Software Engineering Research, Management And Applications 2012

To the best of the author’s knowledge this is the first book of its kind exclusively dedicated to the application of computational intelligence techniques in fractional order systems and control. Computational Intelligence (CI) techniques have been applied to engineering problems to find solutions to many hitherto intractable conundrums and is a useful tool for dealing with problems of higher computational complexity.   This book borders on the interface between CI techniques and fractional calculus, and looks at ways in which fractional order control systems may be designed or enhanced using CI based paradigms.

The main focus of DART was to discuss and compare suitable novel solutions based on intelligent techniques and applied to real-world applications. Authors, both practitioners and researchers, shared their results in several topics such as "Multi-Agent Systems", "Natural Language Processing", "Automatic Advertisement", "Customer Interaction Analytics", "Opinion Mining".

The first approach aimed at handling the uncertainty in the CAC problem by employing fuzzy comparators.  Evolutionary techniques, including Genetic Algorithm and Biogeography Based Optimization, have been employed to solve the optimization problems. Call Admission Control in Mobile Cellular Networks. Current research in mobile communication considers them as two independent problems, although the former greatly depends on the resulting free channels obtained as the outcome of the latter.

iScale, a tool for the retrospective assessment of usersʼ experiences over time is proposed as an alternative to longitudinal field studies, and a semi-automated technique for the analysis of the elicited experience narratives is introduced. Modeling Users' Experiences with Interactive Systems It proposes the development of interactive tools that can assist designers in moving across multiple levels of abstraction of empirical data, as design-relevant knowledge might be found on all these levels.  This book identifies the notion of diversity in usersʼ experiences with interactive products and proposes methods and tools for modeling this along two levels: (a) interpersonal diversity in usersʽ responses to early conceptual designs, and (b) the dynamics of usersʼ experiences over time. The Repertory Grid Technique is proposed as an alternative to standardized psychometric scales for modeling interpersonal diversity in usersʼ responses to early concepts in the design process, and new Multi-Dimensional Scaling procedures are introduced for modeling such complex quantitative data.

The Repertory Grid Technique is proposed as an alternative to standardized psychometric scales for modeling interpersonal diversity in usersʼ responses to early concepts in the design process, and new Multi-Dimensional Scaling procedures are introduced for modeling such complex quantitative data.

The purpose of the competition is to steer the research in the area of bilateral multi-issue, closed negotiation. For this book, we solicited papers on all aspects of such complex automated negotiations, which are studied in the field of Autonomous Agents and Multi-Agent Systems.

The purpose of the competition is to steer the research in the area of bilateral multi-issue, closed negotiation. ANAC is an international competition in which automated negotiation strategies, submitted by a number of universities and research institutes across the world, are evaluated in a tournament style.

This book discusses the modern advances in intelligent systems and the tools in applied artificial intelligence.. Each part includes three to five chapters. Intelligent systems provide a platform to connect the research in artificial intelligence to real-world problem solving applications.

Modern Advances in Intelligent Systems and Tools It consists of twenty-three chapters authored by participants of the 25th International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems (IEA/AIE 2012) which was held in Dalian, China. We hope that this book provides useful reference values to researchers and students in the field of applied intelligence. Each part includes three to five chapters. This book discusses the modern advances in intelligent systems and the tools in applied artificial intelligence.

The main goal of this book is to provide a state of the art of hybrid metaheuristics.

The main goal of this book is to provide a state of the art of hybrid metaheuristics. Hybrid Metaheuristics.Readers learn to solve large scale problems quickly and efficiently combining metaheuristics with complementary metaheuristics, mathematical programming, constraint programming and machine learning. The book provides a complete background that enables readers to design and implement hybrid metaheuristics to solve complex optimization problems (continuous/discrete, mono-objective/multi-objective, optimization under uncertainty) in a diverse range of application domains.

Metaheuristics are the more popular tools to this end, and then we can find in the book how to best use genetic algorithms, particle swarm, ant colonies, immune systems, variable neighborhood search, and many other bioinspired techniques. The book then covers theory and practice, as well as discrete versus continuous dynamic optimization, in the aim of creating a fresh and comprehensive volume. Metaheuristics for Dynamic Optimization This book is targeted to either beginners and experienced practitioners in dynamic  optimization, since we took care of devising the chapters in a way that a wide audience could profit from its contents. Also, neural network solutions are considered in this book.

Thus, this book is devoted to include several of the most important advances in solving dynamic problems.

In differentiated multicellular organisms, tremendous complexity has arisen in the course of evolution of life on earth. Computational Genetic Regulatory Networks: Evolvable, Self-organizing Systems In this volume an evolutionary GRN paradigm is investigated for its evolvability and robustness in models of biological clocks, in simple differentiated multicellularity, and in evolving artificial developing 'organisms' which grow and express an ontogeny starting from a single cell interacting with its environment, eventually including a changing local neighbourhood of other cells. Engineering and science have so far achieved no working system that can compare with this complexity, depth and scope of organization.

This book points out the potential application areas and provides detailed examples of application case studies in low-energy computational systems. The users of such systems, located at different (geographical or managerial) network cluster may have a limited access to the system’s services and resources, and different, often conflicting, expectations and requirements. An optimal energy utilization has reached to a point that many information technology (IT) managers and corporate executives are all up in arms to identify scalable solution that can reduce electricity consumption (so that the total cost of operation is minimized) of their respective large-scale computing systems and simultaneously improve upon or maintain the current throughput of the system.

Critical to both contributors and readers are the short publication time and world-wide distribution-this permits a rapid and broad dissemination of research results.  The intent is to cover the theory, applications, and design methods of computational intelligence, as embedded in the fields of engineering, computer science, physics and life science, as well as the methodologies behind them.

The development trends and open research issues are also outlined.

  The series contains monographs, lecture notes and edited volumes in computational intelligence spanning the areas of neural networks, connectionist systems, genetic algorithms, evolutionary computation, artificial intelligence, cellular automata, self-organizing systems, soft computing, fuzzy systems and hybrid intelligent systems.  The intent is to cover the theory, applications, and design methods of computational intelligence, as embedded in the fields of engineering, computer science, physics and life science, as well as the methodologies behind them.  The purpose of the 10th International Conference on Software Engineering Research, Management and Applications(SERA 2012) held on May 3- June 1, 2012 in Shanghai, China was to bring together scientists, engineers, computer users, and students to share their experiences and exchange new ideas and research results about all aspects (theory, applications and tools) of Software Engineering Research, Management and Applications, and to discuss the practical challenges encountered along the way and the solutions adopted to solve them.

Computer and Information Science 2012 Critical to both contributors and readers are the short publication time and world-wide distribution - this permits a rapid and broad dissemination of research results. The intent is to cover the theory, applications, and design methods of computational intelligence, as embedded in the fields of engineering, computer science, physics and life science, as well as the methodologies behind them.

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This is typically modeled by random graphs.   The field of Complex Networks has received a major boost caused by the widespread availability of huge network data resources in the last years.Complex Networks In the last decade we have seen the emergence of a new inter-disciplinary field concentrating on the understanding large networks which are dynamic, large, open, and have a structure that borders order and randomness. The field of Complex Networks has helped us better understand many complex phenomena such as spread of decease, protein interaction, social relationships, to name but a few.

Since year 2000, scientists on artificial and natural intelligences started to study chance discovery - methods for discovering events/situations that significantly affect decision making.   joined this field and interacted with cognitive/computational scientists in workshops on chance discovery, to obtain breakthroughs by stimulating each other. Second, basic technologies and sciences including sensor technologies, medical sciences, communication technologies etc.

.Complex Networks In the last decade we have seen the emergence of a new inter-disciplinary field concentrating on the understanding large networks which are dynamic, large, open, and have a structure that borders order and randomness.   The current theories coupled with the availability of data makes the field of Complex Networks (sometimes called Network Sciences) one of the most promising interdisciplinary disciplines of today. The field of Complex Networks has helped us better understand many complex phenomena such as spread of decease, protein interaction, social relationships, to name but a few.

Computational Genetic Regulatory Networks: Evolvable, Self-organizing Systems In this volume an evolutionary GRN paradigm is investigated for its evolvability and robustness in models of biological clocks, in simple differentiated multicellularity, and in evolving artificial developing 'organisms' which grow and express an ontogeny starting from a single cell interacting with its environment, eventually including a changing local neighbourhood of other cells.Genetic Regulatory Networks (GRNs) in biological organisms are primary engines for cells to enact their engagements with environments, via incessant, continually active coupling. Abstracting the dynamics of genetic regulatory control to a computational framework in which artificial GRNs in artificial simulated cells differentiate while connected in a changing topology, it is possible to apply Darwinian evolution in silico to study the capacity of such developmental/differentiated GRNs to evolve.

. The intent is to cover the theory, applications, and design methods of computational intelligence, as embedded in the fields of engineering, computer science, physics and life science, as well as the methodologies behind them.  The papers were chosen based on review scores submitted by members of the program committee, and underwent further rigorous rounds of review. The series contains monographs, lecture notes and edited volumes in computational intelligence spanning the areas of neural networks, connectionist systems, genetic algorithms, evolutionary computation, artificial intelligence, cellular automata, self-organizing systems, soft computing, fuzzy systems, and hybrid intelligent systems.

  The papers were chosen based on review scores submitted by members of the program committee, and underwent further rigorous rounds of review.. The intent is to cover the theory, applications, and design methods of computational intelligence, as embedded in the fields of engineering, computer science, physics and life science, as well as the methodologies behind them.

  The current theories coupled with the availability of data makes the field of Complex Networks (sometimes called Network Sciences) one of the most promising interdisciplinary disciplines of today.. Traditionally, real networks were supposed to have a majority of nodes of about the same number of connections around an average.

  joined this field and interacted with cognitive/computational scientists in workshops on chance discovery, to obtain breakthroughs by stimulating each other.Third, “time” came to be introduced explicitly as a significant variable ruling causalities - background situations causing chances and chances causing impacts on events and actions of humans in the future.g.

The field of Complex Networks has helped us better understand many complex phenomena such as spread of decease, protein interaction, social relationships, to name but a few.   The field of Complex Networks has received a major boost caused by the widespread availability of huge network data resources in the last years. Traditionally, real networks were supposed to have a majority of nodes of about the same number of connections around an average.

Abstracting the dynamics of genetic regulatory control to a computational framework in which artificial GRNs in artificial simulated cells differentiate while connected in a changing topology, it is possible to apply Darwinian evolution in silico to study the capacity of such developmental/differentiated GRNs to evolve. Engineering and science have so far achieved no working system that can compare with this complexity, depth and scope of organization.