Transactions on Computational Science XXIX PDF Download

Author: Marina L. Gavrilova
Publisher: Springer
ISBN: 3662545632
Category : Computers
Languages : en
Pages : 139

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Book Description
This, the 29th issue of the Transactions on Computational Science journal, is comprised of seven full papers focusing on the area of secure communication. Topics covered include weak radio signals, efficient circuits, multiple antenna sensing techniques, modes of inter-computer communication and fault types, geometric meshes, and big data processing in distributed environments.

Author: Marina L. Gavrilova
Publisher: Springer Science & Business Media
ISBN: 354087562X
Category : Computers
Languages : en
Pages : 256

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Book Description
The LNCS journal Transactions on Computational Science reflects recent developments in the field of Computational Science, conceiving the field not as a mere ancillary science but rather as an innovative approach supporting many other scientific disciplines. The journal focuses on original high-quality research in the realm of computational science in parallel and distributed environments, encompassing the facilitating theoretical foundations and the applications of large-scale computations and massive data processing. It addresses researchers and practitioners in areas ranging from aerospace to biochemistry, from electronics to geosciences, from mathematics to software architecture, presenting verifiable computational methods, findings and solutions and enabling industrial users to apply techniques of leading-edge, large-scale, high performance computational methods. Transactions on Computational Science II is devoted to the subject of denotational mathematics for computational intelligence. Denotational mathematics, as a counterpart of conventional analytic mathematics, is a category of expressive mathematical structures that deals with high-level mathematical entities beyond numbers and sets, such as abstract objects, complex relations, behavioral information, concepts, knowledge, processes, granules, and systems. This volume includes 12 papers covering the following four important areas: foundations and applications of denotational mathematics; rough and fuzzy set theories; granular computing; and knowledge and information modeling.

Author: Yingxu Wang
Publisher: Springer
ISBN: 3540875638
Category : Computers
Languages : en
Pages : 250

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Book Description
The denotational and expressive needs in cognitive informatics, computational intelligence, software engineering, and knowledge engineering have led to the development of new forms of mathematics collectively known as denotational mathematics. Denotational mathematics is a category of mathematical structures that formalize rigorous expressions and long-chain inferences of system compositions and behaviors with abstract concepts, complex relations, and dynamic processes. Typical paradigms of denotational mathematics are concept algebra, system algebra, Real-Time Process Algebra (RTPA), Visual Semantic Algebra (VSA), fuzzy logic, and rough sets. A wide range of applications of denotational mathematics have been identified in many modern science and engineering disciplines that deal with complex and intricate mathematical entities and structures beyond numbers, Boolean variables, and traditional sets. This issue of Springer’s Transactions on Computational Science on Denotational Mathematics for Computational Intelligence presents a snapshot of current research on denotational mathematics and its engineering applications. The volume includes selected and extended papers from two international conferences, namely IEEE ICCI 2006 (on Cognitive Informatics) and RSKT 2006 (on Rough Sets and Knowledge Technology), as well as new contributions. The following four important areas in denotational mathem- ics and its applications are covered: Foundations and applications of denotational mathematics, focusing on: a) c- temporary denotational mathematics for computational intelligence; b) deno- tional mathematical laws of software; c) a comparative study of STOPA and RTPA; and d) a denotational mathematical model of abstract games.

Author: Das, Rik
Publisher: IGI Global
ISBN: 1522557768
Category : Computers
Languages : en
Pages : 284

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Book Description
Image data has portrayed immense potential as a foundation of information for numerous applications. Recent trends in multimedia computing have witnessed a rapid growth in digital image collections, resulting in a need for increased image data management. Feature Dimension Reduction for Content-Based Image Identification is a pivotal reference source that explores the contemporary trends and techniques of content-based image recognition. Including research covering topics such as feature extraction, fusion techniques, and image segmentation, this book explores different theories to facilitate timely identification of image data and managing, archiving, maintaining, and extracting information. This book is ideally designed for engineers, IT specialists, researchers, academicians, and graduate-level students seeking interdisciplinary research on image processing and analysis.

Author: Ngoc Thanh Nguyen
Publisher: Springer
ISBN: 9783319902869
Category : Computers
Languages : en
Pages : 201

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Book Description
These transactions publish research in computer-based methods of computational collective intelligence (CCI) and their applications in a wide range of fields such as the semantic Web, social networks, and multi-agent systems. TCCI strives to cover new methodological, theoretical and practical aspects of CCI understood as the form of intelligence that emerges from the collaboration and competition of many individuals (artificial and/or natural). The application of multiple computational intelligence technologies, such as fuzzy systems, evolutionary computation, neural systems, consensus theory, etc., aims to support human and other collective intelligence and to create new forms of CCI in natural and/or artificial systems. This twenty-ninth issue is a regular issue with 10 selected papers. ​

Author: Marina L. Gavrilova
Publisher: Springer
ISBN: 3662470748
Category : Computers
Languages : en
Pages : 201

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Book Description
The LNCS journal Transactions on Computational Science reflects recent developments in the field of Computational Science, conceiving the field not as a mere ancillary science but rather as an innovative approach supporting many other scientific disciplines. The journal focuses on original high-quality research in the realm of computational science in parallel and distributed environments, encompassing the facilitating theoretical foundations and the applications of large-scale computations and massive data processing. It addresses researchers and practitioners in areas ranging from aerospace to biochemistry, from electronics to geosciences, from mathematics to software architecture, presenting verifiable computational methods, findings and solutions and enabling industrial users to apply techniques of leading-edge, large-scale, high performance computational methods. This, the 25th issue of the Transactions on Computational Science journal, consists of two parts. Part I, which is guest edited by Khalid Saeed, Nabendu Chaki and Soharab Hossain Shaikh, covers the areas of computer vision, image processing for biometric security, information fusion, and Kinect activity recognition. The papers in Part II focus on optimization through novel methods for data fusion, clustering in WSN, fault-tolerance, probability, weight assignment and risk analysis.

Author: C. J. Kenneth Tan
Publisher: Springer Science & Business Media
ISBN: 3540792988
Category : Computers
Languages : en
Pages : 192

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Book Description
The LNCS journal Transactions on Computational Science reflects recent developments in the field of Computational Science, conceiving the field not as a mere ancillary science but rather as an innovative approach supporting many other scientific disciplines. The journal focuses on original high-quality research in the realm of Computational Science in parallel and distributed environments, encompassing the facilitating theoretical foundations and the applications of large-scale computations and massive data processing. It addresses researchers and practitioners in areas ranging from aerospace to biochemistry, from electronics to geosciences, from mathematics to software architecture, presenting verifiable computational methods, findings and solutions and enabling industrial users to apply techniques of leading-edge, large-scale, high performance computational methods. This inaugural volume is devoted to computer systems research with an emphasis on core computational science issues faced by researchers and industries today, and focusing on the development of novel computational techniques that are versatile and verifiable in a wide range of applications. The volume is divided into two parts. The five papers in Part 1 focus on the theme of information system design, and the four papers in Part 2 are concerned with specific computational science problems in the area of data processing.

Author: Marina Gavrilova
Publisher: Springer
ISBN: 3642542123
Category : Computers
Languages : en
Pages : 173

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Book Description
This, the 22nd issue of the Transactions on Computational Science journal, consists of two parts. The first part is devoted to neural and social networks and the second to geometric modeling and simulation. The four papers in Part I span the areas of information-driven online social networks, neural networks, collaborative memories, and stability controls in multi-agent networked environments. The four papers in Part II cover the topics of shape reconstruction from planar contours, sharp feature preservation through wavelets, protein structure determination based on the beta-complex, and fast empty volume computation in molecular systems.

Author: Rik Das
Publisher: CRC Press
ISBN: 1000280713
Category : Computers
Languages : en
Pages : 202

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Book Description
Content-Based Image Classification: Efficient Machine Learning Using Robust Feature Extraction Techniques is a comprehensive guide to research with invaluable image data. Social Science Research Network has revealed that 65% of people are visual learners. Research data provided by Hyerle (2000) has clearly shown 90% of information in the human brain is visual. Thus, it is no wonder that visual information processing in the brain is 60,000 times faster than text-based information (3M Corporation, 2001). Recently, we have witnessed a significant surge in conversing with images due to the popularity of social networking platforms. The other reason for embracing usage of image data is the mass availability of high-resolution cellphone cameras. Wide usage of image data in diversified application areas including medical science, media, sports, remote sensing, and so on, has spurred the need for further research in optimizing archival, maintenance, and retrieval of appropriate image content to leverage data-driven decision-making. This book demonstrates several techniques of image processing to represent image data in a desired format for information identification. It discusses the application of machine learning and deep learning for identifying and categorizing appropriate image data helpful in designing automated decision support systems. The book offers comprehensive coverage of the most essential topics, including: Image feature extraction with novel handcrafted techniques (traditional feature extraction) Image feature extraction with automated techniques (representation learning with CNNs) Significance of fusion-based approaches in enhancing classification accuracy MATLAB® codes for implementing the techniques Use of the Open Access data mining tool WEKA for multiple tasks The book is intended for budding researchers, technocrats, engineering students, and machine learning/deep learning enthusiasts who are willing to start their computer vision journey with content-based image recognition. The readers will get a clear picture of the essentials for transforming the image data into valuable means for insight generation. Readers will learn coding techniques necessary to propose novel mechanisms and disruptive approaches. The WEKA guide provided is beneficial for those uncomfortable coding for machine learning algorithms. The WEKA tool assists the learner in implementing machine learning algorithms with the click of a button. Thus, this book will be a stepping-stone for your machine learning journey. Please visit the author's website for any further guidance at https://www.rikdas.com/

Author: Marina L. Gavrilova
Publisher: Springer
ISBN: 366250412X
Category : Computers
Languages : en
Pages : 141

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Book Description
The LNCS journal Transactions on Computational Science reflects recent developments in the field of Computational Science, conceiving the field not as a mere ancillary science but rather as an innovative approach supporting many other scientific disciplines. The journal focuses on original high-quality research in the realm of computational science in parallel and distributed environments, encompassing the facilitating theoretical foundations and the applications of large-scale computations and massive data processing. It addresses researchers and practitioners in areas ranging from aerospace to biochemistry, from electronics to geosciences, from mathematics to software architecture, presenting verifiable computational methods, findings, and solutions, and enabling industrial users to apply techniques of leading-edge, large-scale, high performance computational methods. This, the 27th issue of the Transactions on Computational Science journal, is devoted to the topic of high-performance computing. It contains eight full papers, covering the areas of cloud middleware, multi-processor systems, quantum computing, optimization, and secure biometric-based encryption methods.