Handbook Of Research On Ai Methods And Applications In Computer Engineering
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Artificial Intelligence Methods and Applications in Computer Engineering by Sanaa Kaddoura Pdf
"Since artificial intelligence (AI) is a branch of computer science that focuses on assisting machines in finding human-like answers to complex problems, the goal of this book is to show how today's computer engineers and scientists can use artificial intelligence in real-world applications"--
Handbook of Research on AI Methods and Applications in Computer Engineering by Kaddoura, Sanaa Pdf
The development of artificial intelligence (AI) involves the creation of computer systems that can do activities that would ordinarily require human intelligence, such as visual perception, speech recognition, decision making, and language translation. Through increasingly complex programming approaches, it has been transforming and advancing the discipline of computer science. The Handbook of Research on AI Methods and Applications in Computer Engineering illuminates how todays computer engineers and scientists can use AI in real-world applications. It focuses on a few current and emergent AI applications, allowing a more in-depth discussion of each topic. Covering topics such as biomedical research applications, navigation systems, and search engines, this premier reference source is an excellent resource for computer scientists, computer engineers, IT managers, students and educators of higher education, librarians, researchers, and academicians.
Handbook of Research on Machine Learning Applications and Trends: Algorithms, Methods, and Techniques by Olivas, Emilio Soria,Guerrero, Jos David Mart¡n,Martinez-Sober, Marcelino,Magdalena-Benedito, Jose Rafael,Serrano L¢pez, Antonio Jos Pdf
"This book investiges machine learning (ML), one of the most fruitful fields of current research, both in the proposal of new techniques and theoretic algorithms and in their application to real-life problems"--Provided by publisher.
Handbook of Research on AI and Knowledge Engineering for Real-Time Business Intelligence by Hiran, Kamal Kant,Hemachandran, K.,Pise, Anil,Rabi, B. Justus Pdf
Artificial intelligence (AI) is influencing the future of almost every sector and human being. AI has been the primary driving force behind emerging technologies such as big data, blockchain, robots, and the internet of things (IoT), and it will continue to be a technological innovator for the foreseeable future. New algorithms in AI are changing business processes and deploying AI-based applications in various sectors. The Handbook of Research on AI and Knowledge Engineering for Real-Time Business Intelligence is a comprehensive reference that presents cases and best practices of AI and knowledge engineering applications on business intelligence. Covering topics such as deep learning methods, face recognition, and sentiment analysis, this major reference work is a dynamic resource for business leaders and executives, IT managers, AI scientists, students and educators of higher education, librarians, researchers, and academicians.
Handbook of Research on Artificial Intelligence Techniques and Algorithms by Vasant, Pandian Pdf
For decades, optimization methods such as Fuzzy Logic, Artificial Neural Networks, Firefly, Simulated annealing, and Tabu search, have been capable of handling and tackling a wide range of real-world application problems in society and nature. Analysts have turned to these problem-solving techniques in the event during natural disasters and chaotic systems research. The Handbook of Research on Artificial Intelligence Techniques and Algorithms highlights the cutting edge developments in this promising research area. This premier reference work applies Meta-heuristics Optimization (MO) Techniques to real world problems in a variety of fields including business, logistics, computer science, engineering, and government. This work is particularly relevant to researchers, scientists, decision-makers, managers, and practitioners.
Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry by Chkoniya, Valentina Pdf
The contemporary world lives on the data produced at an unprecedented speed through social networks and the internet of things (IoT). Data has been called the new global currency, and its rise is transforming entire industries, providing a wealth of opportunities. Applied data science research is necessary to derive useful information from big data for the effective and efficient utilization to solve real-world problems. A broad analytical set allied with strong business logic is fundamental in today’s corporations. Organizations work to obtain competitive advantage by analyzing the data produced within and outside their organizational limits to support their decision-making processes. This book aims to provide an overview of the concepts, tools, and techniques behind the fields of data science and artificial intelligence (AI) applied to business and industries. The Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry discusses all stages of data science to AI and their application to real problems across industries—from science and engineering to academia and commerce. This book brings together practice and science to build successful data solutions, showing how to uncover hidden patterns and leverage them to improve all aspects of business performance by making sense of data from both web and offline environments. Covering topics including applied AI, consumer behavior analytics, and machine learning, this text is essential for data scientists, IT specialists, managers, executives, software and computer engineers, researchers, practitioners, academicians, and students.
Handbook of Research on Applied Artificial Intelligence and Robotics for Government Processes by Valle-Cruz, David,Plata-Cesar, Nely,González-Ruíz, Jacobo Leonardo Pdf
Artificial intelligence (AI) and robotics have boomed in the 21st century. These emerging and disruptive technologies are immersed in our lives, from apps in mobile devices, the purchases we make on the internet streaming platforms, and even court decisions and predictive policing. Together with science and certain needs, relevant implementations of AI and robotics arise, related to its transparency, resulting in biases, the kinds of applications that can be implemented, and the degree of workforce replacement in decision-making assistance. It is essential to analyze the widely used AI techniques, the application of these technologies in different sectors, the implications of AI and robotics on society and welfare, and more. The Handbook of Research on Applied Artificial Intelligence and Robotics for Government Processes presents state-of-the-art research on AI and robotics in different fields of knowledge, its benefits, applications, and implications. It features chapters containing theoretical and practical research that analyzes the transparency and expandability of AI in different fields, as well as the analysis of unexpected results, biases, and cases of discrimination. Covering topics such as criminal intelligence, artificial intelligence-based chatbots, and gender violence, this major reference work is an excellent resource for government officials, practitioners in the public sector, business administrators and managers, IT professionals, law enforcement, federal agencies, students and faculty of higher education, researchers, and academicians.
Innovations in Digital Instruction Through Virtual Environments by DeHart, Jason D. Pdf
The implementation of virtual environments in education has been rapidly increasing in frequency after the COVID-19 pandemic. As these technologies rise in popularity, it is essential to understand the roles digital technologies play in fostering connections and learning, the affordances of digital texts and spaces for virtual classroom experiences, the difficulties educators have faced and how these practices have been crafted to meet these challenges, and more. Innovations in Digital Instruction Through Virtual Environments advances knowledge about the pedagogical decisions and lived experiences of researchers and educators both before and after the COVID-19 pandemic. It features research from those who have worked to sustain and develop digital/media pedagogical practices. Covering topics such as active learning environments, emotional labor, and textual engagements, this premier reference source is an excellent resource for educators and administrators of both K-12 and higher education, pre-service teachers, teacher educators, librarians, researchers, and academicians.
Industrial Applications of Big Data, AI, and Blockchain by El Samad, Mahmoud,Nassreddine, Ghalia,El-Chaarani, Hani,El Nemar, Sam Pdf
Blockchain has become the cornerstone of technologies, supported by others including Big Data and Artificial Intelligence (AI). Originating from cryptocurrency, it transcends boundaries, finding resonance in finance, healthcare, e-governance, and beyond. While blockchain relies on a peer-to-peer approach, enabling nodes to collaborate without the shackles of a central authority, appropriate monitoring and updating of these technologies is a constant necessity. This is especially true for healthcare data systems, where data privacy and security concerns, especially with sensitive health information are paramount. Threads of automation in artificial intelligence (AI) weave through sectors such as business, finance, healthcare, marketing, and governance. Industrial Applications of Big Data, AI, and Blockchain delves into the pulsating realms of big data, AI, and blockchain. From natural language processing's eloquent interpretation of human language to the prowess of AI algorithms in predictive tasks, this book explores how AI enhances decision-making accuracy, catalyzing a paradigm shift in diverse industries. This book is ideal for researchers, business visionaries, tech enthusiasts, and curious minds eager to fathom the transformative potential of these technologies.
Artificial Intelligence (AI) by S. Kanimozhi Suguna,M. Dhivya,Sara Paiva Pdf
Addresses the complete functional framework workflow in Artificial Intelligence technology Explores basic and high-level concepts Based on the latest technologies covering the major challenges, issues, and advances in AI Discusses intelligent and automated system through AI and its implications to the real-world Presents data acquisition and case studies related to data-intensive technologies
The Handbook of Artificial Intelligence by Avron Barr,Edward A. Feigenbaum Pdf
The Handbook of Artificial Intelligence, Volume II focuses on the improvements in artificial intelligence (AI) and its increasing applications, including programming languages, intelligent CAI systems, and the employment of AI in medicine, science, and education. The book first elaborates on programming languages for AI research and applications-oriented AI research. Discussions cover scientific applications, teiresias, applications in chemistry, dependencies and assumptions, AI programming-language features, and LISP. The manuscript then examines applications-oriented AI research in medicine and education, including ICAI systems design, intelligent CAI systems, medical systems, and other applications of AI to education. The manuscript explores automatic programming, as well as the methods of program specification, basic approaches, and automatic programming systems. The book is a valuable source of data for computer science experts and researchers interested in conducting further research in artificial intelligence.
Energy Systems Design for Low-Power Computing by Gatti, Rathishchandra Ramachandra,Singh, Chandra,P., Srividya,Bhat, Sandeep Pdf
With the advancement in computing technologies, the need for power is also increasing. Approximately 3% of the total power consumption is spent by data centers and computing devices. This percentage will rise when more internet of things (IoT) devices are connected to the web. The handling of this data requires immense power. Energy Systems Design for Low-Power Computing disseminates the current research and the state-of-the-art technologies, topologies, standards, and techniques for the deployment of energy intelligence in edge computing, distributed computing, and centralized computing infrastructure. Covering topics such as electronic cooling, stochastic data analysis, and energy consumption, this premier reference source is an excellent resource for data center designers, VLSI designers, network developers, students and teachers of higher education, librarians, researchers, and academicians.
Technology Management and Its Social Impact on Education by Lai, P.C. Pdf
Technology Management and Its Social Impact on Education, edited by PC Lai from the University of Malaya, Malaysia, is an essential resource for anyone interested in understanding the transformative role of technology in education and its impact on society. The book covers a broad range of education concepts, strategies, and sectors, including innovation in education, green education, technology management in education, leadership, management & and HR practices, services, and more. It also examines the challenges and opportunities of education value creation, knowledge management, technology transfer, internationalization of education, innovative supply chain, social and economic impact, and social business in the education world. This book provides a forum for the exchange of research ideas and practices and is a reference convergence point for academicians, professionals, managers, and researchers in the entrepreneurship field, including development practitioners. It offers invaluable insights into the transformative role of technology in education and is a must-read for anyone interested in staying at the forefront of education and technology. Whether you are an academician, a practitioner, a researcher, a student, a writer, a blockchain or NFT community member, a corporate manager, a policy maker, or a government official, this book will equip you with the knowledge and skills necessary to navigate the complex relationship between technology, education, and society.
Principles and Theories of Data Mining With RapidMiner by Ramjan, Sarawut,Sunkpho, Jirapon Pdf
The demand for skilled data scientists is rapidly increasing as more organizations recognize the value of data-driven decision- making. Data science, data management, and data mining are all critical components for various types of organizations, including large and small corporations, academic institutions, and government entities. For companies, these components serve to extract insights and value from their data, empowering them to make evidence-driven decisions and gain a competitive advantage by discovering patterns and trends and avoiding costly mistakes. Academic institutions utilize these tools to analyze large datasets and gain insights into various scientific fields of study, including genetic data, climate data, financial data, and in the social sciences they are used to analyze survey data, behavioral data, and public opinion data. Governments use data science to analyze data that can inform policy decisions, such as identifying areas with high crime rates, determining which regions need infrastructure development, and predicting disease outbreaks. However, individuals who are not data science experts, but are experts within their own fields, may need to apply their experience to the data they must manage, but still struggle to expand their knowledge of how to use data mining tools such as RapidMiner software. Principles and Theories of Data Mining With RapidMiner is a comprehensive guide for students and individuals interested in experimenting with data mining using RapidMiner software. This book takes a practical approach to learning through the RapidMiner tool, with exercises and case studies that demonstrate how to apply data mining techniques to real-world scenarios. Readers will learn essential concepts related to data mining, such as supervised learning, unsupervised learning, association rule mining, categorical data, continuous data, and data quality. Additionally, readers will learn how to apply data mining techniques to popular algorithms, including k-nearest neighbor (K-NN), decision tree, naïve bayes, artificial neural network (ANN), k-means clustering, and probabilistic methods. By the end of the book, readers will have the skills and confidence to use RapidMiner software effectively and efficiently, making it an ideal resource for anyone, whether a student or a professional, who needs to expand their knowledge of data mining with RapidMiner software.
A Guided Tour of Artificial Intelligence Research by Pierre Marquis,Odile Papini,Henri Prade Pdf
The purpose of this book is to provide an overview of AI research, ranging from basic work to interfaces and applications, with as much emphasis on results as on current issues. It is aimed at an audience of master students and Ph.D. students, and can be of interest as well for researchers and engineers who want to know more about AI. The book is split into three volumes: - the first volume brings together twenty-three chapters dealing with the foundations of knowledge representation and the formalization of reasoning and learning (Volume 1. Knowledge representation, reasoning and learning) - the second volume offers a view of AI, in fourteen chapters, from the side of the algorithms (Volume 2. AI Algorithms) - the third volume, composed of sixteen chapters, describes the main interfaces and applications of AI (Volume 3. Interfaces and applications of AI). This third volume is dedicated to the interfaces of AI with various fields, with which strong links exist either at the methodological or at the applicative levels. The foreword of this volume reminds us that AI was born for a large part from cybernetics. Chapters are devoted to disciplines that are historically sisters of AI: natural language processing, pattern recognition and computer vision, and robotics. Also close and complementary to AI due to their direct links with information are databases, the semantic web, information retrieval and human-computer interaction. All these disciplines are privileged places for applications of AI methods. This is also the case for bioinformatics, biological modeling and computational neurosciences. The developments of AI have also led to a dialogue with theoretical computer science in particular regarding computability and complexity. Besides, AI research and findings have renewed philosophical and epistemological questions, while their cognitive validity raises questions to psychology. The volume also discusses some of the interactions between science and artistic creation in literature and in music. Lastly, an epilogue concludes the three volumes of this Guided Tour of AI Research by providing an overview of what has been achieved by AI, emphasizing AI as a science, and not just as an innovative technology, and trying to dispel some misunderstandings.
