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Advanced Computing Applications, Databases and Networks
ADVANCED COMPUTING APPLICATIONS, DATABASES AND NETWORKS focuses on new developments and advances in three major areas of Computer Science. The first part presents some significant contributions and surveys major research areas of Advanced Computing Applications viz. Natural Language Processing, Medical Imaging, Soft Computing Methodologies and a wide variety of its application domains. The second part explains different approaches towards development of Unified Theoretical Model for Database Mining, Dimension Reduction of higher dimensional data and the applicability of Soft Computing Methodologies in Data Mining and Clustering. The third part provides the approaches taken to address the challenging problems in the areas of Wired and Wireless Networks. The chapters in this volume are representative of recent research efforts and advances in the area of Advanced Computing Applications, Databases and Networks, covering both theoretical and application issues.
Theory and Practice of Natural Computing
This book constitutes the refereed proceedings of the 9th International Conference on Theory and Practice of Natural Computing, TPNC 2020, held in Taoyuan, Taiwan, in December 2020. The 12 full papers presented in this book, together with one invited talk, were carefully reviewed and selected from 24 submissions. The papers are organized in topical sections named: applications of natural computing; quantum computing and unconventional computing; and swarm intelligence, evolutionary algorithms, and DNA computing.
Distance and Similarity Measures for Neutrosophic HyperSoft Set (NHSS) With Construction of NHSS-TOPSIS and Applications
Neutrosophic HyperSoft Set (NHSS) is a new approach towards computational intelligence and decision making under uncertainty. In this paper, we first consider distances for NHSS, and then propose similarity measures for NHSS. We also consider aggregated operation for aggregating NHSS decision matrix. TOPSIS (Technique for the order preference by similarity to ideal solution) is a strong approach for multi-criteria decision making (MCDM) which has been studied under various extensions of fuzzy sets. These approaches have drawbacks in depicting fuzzy decision-making information for handling MCDM situations under NHSS environment.
A Novel MCDM Method Based on Plithogenic Hypersoft Sets under Fuzzy Neutrosophic Environment
In this paper, we advance the study of plithogenic hypersoft set (PHSS).We present four classifications of PHSS that are based on the number of attributes chosen for application and the nature of alternatives or that of attribute value degree of appurtenance. These four PHSS classifications cover most of the fuzzy and neutrosophic cases that can have neutrosophic applications in symmetry. We also make explanations with an illustrative example for demonstrating these four classifications.
Hausdorff Distance and Similarity Measures for Single-Valued Neutrosophic Sets with Application in Multi-Criteria Decision Making
Hausdorff distance is one of the important distance measures to study the degree of dissimilarity between two sets that had been used in various fields under fuzzy environments. Among those, the framework of single-valued neutrosophic sets (SVNSs) is the one that has more potential to explain uncertain, inconsistent and indeterminate information in a comprehensive way. And so, Hausdorff distance for SVNSs is important. Thus, we propose two novel schemes to calculate the Hausdorff distance and its corresponding similarity measures (SMs) for SVNSs. In doing so, we firstly develop the two forms of Hausdorff distance between SVNSs based on the definition of Hausdorff metric between two sets. We ...
Advanced Concepts for Intelligent Vision Systems
This book constitutes the refereed proceedings of the 7th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2005, held in Antwerp, Belgium in September 2005. The 90 revised full papers presented were carefully reviewed and selected from around 200 submissions. The papers are organized in topical sections on biometrics, classification and recognition, content and performance characterization, image and video analysis, image and video coding, image and video segmentation, medical image processing applications, motion estimation and tracking, noise reduction and restauration, and real-time processing and hardware.
A Novel MCDM Method Based on Plithogenic Hypersoft Sets under Fuzzy Neutrosophic Environment
In this paper, we advance the study of plithogenic hypersoft set (PHSS).We present four classifications of PHSS that are based on the number of attributes chosen for application and the nature of alternatives or that of attribute value degree of appurtenance. These four PHSS classifications cover most of the fuzzy and neutrosophic cases that can have neutrosophic applications in symmetry. We also make explanations with an illustrative example for demonstrating these four classifications. We then propose a novel multi-criteria decision making (MCDM) method that is based on PHSS, as an extension of the technique for order preference by similarity to an ideal solution (TOPSIS).
Artificial Intelligence and Computational Intelligence
This volume proceedings contains revised selected papers from the 4th International Conference on Artificial Intelligence and Computational Intelligence, AICI 2012, held in Chengdu, China, in October 2012. The total of 163 high-quality papers presented were carefully reviewed and selected from 724 submissions. The papers are organized into topical sections on applications of artificial intelligence, applications of computational intelligence, data mining and knowledge discovery, evolution strategy, expert and decision support systems, fuzzy computation, information security, intelligent control, intelligent image processing, intelligent information fusion, intelligent signal processing, machine learning, neural computation, neural networks, particle swarm optimization, and pattern recognition.
Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery
This book consists of papers on the recent progresses in the state of the art in natural computation, fuzzy systems and knowledge discovery. The book is useful for researchers, including professors, graduate students, as well as R & D staff in the industry, with a general interest in natural computation, fuzzy systems and knowledge discovery. The work printed in this book was presented at the 2020 16th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD 2020), held in Xi'an, China, from 19 to 21 December 2020. All papers were rigorously peer-reviewed by experts in the areas.
Analysing Data from Capacitive Floor Sensors for Human Gait Assessment Using Artificial Neural Networks
Gait analysis is valuable in medical research and diagnosis, by delivering information that helps in choosing methods of intervention and rehabilitation that are beneficial for a patient. In gait laboratories, cameras or IMUs are often used to gather gait patterns. This thesis explores the possibility of using sensors below the floor as a gait data source. These sensors measure changes in the electrical capacitance to recognise steps. The construction is designed for indoor environments and is hidden under common flooring layer types. Therefore, it is very robust and suitable for practical use in daily clinical routine. A formal framework was developed to represent the measurements, consider...
