compressor work increase with both higher evaporator and condenser temperatures. The best performing pair is R134a-R170 with the highest COP and lowest mass flow,
MATLAB is a matrix laboratory software package for numerical computation and visualization. It provides functions and tools for matrix manipulation, plotting and visualization, implementation of algorithms, data analysis, and numerical solution of problems. MATLAB has a programming language and interactive environment for algorithm development, data visualization, data analysis and numeric computation. It supports matrix and array operations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages.
K10854 Experimental evaluation of cascade refrigeration plantShraddhey Bhandari
The document summarizes several experiments on cascade refrigeration systems using different refrigerant pairs. The first experiment evaluated a CO2 and NH3 system for freezing applications, finding the optimum CO2 condensing temperature was within 2.4% of published correlations. A second experiment analyzed a R134a and CO2 system, determining compressor performance, temperatures, cooling capacity, and COPs of the individual and overall systems. A third experiment used an R22/R404A pair to determine the optimal condensing temperature of the low-temperature circuit by evaluating the individual and global COPs.
This document provides an introduction to Flexible AC Transmission Systems (FACTS). It discusses why transmission interconnections are needed, including to minimize generation and fuel costs and supply electricity at minimum cost. It also explores if the full potential of interconnections can be used and describes opportunities for FACTS technology to control power flow and enhance transmission line usage. Some key limitations on transmission line loading capability like thermal, dielectric, and stability limits are also summarized.
The document provides an overview of MATLAB, including what it is used for, its graphical user interface, help features, toolboxes, and how to connect to other programs. MATLAB is a numerical computing environment and programming language. It was originally designed for matrix manipulations but has been expanded to include tools for data analysis, signal processing, optimization, and more. Key aspects of MATLAB covered in the document include its command-line interface, workspace, command history, help system, built-in functions, matrices, plotting capabilities, and toolboxes for specialized tasks.
Presentation of Refrigeration SimulationShafiul Munir
This presentation is the aftermath of a laboratory experiment to understand the refrigeration cycles and functions in detail. It also shows the various uses and modifications refrigeration system accounts to.
Signals and systems with matlab computing and simulink modelingvotasugs567
This document provides a summary of the book "Signals and Systems with MATLAB® Computing and Simulink® Modeling, Fourth Edition" by Steven T. Karris. The book covers topics such as elementary signals, Laplace transforms, inverse Laplace transforms, circuit analysis using Laplace transforms, state variables, impulse response, Fourier series, and discrete-time signals. It includes step-by-step procedures for designing analog and digital filters and uses MATLAB and Simulink for examples and applications.
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
MATLAB Programs For Beginners. | Abhi SharmaAbee Sharma
This is MATLAB's 10 most easy & most basic programs that I's supposed to submit in my practicals. In this document I've complied 10 MATLAB programs from basic to advanced through intermediate levels, But overall they are for beginners only. It's only a 26 pages doc. for academic purposes. well, What else a student can offer you, huh? LOLz
This document discusses parallel computing with MATLAB. It introduces MATLAB and parallel computing concepts. It then covers how MATLAB can be used for parallel computing on multi-core systems and distributed computing servers. It discusses parallel commands in MATLAB like matlabpool, parfor, pmode, and spmd. It also demonstrates how to test the efficiency of parallel code and provides an example comparing the execution times of serial and parallel prime number calculation codes.
MATLAB is a numerical computing environment and programming language developed in the 1970s. It was originally designed for matrix computations but has grown to include tools for data analysis, visualization, and GUI design. MATLAB allows both numeric calculations and programming and is commonly used in engineering, science, and mathematics applications. It includes toolboxes for tasks like signal processing, control systems, and computer vision.
Here are the key points about scalar-matrix addition in MATLAB:
- a is a scalar (single value)
- b is a matrix (2D array)
- To add a scalar to a matrix, MATLAB adds the scalar to each element of the matrix
- c = b + a performs element-wise addition, adding the value of a (which is 3) to each element of b
- The result c is the matrix b with 3 added to each element
So c would be:
c =
4 5 6
7 8 9
Scalar-matrix operations in MATLAB perform the operation on each element of the matrix.
MATLAB is a matrix-based programming language used for numerical computations, data analysis, and visualization. It allows matrix manipulations, functions for computation and visualization, toolboxes for different applications, and integrated development environment for programming. MATLAB can be used for engineering and scientific calculations with graphical output. It has built-in functions, user-defined functions, 2D and 3D graphics capabilities, GUI tools, and interfaces with other languages like C and Fortran.
131010 jim cordy - submodel pattern extraction for simulink modelsPtidej Team
This document discusses submodel pattern extraction for Simulink models. It introduces Model Pattern Engineering (MPE) which aims to discover, catalogue and formalize submodel patterns. MPE is inspired by prior work on detecting near-miss clones in code. The document outlines challenges in adapting near-miss clone detection techniques from code to models. It describes the Simone tool, which uses techniques from the NiCad near-miss clone detector adapted to work on Simulink models. Simone addresses challenges through agile parsing, filtering irrelevant elements, and topological sorting of model elements.
This document discusses integrating C/C++ code with MATLAB using MEX files. MEX files allow calling C/C++ functions from MATLAB for increased computation speed compared to MATLAB code. MEX files contain a gateway routine called mexFunction that interacts with MATLAB and subroutines containing the C/C++ code. The document explains how to write MEX files, use MATLAB data structures like mxArrays, call built-in MATLAB functions, and compile and use the resulting MEX binary file.
1. This document describes the modeling of a quarter-car suspension system using Simulink to analyze the system's response.
2. Key parameters of the suspension system are provided, including spring and damping constants for the suspension and tire.
3. The Simulink model sums the forces on the body and suspension masses based on Newton's laws, and integrates the accelerations to obtain velocities and positions over time.
This document presents a simulation and validation of a cascade refrigeration system. It consists of two conventional vapor compression systems coupled through a cascade condenser. One uses CO2 as the refrigerant for low temperatures around -30C, while the other uses R404A at higher temperatures. The document describes simulating each system individually and comparing the heat loads calculated when each is run as an evaporator or condenser. It also describes an experimental analysis using a high temperature system with variable capacity compressors and primary/secondary condensers. The simulation tool predicted the COP with an average error of 4.4% compared to experimental results, validating the simulation approach.
This document discusses using MATLAB to generate a sine wave with minimal computational complexity. It shows that a sine wave can be generated with just three lines of code by plotting x values from 0.1 to 10 against sine of x. This demonstrates MATLAB's simplicity and power as an engineering tool.
This document discusses MATLAB and provides an introduction for non-technical audiences. It covers MATLAB's history, strengths, and weaknesses. MATLAB was developed in the 1970s to provide access to linear algebra subroutines without requiring Fortran knowledge. It has since grown to be useful for students, engineers, and scientists by allowing easy analysis of systems, solving of complex equations, and multi-disciplinary research through its built-in toolboxes and simulation capabilities. However, it is not a general purpose language and is slower than compiled languages.
SIMULATION OF THERMODYNAMIC ANALYSIS OF CASCADE REFRIGERATION SYSTEM WITH ALT...IAEME Publication
This document summarizes a study that analyzes the thermodynamic performance of a cascade refrigeration system using various alternative refrigerant pairs. The study evaluates 15 different refrigerant pairs for the higher and lower temperature circuits. It assumes 5°C subcooling and 10°C superheating, varies the higher circuit condenser temperature from 30-50°C and lower circuit evaporator from -70 to -50°C. The analysis finds that COP increases with higher evaporator temperature but decreases with higher condenser temperature for all pairs. It also finds that mass flow and compressor work increase with both higher evaporator and condenser temperatures. The best performing pair is R134a-R170 with the highest COP and lowest mass flow,
MATLAB is a matrix laboratory software package for numerical computation and visualization. It provides functions and tools for matrix manipulation, plotting and visualization, implementation of algorithms, data analysis, and numerical solution of problems. MATLAB has a programming language and interactive environment for algorithm development, data visualization, data analysis and numeric computation. It supports matrix and array operations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages.
K10854 Experimental evaluation of cascade refrigeration plantShraddhey Bhandari
The document summarizes several experiments on cascade refrigeration systems using different refrigerant pairs. The first experiment evaluated a CO2 and NH3 system for freezing applications, finding the optimum CO2 condensing temperature was within 2.4% of published correlations. A second experiment analyzed a R134a and CO2 system, determining compressor performance, temperatures, cooling capacity, and COPs of the individual and overall systems. A third experiment used an R22/R404A pair to determine the optimal condensing temperature of the low-temperature circuit by evaluating the individual and global COPs.
This document provides an introduction to Flexible AC Transmission Systems (FACTS). It discusses why transmission interconnections are needed, including to minimize generation and fuel costs and supply electricity at minimum cost. It also explores if the full potential of interconnections can be used and describes opportunities for FACTS technology to control power flow and enhance transmission line usage. Some key limitations on transmission line loading capability like thermal, dielectric, and stability limits are also summarized.
The document provides an overview of MATLAB, including what it is used for, its graphical user interface, help features, toolboxes, and how to connect to other programs. MATLAB is a numerical computing environment and programming language. It was originally designed for matrix manipulations but has been expanded to include tools for data analysis, signal processing, optimization, and more. Key aspects of MATLAB covered in the document include its command-line interface, workspace, command history, help system, built-in functions, matrices, plotting capabilities, and toolboxes for specialized tasks.
Presentation of Refrigeration SimulationShafiul Munir
This presentation is the aftermath of a laboratory experiment to understand the refrigeration cycles and functions in detail. It also shows the various uses and modifications refrigeration system accounts to.
Signals and systems with matlab computing and simulink modelingvotasugs567
This document provides a summary of the book "Signals and Systems with MATLAB® Computing and Simulink® Modeling, Fourth Edition" by Steven T. Karris. The book covers topics such as elementary signals, Laplace transforms, inverse Laplace transforms, circuit analysis using Laplace transforms, state variables, impulse response, Fourier series, and discrete-time signals. It includes step-by-step procedures for designing analog and digital filters and uses MATLAB and Simulink for examples and applications.
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfMalak Abu Hammad
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Speck&Tech
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!SOFTTECHHUB
As the digital landscape continually evolves, operating systems play a critical role in shaping user experiences and productivity. The launch of Nitrux Linux 3.5.0 marks a significant milestone, offering a robust alternative to traditional systems such as Windows 11. This article delves into the essence of Nitrux Linux 3.5.0, exploring its unique features, advantages, and how it stands as a compelling choice for both casual users and tech enthusiasts.
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIVladimir Iglovikov, Ph.D.
Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
This presentation delves into the journey of Albumentations.ai, a highly successful open-source library for data augmentation.
Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentations
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/building-and-scaling-ai-applications-with-the-nx-ai-manager-a-presentation-from-network-optix/
Robin van Emden, Senior Director of Data Science at Network Optix, presents the “Building and Scaling AI Applications with the Nx AI Manager,” tutorial at the May 2024 Embedded Vision Summit.
In this presentation, van Emden covers the basics of scaling edge AI solutions using the Nx tool kit. He emphasizes the process of developing AI models and deploying them globally. He also showcases the conversion of AI models and the creation of effective edge AI pipelines, with a focus on pre-processing, model conversion, selecting the appropriate inference engine for the target hardware and post-processing.
van Emden shows how Nx can simplify the developer’s life and facilitate a rapid transition from concept to production-ready applications.He provides valuable insights into developing scalable and efficient edge AI solutions, with a strong focus on practical implementation.
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024Neo4j
Neha Bajwa, Vice President of Product Marketing, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.