Magnetic Resonance Imaging: Recording, Reconstruction and Assessment gives a detailed overview of magnetic resonance imaging (MRI), along with its applications and challenges. The book explores the abnormalities in internal human organs using MRI techniques while also featuring case studies that illustrate measures used. In addition, it explores precautionary measures used during MRI based imaging, the selection of appropriate contrast agents, and the selection of the appropriate modality during the image registration. Sections introduce medical imaging, the use of MRI in brain, cardiac, lung and kidney detection, and also discuss both 2D and 3D imaging techniques and various MRI modalities. This volume will be of interest to researchers, engineers and medical professionals involved in the development and use of MRI systems. - Discusses challenges and issues faced, as well as safety precautions to be followed - Features case studies with benchmark MRIs existing in the literature - Introduces computer-based assessment (Machine Learning and Deep Learning) of the MRI based on its 2D slices
The information age has led to an explosion in the amount of information available to the individual and the means by which it is accessed, stored, viewed, and transferred. In particular, the growth of the internet has led to the creation of huge repositories of multimedia documents in a diverse range of scientific and professional fields, as well as the tools to extract useful knowledge from them. Mining Multimedia Documents is a must-read for researchers, practitioners, and students working at the intersection of data mining and multimedia applications. It investigates various techniques related to mining multimedia documents based on text, image, and video features. It provides an insight into the open research problems benefitting advanced undergraduates, graduate students, researchers, scientists and practitioners in the fields of medicine, biology, production, education, government, national security and economics.
Thanks to recent advances in sensors, communication and satellite technology, data storage, processing and networking capabilities, satellite image acquisition and mining are now on the rise. In turn, satellite images play a vital role in providing essential geographical information. Highly accurate automatic classification and decision support systems can facilitate the efforts of data analysts, reduce human error, and allow the rapid and rigorous analysis of land use and land cover information. Integrating Machine Learning (ML) technology with the human visual psychometric can help meet geologists’ demands for more efficient and higher-quality classification in real time. This book introduces readers to key concepts, methods and models for satellite image analysis; highlights state-of-the-art classification and clustering techniques; discusses recent developments and remaining challenges; and addresses various applications, making it a valuable asset for engineers, data analysts and researchers in the fields of geographic information systems and remote sensing engineering.
Soft Computing Based Medical Image Analysis presents the foremost techniques of soft computing in medical image analysis and processing. It includes image enhancement, segmentation, classification-based soft computing, and their application in diagnostic imaging, as well as an extensive background for the development of intelligent systems based on soft computing used in medical image analysis and processing. The book introduces the theory and concepts of digital image analysis and processing based on soft computing with real-world medical imaging applications. Comparative studies for soft computing based medical imaging techniques and traditional approaches in medicine are addressed, providing flexible and sophisticated application-oriented solutions. - Covers numerous soft computing approaches, including fuzzy logic, neural networks, evolutionary computing, rough sets and Swarm intelligence - Presents transverse research in soft computing formation from various engineering and industrial sectors in the medical domain - Highlights challenges and the future scope for soft computing based medical analysis and processing techniques
A Beginner’s Guide to Image Multi-Level Thresholding emphasizes various image thresholding methods that are necessary for image pre-processing and initial level enhancement. Explains basic concepts and the implementation of Image Multi-Level Thresholding (grayscale and RGB images) Presents a detailed evaluation in real-time application, including the need for heuristic algorithm, the choice of objective and threshold function, and the evaluation of the outcome Describes how the image thresholding acts as a pre-processing technique and how the region of interest in a medical image is enhanced with thresholding Illustrates integration of the thresholding technique with bio-inspired algorithms Includes current findings and future directions of image multi-level thresholding and its practical implementation Emphasizes the need for multi-level thresholding with suitable examples The book is aimed at graduate students and researchers in image processing, electronics engineering, computer sciences and engineering.
As UAV technology is rapidly evolving, a pervasive need for a thorough investigation of its full capabilities has come to the forefront. Internet of Drone Things: Architectures, Approaches, and Applications fulfils this need enabling its readers to easily find the answers they are seeking by providing a comprehensive overview of the topic.This book, in fact, includes fundamental information related to IoDT architecture design and features; reviews the state of the art in hardware and software platforms to deploy, connect, and control drones or swarms of drones; and covers the latest developments in innovative drone-facilitated applications and services that can significantly improve efficiency, productivity, and sustainability of various operations in modern society and a growing number of its industries. Finally, experimental modeling and simulations are accompanied by prototyping examples, which are set to become the benchmark of next-level automation in the field.Internet of Drone Things: Architectures, Approaches, and Applications is, therefore, an invaluable resource for engineering students, researchers, and professionals, as well as sector experts who work to develop new drone standards or to identify new drone technology use and commercialization areas at an international level. - Educates readers on the fundamental properties of an Internet of Drone Things (IoDT) ecosystem - Guides readers to effective network architecture design through experimental modeling and simulations - Provides in-depth research on the progress made in the domain of UAV networks, routing, sensing, and UAV operation management - Offers state-of-the-art IoDT platform-enabled application examples
For optimal computer vision outcomes, attention to image pre-processing is required so that one can improve image features by eliminating unwanted falsification. This book emphasizes various image pre-processing methods which are necessary for early extraction of features from the image. Effective use of image pre-processing can offer advantages and resolve complications that finally results in improved detection of local and global features. Different approaches for image enrichments and improvements are conferred in this book that will affect the feature analysis depending on how the procedures are employed. Key Features Describes the methods used to prepare images for further analysis which includes noise removal, enhancement, segmentation, local, and global feature description Includes image data pre-processing for neural networks and deep learning Covers geometric, pixel brightness, filtering, mathematical morphology transformation, and segmentation pre-processing techniques Illustrates a combination of basic and advanced pre-processing techniques essential to computer vision pipeline Details complications to resolve using image pre-processing
Biomedical Sensors and Smart Sensing: A Beginner's Guide, a book in the 10-volume Primers in Biomedical Imaging Devices and Systems series, covers a wide range of interdisciplinary applications in imaging modalities, nuclear medicine, computed tomographic systems, x-ray systems, magnetic resonance imaging, ultrasound, and virtual reality. The series explores the essential fundamental techniques required to analyze and process signals and images for diagnosis, scientific discovery and medical applications. Volumes in this series cover a wide range of interdisciplinary areas, combining foundational content with practical case studies to demonstrate the applications of these technologies in real-world situations. In addition, the 10-volume series considers various medical devices, electronics, circuits, sensors and algorithms. Several applications ranging from basic biological science to clinical practice are included to facilitate ongoing research. - Covers a variety of sensing and signal processing techniques - Introduces different approaches relating to communication and intelligent data processing for early detection and prediction of diseases - Includes practical case studies
Coefficient of Variation (CV) is a unit free index indicating the consistency of the data associated with a real-world process and is simple to mold into computational paradigms. This book provides necessary exposure of computational strategies, properties of CV and extracting the metadata leading to efficient knowledge representation. It also compiles representational and classification strategies based on the CV through illustrative explanations. The potential nature of CV in the context of contemporary Machine Learning strategies and the Big Data paradigms is demonstrated through selected applications. Overall, this book explains statistical parameters and knowledge representation models.
The Book presents an overview of newly developed watermarking techniques in various independent and hybrid domains Covers the basics of digital watermarking, its types, domain in which it is implemented and the application of machine learning algorithms onto digital watermarking Reviews hardware implementation of watermarking Discusses optimization problems and solutions in watermarking with a special focus on bio-inspired algorithms Includes a case study along with its MATLAB code and simulation results
A Beginners Guide to Data Agglomeration and Intelligent Sensing provides an overview of the Sensor Cloud Platform, Converge-casting, and Data Aggregation in support of intelligent sensing and relaying of information. The book begins with a brief introduction on sensors and transducers, giving readers insight into the various types of sensors and how one can work with them. In addition, it gives several real-life examples to help readers properly understand concepts. An overview of concepts such as wireless sensor networks, cloud platforms, and device-to-cloud and sensor cloud architecture are explained briefly, as is data gathering in wireless sensor networks and aggregation procedures. Final sections explore how to process gathered data and relay the data in an intelligent way, including concepts such as supervised and unsupervised learning, software defined networks, sensor data mining and smart systems.
Today’s India is bold and ambitious, seeing eye-to-eye with the Global North. It is a nation that has big dreams and works hard to achieve those dreams. This volume is a tribute to the India that has traversed a long way over the last 75 years and aspires to reach even greater milestones. It is also a tribute to the millennial India that understands its priorities for the next 25 years and is gearing up to face and overcome its challenges. Azadi Ka Amrit Mahotsav is the government’s initiative to celebrate and commemorate 75 years of India’s independence and the glorious history of its people, cultures, and achievements. Yet, it is not merely a celebration of the India of yore, but of the aspirational and ambitious India of the present and future. It is in this context that this compendium discusses the 10 policies that will shape the future sustainable India. During the 2021 Independence Day celebration, Prime Minister Narendra Modi used the term Amrit Kaal to delineate India’s development pathway over the next 25 years. “The fulfilment of our resolutions in this Amrit period will take us to the hundredth anniversary of Indian independence with pride,” he stated.[1] This compendium, Amrit Mahotsav: 10 Policies Shaping a Sustainable India, aims to celebrate the 75 years of Indian independence (the Amrit Mahotsav) and is a tribute to the India that will traverse the next 25 years of its development armed with crucial policies that will address enduring challenges and shape a more sustainable future for the country and its people.
The development of a state cannot be confined only to its economic arena but the socio-political, as well as cultural fields of a state, were also needed to be developed and modernized. Among the various guiding forces behind the development process of a state, migration sometimes plays a vital role in it. During the last fifty years of Manikya rule, a large number of immigrants, especially Bengali immigrants, entered into the princely, hilly state of Tripura from colonial India. These immigrations though outnumbered the aborigines of this hilly state, but it stimulated the developmental process of this Princely State which was initiated by the Manikya rulers in the last quarter of the 19th century. This book is a humble attempt to find out the relations between migration and the material development of Tripura. Furthermore, how much migration is responsible for changing the total infrastructural change of the Princely State Tripura and what were the factors that worked behind the immigrations during the last fifty years of Manikya rule are highlighted from a historical perspective.
The National Level Peer Reviewed Edited Book titled ‘Digital Transformation in Emerging Business Environment’ is a wonderful treatise which concentrates on the efficiency of improved infrastructure and its impact on the socio-economic growth and addresses diverse theme of great importance and relevance to the business, economy and society. This book contains research papers and scholarly articles of the eminent academicians, scholars and researchers in the diverse fields of Business, Finance, Marketing, Management etc. in a highly organised and lucid manner.
The book is a thoughtful discussion with scientists studying convergent plate boundaries such as the well-known, active India-Eurasia collision zone. It provides a comprehensive collection of petrographic images of ophiolitic rocks exhumed from oceanic lithosphere and mantle at the India-Asia plate boundary. Ophiolite is exposed in the northwestern Himalayas, eastern Indian plate margin and Andaman-Nicobar Islands. At the eastern margin, it occurs in a narrow strip comprising mantle peridotite tectonite, cummulate peridotite-gabbro-plagiogranite-anorthosite, mafic dyke, volcanics and oceanic sediments. Low temperature/high pressure rocks including blueschists and eclogites were extensively studied recently. Ophiolite derived sediments and podiform chromites will also be discussed to provide complete details. Supplemental maps, geological sections, field sketches and photographs will explain the structure, stratigraphy, ore mineralization, and metamorphic history.
Embedded Systems and Robotics with Open-Source Tools provides easy-to-understand and easy-to-implement guidance for rapid prototype development. Designed for readers unfamiliar with advanced computing technologies, this highly accessible book: Describes several cutting-edge open-source software and hardware technologies Examines a number of embedded computer systems and their practical applications Includes detailed projects for applying rapid prototype development skills in real time Embedded Systems and Robotics with Open-Source Tools effectively demonstrates that, with the help of high-performance microprocessors, microcontrollers, and highly optimized algorithms, one can develop smarter embedded devices.
Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis covers the most current advances on how to apply classification techniques to a wide variety of clinical applications that are appropriate for researchers and biomedical engineers in the areas of machine learning, deep learning, data analysis, data management and computer-aided diagnosis (CAD) systems design. The book covers several complex image classification problems using pattern recognition methods, including Artificial Neural Networks (ANN), Support Vector Machines (SVM), Bayesian Networks (BN) and deep learning. Further, numerous data mining techniques are discussed, as they have proven to be good classifiers for medical images. - Examines the methodology of classification of medical images that covers the taxonomy of both supervised and unsupervised models, algorithms, applications and challenges - Discusses recent advances in Artificial Neural Networks, machine learning, and deep learning in clinical applications - Introduces several techniques for medical image processing and analysis for CAD systems design
A Beginners Guide to Data Agglomeration and Intelligent Sensing provides an overview of the Sensor Cloud Platform, Converge-casting, and Data Aggregation in support of intelligent sensing and relaying of information. The book begins with a brief introduction on sensors and transducers, giving readers insight into the various types of sensors and how one can work with them. In addition, it gives several real-life examples to help readers properly understand concepts. An overview of concepts such as wireless sensor networks, cloud platforms, and device-to-cloud and sensor cloud architecture are explained briefly, as is data gathering in wireless sensor networks and aggregation procedures. Final sections explore how to process gathered data and relay the data in an intelligent way, including concepts such as supervised and unsupervised learning, software defined networks, sensor data mining and smart systems. - Presents the latest advances in data agglomeration for intelligent sensing - Discusses the basic concepts of sensors, real-life applications of sensors and systems, the protocols and applications of wireless sensor networks, the methodology of sensor data accumulation, and real-life applications of Intelligent Sensor Networks - Provides readers with an easy-to-learn and understand introduction to the concepts of the cloud platform, Sensor Cloud and Machine Learning
Applied Speech Processing: Algorithms and Case Studies is concerned with supporting and enhancing the utilization of speech analytics in several systems and real-world activities, including sharing data analytics related information, creating collaboration networks between several participants, and the use of video-conferencing in different application areas. The book provides a well-standing forum to discuss the characteristics of the intelligent speech signal processing systems in different domains. The book is proposed for professionals, scientists, and engineers who are involved in new techniques of intelligent speech signal processing methods and systems. It provides an outstanding foundation for undergraduate and post-graduate students as well. - Includes basics of speech data analysis and management tools with several applications, highlighting recording systems - Covers different techniques of big data and Internet-of-Things in speech signal processing, including machine learning and data mining - Offers a multidisciplinary view of current and future challenges in this field, with extensive case studies on the design, implementation, development and management of intelligent systems, neural networks, and related machine learning techniques for speech signal processing
Biomedical Sensors and Smart Sensing: A Beginner's Guide, a book in the 10-volume Primers in Biomedical Imaging Devices and Systems series, covers a wide range of interdisciplinary applications in imaging modalities, nuclear medicine, computed tomographic systems, x-ray systems, magnetic resonance imaging, ultrasound, and virtual reality. The series explores the essential fundamental techniques required to analyze and process signals and images for diagnosis, scientific discovery and medical applications. Volumes in this series cover a wide range of interdisciplinary areas, combining foundational content with practical case studies to demonstrate the applications of these technologies in real-world situations. In addition, the 10-volume series considers various medical devices, electronics, circuits, sensors and algorithms. Several applications ranging from basic biological science to clinical practice are included to facilitate ongoing research. - Covers a variety of sensing and signal processing techniques - Introduces different approaches relating to communication and intelligent data processing for early detection and prediction of diseases - Includes practical case studies
This book serves as a source of introductory material and reference for medical application development and related technologies by providing the detailed implementation of cutting-edge deep learning methodologies. It targets cloud-based advanced medical application developments using open-source Python-based deep learning libraries. It includes code snippets and sophisticated convolutional neural networks to tackle real-world problems in medical image analysis and beyond. Features: Provides programming guidance for creation of sophisticated and reliable neural networks for image processing. Incorporates the comparative study on GAN, stable diffusion, and its application on medical image data augmentation. Focuses on solving real-world medical imaging problems. Discusses advanced concepts of deep learning along with the latest technology such as GPT, stable diffusion, and ViT. Develops applicable knowledge of deep learning using Python programming, followed by code snippets and OOP concepts. This book is aimed at graduate students and researchers in medical data analytics, medical image analysis, signal processing, and deep learning.
As UAV technology is rapidly evolving, a pervasive need for a thorough investigation of its full capabilities has come to the forefront. Internet of Drone Things: Architectures, Approaches, and Applications fulfils this need enabling its readers to easily find the answers they are seeking by providing a comprehensive overview of the topic.This book, in fact, includes fundamental information related to IoDT architecture design and features; reviews the state of the art in hardware and software platforms to deploy, connect, and control drones or swarms of drones; and covers the latest developments in innovative drone-facilitated applications and services that can significantly improve efficiency, productivity, and sustainability of various operations in modern society and a growing number of its industries. Finally, experimental modeling and simulations are accompanied by prototyping examples, which are set to become the benchmark of next-level automation in the field.Internet of Drone Things: Architectures, Approaches, and Applications is, therefore, an invaluable resource for engineering students, researchers, and professionals, as well as sector experts who work to develop new drone standards or to identify new drone technology use and commercialization areas at an international level. - Educates readers on the fundamental properties of an Internet of Drone Things (IoDT) ecosystem - Guides readers to effective network architecture design through experimental modeling and simulations - Provides in-depth research on the progress made in the domain of UAV networks, routing, sensing, and UAV operation management - Offers state-of-the-art IoDT platform-enabled application examples
Despite advancements in medical imaging modalities, build-up of noise and distortion is still an issue faced by users of medical imaging technology. Consequently, de-noising procedures are developed to preserve the quality of the textured image by removing the noise encountered. Parametric and Nonparametric Techniques in Medical Image De-noising and Restoration explores the different medical image de-noising techniques for medical image quality enhancement. It introduces soft computing and optimization techniques and reports on the challenges of medical image denoising, also highlighting artifacts and noise sources in different imaging modalities and discussing performance evaluation metrics. This is a key reference for anyone involved in medical imaging who is looking to learn about both the parametric and non-parametric approaches available and apply them to their own work and research. Explores the types of denoising and restoration with different noise sources of each medical modality Emphasizes the different approaches of denoising and restoration, including parametric and nonparametric techniques Provides applied examples of medical image denoising
This book is focused on AI-empowered knowledge management to improve processes, implementation of technology for providing easy access to knowledge and the impact of knowledge management to promote the platform for generation of new knowledge through continuous learning. The book discusses process of knowledge management which includes entirety of the creation, distribution, and maintenance of knowledge to achieve organizational objectives. It also covers knowledge management tools which enable and enhance knowledge creation, codification, and transfer within business firms thereby reducing the burden of work and allowing application of resources and effective usage towards practical tasks. An immense growth of artificial intelligence in business organizations has occurred and AI-empowered knowledge management practice is leading towards growth and development of the organization.
Coefficient of Variation (CV) is a unit free index indicating the consistency of the data associated with a real-world process and is simple to mold into computational paradigms. This book provides necessary exposure of computational strategies, properties of CV and extracting the metadata leading to efficient knowledge representation. It also compiles representational and classification strategies based on the CV through illustrative explanations. The potential nature of CV in the context of contemporary Machine Learning strategies and the Big Data paradigms is demonstrated through selected applications. Overall, this book explains statistical parameters and knowledge representation models.
The Book presents an overview of newly developed watermarking techniques in various independent and hybrid domains Covers the basics of digital watermarking, its types, domain in which it is implemented and the application of machine learning algorithms onto digital watermarking Reviews hardware implementation of watermarking Discusses optimization problems and solutions in watermarking with a special focus on bio-inspired algorithms Includes a case study along with its MATLAB code and simulation results
This book covers all small details about Underwater Sensor Networks (UWSN). Researchers can use this book as a prerequisite before starting any research on underwater networks or underwater applications. This book covers the introduction, challenges, different architectural models for UWSN, various attacks on UWSN, underwater applications, and networking layers. The target audience includes professors and students in engineering, and researchers and engineers working on marine applications. In academic level, the book is helpful for students having Networking and Information Security as elective subject and doing projects in Wireless Networks. It is also helpful for spostgraduates and Ph.D. researchers to learn basics of Underwater Sensor Networks.
This book discusses in detail the latest trends in sentiment analysis,focusing on “how online reviews and feedback reflect the opinions of users and have led to a major shift in the decision-making process at organizations.” Social networking has become essential in today’s society. In the past, people’s decisions to buy certain products (and companies’ efforts to sell them) were largely based on advertisements, surveys, focus groups, consultants, and the opinions of friends and relatives. But now this is no longer limited to one’s circle of friends, family or small surveys;it has spread globally to online social media in the form of blogs, posts, tweets, social networking sites, review sites and so on. Though not always easy, the transition from surveys to social media is certainly lucrative. Business analytical reports have shown that many organizations have improved their sales, marketing and strategy, setting up new policies and making decisions based on opinion mining techniques.
This book presents research and applications on arrival estimation and localization in speech processing to ensure that the broad vision of the direction of arrival estimation (DOAE) / localization of speech sources is well-established. The book first provides a brief overview of the most classical direction of arrival estimation and localization techniques. It then introduces the concept and model of acoustics sources and then highlights the most contemporary studies on this pervasive problem. In addition, the authors explore employing the optimization algorithms to improve the DOAE techniques. The book then highlights the concept and principles of the multi-DOAE approaches. Using a microphone array, the book introduces the localization and tracking problem of multiple speech/acoustic sources. It includes several applications and real-life speech sources localization based on the DOAE approaches. The book reports the challenges facing the DOAE techniques in speech-sources localization. The book pertains to researchers, designers, and engineers in speech processing fields.
A Beginner’s Guide to Image Multi-Level Thresholding emphasizes various image thresholding methods that are necessary for image pre-processing and initial level enhancement. Explains basic concepts and the implementation of Image Multi-Level Thresholding (grayscale and RGB images) Presents a detailed evaluation in real-time application, including the need for heuristic algorithm, the choice of objective and threshold function, and the evaluation of the outcome Describes how the image thresholding acts as a pre-processing technique and how the region of interest in a medical image is enhanced with thresholding Illustrates integration of the thresholding technique with bio-inspired algorithms Includes current findings and future directions of image multi-level thresholding and its practical implementation Emphasizes the need for multi-level thresholding with suitable examples The book is aimed at graduate students and researchers in image processing, electronics engineering, computer sciences and engineering.
This book discusses in-depth role of optimization to optimize the controller parameters with reference to bio-inspired algorithms. Comparative studies to evaluate the performance of different optimization techniques in terms of the settling time, overshoot and undershoot responses of the frequency deviations, tie-line power flow deviations, and the area control error are included, supported by examples. The book also includes different scenarios of the load frequency controller for single area as well as multi-area thermal power generating unit considering different algorithms. Key Features: Highlights the importance of tuning the power system controller parameters with emphasis on bio-inspiration algorithms Provides some applied applications/examples of the thermal power system Focusses on power system applications based on the optimization algorithms with different single area and multi-area thermal power systems Reports different cases on the interconnected power systems with providing optimal performance by optimizing the controller’s parameters
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