Mohammed M. Alani – författare

Edge AI is the seamless and spontaneous combination of Edge or Fog computing and AI. It enables acquiring real-time insights, which, in turn, leads to the realization of real-time, people-centric, event-driven, business-critical, process-aware, and knowledge-filled software services and applications.Edge AI for Industry 5.0 and Healthcare 5.0 Applications looks at the unique contributions of Edge AI for developing solutions for Industry 5.0 and Healthcare 5.0. It explains how Industry 5.0 fine tunes the human-machine connection and leverages tiny, high-performance AI-centric processors in IoT edge devices for real-time decision-making and application processing.Focusing on Explainable AI (XAI), the book discusses:The role of XAI in Healthcare 5.0Best practices, challenges, and opportunities of applying XAI in healthcare settingHow to enhance transparency and trust of XAI in Healthcare 5.0XAI and its methods in predicting healthcare outcomesOther highlights of the book include:5G communication networks requirementsThe fusion of IoT, AI, Edge, Cloud, and blockchainTrustworthiness of blockchain technology in healthcare 5.0 and Industry 5.0The future of trust and the potential of blockchain technologyBy explaining how Edge AI can transform healthcare and industry, this book empowers researchers and professionals to envisage and implement sophisticated and smart digital solutions.

This timely text/reference reviews the state of the art of big data analytics, with a particular focus on practical applications. An authoritative selection of leading international researchers present detailed analyses of existing trends for storing and analyzing big data, together with valuable insights into the challenges inherent in current approaches and systems. This is further supported by real-world examples drawn from a broad range of application areas, including healthcare, education, and disaster management. The text also covers, typically from an application-oriented perspective, advances in data science in such areas as big data collection, searching, analysis, and knowledge discovery.Topics and features:Discusses a model for data traffic aggregation in 5G cellular networks, and a novel scheme for resource allocation in 5G networks with network slicingExplores methods that use big data in the assessment of flood risks, and apply neural networks techniques to monitor the safety of nuclear power plantsDescribes a system which leverages big data analytics and the Internet of Things in the application of drones to aid victims in disaster scenariosProposes a novel deep learning-based health data analytics application for sleep apnea detection, and a novel pathway for diagnostic models of headache disordersReviews techniques for educational data mining and learning analytics, and introduces a scalable MapReduce graph partitioning approach for high degree verticesPresents a multivariate and dynamic data representation model for the visualization of healthcare data, and big data analytics methods for software reliability assessmentThis practically-focused volume is an invaluable resource for all researchers, academics, data scientists and business professionals involved in the planning, designing, and implementation of big data analytics projects.Dr. Mohammed M. Alani is an Associate Professor in Computer Engineering and currently is the Provost at Al Khawarizmi International College, Abu Dhabi, UAE. Dr. Hissam Tawfik is a Professor of Computer Science in the School of Computing, Creative Technologies & Engineering at Leeds Beckett University, UK. Dr. Mohammed Saeed is a Professor in Computing and currently is the Vice President for Academic Affairs and Research at the University of Modern Sciences, Dubai, UAE. Dr. Obinna Anya is a Research Staff Member at IBM Research – Almaden, San Jose, CA, USA.

This work opens with an accessible introduction to computer networks, providing general definitions of commonly used terms in networking. This is followed by a detailed description of the OSI model, including the concepts of connection-oriented and connectionless communications. The text carefully elaborates the specific functions of each layer, along with what is expected of protocols operating at each layer. Next, the journey of a single packet, from source to destination, is described in detail. The final chapter is devoted to the TCP/IP model, beginning with a discussion of IP protocols and the supporting ARP, RARP and In ARP protocols. The work also discusses the TCP and UDP protocols operating at the transport layer and the application layer protocols HTTP, DNS, FTP, TFTP, SMTP, POP3 and Telnet. Important facts and definitions are highlighted in gray boxes found throughout the text.

This book offers a thorough yet easy-to-read reference guide to various aspects of cloud computing security. It begins with an introduction to the general concepts of cloud computing, followed by a discussion of security aspects that examines how cloud security differs from conventional information security and reviews cloud-specific classes of threats and attacks. A range of varying threats in cloud computing are covered, from threats of data loss and data breaches, to threats to availability and threats posed by malicious insiders. Further, the book discusses attacks launched on different levels, including attacks on the hypervisor, and on the confidentiality of data. Newer types, such as side-channel attacks and resource-freeing attacks, are also described. The work closes by providing a set of general security recommendations for the cloud.

This easy-to-follow text/reference presents a practical guide to the configuration of Cisco routers, from tasks for beginners to advanced operations. The work starts with the simple step-by-step task of connecting the router and performing basic configuration, before building up to complex and sensitive operations such as router IOS upgrade and Site-to-Site VPNs. This updated and expanded new edition has been enhanced with a more detailed treatment of each topic, supported by a set of training scenarios. Features: discusses basic configuration, domestic duties, standard and advanced routing, WANtechnologies, security, router management, remote connectivity, and practical tips; explains in detail the steps required to configure different protocols on Cisco routers; includes coverage of MPLS, multicasting, GRE, HSRP, reflexive and timed-access lists, and configuration steps for IPv6 (NEW); provides an extensive selection of training scenarios, designed to offer hands-on practice in the relevant tasks (NEW).

This timely text/reference reviews the state of the art of big data analytics, with a particular focus on practical applications. An authoritative selection of leading international researchers present detailed analyses of existing trends for storing and analyzing big data, together with valuable insights into the challenges inherent in current approaches and systems. This is further supported by real-world examples drawn from a broad range of application areas, including healthcare, education, and disaster management. The text also covers, typically from an application-oriented perspective, advances in data science in such areas as big data collection, searching, analysis, and knowledge discovery.Topics and features:Discusses a model for data traffic aggregation in 5G cellular networks, and a novel scheme for resource allocation in 5G networks with network slicingExplores methods that use big data in the assessment of flood risks, and apply neural networks techniques to monitor the safety of nuclear power plantsDescribes a system which leverages big data analytics and the Internet of Things in the application of drones to aid victims in disaster scenariosProposes a novel deep learning-based health data analytics application for sleep apnea detection, and a novel pathway for diagnostic models of headache disordersReviews techniques for educational data mining and learning analytics, and introduces a scalable MapReduce graph partitioning approach for high degree verticesPresents a multivariate and dynamic data representation model for the visualization of healthcare data, and big data analytics methods for software reliability assessmentThis practically-focused volume is an invaluable resource for all researchers, academics, data scientists and business professionals involved in the planning, designing, and implementation of big data analytics projects.Dr. Mohammed M. Alani is an Associate Professor in Computer Engineering and currently is the Provost at Al Khawarizmi International College, Abu Dhabi, UAE. Dr. Hissam Tawfik is a Professor of Computer Science in the School of Computing, Creative Technologies & Engineering at Leeds Beckett University, UK. Dr. Mohammed Saeed is a Professor in Computing and currently is the Vice President for Academic Affairs and Research at the University of Modern Sciences, Dubai, UAE. Dr. Obinna Anya is a Research Staff Member at IBM Research – Almaden, San Jose, CA, USA.