Anuradha D Thakare – författare

Hybrid Intelligent Systems for Information Retrieval covers three areas along with the introduction to Intelligent IR, i.e., Optimal Information Retrieval Using Evolutionary Approaches, Semantic Search for Web Information Retrieval, and Natural Language Processing for Information Retrieval.• Talks about the design, implementation, and performance issues of the hybrid intelligent information retrieval system in one book• Gives a clear insight into challenges and issues in designing a hybrid information retrieval system• Includes case studies on structured and unstructured data for hybrid intelligent information retrieval• Provides research directions for the design and development of intelligent search enginesThis book is aimed primarily at graduates and researchers in the information retrieval domain.

Hybrid Intelligent Systems for Information Retrieval covers three areas along with the introduction to Intelligent IR, i.e., Optimal Information Retrieval Using Evolutionary Approaches, Semantic Search for Web Information Retrieval, and Natural Language Processing for Information Retrieval.• Talks about the design, implementation, and performance issues of the hybrid intelligent information retrieval system in one book• Gives a clear insight into challenges and issues in designing a hybrid information retrieval system• Includes case studies on structured and unstructured data for hybrid intelligent information retrieval• Provides research directions for the design and development of intelligent search enginesThis book is aimed primarily at graduates and researchers in the information retrieval domain.

Fundamentals of Data Science is designed for students, academicians and practitioners with a complete walkthrough right from the foundational groundwork required to outlining all the concepts, techniques and tools required to understand Data Science.Data Science is an umbrella term for the non-traditional techniques and technologies that are required to collect, aggregate, process, and gain insights from massive datasets. This book offers all the processes, methodologies, various steps like data acquisition, pre-process, mining, prediction, and visualization tools for extracting insights from vast amounts of data by the use of various scientific methods, algorithms, and processesReaders will learn the steps necessary to create the application with SQl, NoSQL, Python, R, Matlab, Octave and Tablue.This book provides a stepwise approach to building solutions to data science applications right from understanding the fundamentals, performing data analytics to writing source code. All the concepts are discussed in simple English to help the community to become Data Scientist without much pre-requisite knowledge.Features : Simple strategies for developing statistical models that analyze data and detect patterns, trends, and relationships in data sets. Complete roadmap to Data Science approach with dedicatedsections which includes Fundamentals, Methodology and Tools. Focussed approach for learning and practice various Data Science Toolswith Sample code and examples for practice. Information is presented in an accessible way for students, researchers and academicians and professionals.

This book provides an essential overview of IoT, energy-efficient topology control protocols, motivation, and challenges for topology control for Wireless Sensor Networks, and the scope of the research in the domain of IoT. Further, it discusses the different design issues of topology control and energy models for IoT applications, different types of simulators with their advantages and disadvantages. It also discusses extensive simulation results and comparative analysis for various algorithms. The key point of this book is to present a solution to minimize energy and extend the lifetime of IoT networks using optimization methods to improve the performance.Features:Describes various facets necessary for energy optimization in IoT domainCovers all aspects to achieve energy optimization using latest technologies and algorithms, in wireless sensor networksPresents various IoT and Topology Control Methods and protocols, various network models, and model simulation using MATLAB®Reviews methods and results of optimization with Simulation Hardware architecture leading to prolonged life of IoT networksFirst time introduces bio-inspired algorithms in the IoT domain for performance optimizationThis book aims at Graduate Students, Researchers in Information Technology, Computer Science and Engineering, Electronics and Communication Engineering.

This book provides an essential overview of IoT, energy-efficient topology control protocols, motivation, and challenges for topology control for Wireless Sensor Networks, and the scope of the research in the domain of IoT. Further, it discusses the different design issues of topology control and energy models for IoT applications, different types of simulators with their advantages and disadvantages. It also discusses extensive simulation results and comparative analysis for various algorithms. The key point of this book is to present a solution to minimize energy and extend the lifetime of IoT networks using optimization methods to improve the performance.Features:Describes various facets necessary for energy optimization in IoT domainCovers all aspects to achieve energy optimization using latest technologies and algorithms, in wireless sensor networksPresents various IoT and Topology Control Methods and protocols, various network models, and model simulation using MATLAB®Reviews methods and results of optimization with Simulation Hardware architecture leading to prolonged life of IoT networksFirst time introduces bio-inspired algorithms in the IoT domain for performance optimizationThis book aims at Graduate Students, Researchers in Information Technology, Computer Science and Engineering, Electronics and Communication Engineering.

OBJECT DETECTION BY STEREO VISION IMAGES Since both theoretical and practical aspects of the developments in this field of research are explored, including recent state-of-the-art technologies and research opportunities in the area of object detection, this book will act as a good reference for practitioners, students, and researchers. Current state-of-the-art technologies have opened up new opportunities in research in the areas of object detection and recognition of digital images and videos, robotics, neural networks, machine learning, stereo vision matching algorithms, soft computing, customer prediction, social media analysis, recommendation systems, and stereo vision. This book has been designed to provide directions for those interested in researching and developing intelligent applications to detect an object and estimate depth. In addition to focusing on the performance of the system using high-performance computing techniques, a technical overview of certain tools, languages, libraries, frameworks, and APIs for developing applications is also given. More specifically, detection using stereo vision images/video from its developmental stage up till today, its possible applications, and general research problems relating to it are covered. Also presented are techniques and algorithms that satisfy the peculiar needs of stereo vision images along with emerging research opportunities through analysis of modern techniques being applied to intelligent systems. Audience Researchers in information technology looking at robotics, deep learning, machine learning, big data analytics, neural networks, pattern & data mining, and image and object recognition. Industrial sectors include automotive electronics, security and surveillance systems, and online retailers.

ARTIFICIAL INTELLIGENCE APPLICATIONS and RECONFIGURABLE ARCHITECTURES The primary goal of this book is to present the design, implementation, and performance issues of AI applications and the suitability of the FPGA platform. This book covers the features of modern Field Programmable Gate Arrays (FPGA) devices, design techniques, and successful implementations pertaining to AI applications. It describes various hardware options available for AI applications, key advantages of FPGAs, and contemporary FPGA ICs with software support. The focus is on exploiting parallelism offered by FPGA to meet heavy computation requirements of AI as complete hardware implementation or customized hardware accelerators. This is a comprehensive textbook on the subject covering a broad array of topics like technological platforms for the implementation of AI, capabilities of FPGA, suppliers’ software tools and hardware boards, and discussion of implementations done by researchers to encourage the AI community to use and experiment with FPGA. Readers will benefit from reading this book because It serves all levels of students and researcher’s as it deals with the basics and minute details of Ecosystem Development Requirements for Intelligent applications with reconfigurable architectures whereas current competitors’ books are more suitable for understanding only reconfigurable architectures.It focuses on all aspects of machine learning accelerators for the design and development of intelligent applications and not on a single perspective such as only on reconfigurable architectures for IoT applications.It is the best solution for researchers to understand how to design and develop various AI, deep learning, and machine learning applications on the FPGA platform.It is the best solution for all types of learners to get complete knowledge of why reconfigurable architectures are important for implementing AI-ML applications with heavy computations.Audience Researchers, industrial experts, scientists, and postgraduate students who are working in the fields of computer engineering, electronics, and electrical engineering, especially those specializing in VLSI and embedded systems, FPGA, artificial intelligence, Internet of Things, and related multidisciplinary projects.

Fundamentals of Data Science is designed for students, academicians and practitioners with a complete walkthrough right from the foundational groundwork required to outlining all the concepts, techniques and tools required to understand Data Science.Data Science is an umbrella term for the non-traditional techniques and technologies that are required to collect, aggregate, process, and gain insights from massive datasets. This book offers all the processes, methodologies, various steps like data acquisition, pre-process, mining, prediction, and visualization tools for extracting insights from vast amounts of data by the use of various scientific methods, algorithms, and processesReaders will learn the steps necessary to create the application with SQl, NoSQL, Python, R, Matlab, Octave and Tablue.This book provides a stepwise approach to building solutions to data science applications right from understanding the fundamentals, performing data analytics to writing source code. All the concepts are discussed in simple English to help the community to become Data Scientist without much pre-requisite knowledge.Features : Simple strategies for developing statistical models that analyze data and detect patterns, trends, and relationships in data sets. Complete roadmap to Data Science approach with dedicatedsections which includes Fundamentals, Methodology and Tools. Focussed approach for learning and practice various Data Science Toolswith Sample code and examples for practice. Information is presented in an accessible way for students, researchers and academicians and professionals.

Real-time IoT-based healthcare systems can be modeled using an IoT-based metaheuristic approach to generate optimal solutions.Metaheuristics are powerful technologies for optimization problems in healthcare systems.