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Distribution (Probability theory) --- Land settlement patterns, Prehistoric --- Mesolithic period --- Nearest neighbor analysis (Statistics) --- Paleolithic period --- Stone implements

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This book presents collective works published in the recent Special Issue (SI) entitled "Recent Developments on Mobile Ad-Hoc Networks and Vehicular Ad-Hoc Networks”. These works expose the readership to the latest solutions and techniques for MANETs and VANETs. They cover interesting topics such as power-aware optimization solutions for MANETs, data dissemination in VANETs, adaptive multi-hop broadcast schemes for VANETs, multi-metric routing protocols for VANETs, and incentive mechanisms to encourage the distribution of information in VANETs. The book demonstrates pioneering work in these fields, investigates novel solutions and methods, and discusses future trends in these fields

routing protocols --- intelligent transportation systems --- VANETs --- vehicle routing --- vehicular networks --- data dissemination --- epidemic algorithms --- MANET --- energy-efficient routing --- transmission power control --- power-aware routing metrics --- power-aware optimization --- cross-layer optimization --- hybrid optimization --- fuzzy logic --- bloom filter --- nearest neighbor --- contention window size --- transmission range --- VANET broadcast --- vehicular ad-hoc networks --- loss aversion --- incentive mechanism --- message transmission --- n/a

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The present book contains all the articles accepted and published in the Special Issue “Advances in Artificial Intelligence: Models, Optimization, and Machine Learning” of the MDPI Mathematics journal, which covers a wide range of topics connected to the theory and applications of artificial intelligence and its subfields. These topics include, among others, deep learning and classic machine learning algorithms, neural modelling, architectures and learning algorithms, biologically inspired optimization algorithms, algorithms for autonomous driving, probabilistic models and Bayesian reasoning, intelligent agents and multiagent systems. We hope that the scientific results presented in this book will serve as valuable sources of documentation and inspiration for anyone willing to pursue research in artificial intelligence, machine learning and their widespread applications.

large margin nearest neighbor regression --- distance metrics --- prototypes --- evolutionary algorithm --- approximate differential optimization --- multiple point hill climbing --- adaptive sampling --- free radical polymerization --- autonomous driving --- object tracking --- trajectory prediction --- deep neural networks --- stochastic methods --- applied machine learning --- classification and regression --- data mining --- ensemble model --- engineering informatics --- gender-based violence in Mexico --- twitter messages --- class imbalance --- k-nearest neighbor --- instance-based learning --- graph neural network --- deep learning --- hyperparameters --- machine learning --- optimization --- inference --- metaheuristics --- animal-inspired --- exploration --- exploitation --- hot rolled strip steel --- surface defects --- defect classification --- knockout tournament --- dynamic programming algorithm --- computational complexity --- combinatorics --- intelligent transport systems --- traffic control --- spatial-temporal variable speed limit --- multi-agent systems --- reinforcement learning --- distributed W-learning --- urban motorways --- multi-agent framework --- .NET framework --- simulations --- agent-based systems --- agent algorithms --- software design --- multisensory fingerprint --- interoperability --- DeepFKTNet --- classification --- generative adversarial networks --- image classification --- transfer learning --- plastic bottle --- n/a

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Molecular Machines presents a dynamic new approach to the physics of enzymes and DNA from the perspective of materials science. Unified around the concept of molecular deformability-how proteins and DNA stretch, fold, and change shape-this book describes the complex molecules of life from the innovative perspective of materials properties and dynamics, in contrast to structural or purely chemical approaches. It covers a wealth of topics, including nonlinear deformability of enzymes and DNA; the chemo-dynamic cycle of enzymes; supra-molecular constructions with internal stress; nano-rheology and viscoelasticity; and chemical kinetics, Brownian motion, and barrier crossing. Essential reading for researchers in materials science, engineering, and nanotechnology, the book also describes the landmark experiments that have established the materials properties and energy landscape of large biological molecules.Molecular Machines is also ideal for the classroom. It gives graduate students a working knowledge of model building in statistical mechanics, making it an essential resource for tomorrow's experimentalists in this cutting-edge field. In addition, mathematical methods are introduced in the bio-molecular context-for example, DNA conformational transitions are used to illustrate the transfer matrix formalism. The result is a generalized approach to mathematical problem solving that enables students to apply their findings more broadly.Molecular Machines represents the next leap forward in nanoscience, as researchers strive to harness proteins, enzymes, and DNA as veritable machines in medicine, technology, and beyond.

Molecular biology. --- Biomolecules. --- Microbiology. --- Microbial biology --- Biology --- Microorganisms --- Biological molecules --- Molecules --- Molecular biology --- Molecular biochemistry --- Molecular biophysics --- Biochemistry --- Biophysics --- Biomolecules --- Systems biology --- Brownian motion. --- DNA deformation. --- DNA melting. --- DNA molecules. --- DNA. --- allosteric control. --- atoms. --- base pairing. --- base stacking. --- cells. --- chemical kinetics. --- deformations. --- diffusion. --- enzyme deformability dynamics. --- enzyme operation. --- enzymes. --- equilibrium. --- folded protein. --- gene expression. --- kinematics. --- mathematical methods. --- molecular deformability. --- molecular machine. --- molecular machines. --- nano-rheology. --- nearest neighbor model. --- nonequilibrium state. --- nonequilibrium thermodynamics. --- nonlinear deformability. --- statistical mechanics. --- steady state. --- thermal fluctuation. --- viscoelasticity. --- zipper model.

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The present book contains all the articles accepted and published in the Special Issue “Advances in Artificial Intelligence: Models, Optimization, and Machine Learning” of the MDPI Mathematics journal, which covers a wide range of topics connected to the theory and applications of artificial intelligence and its subfields. These topics include, among others, deep learning and classic machine learning algorithms, neural modelling, architectures and learning algorithms, biologically inspired optimization algorithms, algorithms for autonomous driving, probabilistic models and Bayesian reasoning, intelligent agents and multiagent systems. We hope that the scientific results presented in this book will serve as valuable sources of documentation and inspiration for anyone willing to pursue research in artificial intelligence, machine learning and their widespread applications.

Research & information: general --- Mathematics & science --- large margin nearest neighbor regression --- distance metrics --- prototypes --- evolutionary algorithm --- approximate differential optimization --- multiple point hill climbing --- adaptive sampling --- free radical polymerization --- autonomous driving --- object tracking --- trajectory prediction --- deep neural networks --- stochastic methods --- applied machine learning --- classification and regression --- data mining --- ensemble model --- engineering informatics --- gender-based violence in Mexico --- twitter messages --- class imbalance --- k-nearest neighbor --- instance-based learning --- graph neural network --- deep learning --- hyperparameters --- machine learning --- optimization --- inference --- metaheuristics --- animal-inspired --- exploration --- exploitation --- hot rolled strip steel --- surface defects --- defect classification --- knockout tournament --- dynamic programming algorithm --- computational complexity --- combinatorics --- intelligent transport systems --- traffic control --- spatial-temporal variable speed limit --- multi-agent systems --- reinforcement learning --- distributed W-learning --- urban motorways --- multi-agent framework --- .NET framework --- simulations --- agent-based systems --- agent algorithms --- software design --- multisensory fingerprint --- interoperability --- DeepFKTNet --- classification --- generative adversarial networks --- image classification --- transfer learning --- plastic bottle --- large margin nearest neighbor regression --- distance metrics --- prototypes --- evolutionary algorithm --- approximate differential optimization --- multiple point hill climbing --- adaptive sampling --- free radical polymerization --- autonomous driving --- object tracking --- trajectory prediction --- deep neural networks --- stochastic methods --- applied machine learning --- classification and regression --- data mining --- ensemble model --- engineering informatics --- gender-based violence in Mexico --- twitter messages --- class imbalance --- k-nearest neighbor --- instance-based learning --- graph neural network --- deep learning --- hyperparameters --- machine learning --- optimization --- inference --- metaheuristics --- animal-inspired --- exploration --- exploitation --- hot rolled strip steel --- surface defects --- defect classification --- knockout tournament --- dynamic programming algorithm --- computational complexity --- combinatorics --- intelligent transport systems --- traffic control --- spatial-temporal variable speed limit --- multi-agent systems --- reinforcement learning --- distributed W-learning --- urban motorways --- multi-agent framework --- .NET framework --- simulations --- agent-based systems --- agent algorithms --- software design --- multisensory fingerprint --- interoperability --- DeepFKTNet --- classification --- generative adversarial networks --- image classification --- transfer learning --- plastic bottle