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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.
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.
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 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.
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.
Neural networks and deep learning
Covers both classical and modern models in deep learning. The primary focus is on the theory and algorithms of deep learning. The theory and algorithms of neural networks are particularly important for understanding important concepts, so that one can understand the important design concepts of neural architectures in different applications. Why do neural networks work? When do they work better than off-the-shelf machine-learning models? When is depth useful? Why is training neural networks so hard? What are the pitfalls? The book is also rich in discussing different applications in order to give the practitioner a flavor of how neural architectures are designed for different types of problems.
Neural Nets ; 16th Italian Workshop on Neural Nets, WIRN 2005, International workshop on natural and artificial immune systems, NAIS 2005, Vietri sul Mare, Italy, June 8-11, 2005, Revised Selected Papers
This book constitutes the thoroughly refereed postproceedings of the 16th Italian Workshop on Neural Nets, WIRN 2005, as well as the satellite International Workshop on Natural and Artificial Immune Systems, NAIS 2005, held in Vietri sul Mare, Italy in June 2005. The 41 revised papers presented together with a lecture by the winner of the Premio Caianiello award were carefully reviewed and improved during two rounds of selection and refereeing.
Network Classification For Traffic Management : Anomaly detection, feature selection, clustering and classification
Investigates network traffic classification solutions by proposing transport-layer methods to achieve better run and operated enterprise-scale networks. With the massive increase of data and traffic on the Internet within the 5G, IoT and smart cities frameworks, current network classification and analysis techniques are falling short. Novel approaches using machine learning algorithms are needed to cope with and manage real-world network traffic, including supervised, semi-supervised, and unsupervised classification techniques. Accurate and effective classification of network traffic will lead to better quality of service and more secure and manageable networks. Investigates network traffic classification solutions by proposing transport-layer methods to achieve better run and operated enterprise-scale networks. The authors explore novel methods for enhancing network statistics at the transport layer, helping to identify optimal feature selection through a global optimization approach and providing automatic labelling for raw traffic through a SemTra framework to maintain provable privacy on information disclosure properties.
Natural Language Processing and Information Systems ; Vol. 3513 ; 10th International Conference on Applications of Natural Language to Information Systems, NLDB 2005, Alicante, Spain, June 15-17, Proceedings
The development and convergence of computing, telecommunications and information systems has already led to a revolution in the way that we work, communicate with each other, buy goods and use services, and even in the way that we entertain and educate ourselves.The revolution continues, and one of its results is that large volumes of information will increasingly be held in a form which is more natural for users than the data presentation formats typical of computer systems of the past. Natural language processing (NLP) is crucial in solving these problems, and language technologies will make an indispensable contribution to the success of information systems. We hope that NLDB 2005 was a modest contribution to this goal. NLDB 2005 contributed to advancing the goals and the high international standing of these conferences, largely due to its Program Committee, composed of renowned researchers in the field of natural language processing and inf- mation system engineering. Papers were reviewed by three reviewers from the Program Committee. This clearly contributed to the significant number of - pers submitted (95). Twenty-nine were accepted as regular papers, while 18 were accepted as short papers.
