This monograph presents a new discipline-cultural genomics-as a complex approach for studying the interrelation between genomic data and culture and the impact of culture on genomic evolution in human history.
This volume in the Encyclopedia of Complexity and Systems Science (ECSS) covers such fascinating and practical topics as (i) Vehicular traffic flow theory, (ii) Studies of real field traffic data, (iii) Complex phenomena of self-organization in vehicular traffic, (iv) Effect of automatic driving (self-driving vehicles) on traffic flow, v) Complex dynamics of city traffic, (vi) Dynamic control and optimization of traffic and transportation networks, including dynamic traffic assignment in the network, (vii) Pedestrian traffic, (viii) Evacuation scenarios, and (ix) Network characteristics of air control.
Numerical partial differential equations (PDEs) are an important part of numerical simulation, the third component of the modern methodology for science and engineering, besides the traditional theory and experiment.
The Encyclopedia of Social Network Analysis and Mining (ESNAM) is the first major reference work to integrate fundamental concepts and research directions in the areas of social networks and applications to data mining.
This book describes the mathematical background behind discrete approaches to morphological analysis of scalar fields, with a focus on Morse theory and on the discrete theories due to Banchoff and Forman.
The Handbook of Simulation Optimization presents an overview of the state of the art of simulation optimization, providing a survey of the most well-established approaches for optimizing stochastic simulation models and a sampling of recent research advances in theory and methodology.
This volume explores how context has been and can be used in computing to model human behaviors, actions and communications as well as to manage data and knowledge.
This book portrays the commonality of tissue micro-structure that dictates physiological function in various organs (microstructure-function relation).
Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning introduce the evolving area of static and dynamic simulation-based optimization.
Cutting-Edge Techniques to Better Analyze and Predict Complex Physical PhenomenaGeometric Modeling and Mesh Generation from Scanned Images shows how to integrate image processing, geometric modeling, and mesh generation with the finite element method (FEM) to solve problems in computational biology, medicine, materials science, and engineering.
