Prediction of novel targets using disease association data from Open TargetsEnrico Ferrero
The document summarizes research using disease association data from Open Targets to predict novel drug targets. A positive-unlabeled learning approach was used to train classifiers on features from Open Targets data. The best-performing neural network achieved 71% accuracy on the test set. Predictions were validated through literature mining and showed targets with clearer disease links had higher predictive scores. While limitations exist, the results demonstrate machine learning can aid drug target discovery by predicting targets from gene-disease association data.
Prediction of therapeutic targets using the Open Targets dataEnrico Ferrero
1. The document discusses using machine learning models to predict novel therapeutic targets using gene-disease association data from the Open Targets platform.
2. A neural network model was able to predict therapeutic targets with 71% accuracy on a held-out test set, outperforming random forest, SVM, and gradient boosting models.
3. Predictions were validated through literature text mining, finding a highly significant overlap between predictions and mined therapeutic targets.
Prediction of novel targets using disease association data from Open TargetsEnrico Ferrero
Using gene-disease association data from Open Targets, a machine learning model was developed to predict novel therapeutic targets. A positive-unlabeled learning approach was used to train classifiers on known gene targets and unlabeled genes. The neural network achieved 71% accuracy on the test set. Analysis found that targets with stronger disease evidence were predicted with more accuracy. Literature validation supported many predictions as potential drug targets. The results suggest machine learning can aid automated drug target discovery by predicting targets from gene-disease association data.
Automating drug target discovery with machine learningEnrico Ferrero
1) The document discusses using machine learning to automate drug target discovery by analyzing gene-disease association data from Open Targets.
2) A neural network classifier was able to predict therapeutic targets with 71% accuracy by analyzing features like genetic associations, somatic mutations, animal models, and pathway evidence from Open Targets.
3) The most informative features for prediction were animal models showing disease-relevant phenotypes, dysregulated gene expression in disease tissue, and genetic associations between genes and diseases.
The document describes the scientific method which involves making observations or asking questions, forming hypotheses to explain observations, designing controlled experiments to test hypotheses by systematically changing one variable at a time and analyzing results to determine if evidence supports or disproves the hypothesis, potentially leading to the formation of a scientific theory supported by evidence from repeated experiments.
Leveraging functional genomics analytics for target discoveryEnrico Ferrero
The document discusses how GSK is leveraging functional genomics analytics like RNA-seq, ChIP-seq, and DNase-seq to improve target discovery. It provides examples of projects analyzing disease progression in rheumatoid arthritis, responses to viral infection, and mechanisms of action of neurogenesis compounds. The goal is to better understand diseases, targets, and drugs to reduce late stage clinical trial failures and costs through more rigorous target validation early on. Partnerships with academic institutions are also highlighted.
The document discusses the steps required to perform a systematic review of animal studies. It outlines that a systematic review involves 1) phrasing a clear research question, 2) defining inclusion and exclusion criteria, 3) systematically searching for all original papers on the topic, 4) selecting relevant papers, 5) assessing study quality and validity, 6) extracting data, 7) analyzing results through meta-analysis if possible, and 8) interpreting and presenting the data. The presentation focuses on how to phrase the research question, define criteria, systematically search the literature, assess study quality, and analyze results through meta-analysis to draw overall conclusions.
Prediction of novel targets using disease association data from Open TargetsEnrico Ferrero
The document summarizes research using disease association data from Open Targets to predict novel drug targets. A positive-unlabeled learning approach was used to train classifiers on features from Open Targets data. The best-performing neural network achieved 71% accuracy on the test set. Predictions were validated through literature mining and showed targets with clearer disease links had higher predictive scores. While limitations exist, the results demonstrate machine learning can aid drug target discovery by predicting targets from gene-disease association data.
Prediction of therapeutic targets using the Open Targets dataEnrico Ferrero
1. The document discusses using machine learning models to predict novel therapeutic targets using gene-disease association data from the Open Targets platform.
2. A neural network model was able to predict therapeutic targets with 71% accuracy on a held-out test set, outperforming random forest, SVM, and gradient boosting models.
3. Predictions were validated through literature text mining, finding a highly significant overlap between predictions and mined therapeutic targets.
Prediction of novel targets using disease association data from Open TargetsEnrico Ferrero
Using gene-disease association data from Open Targets, a machine learning model was developed to predict novel therapeutic targets. A positive-unlabeled learning approach was used to train classifiers on known gene targets and unlabeled genes. The neural network achieved 71% accuracy on the test set. Analysis found that targets with stronger disease evidence were predicted with more accuracy. Literature validation supported many predictions as potential drug targets. The results suggest machine learning can aid automated drug target discovery by predicting targets from gene-disease association data.
Automating drug target discovery with machine learningEnrico Ferrero
1) The document discusses using machine learning to automate drug target discovery by analyzing gene-disease association data from Open Targets.
2) A neural network classifier was able to predict therapeutic targets with 71% accuracy by analyzing features like genetic associations, somatic mutations, animal models, and pathway evidence from Open Targets.
3) The most informative features for prediction were animal models showing disease-relevant phenotypes, dysregulated gene expression in disease tissue, and genetic associations between genes and diseases.
The document describes the scientific method which involves making observations or asking questions, forming hypotheses to explain observations, designing controlled experiments to test hypotheses by systematically changing one variable at a time and analyzing results to determine if evidence supports or disproves the hypothesis, potentially leading to the formation of a scientific theory supported by evidence from repeated experiments.
Leveraging functional genomics analytics for target discoveryEnrico Ferrero
The document discusses how GSK is leveraging functional genomics analytics like RNA-seq, ChIP-seq, and DNase-seq to improve target discovery. It provides examples of projects analyzing disease progression in rheumatoid arthritis, responses to viral infection, and mechanisms of action of neurogenesis compounds. The goal is to better understand diseases, targets, and drugs to reduce late stage clinical trial failures and costs through more rigorous target validation early on. Partnerships with academic institutions are also highlighted.
The document discusses the steps required to perform a systematic review of animal studies. It outlines that a systematic review involves 1) phrasing a clear research question, 2) defining inclusion and exclusion criteria, 3) systematically searching for all original papers on the topic, 4) selecting relevant papers, 5) assessing study quality and validity, 6) extracting data, 7) analyzing results through meta-analysis if possible, and 8) interpreting and presenting the data. The presentation focuses on how to phrase the research question, define criteria, systematically search the literature, assess study quality, and analyze results through meta-analysis to draw overall conclusions.
The document outlines the steps of the scientific method which are used to systematically gather knowledge about the world. It explains that the scientific method involves making observations, asking questions, forming hypotheses, performing experiments, analyzing data, and drawing conclusions. Key aspects of the method include identifying independent and dependent variables, stating testable hypotheses, designing experiments to test hypotheses, carefully collecting and analyzing results, and determining if the conclusions drawn from data support or contradict the original hypotheses. The overall goal of using this process is to improve understanding of phenomena through empirical investigation.
The document provides an introduction to science and the scientific method. It defines science as using observation to discover facts and form principles that can be tested. It explains that physical science studies non-living matter, including chemistry which examines interactions between forms of matter, and physics which examines energy and its effects on matter. The scientific method is then described as a step-by-step process scientists use to answer questions, involving asking questions, researching, forming hypotheses, testing, gathering data, analyzing results, and drawing conclusions.
Applications of high-throughput sequencing (HTS) technologies in the pharma i...Enrico Ferrero
High-throughput sequencing (HTS) technologies like RNA-seq, ChIP-seq, and whole-genome bisulfite sequencing (WGBS) are increasingly being used in the pharmaceutical industry to better understand diseases, discover new drug targets, and elucidate drug mechanisms of action. GSK is applying these technologies throughout its drug discovery pipeline, including projects studying disease progression in rheumatoid arthritis, identifying targets from host responses to viral infection, and determining the pathways activated by neurogenesis-inducing compounds. Partnerships with academic institutions further enhance the application of HTS to improve target discovery.
The document outlines the scientific method and provides an example of Francesco Redi's experiment on spontaneous generation. It discusses the 10 main steps of the scientific method: 1) making observations, 2) asking questions, 3) conducting research, 4) stating hypotheses, 5) experimentation, 6) collecting and recording data, 7) analyzing data, 8) drawing conclusions, 9) determining limitations, and 10) publishing results. It then summarizes Redi's experiment which aimed to disprove spontaneous generation through a controlled experiment comparing jars of meat covered and uncovered, observing that maggots only formed on uncovered meat exposed to flies.
The document outlines the key aspects of the scientific method including asking questions, forming hypotheses, designing and running experiments, collecting and analyzing data, and drawing conclusions. It defines important scientific terms like hypothesis, experiment, data, control and experimental groups, and the difference between a hypothesis, theory, and law. The overall process involves making observations, identifying problems or questions, proposing hypotheses, experimentally testing hypotheses, and analyzing results.
The document discusses the scientific method, which is a process used by scientists to investigate questions about the natural world through organized and reliable experiments. There are several versions of the scientific method, but they generally involve identifying a problem, developing a hypothesis to test, designing an experiment to collect data, analyzing the results, and communicating the conclusions. The goal of science is to understand the natural world by proposing explanations that can be tested through examination of evidence in a careful and systematic way.
This document outlines the scientific method process which involves stating a problem, formulating a hypothesis, designing an experiment to test the hypothesis, making observations during the experiment, interpreting the collected data, drawing conclusions based on the data, determining if the results support or falsify the original hypothesis, and reporting or revising the hypothesis based on the findings.
Does preregistration improve the interpretability and credibility of research...Mark Rubin
Rubin, M. (2022, March). Does preregistration improve the interpretability and credibility of research findings? In Research transparency: From preregistration to open access. Erasmus Research Institute of Management Research Transparency Campaign, Erasmus University Rotterdam. [Video recording: https://www.youtube.com/watch?v=xsEoLhQrKNQ&t=1s]
Three well-designed studies found that group cognitive behavioral interventions for individuals at risk of panic disorder can effectively reduce panic and agoraphobic symptoms. The strongest treatment gains came from multi-session group programs that included education, breathing retraining, exposure exercises, and cognitive restructuring. A single-day workshop format was also effective in reducing panic symptoms and risk of panic disorder onset at 6-month follow up. However, brief interventions and unguided online self-help programs showed limited effectiveness. Comprehensive 8-week group treatments or single-day workshops including exposure techniques are recommended.
An East Rockaway, New York, native and a magna cum laude graduate of Boston University, attorney Marc Rovner serves as general counsel and director of business development for BETA Abstract, LLC. He has been recognized by many professional organizations, and earned a 2015 Client Distinction Award given by Martindale-Hubbell on behalf of Lawyers.com. In conjunction with his professional pursuits, Marc Rovner also belongs to the American Bar Association.
This document is a resume for Nicholas Norgaard providing his contact information, skills, professional experience, and education. It summarizes that he has worked in several customer service and sales roles in the golf and sporting goods industries, including at golf courses and Dick's Sporting Goods, where he demonstrated skills in customer service, sales, multi-tasking, and handling unexpected events. He is currently studying Business Administration and expects to graduate in April 2016.
Kimberly Jacobs is seeking a position in healthcare administration or psychology. She has a Bachelor's in Human and Social Service Administration from Bellevue University and an MBA in Healthcare Systems from Grand Canyon University. She is currently attending GCU for a Doctorate in Psychology. Jacobs has over 5 years of experience in healthcare, including positions as an Intake Clinician, High Needs Case Manager, and Director of Social Services at various facilities. She maintains clinical records, assesses clients, develops treatment plans, and provides crisis management. Jacobs aims to increase customer satisfaction and organizational profitability with her goal-oriented and culturally sensitive approach.
Andrew Feinberg is a quality and materials engineer with over 30 years of experience in supply chain management, supplier development, quality assurance, and root cause analysis. He has extensive experience ensuring products meet requirements from low to high volume production. He is Six Sigma Black Belt certified and has led teams that successfully achieved ISO and TS-16949 certifications. Currently he is the lead supplier quality engineer at Orbital ATK responsible for supplier audits, non-conformance resolution, and corrective action implementation.
This document discusses challenges in integrating different types of omics data. It notes that data comes from different experimental sources and levels of resolution, from ecosystems down to individual atoms. It also notes challenges including different data formats, mapping and identifier issues, and statistical analysis of similarity and differences. Integrating such diverse data requires addressing these challenges.
O Papel das Pessoas dos Sensores no Desenvolvimento das Smart Cities: Uma Rev...Italberto Dantas
Nos últimos anos, com o aumento acelerado da população nas grandes cidades do mundo, problemas como poluição do ar, escassez de água e condições de tráfego intenso, tornaram-se muito mais evidentes. Tentando mitigá-los, foi apresentado o conceito de Smart City, que usa tecnologia e recursos humanos para gerenciar os recursos urbanos de forma sustentável. A medida que novas pesquisas científicas sobre este fenômeno são realizadas, fica implícita a importância de ambos, recursos humanos e tecnológicos, no desenvolvimento das Smart Cities. Porém não fica claro qual papel cada um ocupa nas diversas etapas de evolução, as quais uma cidade passa até ser considerada smart. Dado o contexto, neste trabalho utilizou-se o método de revisão sistemática da literatura para analisar publicações científicas, e com isto determinar qual o papel das pessoas, representando o fator humano, e dos sensores, representando o fator tecnológico, no desenvolvimento das Smart Cities. Ademais, criou-se um panorama da pesquisa científica, sendo possível identificar áreas mais e menos abordadas dentre aquelas avaliadas neste estudo.
The document outlines the steps of the scientific method which are used to systematically gather knowledge about the world. It explains that the scientific method involves making observations, asking questions, forming hypotheses, performing experiments, analyzing data, and drawing conclusions. Key aspects of the method include identifying independent and dependent variables, stating testable hypotheses, designing experiments to test hypotheses, carefully collecting and analyzing results, and determining if the conclusions drawn from data support or contradict the original hypotheses. The overall goal of using this process is to improve understanding of phenomena through empirical investigation.
The document provides an introduction to science and the scientific method. It defines science as using observation to discover facts and form principles that can be tested. It explains that physical science studies non-living matter, including chemistry which examines interactions between forms of matter, and physics which examines energy and its effects on matter. The scientific method is then described as a step-by-step process scientists use to answer questions, involving asking questions, researching, forming hypotheses, testing, gathering data, analyzing results, and drawing conclusions.
Applications of high-throughput sequencing (HTS) technologies in the pharma i...Enrico Ferrero
High-throughput sequencing (HTS) technologies like RNA-seq, ChIP-seq, and whole-genome bisulfite sequencing (WGBS) are increasingly being used in the pharmaceutical industry to better understand diseases, discover new drug targets, and elucidate drug mechanisms of action. GSK is applying these technologies throughout its drug discovery pipeline, including projects studying disease progression in rheumatoid arthritis, identifying targets from host responses to viral infection, and determining the pathways activated by neurogenesis-inducing compounds. Partnerships with academic institutions further enhance the application of HTS to improve target discovery.
The document outlines the scientific method and provides an example of Francesco Redi's experiment on spontaneous generation. It discusses the 10 main steps of the scientific method: 1) making observations, 2) asking questions, 3) conducting research, 4) stating hypotheses, 5) experimentation, 6) collecting and recording data, 7) analyzing data, 8) drawing conclusions, 9) determining limitations, and 10) publishing results. It then summarizes Redi's experiment which aimed to disprove spontaneous generation through a controlled experiment comparing jars of meat covered and uncovered, observing that maggots only formed on uncovered meat exposed to flies.
The document outlines the key aspects of the scientific method including asking questions, forming hypotheses, designing and running experiments, collecting and analyzing data, and drawing conclusions. It defines important scientific terms like hypothesis, experiment, data, control and experimental groups, and the difference between a hypothesis, theory, and law. The overall process involves making observations, identifying problems or questions, proposing hypotheses, experimentally testing hypotheses, and analyzing results.
The document discusses the scientific method, which is a process used by scientists to investigate questions about the natural world through organized and reliable experiments. There are several versions of the scientific method, but they generally involve identifying a problem, developing a hypothesis to test, designing an experiment to collect data, analyzing the results, and communicating the conclusions. The goal of science is to understand the natural world by proposing explanations that can be tested through examination of evidence in a careful and systematic way.
This document outlines the scientific method process which involves stating a problem, formulating a hypothesis, designing an experiment to test the hypothesis, making observations during the experiment, interpreting the collected data, drawing conclusions based on the data, determining if the results support or falsify the original hypothesis, and reporting or revising the hypothesis based on the findings.
Does preregistration improve the interpretability and credibility of research...Mark Rubin
Rubin, M. (2022, March). Does preregistration improve the interpretability and credibility of research findings? In Research transparency: From preregistration to open access. Erasmus Research Institute of Management Research Transparency Campaign, Erasmus University Rotterdam. [Video recording: https://www.youtube.com/watch?v=xsEoLhQrKNQ&t=1s]
Three well-designed studies found that group cognitive behavioral interventions for individuals at risk of panic disorder can effectively reduce panic and agoraphobic symptoms. The strongest treatment gains came from multi-session group programs that included education, breathing retraining, exposure exercises, and cognitive restructuring. A single-day workshop format was also effective in reducing panic symptoms and risk of panic disorder onset at 6-month follow up. However, brief interventions and unguided online self-help programs showed limited effectiveness. Comprehensive 8-week group treatments or single-day workshops including exposure techniques are recommended.
An East Rockaway, New York, native and a magna cum laude graduate of Boston University, attorney Marc Rovner serves as general counsel and director of business development for BETA Abstract, LLC. He has been recognized by many professional organizations, and earned a 2015 Client Distinction Award given by Martindale-Hubbell on behalf of Lawyers.com. In conjunction with his professional pursuits, Marc Rovner also belongs to the American Bar Association.
This document is a resume for Nicholas Norgaard providing his contact information, skills, professional experience, and education. It summarizes that he has worked in several customer service and sales roles in the golf and sporting goods industries, including at golf courses and Dick's Sporting Goods, where he demonstrated skills in customer service, sales, multi-tasking, and handling unexpected events. He is currently studying Business Administration and expects to graduate in April 2016.
Kimberly Jacobs is seeking a position in healthcare administration or psychology. She has a Bachelor's in Human and Social Service Administration from Bellevue University and an MBA in Healthcare Systems from Grand Canyon University. She is currently attending GCU for a Doctorate in Psychology. Jacobs has over 5 years of experience in healthcare, including positions as an Intake Clinician, High Needs Case Manager, and Director of Social Services at various facilities. She maintains clinical records, assesses clients, develops treatment plans, and provides crisis management. Jacobs aims to increase customer satisfaction and organizational profitability with her goal-oriented and culturally sensitive approach.
Andrew Feinberg is a quality and materials engineer with over 30 years of experience in supply chain management, supplier development, quality assurance, and root cause analysis. He has extensive experience ensuring products meet requirements from low to high volume production. He is Six Sigma Black Belt certified and has led teams that successfully achieved ISO and TS-16949 certifications. Currently he is the lead supplier quality engineer at Orbital ATK responsible for supplier audits, non-conformance resolution, and corrective action implementation.
This document discusses challenges in integrating different types of omics data. It notes that data comes from different experimental sources and levels of resolution, from ecosystems down to individual atoms. It also notes challenges including different data formats, mapping and identifier issues, and statistical analysis of similarity and differences. Integrating such diverse data requires addressing these challenges.
O Papel das Pessoas dos Sensores no Desenvolvimento das Smart Cities: Uma Rev...Italberto Dantas
Nos últimos anos, com o aumento acelerado da população nas grandes cidades do mundo, problemas como poluição do ar, escassez de água e condições de tráfego intenso, tornaram-se muito mais evidentes. Tentando mitigá-los, foi apresentado o conceito de Smart City, que usa tecnologia e recursos humanos para gerenciar os recursos urbanos de forma sustentável. A medida que novas pesquisas científicas sobre este fenômeno são realizadas, fica implícita a importância de ambos, recursos humanos e tecnológicos, no desenvolvimento das Smart Cities. Porém não fica claro qual papel cada um ocupa nas diversas etapas de evolução, as quais uma cidade passa até ser considerada smart. Dado o contexto, neste trabalho utilizou-se o método de revisão sistemática da literatura para analisar publicações científicas, e com isto determinar qual o papel das pessoas, representando o fator humano, e dos sensores, representando o fator tecnológico, no desenvolvimento das Smart Cities. Ademais, criou-se um panorama da pesquisa científica, sendo possível identificar áreas mais e menos abordadas dentre aquelas avaliadas neste estudo.
Mellanox Technologies presented a financial overview, highlighting:
- Exponential data growth driving demand for their interconnect solutions.
- Acquisitions expanded their total addressable market, team, and geography.
- Historical annual revenue grew at a 30% compound annual growth rate over 5 years, though growth slowed in 2013.
- The presentation outlined financial metrics including revenue breakdown by product and data rate, headcount trends, cash flow, and long-term financial targets.
GraphRAG for Life Science to increase LLM accuracyTomaz Bratanic
GraphRAG for life science domain, where you retriever information from biomedical knowledge graphs using LLMs to increase the accuracy and performance of generated answers
Programming Foundation Models with DSPy - Meetup SlidesZilliz
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
Taking AI to the Next Level in Manufacturing.pdfssuserfac0301
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
Introduction of Cybersecurity with OSS at Code Europe 2024Hiroshi SHIBATA
I develop the Ruby programming language, RubyGems, and Bundler, which are package managers for Ruby. Today, I will introduce how to enhance the security of your application using open-source software (OSS) examples from Ruby and RubyGems.
The first topic is CVE (Common Vulnerabilities and Exposures). I have published CVEs many times. But what exactly is a CVE? I'll provide a basic understanding of CVEs and explain how to detect and handle vulnerabilities in OSS.
Next, let's discuss package managers. Package managers play a critical role in the OSS ecosystem. I'll explain how to manage library dependencies in your application.
I'll share insights into how the Ruby and RubyGems core team works to keep our ecosystem safe. By the end of this talk, you'll have a better understanding of how to safeguard your code.
Building Production Ready Search Pipelines with Spark and MilvusZilliz
Spark is the widely used ETL tool for processing, indexing and ingesting data to serving stack for search. Milvus is the production-ready open-source vector database. In this talk we will show how to use Spark to process unstructured data to extract vector representations, and push the vectors to Milvus vector database for search serving.
5th LF Energy Power Grid Model Meet-up SlidesDanBrown980551
5th Power Grid Model Meet-up
It is with great pleasure that we extend to you an invitation to the 5th Power Grid Model Meet-up, scheduled for 6th June 2024. This event will adopt a hybrid format, allowing participants to join us either through an online Mircosoft Teams session or in person at TU/e located at Den Dolech 2, Eindhoven, Netherlands. The meet-up will be hosted by Eindhoven University of Technology (TU/e), a research university specializing in engineering science & technology.
Power Grid Model
The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services.
Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.
Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization.
What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
-Insightful presentations covering two practical applications of the Power Grid Model.
-An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024.
-An interactive brainstorming session to discuss and propose new feature requests.
-An opportunity to connect with fellow Power Grid Model enthusiasts and users.
leewayhertz.com-AI in predictive maintenance Use cases technologies benefits ...alexjohnson7307
Predictive maintenance is a proactive approach that anticipates equipment failures before they happen. At the forefront of this innovative strategy is Artificial Intelligence (AI), which brings unprecedented precision and efficiency. AI in predictive maintenance is transforming industries by reducing downtime, minimizing costs, and enhancing productivity.
Main news related to the CCS TSI 2023 (2023/1695)Jakub Marek
An English 🇬🇧 translation of a presentation to the speech I gave about the main changes brought by CCS TSI 2023 at the biggest Czech conference on Communications and signalling systems on Railways, which was held in Clarion Hotel Olomouc from 7th to 9th November 2023 (konferenceszt.cz). Attended by around 500 participants and 200 on-line followers.
The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
The videorecording (in Czech) from the presentation is available here: https://youtu.be/WzjJWm4IyPk?si=SImb06tuXGb30BEH .
Generating privacy-protected synthetic data using Secludy and MilvusZilliz
During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
Digital Marketing Trends in 2024 | Guide for Staying AheadWask
https://www.wask.co/ebooks/digital-marketing-trends-in-2024
Feeling lost in the digital marketing whirlwind of 2024? Technology is changing, consumer habits are evolving, and staying ahead of the curve feels like a never-ending pursuit. This e-book is your compass. Dive into actionable insights to handle the complexities of modern marketing. From hyper-personalization to the power of user-generated content, learn how to build long-term relationships with your audience and unlock the secrets to success in the ever-shifting digital landscape.
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
Nunit vs XUnit vs MSTest Differences Between These Unit Testing Frameworks.pdfflufftailshop
When it comes to unit testing in the .NET ecosystem, developers have a wide range of options available. Among the most popular choices are NUnit, XUnit, and MSTest. These unit testing frameworks provide essential tools and features to help ensure the quality and reliability of code. However, understanding the differences between these frameworks is crucial for selecting the most suitable one for your projects.
Best 20 SEO Techniques To Improve Website Visibility In SERPPixlogix Infotech
Boost your website's visibility with proven SEO techniques! Our latest blog dives into essential strategies to enhance your online presence, increase traffic, and rank higher on search engines. From keyword optimization to quality content creation, learn how to make your site stand out in the crowded digital landscape. Discover actionable tips and expert insights to elevate your SEO game.