Dielectric Metamaterials and Metasurfaces in Transformation Optics and Photonics by
Dielectric Metamaterials and Metasurfaces in Transformation Optics and Photonics addresses the complexity of electromagnetic responses from arrays of dielectric resonators, which are often omitted from consideration when using simplified metamaterials concepts. The book's authors present a thorough consideration of dielectric resonances in different environments which is needed to design optical and photonic devices. Dielectric metamaterials and photonic crystals are compared, with their effects analyzed. Design approaches and examples of designs for invisibility cloaks based on artificial media are also included. Current challenge of incorporating artificial materials into transformation optics-based and photonics devices are also covered.
Artificial Intelligence Applications in Electrical Transmission and Distribution Systems Protection by
Provides essential insight on uses of different AI techniques for pattern recognition, classification, prediction and estimation, exclusive to power system protection issues Presents introduction to enhanced electricity system analysis using decision-making tools Covers AI Applications in different protective relaying functions Discusses Issues and challenges in the protection of transmission and distribution systems Includes dedicated chapter on case studies, and applications
Theoretical Foundations of Nanoscale Quantum Devices by
Nanooptics which describes the interaction of light with matter at the nanoscale, is a topic of great fundamental interest to physicists and engineers and allows the direct observation of quantum mechanical phenomena in action. This self-contained and extensively referenced text describes the underlying theory behind nanodevices operating in the quantum regime for use both in advanced courses and as a reference for researchers in physics, chemistry, electrical engineering, and materials science. Presenting an extensive theoretical toolset for design and analysis of nanodevices, the authors demonstrate the art of developing approximate quantum models of real nanodevices. The rudimentary mathematical knowledge required to master the material is carefully introduced, with detailed derivations and frequent worked examples allowing readers to gain a thorough understanding of the material. More advanced applications are gradually introduced alongside analytical approximations and simplifying assumptions often used to make such problems tractable while representative of the observed features.
Electroanalytical Applications of Quantum Dot-Based Biosensors by
Quantum dots (QDs) are hybrid organic/inorganic nanoparticles with novel physical properties. QDs have two components: an inorganic core and an optically active coated shell. Moreover, surface coatings can be applied to QDs to modify the particle as needed for experiments. Hydrophilic coatings prevent leaking of metal cargo from the core, enhancing the solubility in biological contexts and bind molecules, such as receptor-ligands, antibodies, therapeutic, and diagnostic macromolecules for enhanced effects. Their high surface-to-volume ratio allows multiple functional groups to attach onto the surface of the particles at constant surface volume. Silicon-, gallium-, indium-, or germanium-based; cadmium-based; and carbon-based QDs have already been used in many applications, such as imaging probes for the engineering of multifunctional nanodevices. Superior properties of QDs make them an excellent system in technology and biotechnology. This book describes electroanalytical applications of QD-based nanobiosensors, including brief information about the synthesis and characterization of QDs and basics of electroanalytical methods, followed by QDs in electrochemical biomimetic sensors, QDs in microchips, inorganic materials doped QDs, QD-based electrochemical DNA biosensors, electroluminescence for biomarker analysis using aptamer-based QDs, QD-based photoelectrochemical techniques, enzyme-based nanobiosensors using QDs, QD-based electrochemical immunosensors, and QD-modified nanosensors in drug analysis.
Artificial Intelligence and Quantum Computing for Advanced Wireless Networks by
ARTIFICIAL INTELLIGENCE AND QUANTUM COMPUTING FOR ADVANCED WIRELESS NETWORKS A comprehensive presentation of the implementation of artificial intelligence and quantum computing technology in large-scale communication networks Increasingly dense and flexible wireless networks require the use of artificial intelligence (AI) for planning network deployment, optimization, and dynamic control. Machine learning algorithms are now often used to predict traffic and network state in order to reserve resources for smooth communication with high reliability and low latency. In Artificial Intelligence and Quantum Computing for Advanced Wireless Networks, the authors deliver a practical and timely review of AI-based learning algorithms, with several case studies in both Python and R. The book discusses the game-theory-based learning algorithms used in decision making, along with various specific applications in wireless networks, like channel, network state, and traffic prediction. Additional chapters include Fundamentals of ML, Artificial Neural Networks (NN), Explainable and Graph NN, Learning Equilibria and Games, AI Algorithms in Networks, Fundamentals of Quantum Communications, Quantum Channel, Information Theory and Error Correction, Quantum Optimization Theory, and Quantum Internet, to name a few. The authors offer readers an intuitive and accessible path from basic topics on machine learning through advanced concepts and techniques in quantum networks. Readers will benefit from: A thorough introduction to the fundamentals of machine learning algorithms, including linear and logistic regression, decision trees, random forests, bagging, boosting, and support vector machines An exploration of artificial neural networks, including multilayer neural networks, training and backpropagation, FIR architecture spatial-temporal representations, quantum ML, quantum information theory, fundamentals of quantum internet, and more Discussions of explainable neural networks and XAI Examinations of graph neural networks, including learning algorithms and linear and nonlinear GNNs in both classical and quantum computing technology Perfect for network engineers, researchers, and graduate and masters students in computer science and electrical engineering, Artificial Intelligence and Quantum Computing for Advanced Wireless Networks is also an indispensable resource for IT support staff, along with policymakers and regulators who work in technology.
本學科指引提供您精密工程研究領域的相關資源，整合館藏紙本、電子資源、期刊資源、學位論文、以及校外的網路資源等，主題式的引介各種資源使用。
若需更進一步的協助，請與學科館員聯絡。
本館館藏資源以配合校內師生教學研究之需要為主，舉凡相關之圖書、期刊、多媒體資料、電子資源等均予蒐藏。
圖書/期刊 Books & Journals
電子資源 Electronic Resources
