The IoT topology defines the way various components communicate with each other within a network. Topologies can vary greatly in terms of security, power consumption, cost, and complexity. Optimizing the IoT topology for different applications and requirements can help to boost the network’s performance and save costs. More importantly, optimizing the topology robustness can ensure security and prevent network failure at the foundation level. In this context, this book examines the optimization schemes for topology robustness in the IoT, helping readers to construct a robustness optimization framework, from self-organizing to intelligent networking. The book provides the relevant theoretical framework and the latest empirical research on robustness optimization of IoT topology. Starting with the self-organization of networks, it gradually moves to genetic evolution. It also discusses the application of neural networks and reinforcement learning to endow the node with self-learning ability to allow intelligent networking. This book is intended for students, practitioners, industry professionals, and researchers who are eager to comprehend the vulnerabilities of IoT topology. It helps them to master the research framework for IoT topology robustness optimization and to build more efficient and reliable IoT topologies in their industry.
Li Yifan, with the Nine Yin Meridians on his body, was able to reach the world with just his hands alone. He had stolen the hearts of countless young girls, and facing the women around him, Li Yifan chuckled and waved his hand, "Come ... Let this Divine Doctor treat your illnesses.
Cognitive linguists believe that metaphors are prevalent in human thought, while metaphorical structures are reflected at the linguistic level. Therefore, analysing extensive language data can aid in revealing the metaphorical mappings of embodied experience with the senses of vision, hearing, smell, taste, touch, and temperature. This volume seeks to discover the similarities and differences between the metaphorical systems of the English and Chinese languages. Adopting a comparative view, the authors examine the semantic extensions of perception words in English and Chinese, in order to reveal the metaphorical scope of each sense and the metaphorical system behind it. They argue that the metaphorical systems of the senses not only help us understand and use conventionalised metaphorical expressions but also allow us to create novel expressions. The findings also unveil how abstract concepts are constructed via cognitive mechanisms, such as image schema and metaphor. This title is a useful reference for scholars and students who are interested in cognitive linguistics, comparative linguistics, and the philosophy of language.
Metamaterials have attracted enormous interests from both physics and engineering communities in the past 20 years, owing to their powerful ability in manipulating electromagnetic waves. However, the functionalities of traditional metamaterials are fixed at the time of fabrication. To control the EM waves dynamically, active components are introduced to the meta-atoms, yielding active metamaterials. Recently, a special kind of active metamaterials, digital coding and programmable metamaterials, are proposed, which can achieve dynamically controllable functionalities using field programmable gate array (FPGA). Most importantly, the digital coding representations of metamaterials set up a bridge between the digital world and physical world, and allow metamaterials to process digital information directly, leading to information metamaterials. In this Element, we review the evolution of information metamaterials, mainly focusing on their basic concepts, design principles, fabrication techniques, experimental measurement and potential applications. Future developments of information metamaterials are also envisioned.
Metamaterials, including their two-dimensional counterparts, are composed of subwavelength-scale artificial particles. These materials have novel electromagnetic properties, and can be artificially tailored for various applications. Based on metamaterials and metasurfaces, many abnormal physical phenomena have been realized, such as negative refraction, invisible cloaking, abnormal reflection and focusing, and many new functions and devices have been developed. The effective medium theory lays the foundation for design and application of metamaterials and metasurfaces, connecting metamaterials with real world applications. In this Element, the authors combine these essential ingredients, and aim to make this Element an access point to this field. To this end, they review classical theories for dielectric functions, effective medium theory, and effective parameter extraction of metamaterials, also introducing front edge technologies like metasurfaces with theories, methods, and potential applications. Energy densities are also included.
Metamaterials: Beyond Crystals, Noncrystals, and Quasicrystals is a comprehensive and updated research monograph that focuses on recent advances in metamaterials based on the effective medium theory in microwave frequencies. Most of these procedures were conducted in the State Key Laboratory of Millimeter Waves, Southeast University, China. The book conveys the essential concept of metamaterials from the microcosmic structure to the macroscopic electromagnetic properties and helps readers quickly obtain needed skills in creating new devices at microwave frequencies using metamaterials. The authors present the latest progress on metamaterials and transformation optics and provide abundant examples of metamaterial-based devices accompanied with detailed procedures to simulate, fabricate, and measure them. Comprised of ten chapters, the book comprehensively covers both the fundamentals and the applications of metamaterials. Along with an introduction to the subject, the first three chapters discuss effective medium theory and artificial particles. The next three chapters cover homogeneous metamaterials (super crystals), random metamaterials (super noncrystals), and inhomogeneous metamaterials (super quasicrystals). The final four chapters examine gradient-index inhomogeneous metamaterials, nearly isotropic inhomogeneous metamaterials, and anisotropic inhomogeneous metamaterials, after which the authors provide their conclusions and closing remarks. The book is completely self-contained, making it easy to follow.
The IoT topology defines the way various components communicate with each other within a network. Topologies can vary greatly in terms of security, power consumption, cost, and complexity. Optimizing the IoT topology for different applications and requirements can help to boost the network’s performance and save costs. More importantly, optimizing the topology robustness can ensure security and prevent network failure at the foundation level. In this context, this book examines the optimization schemes for topology robustness in the IoT, helping readers to construct a robustness optimization framework, from self-organizing to intelligent networking. The book provides the relevant theoretical framework and the latest empirical research on robustness optimization of IoT topology. Starting with the self-organization of networks, it gradually moves to genetic evolution. It also discusses the application of neural networks and reinforcement learning to endow the node with self-learning ability to allow intelligent networking. This book is intended for students, practitioners, industry professionals, and researchers who are eager to comprehend the vulnerabilities of IoT topology. It helps them to master the research framework for IoT topology robustness optimization and to build more efficient and reliable IoT topologies in their industry.
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