Page 108
Page 108
Exchange traded funds : Structure, regulation and application of a new fund class
The organization of traditional mutual funds as Exchange Traded Funds (ETFs) produced revolutionary changes in the fund industry. These changes, and the subsequent events to which they led, have greatly - creased the practical way of trading funds. Traditional mutual fund m- kets were fragmented, and transactions were both costly and from time to time difficult to arrange. Investments in emerging markets for example were anything but efficient. As a consequence of establishing ETF funds market segments, the efficiency of transactions has been broadly increased as well as transaction costs dramatically reduced. All this changed in the early Nineties with the introduction of the first ETF for the purpose of trading funds. Exchange Traded Funds – Structure, Regulation and Application of a New Fund Class is a comprehensive summary of articles covering all aspects of the Exchange Traded Fund industry.The present book is divided into four parts: The opening part, containing ETFs – A Leading Financial Innovation and From Continent to Sectors: Challenges and Uses of ETFs in Europe, is - signed to give the reader broad insight into the industry, developments and trends. Further, the article Spiders: Where Are the Bugs? examine the characteristics and performance of these instruments from an academic point of view.
Excel PivotTables Recipe Book : A Problem-Solution Approach
Excel Pivot Tables Recipe Book: A Problem-Solution Approach is for anyone who uses Excel frequently. This book follows a problem-solution format that covers the entire breadth of situations you might encounter when working with PivotTables—from planning and creating, to formatting and extracting data, to maximizing performance and troubleshooting. The author presents tips and techniques in this collection of recipes that cannot be found in Excel's Help section, and she carefully explains the most confusing features of PivotTables.
Excel 2007 PivotTables Recipes : A Problem-Solution Approach
You'll find this book when facing any new or difficult problem in PivotTables, covering the entire breadth of situations you could ever encounter, from planning and creating, to formatting and extracting data, to maximizing performance and troubleshooting.
Examples & explanations : criminal law
Combines textual material with well-written and comprehensive examples, explanations, and questions to test students' comprehension of the materials and to provide practice in applying information to fact patterns. The questions, which often raise a variety of issues in one fact situation, are similar to those on a law school or bar examination. New to the eighth edition: discussion of self-defense and police use of force issues; impact of #MeToo movement on rape law; interesting hypothetical situations based on real cases in the last few years
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 ; 8th International Conference, ICES 2008, Prague, Czech Republic, September 21-24, 2008. Proceedings
This book constitutes the refereed proceedings of the 8th International Conference on Evolvable Systems, ICES 2008, held in Prague, Czech Republic, in September 2008.The 28 revised full papers and 14 revised poster papers presented were carefully reviewed and selected from 52 submissions. The papers are organized in topical sections on evolution of analog circuits, evolution of digital circuits, hardware-software codesign and platforms for adaptive systems, evolutionary robotics, development, real-world applications, evolutionary networking, evolvable artificial neural networks, and transistor-level circuit evolution.
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 Synthesis of Pattern Recognition Systems
Evolutionary Synthesis of Pattern Recognition Systems presents novel effective approaches based on evolutionary computational techniques, such as genetic programming (GP), linear genetic programming (LGP), coevolutionary genetic programming (CGP) and genetic algorithms (GA) to automate the synthesis and analysis of object detection and recognition systems. The book’s concepts, principles, and methodologies will enable readers to automatically build robust and flexible systems—in a systematic manner—that can provide human-competitive performance and reduce the cost of designing and maintaining these systems. Its content covers all key aspects of object recognition: object detection, feature selection, feature discovery, object recognition, domain knowledge. Basic knowledge of programming and data structures, and some calculus, is presupposed.ing the book’s novel ideas
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 Computer Music
The evolutionary computation approach to music is an exciting new development for composers and musicologists alike. For composers, it provides an innovative and natural means for generating musical ideas from a specifiable set of primitive components and processes. For musicologists, these techniques are used to model the cultural transmission and change of a population's body of musical ideas over time. In both cases, musical evolution can be guided by a variety of constraints and tendencies built into the system, such as realistic psychological factors that influence the way music is expressed, experienced, learned, stored, modified, and passed on among individuals. This book discusses not only the applications of evolutionary computation to music, but also the tools needed to create and study such systems. These tools are drawn in part from research into the origins and evolution of biological organisms, ecologies, and cultural systems on the one hand, and from computer simulation methodologies on the other. They can be combined to create surrogate artificial worlds populated by interacting simulated organisms in which complex musical experiments can be performed that would otherwise be impossible.
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.
