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This volume constitutes the refereed proceedings of the 4th International Conference on Information Systems, Technology and Management, ICISTM 2010, held in Bangkok, Thailand, in March 2010. The 28 revised full papers presented together with 3 keynote lectures, 9 short papers, and 2 tutorial papers were carefully reviewed and selected from 86 submissions. The papers are organized in topical sections on information systems, information technology, information management, and applications.
This is an authoritative introduction to Computing Education research written by over 50 leading researchers from academia and the industry.
This book constitutes the post-conference proceedings of the 5th International Conference on Machine Learning, Optimization, and Data Science, LOD 2019, held in Siena, Italy, in September 2019. The 54 full papers presented were carefully reviewed and selected from 158 submissions. The papers cover topics in the field of machine learning, artificial intelligence, reinforcement learning, computational optimization and data science presenting a substantial array of ideas, technologies, algorithms, methods and applications.
The International Workshop on Hybrid Metaheuristics was established with the aim of providing researchers and scholars with a forum for discussing new ideas and research on metaheuristics and their integration with techniques typical of other ?elds. The papers accepted for the sixth workshop con?rm that such a combination is indeed e?ective and that several research areas can be put together.Slowlybut surely,thisprocesshasbeen promotingproductivedialogue amongresearcherswithdi?erentexpertiseanderodingbarriersbetweenresearch areas. The papers in this volume give a representativesample of current researchin hybrid metaheuristics. It is worth emphasizing that this year, a large number of papers demonstrated how metaheuristics can be integrated with integer linear programmingandotheroperationsresearchtechniques.Constraintprogramming is also featured, which is a notable representative of arti?cial intelligence solving methods. Most of these papers are not only a proof of concept – which can be valuable by itself – but also show that the hybrid techniques presented tackle di?cult and relevant problems. In keeping with the tradition of this workshop, special care was exercised in the review process: out of 22 submissions received, 12 papers were selected on the basis of reviews by the Program Committee members and evaluations by the Program Chairs. Reviews were in great depth: reviewers sought to p- vide authors with constructive suggestions for improvement. Special thanks are extended to the Program Committee members who devoted their time and - fort. Special gratitude is due to Andrea Lodi and Vittorio Maniezzo, who both accepted our invitation to give an overview talk.
Machine learning is able to solve real-time problems. It has several algorithms such as classification, clustering, and more. To learn these essential algorithms, we require tools like Scikit and TensorFlow. Machine Learning Algorithms Using Scikit and TensorFlow Environments assists researchers in learning and implementing these critical algorithms. Covering key topics such as classification, artificial neural networks, prediction, random forest, and regression analysis, this premier reference source is ideal for industry professionals, computer scientists, researchers, academicians, scholars, practitioners, instructors, and students.
In providing a comprehensive overview on how to design and execute effective advocacy strategies for organizations, this book challenges the way communications used to be managed. Instead it proposes and provides tools for multilateral advocacy, where multiple actors and institutions cooperate, as a driver for corporate decisions.
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.