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Ontology Alignment : Bridging the Semantic Gap
Ontology Alignment: Bridging the Semantic Gap introduces novel methods and approaches for semantic integration. In addition to developing new methods for ontology alignment, the author provides extensive explanations of up-to-date case studies. The topic of this book, coupled with the application-focused methodology, will appeal to professionals from a number of different domains.
Official Statistics 4.0 : Verified Facts for People in the 21st Century
Explores official statistics and their social function in modern societies. Digitisation and globalisation are creating completely new opportunities and risks, a context in which facts (can) play an enormously important part if they are produced with a quality that makes them credible and purpose-specific. In order for this to actually happen, official statistics must continue to actively pursue the modernisation of their working methods.
Obstructions in Security-Aware Business Processes : Analysis, Detection, and Handling
This book explores the dilemma-like stalemate between security and regulatory compliance in business processes on the one hand and business continuity and governance on the other. The growing number of regulations, e.g., on information security, data protection, or privacy, implemented in increasingly digitized businesses can have an obstructive effect on the automated execution of business processes. Such security-related obstructions can particularly occur when an access control-based implementation of regulations blocks the execution of business processes. By handling obstructions, security in business processes is supposed to be improved. For this, the book presents a framework that allows the comprehensive analysis, detection, and handling of obstructions in a security-sensitive way. Thereby, methods based on common organizational security policies, process models, and logs are proposed. The Petri net-based modeling and related semantic and language-based research, as well as the analysis of event data and machine learning methods finally lead to the development of algorithms and experiments that can detect and resolve obstructions and are reproducible with the provided software.
Object-Oriented Software Engineering Using UML Patterns and Java
Shows students how to use both the principles of software engineering and the practices of various object-oriented tools, processes, and products. Using a step-by-step case study to illustrate the concepts and topics in each chapter, Bruegge and Dutoit emphasize learning object-oriented software engineer through practical experience: students can apply the techniques learned in class by implementing a real-world software project. The third edition addresses new trends, in particular agile project management (Chapter 14 Project Management) and agile methodologies (Chapter 16 Methodologies).
Object detection with deep learning models : Principles and applications
Discusses recent advances in object detection and recognition using deep learning methods, which have achieved great success in the field of computer vision and image processing. It provides a systematic and methodical overview of the latest developments in deep learning theory and its applications to computer vision, illustrating them using key topics, including object detection, face analysis, 3D object recognition, and image retrieval / A structured overview of deep learning in object detection / A diversified collection of applications of object detection using deep neural networks / Emphasize agriculture and remote sensing domains / Exclusive discussion on moving object detection
Nonparametric Bayesian Learning for Collaborative Robot Multimodal Introspection
This book focuses on robot introspection, which has a direct impact on physical human–robot interaction and long-term autonomy, and which can benefit from autonomous anomaly monitoring and diagnosis, as well as anomaly recovery strategies.
Nonlinear Speech Modeling and Applications : Advanced Lectures and Revised Selected Papers
Presents the revised tutorial lectures given at the International Summer School on Nonlinear Speech Processing-Algorithms and Analysis held in Vietri sul Mare, Salerno, Italy in September 2004. The 14 revised tutorial lectures by leading international researchers are organized in topical sections on dealing with nonlinearities in speech signals, acoustic-to-articulatory modeling of speech phenomena, data driven and speech processing algorithms, and algorithms and models based on speech perception mechanisms. Besides the tutorial lectures, 15 revised reviewed papers are included presenting original research results on task oriented speech applications.
Nine algorithms that changed the future : The ingenious ideas that drive today’s computers
Every day, we use our computers to perform remarkable feats. A simple web search picks out a handful of relevant needles from the world’s biggest haystack. Uploading a photo to Facebook transmits millions of pieces of information over numerous error-prone network links, yet somehow a perfect copy of the photo arrives intact. Without even knowing it, we use public-key cryptography to transmit secret information like credit card numbers, and we use digital signatures to verify the identity of the websites we visit. How do our computers perform these tasks with such ease?
News bot
The process of gathering and organizing news content has become a challenging task for emerging news sites, necessitating the employment of highly experienced personnel with specialized skills in the field. However, recent advancements in artificial intelligence technology have led to the development of news bots that can efficiently fetch, classify, and rephrase news content from various sources, enabling users to access the latest and well-formulated news without the need for RSS (Really Simple Syndication).
New Trends in Databases and Information Systems ; ADBIS 2020 Short Papers, Lyon, France, August 25–27, 2020, Proceedings
This book constitutes thoroughly refereed short papers of the 24th European Conference on Advances in Databases and Information Systems, ADBIS 2020, held in August 2020. ADBIS 2020 was to be held in Lyon, France, however due to COVID-19 pandemic the conference was held in online format. The 18 presented short research papers were carefully reviewed and selected from 69 submissions. The papers are organized in the following sections: data access and database performance; machine learning; data processing; semantic web; data analytics.
New trends in computational vision and bio-inspired computing : Selected works presented at the ICCVBIC 2018, Coimbatore, India
Gathers selected, peer-reviewed original contributions presented at the International Conference on Computational Vision and Bio-inspired Computing (ICCVBIC) conference which was held in Coimbatore, India, on November 29-30, 2018. The works included here offer a rich and diverse sampling of recent developments in the fields of Computational Vision, Fuzzy, Image Processing and Bio-inspired Computing. The topics covered include computer vision; cryptography and digital privacy; machine learning and artificial neural networks; genetic algorithms and computational intelligence; the Internet of Things; and biometric systems, to name but a few. The applications discussed range from security, healthcare and epidemic control to urban computing, agriculture and robotics.
New Trends in Applied Artificial Intelligence ; 20th International Conference on Industrial, Engineering, and Other Applications of Applied Intelligent Systems. IEA/AIE 2007, Kyoto, Japan, June 26-29, 2007, Proceedings
The 20 International Conference on Industrial, Engineering and Other Applications of Applied Intelligent S- tems (IEA/AIE-2007) held in Kyoto, Japan presented such work performed by many scientists worldwide. The previous IEA/AIE conference held in Japan was the Ninth International Conference on Industrial and Engineering Applications of Arti?cial Intelligence and Expert systems (IEA/AIE-1996) in Fukuoka in 1996.
New perspectives in critical data studies: the ambivalences of data power
Examines the ambivalences of data power. Firstly, the ambivalences between global infrastructures and local invisibilities challenge the grand narrative of the ephemeral nature of a global data infrastructure. They make visible local working and living conditions, and the resources and arrangements required to operate and run them. Secondly, the book examines ambivalences between the state and data justice. It considers data justice in relation to state surveillance and data capitalism, and reflects on the ambivalences between an “entrepreneurial state” and a “welfare state”. Thirdly, the authors discuss ambivalences of everyday practices and collective action, in which civil society groups, communities, and movements try to position the interests of people against the “big players” in the tech industry.
New insights in machine learning and deep neural networks
Gatheres ten exemplary papers, each delineating advancements within the spheres of machine learning and deep neural networks. Commencing with a thorough exploration by Figueira and Vaz, readers are introduced to the nuances of synthetic data generation and evaluation, followed closely by Silva and Pedroso's systematic approach to leveraging deep reinforcement learning within the intricate realm of delivery logistics. Kamran et al. contribute an astute methodology for camouflage object segmentation, whereas Pinheiro and collaborators offer a crafted semi-supervised strategy for predicting EGFR mutations via CT images. Subsequent contributions, such as Lee and Yoo's framework for portrait emotion recognition and Balakrishnan et al.'s analytical exploration of transformer models for Twitter disaster detection, further exemplify the depth of research contained herein.
New frontiers in artificial intelligence ; JSAI-isAI International Workshops, JURISIN, AI-Biz, LENLS, Kansei-AI, Yokohama, Japan, November 10–12, 2019, Revised Selected Papers
This book constitutes extended, revised and selected papers from the 11th International Symposium of Artificial Intelligence supported by the Japanese Society for Artificial Intelligence, JSAI-isAI 2019. It was held in November 2019 in Yokohama, Japan. The 26 papers were carefully selected from 46 submissions and deal with topics of AI research and are organized into 4 sections, according to the 4 workshops: JURISIN 2019, AI-Biz 2019, LENLS 16, and Kansei-AI 2019.
New Frontiers in Applied Artificial Intelligence ; 21st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2008 Wrocław, Poland, June 18-20, 2008 Proceedings
The 75 revised full papers presented were carefully reviewed and selected from 302 submissions. The papers are organized in topical sections on computer vision, fuzzy system applications, robot and manufacturing, data mining and KDS, neural networks, machine learning, natural language processing, internet application and education, heuristic search, application systems, agent-based system, evolutionary and genetic algorithms, knowledge management, and other applications. The book concludes with 15 contributions from the following special sessions: knowledge driven manufacturing systems, joint session on adaptive networked systems and fuzzy knowledge bases, and software agents and multi-agent systems.
New Developments in Parsing Technology
Parsing can be defined as the decomposition of complex structures into their constituent parts, and parsing technology as the methods, the tools, and the software to parse automatically. Parsing is a central area of research in the automatic processing of human language. Parsers are being used in many application areas, for example question answering, extraction of information from text, speech recognition and understanding, and machine translation. New developments in parsing technology are thus widely applicable. This book contains contributions from many of today's leading researchers in the area of natural language parsing technology. The contributors describe their most recent work and a diverse range of techniques and results. This collection provides an excellent picture of the current state of affairs in this area. This volume is the third in a series of such collections, and its breadth of coverage should make it suitable both as an overview of the current state of the field for graduate students, and as a reference for established researchers.
New Algorithms for Macromolecular Simulation
Molecular simulation is a widely used tool in biology, chemistry, physics and engineering. This book contains a collection of articles by leading researchers who are developing new methods for molecular modelling and simulation. Topics addressed here include: multiscale formulations for biomolecular modelling, such as quantum-classical methods and advanced solvation techniques; protein folding methods and schemes for sampling complex landscapes; membrane simulations; free energy calculation; and techniques for improving ergodicity. The book is meant to be useful for practitioners in the simulation community and for those new to molecular simulation who require a broad introduction to the state of the art.
Neuroscribe = نيوروسكرايب
Neuroscribe is a cutting-edge deep learning framework designed to address the complexities and inefficiencies encountered in existing frameworks like PyTorch and TensorFlow. Aimed at streamlining model development and enhancing performance across diverse hardware environments, NeuroScribe offers a lightweight and flexible solution. The framework features a robust tensor library, an auto-differentiation engine, a comprehensive neural network module, and advanced optimization algorithms. With built-in visualization tools and a user-friendly interface, NeuroScribe simplifies both beginner and advanced workflows. Its cross-platform compatibility, supported by CUDA and Metal Performance Shaders (MPS), ensures optimal performance, and in some scenarios, NeuroScribe demonstrates superior speed compared to leading frameworks. Additionally, NeuroScribe introduces unique libraries and features not found in other frameworks, further enhancing its versatility and appeal. The modular architecture and automatic system detection further enhance its adaptability, making NeuroScribe a versatile and powerful tool for deep learning practitioners.
Neural Preprocessing and Control of Reactive Walking Machines: Towards Versatile Artificial Perception-Action Systems
This book presents biologically inspired walking machines interacting with their physical environment. It describes how the designs of the morphology and the behavior control of walking machines can benefit from biological studies. The purpose of this book is to develop a modular structure of neural control generating different reactive behaviors of the physical walking machines, to analyze the neural mechanisms underlying the reactive behaviors, and to demonstrate the sensor fusion technique leading to smooth switching between appropriate behaviors, like obstacle avoidance and sound tropism.
