With new technologies, such as computer vision, internet of things, mobile computing, e-governance and e-commerce, and wide applications of social media, organizations generate a huge volume of data and at a much faster rate than several years ago. Big data in large-/small-scale systems, characterized by high volume, diversity, and velocity, increasingly drives decision making and is changing the landscape of business intelligence. From governments to private organizations, from communities to individuals, all areas are being affected by this shift. There is a high demand for big data analytics that offer insights for computing efficiency, knowledge discovery, problem solving, and event prediction. To handle this demand and this increase in big data, there needs to be research on innovative and optimized machine learning algorithms in both large- and small-scale systems. Applications of Big Data in Large- and Small-Scale Systems includes state-of-the-art research findings on the latest development, up-to-date issues, and challenges in the field of big data and presents the latest innovative and intelligent applications related to big data. This book encompasses big data in various multidisciplinary fields from the medical field to agriculture, business research, and smart cities. While highlighting topics including machine learning, cloud computing, data visualization, and more, this book is a valuable reference tool for computer scientists, data scientists and analysts, engineers, practitioners, stakeholders, researchers, academicians, and students interested in the versatile and innovative use of big data in both large-scale and small-scale systems.

The emergent phenomena of virtual reality, augmented reality, and mixed reality is having an impact on ways people communicate with technology and with each other. Schools and higher education institutions are embracing these emerging technologies and implementing them at a rapid pace. The challenge, however, is to identify well-defined problems where these innovative technologies can support successful solutions and subsequently determine the efficacy of effective virtual learning environments. Emerging Technologies in Virtual Learning Environments is an essential scholarly research publication that provides a deeper look into 3D virtual environments and how they can be developed and applied for the benefit of student learning and teacher training. This book features a wide range of topics in the areas of science, technology, engineering, arts, and math to ensure a blend of both science and humanities research. Therefore, it is ideal for curriculum developers, instructional designers, teachers, school administrators, higher education faculty, professionals, researchers, and students studying across all academic disciplines.

Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques: A MATLAB Based Approach presents how machine learning and biomedical signal processing methods can be used in biomedical signal analysis. Different machine learning applications in biomedical signal analysis, including those for electrocardiogram, electroencephalogram and electromyogram are described in a practical and comprehensive way, helping readers with limited knowledge. Sections cover biomedical signals and machine learning techniques, biomedical signals, such as electroencephalogram (EEG), electromyogram (EMG) and electrocardiogram (ECG), different signal-processing techniques, signal de-noising, feature extraction and dimension reduction techniques, such as PCA, ICA, KPCA, MSPCA, entropy measures, and other statistical measures, and more. This book is a valuable source for bioinformaticians, medical doctors and other members of the biomedical field who need a cogent resource on the most recent and promising machine learning techniques for biomedical signals analysis.

For introductory courses (freshman and sophomore courses) in Digital Signal Processing and Signals and Systems. Text may be used before the student has taken a course in circuits. DSP First and its accompanying digital assets are the result of more than 20 years of work that originated from, and was guided by, the premise that signal processing is the best starting point for the study of electrical and computer engineering. The "DSP First" approach introduces the use of mathematics as the language for thinking about engineering problems, lays the groundwork for subsequent courses, and gives students hands-on experiences with MATLAB. The 2nd Edition features three new chapters on the Fourier Series, Discrete-Time Fourier Transform, and the The Discrete Fourier Transform as well as updated labs, visual demos, an update to the existing chapters, and hundreds of new homework problems and solutions.

With technology creating a more competitive market, the global economy has been continually evolving in recent years. These technological developments have drastically changed the ways organizations manage their resources, as they are constantly seeking innovative methods to implement new systems. Because of this, there is an urgent need for empirical research that studies advancing theories and applications that organizations can use to successfully handle information and supplies. Novel Theories and Applications of Global Information Resource Management is a pivotal reference source that provides vital research on developing practices for businesses to effectively manage their assets on a global scale. While highlighting topics such as enterprise systems, library management, and information security, this publication explores the implementation of technological innovation into business techniques as well as the methods of controlling information in a contemporary society. This book is ideally designed for brokers, accountants, marketers, researchers, data scientists, financiers, managers, and academicians seeking current research on global resource management.

While human capabilities can withstand broad levels of strain, they cannot hope to compete with the advanced abilities of automated technologies. Developing advanced robotic systems will provide a better, faster means to produce goods and deliver a level of seamless communication and synchronization that exceeds human skill. Advanced Robotics and Intelligent Automation in Manufacturing is a pivotal reference source that provides vital research on the application of advanced manufacturing technologies in regards to production speed, quality, and innovation. While highlighting topics such as human-machine interaction, quality management, and sensor integration, this publication explores state-of-the-art technologies in the field of robotics engineering as well as human-robot interaction. This book is ideally designed for researchers, students, engineers, manufacturers, managers, industry professionals, and academicians seeking to enhance their innovative design capabilities.

Quality assurance is an essential aspect for ensuring the success of corporations worldwide. Consistent quality requirements across organizations of similar types ensure that these requirements can be accurately and easily evaluated. Shaping the Future Through Standardization is an essential scholarly book that examines quality and standardization within diverse organizations globally with a special focus on future perspectives, including how standards and standardization may shape the future. Featuring a wide range of topics such as economics, pedagogy, and management, this book is ideal for academicians, researchers, decision makers, policymakers, managers, corporate professionals, and students.

Competition in today's global market offers strong motivation for the development of sophisticated tools within computer science. The neuron multi-functional technology platform is a developing field of study that regards the various interactive approaches that can be applied within this subject matter. As advancing technologies continue to emerge, managers and researchers need a compilation of research that discusses the advancements and specific implementations of these intelligent approaches with this platform. Avatar-Based Control, Estimation, Communications, and Development of Neuron Multi-Functional Technology Platforms is a pivotal reference source that provides vital research on the application of artificial and natural approaches towards neuron-based programs. While highlighting topics such as natural intelligence, neurolinguistics, and smart data storage, this publication presents techniques, case studies, and methodologies that combine the use of intelligent artificial and natural approaches with optimization techniques for facing problems and combines many types of hardware and software with a variety of communication technologies to enable the development of innovative applications. This book is ideally designed for researchers, practitioners, scientists, field experts, professors, and students seeking current research on the optimization of avatar-based advancements in multifaceted technology systems.

This book presents the state-of-the-art, current challenges, and future perspectives for the field of many-criteria optimization and decision analysis. The field recognizes that real-life problems often involve trying to balance a multiplicity of considerations simultaneously – such as performance, cost, risk, sustainability, and quality. The field develops theory, methods and tools that can support decision makers in finding appropriate solutions when faced with many (typically more than three) such criteria at the same time.  The book consists of two parts: key research topics, and emerging topics. Part I begins with a general introduction to many-criteria optimization, perspectives from research leaders in real-world problems, and a contemporary survey of the attributes of problems of this kind. This part continues with chapters on fundamental aspects of many-criteria optimization, namely on order relations, quality measures, benchmarking, visualization, and theoretical considerations. Part II offers more specialized chapters on correlated objectives, heterogeneous objectives, Bayesian optimization, and game theory. Written by leading experts across the field of many-criteria optimization, this book will be an essential resource for researchers in the fields of evolutionary computing, operations research, multiobjective optimization, and decision science.

Interest in developing smart cities has grown exponentially over the years with many governments across the world hoping to initiate these projects in their own countries. One of the key challenges for the success of any smart city project is the assurance of smart security and privacy of the citizens. Due to the use of a wide range of interconnected cyber-physical systems, traditional security solutions cannot be applied to smart city applications, and new practices must be sought. Secure Cyber-Physical Systems for Smart Cities is an essential reference publication that examines information security and privacy in smart city settings including discussions on new security frameworks, solutions, cybersecurity laws and regulations, and risk management frameworks for smart city environments. Covering a wide range of topics including wireless networks, security, and cyber-physical systems, this book is ideally designed for IT specialists and consultants, engineers, government officials, policymakers, researchers, academicians, and industry professionals.

Research on artificial life is critical to solving various dynamic obstacles individuals face on a daily basis. From electric wheelchairs to navigation, artificial life can play a role in improving both the simple and complex aspects of civilian life. The Handbook of Research on Investigations in Artificial Life Research and Development is a vital scholarly reference source that examines emergent research in handling real-world problems through the application of various computation technologies and techniques. Examining topics such as computational intelligence, multi-agent systems, and fuzzy logic, this publication is a valuable resource for academicians, scientists, researchers, and individuals interested in artificial intelligence developments.

Though an individual can process a limitless amount of information, the human brain can only comprehend a small amount of data at a time. Using technology can improve the process and comprehension of information, but the technology must learn to behave more like a human brain to employ concepts like memory, learning, visualization ability, and decision making. Emerging Trends and Applications in Cognitive Computing is a fundamental scholarly source that provides empirical studies and theoretical analysis to show how learning methods can solve important application problems throughout various industries and explain how machine learning research is conducted. Including innovative research on topics such as deep neural networks, cyber-physical systems, and pattern recognition, this collection of research will benefit individuals such as IT professionals, academicians, students, researchers, and managers.

The success of many companies through the assistance of bitcoin proves that technology continually dominates and transforms how economics operate. However, a deeper, more conceptual understanding of how these technologies work to identify innovation opportunities and how to successfully thrive in an increasingly competitive environment is needed for the entrepreneurs of tomorrow. Transforming Businesses With Bitcoin Mining and Blockchain Applications provides innovative insights into IT infrastructure and emerging trends in the realm of digital business technologies. This publication analyzes and extracts information from Bitcoin networks and provides the necessary steps to designing open blockchain. Highlighting topics that include financial markets, risk management, and smart technologies, the research contained within the title is ideal for entrepreneurs, business professionals, managers, executives, academicians, researchers, and business students.

Developments and Applications for ECG Signal Processing: Modeling, Segmentation, and Pattern Recognition covers reliable techniques for ECG signal processing and their potential to significantly increase the applicability of ECG use in diagnosis. This book details a wide range of challenges in the processes of acquisition, preprocessing, segmentation, mathematical modelling and pattern recognition in ECG signals, presenting practical and robust solutions based on digital signal processing techniques. Users will find this to be a comprehensive resource that contributes to research on the automatic analysis of ECG signals and extends resources relating to rapid and accurate diagnoses, particularly for long-term signals. Chapters cover classical and modern features surrounding f ECG signals, ECG signal acquisition systems, techniques for noise suppression for ECG signal processing, a delineation of the QRS complex, mathematical modelling of T- and P-waves, and the automatic classification of heartbeats.

Data-Driven Solutions to Transportation Problems explores the fundamental principle of analyzing different types of transportation-related data using methodologies such as the data fusion model, the big data mining approach, computer vision-enabled traffic sensing data analysis, and machine learning. The book examines the state-of-the-art in data-enabled methodologies, technologies and applications in transportation. Readers will learn how to solve problems relating to energy efficiency under connected vehicle environments, urban travel behavior, trajectory data-based travel pattern identification, public transportation analysis, traffic signal control efficiency, optimizing traffic networks network, and much more.

20 years in conception and 15 in construction, the SpiNNaker project has delivered the world's largest neuromorphic computing platform incorporating over a million ARM mobile phone processors and capable of modelling spiking neural networks of the scale of a mouse brain in biological real time. This machine, hosted at the University of Manchester in the UK, is freely available under the auspices of the EU Flagship Human Brain Project. This books tells the story of the origins of the machine, its development and its deployment, and the immense software development effort that has gone into making it openly available and accessible to researchers and students the world over. It also presents exemplar applications from 'Talk', a SpiNNaker-controlled robotic exhibit at the Manchester Art Gallery as part of 'The Imitation Game', a set of works commissioned in 2016 in honour of Alan Turing, through to a way to solve hard computing problems using stochastic neural networks. The book concludes with a look to the future, and the SpiNNaker-2 machine which is yet to come

Multimodal Behavioral Analysis in the Wild: Advances and Challenges presents the state-of- the-art in behavioral signal processing using different data modalities, with a special focus on identifying the strengths and limitations of current technologies. The book focuses on audio and video modalities, while also emphasizing emerging modalities, such as accelerometer or proximity data. It covers tasks at different levels of complexity, from low level (speaker detection, sensorimotor links, source separation), through middle level (conversational group detection, addresser and addressee identification), and high level (personality and emotion recognition), providing insights on how to exploit inter-level and intra-level links. This is a valuable resource on the state-of-the- art and future research challenges of multi-modal behavioral analysis in the wild. It is suitable for researchers and graduate students in the fields of computer vision, audio processing, pattern recognition, machine learning and social signal processing.

Because trainees need to learn about the underlying technologies to use automation safely and efficiently, the development of automated aviation systems training is a growing challenge. Task analysis has been singled out as the basis of the training, but it can be more time-consuming than traditional development techniques. Cases on Modern Computer Systems in Aviation is an essential reference source that covers new information technology use in aviation systems to streamline the cybersecurity, decision-making, planning, and design processes within the aviation industry. Featuring coverage on a broad range of topics such as computer systems in aviation, artificial intelligence, software-defined networking (SDN), air navigation systems, decision support systems (DSS), and more, this publication is ideally designed for aviation specialists and industry professionals, technicians, practitioners, researchers, and academicians seeking current research on modern modeling approaches to streamline management in aviation.