The realization of service-oriented e-Marketplaces

Electronic Marketplaces (or e-Marketplaces) require technologies which provide support for the adaptability, flexibility and the integration of business applications in order to meet rapid changes in business environment. Traditional web technologies are unable to meet the new business requirements which are derived from the rapid growth of e-Marketplaces. In this research, a service-oriented framework is proposed in order to address the issues associated with the development of e-Marketplaces. Specifically, it introduces a generic trading model oriented to e-Marketplaces so as to overcome the inadequacy of existing models and to facilitate the development of a computational trading process. In the proposed framework, required services are identified through the utilization of the business-centric trading model. Using a service metamodel, services are equipped with intelligence such that they work seamlessly and coherently within and across e-Marketplaces. A multi-model driven integrated development platform has been developed to support the proposed models and framework. The proposed framework and concepts have been validated through a case study of a mutual funds auction in an e-Marketplace.

Ethical regulations on robotics in Europe

There are only a few ethical regulations that deal explicitly with robots, in contrast to a vast number of regulations, which may be applied. We will focus on ethical issues with regard to “responsibility and autonomous robots”, “machines as a replacement for humans”, and “tele-presence”. Furthermore we will examine examples from special fields of application (medicine and healthcare, armed forces, and entertainment). We do not claim to present a complete list of ethical issue nor of regulations in the field of robotics, but we will demonstrate that there are legal challenges with regard to these issues.

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Understanding and capturing people’s privacy policies in a mobile social networking application

A number of mobile applications have emerged that allow users to locate one another. However, people have expressed concerns about the privacy implications associated with this class of software, suggesting that broad adoption may only happen to the extent that these concerns are adequately addressed. In this article, we report on our work on PeopleFinder, an application that enables cell phone and laptop users to selectively share their locations with others (e.g. friends, family, and colleagues). The objective of our work has been to better understand people’s attitudes and behaviors towards privacy as they interact with such an application, and to explore technologies that empower users to more effectively and efficiently specify their privacy preferences (or “policies”). These technologies include user interfaces for specifying rules and auditing disclosures, as well as machine learning techniques to refine user policies based on their feedback. We present evaluations of these technologies in the context of one laboratory study and three field studies.

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Method of design and specification of web services based on quality system documentation

In this paper, we present a method for development and specification of web services based on the quality system documentation. The general assumption is that service oriented architecture is based on business services and these business services mostly correspond to exchanged documentation in a real business system. Documentation of a quality system is recognized in form of documents that describe business processes in a real business system and identify exchanged documentation with environment. Presented method uses documentation of quality system and documentation flow for web service specification. We developed the CASE tool for web service specification based on a new approach, and we compare it to other existing tools.

Performance of the MAP/G/1 Queue Under the Dyadic Control of Workload and Server Idleness

This paper studies the steady-state queue length process of the MAP/G/1 queue under the dyadic control of the D-policy and multiple server vacations. We derive the probability generating function of the queue length and the mean queue length. We then present computational experiences and compare the MAP queue with the Poisson queue.

Model-based mapping of reconfigurable image registration on FPGA platforms

Image registration is a computationally intensive application in the medical imaging domain that places stringent requirements on performance and memory management efficiency. This paper develops techniques for mapping rigid image registration applications onto configurable hardware under real-time performance constraints. Building on the framework of homogeneous parameterized dataflow, which provides an effective formal model of design and analysis of hardware and software for signal processing applications, we develop novel methods for representing and exploring the hardware design space when mapping image registration algorithms onto configurable hardware. Our techniques result in an efficient framework for trading off performance and configurable hardware resource usage based on the constraints of a given application. Based on trends that we have observed when applying these techniques, we also present a novel architecture that enables dynamically-reconfigurable image registration. This proposed architecture has the ability to tune its parallel processing structure adaptively based on relevant characteristics of the input images.

Exploring interoperability of language resources: the case of cross-lingual semi-automatic enrichment of wordnets

In this paper we present an application fostering the integration and interoperability of computational lexicons, focusing on the particular case of mutual linking and cross-lingual enrichment of two wordnets, the ItalWordNet and Sinica BOW lexicons. This is intended as a case-study investigating the needs and requirements of semi-automatic integration and interoperability of lexical resources, in the view of developing a prototype web application to support the GlobalWordNet Grid initiative.

A theoretical investigation of the emerging standards for web services

Currently, standards for web services are being developed via three different initiatives (W3C, Semantic web services and ebXML). To the best of our knowledge, no theoretical perspectives underlie these standardization efforts. Without the benefit of a strong theoretical basis, the results, within and across these initiatives, have remained piecemeal. We suggest ‘Language–Action Theories’ as a plausible perspective that can effectively define, assess and refine web services standards. In this paper, we first investigate the existing initiatives to identify commonalities that point to theories of ‘Language–Action’ as an appropriate theoretical basis for web services standards. Next, we adapt work from these theories to develop a comprehensive reference framework for understanding web services standards. Finally, we use this reference framework to assess the three initiatives, and analyze the findings to provide insights for future development and refinement of web services standards.

The 2007 IEEE CEC simulated car racing competition

This paper describes the simulated car racing competition that was arranged as part of the 2007 IEEE Congress on Evolutionary Computation. Both the game that was used as the domain for the competition, the controllers submitted as entries to the competition and its results are presented. With this paper, we hope to provide some insight into the efficacy of various computational intelligence methods on a well-defined game task, as well as an example of one way of running a competition. In the process, we provide a set of reference results for those who wish to use the simplerace game to benchmark their own algorithms. The paper is co-authored by the organizers and participants of the competition.

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M-CASH: A real-time resource reclaiming algorithm for multiprocessor platforms

Resource reclaiming schemes are typically applied in reservation-based real-time uniprocessor systems to support efficient reclaiming and sharing of computational resources left unused by early completing tasks, improving the response times of aperiodic and soft tasks in the presence of overruns. In this paper, we introduce a novel and efficient reclaiming algorithm, named M-CASH, for multiprocessor platforms. M-CASH leverages the resource reservation approach offered by the Multiprocessor CBS server offering significant improvements. The correctness of the algorithm is formally proven and its performance is evaluated through extensive synthetic simulations.

ONTRACK: Dynamically adapting music playback to support navigation

Listening to music on personal, digital devices whilst mobile is an enjoyable, everyday activity. We explore a scheme for exploiting this practice to immerse listeners in navigation cues. Our prototype, ONTRACK, continuously adapts audio, modifying the spatial balance and volume to lead listeners to their target destination. First we report on an initial lab-based evaluation that demonstrated the approach’s efficacy: users were able to complete tasks within a reasonable time and their subjective feedback was positive. Encouraged by these results we constructed a handheld prototype. Here, we discuss this implementation and the results of field-trials. These indicate that even with a low-fidelity realisation of the concept, users can quite effectively navigate complicated routes.

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Multimodal support to group dynamics

The complexity of group dynamics occurring in small group interactions often hinders the performance of teams. The availability of rich multimodal information about what is going on during the meeting makes it possible to explore the possibility of providing support to dysfunctional teams from facilitation to training sessions addressing both the individuals and the group as a whole. A necessary step in this direction is that of capturing and understanding group dynamics. In this paper, we discuss a particular scenario, in which meeting participants receive multimedia feedback on their relational behaviour, as a first step towards increasing self-awareness. We describe the background and the motivation for a coding scheme for annotating meeting recordings partially inspired by the Bales’ Interaction Process Analysis. This coding scheme was aimed at identifying suitable observable behavioural sequences. The study is complemented with an experimental investigation on the acceptability of such a service.

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Efficient Detection of Patterns in 2D Trajectories of Moving Points

Moving point object data can be analyzed through the discovery of patterns in trajectories. We consider the computational efficiency of detecting four such spatio-temporal patterns, namely flock, leadership, convergence, and encounter, as defined by Laube et al., Finding REMO—detecting relative motion patterns in geospatial lifelines, 201–214, (2004). These patterns are large enough subgroups of the moving point objects that exhibit similar movement in the sense of direction, heading for the same location, and/or proximity. By the use of techniques from computational geometry, including approximation algorithms, we improve the running time bounds of existing algorithms to detect these patterns.

Interacting with mobile services: an evaluation of camera-phones and visual tags

We present a study of using camera-phones and visual-tags to access mobile services. Firstly, a user-experience study is described in which participants were both observed learning to interact with a prototype mobile service and interviewed about their experiences. Secondly, a pointing-device task is presented in which quantitative data was gathered regarding the speed and accuracy with which participants aimed and clicked on visual-tags using camera-phones. We found that participants’ attitudes to visual-tag-based applications were broadly positive, although they had several important reservations about camera-phone technology more generally. Data from our pointing-device task demonstrated that novice users were able to aim and click on visual-tags quickly (well under 3 s per pointing-device trial on average) and accurately (almost all meeting our defined speed/accuracy tradeoff of 6% error-rate). Based on our findings, design lessons for camera-phone and visual-tag applications are presented.

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Legal safeguards for privacy and data protection in ambient intelligence

To get the maximum benefit from ambient intelligence (AmI), we need to anticipate and react to possible drawbacks and threats emerging from the new technologies in order to devise appropriate safeguards. The SWAMI project took a precautionary approach in its exploration of the privacy risks in AmI and sought ways to reduce them. It constructed four “dark scenarios” showing possible negative implications of AmI, notably for privacy protection. Legal analysis of the depicted futures showed the shortcomings of the current legal framework in being able to provide adequate privacy protection in the AmI environment. In this paper, the authors, building upon their involvement in SWAMI research as well as the further advancement of EU privacy analysis, identify various outstanding issues regarding the legal framework that still need to be resolved in order to deal with AmI in an equitable and efficacious way. This article points out some of the lacunae in the legal framework and postulates several privacy-specific safeguards aimed at overcoming them.

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An exploratory study for analyzing interactional processes of group discussion: the case of a focus group interview

The purposes of this study are (a) to establish a measurement for evaluating conversational impressions of group discussions, and (b) to make an exploratory investigation on their interactional processes which may affect to form those impressions. The impression rating and factor analysis undertaken first give us four factors concerning conversational impressions of “focus group interviews (FGIs)”: conversational activeness, conversational sequencing, the attitudes of participants and the relationships of participants. In relation to the factors of conversational activeness and conversational sequencing in particular, the microanalysis of four selected topical scenes from our database further shows that the behavior of the moderator and the interviewees is organized not independently but with reference to each other. The study thus emphasizes the importance of the integration of quantitative and qualitative approaches towards human interactions.

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Evolving strategy for a probabilistic game of imperfect information using genetic programming

We provide the complete record of methodology that let us evolve BrilliAnt, the winner of the Ant Wars contest. Ant Wars contestants are virtual ants collecting food on a grid board in the presence of a competing ant. BrilliAnt has been evolved through a competitive one-population coevolution using genetic programming and fitnessless selection. In this paper, we detail the evolutionary setup that lead to BrilliAnt’s emergence, assess its direct and indirect human-competitiveness, and describe the behavioral patterns observed in its strategy.

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The load balancing problem in OTIS-Hypercube interconnection networks

An interconnection network architecture that promises to be an interesting option for future-generation parallel processing systems is the OTIS (Optical Transpose Interconnection System) optoelectronic architecture. Therefore, all performance improvement aspects of such a promising architecture need to be investigated; one of which is load balancing technique. This paper focuses on devising an efficient algorithm for load balancing on the promising OTIS-Hypercube interconnection networks. The proposed algorithm is called Clusters Dimension Exchange Method (CDEM). The analytical model and the experimental evaluation proved the excellence of OTIS-Hypercube compared to Hypercube in terms of various parameters, including execution time, load balancing accuracy, number of communication steps, and speed.

Inverse multi-objective robust evolutionary design

In this paper, we present an Inverse Multi-Objective Robust Evolutionary (IMORE) design methodology that handles the presence of uncertainty without making assumptions about the uncertainty structure. We model the clustering of uncertain events in families of nested sets using a multi-level optimization search. To reduce the high computational costs of the proposed methodology we proposed schemes for (1) adapting the step-size in estimating the uncertainty, and (2) trimming down the number of calls to the objective function in the nested search. Both offline and online adaptation strategies are considered in conjunction with the IMORE design algorithm. Design of Experiments (DOE) approaches further reduce the number of objective function calls in the online adaptive IMORE algorithm. Empirical studies conducted on a series of test functions having diverse complexities show that the proposed algorithms converge to a set of Pareto-optimal design solutions with non-dominated nominal and robustness performances efficiently.

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