| Description |
1 online resource (211 p.) |
| Contents |
Cover -- Half Title -- Title Page -- Copyright Page -- Table of Contents -- Preface -- About the Authors -- 1 Introduction -- 1.1 Introduction to Green Energy Harvesting -- 1.2 Energy Resources -- 1.3 Natural Sources -- 1.3.1 Solar Energy -- 1.3.2 Wind Energy -- 1.3.3 Wave Energy -- 1.3.4 Geothermal Energy -- 1.4 Artificial Resources -- 1.4.1 Piezoelectric -- 1.4.2 Thermoelectric -- 1.4.3 Magnetostrictive -- 1.4.4 Magnetoelectric -- 1.5 Summary -- References -- 2 Piezoelectric Figure of Merits -- 2.1 Fundamentals of Piezoelectricity -- 2.1.1 Domain Structure and Domain Wall Motion |
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2.1.2 P-E Hysteresis Loop -- 2.2 Constitutive Relations -- 2.2.1 Piezoelectric Charge Constant (D) and Piezoelectric Voltage Constant (G) -- 2.2.2 Electromechanical Coupling Factor (K) -- 2.2.3 Mechanical Quality Factor (Qm) -- 2.3 Other Material Parameters of Interest -- 2.3.1 Permittivity -- 2.3.2 Power Output -- 2.3.3 Energy Storage Efficiency -- 2.4 Road Map to Achieve Optimum Figures of Merit -- 2.4.1 Constructing Morphotropic Phase Boundaries -- 2.4.2 Introducing Relaxor Behavior: Role of PNRs -- 2.5 Summary -- References -- 3 Materials for Piezoelectric Energy Harvesting -- 3.1 Ceramics |
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3.1.1 Polycrystalline -- 3.1.2 Single Crystal -- 3.1.3 Textured -- 3.1.4 Nano -- 3.1.5 Thin Films -- 3.2 Polymers -- 3.3 Composites -- 3.3.1 0-3 Piezo Composites -- 3.3.2 1-3 Piezo Composites -- 3.3.3 3-3 Piezo Composites -- 3.4 Bio-Inspired -- 3.5 Summary -- References -- 4 Synthesis/Fabrication Techniques of Piezoelectric Materials -- 4.1 Synthesis Techniques -- 4.1.1 Powder Processing -- 4.1.1.1 Solid-State Reaction -- 4.1.1.1.1 One Stage Solid-State Reaction -- 4.1.1.1.2 Two-Stage Solid-State Reaction -- 4.1.1.2 Chemical Synthesis -- 4.1.1.2.1 Sol-Gel -- 4.1.1.2.2 Co-Precipitation |
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4.1.1.2.3 Molten Salt -- 4.1.1.2.4 Hydrothermal -- 4.1.1.2.5 Spray Pyrolysis -- 4.1.1.2.6 Emulsion Synthesis -- 4.1.2 Thin Film Fabrication -- 4.1.2.1 Physical Vapor Deposition -- 4.1.2.1.1 Sputtering -- 4.1.2.1.2 Evaporation -- 4.1.2.2 Chemical Vapor Deposition -- 4.1.2.2.1 Low Pressure CVD -- 4.1.2.2.2 Metal-Organic CVD -- 4.1.2.2.3 Plasma Enhanced CVD -- 4.1.2.3 Chemical Solvent Deposition -- 4.1.2.3.1 Sol-Gel -- 4.1.2.3.2 Electrochemical Reaction -- 4.1.2.3.3 Hydrothermal -- 4.1.2.4 Chemical Melt Deposition (Liquid Phase Epitaxy) -- 4.1.3 Single Crystals -- 4.1.3.1 Melt Growth Techniques |
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4.1.3.1.1 Bridgeman -- 4.1.3.1.2 Czochralski -- 4.3.1.3 Verneuil -- 4.1.3.2 Solution Growth -- 4.1.3.2.1 Hydrothermal -- 4.1.3.2.2 Gel Growth -- 4.1.3.2.3 Low Temperature Crystal Growth -- 4.1.3.2.4 High Temperature Crystal Growth -- 4.1.3.3 Vapor Growth -- 4.1.3.4 Solid State Crystal Growth -- 4.1.4 Composites -- 4.1.4.1 High Temperature Dielectrophoresis Technique -- 4.1.4.2 Injection Molding -- 4.1.4.3 Lost Foam Mold -- 4.1.4.4 Dice and Fill -- 4.2 Summary -- References -- 5 Characterization and Properties of Piezoelectric Materials -- 5.1 Characterization TECHNIQUES -- 5.1.1 X-Ray Diffraction |
| Summary |
This book covers the description of both conventional methods and advanced methods. In conventional methods, visual tracking techniques such as stochastic, deterministic, generative, and discriminative are discussed. The conventional techniques are further explored for multi-stage and collaborative frameworks. In advanced methods, various categories of deep learning-based trackers and correlation filter-based trackers are analyzed. The book also: Discusses potential performance metrics used for comparing the efficiency and effectiveness of various visual tracking methods Elaborates on the salient features of deep learning trackers along with traditional trackers, wherein the handcrafted features are fused to reduce computational complexity Illustrates various categories of correlation filter-based trackers suitable for superior and efficient performance under tedious tracking scenarios Explores the future research directions for visual tracking by analyzing the real-time applications The book comprehensively discusses various deep learning-based tracking architectures along with conventional tracking methods. It covers in-depth analysis of various feature extraction techniques, evaluation metrics and benchmark available for performance evaluation of tracking frameworks. The text is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology |
| Notes |
Description based upon print version of record |
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5.1.2 Density |
| Bibliography |
Includes bibliographical references and index |
| Subject |
Automobiles -- Design and construction.
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Electrical engineering.
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electrical engineering.
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Automobiles -- Design and construction
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Electrical engineering
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| Form |
Electronic book
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| Author |
Rout, Dibyaranjan
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| ISBN |
9781003803843 |
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1003803849 |
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