Slides presented at the the eight International Conference on Chemical & Process Engineering in the Island of Ischia, Gulf of Naples, Italy (ICheaP-8) concerning LIBPF (the LIBrary for Process Flowsheeting)
This document describes the development of process simulation software for the polymer industry using object-oriented design and CAPE-OPEN standards. It discusses refactoring an existing Fortran code for simulating methyl methacrylate polymerization into logical objects and developing a wrapper to allow integration with other equipment models according to CAPE-OPEN. The conclusions highlight benefits like reduced code redundancy and improved maintenance, while suggestions focus on optimizing numerical computations for speed without sacrificing flexibility.
The document discusses thread management in mashup execution platforms. It introduces different types of service components - call-response, polling, and callback. It then presents a case study on polling services, comparing a trivial one-thread-per-service solution to a proposed solution of one monitoring thread plus a thread pool for each service. The proposed solution uses system resources more efficiently by reducing memory consumption and response times compared to the trivial solution. Future work areas discussed include analyzing interactions with the JVM memory management and effects of garbage collection on performance.
The document describes a methodology for designing dynamic reconfigurable multi-FPGA systems. It presents an intermediate representation for hierarchical circuits and a design flow with three main phases: design extraction from VHDL, static global layout partitioning and placement, and reuse through dynamic reconfiguration to minimize delays. Experimental results validate partitioning, placement and blocks reuse approaches. Future work includes improving clustering metrics, time estimation, and adding routing algorithms.
This thesis proposes a design methodology for dynamically reconfigurable multi-FPGA systems. The methodology includes three main phases: design extraction from VHDL, static global layout partitioning and placement, and reuse of blocks through dynamic reconfiguration when needed to minimize delays. The major contribution is a multi-FPGA design flow that exploits dynamic reconfiguration to reuse blocks and reduce the application area requirements. Experimental results show the proposed approaches partition and place designs efficiently. Future work includes improving clustering metrics, routing algorithms, and time estimation for dynamic block reuse.
Collaborative editing of emf ecore meta models and models conflict detection,...Amanuel Alemayehu
This document summarizes a research paper presented at the MODELSWARD 2014 conference on collaborative editing of EMF/Ecore meta-models and models. It describes the DiCoMEF framework for managing collaboration, conflict detection, and reconciliation when multiple users concurrently edit models and meta-models. DiCoMEF uses a centralized controller approach where editors make modification requests to a controller, who approves or rejects changes. It detects conflicts using operation-based differencing and provides reconciliation by prioritizing propagated changes. The framework was presented as an improvement over line-based tools by addressing models' graph structure, though scaling remains a challenge.
This document describes the development of process simulation software for the polymer industry using object-oriented design and CAPE-OPEN standards. It discusses refactoring an existing Fortran code for simulating methyl methacrylate polymerization into logical objects and developing a wrapper to allow integration with other equipment models according to CAPE-OPEN. The conclusions highlight benefits like reduced code redundancy and improved maintenance, while suggestions focus on optimizing numerical computations for speed without sacrificing flexibility.
The document discusses thread management in mashup execution platforms. It introduces different types of service components - call-response, polling, and callback. It then presents a case study on polling services, comparing a trivial one-thread-per-service solution to a proposed solution of one monitoring thread plus a thread pool for each service. The proposed solution uses system resources more efficiently by reducing memory consumption and response times compared to the trivial solution. Future work areas discussed include analyzing interactions with the JVM memory management and effects of garbage collection on performance.
The document describes a methodology for designing dynamic reconfigurable multi-FPGA systems. It presents an intermediate representation for hierarchical circuits and a design flow with three main phases: design extraction from VHDL, static global layout partitioning and placement, and reuse through dynamic reconfiguration to minimize delays. Experimental results validate partitioning, placement and blocks reuse approaches. Future work includes improving clustering metrics, time estimation, and adding routing algorithms.
This thesis proposes a design methodology for dynamically reconfigurable multi-FPGA systems. The methodology includes three main phases: design extraction from VHDL, static global layout partitioning and placement, and reuse of blocks through dynamic reconfiguration when needed to minimize delays. The major contribution is a multi-FPGA design flow that exploits dynamic reconfiguration to reuse blocks and reduce the application area requirements. Experimental results show the proposed approaches partition and place designs efficiently. Future work includes improving clustering metrics, routing algorithms, and time estimation for dynamic block reuse.
Collaborative editing of emf ecore meta models and models conflict detection,...Amanuel Alemayehu
This document summarizes a research paper presented at the MODELSWARD 2014 conference on collaborative editing of EMF/Ecore meta-models and models. It describes the DiCoMEF framework for managing collaboration, conflict detection, and reconciliation when multiple users concurrently edit models and meta-models. DiCoMEF uses a centralized controller approach where editors make modification requests to a controller, who approves or rejects changes. It detects conflicts using operation-based differencing and provides reconciliation by prioritizing propagated changes. The framework was presented as an improvement over line-based tools by addressing models' graph structure, though scaling remains a challenge.
Phenoflow: A Microservice Architecture for Portable Workflow-based Phenotype ...Martin Chapman
The document describes Phenoflow, a microservice architecture for defining phenotypes in a structured workflow-based model to improve portability. The model defines phenotypes as sequential steps with multiple descriptions at the abstract layer and specifies entity metadata at the functional layer. Phenoflow is an online library that generates executable Common Workflow Language implementations from definitions. Evaluating diabetes and COVID-19 phenotypes showed the structured definitions improved portability over traditional logic/code by reducing clinical and programming expertise requirements. Future work includes enhancing the library search and expanding available implementation modules.
The document discusses key language changes in Java 8 including the shift from imperative to functional programming and sequential to parallel operations. It introduces lambda expressions, method references, and streams which allow for more concise coding of functional operations and parallel processing of collections. The document also provides demonstrations and guidance on migrating code to Java 8 features through the NetBeans IDE.
This is a presentation by Prof. Anne Elster at the International Workshop on Open Source Supercomputing held in conjunction with the 2017 ISC High Performance Computing Conference.
The document discusses React patterns and hooks. It covers topics like inheritance, composition, mixins, render props, higher order components (HOCs), and React hooks. Some key points:
- Inheritance and composition are approaches to code reuse in object-oriented programming. React uses composition over inheritance.
- Mixins were introduced in 2015 for code reuse but are now deprecated due to issues. Render props and HOCs are preferred patterns.
- Render props and HOCs allow code and state to be shared across components. Render props have fewer levels of nesting while HOCs are better for applying multiple concerns.
- Hooks were introduced to overcome class component limitations and support functional components with local state and lif
Machine Learning At Speed: Operationalizing ML For Real-Time Data StreamsLightbend
Audience: Architects, Data Scientists, Developers
Technical level: Introductory
From home intrusion detection, to self-driving cars, to keeping data center operations healthy, Machine Learning (ML) has become one of the hottest topics in software engineering today. While much of the focus has been on the actual creation of the algorithms used in ML, the less talked-about challenge is how to serve these models in production, often utilizing real-time streaming data.
The traditional approach to model serving is to treat the model as code, which means that ML implementation has to be continually adapted for model serving. As the amount of machine learning tools and techniques grows, the efficiency of such an approach is becoming more questionable. Additionally, machine learning and model serving are driven by very different quality of service requirements; while machine learning is typically batch, dealing with scalability and processing power, model serving is mostly concerned with performance and stability.
In this webinar with O’Reilly author and Lightbend Principal Architect, Boris Lublinsky, we will define an alternative approach to model serving, based on treating the model itself as data. Using popular frameworks like Akka Streams and Apache Flink, Boris will review how to implement this approach, explaining how it can help you:
* Achieve complete decoupling between the model implementation for machine learning and model serving, enforcing better standardization of your model serving implementation.
* Enable dynamic updates of the served model without having to restart the system.
* Utilize Tensorflow and PMML as model representation and their usage for building “real time updatable” model serving architecture.
LIBPF: A LIBRARY FOR PROCESS FLOWSHEETING IN C++libpf
1) LIBPF is a C++ library for process flowsheeting that allows modeling of continuous processes through a directed graph approach.
2) It aims to address challenges in modeling continuous processes for industry, including customization, integration, reliability, and maintainability.
3) LIBPF provides capabilities for modeling common unit operations and properties through a graph-based approach implemented in portable, open-source C++.
Software development effort reduction with Co-oplbergmans
This talks explains the motivations for the Co-op technology: what are the challenges it addresses, in particular focusing on reducing accidental complexity, where it comes from, and a general vision on how to resolve it. Then we continue to show practical application of Co-op, including experience figures from large-scale application of a previous generation of this technology. Show a little bit about its realization, and conclude with an evaluation of the technology.
Nocito Gobel Unh Introduction To Engineering Project BasedIntro Engineering
This document provides an overview of the Introduction to Engineering project-based course at the University of New Haven. The key points are:
1. The course uses a project-based approach with team projects, lectures as needed, and focuses on exploratory engineering concepts and developing analytical and professional skills.
2. The course outcomes include recognizing differences in engineering disciplines, effective teamwork, communicating technical information, applying the engineering design process, and demonstrating basic concepts in materials, electrical circuits, thermodynamics, mechanics, and systems.
3. The course consists of 4 modules involving structural systems, solid modeling, fuel cells, and mobile robotics, each with a challenge for students to work on as a team.
Open Archives Initiative Object Reuse and Exchangelagoze
This document discusses infrastructure to support new models of scholarly publication by enabling interoperability across repositories through common data modeling and services. It proposes building blocks like repositories, digital objects, a common data model, serialization formats, and core services. This would allow components like publications and data to move across repositories and workflows, facilitating reuse and new value-added services that expose the scholarly communication process.
This document provides an introduction to design patterns, including their motivation, history, definition, categories, and examples. Some key points:
- Design patterns solve common programming problems by describing reusable solutions that can be adapted for different situations.
- Common categories include creational, structural, and behavioral patterns. Example patterns discussed are Singleton, Decorator, Abstract Factory.
- Design patterns speed up development, promote code reuse, and make software more robust, maintainable and extensible. Resources for further information on design patterns are provided.
A Recommender System for Refining Ekeko/X TransformationCoen De Roover
This document discusses an automated recommender system for refining Ekeko/X transformations. It begins by introducing logic meta-programming and how it allows querying a "database" of program information using logic relations. Templates with meta-variables and directives are used to specify transformations, and formal operators define ways to mutate templates. A genetic search evaluates templates based on precision, recall, partial matches, and directive usage to recommend refinements for better specifying transformations.
MLOps pipelines using MLFlow - From training to productionFabian Hadiji
This talk was given at the Cologne AI and Machine Learning Meetup on April 13, 2023 (https://www.meetup.com/de-DE/cologne-ai-and-machine-learning-meetup/events/291513393/) by Dr. Andreas Weiden, Co-Lead Cloud / Data Engineering at skillbyte: MLOps pipelines using MLFlow - From training to production
In this talk we explore the world of MLOps pipelines and how MLFlow can be used to facilitate workflows for getting your machine learning models from training to production. We will briefly delve into the tracking aspects of MLFlow and how to store experiments and runs. Next, we will move on to an actual use case that involves managing artefacts generated by multiple training pipelines running on a daily schedule. These artefacts are used in prediction services but also in managed vector search engines such as ElasticSearch and Google VertexAI. A simple microservice that polls the MLFlow registry is used to update both REST-APIs running in Kubernetes and to ingest the models into the vector search services. Finally, we will compare different alternatives that were considered.
This document provides an overview of a course on operational amplifiers taught at MIT. The course uses operational amplifiers as a vehicle to teach circuit design techniques and feedback concepts. It covers topics such as direct-coupled amplifiers, high-gain amplifier stages, operational amplifier design, applications, and integrated circuit operational amplifiers. The course is offered in two versions - one focused more on circuits and applications, and one focused more on feedback concepts. The document outlines the course content and objectives.
Slide deck to give some theoretical background before stepping into the hands-on tutorial at http://sdnhub.org/tutorials/opendaylight. Compared to earlier version of this slide deck, this tutorial slide deck has been updated to focus more on MD-SAL and YANG modeled app development.
The document discusses the steps involved in component-level design in software engineering. It explains that component-level design defines the internal data structures, algorithms, interfaces and communication mechanisms for each software component. It then covers key aspects of component-level design like defining components and their views, applying basic design principles, elaborating classes, modeling persistent data sources, behavior and deployment. The document emphasizes that component-level design is an iterative process that involves reconsidering alternatives to create an accurate and consistent model.
This presentation describes some key features of Scala uses in the creation of machine learning algorithms:
1 Functorial definition of tensors for learning non-linear models (manifolds)
2. Monads to compose of explicit kernel functions in Euclidean space
3. Implicit class to extends Scala standard library
4. Stackable traits and dependency injection to build formal models and dynamic workflows
5. Tail recursion to implementation dynamic programming techniques
6. Streaming to reduce memory consumption for big data
7. Control of back pressure in data flows
http://patricknicolas.blogspot.com
http://bit.ly/12GjRu9
The document describes an Android application architecture that was developed. It includes consuming a REST API with Retrofit, parsing response data with Jackson, communicating between components using an event bus (Otto was chosen), and ensuring events are received on the main thread. The architecture abstracts away network calls, handles different event types through inheritance, and provides a unified interface through a BusManager facade.
This document summarizes a presentation about serving machine learning models with Apache Flink. It discusses Flink's ML roadmap, modeling concepts, and model serving considerations like customer needs, governance, and the model lifecycle. It proposes using Flink's streaming capabilities to dynamically update models without interruption. A prototype exploits Flink joins to merge prediction requests with cached models. Next steps include finalizing specifications, integrating TensorFlow and PMML models, and addressing governance.
RuCORD: Rule-based Composite Operation Recovering and Detection to Support Co...Amanuel Alemayehu
This document discusses RuCORD, a framework for recovering and detecting composite operations to support cooperative editing of models. It introduces the challenges of collaborative modeling such as merge conflicts and model migration. RuCORD uses rule-based techniques to recover high-level composite operations from low-level edits, making modifications easier for users to understand. The framework allows isolated work with mainline and branch concepts to manage collaboration. Modifications are overseen by a human controller whose role is flexible. Fully utilizing domain-specific modeling tools requires ensuring collaboration among them.
Phenoflow: A Microservice Architecture for Portable Workflow-based Phenotype ...Martin Chapman
The document describes Phenoflow, a microservice architecture for defining phenotypes in a structured workflow-based model to improve portability. The model defines phenotypes as sequential steps with multiple descriptions at the abstract layer and specifies entity metadata at the functional layer. Phenoflow is an online library that generates executable Common Workflow Language implementations from definitions. Evaluating diabetes and COVID-19 phenotypes showed the structured definitions improved portability over traditional logic/code by reducing clinical and programming expertise requirements. Future work includes enhancing the library search and expanding available implementation modules.
The document discusses key language changes in Java 8 including the shift from imperative to functional programming and sequential to parallel operations. It introduces lambda expressions, method references, and streams which allow for more concise coding of functional operations and parallel processing of collections. The document also provides demonstrations and guidance on migrating code to Java 8 features through the NetBeans IDE.
This is a presentation by Prof. Anne Elster at the International Workshop on Open Source Supercomputing held in conjunction with the 2017 ISC High Performance Computing Conference.
The document discusses React patterns and hooks. It covers topics like inheritance, composition, mixins, render props, higher order components (HOCs), and React hooks. Some key points:
- Inheritance and composition are approaches to code reuse in object-oriented programming. React uses composition over inheritance.
- Mixins were introduced in 2015 for code reuse but are now deprecated due to issues. Render props and HOCs are preferred patterns.
- Render props and HOCs allow code and state to be shared across components. Render props have fewer levels of nesting while HOCs are better for applying multiple concerns.
- Hooks were introduced to overcome class component limitations and support functional components with local state and lif
Machine Learning At Speed: Operationalizing ML For Real-Time Data StreamsLightbend
Audience: Architects, Data Scientists, Developers
Technical level: Introductory
From home intrusion detection, to self-driving cars, to keeping data center operations healthy, Machine Learning (ML) has become one of the hottest topics in software engineering today. While much of the focus has been on the actual creation of the algorithms used in ML, the less talked-about challenge is how to serve these models in production, often utilizing real-time streaming data.
The traditional approach to model serving is to treat the model as code, which means that ML implementation has to be continually adapted for model serving. As the amount of machine learning tools and techniques grows, the efficiency of such an approach is becoming more questionable. Additionally, machine learning and model serving are driven by very different quality of service requirements; while machine learning is typically batch, dealing with scalability and processing power, model serving is mostly concerned with performance and stability.
In this webinar with O’Reilly author and Lightbend Principal Architect, Boris Lublinsky, we will define an alternative approach to model serving, based on treating the model itself as data. Using popular frameworks like Akka Streams and Apache Flink, Boris will review how to implement this approach, explaining how it can help you:
* Achieve complete decoupling between the model implementation for machine learning and model serving, enforcing better standardization of your model serving implementation.
* Enable dynamic updates of the served model without having to restart the system.
* Utilize Tensorflow and PMML as model representation and their usage for building “real time updatable” model serving architecture.
LIBPF: A LIBRARY FOR PROCESS FLOWSHEETING IN C++libpf
1) LIBPF is a C++ library for process flowsheeting that allows modeling of continuous processes through a directed graph approach.
2) It aims to address challenges in modeling continuous processes for industry, including customization, integration, reliability, and maintainability.
3) LIBPF provides capabilities for modeling common unit operations and properties through a graph-based approach implemented in portable, open-source C++.
Software development effort reduction with Co-oplbergmans
This talks explains the motivations for the Co-op technology: what are the challenges it addresses, in particular focusing on reducing accidental complexity, where it comes from, and a general vision on how to resolve it. Then we continue to show practical application of Co-op, including experience figures from large-scale application of a previous generation of this technology. Show a little bit about its realization, and conclude with an evaluation of the technology.
Nocito Gobel Unh Introduction To Engineering Project BasedIntro Engineering
This document provides an overview of the Introduction to Engineering project-based course at the University of New Haven. The key points are:
1. The course uses a project-based approach with team projects, lectures as needed, and focuses on exploratory engineering concepts and developing analytical and professional skills.
2. The course outcomes include recognizing differences in engineering disciplines, effective teamwork, communicating technical information, applying the engineering design process, and demonstrating basic concepts in materials, electrical circuits, thermodynamics, mechanics, and systems.
3. The course consists of 4 modules involving structural systems, solid modeling, fuel cells, and mobile robotics, each with a challenge for students to work on as a team.
Open Archives Initiative Object Reuse and Exchangelagoze
This document discusses infrastructure to support new models of scholarly publication by enabling interoperability across repositories through common data modeling and services. It proposes building blocks like repositories, digital objects, a common data model, serialization formats, and core services. This would allow components like publications and data to move across repositories and workflows, facilitating reuse and new value-added services that expose the scholarly communication process.
This document provides an introduction to design patterns, including their motivation, history, definition, categories, and examples. Some key points:
- Design patterns solve common programming problems by describing reusable solutions that can be adapted for different situations.
- Common categories include creational, structural, and behavioral patterns. Example patterns discussed are Singleton, Decorator, Abstract Factory.
- Design patterns speed up development, promote code reuse, and make software more robust, maintainable and extensible. Resources for further information on design patterns are provided.
A Recommender System for Refining Ekeko/X TransformationCoen De Roover
This document discusses an automated recommender system for refining Ekeko/X transformations. It begins by introducing logic meta-programming and how it allows querying a "database" of program information using logic relations. Templates with meta-variables and directives are used to specify transformations, and formal operators define ways to mutate templates. A genetic search evaluates templates based on precision, recall, partial matches, and directive usage to recommend refinements for better specifying transformations.
MLOps pipelines using MLFlow - From training to productionFabian Hadiji
This talk was given at the Cologne AI and Machine Learning Meetup on April 13, 2023 (https://www.meetup.com/de-DE/cologne-ai-and-machine-learning-meetup/events/291513393/) by Dr. Andreas Weiden, Co-Lead Cloud / Data Engineering at skillbyte: MLOps pipelines using MLFlow - From training to production
In this talk we explore the world of MLOps pipelines and how MLFlow can be used to facilitate workflows for getting your machine learning models from training to production. We will briefly delve into the tracking aspects of MLFlow and how to store experiments and runs. Next, we will move on to an actual use case that involves managing artefacts generated by multiple training pipelines running on a daily schedule. These artefacts are used in prediction services but also in managed vector search engines such as ElasticSearch and Google VertexAI. A simple microservice that polls the MLFlow registry is used to update both REST-APIs running in Kubernetes and to ingest the models into the vector search services. Finally, we will compare different alternatives that were considered.
This document provides an overview of a course on operational amplifiers taught at MIT. The course uses operational amplifiers as a vehicle to teach circuit design techniques and feedback concepts. It covers topics such as direct-coupled amplifiers, high-gain amplifier stages, operational amplifier design, applications, and integrated circuit operational amplifiers. The course is offered in two versions - one focused more on circuits and applications, and one focused more on feedback concepts. The document outlines the course content and objectives.
Slide deck to give some theoretical background before stepping into the hands-on tutorial at http://sdnhub.org/tutorials/opendaylight. Compared to earlier version of this slide deck, this tutorial slide deck has been updated to focus more on MD-SAL and YANG modeled app development.
The document discusses the steps involved in component-level design in software engineering. It explains that component-level design defines the internal data structures, algorithms, interfaces and communication mechanisms for each software component. It then covers key aspects of component-level design like defining components and their views, applying basic design principles, elaborating classes, modeling persistent data sources, behavior and deployment. The document emphasizes that component-level design is an iterative process that involves reconsidering alternatives to create an accurate and consistent model.
This presentation describes some key features of Scala uses in the creation of machine learning algorithms:
1 Functorial definition of tensors for learning non-linear models (manifolds)
2. Monads to compose of explicit kernel functions in Euclidean space
3. Implicit class to extends Scala standard library
4. Stackable traits and dependency injection to build formal models and dynamic workflows
5. Tail recursion to implementation dynamic programming techniques
6. Streaming to reduce memory consumption for big data
7. Control of back pressure in data flows
http://patricknicolas.blogspot.com
http://bit.ly/12GjRu9
The document describes an Android application architecture that was developed. It includes consuming a REST API with Retrofit, parsing response data with Jackson, communicating between components using an event bus (Otto was chosen), and ensuring events are received on the main thread. The architecture abstracts away network calls, handles different event types through inheritance, and provides a unified interface through a BusManager facade.
This document summarizes a presentation about serving machine learning models with Apache Flink. It discusses Flink's ML roadmap, modeling concepts, and model serving considerations like customer needs, governance, and the model lifecycle. It proposes using Flink's streaming capabilities to dynamically update models without interruption. A prototype exploits Flink joins to merge prediction requests with cached models. Next steps include finalizing specifications, integrating TensorFlow and PMML models, and addressing governance.
RuCORD: Rule-based Composite Operation Recovering and Detection to Support Co...Amanuel Alemayehu
This document discusses RuCORD, a framework for recovering and detecting composite operations to support cooperative editing of models. It introduces the challenges of collaborative modeling such as merge conflicts and model migration. RuCORD uses rule-based techniques to recover high-level composite operations from low-level edits, making modifications easier for users to understand. The framework allows isolated work with mainline and branch concepts to manage collaboration. Modifications are overseen by a human controller whose role is flexible. Fully utilizing domain-specific modeling tools requires ensuring collaboration among them.
Similar to Object-oriented modelling applied to hybrid unit operations (20)
AI 101: An Introduction to the Basics and Impact of Artificial IntelligenceIndexBug
Imagine a world where machines not only perform tasks but also learn, adapt, and make decisions. This is the promise of Artificial Intelligence (AI), a technology that's not just enhancing our lives but revolutionizing entire industries.
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.
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
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.
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
Infrastructure Challenges in Scaling RAG with Custom AI modelsZilliz
Building Retrieval-Augmented Generation (RAG) systems with open-source and custom AI models is a complex task. This talk explores the challenges in productionizing RAG systems, including retrieval performance, response synthesis, and evaluation. We’ll discuss how to leverage open-source models like text embeddings, language models, and custom fine-tuned models to enhance RAG performance. Additionally, we’ll cover how BentoML can help orchestrate and scale these AI components efficiently, ensuring seamless deployment and management of RAG systems in the cloud.
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
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.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
Full-RAG: A modern architecture for hyper-personalizationZilliz
Mike Del Balso, CEO & Co-Founder at Tecton, presents "Full RAG," a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
Mind map of terminologies used in context of Generative AI
Object-oriented modelling applied to hybrid unit operations
1. Object-oriented modelling applied to hybrid unit operations Paolo Greppi , Barbara Bosio, Elisabetta Arato Department of Civil Environmental Architectural Engineering Università degli Studi di Genova ICheaP-8 - The eight International Conference on Chemical & Process Engineering ISCHIA Island Gulf of Naples, Italy - June 24-27 th 2007