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Books > Computing & IT > Applications of computing
Recent advances in eye tracking technology will allow for a proliferation of new applications. Improvements in interactive methods using eye movement and gaze control could result in faster and more efficient human computer interfaces, benefitting users with and without disabilities. Gaze Interaction and Applications of Eye Tracking: Advances in Assistive Technologies focuses on interactive communication and control tools based on gaze tracking, including eye typing, computer control, and gaming, with special attention to assistive technologies. For researchers and practitioners interested in the applied use of gaze tracking, the book offers instructions for building a basic eye tracker from off-the-shelf components, gives practical hints on building interactive applications, presents smooth and efficient interaction techniques, and summarizes the results of effective research on cutting edge gaze interaction applications.
Statistical learning and analysis techniques have become extremely important today, given the tremendous growth in the size of heterogeneous data collections and the ability to process it even from physically distant locations. Recent advances made in the field of machine learning provide a strong framework for robust learning from the diverse corpora and continue to impact a variety of research problems across multiple scientific disciplines. The aim of this handbook is to familiarize beginners as well as experts with some of the recent techniques in this field. The Handbook is divided in two sections: Theory and
Applications, covering machine learning, data analytics,
biometrics, document recognition and security. emphasis on applications-oriented techniques
Swarm Intelligence and bio-inspired computation have become
increasing popular in the last two decades. Bio-inspired algorithms
such as ant colony algorithms, bat algorithms, bee algorithms,
firefly algorithms, cuckoo search and particle swarm optimization
have been applied in almost every area of science and engineering
with a dramatic increase of number of relevant publications. This
book reviews the latest developments in swarm intelligence and
bio-inspired computation from both the theory and application side,
providing a complete resource that analyzes and discusses the
latest and future trends in research directions. It can help new
researchers to carry out timely research and inspire readers to
develop new algorithms. With its impressive breadth and depth, this
book will be useful for advanced undergraduate students, PhD
students and lecturers in computer science, engineering and science
as well as researchers and engineers.
Modern devices, from phones and cars to houses and the appliances within them, are being designed with formidable computational power and expanded functionality. To be truly effective, these smart devices must effectively process data from their environment and experiences and make decisions based on that information. Recent Advances in Ambient Intelligence and Context-Aware Computing investigates the functionality of ubiquitous computational systems and how they may adapt to their environment to improve the quality of interaction for the end-user. This reference book will be of value to under- and post-graduate students, professionals, and researchers networking, computer science, communications, and other information technology disciplines.
Everyone wants privacy and security online, something that most computer users have more or less given up on as far as their personal data is concerned. There is no shortage of good encryption software, and no shortage of books, articles and essays that purport to be about how to use it. Yet there is precious little for ordinary users who want just enough information about encryption to use it safely and securely and appropriately--WITHOUT having to become experts in cryptography. Data encryption is a powerful tool, if used properly. Encryption turns ordinary, readable data into what looks like gibberish, but gibberish that only the end user can turn back into readable data again. The difficulty of encryption has much to do with deciding what kinds of threats one needs to protect against and then using the proper tool in the correct way. It's kind of like a manual transmission in a car: learning to drive with one is easy; learning to build one is hard. The goal of this title is to present just enough for an average reader to begin protecting his or her data, immediately. Books and articles currently available about encryption start out with statistics and reports on the costs of data loss, and quickly get bogged down in cryptographic theory and jargon followed by attempts to comprehensively list all the latest and greatest tools and techniques. After step-by-step walkthroughs of the download and install process, there's precious little room left for what most readers really want: how to encrypt a thumb drive or email message, or digitally sign a data file. There are terabytes of content that explain how cryptography works, why it's important, and all the different pieces of software that can be used to do it; there is precious little content available that couples concrete threats to data with explicit responses to those threats. This title fills that niche. By reading this title readers will be provided with a step by step hands-on guide that includes: Simple descriptions of actual threat scenarios Simple, step-by-step instructions for securing data How to use open source, time-proven and peer-reviewed cryptographic software Easy to follow tips for safer computing Unbiased and platform-independent coverage of encryption tools
and techniques
This book provides a snapshot of the state of current research at the interface between machine learning and healthcare with special emphasis on machine learning projects that are (or are close to) achieving improvement in patient outcomes. The book provides overviews on a range of technologies including detecting artefactual events in vital signs monitoring data; patient physiological monitoring; tracking infectious disease; predicting antibiotic resistance from genomic data; and managing chronic disease. With contributions from an international panel of leading researchers, this book will find a place on the bookshelves of academic and industrial researchers and advanced students working in healthcare technologies, biomedical engineering, and machine learning.
Deep learning has become a trending area of research due to its adaptive characteristics and high levels of applicability. In recent years, researchers have begun applying deep learning strategies to image analysis and pattern recognition for solving technical issues within image classification. As these technologies continue to advance, professionals have begun translating this intelligent programming language into mobile applications for devices. Programmers and web developers are in need of significant research on how to successfully develop pattern recognition applications using intelligent programming. MatConvNet Deep Learning and iOS Mobile App Design for Pattern Recognition: Emerging Research and Opportunities is an essential reference source that presents a solution to developing intelligent pattern recognition Apps on iOS devices based on MatConvNet deep learning. Featuring research on topics such as medical image diagnosis, convolutional neural networks, and character classification, this book is ideally designed for programmers, developers, researchers, practitioners, engineers, academicians, students, scientists, and educators seeking coverage on the specific development of iOS mobile applications using pattern recognition strategies.
For Database Systems and Database Design and Application courses offered at the junior, senior and graduate levels in Computer Science departments. Written by well-known computer scientists, this introduction to database systems offers a comprehensive approach, focusing on database design, database use, and implementation of database applications and database management systems. The first half of the book provides in-depth coverage of databases from the point of view of the database designer, user, and application programmer. It covers the latest database standards SQL:1999, SQL/PSM, SQL/CLI, JDBC, ODL, and XML, with broader coverage of SQL than most other texts. The second half of the book provides in-depth coverage of databases from the point of view of the DBMS implementor. It focuses on storage structures, query processing, and transaction management. The book covers the main techniques in these areas with broader coverage of query optimisation than most other texts, along with advanced topics including multidimensional and bitmap indexes, distributed transactions, and information integration techniques.
As governments worldwide are entering the digital age, there are increasing expectations from citizens and stakeholders for a more responsive, efficient, and open government. Innovations in information technology and web technologies can facilitate these changes. Innovative Perspectives on Public Administration in the Digital Age is a critical scholarly resource that examines the prevalence of e-government and the advancements of information systems to facilitate a government that is more open and accessible to citizens and businesses. Highlighting coverage on a broad range of topics such as online civic engagement, e-petition, and privacy and security, this publication is geared toward academicians, practitioners, and government officials seeking current and relevant research on the use of online and technological systems for the advancement of government and public policy.
Information in today's advancing world is rapidly expanding and becoming widely available. This eruption of data has made handling it a daunting and time-consuming task. Natural language processing (NLP) is a method that applies linguistics and algorithms to large amounts of this data to make it more valuable. NLP improves the interaction between humans and computers, yet there remains a lack of research that focuses on the practical implementations of this trending approach. Neural Networks for Natural Language Processing is a collection of innovative research on the methods and applications of linguistic information processing and its computational properties. This publication will support readers with performing sentence classification and language generation using neural networks, apply deep learning models to solve machine translation and conversation problems, and apply deep structured semantic models on information retrieval and natural language applications. While highlighting topics including deep learning, query entity recognition, and information retrieval, this book is ideally designed for research and development professionals, IT specialists, industrialists, technology developers, data analysts, data scientists, academics, researchers, and students seeking current research on the fundamental concepts and techniques of natural language processing.
Business operations in large organizations today involve massive, interactive, and layered networks of teams and personnel collaborating across hierarchies and countries on complex tasks. To optimize productivity, businesses need to know: what communication patterns do high-performing teams have in common? Is it possible to predict a team's performance before it starts work on a project? How can productive team behavior be fostered? This comprehensive review for researchers and practitioners in data mining and social networks surveys recent progress in the emerging field of network science of teams. Focusing on the underlying social network structure, the authors present models and algorithms characterizing, predicting, optimizing, and explaining team performance, along with key applications, open challenges, and future trends.
Human hands are natural tools for performing actions and gestures that interact with the physical world. Radar technology allows for touchless wireless gesture sensing by transmitting radio frequency (RF) signals to the target, analyzing the backscattering reflections to extract the target's movements, and thereby accurately detecting gestures for Human Computer Interaction (HCI). A key advantage of this technology is that it allows interaction with machines without any need to attach a sensing device to the hands. Led by researchers from Google's Project Soli, the authors introduce the concept and underpinning technology, cover all design phases, and provide researchers and professionals with the latest advances and innovations in microwave and millimeter wave radar sensing to capture relative movements such as micro gestures.
In this collection of 17 articles, top scholars synthesize and
analyze scholarship on this widely used tool of policy analysis,
setting forth its accomplishments, difficulties, and means of
implementation. Though CGE modeling does not play a prominent role
in top US graduate schools, it is employed universally in the
development of economic policy. This collection is particularly
important because itpresents a history of modeling applications and
examines competing points of view.
Churn prediction, recognition, and mitigation have become essential topics in various industries. As a means for forecasting and manageing risk, further research in this field can greatly assist companies in making informed decisions based on future possible scenarios. Developing Churn Models Using Data Mining Techniques and Social Network Analysis provides an in-depth analysis of attrition modeling relevant to business planning and management. Through its insightful and detailed explanation of best practices, tools, and theory surrounding churn prediction and the integration of analytics tools, this publication is especially relevant to managers, data specialists, business analysts, academicians, and upper-level students.
Artificial intelligence is headline news with the launch of the latest ChatGPT and Google Bard. But when did we start making computers mimic the human mind? And what is the reality of the capabilities of AI now, and in the future? AI has always stirred emotions and caused great excitement and concern. Since the launch of large language models such as ChatGPT, the scope and capabilities of AI look set to transform our technology, in both good and bad ways. AI can help teach us how to write better or help us generate amazing artwork. But in the wrong hands, AI can create fake images and fake information that can be used to damage our societies. A new addition to the popular Bite-sized Chunks series, this expert-led book will explore how AI has developed from humble beginnings in the 1950s to today’s extraordinary AIs with more neurons than the human brain. Focusing on specific AIs and their creators over the years, it explains the science and engineering behind each AI, discusses ethical issues, and covers all the most fascinating information about one of the most important and contentious developments in human technology (including the latest on generative AI/ChatGPT), as well as what we can expect to see in the future of this field – all in short, accessible bite-sized chunks.
For the past decade or more, much of cell biology research has been focused on determining the key molecules involved in different cellular processes, an analytical problem that has been amenable to biochemical and genetic approaches. Now, we face an integrative problem of understanding how all of these molecules work together to produce living cells, a challenge that requires using quantitative approaches to model the complex interactions within a cell, and testing those models with careful quantitative measurements. This book is an introductory overview of the various approaches, methods, techniques, and models employed in quantitative cell biology, which are reviewed in greater detail in the other volumes in this e-book series. Particular emphasis is placed on the goals and purpose of quantitative analysis and modeling, and the special challenges that cell biology holds for understanding life at the physical level.
As humans interact more often and more intimately with computers, and as computational systems become an ever more important element of our society, playing roles in education, the production of culture and goods, and management, it is inevitable that we should seek to interact with these systems in ways that take advantage of our powerful emotional capabilities. Creating Synthetic Emotions through Technological and Robotic Advancements compiles progressive research in the emerging and groundbreaking fields of artificial emotions, affective computing, and sociable robotics that allow humans to begin the once impossible-seeming task of interacting with robots, systems, devices, and agents. This landmark volume brings together expert international researchers to expound upon these topics as synthetic emotions move toward becoming a daily reality.
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