Handbook of Intelligent Computing and Optimization for Sustainable Development. Группа авторов

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Handbook of Intelligent Computing and Optimization for Sustainable Development - Группа авторов

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and servants to humanity and anybody curious about and interested in past, present and future times and lives.

      To all the respected authors of this amazingly high number of valuable 41 chapters, I convey my compliments and gratitude for having shared their care and foresight, enthusiasm and dedication, knowledge and assessment, wisdom and vision with our scientific and applied communities, and with humankind. I express my thanks to the publishing house Wiley-Scrivener Publishing, USA, and to the editors, Dr. Mukhdeep Singh Manshahia (Punjabi University, Patiala. Punjab, India), Dr. Valeriy Kharchenko (Federal Scientific Agroengineering Center VIM, Russia), Dr. Elias Munapo (Department of Statistics & Operations Research, NWUMafikeng Campus, South Africa), Dr. J. Joshua Thomas (UOW Malaysia, KDU Penang University College, Malaysia), and Dr. Pandian Vasant (University Technology Petronas, Malaysia), for having provided, maintained and developed this chance for many experts to make public and popular the best parts of their achievements, contributions, works and even lifework. To all of them I express my thankfulness for having spent so much care to guarantee a premium compendium and monograph of a highly academic, practical and impactful socially significant and paradigm-shifting offer to our world, our times and lives.

      Now, what is left for me is to wish you all a lot of pleasure, interest and joy when browsing through, inquiring deeply, getting inspired and richly benefitting from this enriching handbook. Yes, very much I hope that its blessings will be great for you and us all, personally and societally, and continue to remain with humankind and all of creation.

      Gerhard-Wilhelm Weber Poznan University of Technology, Poznan, Poland Middle East Technical University, Ankara, Turkey

      Preface

      The editors are immensely gratified to introduce this Handbook of Intelligent Computing and Optimization for Sustainable Development, with the intent of compiling information that advances sustainability as a fundamental factor for intelligent computing and optimization.

      Intelligent and smart technologies are at the forefront of technological advances that represent potential transformations in smart living. These technologies and their applications are already rapidly impacting many industries and occupations. With applications in a number of fields such as the Internet of Things (IoT), optimization, renewable energy, manufacturing, agriculture, healthcare and smart cities, research on the developments of artificial intelligence is essential for sustainable development. The recent rise of emerging networking technologies such as 5G networks, social networks, IoT networks, etc., have attracted significant attention from academia as well as industry professionals looking to utilize these technologies for efficient communication purposes. Future citizens of the world will face increasing sustainability issues and need to be better prepared for energy transformation and sustainable future economic development in a smart world. Advances in artificial intelligence (AI) paradigms and smart informatics systems domains highlight the need for systems that aim to improve the quality and security of human life; therefore, this book discusses applications of artificial intelligence in sustainable development.

      Recently, optimization has also received enormous attention along with the rapidly increasing use of communication technology and development of user-friendly software and artificial intelligence. In almost all human activities, there is a desire to deliver the highest possible results with the least amount of effort. Moreover, optimization is a very well-known area with a vast number of applications, from route finding problems to medical treatment, construction, finance, accounting, engineering and maintenance schedules in plants. As far as optimization of real-world problems is concerned, understanding the nature of the problem and grouping it in a proper class may help the designer employ proper techniques which can solve the problem efficiently. Many intelligent optimization techniques can find optimal solutions without the use of objective function and are less prone to local optima.

      This book provides the reader with an integrated understanding of the importance that intelligent computing has in the sustainable development of current societies. It discusses the emerging research exploring the theoretical and practical aspects of successfully implementing new and innovative intelligent techniques in a variety of sectors, including the IoT, manufacturing, optimization and healthcare. In general, the book is intended as a presentation of a wide range of publicly advanced achievements in the field of intelligent computing and optimization, which will be useful for a wide range of readers and will doubtless have a positive impact on a solution to the problem of sustainable development.

      Based on double-blind review processes, the 41 chapters were accepted for publication according to their suitability for the five parts of the book. A brief description of each chapter is given below.

       Part I: Intelligent Computing and Applications

      Chapter 1 proposes a mental workload prediction model using a neural network and the Bernoulli Boltzmann machine. For measuring mental workload, eye movement metrics were considered. The eye metrics were computed from raw eye movement data, which were recorded using an eye tracking device while solving coding problems. The authors found that the Bernoulli Boltzmann machine provides better accuracy in predicting mental workload from eye metrics.

      Chapter 2 discusses the development of an artificial neural network (ANN) using short DNA strands, i.e., oligonucleotides. The short sequences of DNA molecules can be used to code input and output signals and to build the basic architecture of the neuron. The authors also illustrate the design methodology of DNA logic gates and DNA logic circuits. Because of a few drawbacks, viz. immense energy consumption, vast memory requirement and heat dissipation, the traditional computation approaches the limitations of its processing power and design strategy. The aim of the authors is a paradigm shift in the computational world; from silicon to carbon. The design strategies discussed in this chapter are essential for effective development of a practical DNA computer.

      Chapter 3 focuses on a novel framework for detection of garments of interest from the footage of a surveillance camera. The video frames are processed using the GMG background subtraction model to obtain relevant foreground information along with foreground masks. The Mask R-CNN object detection model is used to identify customers and multiple image processing techniques are used to obtain the active garments in these frames. The detected customers are tracked and the OpenPose human pose estimation framework is utilized on them to obtain useful landmarks. The garments of interest are then determined based on the filtration of confidence scores calculated for each active garment. The framework was tested on a CCTV video dataset and was found to be effective despite facing arduous obstacles such as background noise and occlusions.

      Chapter 4 studies matrix algebra and elliptic curve arithmetic computing based on the integration of modular arithmetic and complex number arithmetic. It describes the intelligent computing of nonlinear transformations based on the residue matrices and the elliptic curve arithmetic over complex plane that can be applied in the computer science fields, which deal with cryptographic

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