503 hasil untuk machine learning
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Handbook of Energy Transitions
…storage systems, batteries, digitalization, smart grids, blockchain, and machine learning. It also discusses the present energy transition in terms of broader policy and developmental perspectives. Further, it examines sustainable development, the economics of energy and green growth, and the role…
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Digitalization of Medicine in Low- and Middle-Income Countries
…digitalization, but with recent progress in digitized data acquisition, machine learning and computing infrastructure, healthcare applications are expanding into areas that were previously thought to be the exclusive domain of human experts. It is increasingly accepted that the transformation in…
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Chapter 3 Geopolitics of the Energy Transition
…storage systems, batteries, digitalization, smart grids, blockchain, and machine learning. It also discusses the present energy transition in terms of broader policy and developmental perspectives. Further, it examines sustainable development, the economics of energy and green growth, and the role…
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Technologies and Applications for Big Data Value
…various fields, including big data, data science, data engineering, and machine learning and AI. Second, practitioners and industry experts engaged in data-driven systems, software design and deployment projects who are interested in employing these advanced methods to address real-world problems.
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Classical and Bayesian Statistical Approaches in Infectious Disease Data Analysis
…Disease Analysis and Surveillance: Methods for Independent Data Machine Learning Models for Probabilistic Inference and Prediction Generalized Linear Models in Infectious Disease Analysis and Surveillance: Methods for Correlated Data Residuals and Overdispersion in Generalized Linear Models…
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Electronic Evidence
…infocommunications law, evidence and procedure, artificial intelligence, machine learning and legal reasoning. His research interests also include empirical legal studies and quantitative research and data analytics on big data sets. Between 2001 and 2003, he was concurrently the Director of…
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Chapter An experimental annotation task to investigate annotators’ subjectivity in a Misogyny dataset
…both from the viewpoint of computational linguistics and from that of machine learning, less effort has been devoted to analysing whether models for the detection of misogyny are affected by bias. An emerging topic that challenges traditional approaches for the creation of corpora is the presence…
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Responsible Use of AI in Military Systems
Artificial Intelligence (AI) is widely used in society today. The (mis)use of biased data sets in machine learning applications is well‑known, resulting in discrimination and exclusion of citizens. Another example is the use of non‑transparent algorithms that can’t explain themselves to users…
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Challenges in Information, Communication and Computing Technology Volume 1
…ethical implications and technical hurdles of artificial intelligence and machine learning, and the promise and complexity of quantum computing. The book also addresses the management of big data, highlighting both its potential and the challenges of ensuring data privacy and security…
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Cyber-Physical Threat Intelligence for Critical Infrastructures Security
…and security information sharing, based on leading edge technologies like machine learning, security knowledge modelling, IoT security and distributed ledger infrastructures. Likewise, it presets how established security technologies like Security Information and Event Management (SIEM)…
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A Web-Based Approach to Measure Skill Mismatches and Skills Profiles for a Developing Country
…a novel mixed-methods approach (such as web scraping, text mining, machine learning, etc.) to investigate to what extent a web-based model of skill mismatches can be developed for Colombia. The main contribution of this book is demonstrating that, with the proper techniques, job portals can be a…
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Challenges in Information, Communication and Computing Technology Volume 2
…ethical implications and technical hurdles of artificial intelligence and machine learning, and the promise and complexity of quantum computing. The book also addresses the management of big data, highlighting both its potential and the challenges of ensuring data privacy and security…
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Tunnelling for a Better Life
…Testing and Inspection 11. Digital and Information Technology 12. Machine Learning 13. Underground Caverns/Underground Space Use 14. Operational Safety, Maintenance and Repair 15. Contractual Practices and Risk Management Tunnelling for a Better Life is a must-read for professionals, engineers…
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Expanding Underground - Knowledge and Passion to Make a Positive Impact on the World
…and Lessons Learned Innovation, Robotics and Automation BIM, Big Data and Machine Learning Applications in Tunnelling Safety, Risk and Operation of Underground Infrastructure, and Contractual Practices, Insurance and Project Management The book is a must-have reference for all professionals and…
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Referring expression generation in context
…development steps. An experimental analysis of various feature-based machine learning models reveals that those with a concise set of linguistically-informed features can rival models with more features. Furthermore, this work highlights the importance of paragraph-related concepts, an area…
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Intelligent Secure Trustable Things
…they are mutually beneficial. AI increases the value of the IoT through machine learning by transforming the data into useful information, while the IoT increases the value of AI through connectivity and data exchange. Therefore, InSecTT—Intelligent Secure Trustable Things, a pan-European effort…
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Physically Inspired Predistortion of RF Power Amplifiers with Artificial Neural Networks
…which mitigates certain effects. This work treats impairments from machine learning perspective. IQ Imbalance of modulators as well as power amplifier nonlinearities are representive impairments with significant influence on the signal quality. These effects are trained to artificial neural…
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Demystifying Intelligent Multimode Security Systems
…Understand the unique risks and threats to the intelligence in IMSS (machine learning training and inferencing, regulations, and standards) and explore the solution space for mitigations to these threats Sample applications illustrate how to design in security for several types of IMSS.— Explore…
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Charting the Intelligence Frontiers – Edge AI Systems Nexus
…rigorous investigations spanning verification and validation, federated learning, neuromorphic design, scalable architectures, sensor fusion, and human–machine collaboration, each chapter demonstrating the innovation wave fuelling Europe's edge AI landscape. Together, these twenty chapters provide…
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Trusted Artificial Intelligence in Manufacturing; Trusted Artificial Intelligence in Manufacturing
…and unpredictable environments. Specifically, data reliability, human machine interaction, security, transparency and explainability challenges need to be addressed at the same time. Recent advances in AI research (e.g., in deep neural networks security and explainable AI (XAI) systems), coupled…