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Doppler Applications in LEO Satellite Communication Systems develops and presents an important class of techniques useful in the construction of little Low Earth Orbit (LEO) satellite communication systems. It centers on the very significant Doppler shift that attends communications through a LEO satellite and shows how this phenomenon can be exploited for an unexpected benefit. The techniques taught in the book are expected to be particularly attractive to system engineers because ground-based transceivers must generally compensate for the large Doppler component and therefore the necessary receiver processing loops are often already in place and expensed. This volume starts with a recounting of the characteristics of a LEO satellite and its orbit. The 2nd chapter addresses the LEO orbital geometry and reviews the Doppler effect attending LEO communications. Chapter three is focused on the important task of estimating the Doppler at a ground terminal. Appropriate signal processing algorithms are reviewed. Chapter four is concerned with predicting LEO satellite visibility. Chapters five and six are, respectively, devoted to the use of the significant LEO Doppler as an aid in a new traffic flow control protocol and as an aid for effecting communications power control. The last chapter describes MATLAB® based analysis. Doppler Applications in LEO Satellite Communication Systems provides a thorough review of the LEO Doppler phenomenon.

Artificial satellites in telecommunication. --- Doppler effect. --- Signal processing. --- Computer engineering. --- Electrical Engineering. --- Signal, Image and Speech Processing. --- Electrical engineering. --- Image processing. --- Speech processing systems. --- Computational linguistics --- Electronic systems --- Information theory --- Modulation theory --- Oral communication --- Speech --- Telecommunication --- Singing voice synthesizers --- Pictorial data processing --- Picture processing --- Processing, Image --- Imaging systems --- Optical data processing --- Processing, Signal --- Information measurement --- Signal theory (Telecommunication) --- Electric engineering --- Engineering --- Doppler shift --- Collision broadening --- Frequencies of oscillating systems --- Light --- Radiation --- Red shift --- Sound-waves --- Spectral line broadening --- Waves --- Communication satellites --- Communications-relay satellites --- Communications satellites --- Global satellite communications systems --- Satellite communication systems --- Telecommunication satellites --- Telecommunications satellites --- Telstar satellites

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This book comprehensively discusses nature-inspired algorithms, deep learning methods, applications of mathematical programming and artificial intelligence techniques. It will further cover important topic such as linking green supply chain management practices with competitiveness, industry 4.0 and social responsibility.

Artificial intelligence --- Decision making --- Industrial applications. --- Data processing.

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This book addresses the different problems, practices, challenges and opportunities in sustainable resource management with the help of decision-making techniques to showcase the relevance of computational modelling approaches in sustainable management and Industry 4.0. It aims to address the inherent complexity of managing ecosystems, particularly with respect to involvement of multi-stakeholders, lack of information and uncertainties. Critical analyses are made to point out the need for, and propose a call to, a new way of thinking about sustainable resource management. This book will be useful for academicians, researchers, and industrialists in the field of industrial and production engineering.

Methodology of economics --- Engineering sciences. Technology --- Production management --- Business management --- Business economics --- financieel management --- productie --- ingenieurswetenschappen

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This study investigates the application of Decision-Focused Learning (DFL) in addressing Vehicle Routing Problems (VRPs) with unknown edge costs. We emphasize scalability and computational efficiency, introducing an end-to-end pipeline that mitigates the computational challenges posed by combinatorial solvers during training. Our approach seamlessly integrates heuristic and approximate solvers, enhancing both scalability and training efficiency. We delve into the capacitated VRP, contrasting the traditional two-stage cost prediction approach with our methodology. Using synthetic data, the proposed pipeline is applied to problem instances with up to 160 nodes, or 25,440 directed edges, and we introduce a model tailored for edge-specific features. Our empirical results underscore the robustness and viability of DFL in tackling such problems, highlighting its potential for real-world applications in logistics and transportation, among others. This research not only offers valuable and practical insights but also paves the way for future explorations in the domains of stochastic vehicle routing and combinatorial optimization.