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Books > Computing & IT > Applications of computing > Artificial intelligence > General
Provides a structured look, at the unique characteristic for smart sensor networks to resolving the issues of many real-world applications in a broad range of areas such as Smart Healthcare, Engineering, Scientific Research, Social Media, Industrial Automation and more Offers a systematic look at the unique characteristics of AI based wireless sensor networks through their usage in a broad range of areas Delivers recent trends and core concepts in both analytics and application in smart sensor networks using AI Explores the development and application of AI and evolutionary computing as applied to wireless sensor networks Focuses on stepwise discussion, exhaustive literature review, detailed analysis and discussion, rigorous experimentation result and an application-oriented approach.
Introduces design of experiments and digital twin concepts in simple lay terms for physicists to understand, adopt and adapt. Free from endless derivations equations are presented and explained strategically, explaining why it is imperative to use them and how they will help in your task at hand. Illustrations and simple explanation help readers visualize and absorb easily, difficult to understand concepts.
The healthcare industry is on the cutting edge of voice-user interface (VUI) design and making great progress to improve patient care through developing technologies, literally transforming the voice of the industry. The advantages of VUI extend far beyond simple conveniences for patients or a healthcare employee's saved phone call. VUI has a profound impact on care improvement. Just like a person, a well-designed VUI can use tone of voice, inflection and other elements in conversation to shape behaviors or calm nerves. With VUI, physicians and patients become empowered to make informed decisions about healthcare. The use of voice technology across smart speakers, IoT, clinical and home devices, and wearables for improving the patient experience and clinical outcomes was recently identified as one of most significant emerging technologies in healthcare. Smart speakers are the #1 selling consumer item in the world and major competition is heating up between Amazon Alexa, Apple Siri, Microsoft Cortana, Google Voice Assistant, and a host of other specialty platforms specific to healthcare. From Orbita and Macadamia to voice-enabled robotics from Pillo, Intuitive, Vivify, and RealView Imaging, voice technology is pervasive across the gamut of levels of devices. Voice technology is not just pervasive in smart speakers and smart phones - it is finding its way into wearables, vehicles, homes, and even consumer and clinical medical devices. We even have smart jewelry emerging with health, wellness, and safety features built in. Best of all, this trend spans intergenerational health and wellness that goes beyond clinical care into long term health and wellbeing and the potential for increased patient engagement. In this book, the editors review information from the top thought-leaders in this space and examine real-world case studies of the outcomes and potential of voice technology in healthcare. Topics include a market survey, clinical use cases, home health use cases, health and wellness topics - fitness, nutrition, and wellbeing; next generation fitness facilities; voice and wearables in smart, connected communities; voice technology in social companions/robots; voice technology in the future surgical suites; a roadmap for the future from top technology; standards in voice technology; and the future of voice technology and artificial intelligence.
Winner of the "Outstanding Academic Title" recognition by Choice for the 2020 OAT Awards. The Choice OAT Award represents the highest caliber of scholarly titles that have been reviewed by Choice and conveys the extraordinary recognition of the academic community. In recent years social media has gained significant popularity and has become an essential medium of communication. Such user-generated content provides an excellent scenario for applying the metaphor of mining any information. Transfer learning is a research problem in machine learning that focuses on leveraging the knowledge gained while solving one problem and applying it to a different, but related problem. Features: Offers novel frameworks to study user behavior and for addressing and explaining task heterogeneity Presents a detailed study of existing research Provides convergence and complexity analysis of the frameworks Includes algorithms to implement the proposed research work Covers extensive empirical analysis Social Media Analytics for User Behavior Modeling: A Task Heterogeneity Perspective is a guide to user behavior modeling in heterogeneous settings and is of great use to the machine learning community.
Artificial intelligence will not necessarily create a super-intelligent "human robot"; however, it is very probable that intelligent robots and intelligent informats will bring about a form of super-globalization, in which money and goods are prioritized over people and democracy and where the widespread use of casual labour - that is, short-term contracts - will become the most common form of employment relationship. It is also very likely that artificial intelligence will bring about what is known as singularity. This term is used to describe a situation where intelligent robots, from a rational and logical perspective, are smarter than humans, i.e. the development of AI. This book explores the impact that these intelligent robots and intelligent informats will have on social and societal development. The author tackles the question of singularity from three distinct standpoints: technological singularity - the intelligence of machines compared to that of humans - which he argues will bring about a qualitatively new labour market; economic singularity - the consequences for work relationships, value creation and employment - which he asserts will promote full automation, result in precarious contracts with low salaries, and, in some countries, possibly lead to the introduction of a universal basic income; and social singularity - the consequences of technological and economic singularity for democratic processes, bureaucratic procedures for exercising authority and control, and the direction in which society will develop, in addition to the emergence of new social institutions - which Johannessen says will promote a transition from representative democracy to genuine democracy. The book will appeal to academics, researchers and students of economic sociology and political economy, as well as those focusing upon the emerging innovation economy. It will also find an audience among professionals and policymakers keen to understand the impact the Fourth Industrial Revolution will have on organizations, individuals and society at large.
Introduces a new web-based optimizer for Geometric algebra algorithms; Supports many programming languages as well as hardware; Covers the advantages of High-dimensional algebras; Includes geometrically intuitive support of quantum computing
Data science is an emerging field and innovations in it need to be explored for the success of society 5.0. This book not only focuses on the practical applications of data science to achieve computational excellence, but also digs deep into the issues and implications of intelligent systems. This book highlights innovations in data science to achieve computational excellence that can optimize performance of smart applications. The book focuses on methodologies, framework, design issues, tools, architectures, and technologies necessary to develop and understand data science and its emerging applications in the present era. Data Science and Innovations for Intelligent Systems: Computational Excellence and Society 5.0 is useful for the research community, start-up entrepreneurs, academicians, data-centered industries, and professeurs who are interested in exploring innovations in varied applications and the areas of data science.
Provides a clear and concise overview of how AI is used in game development Gives a brief overview of the history of AI in games Considers the different models, techniques and algorithms that are used in creating game AI
The impact of the proposed book is to provide a significant area of concern to develop a foundation for the implementation process renewable energy system with intelligent techniques. The researchers working on a renewable energy system can correlate their work with intelligent and machine learning approaches. To make aware of the international standards for intelligent renewable energy systems design, reliability and maintenance. To give better incites of the solar cell, biofuels, wind and other renewable energy system design and characterization, including the equipment for smart energy systems.
Machine Translation (MT) has become widely used throughout the world as a medium of communication between those who live in different countries and speak different languages. However, translation between distant languages constitutes a challenge for machines. Therefore, translation evaluation is poised to play a significant role in the process of designing and developing effective MT systems. This book evaluates three prominent MT systems, including Google Translate, Microsoft Translator, and Sakhr, each of which provides translation between English and Arabic. In the book Almahasees scrutinizes the capacity of the three systems in dealing with translation between English and Arabic in a large corpus taken from various domains, including the United Nation (UN), the World Health Organization (WHO), the Arab League, Petra News Agency reports, and two literary texts: The Old Man and the Sea and The Prophet. The evaluation covers holistic analysis to assess the output of the three systems in terms of Translation Automation User Society (TAUS) adequacy and fluency scales. The text also looks at error analysis to evaluate the systems' output in terms of orthography, lexis, grammar, and semantics at the entire-text level and in terms of lexis, grammar, and semantics at the collocation level. The research findings contained within this volume provide important feedback about the capabilities of the three MT systems with respect to English<>Arabic translation and paves the way for further research on such an important topic. This book will be of interest to scholars and students of translation studies and translation technology.
Provides insight into the skill set that requires leveraging strength to move further to act as a good data analyst Discusses how big data along with deep learning holds the potential to significantly increase data understanding and in turn, helps to make decisions Covers the numerous potential applications in healthcare, education, communications, media, and the entertainment industry Offers innovative platforms for integrating big data and deep learning Presents issues related to adequate data storage, sematic indexing, data tagging, and fast information retrieval from big data
Disruptive Trends in Computer Aided Diagnosis collates novel techniques and methodologies in the domain of content based image classification and deep learning/machine learning techniques to design efficient computer aided diagnosis architecture. It is aimed to highlight new challenges and probable solutions in the domain of computer aided diagnosis to leverage balancing of sustainable ecology. The volume focuses on designing efficient algorithms for proposing CAD systems to mitigate the challenges of critical illnesses at an early stage. State-of-the-art novel methods are explored for envisaging automated diagnosis systems thereby overriding the limitations due to lack of training data, sample annotation, region of interest identification, proper segmentation and so on. The assorted techniques addresses the challenges encountered in existing systems thereby facilitating accurate patient healthcare and diagnosis. Features: An integrated interdisciplinary approach to address complex computer aided diagnosis problems and limitations. Elucidates a rich summary of the state-of-the-art tools and techniques related to automated detection and diagnosis of life threatening diseases including pandemics. Machine learning and deep learning methodologies on evolving accurate and precise early detection and medical diagnosis systems. Information presented in an accessible way for students, researchers and medical practitioners. The volume would come to the benefit of both post-graduate students and aspiring researchers in the field of medical informatics, computer science and electronics and communication engineering. In addition, the volume is also intended to serve as a guiding factor for the medical practitioners and radiologists in accurate diagnosis of diseases.
Up to 70% and even more of corporate Analytics Efforts fail!!! Even after these corporations have made very large investments, in time, talent, and money, in developing what they thought were good data and analytics programs. Why? Because the executives and decision makers and the entire analytics team have not considered the most important aspect of making these analytics efforts successful. In this Book II of "It's All Analytics!" series, we describe two primary things: 1) What this "most important aspect" consists of, and 2) How to get this "most important aspect" at the center of the analytics effort and thus make your analytics program successful. This Book II in the series is divided into three main parts: Part I, Organizational Design for Success, discusses ....... The need for a complete company / organizational Alignment of the entire company and its analytics team for making its analytics successful. This means attention to the culture - the company culture culture!!! To be successful, the CEO's and Decision Makers of a company / organization must be fully cognizant of the cultural focus on 'establishing a center of excellence in analytics'. Simply, "culture - company culture" is the most important aspect of a successful analytics program. The focus must be on innovation, as this is needed by the analytics team to develop successful algorithms that will lead to greater company efficiency and increased profits. Part II, Data Design for Success, discusses ..... Data is the cornerstone of success with analytics. You can have the best analytics algorithms and models available, but if you do not have good data, efforts will at best be mediocre if not a complete failure. This Part II also goes further into data with descriptions of things like Volatile Data Memory Storage and Non-Volatile Data Memory Storage, in addition to things like data structures and data formats, plus considering things like Cluster Computing, Data Swamps, Muddy Data, Data Marts, Enterprise Data Warehouse, Data Reservoirs, and Analytic Sandboxes, and additionally Data Virtualization, Curated Data, Purchased Data, Nascent & Future Data, Supplemental Data, Meaningful Data, GIS (Geographic Information Systems) & Geo Analytics Data, Graph Databases, and Time Series Databases. Part II also considers Data Governance including Data Integrity, Data Security, Data Consistency, Data Confidence, Data Leakage, Data Distribution, and Data Literacy. Part III, Analytics Technology Design for Success, discusses .... Analytics Maturity and aspects of this maturity, like Exploratory Data Analysis, Data Preparation, Feature Engineering, Building Models, Model Evaluation, Model Selection, and Model Deployment. Part III also goes into the nuts and bolts of modern predictive analytics, discussing such terms as AI = Artificial Intelligence, Machine Learning, Deep Learning, and the more traditional aspects of analytics that feed into modern analytics like Statistics, Forecasting, Optimization, and Simulation. Part III also goes into how to Communicate and Act upon Analytics, which includes building a successful Analytics Culture within your company / organization. All-in-all, if your company or organization needs to be successful using analytics, this book will give you the basics of what you need to know to make it happen.
Visualization and visual analytics are powerful concepts for exploring data from various application domains. The endless number of possible parameters and the many ways to combine visual variables as well as algorithms and interaction techniques create lots of possibilities for building such techniques and tools. The major goal of those tools is to include the human users with their tasks at hand, their hypotheses, and research questions to provide ways to find solutions to their problems or at least to hint them in a certain direction to come closer to a problem solution. However, due to the sheer number of design variations, it is unclear which technique is suitable for those tasks at hand, requiring some kind of user evaluation to figure out how the human users perform while solving their tasks. The technology of eye tracking has existed for a long time; however, it has only recently been applied to visualization and visual analytics as a means to provide insights to the users' visual attention behavior. This generates another kind of dataset that has a spatio-temporal nature and hence demands for advanced data science and visual analytics concepts to find insights into the recorded eye movement data, either as a post process or even in real-time. This book describes aspects from the interdisciplinary field of visual analytics, but also discusses more general approaches from the field of visualization as well as algorithms and data handling. A major part of the book covers research on those aspects under the light and perspective of eye tracking, building synergy effects between both fields - eye tracking and visual analytics - in both directions, i.e. eye tracking applied to visual analytics and visual analytics applied to eye tracking data. Technical topics discussed in the book include: * Visualization; * Visual Analytics; * User Evaluation; * Eye Tracking; * Eye Tracking Data Analytics; Eye Tracking and Visual Analytics includes more than 500 references from the fields of visualization, visual analytics, user evaluation, eye tracking, and data science, all fields which have their roots in computer science. Eye Tracking and Visual Analytics is written for researchers in both academia and industry, particularly newcomers starting their PhD, but also for PostDocs and professionals with a longer research history in one or more of the covered research fields. Moreover, it can be used to get an overview about one or more of the involved fields and to understand the interface and synergy effects between all of those fields. The book might even be used for teaching lectures in the fields of information visualization, visual analytics, and/or eye tracking.
* This highly topical book will look at and discuss the holistic world of the new intelligences and the new ways to educate us all for living in the future. * Combines, educational research, cognitive psychology and AI perspectives * A book to help increase and develop creativity in response to fundamental changes in our societies and to enhance our intelligence, our ability to understand and act in an informed way. * Contains numerous illustrations and activities
* This highly topical book will look at and discuss the holistic world of the new intelligences and the new ways to educate us all for living in the future. * Combines, educational research, cognitive psychology and AI perspectives * A book to help increase and develop creativity in response to fundamental changes in our societies and to enhance our intelligence, our ability to understand and act in an informed way. * Contains numerous illustrations and activities
Today, innovation does not just occur in large and incumbent R&D organizations. Instead, it often emerges from the start-up community. In the new innovation economy, the key is to quickly find pieces of innovation, some of which may already be developed. Therefore, there is the need for more advanced means of searching and identifying innovation wherever it may occurs. We point to the importance of data-driven innovation based on digital platforms, as their footprints are growing rapidly and in sync with the shift from analogue to digital innovation workflows. This book offers companies insights on paths to business success and tools that will help them find the right route through the various options when it comes to the digital platforms where innovations may be discovered and from which value may be appropriated. The world hungers for growth and one of the most important vehicles for growth is innovation. In light of the new digital platforms from which data-driven innovation can be extracted, major parts of analogue workflows will be substituted with digital workflows. Data-driven innovation and digital innovation workflows are here to stay. Are you?
Using Marxist critique, this book explores manifestations of Artificial Intelligence (AI) in Higher Education and demonstrates how it contributes to the functioning and existence of the capitalist university. Challenging the idea that AI is a break from previous capitalist technologies, the book offers nuanced examination of the impacts of AI on the control and regulation of academic work and labour, on digital learning and remote teaching, and on the value of learning and knowledge. Applying a Marxist perspective, Preston argues that commodity fetishism, surveillance, and increasing productivity ushered in by the growth of AI, further alienates and exploits academic labour and commodifies learning and research. The text puts forward a solid theoretical framework and methodology for thinking about AI to inform critical and revolutionary pedagogies. Offering an impactful and timely analysis, this book provides a critical engagement and application of key Marxist concepts in the study of AI's role in Higher Education. It will be of interest to those working or researching in Higher Education.
Artificial Intelligence and Machine Learning in Business Management The focus of this book is to introduce artificial intelligence (AI) and machine learning (ML) technologies into the context of business management. The book gives insights into the implementation and impact of AI and ML to business leaders, managers, technology developers, and implementers. With the maturing use of AI or ML in the field of business intelligence, this book examines several projects with innovative uses of AI beyond data organization and access. It follows the Predictive Modeling Toolkit for providing new insight on how to use improved AI tools in the field of business. It explores cultural heritage values and risk assessments for mitigation and conservation and discusses on-shore and off-shore technological capabilities with spatial tools for addressing marketing and retail strategies, and insurance and healthcare systems. Taking a multidisciplinary approach for using AI, this book provides a single comprehensive reference resource for undergraduate, graduate, business professionals, and related disciplines.
In recent years, the fast-paced development of social information and networks has led to the explosive growth of data. A variety of big data have emerged, encouraging researchers to make business decisions by analysing this data. However, many challenges remain, especially concerning data security and privacy. Big data security and privacy threats permeate every link of the big data industry chain, such as data production, collection, processing, and sharing, and the causes of risk are complex and interwoven. Blockchain technology has been highly praised and recognised for its decentralised infrastructure, anonymity, security, and other characteristics, and it will change the way we access and share information. In this book, the author demonstrates how blockchain technology can overcome some limitations in big data technology and can promote the development of big data while also helping to overcome security and privacy challenges. The author investigates research into and the application of blockchain technology in the field of big data and assesses the attendant advantages and challenges while discussing the possible future directions of the convergence of blockchain and big data. After mastering concepts and technologies introduced in this work, readers will be able to understand the technical evolution, similarities, and differences between blockchain and big data technology, allowing them to further apply it in their development and research. Author: Shaoliang Peng is the Executive Director and Professor of the College of Computer Science and Electronic Engineering, National Supercomputing Centre of Hunan University, Changsha, China. His research interests are high-performance computing, bioinformatics, big data, AI, and blockchain.
* The first real AI in project management book on the market published by a respected press * Provides behind-the-scenes insights on what technology providers are planning for project managers * Explores how AI will reinvent project, programme, and portfolio management, allowing project managers to get back to focusing on people
Explores basic and high-level concepts, thus serving as a manual for those in the industry while also helping beginners to understand both basic and advanced aspects Based on the latest technologies, covering the major challenges, issues, and advances of big data and data analytics in green computing Covers intelligent data management and automated systems through big data and data analytics Presents the use of machine learning using big data Provides advanced system implementation for smart cities
This book offers a thorough review of research on intelligent
communication systems, focusing on the applications of artificial
intelligence to telecommunications that help realize user-friendly
interfaces.
1. Provides cutting edge GIS visualization, spatial temporal pattern, and hot spot tracking applications used for predictive modeling of COVID-19. 2. Includes real world case studies with broad geographic scope that reflect COVID-19 trends in cases, deaths, and vaccinations. 3. Provides lifestyle segmentation analysis on the risk of transmission of COVID-19 and spatial patterns of vaccination hesitancy 4. Highlights real world issues brought to light with the help of GIS, such as social discrimination, inequalities in women’s access to mental health care, and analyzes the risk of transmission due to vaccination hesitancy. 5. Shows the use of GIS and spatial analysis at pandemic mapping, management, and control from masking and social distancing to testing site locations accounting for at-risk and vulnerable populations. 6. Discusses facilitating policy making with GIS. |
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