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Impact and implications of AI methods and tools for the future of education
The congruence of technology such as AI and its use for education can help transform the different pedagogical practices and future of education. Educational organizations like The UNESCO and The World Bank are already calling for research and development-oriented projects, and creation/mobilization of technological initiatives on how to re-imagine education and operationalize the use of digital technologies for its purpose, the "Digitized-Education". Those goals mean or include methodological approaches and wide adoption of the AI-methods in fostering education in the classroom or learning environments. Also noteworthy is the fact that "digitized-education" is now an inevitable and integral element to achieving the global sustainable development goals (SDGs) particularly the SDG4 that promotes quality of education.
Innovations in Bio-Inspired Computing and Applications
This book highlights recent research on bio-inspired computing and its various innovative applications in information and communication technologies. It presents 38 high-quality papers from the 10th International Conference on Innovations in Bio-Inspired Computing and Applications (IBICA 2019) and 9th World Congress on Information and Communication Technologies (WICT 2019), which was held at GIET University, Gunupur, India, on December 16–18, 2019. As a premier conference, IBICA–WICT brings together researchers, engineers and practitioners whose work involves bio-inspired computing, computational intelligence and their applications in information security, real-world contexts, etc. Including contributions by authors from 18 countries, the book offers a valuable reference guide for all researchers, students and practitioners in the fields of Computer Science and Engineering.
Linked Open Data
This book intends to provide the reader with a comprehensive knowledge of the latest developments within the Linked Open Data (LOD) framework and the benefits of supported systems. The book covers the entire spectrum of “Linked Open Data - Applications, Trends and Future Developments” with six chapters. Each of the chapters provides an all-inclusive conceptualization of the LOD concepts, methodological approaches, case studies, and the main applications both in theory and practice. This book is a reference and educational book targeted to data scientists, software developers, semantic web engineers, information system designers, process managers, teachers, and researchers, and general consumers in application of LOD methods within various contexts.
R Programming
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Data-Driven Modelling and Predictive Analytics in Business and Finance
Data-driven and AI-aided applications are next-generation technologies that can be used to visualize and realize intelligent transactions in finance, banking, and business. These transactions will be enabled by powerful data-driven solutions, IoT technologies, AI-aided techniques, data analytics, and visualization tools. To implement these solutions, frameworks will be needed to support human control of intelligent computing and modern business systems. The power and consistency of data-driven competencies are a critical challenge, and so is developing explainable AI (XAI) to make data-driven transactions transparent. Data- Driven Modelling and Predictive Analytics in Business and Finance co...
Social Media and Crowdsourcing
Social media and crowdsourcing are important tools for solving complex problems. The benefit of crowdsourcing is that it leverages the power of human intelligence cost effectively and with less time. Social Media and Crowdsourcing: Application and Analytics examines the concepts of social media and crowdsourcing as well as their analytical aspects. It explores how these technologies contribute to the real world and examines such applications as promoting social good, agriculture, healthcare, tourism, disaster management, education, crime control, and cultural heritage. The book also looks at ethical issues in crowdsourcing and future scenarios and challenges for policy. Highlights of the boo...
Analyzing Data Through Probabilistic Modeling in Statistics
Probabilistic modeling represents a subject arising in many branches of mathematics, economics, and computer science. Such modeling connects pure mathematics with applied sciences. Similarly, data analyzing and statistics are situated on the border between pure mathematics and applied sciences. Therefore, when probabilistic modeling meets statistics, it is a very interesting occasion that has gained much research recently. With the increase of these technologies in life and work, it has become somewhat essential in the workplace to have planning, timetabling, scheduling, decision making, optimization, simulation, data analysis, and risk analysis and process modeling. However, there are still...
TEACHING & LEARNING
THE TEACHING & LEARNING MCQ (MULTIPLE CHOICE QUESTIONS) SERVES AS A VALUABLE RESOURCE FOR INDIVIDUALS AIMING TO DEEPEN THEIR UNDERSTANDING OF VARIOUS COMPETITIVE EXAMS, CLASS TESTS, QUIZ COMPETITIONS, AND SIMILAR ASSESSMENTS. WITH ITS EXTENSIVE COLLECTION OF MCQS, THIS BOOK EMPOWERS YOU TO ASSESS YOUR GRASP OF THE SUBJECT MATTER AND YOUR PROFICIENCY LEVEL. BY ENGAGING WITH THESE MULTIPLE-CHOICE QUESTIONS, YOU CAN IMPROVE YOUR KNOWLEDGE OF THE SUBJECT, IDENTIFY AREAS FOR IMPROVEMENT, AND LAY A SOLID FOUNDATION. DIVE INTO THE TEACHING & LEARNING MCQ TO EXPAND YOUR TEACHING & LEARNING KNOWLEDGE AND EXCEL IN QUIZ COMPETITIONS, ACADEMIC STUDIES, OR PROFESSIONAL ENDEAVORS. THE ANSWERS TO THE QUESTIONS ARE PROVIDED AT THE END OF EACH PAGE, MAKING IT EASY FOR PARTICIPANTS TO VERIFY THEIR ANSWERS AND PREPARE EFFECTIVELY.
Handbook of Research on Engineering, Business, and Healthcare Applications of Data Science and Analytics
Analyzing data sets has continued to be an invaluable application for numerous industries. By combining different algorithms, technologies, and systems used to extract information from data and solve complex problems, various sectors have reached new heights and have changed our world for the better. The Handbook of Research on Engineering, Business, and Healthcare Applications of Data Science and Analytics is a collection of innovative research on the methods and applications of data analytics. While highlighting topics including artificial intelligence, data security, and information systems, this book is ideally designed for researchers, data analysts, data scientists, healthcare administrators, executives, managers, engineers, IT consultants, academicians, and students interested in the potential of data application technologies.
