Parametric probabilistic transition systems for system design and analysis

We develop a model of parametric probabilistic transition Systems (PPTSs), where probabilities associated with transitions may be parameters. We show how to find instances of the parameters that satisfy a given property and instances that either maximize or minimize the probability of reaching a certain state. As an application, we model a probabilistic non-repudiation protocol with a PPTS. The theory we develop allows us to find instances that maximize the probability that the protocol ends in a fair state (no participant has an advantage over the others). A preliminary version of this paper was presented at SEFM’04 [LMT04]. 05 April 2006     

Combining electrodermal responses and cardiovascular measures for probing adaptive automation during simulated flight

Adaptive automation increases the operator's workload in case of hypovigilance and takes over more responsibility if workload becomes too high. Two consecutive studies were conducted to construct a biocybernetic adaptive system for a professional flight simulator, based on autonomic measures. Workload was varied through different stages of turbulences. In a first study with 18 participants, electrodermal responses of experimental subjects oscillated very close to the individual set point, demonstrating that workload level was adjusted as a result of adaptive control, which was not the case in yoked control subjects without adaptive automation. Combining electrodermal responses with heart rate variability in a second study with 48 participants further enhanced the adaptive power which was seen in even smaller set point deviations for the experimental compared to the yoked control group. We conclude that the level of arousal can be adjusted to avoid hypovigilance by combining autonomic measures in a closed loop.     

Development and evaluation of a virtual campus on Second Life: The case of SecondDMI

Video games and new communication metaphors are quickly changing today’s young people habits. Considering the actual e-learning scenarios, embedded in a fully technological enabled environment it is crucial to take advantage of this kind of capabilities to let learning process gain best results.     

Quality of Service Networking for High Performance Grid Applications

This paper reports on different efforts to provide quality of service (QoS) Networking to Grid applications done in the context of the MB-NG, GRS and DataTAG EU projects. These are leading edge network research projects involving more that 50 researchers in the UK, Europe and North America, concerned with the development and testing of protocols and standards for the next generation of high speed networks. We have implemented and tested the Differentiated Services Architecture (DiffServ) in a multi-domain, 2.5 Gbits/s network (the first such deployment) defining appropriate Service Level Agreements (SLAs) to be used between administrative domains to guarantee end-to-end Quality of Service. We characterised several hardware implementations of DiffServ and concluded on their appropriateness for several network scenarios. Since current and future Grid applications will have to use modified mechanisms of congestion control we have evaluated old and new TCP implementations over a Differentiated Services Networks. These quality of service tests have also included innovative MPLS (Multi-Protocol Label Switching) experiments to establish guaranteed bandwidth connections to Grid applications in a fast and efficient way. We have also developed a software based bandwidth broker architecture for Grids based on IETF standards which allows applications to transparently request dynamic and advanced reservations and implemented it in a real experimental network. We finally report on experiences delivering Quality of Service networking to high performance applications like Particle Physics data transfer and High Performance Computation. This includes quantitative results on the performance improvements that QoS brought to real data transfers in the context of High Performance Computing.     

A low-power wireless video sensor node for distributed object detection

In this paper we propose MicrelEye, a wireless video node for cooperative distributed video processing applications that involve image classification. The node is equipped with a low-cost VGA CMOS image sensor, a reconfigurable processing engine (FPGA, Microcontroller, SRAM) and a Bluetooth 100-m transceiver. It has a size of few cubic centimeters and its typical power consumption is approximately ten times less than that of typical commercial DSP-based solutions. As regards classification, a highly optimized hardware-oriented support vector machine-like (SVM-like) algorithm called ERSVM is proposed and implemented. We describe our hardware and software architecture, its performance and power characteristics. The case study considered in this paper is people detection. The obtained results suggest that the present technology allows for the design of simple intelligent video nodes capable of performing classification tasks locally.

Environment as a first class abstraction in multiagent systems

The current practice in multiagent systems typically associates the environment with resources that are external to agents and their communication infrastructure. Advanced uses of the environment include infrastructures for indirect coordination, such as digital pheromones, or support for governed interaction in electronic institutions. Yet, in general, the notion of environment is not well defined. Functionalities of the environment are often dealt with implicitly or in an ad hoc manner. This is not only poor engineering practice, it also hinders engineers to exploit the full potential of the environment in multiagent systems. In this paper, we put forward the environment as an explicit part of multiagent systems.We give a definition stating that the environment in a multiagent system is a first-class abstraction with dual roles: (1) the environment provides the surrounding conditions for agents to exist, which implies that the environment is an essential part of every multiagent system, and (2) the environment provides an exploitable design abstraction for building multiagent system applications. We discuss the responsibilities of such an environment in multiagent systems and we present a reference model for the environment that can serve as a basis for environment engineering. To illustrate the power of the environment as a design abstraction, we show how the environment is successfully exploited in a real world application. Considering the environment as a first-class abstraction in multiagent systems opens up new horizons for research and development in multiagent systems.     

Molecular dynamics at the receptor level of immunodominant myelin basic protein epitope 87-99 implicated in multiple sclerosis and its antagonists altered peptide ligands: triggering of immune response

This work reports molecular dynamics studies at the receptor level of the immunodominant myelin basic protein (MBP) epitope 87-99 implicated in multiple sclerosis, and its antagonists altered peptide ligands (APLs), namely [Arg91, Ala96] MBP87-99 and [Ala91,96] MBP87-99. The interaction of each peptide ligand with the receptor human leukocyte antigen HLA-DR2b was studied, starting from X-ray structure with pdb code: 1ymm. This is the first such study of APL-HLA-DR2b complexes, and hence the first attempt to gain a better understanding of the molecular recognition mechanisms that underlie TCR antagonism by these APLs. The amino acids His88 and Phe89 serve as T-cell receptor (TCR) anchors in the formation of the trimolecular complex TCR-peptide-HLA-DR2b, where the TCR binds in a diagonal, off-centered mode to the peptide-HLA complex. The present findings indicate that these two amino acids have a different orientation in the APLs [Arg91, Ala96] MBP87-99 and [Ala91,96] MBP87-99: His88 and Phe89 remain buried in HLA grooves and are not available for interaction with the TCR. We propose that this different topology could provide a possible mechanism of action for TCR antagonism.     

Survey on using constraints in data mining

This paper provides an overview of the current state-of-the-art on using constraints in knowledge discovery and data mining. The use of constraints in a data mining task requires specific definition and satisfaction tools during knowledge extraction. This survey proposes three groups of studies based on classification, clustering and pattern mining, whether the constraints are on the data, the models or the measures, respectively. We consider the distinctions between hard and soft constraint satisfaction, and between the knowledge extraction phases where constraints are considered. In addition to discussing how constraints can be used in data mining, we show how constraint-based languages can be used throughout the data mining process.