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Ontologies for Agents : Theory and Experiences
On the other hand, ontologies have established themselves as a powerful tool to enable kno- edge sharing, and a growing number of applications have bene?ted from the use of ontologies as a means to achieve semantic interoperability among heterogeneous, distributed systems. In principle ontologies and agents are a match made in heaven, that has failed to happen. What makes a simple piece of software an agent is its ability to communicate in a ”social” environment, to make autonomous decisions, and to be proactive on behalf of its user. Communication ultimately depends on und- standing the goals, preferences, and constraints posed by the user. Autonomy is theabilitytoperformataskwithlittleornouserintervention,whileproactiveness involves acting autonomously with no need for user prompting. Communication, but also autonomy and proactiveness, depend on knowledge. The ability to c- municate depends on understanding the syntax (terms and structure) and the semantics of a language. Ontologies provide the terms used to describe a domain and the semantics associated with them. In addition, ontologies are often comp- mented by some logical rules that constrain the meaning assigned to the terms. These constraints are represented by inference rules that can be used by agents to perform the reasoning on which autonomy and proactiveness are based.
omputer science : Theory and applications ; 3rd International computer science symposium in Russia, CSR 2008 Moscow, Russia, June 7-12, 2008 Proceedings
This book constitutes the refereed proceedings of the Third International Computer Science Symposium in Russia, CSR 2008, held in Moscow, Russia, June 7-12, 2008.
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.
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.
New Trends and Technologies in Computer-Aided Learning for Computer-Aided Design ; IFIP International Working Conference: EduTech 2005, Perth, Australia, October 20-21, 2005
Computation and communication technologies underpin work and development in many different areas. Among them, Computer-Aided Design of electronic systems and E-Learning technologies are two areas which are different but share many concerns. The design of CAD and E-Learning systems already touches on a number of parallels, such as system interoperability, user interfaces, standardization, EML-based formats, reusability aspects (of content or designs), and intellectual property rights. Furthermore, the teaching of Design Automation tools and methods is particularly amenable to a distant or blended learning setting, and implies the interconnection of typical CAD tools, such as simulators or synthesis tools, with e-learning tools. There are many other aspects in which synergy can be found when using E-Learning technology for teaching and learning technology. This workshop, sponsored by IFIP WG 10.5 Design and Engineering of Electronic Systems in cooperation with IFIP WG 3.6 Distance Education, will explore the interrelationship between these two subjects, where Computer-Aided Design meets Computer-Aided Learning. New Trends and Technologies in Computer-Aided Learning for Computer-Aided Design documents recent approaches and results presented at the EduTech 2005 Workshop, which was held in October 2005 in Perth, Australia and sponsored by the International Federation for Information Processing (IFIP). The topics chosen for this working conference are very timely: learning environments, tools and applications for education, education technologies and trends, and teaching in the hardware design area.
New Horizons of Parallel and Distributed Computing
Parallel and distributed computing is one of the foremost technologies for shaping future research and development activities in academia and industry. Hyperthreading in Intel processors, hypertransport links in next generation AMD processors, multicore silicon in today’s high-end microprocessors, emerging cluster and grid computing, has moved parallel/distributed computing into the mainstream of computing. New Horizons of Parallel and Distributed Computing is a collection of self-contained chapters written by pioneers and researchers to provide solutions for newly emerging problems in this field. This volume will not only provide novel ideas, work in progress and state-of-the-art techniques in the field, but also stimulate future research activities in the area of parallel and distributed computing with applications. New Horizons of Parallel and Distributed Computing is intended for researchers and graduate students in computer science and electrical engineering, as well as researchers and developers in industry. This book can be used as a textbook and a reference for use by students, researchers, and developers.
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 challenges in software engineering ; Vol 1
Explores the key challenges shaping the future of software development, including automation, AI-driven development, security-focused engineering, resilient and autonomous architectures, business process optimization, cloud computing, microservices, high-performance distributed systems, and sustainable technologies. Software engineering is undergoing a constant transformation, driven by rapid technological advances and evolving market demands. additionally, it delves into the ethical considerations of AI, the evolution of intuitive user interfaces, and the importance of multidisciplinary collaboration.
New advances in audio signal processing
In the era of digitalization, audio signal processing is gaining peculiar relevance as an automation and remote analysis means, also considering its enhancement by novel artificial intelligence (AI) techniques. This Reprint aims to offer an overview of the current developments in all fields that revolve around audio processing: from advancements in the acoustic domain to deep learning architectures for the audio-based analysis of real-world problems such as pitch detection or pathology identification.
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 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.
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.
Multi-Robot Systems. From Swarms to Intelligent Automata, Vol. III ; Proceedings from the 2005 International Workshop on Multi-Robot Systems
Documents developments in multi-robot systems research. This volume is the result of the Third International workshop on Multi-Robot Systems that was held in March 2005 at the Naval Research Laboratory in Washington, DC.
Multi-point Interaction with Real and Virtual Objects
This edited book covers some of the most challenging problems on the forefront of today’s research on physical interaction with real and virtual objects, with special emphasis on modelling contacts between objects, grasp planning algorithms, haptic perception, and advanced design of hands, devices and interfaces.
Multiple Classifier Systems ; 7th International Workshop, MCS 2007, Prague, Czech Republic, May 23-25, 2007, Proceedings
These proceedings are a record of the Multiple Classifier Systems Workshop, MCS 2007, held at the Institute of Information Theory and Automation, Czech Academy of Sciences, Prague in May 2007. the workshop achieved its objective of bringing together researchers from diverse communities (neural networks, pattern rec- nition, machine learning and statistics) concerned with this research topic.
Multiparadigm Programming in Mozart/Oz ; 2nd International Conference, MOZ 2004, Charleroi, Belgium, October 7-8, 2004, Revised Selected Papers
Oz's concurrency model yields simplicity and clarity (because Oz makes it easier to express complex programs with many interacting components), g- erality, and better interfaces (because the data?ow model automatically makes interfaces more lightweight). Constraint programming in Oz again yields simplicity and clarity (because theprogrammercanexpresswhatneedstobetrueratherthanthemorecomplex issue of how to make it true), and o?ers a powerful mathematical notation that is di?cult to implement on top of languages that do not support it natively. Mozart's distributed computing model makes for improved interfaces and eases the evolution of systems. In my own work, one of the most important concernsistobeabletoquicklyscaleupaprototypeimplementationintoalar- scale service that can run reliably on thousands of computers, serving millions of users.
Modern front-end architecture : Optimize your front-end development with components, storybook, and mise en place philosophy
Learn how to build front-end applications that can help you ship applications faster with fewer defects. Many software projects fail because they are not planned well, or lack organization. Applying strategies from other industries can help you create better software. Explores the “mise en place” technique from cooking and reveals how you can apply it to the art of creating software. Describes to how to structure your code base for reuse, and how to communicate the code’s intent to other developers. You’ll develop your components in isolation and test these building blocks for quality at a granular level. Then compose these components as building blocks in increasingly complicated features. Finally, you’ll apply some strategies not directly related to code to ensure maximum quality and efficiency. You will : Structure an application as a series of components / Build a component library that others in an organization can leverage / Ensure quality and accessibility at a component level rather than a page or app level / Test code in a way that gives the maximum amount of confidence while providing an excellent developer experience / Automate repeatable tasks
Modern Deep Learning Design and Application Development : Versatile Tools to Solve Deep Learning Problems
Learn how to harness modern deep-learning methods in many contexts. Packed with intuitive theory, practical implementation methods, and deep-learning case studies, this book reveals how to acquire the tools you need to design and implement like a deep-learning architect. It covers tools deep learning engineers can use in a wide range of fields, from biology to computer vision to business. With nine in-depth case studies, this book will ground you in creative, real-world deep learning thinking. You will: Improve the performance of deep learning models by using pre-trained models, extracting rich features, and automating optimization. Compress deep learning models while maintaining performance. Reframe a wide variety of difficult problems and design effective deep learning solutions to solve them. Use the Keras framework, with some help from libraries like HyperOpt, TensorFlow, and PyTorch, to implement a wide variety of deep learning approaches.
Modelling and Reasoning with Vague Concepts
This volume outlines a formal representation framework for modelling and reasoning with vague concepts in Artificial Intelligence. The new calculus has many applications, especially in automated reasoning, learning, data analysis and information fusion. This book gives a rigorous introduction to label semantics theory, illustrated with many examples, and suggests clear operational interpretations of the proposed measures. It also provides a detailed description of how the theory can be applied in data analysis and information fusion based on a range of benchmark problems.
Modeling and Simulation for RF System Design
The focus of Modeling and Simulation for RF System Design lies on RF specific modeling and simulation methods and the consideration of system and circuit level descriptions. It contains application-oriented training material for RF designers which combines the presentation of a mixed-signal design flow.
