Advances in Probabilistic Graphical Models
This carefully edited book brings together in one volume some of the most important topics of current research in probabilistic graphical modelling, learning from data and probabilistic inference. This includes topics such as the characterisation of conditional independence, the sensitivity of the underlying probability distribution of a Bayesian network to variation in its parameters, the learning of graphical models with latent variables and extensions to the influence diagram formalism. In addition, attention is given to important application fields of probabilistic graphical models, such as the control of vehicles, bioinformatics and medicine.
Advances in Databases and Information Systems ; 12th East European Conference, ADBIS 2008, Pori, Finland, September 5-9, 2008. Proceedings
This book constitutes the refereed proceedings of the 12th East European Conference on Advances in Databases and Information Systems, ADBIS 2008, held in Pori, Finland, on September 5-9, 2008.
Advances in Cooperative Control and Optimization ; Proceedings of the 7th International Conference on Cooperative Control and Optimization
Each year, the International Conference on Cooperative Control and Optimization (CCO) brings together top researchers from around the world to present new ideas, theories, applications, and advances in the fields of autonomous agents, cooperative systems, control theory, and optimization. The works in this volume are a result of invited papers and selected presentations at the Seventh Annual International Conference on Cooperative Control and Optimization, held in Gainesville, Florida, January 31 – February 2, 2007.The works presented in this book are suitable for faculty, graduate students, and industrial researchers in the fields of optimization, control theory, electrical engineering, computer science, and mathematics.
Advances in Cardiac Signal Processing
Deals with the acquisition and extraction of the various morphological features of the electrocardiogram signals.In the first chapters the book first presents data fusion and different data mining techniques that have been used for the cardiac state diagnosis. The second part deals with heart rate variability (HRV), a non-invasive measurement of cardiovascular autonomic regulation. Next, visualization of ECG data is discussed, an important part of the display in life threatening state. Here, the handling of data is discussed which were acquired during several hours. In the following chapters the book discusses aortic pressure measurement which is of significant clinical importance. It presents non-invasive methods for analysis of the aortic pressure waveform, indicating how it can be employed to determine cardiac contractility, arterial compliance, and peripheral resistance. In addition, the book demonstrates methods to extract diagnostic parameters for assessing cardiac function. Further the measurement strategies for contractile effort of the left ventricle are presented. Finally, the book concludes about the future of cardiac signal processing leading to next generation research topics which directly impacts the cardiac health care.
Advances in Biologically Inspired Information Systems : Models, Methods, and Tools
A comprehensive overview of the most promising research directions in the area of bio-inspired computing. According to the broad spectrum addressed by the different book chapters, a rich variety of biological principles and their application to ICT systems are presented.
Advances in Artificial Life ; 9th European Conference, ECAL 2007, Lisbon, Portugal, September 10-14, 2007, Proceedings
This book is organized in topical sections on conceptual articles, morphogenesis and development, robotics and autonomous agents, evolutionary computation and theory, cellular automata, models of biological systems and their applications, ant colony and swarm systems, evolution of communication, simulation of social interactions, self-replication, artificial chemistry, and posters.
Advances in artificial life ; 8th European Conference, ECAL 2005 , Canterbury, UK, September 5-9, 2005, Proceedings
The Artificial Life term appeared more than 20 years ago . Since then the area has developed dramatically, many researchersjoining enthusiastically and research groups sprouting everywhere.a conceptual track, where papers were judged on criteria like importance and/or novelty of the concepts proposed rather than the experimental / theoretical results, has been introduced this year. A conference on a theme as broad as Artificial Life is bound to be very di-verse, but a few tendencies emerged. First, fields like ‘Robotics and Autonomous Agents’ or ‘Evolutionary Computation’are still extremely active and keep onbringing a wealth of results to the A-Life community. Even there, however, new tendencies appear, like collective robotics, and more specifically self-assembling robotics, which represent now a large subsection. Second, new areas appear.‘Morphogenesis and Development’ which used to be the subject of only a fewpapers, is now one of the largest subsections, and seems to be on the brinkof becoming a field of its own. Finally, most classical themes of A-Life re-search like ‘Artificial Chemistry’, ‘Ant-Inspired Systems’, ‘Cellular Automata’,‘Self-Replication’, ‘Social Simulations’ or ‘Bio-realist Simulations’ are still goingstrong and are well represented within this volume.
Advances in artificial intelligence: models, optimization, and machine learning
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.
Advances in Artificial Intelligence - SBIA 2008 ; 19th Brazilian Symposium on Artificial Intelligence Savador, Brazil, October 26-30, 2008. Proceedings
Constitutes the refereed proceedings of the 19th Brazilian Symposium on Artificial Intelligence, SBIA 2008, held in Salvador, Brazil, in October 2008.
Advances in Artificial Intelligence - IBERAMIA-SBIA 2006 ; 2nd International Joint Conference, 10th Ibero-American Conference on AI, 18th Brazilian AI Symposium, Ribeirao Preto, Brazil, October 23-27, 2006
This decision was a consequence of the successful event organized in 2000, when the First International Joint Conference IBERAMIA/ SBIA 2000 (7th Ibero- American Artifcial Intelligence Conference and 15th Brazilian Artifcial Intel- gence Symposium) occurred in Brazil. Moreover, in 2006 the artifcial intelligence community celebrated the golden anniversary of the 1956 Dartmouth Conference that marked the beginning of artifcial intelligence as a research feld. th SBIA 2006 was the 18 conference of the SBIA conference series, which is the leading Brazilian conference for the presentation of AI research and applications.
Advanced Microsystems for Automotive Applications 2006 ; 2nd ed.
Microsystems in many cases provided the key functions for this progress. Although the issues the event concentrated on didn’t change significantly (safety, powertrain, comfort, etc.), considerable shifts of technological paradigms and approaches can be stated. The future of microsystems will consist of integrated smart systems which are able to diagnose a situation, to describe and to qualify it. They will be able to identify and mutually address each other. They will be predictive and therefore they will be able to decide and help to decide. Smart systems will enable the automobile to interact with the environment, they will perform multiple tasks and assist a variety of activities. Smart systems will be highly reliable, often networked and energy autonomous.
Advanced mathematical science for mobility society
The automotive industry has made steady progress in technological innovations under the names of Connected Autonomous-Shared-Electric (CASE) and Mobility as a Service (MaaS). Needless to say, mathematics and informatics are important to support such innovations. As the concept of cars and movement itself is diversifying, they are indispensable for grasping the essence of the future mobility society and building the foundation for the next generation. This book contains three main contents. 1. Mathematical models of flow 2. Mathematical methodsfor huge data and network analysis 3. Algorithm for mobility society The first one discusses mathematical models of pedestrian and traffic flow, as they are important for preventing accidents and achieving efficient transportation.
Advanced Intelligent Computing Theories and Applications : With Aspects of Artificial Intelligence ; 3rd International Conference on Intelligent Computing, ICIC 2007, Qingdao, China, August 21-24, 2007, Proceedings
The International Conference on Intelligent Computing (ICIC) was formed to provide an annual forum dedicated to the emerging and challenging topics in artificial intelligence, machine learning, bioinformatics, and computational biology, etc. It aims to bring gether researchers and practitioners from both academia and industry to share ideas, problems and solutions related to the multifaceted aspects of intelligent computing.This year, the conference concentrated mainly on the theories and methodologies as well as the emerging applications of intelligent computing. Its aim was to unify the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications.
Advanced Fuzzy Logic Technologies in Industrial Applications
Addresses the problem by introducing a dynamic, on-line fuzzy inference system. In this system membership functions and control rules are not determined until the system is applied and each output of its lookup table is calculated based on current inputs. The tuning process is a major focus in this volume because it is the most difficult stage in fuzzy control application. Using new methods such as µ-law technique, histogram equalization and the Bezier-based method, all detailed here, the tuning process can be significantly simplified and control performance improved. The other great strength of this book lies in the range and contemporaneity of its applications and examples which include: laser tracking and control; robot calibration; image processing and pattern recognition; medical engineering; audio systems; autonomous underwater vehicles and data mining.
Advanced Autonomic Networking and Communication
This book presents a comprehensive reference of state-of-the-art efforts and early results in the area of autonomic networking and communication.
Adaptive Cooperation between Driver and Assistant System : Improving Road Safety
One of the next challenges in vehicular technology field is to improve drastically the road safety. Current developments are focusing on both vehicle platform and diverse assistance systems. This book presents a new engineering approach based on lean vehicle architecture ready for the drive-by-wire technology.
Adaptive Autonomous Secure Cyber Systems
Establishes scientific foundations for adaptive autonomous cyber systems and ultimately brings about a more secure and reliable Internet. The recent advances in adaptive cyber defense (ACD) have developed a range of new ACD techniques and methodologies for reasoning in an adaptive environment.
Adaptive agents and multi-agent systems II : Adaptation and multi-agent learning
Adaptive agents and multi-agent systems is an emerging and exciting interdisciplinary area of research and development involving artificial intelligence, software engineering, and developmental biology, as well as cognitive and social science. This book presents 17 revised and carefully reviewed papers taken from two workshops on the topic as well as 2 invited papers by leading researchers in the area. The papers deal with various aspects of machine learning, adaptation, and evolution in the context of agent systems and autonomous agents.
Absolute Stability of Nonlinear Control Systems
Following the recent developments in the field of absolute stability, Professor Xiaoxin Liao, in conjunction with Professor Pei Yu, has created a second edition of his seminal work on the subject. Liao begins with an introduction to the Lurie problem and the Lurie control system, before moving on to the simple algebraic sufficient conditions for the absolute stability of autonomous and non-autonomous ODE systems, as well as several special classes of Lurie-type systems. The focus of the book then shifts toward the new results and research that have appeared in the decade since the first edition was published. This includes nonlinear control systems with multiple controls, interval control systems, time-delay and neutral Lurie control systems, systems described by functional differential equations, the absolute stability for neural networks, as well as applications to chaos control and chaos synchronization.
3D-Position Tracking and Control for All-Terrain Robots
Rough terrain robotics is a fast evolving field of research and a lot of effort is deployed towards enabling a greater level of autonomy for outdoor vehicles. This book demonstrates how the accuracy of 3D position tracking can be improved by considering rover locomotion in rough terrain as a holistic problem. In this work, a mechanical structure allowing smooth motion across obstacles with limited wheel slip is used. In particular, it enables the use of odometry and inertial sensors to improve the position estimation in rough terrain. A method for computing 3D motion increments based on the wheel encoders and chassis state sensors is developed. The algorithm runs online and can be adapted to any kind of passive wheeled rover. Finally, sensor fusion using 3D-Odometry, inertial sensors and visual motion estimation based on stereovision is presented. The experimental results demonstrate how each sensor contributes to increase the accuracy and robustness of the 3D position estimation.



















