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Research Exhibition in Mathematics and Computer Sciences (REMACS 5.0)
The abstracts in this book cover a wide range of topics, including algebra, analysis, logic, computer architecture, algorithms, artificial intelligence, machine learning, computer network, netcentric computing and many more. The work presented here is both theoretical and practical, and has the potential to impact many areas of society, from finance and healthcare to education and security.
The Digital Collection of Extended Abstracts from Research Exhibition in Mathematics and Computer Sciences (REMACS 6.0)
The objective of this publication is to highlight the extensive range and profundity of research across these intimately connected disciplines. The intersection of Mathematics and Computer Science continues to be a dynamic area of exploration, witnessing remarkable progress and innovation over recent years. In an era dominated by technological breakthroughs and an ever-growing reliance on data-centric methodologies, researchers within these domains are relentlessly pursuing novel theories, algorithms, and models aimed at addressing some of the most challenging and pertinent issues of our contemporary society. This publication stands as a tribute to their unwavering commitment and scholarly rigor.
Charting a Sustainable Future of ASEAN in Business and Social Sciences
This volume showcases selected conference papers addressing the sustainable future of ASEAN from the perspectives of business and social science disciplines. In addressing the 17 Sustainable Developments Goals (SDGs) envisioned by the United Nations in the domains of environment, health and well-being, posing potential means of reducing inequalities globally, the authors target specific issues and challenges confronting the fast-growing region of ASEAN and present suggestions for co-operation and commitment from governments, non-governmental organisations (NGOs) and society at large, in line with the ASEAN Vision 2020. Papers are selected from the 3rd International Conference on the Future o...
Ccsme 2015 Proceedings
Colloquium in Computer & Mathematical Sciences Education 2015 (CCMSE 2015) is an initiative from the Faculty of Computer & Mathematical Sciences, UiTM Perlis to foster a platform for discussing issues related to Teaching and Learning approach within the field of Computer Sciences, System Sciences, Information Technology, Computer Networks, Mathematics and Statistics.
New Approaches to Data Analytics and Internet of Things Through Digital Twin
Even though many data analytics tools have been developed in the past years, their usage in the field of cyber twin warrants new approaches that consider various aspects including unified data representation, zero-day attack detection, data sharing across threat detection systems, real-time analysis, sampling, dimensionality reduction, resource-constrained data processing, and time series analysis for anomaly detection. Further study is required to fully understand the opportunities, benefits, and difficulties of data analytics and the internet of things in today’s modern world. New Approaches to Data Analytics and Internet of Things Through Digital Twin considers how data analytics and the internet of things can be used successfully within the field of digital twin as well as the potential future directions of these technologies. Covering key topics such as edge networks, deep learning, intelligent data analytics, and knowledge discovery, this reference work is ideal for computer scientists, industry professionals, researchers, scholars, practitioners, academicians, instructors, and students.
MANUAL PENGGUNA: Sistem e-ZAKAT Unit Zakat, Sedekah dan Wakaf (ZAWAF)
This is the user manual for the e-Zakat system developed for Unit Zakat, Sedekah dan Wakaf (ZAWAF) Universiti Teknologi MARA Cawangan Perlis
Informal Digital Learning of English
In today’s digital era, increasing numbers of youth around the world learn English outside classrooms, frequently with the use of technology. This timely book brings together research and theory on the increasingly common phenomenon of Informal Digital Learning of English (IDLE) among students of all ages and across a wide range of contexts globally. By examining the positive impact of IDLE on students’ reading, writing, listening, and speaking abilities, as well as the unique challenges that result, Lee synthesizes research in one accessible and comprehensive volume in this rapidly developing domain. This book addresses key concepts, including Computer Assisted Language Learning, the impact on standardized assessment, and the role of classroom learning. Lee offers empirically tested activities, pedagogical recommendations, and lesson plans to engage ESL/EFL students. The research overview and practical offerings make this an ideal text for courses in TESOL on online education, language teaching online, digital learning, community and language, and applied linguistics.
Explainable Fuzzy Systems
The importance of Trustworthy and Explainable Artificial Intelligence (XAI) is recognized in academia, industry and society. This book introduces tools for dealing with imprecision and uncertainty in XAI applications where explanations are demanded, mainly in natural language. Design of Explainable Fuzzy Systems (EXFS) is rooted in Interpretable Fuzzy Systems, which are thoroughly covered in the book. The idea of interpretability in fuzzy systems, which is grounded on mathematical constraints and assessment functions, is firstly introduced. Then, design methodologies are described. Finally, the book shows with practical examples how to design EXFS from interpretable fuzzy systems and natural language generation. This approach is supported by open source software. The book is intended for researchers, students and practitioners who wish to explore EXFS from theoretical and practical viewpoints. The breadth of coverage will inspire novel applications and scientific advancements.
Feature Extraction, Construction and Selection
There is broad interest in feature extraction, construction, and selection among practitioners from statistics, pattern recognition, and data mining to machine learning. Data preprocessing is an essential step in the knowledge discovery process for real-world applications. This book compiles contributions from many leading and active researchers in this growing field and paints a picture of the state-of-art techniques that can boost the capabilities of many existing data mining tools. The objective of this collection is to increase the awareness of the data mining community about the research of feature extraction, construction and selection, which are currently conducted mainly in isolation...
