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Machine Learning in Team Sports: Performance Analysis and Talent Identification in Beach Soccer & Sepak-takraw (SpringerBriefs in Applied Sciences and Technology)
by Mohamad Razali Abdullah Rabiu Muazu Musa Anwar P.P. Abdul Majeed Norlaila Azura KosniThis brief highlights the application of performance analysis tools in data acquisition, and various machine learning algorithms for evaluating team performance as well as talent identification in beach soccer and sepak takraw. Numerous performance indicators and human performance parameters are considered based on their relevance to each sport. The findings presented here demonstrate that the key performance indicators as well as human performance parameters can be used in the future evaluation of team performance as well as talent identification in these sports. Accordingly, they offer a valuable resource for coaches, club managers, talent identification experts, performance analysts and other relevant stakeholders involved in performance assessments.
Swarm Intelligence and its Applications in Biomedical Informatics
by A. Sheik AbdullahSwarm Intelligence and Its Applications in Biomedical Informatics discusses Artificial Intelligence (AI) applications in medicine and biology, as well as challenges and opportunities presented in these arenas. It covers healthcare big data analytics, mobile health, personalized medicine, and clinical trial data management. This book shows how AI can be used for early disease diagnosis, prediction, and prognosis, and it offers healthcare case studies that demonstrate the application of AI and Machine Learning. Key Features: • Covers all major topics of swarm intelligence research and development such as novel-based search methods and novel optimization algorithm: applications of swarm intelligence to management problems and swarm intelligence for real-world application.• Provides a unique insight into the complex problems of bioinformatics and the innovative solutions which make up ‘intelligent bioinformatics’.• Covers a wide range of topics on the role of AI, Machine Learning, and Big Data for healthcare applications and deals with the ethical issues and concerns associated with it.• Explores applications in different areas of healthcare and highlights the current research. This book is designed as a reference text, and it aims primarily at advanced undergraduates and postgraduate students studying computer science and bioinformatics. Researchers and professionals will find this book useful.
Networked Systems
by Parosh Aziz Abdulla Carole Delporte-GalletThis book constitutes the refereed post-proceedings of the 4th International Conference on Networked Systems, NETYS 2016, held in Marrakech, Morocco, in May 2016. The 22 full papers and 11 short papers presented together with 19 poster abstracts were carefully reviewed and selected from 121 submissions. They report on best practices and novel algorithms, results and techniques on networked systems and cover topics such as multi-core architectures, concurrent and distributed algorithms, parallel/concurrent/distributed programming, distributed databases, cloud systems, networks, security, and formal verification.
Machine Learning in Clinical Neuroimaging: 4th International Workshop, MLCN 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, Proceedings (Lecture Notes in Computer Science #13001)
by Ahmed Abdulkadir Seyed Mostafa Kia Mohamad Habes Vinod Kumar Jane Maryam Rondina Chantal Tax Thomas WolfersThis book constitutes the refereed proceedings of the 4th International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2021, held on September 27, 2021, in conjunction with MICCAI 2021. The workshop was held virtually due to the COVID-19 pandemic. The 17 papers presented in this book were carefully reviewed and selected from 27 submissions. They were organized in topical sections named: computational anatomy and brain networks and time series.
Machine Learning in Clinical Neuroimaging: 5th International Workshop, MLCN 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings (Lecture Notes in Computer Science #13596)
by Ahmed Abdulkadir Deepti R. Bathula Nicha C. Dvornek Mohamad Habes Seyed Mostafa Kia Vinod Kumar Thomas WolfersThis book constitutes the refereed proceedings of the 5th International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2022, held in Conjunction with MICCAI 2022, Singapore in September 2022. The book includes 17 papers which were carefully reviewed and selected from 23 full-length submissions.The 5th international workshop on Machine Learning in Clinical Neuroimaging (MLCN2022) aims to bring together the top researchers in both machine learning and clinical neuroscience as well as tech-savvy clinicians to address two main challenges: 1) development of methodological approaches for analyzing complex and heterogeneous neuroimaging data (machine learning track); and 2) filling the translational gap in applying existing machine learning methods in clinical practices (clinical neuroimaging track).The papers are categorzied into topical sub-headings: Morphometry; Diagnostics, and Aging, and Neurodegeneration.
Machine Learning in Clinical Neuroimaging: 6th International Workshop, MLCN 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings (Lecture Notes in Computer Science #14312)
by Ahmed Abdulkadir Deepti R. Bathula Nicha C. Dvornek Sindhuja T. Govindarajan Mohamad Habes Vinod Kumar Esten Leonardsen Thomas Wolfers Yiming XiaoThis book constitutes the refereed proceedings of the 6th International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2023, held in Conjunction with MICCAI 2023 in Vancouver, Canada, in October 2023. The book includes 16 papers which were carefully reviewed and selected from 28 full-length submissions.The 6th International Workshop on Machine Learning in Clinical Neuroimaging (MLCN 2023) aims to bring together the top researchers in both machine learning and clinical neuroscience as well as tech-savvy clinicians to address two main challenges: 1) development of methodological approaches for analyzing complex and heterogeneous neuroimaging data (machine learning track); and 2) filling the translational gap in applying existing machine learning methods in clinical practices (clinical neuroimaging track).The papers are categorzied into topical sub-headings on Machine Learning and Clinical Applications.
Excel Best Practices for Business
by Loren AbdulezerHow to create, manage, and validate spreadsheets that will stand up to scrutiny and provide a clear and accurate picture of your enterprise.
The Cloud Adoption Playbook: Proven Strategies for Transforming Your Organization with the Cloud
by Moe Abdula Ingo Averdunk Roland Barcia Kyle Brown Ndu EmuchayThe essential roadmaps for enterprise cloud adoption As cloud technologies continue to challenge the fundamental understanding of how businesses work, smart companies are moving quickly to adapt to a changing set of rules. Adopting the cloud requires a clear roadmap backed by use cases, grounded in practical real-world experience, to show the routes to successful adoption. The Cloud Adoption Playbook helps business and technology leaders in enterprise organizations sort through the options and make the best choices for accelerating cloud adoption and digital transformation. Written by a team of IBM technical executives with a wealth of real-world client experience, this book cuts through the hype, answers your questions, and helps you tailor your cloud adoption and digital transformation journey to the needs of your organization. This book will help you: Discover how the cloud can fulfill major business needs Adopt a standardized Cloud Adoption Framework and understand the key dimensions of cloud adoption and digital transformation Learn how cloud adoption impacts culture, architecture, security, and more Understand the roles of governance, methodology, and how the cloud impacts key players in your organization. Providing a collection of winning plays, championship advice, and real-world examples of successful adoption, this playbook is your ultimate resource for making the cloud work. There has never been a better time to adopt the cloud. Cloud solutions are more numerous and accessible than ever before, and evolving technology is making the cloud more reliable, more secure, and more necessary than ever before. Don’t let your organization be left behind! The Cloud Adoption Playbook gives you the essential guidance you need to make the smart choices that reduce your organizational risk and accelerate your cloud adoption and digital transformation.
Understanding Cybersecurity on Smartphones: Challenges, Strategies, and Trends (Progress in IS)
by Andi Fitriah Abdul Kadir Arash Habibi Lashkari Mahdi Daghmehchi FiroozjaeiThis book offers a comprehensive overview of smartphone security, focusing on various operating systems and their associated challenges. It covers the smartphone industry's evolution, emphasizing security and privacy concerns. It explores Android, iOS, and Windows OS security vulnerabilities and mitigation measures. Additionally, it discusses alternative OSs like Symbian, Tizen, Sailfish, Ubuntu Touch, KaiOS, Sirin, and HarmonyOS.The book also addresses mobile application security, best practices for users and developers, Mobile Device Management (MDM) in enterprise settings, mobile network security, and the significance of mobile cloud security and emerging technologies such as IoT, AI, ML, and blockchain. It discusses the importance of balancing innovation with solid security practices in the ever-evolving mobile technology landscape.
Transforming Your Business with AWS: Getting the Most Out of Using AWS to Modernize and Innovate Your Digital Services
by Philippe AbdoulayeExpert guidance on how to use Amazon Web Services to supercharge your digital services business In Transforming Your Business with AWS: Getting the Most Out of Using AWS to Modernize and Innovate Your Digital Services, renowned international consultant and sought-after speaker Philippe Abdoulaye delivers a practical and accessible guide to using Amazon Web Services to modernize your business and the digital services you offer. This book provides you with a concrete action plan to build a team capable of creating world-class digital services and long-term competitive advantages. You’ll discover what separates merely average digital service organizations from the truly outstanding, as well as how moving to the cloud will enable your business to deliver your services faster, better, and more efficiently. This book also includes: A comprehensive overview of building industry-leading digital service delivery capabilities, including discussions of the development lifecycle, best practices, and AWS-based development infrastructure Explanations of how to implement a digital business transformation strategy An exploration of key roles like DevOps Continuous Delivery, Continuous Deployment, Continuous Integration, Automation, and DevSecOps Hands-on treatments of AWS application management tools, including Elastic Beanstalk, CodeDeploy, and CodePipeline Perfect for executives, managers, and other business leaders attempting to clarify and implement their organization’s digital vision and strategy, Transforming Your Business with AWS is a must-read reference that answers the “why” and, most importantly, the “how,” of digital transformation with Amazon Web Services.
The Deep Learning with Keras Workshop - Third Edition: Solve Complex Real-life Problems With The Simplicity Of Keras
by Mahla Abdolahnejad Matthew MoocarmeIf you know the basics of data science and machine learning, and want to get started with advanced machine learning technologies, such as artificial neural networks and deep learning, this workshop makes it easy. To grasp the concepts explained in this deep learning book more effectively, prior experience in Python programming and some familiarity with statistics and logistic regression are a must.
Smart Meters: Artificial Intelligence to Support Proactive Management of Energy Consumption (Lecture Notes in Energy #97)
by Djaffar Ould AbdeslamThis book describes how equipping buildings with smart meters is essential to improve the prediction of energy costs within smart grids and to help end-users optimize their energy consumption. The book reports on the results of the European Upper Rhine INTERREG project SMI (www.smi.uha.fr), which connects artificial intelligence and micro-societal analysis. It is multidisciplinary and addresses the following aspects: social, legal, environmental, and technical.One of the critical factors for the transition to clean energy is the flexibility of the power grid. A flexible grid requires a constant flow of data about the network and its demand, on the other hand, clients who produce electrical power can be an active part of the demand response if they are informed about the power needs of their appliances.“If you cannot measure it, you cannot improve it.” This common management saying also holds true for the area energy efficiency. Without a clear understanding of their energy usage, consumers are unable to take steps to reduce their consumption. A new intelligent tool is presented that is more efficient, safe, and acceptable to consumers. Thus, users of this intelligent tool will be able to collect and predict the consumption of their electrical appliances. At the same time, the consumption information is anonymized before being relayed to the energy supplier. In parallel, new techniques will be evaluated to improve the security level of the smart meter in a highly heterogeneous network.
Model and Data Engineering: 8th International Conference, MEDI 2018, Marrakesh, Morocco, October 24–26, 2018, Proceedings (Lecture Notes in Computer Science #11163)
by El Hassan Abdelwahed Ladjel Bellatreche Mattéo Golfarelli Dominique Méry Carlos OrdonezThis book constitutes the refereed proceedings of the 8h International Conference on Model and Data Engineering, MEDI 2018, held in Marrakesh, Morocco, in October 2018.The 23 full papers and 4 short papers presented together with 2 invited talks were carefully reviewed and selected from 86 submissions. The papers covered the recent and relevant topics in the areas of databases; ontology and model-driven engineering; data fusion, classsification and learning; communication and information technologies; safety and security; algorithms and text processing; and specification, verification and validation.
New Trends in Model and Data Engineering: MEDI 2018 International Workshops, DETECT, MEDI4SG, IWCFS, REMEDY, Marrakesh, Morocco, October 24–26, 2018, Proceedings (Communications in Computer and Information Science #929)
by El Hassan Abdelwahed Ladjel Bellatreche Djamal Benslimane Matteo Golfarelli Stéphane Jean Dominique Mery Kazumi Nakamatsu Carlos OrdonezThis book constitutes the thoroughly refereed papers of the workshops held at the 8th International Conference on New Trends in Model and Data Engineering, MEDI 2018, in Marrakesh, Morocco, in October 2018.The 19 full and the one short workshop papers were carefully reviewed and selected from 50 submissions. The papers are organized according to the 4 workshops: International Workshop on Modeling, Verification and Testing of Dependable Critical Systems, DETECT 2018, Model and Data Engineering for Social Good Workshop, MEDI4SG 2018, Second International Workshop on Cybersecurity and Functional Safety in Cyber-Physical Systems, IWCFS 2018, International Workshop on Formal Model for Mastering Multifaceted Systems, REMEDY 2018.
Information Sciences and Systems 2015
by Omer H. Abdelrahman Erol Gelenbe Gokce Gorbil Ricardo LentThe 30th Anniversary of the ISCIS (International Symposium on Computer and Information Sciences) series of conferences, started by Professor Erol Gelenbe at Bilkent University, Turkey, in 1986, will be held at Imperial College London on September 22-24, 2015. The preceding two ISCIS conferences were held in Krakow, Poland in 2014, and in Paris, France, in 2013. The Proceedings of ISCIS 2015 published by Springer brings together rigorously reviewed contributions from leading international experts. It explores new areas of research and technological development in computer science, computer engineering, and information technology, and presents new applications in fast changing fields such as information science, computer science and bioinformatics. The topics covered include (but are not limited to) advances in networking technologies, software defined networks, distributed systems and the cloud, security in the Internet of Things, sensor systems, and machine learning and large data sets.
Innovation Practices for Digital Transformation in the Global South: IFIP WG 13.8, 9.4, Invited Selection (IFIP Advances in Information and Communication Technology #645)
by José Abdelnour-Nocera Elisha Ondieki Makori Jose Antonio Robles-Flores Constance BitsoThis book is a collection of chapters from the IFIP working groups 13.8 and 9.4. The 10 papers included present experiences and research on the topic of digital transformation and innovation practices in the global south. The topics span from digital transformation initiatives to novel innovative technological developments, practices and applications of marginalised people in the global south.
Computer Modeling Applications for Environmental Engineers
by Isam Mohammed Abdel-Magid Ahmed Mohammed Isam Mohammed Abdel-MagidComputer Modeling Applications for Environmental Engineers in its second edition incorporates changes and introduces new concepts using Visual Basic.NET, a programming language chosen for its ease of comprehensive usage. This book offers a complete understanding of the basic principles of environmental engineering and integrates new sections that address Noise Pollution and Abatement and municipal solid-waste problem solving, financing of waste facilities, and the engineering of treatment methods that address sanitary landfill, biochemical processes, and combustion and energy recovery. Its practical approach serves to aid in the teaching of environmental engineering unit operations and processes design and demonstrates effective problem-solving practices that facilitate self-teaching. A vital reference for students and professional sanitary and environmental engineers this work also serves as a stand-alone problem-solving text with well-defined, real-work examples and explanations.
Sustainability, Big Data, and Corporate Social Responsibility: Evidence from the Tourism Industry (Information Technology, Management and Operations Research Practices)
by Abdelli, Mohammed El AmineThis book aims to provide theoretical and empirical frameworks and highlights the challenges and solutions with using Big Data for Corporate Social Responsibility (CSR) and Sustainability in the field of digital transformation and tourism. Sustainability, Big Data, and Corporate Social Responsibility: Evidence from the Tourism Industry offers a theoretical and empirical framework in the field of digital transformation and applies it to the tourism sector. It discusses Big Data used with CSR and sustainability for the improvement of innovation and highlights the challenges and prospects. It presents a modern insight and approach for use by decision-makers as an application to solve various problems and explores how data collection can shed light on consumer behavior making it possible to account for existing situations and plan for the future. This book is intended to provide a modern insight for researcher, students, professionals, and decision-makers on the application of Big Data to improve CSR and sustainability in the tourism sector.
Unmanned Aerial Vehicles Applications: Challenges and Trends (Synthesis Lectures on Intelligent Technologies)
by Mohamed Abdelkader Anis KoubaaThis is a book that covers different aspects of UAV technology, including design and development, applications, security and communication, and legal and regulatory challenges. The book is divided into 13 chapters, grouped into four parts. The first part discusses the design and development of UAVs, including ROS customization, structured designs, and intelligent trajectory tracking. The second part explores diverse applications such as search and rescue, monitoring distributed parameter systems, and leveraging drone technology in accounting. The third part focuses on security and communication challenges, including security concerns, multi-UAV systems, and communications security. The final part delves into the legal and regulatory challenges of integrating UAVs into non-segregated airspace. The book serves as a valuable resource for researchers, practitioners, and students in the field of unmanned aerial vehicles, providing a comprehensive understanding of UAV technology and its applications.
Transactions on Large-Scale Data- and Knowledge-Centered Systems XIII (Lecture Notes in Computer Science #8420)
by Abdelkader Hameurlain, Josef Küng and Roland WagnerThis, the 13th issue of Transactions on Large-Scale Data and Knowledge-Centered Systems, contains six revised selected regular papers. Topics covered include federated data sources, information filtering, web data clouding, query reformulation, package skyline queries and SPARQL query processing over a LaV (Local-as-View) integration system.
Cellular Communications Systems in Congested Environments: Resource Allocation and End-to-End Quality of Service Solutions with MATLAB
by Ahmed Abdelhadi Mo Ghorbanzadeh Charles ClancyThis book presents a mathematical treatment of the radio resource allocation of modern cellular communications systems in contested environments. It focuses on fulfilling the quality of service requirements of the living applications on the user devices, which leverage the cellular system, and with attention to elevating the users' quality of experience. The authors also address the congestion of the spectrum by allowing sharing with the band incumbents while providing with a quality-of-service-minded resource allocation in the network. The content is of particular interest to telecommunications scheduler experts in industry, communications applications academia, and graduate students whose paramount research deals with resource allocation and quality of service.
Responsible Graph Neural Networks
by Mohamed Abdel-Basset Nour Moustafa Hossam Hawash Zahir TariMore frequent and complex cyber threats require robust, automated, and rapid responses from cyber-security specialists. This book offers a complete study in the area of graph learning in cyber, emphasizing graph neural networks (GNNs) and their cyber-security applications. Three parts examine the basics, methods and practices, and advanced topics. The first part presents a grounding in graph data structures and graph embedding and gives a taxonomic view of GNNs and cyber-security applications. The second part explains three different categories of graph learning, including deterministic, generative, and reinforcement learning and how they can be used for developing cyber defense models. The discussion of each category covers the applicability of simple and complex graphs, scalability, representative algorithms, and technical details. Undergraduate students, graduate students, researchers, cyber analysts, and AI engineers looking to understand practical deep learning methods will find this book an invaluable resource.
Deep Learning Techniques for IoT Security and Privacy (Studies in Computational Intelligence #997)
by Mohamed Abdel-Basset Nour Moustafa Hossam Hawash Weiping DingThis book states that the major aim audience are people who have some familiarity with Internet of things (IoT) but interested to get a comprehensive interpretation of the role of deep Learning in maintaining the security and privacy of IoT. A reader should be friendly with Python and the basics of machine learning and deep learning. Interpretation of statistics and probability theory will be a plus but is not certainly vital for identifying most of the book's material.
Deep Learning Approaches for Security Threats in IoT Environments
by Mohamed Abdel-Basset Nour Moustafa Hossam HawashDeep Learning Approaches for Security Threats in IoT Environments An expert discussion of the application of deep learning methods in the IoT security environment In Deep Learning Approaches for Security Threats in IoT Environments, a team of distinguished cybersecurity educators deliver an insightful and robust exploration of how to approach and measure the security of Internet-of-Things (IoT) systems and networks. In this book, readers will examine critical concepts in artificial intelligence (AI) and IoT, and apply effective strategies to help secure and protect IoT networks. The authors discuss supervised, semi-supervised, and unsupervised deep learning techniques, as well as reinforcement and federated learning methods for privacy preservation. This book applies deep learning approaches to IoT networks and solves the security problems that professionals frequently encounter when working in the field of IoT, as well as providing ways in which smart devices can solve cybersecurity issues. Readers will also get access to a companion website with PowerPoint presentations, links to supporting videos, and additional resources. They’ll also find: A thorough introduction to artificial intelligence and the Internet of Things, including key concepts like deep learning, security, and privacy Comprehensive discussions of the architectures, protocols, and standards that form the foundation of deep learning for securing modern IoT systems and networks In-depth examinations of the architectural design of cloud, fog, and edge computing networks Fulsome presentations of the security requirements, threats, and countermeasures relevant to IoT networks Perfect for professionals working in the AI, cybersecurity, and IoT industries, Deep Learning Approaches for Security Threats in IoT Environments will also earn a place in the libraries of undergraduate and graduate students studying deep learning, cybersecurity, privacy preservation, and the security of IoT networks.
Multi-Criteria Decision Making Theory and Applications in Sustainable Healthcare
by Mohamed Abdel-Basset Ripon Kumar Chakrabortty Abduallah GamalMulti-Criteria Decision Making Theory and Applications in Sustainable Healthcare, 1st Edition, is an excellent compilation of current and advanced Multi-Criteria Decision Making (MCDM) techniques and their applications to multiple recent and innovative healthcare analytics problems. The healthcare business has expanded rapidly in recent years, and one of the top priorities in the sector is now the efficacy and efficiency of the various healthcare delivery systems. The entire performance of hospitals must be improved if the healthcare business wants to see an improvement in both the satisfaction and safety of their patients. Finding the best medical facility among many of its competitors may be difficult since there are so many, and they are so highly diverse in terms of features and performance trade-offs. This book has brought together the introductory discussions, fundamental concepts, challenges, and insights of multiple advanced healthcare management problems along with the application of MCDM to obtain the best option among multiple alternatives. A few important takeaways from this book are: Developing an efficient model for supplier performance evaluation and selection in healthcare industries with incomplete information. A computational reliance approach for assessing healthcare service quality aspects and their measurement in an uncertain environment. An efficient and provable approach for recommending suitable mobile healthcare products under uncertain environments. Establishing a decision-making strategy to select healthcare waste treatment methods. Assessing the usability of mHealth applications in practice related to type 2 diabetes. The successful outcome of this book will enable a decision-maker or practitioner to pick a suitable MCDM technique when making decisions to prioritize the selection criteria of any healthcare-related problems to ensure a sustainable practice. .