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This book appeals to scientists, teachers and graduate students in mathematics, and will be of interest for scholars in applied sciences as well, in particular in medicine, biology and social sciences. The models in this connection apply, in particular, to the study of the immune system response and to the predator–prey dynamic. The efficiency of public transport is also considered and blast waves in explosions are studied. Other contributions concern pure mathematics, in particular Pythagorean means, sequences of matrices and Markov chains, and these give evidence of deep links with Symmetry.

paradox of enrichment --- prey–predator system --- persistence of predators --- extinction of predators --- blast waves --- non-ideal gas --- Rankine–Hugoniot conditions --- magnetogasdynamics --- dynamic model --- immune system response --- immune cells --- abnormal cells --- nonlinear ordinary differential equations --- stability --- diet --- Aggregation dynamic system --- Discrete system --- Epidemic model --- Cauchy’s interlacing theorem --- Output-feedback control --- Stability --- Antistable/Stable matrix --- onboard comfort level --- Markow chain --- bus passenger occupancy prediction --- Chebyshev inequality --- Tracy-Singh product --- continuous field of operators --- Bochner integral --- weighted Pythagorean mean

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Party competition for votes in free and fair elections involves complex interactions by multiple actors in political landscapes that are continuously evolving, yet classical theoretical approaches to the subject leave many important questions unanswered. Here Michael Laver and Ernest Sergenti offer the first comprehensive treatment of party competition using the computational techniques of agent-based modeling. This exciting new technology enables researchers to model competition between several different political parties for the support of voters with widely varying preferences on many different issues. Laver and Sergenti model party competition as a true dynamic process in which political parties rise and fall, a process where different politicians attack the same political problem in very different ways, and where today's political actors, lacking perfect information about the potential consequences of their choices, must constantly adapt their behavior to yesterday's political outcomes. Party Competition shows how agent-based modeling can be used to accurately reflect how political systems really work. It demonstrates that politicians who are satisfied with relatively modest vote shares often do better at winning votes than rivals who search ceaselessly for higher shares of the vote. It reveals that politicians who pay close attention to their personal preferences when setting party policy often have more success than opponents who focus solely on the preferences of voters, that some politicians have idiosyncratic "valence" advantages that enhance their electability--and much more.

Competition --- Political parties. --- Competition (Economics) --- Competitiveness (Economics) --- Economic competition --- Commerce --- Conglomerate corporations --- Covenants not to compete --- Industrial concentration --- Monopolies --- Open price system --- Supply and demand --- Trusts, Industrial --- Parties, Political --- Party systems, Political --- Political party systems --- Political science --- Divided government --- Intra-party disagreements (Political parties) --- Political conventions --- Political aspects --- Simulation methods. --- Economic aspects --- Monte Carlo parameterization. --- Robert Axelrod. --- Voronoi tessellations. --- agent-based model. --- agent-based modeling. --- agent-based models. --- competition. --- competitive spatial location. --- computational geometry. --- computer simulation. --- decision rules. --- decisions rules. --- dynamic multiparty competition. --- dynamic system. --- grid sweeping. --- multiparty competition. --- party competition. --- party leaders. --- party policy. --- policy preferences. --- political parties. --- political party. --- political systems. --- politicians. --- postwar democracy. --- spatial models. --- stochastic processes. --- valence models. --- vote-seeking rules. --- voter behavior. --- voter preferences. --- votes. --- Political sociology --- Political parties

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The advent of Internet of Things offers a scalable and seamless connection of physical objects, including human beings and devices. This, along with artificial intelligence, has moved transportation towards becoming intelligent transportation. This book is a collection of eleven articles that have served as examples of the success of internet of things and artificial intelligence deployment in transportation research. Topics include collision avoidance for surface ships, indoor localization, vehicle authentication, traffic signal control, path-planning of unmanned ships, driver drowsiness and stress detection, vehicle density estimation, maritime vessel flow forecast, and vehicle license plate recognition. High-performance computing services have become more affordable in recent years, which triggered the adoption of deep-learning-based approaches to increase the performance standards of artificial intelligence models. Nevertheless, it has been pointed out by various researchers that traditional shallow-learning-based approaches usually have an advantage in applications with small datasets. The book can provide information to government officials, researchers, and practitioners. In each article, the authors have summarized the limitations of existing works and offered valuable information on future research directions.

decision-making --- autonomous navigation --- collision avoidance --- scene division --- deep reinforcement learning --- maritime autonomous surface ships --- internet of things --- crowdsourcing --- indoor localization --- data fusion --- security --- authentication --- Inertial Measurement Units --- road transportation --- traffic signal control --- speed guidance --- vehicle arrival time --- connected vehicle --- unmanned ships --- DDPG --- autonomous path planning --- end-to-end --- at-risk driving --- deep support vector machine --- driver drowsiness --- driver stress --- multi-objective genetic algorithm --- multiple kernel learning --- urban freeway --- hybrid dynamic system --- state transition --- unknown inputs observer --- vehicle density --- maritime vessel flows --- intelligent transportation systems --- deep learning --- automatic license plate recognition --- intelligent vehicle access --- histogram of oriented gradients --- artificial neural networks --- convolutional neural networks --- time-frequency --- Inertial Measurement Unit (IMU) --- road anomalies --- n/a