Dear Sirs, dear Madams,

please find herein

the contents of the latest issue of the International Journal of Adaptive, Resilient and Autonomic Systems (IJARAS), guest edited by Prof. Andrew M. Tyrrell and Prof. Tempesti, York University; IJARAS’ latest call for paper; Information on the yearly book series Advances in Adaptive, Resilient and Autonomic Systems, which is to reprint all papers published in IJARAS' volumes.

For any questions regarding IJARAS and its Advanced Book Series please contact me through vincenzo.deflorio at ua.ac.be. Thank you very much.

Kind regards,

Vincenzo De Florio

The contents of the latest issue of:

International Journal of Adaptive, Resilient and Autonomic Systems (IJARAS)

Official Publication of the Information Resources Management Association

Volume 3, Issue 4, October - December 2012

Published: Quarterly in Print and Electronically

ISSN: 1947-9220 EISSN: 1947-9239

Published by IGI Publishing, Hershey-New York, USA

www.igi-global.com/ijaras

Guest editors: Prof. Andrew M. Tyrrell and Prof. Tempesti, York University

Editor-in-Chief: Vincenzo De Florio, University of Antwerp and IBBT, Belgium

PAPER ONE

Investigating Power Reduction for NoC-Based Spiking Neural Network Platforms using Channel Encoding

Neil McDonnell (School of Computing and Intelligent Systems, University of Ulster, Magee Campus, Northern Ireland, UK), Snaider Carrillo (School of Computing and Intelligent Systems, University of Ulster, Magee Campus, Northern Ireland, UK), Jim Harkin (School of Computing and Intelligent Systems, University of Ulster, Magee Campus, Northern Ireland, UK) and Liam McDaid (School of Computing and Intelligent Systems, University of Ulster, Magee Campus, Northern Ireland, UK)

Recent focus has been placed on exploring the possibility to switch from parallel to serial data links between NoC routers in order to improve signal integrity in the communication channel. However, moving streams of data between the parallel path of the internal router and external serial-channel links between them consumes additional power. One challenge is encoding the data and minimise the switching activity of data in the serial links in order to reduce the additional power dissipation; while under real-time and minimal hardware constraints. Consequently, proposed is a novel low area/power decision circuit for NoC channel encoding which identifies in real-time packets for encoding and extends the existing SILENT encoders/decoders to further minimise power consumption and demonstrates the power performance savings of the decision circuit and modified (en)decoders using example test traffic with the EMBRACE NoC router, a mixed signal spiking neural network (SNNs) embedded platform.

To obtain a copy of the entire article, click on the link below.

http://www.igi-global.com/article/investigating-power-reduction-noc-based/74...

To read a PDF sample of this article, click on the link below.

http://www.igi-global.com/viewtitlesample.aspx?id=74363&ptid=59552&t...

PAPER TWO

Compensating Resource Fluctuations by Means of Evolvable Hardware: The Run-Time Reconfigurable Functional Unit Row Classifier Architecture

Paul Kaufmann (Department of Computer Science, University of Paderborn, Paderborn, Germany), Kyrre Glette (University of Oslo, Norway), Marco Platzner (University of Paderborn, Paderborn, Germany) and Jim Torresen (University of Oslo, Norway)

The evolvable hardware (EHW) paradigm facilitates the construction of autonomous systems that can adapt to environmental changes and degradation of the computational resources. Extending the EHW principle to architectural adaptation, the authors study the capability of evolvable hardware classifiers to adapt to intentional run-time fluctuations in the available resources, i.e., chip area, in this work. To that end, the authors leverage the Functional Unit Row (FUR) architecture, a coarse-grained reconfigurable classifier, and apply it to two medical benchmarks, the Pima and Thyroid data sets from the UCI Machine Learning Repository. While quick recovery from architectural changes was already demonstrated for the FUR architecture, the authors also introduce two reconfiguration schemes helping to reduce the magnitude of degradation after architectural reconfiguration.

To obtain a copy of the entire article, click on the link below.

http://www.igi-global.com/article/compensating-resource-fluctuations-means-e...

To read a PDF sample of this article, click on the link below.

http://www.igi-global.com/viewtitlesample.aspx?id=74364&ptid=59552&t...

PAPER THREE

Automatic Machine Code Generation for a Transport Triggered Architecture using Cartesian Genetic Programming

James Alfred Walker (Department of Electronics, University of York, York, UK), Yang Liu (Department of Electronics, University of York, York, UK), Gianluca Tempesti (Department of Electronics, University of York, York, UK), Jon Timmis (Departments of Electronics and Computer Science, University of York, York, UK) and Andy M. Tyrrell (Department of Electronics, University of York, York, UK)

Transport triggered architectures are used for implementing bio-inspired systems due to their simplicity, modularity and fault-tolerance. However, producing efficient, optimised machine code for such architectures is extremely difficult, since computational complexity has moved from the hardware-level to the software-level. Presented is the application of Cartesian Genetic Programming (CGP) to the evolution of machine code for a simple implementation of transport triggered architecture. The effectiveness of the algorithm is demonstrated by evolving machine code for a 4-bit multiplier with three different levels of parallelism. The results show that 100% successful solutions were found by CGP and by further optimising the size of the solutions, it’s possible to find efficient implementations of the 4-bit multiplier. Further analysis of the solutions showed that use of loops within the CGP function set could be beneficial and was demonstrated by repeating the earlier 4-bit multiplier experiment with the addition of a loop function.

To obtain a copy of the entire article, click on the link below.

http://www.igi-global.com/article/automatic-machine-code-generation-transpor...

To read a PDF sample of this article, click on the link below.

http://www.igi-global.com/viewtitlesample.aspx?id=74365&ptid=59552&t...

PAPER FOUR

Multi-View Human Body Pose Estimation with CUDA-PSO

Luca Mussi (Henesis s.r.l., Parma, Italy), Spela Ivekovic (Department of Mechanical & Aerospace Engineering, University of Strathclyde, Glasgow, UK), Youssef S.G. Nashed (Department of Information Engineering, University of Parma, Parma, Italy) and Stefano Cagnoni (Department of Information Engineering, University of Parma, Parma, Italy)

The authors formulate the body pose estimation as a multi-dimensional nonlinear optimization problem, suitable to be approximately solved by a meta-heuristic, specifically, the particle swarm optimization (PSO). Starting from multi-view video sequences acquired in a studio environment, a full skeletal configuration of the human body is retrieved. They use a generic subdivision-surface body model in 3-D to generate solutions for the optimization problem. PSO then looks for the best match between the silhouettes generated by the projection of the model in a candidate pose and the silhouettes extracted from the original video sequence. The optimization method, in this case PSO, is run in parallel on the Graphics Processing Unit (GPU) and is implemented in Cuda-C™ on the nVidia CUDA™ architecture. The authors compare the results obtained by different configurations of the camera setup, fitness function, and PSO neighborhood topologies.

To obtain a copy of the entire article, click on the link below.

http://www.igi-global.com/article/multi-view-human-body-pose/74366

To read a PDF sample of this article, click on the link below.

http://www.igi-global.com/viewtitlesample.aspx?id=74366&ptid=59552&t...

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For full copies of the above articles, check for this issue of the International Journal of Adaptive, Resilient and Autonomic Systems (IJARAS) in your institution's library. This journal is also included in the IGI Global aggregated "InfoSci-Journals" database: http://www.igi-global.com/eresources/infosci-journals.aspx.

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CALL FOR PAPERS

The International Journal of Adaptive, Resilient and Autonomic Systems (IJARAS) examines systems and organizations characterized by the following two properties: the ability to self-adapt to the characteristics of rapidly changing and turbulent environments by adopting complex individual and social strategies and the ability to control their changes to prevent the invalidation of their original mission statements. The central focus of IJARAS is on modeling, simulating, designing, developing, maintaining, evaluating, and benchmarking such “entelechial systems”. Perception, awareness, and the planning and execution of resilient adaptation behaviors in systems and organizations are central topics of the journal. Such systems range from individual and simple embedded systems with limited perception and predefined specialized behaviors to complex hybrid social organizations like cyber-physical societies or service-oriented communities, whose emerging behaviors are many and, in some cases, difficult to predict. IJARAS focuses on the full spectrum of these problems providing academicians, practitioners, and researchers with awareness and insight on conceptual models, applied and theoretical approaches, paradigms, and other technological innovations on self-adaptive and/or self-resilient systems and organizations of any scale and nature.

Mission

Society is currently experiencing the increasing population of “things,” able to autonomously link with each other and enact complex strategies to achieve tasks. The emergence of the Semantic Web, the Internet-of-Things, Ambient Intelligence, and cyber-physical societies make it impossible to capture the intricacies of the future highly dynamic and turbulent networks of interrelated computer-based and hybrid components. As such, it is important that systems are designed to self-adapt to changes without diverging from their intended functions as prescribed in their specifications. The mission of the International Journal of Adaptive, Resilient and Autonomic Systems (IJARAS) is to offer awareness and visibility to novel techniques and methods to achieve self-adaptability and self-resilience when systems and organizations are deployed in environments where change is the rule rather than the exception. IJARAS is also a tool to enhance the awareness of the key role played by said techniques and methods: engineering self-adaptive and self-resilient systems and organizations is an urgent necessity to keep society resilient in the face of the technology that sustains it. The journal pursues its mission by addressing researchers, practitioners, engineers, educators, and professionals and by publishing novel results on each of the diverse components of such a complex and multi-disciplinary research problem.

Topics Covered

Topics to be discussed in this journal include (but are not limited to) the following:

- Adaptive data integrity

- Adaptive fault-tolerance

- Analytical and simulation tools to measure a system’s ability to withstand faults and

optimally re-adjust to new environments

- Architecture-based adaptation

- Autonomic applications

- Autonomous and adaptive systems in robotics

- Biologically inspired mechanisms to enact complex adaptation strategies

- Collective strategies for adaptation and resilience, including cooperation, competition,

co-opetition, co-innovation, and co-evolution

- Complex adaptive-and-resilient systems and organizations

- Context- and situation-awareness

- Design-time/run-time methods and tools to identify and enforce optimal trade-offs between

energy consumption, performance, safety, and security

- Dynamics of complex adaptive and resilient systems and organizations

- Human aspects

- Evolutionary approaches to autonomic computing, resilience, and adaptive systems

- Mechanisms to model, design, express, and develop adaptive, autonomic, and resilient

systems

- Methods to express resilience (e.g., resilience policies and contracts)

- Perception and introspection capabilities

- Personalization

- Quality of experience

- Recovery-oriented computing

- Resilient adaptation behavior composition

- Resilient adaptation planning

- Resilience and adaptation in management science

- Resilience engineering

- Role of diversity in the emergence of survivability, innovability, value capture, etc.

- Role of organizations on the emergence of adaptation and resilience: heterarchies,

holarchies, fractal social organizations, etc.

- Scalable, maintainable, and cost-effective provisions located at all system levels

to achieve adaptability and dependability

- Self-adaptive and self-resilient systems: models, design, development, maintenance,

evaluation, and benchmarking issues

- Software elasticity: techniques, tools, and approaches to absorb and tolerate the

consequences of failures, attacks, and changes within and without system boundaries

Submissions and enquiries:

All inquiries and submissions should be sent to:

Editor-in-Chief: Vincenzo De Florio at vincenzo.deflorio@gmail.com; vincenzo.deflorio@ua.ac.be

For enquiries please contact the editor in chief

Advanced Book Series:

- An Advances Book Series is now associated with IJARAS: Advances in Adaptive, Resilient and Autonomic Systems (AARAS). All papers published in IJARAS will also appear (possibly extended) as chapters in the volumes in this series. The first volume of this series is available from March 2012 as "Technological Innovations in Adaptive and DependableSystems: Advancing Models and Concepts" and may be ordered fromhttp://www.igi-global.com/book/technological-innovations-adaptive-dependable.... A second volume, entitled "Innovations and Approaches for Resilient and Adaptive Systems," is available from September 2012 and may be ordered from http://www.igi-global.com/book/innovations-approaches-resilient-adaptive-sys...

For enquiries please contact the editor in chief through vincenzo.deflorio at ua.ac.be.