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Semantic and Fuzzy Modelling for Human Behaviour Recognition in Smart Spaces
One of the major limitations of the Ambient Intelligent Systems today is the lack of semantic models of those activities on the environment, so that the system can recognize the specific activity being performed by the user(s) and act accordingly. In this context, this thesis addresses the general problem of knowledge representation in Smart Spaces. The main objective is to develop knowledge-based models, equipped with semantics to learn, infer and monitor human behaviours in Smart Spaces. Moreover, it is easy to recognize that some aspects of this problem have a high degree of uncertainty, and therefore, the developed models must be equipped with mechanisms to manage this type of informatio...
Manuel Díaz Rodríguez
This book offers a stylistic analysis of an early-twentieth-century Venezuelan writer known for his travel accounts, stories, novels, and essays. It concentrates on three novels: dolos rotos, Sangre patricidia, and Peregrina. It discusses contexts (criollismo and modernismo), summarizes plots, and examines sense impressions, imagery, and syntactic devices.
Cancer Research Supported Under BIOMED 1
The pace of discovery, within the EU, of scientific aspects of cancer research and of developments in the clinical field is so rapid that it is sometimes difficult to keep abreast. This brief overview attempts to highlight some of the advances in the field, as part of BIOMED programme funded research and specific results due to the co-operative spirit established by the scientific community. It is particularly worth noting the financial investment of 35 million ECU in the current programme, has d as a catalyst in attracting a large number of Member States funded research in pooling their collective knowledge base.
Elements of Data Science, Machine Learning, and Artificial Intelligence Using R
The textbook provides students with tools they need to analyze complex data using methods from data science, machine learning and artificial intelligence. The authors include both the presentation of methods along with applications using the programming language R, which is the gold standard for analyzing data. The authors cover all three main components of data science: computer science; mathematics and statistics; and domain knowledge. The book presents methods and implementations in R side-by-side, allowing the immediate practical application of the learning concepts. Furthermore, this teaches computational thinking in a natural way. The book includes exercises, case studies, Q&A and examples.
Explainable Edge AI: A Futuristic Computing Perspective
This book presents explainability in edge AI, an amalgamation of edge computing and AI. The issues of transparency, fairness, accountability, explainability, interpretability, data-fusion, and comprehensibility that are significant for edge AI are being addressed in this book through explainable models and techniques. The concept of explainable edge AI is new in front of the academic and research community, and consequently, it will undoubtedly explore multiple research dimensions. The book presents the concept of explainability in edge AI which is the amalgamation of edge computing and AI. In the futuristic computing scenario, the goal of explainable edge AI will be to execute the AI tasks ...
Explainable Artificial Intelligence for Autonomous Vehicles
Explainable AI for Autonomous Vehicles: Concepts, Challenges, and Applications is a comprehensive guide to developing and applying explainable artificial intelligence (XAI) in the context of autonomous vehicles. It begins with an introduction to XAI and its importance in developing autonomous vehicles. It also provides an overview of the challenges and limitations of traditional black-box AI models and how XAI can help address these challenges by providing transparency and interpretability in the decision-making process of autonomous vehicles. The book then covers the state-of-the-art techniques and methods for XAI in autonomous vehicles, including model-agnostic approaches, post-hoc explana...
Artificial Intelligence
The first text to take a systems engineering approach to artificial intelligence (AI), from architecture principles to the development and deployment of AI capabilities. Most books on artificial intelligence (AI) focus on a single functional building block, such as machine learning or human-machine teaming. Artificial Intelligence takes a more holistic approach, addressing AI from the view of systems engineering. The book centers on the people-process-technology triad that is critical to successful development of AI products and services. Development starts with an AI design, based on the AI system architecture, and culminates with successful deployment of the AI capabilities. Directed towar...
Visual Object Tracking using Deep Learning
This book covers the description of both conventional methods and advanced methods. In conventional methods, visual tracking techniques such as stochastic, deterministic, generative, and discriminative are discussed. The conventional techniques are further explored for multi-stage and collaborative frameworks. In advanced methods, various categories of deep learning-based trackers and correlation filter-based trackers are analyzed. The book also: Discusses potential performance metrics used for comparing the efficiency and effectiveness of various visual tracking methods Elaborates on the salient features of deep learning trackers along with traditional trackers, wherein the handcrafted feat...
Material Forming
These ESAFORM 2024 conference proceedings cover a wide range of topics: Additive manufacturing; Composites forming processes; Extrusion and drawing; Forging and rolling; Formability of metallic materials; Friction and wear in metal forming; Incremental and sheet metal forming; Innovative joining by forming technologies; Optimization and inverse analysis in forming; Machining, Cutting and severe plastic deformation processes; Material behavior modelling; New and advanced numerical strategies for material forming; Non-conventional processes; Polymer processing and thermomechanical properties; Sustainability on material forming. Keywords: WAAM Technology, Fused deposition Modeling (FDM), Fiber Composite Printers, Ultrasonic Powder Atomization, Finite Element Modeling (FEM), Laser Powder Bed Fusion (L-PBF), Rapid Prototyping in Additive Manufacturing, Directed Energy Deposition (DED), GTAW Droplet Deposition, Deep Learning, Thermoplastic Pultrusion, Textile Reinforcements, Thermoforming Simulation, New Sustainable Materials, Non-Crimp Fabrics, CFRP Scraps, PEEK Composites, Thermoplastic Sheets, Flax/PP Composites.
Explainable Artificial Intelligence for Cyber Security
This book presents that explainable artificial intelligence (XAI) is going to replace the traditional artificial, machine learning, deep learning algorithms which work as a black box as of today. To understand the algorithms better and interpret the complex networks of these algorithms, XAI plays a vital role. In last few decades, we have embraced AI in our daily life to solve a plethora of problems, one of the notable problems is cyber security. In coming years, the traditional AI algorithms are not able to address the zero-day cyber attacks, and hence, to capitalize on the AI algorithms, it is absolutely important to focus more on XAI. Hence, this book serves as an excellent reference for those who are working in cyber security and artificial intelligence.
