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Communication in Plants : Neuronal Aspects of Plant Life
Plant neurobiology is a newly emerging field of plant sciences. It covers signalling and communication at all levels of biological organization – from molecules up to ecological communities. In this book, plants are presented as intelligent and social organisms with complex forms of communication and information processing. Authors from diverse backgrounds such as molecular and cellular biology, electrophysiology, as well as ecology treat the most important aspects of plant communication, including the plant immune system, abilities of plants to recognize self, signal transduction, receptors, plant neurotransmitters and plant neurophysiology. Further, plants are able to recognize the identity of herbivores and organize the defence responses accordingly. The similarities in animal and plant neuronal/immune systems are discussed too. All these hidden aspects of plant life and behaviour will stimulate further intense investigations in order to understand the communicative plants in their whole complexity.
Advances in cognitive neurodynamics ICCN 2007; Proceedings of the International conference on cognitive neurodynamics - 2007
Contains the Proceedings of the 1st International Conference on Cognitive Neurodynamics held in Shanghai, November 17-21, 2007. The participants were treated to an exciting and stimulating conference that left everyone with an enthusiastic vision for the future of the field. The latest important progress was covered by 13 mini-symposia including: Models of Mental Disorders; Cognitive Machines; Dynamics in learning and memory; Central nervous system synchronization; Neuroinformatics; Cognitive Computational Modeling of Human Language Processing; Cognitive Neurodynamics of Attention; Bottom-Up and Top-Down; Brain Networks; From Anatomy to Dynamics; Translational Cognitive Neuroimaging; K-sets; Theory and Applications; Advanced Signal Processing Techniques for Brain Data Analysis; Visual cortex: information processing and dynamics; Dynamics of Firing Patterns and Synchronization in Neuronal Systems.
Knowledge Sharing in the Integrated Enterprise : Interoperability Strategies for the Enterprise Architect
The IFIP series publishes state-of-the-art results in the sciences and technologies of information and communication. The scope of the series includes: foundations of computer science; software theory and practice; education; computer applications in technology; communication systems; systems modeling and optimization; information systems; computers and society; computer systems technology; security and protection in information processing systems; artificial intelligence; and human-computer interaction. Proceedings and post-proceedings of referred international conferences in computer science and interdisciplinary fields are featured. These results often precede journal publication and represent the most current research. The principal aim of the IFIP series is to encourage education and the dissemination and exchange of information about all aspects of computing.
Classification and Modeling with Linguistic Information Granules : Advanced Approaches to Linguistic Data Mining
Many approaches have already been proposed for classification and modeling in the literature. These approaches are usually based on mathematical mod els. Computer systems can easily handle mathematical models even when they are complicated and nonlinear (e.g., neural networks). On the other hand, it is not always easy for human users to intuitively understand mathe matical models even when they are simple and linear. This is because human information processing is based mainly on linguistic knowledge while com puter systems are designed to handle symbolic and numerical information. A large part of our daily communication is based on words. We learn from various media such as books, newspapers, magazines, TV, and the Inter net through words. We also communicate with others through words. While words play a central role in human information processing, linguistic models are not often used in the fields of classification and modeling. If there is no goal other than the maximization of accuracy in classification and modeling, mathematical models may always be preferred to linguistic models. On the other hand, linguistic models may be chosen if emphasis is placed on interpretability.
Charting a new course : Natural language processing and information retrieval : Essays in Honour of Karen Spärck Jones
This book celebrates the life and work of Karen Spärck Jones in her seventieth year. she is one of the major figures of 20th century and early 21st Century computing and information processing. It book consists of fifteen new and original chapters written by leading international authorities reviewing the state of the art and her influence in the areas in which Karen Spärck Jones has been active. Although she has a publication record which goes back over forty years, it is clear even the very early work reviewed in the book can be read with profit by those working on recent developments in information processing like bioinformatics and the semantic web.
Advances in Information Processing and Protection
This book contains a selection of the best papers given at the international Advanced Computer Systems Conference in October 2006 in Miedzyzdroje, Poland. Combining research areas from both Computer Science and Industrial Management.
Advances in Digital Forensics IV
Advances in Digital Forensics IV describes original research results and innovative applications in the emerging discipline of digital forensics. In addition, it highlights some of the major technical and legal issues related to digital evidence and electronic crime investigations.
Advances in Digital Forensics II
This book is the second volume in the anual series produced by the International Federation for Information Processing (IFIP) Working Group 11.9 on Digital Forensics, an international community of scientists, engineers and practitioners dedicated to advancing the state of the art of research and practice in digital forensics. The book contains a selection of twenty-five edited papers from the First Annual IFIP WG 11.9 Conference on Digital Forensics, held at the National Center for Forensic Science, Orlando, Florida, USA in the spring of 2006.
Bio-inspired credit risk analysis : Computational intelligence with support vector machines
Credit risk analysis is one of the most important topics in the field of financial risk management. Due to recent financial crises and regulatory concern of Basel II, credit risk analysis has been the major focus of financial and banking industry. Especially for some credit-granting institutions such as commercial banks and credit companies, the ability to discriminate good customers from bad ones is crucial. The need for reliable quantitative models that predict defaults accurately is imperative so that the interested parties can take either preventive or corrective action. Hence credit risk analysis becomes very important for sustainability and profit of enterprises. In such backgrounds, this book tries to integrate recent emerging support vector machines and other computational intelligence techniques that replicate the principles of bio-inspired information processing to create some innovative methodologies for credit risk analysis and to provide decision support information for interested parties.
Le choix bayésien: Principes et pratique
Covers the so-called Bayesian approach to statistical inference and in particular its decision-making aspects. The bases of this axiomatics (choice of the a priori, optimal decisions, tests and regions of confidence) are discussed in detail, as well as more recent openings of Bayesian analysis such as the choice of models, the use of numerical methods. Stochastic approximation (MCMC), the theory of noninformative laws (Berger-Bernardo axioms) and the relation to the classical theory of admissibility. Each chapter is completed by an extensive series of exercises of increasing difficulty and by bibliographical notes on the themes addressed. This book can be used in a Master's program in Applied Mathematics, Biometrics, Econometrics or any other program that uses quantitative information processing techniques. It only requires a basic course in probability theory and mathematical statistics as a preliminary.
Complex-valued neural networks
This book is the first monograph ever on complex-valued neural networks, which lends itself to graduate and undergraduate courses in electrical engineering, informatics, control engineering, mechanics, robotics, bioengineering, and other relevant fields. It is useful for those beginning their studies, for instance, adaptive signal processing for highly functional sensing and imaging, control in unknown and changing environment, brainlike information processing, robotics inspired by human neural systems, and interdisciplinary studies to realize comfortable society. It is also helpful to those who carry out research and development regarding new products and services at companies.
Bioinformatics Using Computational Intelligence Paradigms
Bioinformatics as well as Computational Intelligence are undoubtedly remarkably fast growing fields of research and real-world applications with enormous potential for current and future developments. "Bioinformatics using Computational Intelligence Paradigms" contains recent theoretical approaches and guiding applications of biologically inspired information processing systems(Computational Intelligence) against the background of bioinformatics. This carefully edited monograph combines the latest results of Bioinformatics and Computational Intelligence and offers a promising cross-fertilisation and interdisciplinary work between these growing fields.
Barriers and Biases in Computer-Mediated Knowledge Communication : And How They May Be Overcome
This books deals with computer-mediated cooperation and communication scenarios in teaching and learning situations, leisure activities (e.g. laypersons looking for expert information on the internet), and net-based communication at work. Such scenarios will become increasingly important. But the successful use of such computer-mediated settings is not trivial. Cooperative learning and work itself requires special skills and strategies. And the technical settings with sometimes restricted, sometimes new possibilities for communication add problems on top of the cooperation itself. What are the barriers in computer-mediated communication for cooperative learning and work? Which are the most relevant biases in computer-mediated information processing? Based on empirical research the contributors from psychology, education and computer sciences offer different perspectives on the nature and causes of such barriers.
Artificial intelligence in recognition and classification of astrophysical and medical images
This book presents innovative techniques in Recognition and Classification of Astrophysical and Medical Images. The contents include: Introduction to pattern recognition and classification in astrophysical and medical images. Image standardization and enhancement. Region-based methods for pattern recognition in medical and astrophysical images. Advanced information processing using statistical methods. Feature recognition and classification using spectral method
Algorithmic information theory : Mathematics of digital information processing
This book treats the Mathematics of many important areas in digital information processing.It covers, in a unified presentation, five topics: Data Compression, Cryptography, Sampling (Signal Theory), Error Control Codes, Data Reduction. The thematic choices are practice-oriented. So, the important final part of the book deals with the Discrete Cosine Transform and the Discrete Wavelet Transform, acting in image compression. The presentation is dense, the examples and numerous exercises are concrete. The pedagogic architecture follows increasing mathematical complexity.
