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Digital
Classification in BioApps : Automation of Decision Making
Authors: --- ---
ISBN: 9783319659817 Year: 2018 Publisher: Cham Springer International Publishing

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Abstract

This book on classification in biomedical image applications presents original and valuable research work on advances in this field, which covers the taxonomy of both supervised and unsupervised models, standards, algorithms, applications and challenges. Further, the book highlights recent scientific research on artificial neural networks in biomedical applications, addressing the fundamentals of artificial neural networks, support vector machines and other advanced classifiers, as well as their design and optimization. In addition to exploring recent endeavours in the multidisciplinary domain of sensors, the book introduces readers to basic definitions and features, signal filters and processing, biomedical sensors and automation of biomeasurement systems. The target audience includes researchers and students at engineering and medical schools, researchers and engineers in the biomedical industry, medical doctors and healthcare professionals.


Digital
Big Data for Remote Sensing: Visualization, Analysis and Interpretation : Digital Earth and Smart Earth
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ISBN: 9783319899237 Year: 2019 Publisher: Cham Springer International Publishing

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This book thoroughly covers the remote sensing visualization and analysis techniques based on computational imaging and vision in Earth science. Remote sensing is considered a significant information source for monitoring and mapping natural and man-made land through the development of sensor resolutions that committed different Earth observation platforms. The book includes related topics for the different systems, models, and approaches used in the visualization of remote sensing images. It offers flexible and sophisticated solutions for removing uncertainty from the satellite data. It introduces real time big data analytics to derive intelligence systems in enterprise earth science applications. Furthermore, the book integrates statistical concepts with computer-based geographic information systems (GIS). It focuses on image processing techniques for observing data together with uncertainty information raised by spectral, spatial, and positional accuracy of GPS data. The book addresses several advanced improvement models to guide the engineers in developing different remote sensing visualization and analysis schemes. Highlights on the advanced improvement models of the supervised/unsupervised classification algorithms, support vector machines, artificial neural networks, fuzzy logic, decision-making algorithms, and Time Series Model and Forecasting are addressed. This book guides engineers, designers, and researchers to exploit the intrinsic design remote sensing systems. The book gathers remarkable material from an international experts' panel to guide the readers during the development of earth big data analytics and their challenges.


Digital
Internet of Things and Big Data Technologies for Next Generation Healthcare
Authors: --- ---
ISBN: 9783319497365 Year: 2017 Publisher: Cham Springer International Publishing

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This comprehensive book focuses on better big-data security for healthcare organizations. Following an extensive introduction to the Internet of Things (IoT) in healthcare including challenging topics and scenarios, it offers an in-depth analysis of medical body area networks with the 5th generation of IoT communication technology along with its nanotechnology. It also describes a novel strategic framework and computationally intelligent model to measure possible security vulnerabilities in the context of e-health. Moreover, the book addresses healthcare systems that handle large volumes of data driven by patients’ records and health/personal information, including big-data-based knowledge management systems to support clinical decisions. Several of the issues faced in storing/processing big data are presented along with the available tools, technologies and algorithms to deal with those problems as well as a case study in healthcare analytics.  Addressing trust, privacy, and security issues as well as the IoT and big-data challenges, the book highlights the advances in the field to guide engineers developing different IoT devices and evaluating the performance of different IoT techniques. Additionally, it explores the impact of such technologies on public, private, community, and hybrid scenarios in healthcare. This book offers professionals, scientists and engineers the latest technologies, techniques, and strategies for IoT and big data.


Digital
Applied Nature-Inspired Computing: Algorithms and Case Studies
Authors: --- ---
ISBN: 9789811392634 Year: 2020 Publisher: Singapore Springer Singapore, Imprint: Springer

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This book presents a cutting-edge research procedure in the Nature-Inspired Computing (NIC) domain and its connections with computational intelligence areas in real-world engineering applications. It introduces readers to a broad range of algorithms, such as genetic algorithms, particle swarm optimization, the firefly algorithm, flower pollination algorithm, collision-based optimization algorithm, bat algorithm, ant colony optimization, and multi-agent systems. In turn, it provides an overview of meta-heuristic algorithms, comparing the advantages and disadvantages of each. Moreover, the book provides a brief outline of the integration of nature-inspired computing techniques and various computational intelligence paradigms, and highlights nature-inspired computing techniques in a range of applications, including: evolutionary robotics, sports training planning, assessment of water distribution systems, flood simulation and forecasting, traffic control, gene expression analysis, antenna array design, and scheduling/dynamic resource management.


Digital
Workgroups eAssessment: Planning, Implementing and Analysing Frameworks
Authors: --- ---
ISBN: 9789811599088 9789811599095 9789811599101 9789811599071 Year: 2021 Publisher: Singapore Springer Singapore, Imprint: Springer

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This book was developed during a particular pandemic situation in the whole world which confined people to their homes. Therefore, there was a rise in the use of distance working and learning (e-learning) which led to a very quick adoption of technology in order to guarantee different approaches to fulfil the same or better outcomes and ensure that people are connected. This book provides a better understanding about the importance of teams' assessment and collaborative work, as well as the use of collaboration tools and online assessment techniques supported by technology. Consequently, the book is aimed at all institutions that seek new working environments, namely higher education institutions, companies and organizations, sports teams, and others. Furthermore, this book provides new approaches and systems to carry the knowledge and learning assessment. The book gathers knowledge from several authors, related to collaboration environments and tools, as well as their insights on how technology can be applied to carry assessment processes. The book seeks to provide knowledge on new technologies and different learning environments.


Book
Classification techniques for medical image analysis and computer aided diagnosis
Authors: --- ---
ISBN: 0128180056 0128180048 9780128180044 9780128180051 Year: 2019 Publisher: London, England : Elsevier : Academic Press,

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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


Book
Social network analytics
Authors: --- --- ---
ISBN: 9780128156414 0128156414 9780128154588 0128154586 Year: 2019 Publisher: London


Book
Big Data for Remote Sensing: Visualization, Analysis and Interpretation
Authors: --- --- ---
ISBN: 9783319899237 Year: 2019 Publisher: Cham Springer International Publishing :Imprint: Springer


Book
Applied Nature-Inspired Computing: Algorithms and Case Studies
Authors: --- --- ---
ISBN: 9789811392634 Year: 2020 Publisher: Singapore Springer Singapore :Imprint: Springer


Book
Workgroups eAssessment: Planning, Implementing and Analysing Frameworks
Authors: --- --- ---
ISBN: 9789811599088 9789811599095 9789811599101 9789811599071 Year: 2021 Publisher: Singapore Springer Singapore :Imprint: Springer

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