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This book provides insights into the wetting behavior on fiber-dressed surfaces and guidelines for developing superhydrophobicity based on electrospinning. In developing superhydrophobicity, electrospinning possesses the following advantages over other fabrication techniques. First, the electrospun micro- and nanofibers, which may also featured with secondary fiber morphology, provide sufficient surface roughness for superhydrophobicity. Second, electrospinning is considered an additive manufacturing technique, so the surfaces to be modified are not destroyed for superhydrophobicity. Third, the introduced electrospun structure is featured with high porosity with inter-fiber pores, allowing for a high vapor transmission rate, which is necessary in many applications such as wound dressing, gas sensor.However, books focused on developing superhydrophobicity using electrospinning are rarely found. Electrospinning is only introduced as one section in most superhydrophobicity-related books, and the mechanism of superhydrophobicity by different electrospinning-based methods lacks detailed explanation.

Materials. --- Surfaces (Technology). --- Thin films. --- Manufactures. --- Materials Engineering. --- Surfaces, Interfaces and Thin Film. --- Machines, Tools, Processes. --- Electrospinning.

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Biomedical imaging is the key technique and process to create informative images of the human body or other organic structures for clinical purposes or medical science. Micro-electro-mechanical systems (MEMS) technology has demonstrated enormous potential in biomedical imaging applications due to its outstanding advantages of, for instance, miniaturization, high speed, higher resolution, and convenience of batch fabrication. There are many advancements and breakthroughs developing in the academic community, and there are a few challenges raised accordingly upon the designs, structures, fabrication, integration, and applications of MEMS for all kinds of biomedical imaging. This Special Issue aims to collate and showcase research papers, short commutations, perspectives, and insightful review articles from esteemed colleagues that demonstrate: (1) original works on the topic of MEMS components or devices based on various kinds of mechanisms for biomedical imaging; and (2) new developments and potentials of applying MEMS technology of any kind in biomedical imaging. The objective of this special session is to provide insightful information regarding the technological advancements for the researchers in the community.

micromachining --- n/a --- capacitive micromachined ultrasonic transducer (CMUT) --- transducer --- gold nanoparticles --- cantilever waveguide --- push-pull actuator --- MEMS mirror --- chemo-FET --- ultrahigh frequency ultrasonic transducer --- fluorescence --- lead-free piezoelectric materials --- acoustics --- bioimaging --- scanner --- micro-optics --- MEMS --- microendoscopy --- ego-motion estimation --- rib waveguide --- electromagnetically-driven --- two-photon --- Lissajous scanning --- fabrication --- microwave resonator --- finite element simulation --- noise figure --- imaging --- modelling --- Si lens --- microwave remote sensing --- piezoelectric array --- smart hydrogels --- bio-FET --- surface micromachining --- tilted microcoil --- near-field microwave --- electrochemical sensors --- potentiometric sensor --- photoacoustic imaging --- micromachined US transducer --- electrostatic actuator --- polyimide capillary --- high frequency ultrasonic transducer --- microring resonator --- ultrasonic transducer --- ultrasonic imaging --- indoor navigation --- optical scanner --- scale ambiguity --- bio-sensors --- non-resonating scanner --- wide-filed imaging --- confocal --- acoustic delay line --- tight focus --- miniaturized microscope --- monocular camera --- low noise amplifier (LNA) --- in vivo --- capacitive --- high spatial resolution --- sensing --- microelectromechanical systems (MEMS) --- needle-type --- display --- pseudo-resonant --- MEMS actuators --- microtechnology --- metal oxide field-effect transistor --- transduction techniques --- MEMS scanning mirror --- 3D Printing --- photoacoustic --- chemo-sensor --- in vitro --- wearable sensors

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This book presents state-of-the-art solution methods and applications of stochastic optimal control. It is a collection of extended papers discussed at the traditional Liverpool workshop on controlled stochastic processes with participants from both the east and the west. New problems are formulated, and progresses of ongoing research are reported. Topics covered in this book include theoretical results and numerical methods for Markov and semi-Markov decision processes, optimal stopping of Markov processes, stochastic games, problems with partial information, optimal filtering, robust control, Q-learning, and self-organizing algorithms. Real-life case studies and applications, e.g., queueing systems, forest management, control of water resources, marketing science, and healthcare, are presented. Scientific researchers and postgraduate students interested in stochastic optimal control,- as well as practitioners will find this book appealing and a valuable reference. .

Computational complexity. --- Engineering—Data processing. --- Computational intelligence. --- Statistical physics. --- Probabilities. --- Complexity. --- Data Engineering. --- Computational Intelligence. --- Applications of Nonlinear Dynamics and Chaos Theory. --- Probability Theory and Stochastic Processes. --- Probability --- Statistical inference --- Combinations --- Mathematics --- Chance --- Least squares --- Mathematical statistics --- Risk --- Physics --- Intelligence, Computational --- Artificial intelligence --- Soft computing --- Complexity, Computational --- Electronic data processing --- Machine theory --- Statistical methods --- Stochastic control theory. --- Control theory --- Stochastic processes --- Dynamics. --- Nonlinear theories. --- Engineering --- Nonlinear Optics. --- Stochastic analysis. --- Applied Dynamical Systems. --- Stochastic Analysis. --- Data processing. --- Analysis, Stochastic --- Mathematical analysis --- Optics, Nonlinear --- Optics --- Lasers --- Nonlinear problems --- Nonlinearity (Mathematics) --- Calculus --- Mathematical physics --- Dynamical systems --- Kinetics --- Mechanics, Analytic --- Force and energy --- Mechanics --- Statics

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Neural Networks: Computational Models and Applications covers a wealth of important theoretical and practical issues in neural networks, including the learning algorithms of feed-forward neural networks, various dynamical properties of recurrent neural networks, winner-take-all networks and their applications in broad manifolds of computational intelligence: pattern recognition, uniform approximation, constrained optimization, NP-hard problems, and image segmentation. By presenting various computational models, this book is developed to provide readers with a quick but insightful understanding of the broad and rapidly growing areas in the neural networks domain. Besides laying down fundamentals on artificial neural networks, this book also studies biologically inspired neural networks. Some typical computational models are discussed, and subsequently applied to objection recognition, scene analysis and associative memory. The studies of bio-inspired models have important implications in computer vision and robotic navigation, as well as new efficient algorithms for image analysis. Another significant feature of the book is that it begins with fundamental dynamical problems in presenting the mathematical techniques extensively used in analyzing neurodynamics, thus allowing non-mathematicians to develop and apply these analytical techniques easily. Written for a wide readership, engineers, computer scientists and mathematicians interested in machine learning, data mining and neural networks modeling will find this book of value. This book will also act as a helpful reference for graduate students studying neural networks and complex dynamical systems.

Neural networks (Computer science) --- Réseaux neuronaux (Informatique) --- Natural computation. --- Electronic books. -- local. --- Neural networks (Computer science). --- Civil Engineering --- Computer Science --- Applied Mathematics --- Engineering & Applied Sciences --- Civil & Environmental Engineering --- Biologically-inspired computing. --- Biologically-inspired computing --- Bio-inspired computing --- Natural computing --- Artificial neural networks --- Nets, Neural (Computer science) --- Networks, Neural (Computer science) --- Neural nets (Computer science) --- Computer science. --- Artificial intelligence. --- Applied mathematics. --- Engineering mathematics. --- Computer Science. --- Artificial Intelligence (incl. Robotics). --- Appl.Mathematics/Computational Methods of Engineering. --- Engineering --- Engineering analysis --- Mathematical analysis --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Informatics --- Science --- Mathematics --- Artificial intelligence --- Natural computation --- Soft computing --- Artificial Intelligence. --- Mathematical and Computational Engineering.