This book constitutes the refereed proceedings of the 12th International ICT Innovations Conference, ICT Innovations 2020, held in Skopje, North Macedonia, in September 2020. The 12 full papers and 6 short papers presented were carefully reviewed and selected from 60 submissions. The focal point of the volume is machine learning and applications in spheres of business, science and technology.

This book gathers selected papers presented at the International Conference on Innovations in Information and Communication Technologies (ICI2CT 2020), held at National University of Singapore, Singapore, during 18–19 December 2020. It presents the works on the intersection of the Computer Science and Communication Engineering. Topics covered in the book include communications engineering, Internet and web technology, computer and information science, artificial intelligence, data science and management, and ICT applications.

Computational intelligence (CI) refers to the ability of computers to accomplish tasks that are normally completed by intelligent beings such as humans and animals. Artificial intelligent systems offer great improvement in healthcare systems by providing more intelligent and convenient solutions and services assisted by machine learning, wireless communications, data analytics, cognitive computing, and mobile computing. Modern health treatments are faced with the challenge of acquiring, analysing, and applying the large amount of knowledge necessary to solve complex problems. AI techniques are being effectively used in the field of healthcare systems by extracting the useful information from the vast amounts of data by applying human expertise and CI methods, such as fuzzy models, artificial neural networks, evolutionary algorithms, and probabilistic methods which have recently emerged as promising tools for the development and application of intelligent systems in healthcare practice. This book starts with the fundamentals of computer intelligence and the techniques and procedures associated with them. Contained in the book are state-of-the-art CI methods and other allied techniques used in healthcare systems as well as advances in different CI methods that confront the problem of effective data analysis and storage faced by healthcare institutions. The objective of this book is to provide the latest research related to the healthcare sector to researchers and engineers with a platform encompassing state-of-the-art innovations, research and design, and the implementation of methodologies.

This book features original research and recent advances in ICT fields related to sustainable development. Based the International Conference on Networks, Intelligent systems, Computing & Environmental Informatics for Sustainable Development, held in Marrakech in April 2020, it features peer-reviewed chapters authored by prominent researchers from around the globe. As such it is an invaluable resource for courses in computer science, electrical engineering and urban sciences for sustainable development. This book covered topics including • Green Networks • Artificial Intelligence for Sustainability• Environment Informatics• Computing Technologies

This book presents recent advancements in research, a review of new methods and techniques, and applications in decision support systems (DSS) with Machine Learning and Probabilistic Graphical Models, which are very effective techniques in gaining knowledge from Big Data and in interpreting decisions. It explores Bayesian network learning, Control Chart, Reinforcement Learning for multicriteria DSS, Anomaly Detection in Smart Manufacturing with Federated Learning, DSS in healthcare, DSS for supply chain management, etc. Researchers and practitioners alike will benefit from this book to enhance the understanding of machine learning, Probabilistic Graphical Models, and their uses in DSS in the context of decision making with uncertainty. The real-world case studies in various fields with guidance and recommendations for the practical applications of these studies are introduced in each chapter.

This book constitutes the proceedings of the 6th International Conference on Technologies and Innovation, CITI 2020, held in Guayaquil, Ecuador, in November-December 2020. The 16 full papers presented in this volume were carefully reviewed and selected from 41 submissions. They are organized in topical sections named: semantic technologies and machine learning; ICT for agronomy and environment; mobile and collaborative technologies.

​ This book focuses on new perspectives and applications of data-driven innovation technologies, applied artificial intelligence, applied machine learning and deep learning, data science, and topics related to transforming data into value. It includes theory and use cases to help readers understand the basics of data-driven innovation and to highlight the applicability of the technologies. It emphasizes how the data lifecycle is applied in current technologies in different business domains and industries, such as advanced materials, healthcare and medicine, resource optimization, control and automation, among others. This book is useful for anyone interested in data-driven innovation for smart technologies, as well as those curious in implementing cutting-edge technologies to solve impactful artificial intelligence, data science, and related information technology and communication problems.

This book provides glimpses into contemporary research in information systems & technology, learning, artificial intelligence (AI), machine learning, and security and how it applies to the real world, but the ideas presented also span the domains of telehealth, computer vision, the role and use of mobile devices, brain–computer interfaces, virtual reality, language and image processing and big data analytics and applications. Great research arises from asking pertinent research questions. This book reveals some of the authors’ “beautiful questions” and how they develop the subsequent “what if” and “how” questions, offering readers food for thought and whetting their appetite for further research by the same authors.

This book presents the concept of cryptcoding which arises from the need to obtain secure and accurate transmission. Therefore, it is necessary to improve constantly existing and develop new algorithms that will ensure accurate and secure data transfer. This leads to the intensive development of coding theory and cryptography as scientific fields which solve these problems. To ensure efficient and secure data transmission at the same time, the concept of cryptcoding is developed such that the coding and encryption processes are merged into one process. Cryptcodes provide correction of a certain number of errors in the transmitted message and data confidentiality, using only one algorithm. The main research in this field is to define new algorithms for coding that detects and corrects errors, random codes, stream ciphers, block ciphers, pseudo-random generators, hash functions, etc. This monograph examines an application of quasigroups for designing error-correcting cryptcodes, called Random Codes Based on Quasigroups (RCBQ ). These codes are a combination of cryptographic algorithms and error-correcting codes and depend on several parameters. Some modifications (new coding/decoding algorithms) of RCBQ for improving their performances for transmission ordinary messages, images, and audio files trough a binary-symmetric channel, Gaussian channel, and burst channels are considered. Also, authors propose and analyze filter for visually enhance of the decoded images and improving the quality of decoded audio files.