الصفحة 10
الصفحة 10
Computer algebra in scientific computing ; 22nd International Workshop, CASC 2020, Linz, Austria, September 14–18, 2020, Proceedings
This book constitutes the refereed proceedings of the 22nd International Workshop on Computer Algebra in Scientific Computing, CASC 2020, held in Linz, Austria, in September 2020. The conference was held virtually due to the COVID-19 pandemic. The 34 full papers presented together with 2 invited talks were carefully reviewed and selected from 41 submissions. They deal with cutting-edge research in all major disciplines of computer algebra. The papers cover topics such as polynomial algebra, symbolic and symbolic-numerical computation, applications of symbolic computation for investigating and solving ordinary differential equations, applications of CAS in the investigation and solution of celestial mechanics problems, and in mechanics, physics, and robotics.
Computational methods in systems biology ; Vol. 3082 ; International Conference CMSB 2004, Paris, France, May 26-28, 2004, Revised Selected Papers
present CMBSlib, a library of Computational Models of Biological Systems. It is aimed at providing a list of test problems for formalisms, modeling issues and implementation issues in systems biology. The main motivation for CMBSlib is to stimulate research on the formal modeling of biological systems, by facilitating the exchange of formal models between researchers, and by providing a forum of comparison and validation of not only models, but also modeling formalisms and implementations. Unlike a standardization effort, CMBSlib welcomes the most exotic formalisms and models provided they attack the modeling of well documented biological systems. Models of biological systems written in any referenced formalism can be submitted to CMBSlib. No special format or standard is required. We discuss the advantages of and problems encountered in building such a library, give an example of typical entry in the library, and most of all we invite the community to become active contributors to CMBSlib.
Computational intelligence in economics and finance ; Vol. II
Computational intelligence (CI), as an alternative to statistical and econometric approaches, has been applied to a wide range of economics and finance problems in recent years, for example to price forecasting and market efficiency. This book contains research ranging from applications in financial markets and business administration to various economics problems. Not only are empirical studies utilizing various CI algorithms presented, but so also are theoretical models based on computational methods. In addition to direct applications of computational intelligence, readers can also observe how these methods are combined with conventional analytical methods such as statistical and econometric models to yield preferred results.
Cognitive engineering : A distributed approach to machine intelligence
Cognitive Engineering: A Distributed Approach to Machine Intelligence explores the design issues of intelligent engineering systems. Beginning with the foundations of psychological modeling of the human mind, the main emphasis is given to parallel and distributed realization of intelligent models for application in reasoning, learning, planning and multi-agent co-ordination problems. The last two chapters provide case studies on human-mood detection and control, and behavioral co-operation of mobile robots. This is the first comprehensive text of its kind, bridging the gap between Cognitive Science and Cognitive Systems Engineering. Each chapter includes plenty of numerical examples and exercises with sufficient hints, so that the reader can solve the exercises on their own. Computer simulations are also included in most chapters to give a clear idea about the application of the algorithms undertaken in the book. In addition, mathematical analysis on convergence and stability of the neuro-fuzzy models will enable the reader to pursue their research career in cognitive engineering.
Coding for Data and Computer Communications
In a unique, single volume, this highly versatile text/reference introduces readers to the importance of channel coding (error-correcting codes), secure coding (cryptography), and source coding (data compression). It is organized in three main parts and uses clear, nonmathematical explanations to develop the concepts, principles, and techniques in each area of coding. Requiring only a general familiarity with computer methods, the book deals with all aspects of coding and its relevance to fast, secure, and reliable data transmission and storage. Features & Benefits: Presents comprehensive coverage of areas of coding often found in separate books, and stresses data coding’s relevance in today’s world / Provides a wealth of examples and exercises (with solutions) to help readers easily grasp the material / Incorporates an extensive chapter on data hiding, a sparsely documented topic of increasing importance in the community / Includes an author-supplied website with supplementary material / Possesses a detailed bibliography and helpful glossary, index, and appendixes (including projects for self-study).
CMOS Hotplate Chemical Microsensors
Covers all aspects of successful sensor prototyping: theory of transducer modelling, microelectronics design considerations, system design issues, and issues related to system and device microfabrication, packaging, and testing. A variety of different hotplates for different operation conditions is detailed and a family of metal-oxide-covered microhotplate-based microsensor systems with increasing complexity is presented. These systems belong to a new generation of chemical microsensors and represent examples of the successful integration of nanomaterials, microtechnology and microelectronics.The book provides students, scientists and engineers with an accessible introduction to the field of microhotplate-based chemical sensing, with all the necessary fundamental knowledge included. Beyond that, it also provides detailed information on all important issues concerning complex high-performance CMOS chemical microsensor systems; hence it will also be valuable to experts already familiar with the field.
CMOS Current-Mode Circuits for Data Communications
Addresses the analysis and design principles of CMOS current mode circuits and their applications for data communications. The analytical methods and design principles are based on the characteristics of MOS devices applied to current CMOS technologies. Major topics include: design techniques for current mode circuits, electrical signaling for high speed data links, current-mode transmitters and receivers, switching noise and grounding of mixed mode circuits, a comparison of voltage-mode with current-mode circuits, ESD protection, and additional related topics. Examples are given of CMOS technologies from leading semiconductor companies and analyzed using the latest computer-aided design tools by leading design companies. CMOS Current-Mode Circuits for Data Communications is a valuable reference for circuit design engineers and hardware system engineers.
CMOS Active Inductors and Transformers : Principle, Implementation, and Applications
CMOS Active Inductors and Transformers: Principle, Implementation, and Applications provides a systematic presentation and a detailed examination of the operation principles and implementations, and discusses their emerging applications in high-speed analog signal processing and data communications.
Cloud Native Architecture and Design : A Handbook for Modern Day Architecture and Design with Enterprise-Grade Examples
Explains the fundamentals of cloud-native architecture and services, what cloud principles and patterns to use, and details of designing a cloud-native element. And Progresses to cover the details of how IT systems can modernize to embrace cloud-native architecture, and also provides details of various enterprise assessment techniques to decide what systems can move and cannot move into the cloud. Architecting and designing a cloud-native system isn’t possible without modernized software engineering principles, the culture of automation, and the culture of innovation. As such, this book covers the details of cloud-native software engineering methodologies, and process, and how to adopt an automated governance approach across enterprises with the adoption of artificial intelligence. You will: Discover cloud-native principles and patterns, and how you can leverage them to solve your business problems ; Gain the techniques and concepts you need to adapt to design a cloud-native application ; Use assessment techniques and tools for IT modernization ; Apply cloud-native engineering principles to the culture of automation and culture of innovation ; Harness the techniques and tools to run your cloud-native applications and automate infrastructure ; Operate your cloud-native applications by using AI techniques and zero operation techniques
Matching Properties of Deep Sub-Micron MOS Transistors
Matching Properties of Deep Sub-Micron MOS Transistors examines this interesting phenomenon. Microscopic fluctuations cause stochastic parameter fluctuations that affect the accuracy of the MOSFET. For analog circuits this determines the trade-off between speed, power, accuracy and yield.
Mastering VMware Horizon 8 : An Advanced Guide to Delivering Virtual Desktops and Virtual Apps
Learn all about designing, installing, configuring, and managing VMware Horizon, with a core focus on how to deliver virtual desktops using Horizon. This book allows you to follow the complete process for deploying VMware Horizon and covers the design, deployment, and management of solutions. You will: See the core components of VMware Horizon and their functionality / Design and install a Horizon environment / Deliver the best end-user experience / Manage the deployed solution / Use VMware reference architectures to create real-life scenario examples / Review the minimum requirements for designing a solution
Mastering Oracle SQL and SQL*Plus
This exceptional book explains fundamentals in detail, supported by realistic examples, while most other books on the market do not properly cover such basics. If you work with relational databases you need to understand the SQL language. And you will gain full competence to define, access, and manipulate data in an Oracle database, if you do so following this book's guidance.
Markov Models for Pattern Recognition : From Theory to Applications
Describes the underlying theoretical concepts - covering Hidden Markov models and Markov chain models - and presents the techniques and algorithmic solutions essential to creating real world applications. The actual use of Markov models in their three main application areas - namely speech recognition, handwriting recognition, and biological sequence analysis - is presented with examples of successful systems.
Managing Risk and Information Security : Protect to Enable
Examine the evolving enterprise security landscape and discover how to manage and survive risk. While based primarily on the author’s experience and insights at major companies where he has served as CISO and CSPO, the book also includes many examples from other well-known companies and provides guidance for a management-level audience. Managing Risk and Information Security provides thought leadership in the increasingly important area of enterprise information risk and security. It describes the changing risk environment and why a fresh approach to information security is needed. Because almost every aspect of an enterprise is now dependent on technology not only for internal operations but increasing as a part of product or service creation, the focus of IT security must shift from locking down assets to enabling the business while managing and surviving risk. This edition discusses business risk from a broader perspective, including privacy and regulatory considerations. It describes the increasing number of threats and vulnerabilities and offers strategies for developing solutions. These include discussions of how enterprises can take advantage of new and emerging technologies—such as social media and the huge proliferation of Internet-enabled devices—while minimizing risk.
Management of Data Center Networks
Delivers a rigorous and insightful exploration of the network management challenges that present within intra- and inter-data center networks, including reliability, routing, and security. The book also discusses new architectures found in data center networks that aim to minimize the complexity of network management while maximizing Quality of Service, like Wireless/Wired DCNs, server-only DCNs, and more. offers: A thorough overview of the architectures of data center networks, including the classification of switch-centric, server-centric, enhanced, optical, and wireless DCN architectures An exploration of resource management in wired and wireless data center networks, including routing and wireless channel allocation and assignment challenges and criteria Practical discussions of inter-data center networks, including an overview of basic virtual network embedding Examinations of energy and security management in data center networks
Machine Learning Techniques for Multimedia : Case Studies on Organization and Retrieval
This book provides a comprehensive coverage of the most important machine learning techniques used and their application in this domain. Arising from the EU MUSCLE network, a program that drew together multidisciplinary teams with expertise in machine learning, pattern recognition, artificial intelligence, and image, video, text and crossmedia processing, the book first introduces the machine learning principles and techniques that are applied in multimedia data processing and analysis. The second part focuses on multimedia data processing applications, with chapters examining specific machine learning issues in domains .
Machine Learning Refined : Foundations, Algorithms, and Applications
Provides students with the fundamental knowledge and practical tools needed to conduct research and build data-driven products. The authors prioritize geometric intuition and algorithmic thinking, and include detail on all the essential mathematical prerequisites, to offer a fresh and accessible way to learn. Practical applications are emphasized, with examples from disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology.
Machine learning in healthcare : Fundamentals and recent applications
Discusses how to build various ML algorithms and how they can be applied to improve healthcare systems. Healthcare applications of AI are innumerable: medical data analysis, early detection and diagnosis of disease, providing objective-based evidence to reduce human errors, curtailing inter- and intra-observer errors, risk identification and interventions for healthcare management, real-time health monitoring, assisting clinicians and patients for selecting appropriate medications, and evaluating drug responses. Extensive demonstrations and discussion on the various principles of machine learning and its application in healthcare is provided, along with solved examples and exercises.
Machine learning for data streams : With practical examples in MOA
The book first offers a brief introduction to the topic, covering big data mining, basic methodologies for mining data streams, and a simple example of MOA. More detailed discussions follow, with chapters on sketching techniques, change, classification, ensemble methods, regression, clustering, and frequent pattern mining. Most of these chapters include exercises, an MOA-based lab session, or both. Finally, the book discusses the MOA software, covering the MOA graphical user interface, the command line, use of its API, and the development of new methods within MOA.
Local Pattern Detection ; International Seminar Dagstuhl Castle, Germany, April 12-16, 2004, Revised Selected Papers
Introduction The dramatic increase in available computer storage capacity over the last 10 years has led to the creation of very large databases of scienti?c and commercial information. The need to analyze these masses of data has led to the evolution of the new field knowledge discovery in databases (KDD) at the intersection of machine learning, statistics and database technology. Being interdisciplinary by nature, the field offers the opportunity to combine the expertise of different fields into a common objective. Moreover, within each field diverse methods have been developed and justified with respect to different quality criteria. We have to investigate how these methods can contributet o solving the problem of KDD. Traditionally, KDD was seeking to end global models for the data that - plain most of the instances of the database and describe the general structure of the data. Examples are statistical time series models, cluster models, logic programs with high coverageor classi?cation models like decision trees or linear decision functions. In practice, though, the use of these models often is very l- ited, because global models tend to end only the obvious patterns in the data, 1 which domain experts already are aware of . What is really of interest to the users are the local patterns that deviate from the already-known background knowledge. David Hand, who organized a workshop in 2002, proposed the new field of local patterns.
