الصفحة 58
الصفحة 58
Examining Innovation Management from a Fair Process Perspective
Companies nowadays still differ considerably in that they interact with employees. This interaction depends on different organisational cultures, leadership styles, and the ways in which information and communication take place. A recent trend, even in economic theory, is that interactions are valued in themselves and not solely to achieve rational economic maximisation. People care about outcomes, but they also care about the interactional processes that produce those outcomes. Thomas Limberg investigates a new approach to the management of human relationships in a knowledge-based work environment and analyses the relationship between fair process and innovation performance. Key findings are that social interactions have a significant influence on execution performance in organisations, and fairness can have positive effects on innovative behaviour and therefore on innovation performance. In the transition from a production-based to a knowledge-based economy, fair process is becoming a powerful tool for managing human interactions and for influencing attitudes and behaviours that are so critical in reaching high innovation performance.
E-Voting and Identity ; 1st International Conference, VOTE-ID 2007, Bochum, Germany, October 4-5, 2007, Revised Selected Papers
Voting and identity have a very delicate relationship. Only a few processes - pendso much on an identity management respecting the fine line between reliable identification and reliable non-identifiability each at its part during the process. And only a few processes may change their outer appearance so much with the advent of new IT as voting and identity management do. So it was no surprise in FIDIS, the interdisciplinary Network of Excellence working on the Future of Identity in the Information Society
Evolving Toolbox for Complex Project Management
Enhances learning about complex project management principles and practices through the introduction and discussion of a portfolio of tools presented as an evolving toolbox. Throughout the book, industry practitioners examine the toolsets that are part of the toolbox to develop a broader understanding of complex project management challenges and the available tools to address them.
Evolving methods for macromolecular crystallography : The structural path to the understanding of the mechanism of action of CBRN agents
This volume comprises papers presented at the 2005 edition of the “Crystallography of Molecular Biology” courses that have been held since 1976 at the Ettore Majorana Centre for Scientific Culture in Erice, Italy. The papers span the breadth of material presented in the course, which emphasized the practical aspects of modern macromolecular crystallography and its applications.
Evolving Connectionist Systems : The Knowledge Engineering Approach
Evolving Connectionist Systems is aimed at all those interested in developing and using intelligent computational models and systems to solve challenging real world problems in computer science, engineering, bioinformatics and neuroinformatics. The book challenges scientists and practitioners with open questions about future creation of new information models inspired by Nature. This edition includes new methods for adaptive, knowledge-based learning, such as online incremental feature selection, spiking neural networks, transductive neuro-fuzzy inference, adaptive data and model integration, cellular automata and artificial life systems, particle swarm optimisation, ensembles of evolving systems, and quantum inspired neural networks. New applications to gene and protein interaction modelling, brain data analysis and brain model creation, computational neuro-genetic modelling, adaptive speech, image and multimodal recognition, language modelling, adaptive robotics, modelling dynamic financial and socio-economic systems, and ecological modelling, are covered. An important new feature of the book is the attempt to connect different structural and functional levels of a complex, intelligent system, looking for inspiration from functional relationships in natural systems, such as the genetic and the brain activity.
Evolvable systems : From biology to hardware ; 7th International Conference, ICES 2007, Wuhan, China, September 21-23, 2007, Proceedings
The 41 revised full papers collected in this volume are organized in topical sections on digital hardware evolution, analog hardware evolution, bio-inspired systems, mechanical hardware evolution, evolutionary design, evolutionary algorithms in hardware design, and hardware implementation of evolutionary algorithms.
Evolvable systems : From biology to hardware ; 6th International Conference, ICES 2005, Sitges, Spain, September 12-14, 2005, Proceedings
The flying machines proposed by Leonardo da Vinci in the fifteenth century, the se- reproducing automata theory proposed by John von Neumann in the middle of the twentieth century and the current possibility of designing electronic and mechanical systems using evolutionary principles are all examples of the efforts made by humans to explore the mechanisms present in biological systems that permit them to tackle complex tasks. These initiatives have recently given rise to the emergent field of b- inspired systems and evolvable hardware. The inaugural workshop, Towards Evolvable Hardware, took place in Lausanne in October 1995, followed by the successive events of the International Conference on Evolvable Systems: From Biology to Hardware, held in Tsukuba (Japan) in October 1996, in Lausanne (Switzerland) in September 1998, in Edinburgh (UK) in April 2000, in Tokyo (Japan) in October 2001, and in Trondheim (Norway) in March 2003. Following the success of these past events the sixth international conference was aimed at presenting the latest developments in the field, bringing together researchers who use biologically inspired concepts to implement real systems in artificial intelligence, artificial life, robotics, VLSI design, and related domains. The sixth conference consolidated this biennial event as a reference meeting for the community involved in bio-inspired systems research. All the papers received were reviewed by at least three independent reviewers, thus guaranteeing a high-quality bundle for ICES 2005.
Evolutionary Microeconomics
Classical microeconomics is intended to explain how a price system is able to coordinate the economic agents. But even if it can be extended to incomplete information and externalities, it remains grounded on very heroic assumptions. Agents are endowed with a very strong rationality, equilibrium is stated without a concrete process to achieve it, market is the unique institution considered. Evolutionary microeconomics is aimed at bypassing these limitations by considering a dynamic approach, however not biologically oriented.
Evolutionary Genomics : Statistical and Computational Methods
This book addresses the challenge of analyzing and understanding the evolutionary dynamics of complex biological systems at the genomic level, and elaborates on some promising strategies that would bring us closer to uncovering of the vital relationships between genotype and phenotype. After a few educational primers, the book continues with sections on sequence homology and alignment, phylogenetic methods to study genome evolution, methodologies for evaluating selective pressures on genomic sequences as well as genomic evolution in light of protein domain architecture and transposable elements, population genomics and other omics, and discussions of current bottlenecks in handling and analyzing genomic data. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of detail and expert implementation advice that lead to the best results.
Evolutionary computation, machine learning and data mining in bioinformatics ; 6th European Conference, EvoBIO 2008, Naples, Italy, March 26-28, 2008. Proceedings
The feld of bioinformatics has two main objectives: the creation and main- nance of biological databases, and the discovery of knowledge from life sciences data in order to unravel the mysteries of biological function, leading to new drugs and therapies for human disease. Life sciences data come in the form of biological sequences, structures, pathways, or literature. One major aspect of discovering biological knowledge is to search, predict, or model specifc infortioninagivendatasetinorderto generate new in teresting knowledge.Computer science methods such as evolutionary computation, machine learning, and data mining all have a great deal to ofer the feld of bioinformatics.
Evolutionary computation, machine learning and data mining in bioinformatics ; 5th European Conference, EvoBIO 2007, Valencia, Spain, April 11-13, 2007, Proceedings
This book Covers brings together experts in computer science with experts in bioinformatics and the biological sciences. It presents contributions on fundamental and theoretical issues along with papers dealing with different applications areas.
Evolutionary Computation in Data Mining
This carefully edited book reflects and advances the state of the art in the area of Data Mining and Knowledge Discovery with Evolutionary Algorithms. It emphasizes the utility of different evolutionary computing tools to various facets of knowledge discovery from databases, ranging from theoretical analysis to real-life applications. "Evolutionary Computation in Data Mining" provides a balanced mixture of theory, algorithms and applications in a cohesive manner, and demonstrates how the different tools of evolutionary computation can be used for solving real-life problems in data mining and bioinformatics.
Evolutionary Computation for Modeling and Optimization
Evolutionary Computation for Optimization and Modeling is an introduction to evolutionary computation, a field which includes genetic algorithms, evolutionary programming, evolution strategies, and genetic programming. The text is a survey of some application of evolutionary algorithms. It introduces mutation, crossover, design issues of selection and replacement methods, the issue of populations size, and the question of design of the fitness function. It also includes a methodological material on efficient implementation. Some of the other topics in this book include the design of simple evolutionary algorithms, applications to several types of optimization, evolutionary robotics, simple evolutionary neural computation, and several types of automatic programming including genetic programming. The book gives applications to biology and bioinformatics and introduces a number of tools that can be used in biological modeling, including evolutionary game theory. Advanced techniques such as cellular encoding, grammar based encoding, and graph based evolutionary algorithms are also covered.
Evolutionary Biology from Concept to Application
this book provides an up-to-date overview of evolutionary concepts and how these concepts can be applied to a better understanding of various biological aspects. It is divided into the following four parts: Modelization of Evolution - Concepts in Evolutionary Biology - Knowledge - Applied Evolutionary Biology.This book is an invaluable source of information not only for evolutionary biologists, but also for biologists in general.
Evolution, Monitoring and Predicting Models of Rockburst : Precursor Information for Rock Failure
Focuses on investigating predicting precursor information and key points of rockburst in mining engineering through laboratory experiment, theoretical analysis, numerical simulation and case studies. Understanding the evolution patterns for the microstructure instability of rock is a prerequisite for rockburst prediction. The book provides a guide for readers seeking to understand the evolution patterns for the microstrucure of rock failure, the predicting key point of rock failure and the rockburst predicting model. It will be an essential reference to understand mechanism of rockburst and sheds new light on dynamic disasters prediction. Chapters are carefully developed to cover (1) The evolution patterns for the microstructure instability of rock; (2) Rockburst hazard monitoring and predicting criterion and predicting models. The book addresses the issue with a holistic and systematic approach that investigates the occurrence mechanism of rockburst based on the evolution patterns for the microstructure of rock failure and establishes the predicting model of rockburst.
Evidence-Based Orthodontics ; 2nd ed.
Offers practical strategies for professionals to incorporate EBO in their daily practices Presents brief summaries of the best evidence for a wide range of clinical topics Incorporates information from over 400 systematic reviews, listed by topic
Evidence-Based Oral Surgery : A Clinical Guide for the General Dental Practitioner
This book is designed to guide the dental practitioner in the medical and surgical management of the oral surgery patient. It provides dentists and dental professionals with up-to-date, evidence-based information on how to handle any oral surgical problem and how to work up a patient.
Evidence-Based Management of Patients with Respiratory Failure
this book on the Evidence-based Management of Patients with Respiratory Failure provides important information to improve patient outcome by clearly identifying the research evidence that we can apply in daily clinical practice.
Evidence-Based Implant Dentistry
Covers all aspects of implant dentistry, presenting up-to-date information that reflects the highest level of scientific evidence as presented in the specialized literature. Among the topics addressed by expert authors are the prognosis of natural tooth versus implant restorations, bone response to implant treatment, placement and loading time, implant design and length, platform design, implant abutments, prosthodontic treatment, reconstructive surgery, and periimplantitis.
Evidence Based Global Health Manual for Preterm Birth Risk Assessment
This book is based on global literature, published international, national and regional guidance and it is structured into six chapters providing: an overview of the domains for risk assessment and the summary recommendations in greater depth maternal demographics and past pregnancy histories, accurate pregnancy dating, and the contribution of infection, nutritional status and substance misuse to preterm birth risk. Each chapter has structured sections which include a) background information, b) an evidence statement highlighting the risk factors covered, and c) practical recommendations for evaluating those risks as well as the evidenced recommended and effective interventions for women deemed to be at risk.
