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الصفحة 35
الصفحة 35
Artificial Intelligence : Applications and innovations
It's about the science of artificial intelligence (AI). AI is the study of the design of intelligent computational agents. This book provides a valuable resource for researchers, scientists, professionals, academicians and students dealing with the new challenges and advances in the areas of AI and innovations. This book also covers a wide range of applications of machine learning such as fire detection, structural health and pollution monitoring and control. Provides insight into prospective research and application areas related to industry and technology / Discusses industry- based inputs on success stories of technology adoption / Discusses technology applications from a research perspective in the field of AI / Provides a hands- on approach and case studies for readers of the book to practice and assimilate learning
Architecting dependable systems V
As software systems become increasingly ubiquitous, the issues of dependability become more and more crucial. Given that solutions to these issues must be considered from the very beginning of the design process, it is reasonable that dependability is addressed at the architectural level. This book was born of an effort to bring together the research communities of software architectures and dependability.
Architecting dependable systems IV
As software systems become ubiquitous, the issues of dependability become more and more crucial. Given that solutions to these issues must be considered from the very beginning of the design process, it is reasonable that dependability is addressed at the architectural level. It also contains sections on architectural description languages, architectural components and patterns, architecting distributed systems, and architectural assurances for dependability.
Architecting dependable systems III
As software systems become ubiquitous, the issues of dependability become more and more crucial. Given that solutions to these issues must be considered from the very beginning of the design process, it is reasonable that dependability is addressed at the architectural level. This book comes as a result of an effort to bring together the research communities of software architectures and dependability. The papers are organised in topical sections on architectures for dependable services, monitoring and reconfiguration in software architectures, dependability support for software architectures, architectural evaluation, and architectural abstractions for dependability
Arakelov Geometry and Diophantine Applications
Bridging the gap between novice and expert, the aim of this book is to present in a self-contained way a number of striking examples of current diophantine problems to which Arakelov geometry has been or may be applied. Arakelov geometry can be seen as a link between algebraic geometry and diophantine geometry.The first chapters provide some background and introduction to the subject. These are followed by a presentation of different applications to arithmetic geometry. The final part describes the recent application of Arakelov geometry to Shimura varieties and the proof of an averaged version of Colmez's conjecture. This book thus blends initiation to fundamental tools of Arakelov geometry with original material corresponding to current research.
Arabic and Chinese Handwriting Recognition ; SACH 2006 Summit College Park, MD, USA, September 27-28, 2006 Selected Papers
Cheriet provides an overview of the problems of Arabic recognition and how systems can use natural language processing techniques to correct errors in lexicon-based systems.
Applied mathematics and machine learning
The simultaneous availability of large datasets and high-performance computing capability in recent years has enabled the rapid development of powerful machine learning algorithms. On the one hand, state-of-the-art machine learning techniques have transformed many areas of science and engineering; on the other hand, theoretical discoveries in mathematical algorithms, differential equations, and statistical inferences, to name a few, have provided the foundation for the exploration of new multidisciplinary models for solving practical problems. This Special Issue endeavors to continue the journey that started in our previous Special Issue (Applied Mathematics and Computational Physics) by providing a platform for researchers from both academia and industry, as well as government, to present their new computational methods that have engineering and physics applications.
Applied Deep Learning with TensorFlow 2 : Learn to Implement Advanced Deep Learning Techniques with Python
Focuses on the fundamental concepts and at the same time on practical aspects of implementing neural networks and deep learning for your research projects. This book is designed so that you can focus on the parts you are interested in. You will explore topics as regularization, optimizers, optimization, metric analysis, and hyper-parameter tuning. In addition, you will learn the fundamentals ideas behind autoencoders and generative adversarial networks. All the code presented in the book will be available in the form of Jupyter notebooks which would allow you to try out all examples and extend them in interesting ways. A companion online book is available with the complete code for all examples discussed in the book and additional material more related to TensorFlow and Keras. All the code will be available in Jupyter notebook format and can be opened directly in Google Colab (no need to install anything locally) or downloaded on your own machine and tested locally. You will: Understand the fundamental concepts of how neural networks work / Learn the fundamental ideas behind autoencoders and generative adversarial networks / Be able to try all the examples with complete code examples that you can expand for your own projects / Have available a complete online companion book with examples and tutorials.
Applied cryptography and network security ; 6th International Conference, ACNS 2008, New York, NY, USA, June 3-6, 2008. Proceedings
This book constitutes the refereed proceedings of the 6th International Conference on Applied Cryptography and Network Security, ACNS 2008, held in New York, NY, USA, in June 2008.
Applications of Membrane Computing
Membrane computing is a branch of natural computing which investigates computing models abstracted from the structure and functioning of living cells and from their interactions in tissues or higher-order biological structures. The models considered, called membrane systems (P systems), are parallel, distributed computing models, processing multisets of symbols in cell-like compartmental architectures. In many applications membrane systems have considerable advantages – among these are their inherently discrete nature, parallelism, transparency, scalability and nondeterminism.
Application and theory of multimedia signal processing using machine learning or advanced methods
Consists of a collection of peer-reviewed published papers on various advanced technology researches related to signal processing applications and theories for multimedia systems using machine learning or advanced methods. Multimedia signals include image, video, audio, character recognition, and communication channel optimization for networks. The specific contents included in this book are data hiding, encryption, object detection, image classification, and character recognition.
Anti-Spam Measures : Analysis and Design
The goal of this book is the methodical analysis of the potential, limitations, advantages, and drawbacks of anti-spam measures. These determine to which extent the measures can contribute to the reduction of spam in the long run. The range of considered anti-spam measures includes legislative, organizational, behavioral and technological ones. Furthermore, the conceptual development and analysis of an infrastructural email framework that features such a complementary application, is pointed out. The technological and organizational facets, the framework is analyzed twofold: its theoretical effectiveness is assessed with the aid of the formal model mentioned above, its storage and traffic requirements are analyzed quantitatively.
Anti-fragile ICT Systems
Introduces a novel approach to the design and operation of large ICT systems. It views the technical solutions and their stakeholders as complex adaptive systems and argues that traditional risk analyses cannot predict all future incidents with major impacts. To avoid unacceptable events, it is necessary to establish and operate anti-fragile ICT systems that limit the impact of all incidents, and which learn from small-impact incidents how to function increasingly well in changing environments. The book applies four design principles and one operational principle to achieve anti-fragility for different classes of incidents. It discusses how systems can achieve high availability, prevent malware epidemics, and detect anomalies. Analyses of Netflix’s media streaming solution, Norwegian telecom infrastructures, e-government platforms, and Numenta’s anomaly detection software show that cloud computing is essential to achieving anti-fragility for classes of events with negative impacts.
Anticipatory Behavior in Adaptive Learning Systems : From Brains to Individual and Social Behavior
Anticipatory behavior in adaptive learning systems is steadily gaining the - terest of scientists, although many researchers still do not explicitly consider the actual anticipatory capabilities of their systems.The introductory chapter of this volume therefore does not only provide an overview of the contributions included in this volume but also proposes a taxonomy of how anticipatory mechanisms can improve adaptive behavior and learning in cognitive systems. During the workshop it became clear that ant- ipations are involved in various cognitive processes that range from individual anticipatory mechanisms to social anticipatory behavior.
Anomaly Detection : Techniques and Applications
When information in the data warehouse is processed, it follows a definite pattern. An unexpected deviation in the data pattern from the usual behavior is called an anomaly. The anomaly in the data is also referred to as noise, outlier, spammer, deviations, novelties and exceptions. Identification of the rare items, events, observations, patterns which raise suspension by differing significantly from the majority of data is called anomaly detection. With progress in the technologies and the widespread use of data for the purpose for business the increase in the spams faced by the individuals and the companies are increasing day by day. This noisy data has boomed as a major problem in various areas such as Internet of Things, web service, Machine Learning, Artificial Intelligence, Deep learning, Image Processing, Cloud Computing, Audio processing, Video Processing, VoIP, Data Science, Wireless Sensor etc. Identifying the anomaly data and filtering them before processing is a major challenge for the data analyst. This anomaly is unavoidable in all areas of research. This book covers the techniques and algorithms for detecting the deviated data.
Anatomy ontologies for bioinformatics : Principles and practice
This book provides a timely and first-of-its-kind collection of contributed chapters on anatomy ontologies. It is interdisciplinary in its approach, bringing together relevant expertise from computing and biomedical studies, and covering both theoretical and applied aspects, with an emphasis on newer work relevant to the emerging Semantic Web.
Analysis and Modelling of Faces and Gestures ; 2nd International workshop, AMFG 2005, Beijing, China, October 16, 2005, Proceedings
During the last 30 years, face recognition and related problems such as face detection/tracking and facial expression recognition have attracted researchers from both the engineering and psychology communities. In addition, extensive research has been carried out to study hand and body gestures. The understanding of how humans perceive these important cues has significant scientific value and extensive applications. this one-day workshop (AMFG 2005) provided a focused international forum to bring together well-known researchers and research groups to review the status of recognition, analysis and modeling of faces and gestures, to discuss the challenges that we are facing, and to explore future directions. Overall, 30 papers were selected from 90 submitted manuscripts. The topics of these papers range from feature representation, robust recognition, learning, and 3D modeling to psychology.
Analysis and Development of Sustainable Urban Production Systems
Manufacturing of products in urban production sites is connected to unique potentials, yet also to specific challenges. Urban factories can provide functional diversity and contribute positive impacts to a city. The concept of urban production receives rising attention in research and industry and it is recognized in its interdisciplinary nature. With a holistic approach from both the urban perspective and the factory perspective, negative impacts can be minimized, positive effects enabled and mutually beneficial, symbiotic combinations created. The presented framework and methods for the evaluation and implementation of sustainable urban production systems allow the assessment of impacts and provide the means to control and utilize the unique strengths of urban factories for cities and industry. This will allow a structured derivation of methods and measures from the concept of urban production for producing enterprises and the urban stakeholders.
Analysis and Design of Information Systems : Third ed.
This third edition of the successful Analysis and Design of Information Systems provides a comprehensive introduction and user-friendly survey to all aspects of business transformation and analysis, and aims to provide the complex set of tools covering all types of systems, including legacy, transactional, database, and web/e-commerce topics.
An Introduction to Quantum and Vassiliev Knot Invariants
Provides an accessible introduction to knot theory, focussing on Vassiliev invariants, quantum knot invariants constructed via representations of quantum groups, and how these two apparently distinct theories come together through the Kontsevich invariant. Consisting of four parts, the book opens with an introduction to the fundamentals of knot theory, and to knot invariants such as the Jones polynomial. The second part introduces quantum invariants of knots, working constructively from first principles towards the construction of Reshetikhin-Turaev invariants and a description of how these arise through Drinfeld and Jimbo's quantum groups. Its third part offers an introduction to Vassiliev invariants, providing a careful account of how chord diagrams and Jacobi diagrams arise in the theory, and the role that Lie algebras play. The final part of the book introduces the Konstevich invariant. This is a universal quantum invariant and a universal Vassiliev invariant, and brings together these two seemingly different families of knot invariants. The book provides a detailed account of the construction of the Jones polynomial via the quantum groups attached to sl(2), the Vassiliev weight system arising from sl(2), and how these invariants come together through the Kontsevich invariant.
