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Big Data Technologies and Applications
The objective of this book is to introduce the basic concepts of big data computing and then to describe the total solution of big data problems using HPCC, an open-source computing platform. The book comprises 15 chapters broken into three parts. The first part, Big Data Technologies, includes introductions to big data concepts and techniques; big data analytics; and visualization and learning techniques. The second part, LexisNexis Risk Solution to Big Data, focuses on specific technologies and techniques developed at LexisNexis to solve critical problems that use big data analytics. It covers the open source High Performance Computing Cluster (HPCC Systems®) platform and its architecture...
Mastering HPCC Systems: Platform Overview and History
HPCC Systems is an Open Source Big Data supercomputing platform that is an alternative to the Hadoop and Spark worlds. The Mastering HPCC Systems series introduces the HPCC Systems platform to anyone interested in evaluating it for use on their own big data projects. It also expands the ECL programming knowledge of anyone already working with the platform. This Platform Overview and History volume provides an overview of the platform's infrastructure, design, history, and terminology. It introduces the components to new users and provides a high-level overview for executives whose organization is implementing the HPCC Systems platform.
Role of Emerging Technologies in Social Science
In today’s world, technology has seamlessly woven itself into the fabric of our social existence, leaving an indelible mark. This book aims to illuminate the far-reaching impact of technology across various aspects of our lives, including business, commerce, lifestyle, sentiment analysis, and transportation. It delves into both the advantages and drawbacks of technology, emphasizing the need for a delicate balance between our social interactions and its pervasive influence. In today’s interconnected world, technology profoundly influences our social fabric. This book explores its impact across diverse domains—business, commerce, lifestyle, sentiment analysis, and transportation. It delves into both advantages and drawbacks, emphasizing the delicate balance between social interactions and technology, and guides aspiring researchers through cutting-edge topics like blockchain, the Internet of Things, AI, and machine learning. Key takeaways include understanding tech’s role, evaluating pros and cons, and exploring future research. The book caters to universities, graduate colleges, and research centers.
Technology and Engineering Strategies
This pioneering book is the first-ever practical guide to developing and communicating technology and engineering strategies. It presents a unique step-by-step method for creating robust, evidence-based strategy, known as the Five Dimensions Process (or 5DP). The book also introduces a host of original insights, including a new theory of technology, a novel approach to product innovation, and groundbreaking contributions to our understanding of technological risk. It describes many easy-to-use tools, both new and established, for supporting activities such as solution design, system monitoring, risk identification, project management, the development of personnel, and ethical decision making. The book brims with strategic and tactical advice on such topics as university collaboration, technical compatibility, data utilisation, product design, project cancellations, outsourcing, knowledge management, and risk mitigation. It is essential reading for technologists and engineers across all disciplines, technology and engineering leaders, and professional strategy consultants.
Digital Forensics in the Era of Artificial Intelligence
Digital forensics plays a crucial role in identifying, analysing, and presenting cyber threats as evidence in a court of law. Artificial intelligence, particularly machine learning and deep learning, enables automation of the digital investigation process. This book provides an in-depth look at the fundamental and advanced methods in digital forensics. It also discusses how machine learning and deep learning algorithms can be used to detect and investigate cybercrimes. This book demonstrates digital forensics and cyber-investigating techniques with real-world applications. It examines hard disk analytics and style architectures, including Master Boot Record and GUID Partition Table as part of the investigative process. It also covers cyberattack analysis in Windows, Linux, and network systems using virtual machines in real-world scenarios. Digital Forensics in the Era of Artificial Intelligence will be helpful for those interested in digital forensics and using machine learning techniques in the investigation of cyberattacks and the detection of evidence in cybercrimes.
Security, Privacy, and Anonymity in Computation, Communication, and Storage
This book constitutes the refereed proceedings of six symposiums and two workshops co-located with SpaCCS 2019, the 12th International Conference on Security, Privacy, and Anonymity in Computation, Communication, and Storage. The 26 full papers were carefully reviewed and selected from 75 submissions. This year's symposiums and workshops are: SPIoT 2019 – Security and Privacy of Internet of Things; TSP 2019 – Trust, Security and Privacy for Emerging Applications; SCS 2019 – Sensor-Cloud Systems; UbiSafe 2019 – UbiSafe Computing; ISSR 2019 – Security in e-Science and e-Research; CMRM 2019 – Cybersecurity Metrics and Risk Modeling.
Handbook of Data Intensive Computing
Data Intensive Computing refers to capturing, managing, analyzing, and understanding data at volumes and rates that push the frontiers of current technologies. The challenge of data intensive computing is to provide the hardware architectures and related software systems and techniques which are capable of transforming ultra-large data into valuable knowledge. Handbook of Data Intensive Computing is written by leading international experts in the field. Experts from academia, research laboratories and private industry address both theory and application. Data intensive computing demands a fundamentally different set of principles than mainstream computing. Data-intensive applications typically are well suited for large-scale parallelism over the data and also require an extremely high degree of fault-tolerance, reliability, and availability. Real-world examples are provided throughout the book. Handbook of Data Intensive Computing is designed as a reference for practitioners and researchers, including programmers, computer and system infrastructure designers, and developers. This book can also be beneficial for business managers, entrepreneurs, and investors.
Internet of Things
The book deals with the conceptual and practical knowledge of the latest tools and methodologies of hardware development for Internet of Things (IoT) and variety of real-world challenges. The topics cover the state-of-the-art and future perspectives of IoT technologies, where industry experts, researchers, and academics had shared ideas and experiences surrounding frontier technologies, breakthrough, and innovative solutions and applications. Several aspects of various hardware technologies, methodologies, and communication protocol such as formal design flow for IoT hardware, design approaches for IoT hardware, IoT solution reference architectures and Instances, simulation, modelling and pr...
Engineering Mathematics and Artificial Intelligence
The fields of Artificial Intelligence (AI) and Machine Learning (ML) have grown dramatically in recent years, with an increasingly impressive spectrum of successful applications. This book represents a key reference for anybody interested in the intersection between mathematics and AI/ML and provides an overview of the current research streams. Engineering Mathematics and Artificial Intelligence: Foundations, Methods, and Applications discusses the theory behind ML and shows how mathematics can be used in AI. The book illustrates how to improve existing algorithms by using advanced mathematics and offers cutting-edge AI technologies. The book goes on to discuss how ML can support mathematical modeling and how to simulate data by using artificial neural networks. Future integration between ML and complex mathematical techniques is also highlighted within the book. This book is written for researchers, practitioners, engineers, and AI consultants.
Second International Conference on Sustainable Technologies for Computational Intelligence
This book gathers high-quality papers presented at the Second International Conference on Sustainable Technologies for Computational Intelligence (ICTSCI 2021) held at Graphic Era University, Dehradun, India, during May 22–23, 2021. It covers emerging topics in computational intelligence and effective strategies for its implementation in engineering applications.
