Securing dynamic itineraries for mobile agent applications

In this paper we present a novel mechanism for the protection of dynamic itineraries for mobile agent applications. Itineraries that are decided as the agent goes are essential in complex applications based on mobile agents, but no approach has been presented until now to protect them. We have conceived a cryptographic scheme for shielding dynamic itineraries from tampering, impersonation and disclosure. By using trust strategically, our scheme provides a balanced trade-off between flexibility and security. Our protection scheme has been thought always bearing in mind a feasible implementation, and thus facilitates the development of applications that make use of it. An example application based on a real healthcare scenario is also presented to show its operation.

Automatic Decision-Oriented Mapping of Pollution Data

The paper deals with the development and application of the methodology for automatic mapping of pollution/contamination data. General Regression Neural Network (GRNN) is considered in detail and is proposed as an efficient tool to solve this problem. The automatic tuning of isotropic and an anisotropic GRNN model using cross-validation procedure is presented. Results are compared with k-nearest-neighbours interpolation algorithm using independent validation data set. Quality of mapping is controlled by the analysis of raw data and the residuals using variography. Maps of probabilities of exceeding a given decision level and ?thick? isoline visualization of the uncertainties are presented as examples of decision-oriented mapping. Real case study is based on mapping of radioactively contaminated territories.

Description of a robotics-oriented relational positioning methodology

This paper presents a relational positioning methodology for flexibly and intuitively specifying offline programmed robot tasks, as well as for assisting the execution of teleoperated tasks demanding precise movements.In relational positioning, the movements of an object can be restricted totally or partially by specifying its allowed positions in terms of a set of geometric constraints. These allowed positions are found by means of a 3D sequential geometric constraint solver called PMF – Positioning Mobile with respect to Fixed. PMF exploits the fact that in a set of geometric constraints, the rotational component can often be separated from the translational one and solved independently.

A programming environment having three levels of complexity for mobile robotics = Entorno de programación con tres niveles de complejidad para robótica móvil

This paper presents a programming environment for supporting learning in STEM, particularly mobile robotic learning. It was designed to maintain progressive learning for people with and without previous knowledge of programming and/or robotics. The environment was multi platform and built with open source tools. Perception, mobility, communication, navigation and collaborative behaviour functionalities can be programmed for different mobile robots. A learner is able to programme robots using different programming languages and editor interfaces: graphic programming interface (basic level), XML-based meta language (intermediate level) or ANSI C language (advanced level). The environment supports programme translation transparently into different languages for learners or explicitly on learners’ demand. Learners can access proposed challenges and learning interfaces by examples. The environment was designed to allow characteristics such as extensibility, adaptive interfaces, persistence and low software/hardware coupling. Functionality tests were performed to prove programming environment specifications. UV BOT mobile robots were used in these tests

Fetal programming of pulmonary vascular dysfunction in mice: role of epigenetic mechanisms.

Insults during the fetal period predispose the offspring to systemic cardiovascular disease, but little is known about the pulmonary circulation and the underlying mechanisms. Maternal undernutrition during pregnancy may represent a model to investigate underlying mechanisms, because it is associated with systemic vascular dysfunction in the offspring in animals and humans. In rats, restrictive diet during pregnancy (RDP) increases oxidative stress in the placenta. Oxygen species are known to induce epigenetic alterations and may cross the placental barrier. We hypothesized that RDP in mice induces pulmonary vascular dysfunction in the offspring that is related to an epigenetic mechanism. To test this hypothesis, we assessed pulmonary vascular function and lung DNA methylation in offspring of RDP and in control mice at the end of a 2-wk exposure to hypoxia. We found that endothelium-dependent pulmonary artery vasodilation in vitro was impaired and hypoxia-induced pulmonary hypertension and right ventricular hypertrophy in vivo were exaggerated in offspring of RDP. This pulmonary vascular dysfunction was associated with altered lung DNA methylation. Administration of the histone deacetylase inhibitors butyrate and trichostatin A to offspring of RDP normalized pulmonary DNA methylation and vascular function. Finally, administration of the nitroxide Tempol to the mother during RDP prevented vascular dysfunction and dysmethylation in the offspring. These findings demonstrate that in mice undernutrition during gestation induces pulmonary vascular dysfunction in the offspring by an epigenetic mechanism. A similar mechanism may be involved in the fetal programming of vascular dysfunction in humans.

Python as a programming language for the introductory programming courses

Tämä kandidaatintyö tutkii tietotekniikan perusopetuksessa keskeisen aiheen,ohjelmoinnin, alkeisopetusta ja siihen liittyviä ongelmia. Työssä perehdytään ohjelmoinnin perusopetusmenetelmiin ja opetuksen lähestymistapoihin, sekä ratkaisuihin, joilla opetusta voidaan tehostaa. Näitä ratkaisuja työssä ovat mm. ohjelmointikielen valinta, käytettävän kehitysympäristön löytäminen sekä kurssia tukevien opetusapuvälineiden etsiminen. Lisäksi kurssin läpivientiin liittyvien toimintojen, kuten harjoitusten ja mahdollisten viikkotehtävien valinta kuuluu osaksitätä työtä. Työ itsessään lähestyy aihetta tutkimalla Pythonin soveltuvuutta ohjelmoinnin alkeisopetukseen mm. vertailemalla sitä muihin olemassa oleviin yleisiin opetuskieliin, kuten C, C++ tai Java. Se tarkastelee kielen hyviä ja huonoja puolia, sekä tutkii, voidaanko Pythonia hyödyntää luontevasti pääasiallisena opetuskielenä. Lisäksi työ perehtyy siihen, mitä kaikkea kurssilla tulisi opettaa, sekä siihen, kuinka kurssin läpivienti olisi tehokkainta toteuttaa ja minkälaiset tekniset puitteet kurssin toteuttamista varten olisi järkevää valita.

Étude et implémentation d'un modèle de conscience d'agent

La thèse essaie de montrer comment il est possible d'offrir une implémentation fonctionnelle d'un agent doté d'une conscience (psychologique). Une première étape étudie les différentes approches, définitions et théories de la conscience proposées par la littérature. Cette étude dégage plus particulièrement un modèle psychologique qui offre une modélisation des fonctionnalités de la conscience, de ses éléments constitutifs et des relations entre ces éléments. Cet effort de formalisation permet d'identifier les corrélations computionnelles du modèle ouvrant ainsi la voie à une implémentation fonctionnelle de la conscience. Une seconde étape réuni les outils et méthodes informatiques existants en vue de procéder à une telle implémentation. En particulier, celle-ci repose sur un modèle de communication permettant d'élaborer une machine virtuelle basée sur des processus concurrents synchronisés. La troisième étape consiste à implémenter les corrélations computationnelles dont l'une est une fonction de délibération qui, après une analyse itérative de son état et de son environnement (machine à état), aboutit à la sélection d'une action. Une deuxième fonction est la formation de contextes, autrement dit l'apprentissage d'automatismes, consistant à compiler la délibération. Cette compilation s'opère grâce à un processus concurrent reflétant le processus de délibération, dotant ainsi l'agent de la capacité d'observer son propre fonctionnement. La thèse se conclut en proposant quelques axes de recherches et d'applications futures susceptibles de prolonger le travail.

Emergence of oriented circuits driven by synaptic pruning associated with spike-timing-dependent plasticity (STDP)

ABSTRACT: Massive synaptic pruning following over-growth is a general feature of mammalian brain maturation. Pruning starts near time of birth and is completed by time of sexual maturation. Trigger signals able to induce synaptic pruning could be related to dynamic functions that depend on the timing of action potentials. Spike-timing-dependent synaptic plasticity (STDP) is a change in the synaptic strength based on the ordering of pre- and postsynaptic spikes. The relation between synaptic efficacy and synaptic pruning suggests that the weak synapses may be modified and removed through competitive "learning" rules. This plasticity rule might produce the strengthening of the connections among neurons that belong to cell assemblies characterized by recurrent patterns of firing. Conversely, the connections that are not recurrently activated might decrease in efficiency and eventually be eliminated. The main goal of our study is to determine whether or not, and under which conditions, such cell assemblies may emerge out of a locally connected random network of integrate-and-fire units distributed on a 2D lattice receiving background noise and content-related input organized in both temporal and spatial dimensions. The originality of our study stands on the relatively large size of the network, 10,000 units, the duration of the experiment, 10E6 time units (one time unit corresponding to the duration of a spike), and the application of an original bio-inspired STDP modification rule compatible with hardware implementation. A first batch of experiments was performed to test that the randomly generated connectivity and the STDP-driven pruning did not show any spurious bias in absence of stimulation. Among other things, a scale factor was approximated to compensate for the network size on the ac¬tivity. Networks were then stimulated with the spatiotemporal patterns. The analysis of the connections remaining at the end of the simulations, as well as the analysis of the time series resulting from the interconnected units activity, suggest that feed-forward circuits emerge from the initially randomly connected networks by pruning. RESUME: L'élagage massif des synapses après une croissance excessive est une phase normale de la ma¬turation du cerveau des mammifères. L'élagage commence peu avant la naissance et est complété avant l'âge de la maturité sexuelle. Les facteurs déclenchants capables d'induire l'élagage des synapses pourraient être liés à des processus dynamiques qui dépendent de la temporalité rela¬tive des potentiels d'actions. La plasticité synaptique à modulation temporelle relative (STDP) correspond à un changement de la force synaptique basé sur l'ordre des décharges pré- et post- synaptiques. La relation entre l'efficacité synaptique et l'élagage des synapses suggère que les synapses les plus faibles pourraient être modifiées et retirées au moyen d'une règle "d'appren¬tissage" faisant intervenir une compétition. Cette règle de plasticité pourrait produire le ren¬forcement des connexions parmi les neurones qui appartiennent à une assemblée de cellules caractérisée par des motifs de décharge récurrents. A l'inverse, les connexions qui ne sont pas activées de façon récurrente pourraient voir leur efficacité diminuée et être finalement éliminées. Le but principal de notre travail est de déterminer s'il serait possible, et dans quelles conditions, que de telles assemblées de cellules émergent d'un réseau d'unités integrate-and¬-fire connectées aléatoirement et distribuées à la surface d'une grille bidimensionnelle recevant à la fois du bruit et des entrées organisées dans les dimensions temporelle et spatiale. L'originalité de notre étude tient dans la taille relativement grande du réseau, 10'000 unités, dans la durée des simulations, 1 million d'unités de temps (une unité de temps correspondant à une milliseconde), et dans l'utilisation d'une règle STDP originale compatible avec une implémentation matérielle. Une première série d'expériences a été effectuée pour tester que la connectivité produite aléatoirement et que l'élagage dirigé par STDP ne produisaient pas de biais en absence de stimu¬lation extérieure. Entre autres choses, un facteur d'échelle a pu être approximé pour compenser l'effet de la variation de la taille du réseau sur son activité. Les réseaux ont ensuite été stimulés avec des motifs spatiotemporels. L'analyse des connexions se maintenant à la fin des simulations, ainsi que l'analyse des séries temporelles résultantes de l'activité des neurones, suggèrent que des circuits feed-forward émergent par l'élagage des réseaux initialement connectés au hasard.

CISNE-P: a global scheduling oriented to NOW environments

In this work, we present an integral scheduling system for non-dedicated clusters, termed CISNE-P, which ensures the performance required by the local applications, while simultaneously allocating cluster resources to parallel jobs. Our approach solves the problem efficiently by using a social contract technique. This kind of technique is based on reserving computational resources, preserving a predetermined response time to local users. CISNE-P is a middleware which includes both a previously developed space-sharing job scheduler and a dynamic coscheduling system, a time sharing scheduling component. The experimentation performed in a Linux cluster shows that these two scheduler components are complementary and a good coordination improves global performance significantly. We also compare two different CISNE-P implementations: one developed inside the kernel, and the other entirely implemented in the user space.

Formalizing argumentative reasoning in a possibilistic logic programming setting with fuzzy unification

Possibilistic Defeasible Logic Programming (P-DeLP) is a logic programming language which combines features from argumentation theory and logic programming, incorporating the treatment of possibilistic uncertainty at the object-language level. In spite of its expressive power, an important limitation in P-DeLP is that imprecise, fuzzy information cannot be expressed in the object language. One interesting alternative for solving this limitation is the use of PGL+, a possibilistic logic over Gödel logic extended with fuzzy constants. Fuzzy constants in PGL+ allow expressing disjunctive information about the unknown value of a variable, in the sense of a magnitude, modelled as a (unary) predicate. The aim of this article is twofold: firstly, we formalize DePGL+, a possibilistic defeasible logic programming language that extends P-DeLP through the use of PGL+ in order to incorporate fuzzy constants and a fuzzy unification mechanism for them. Secondly, we propose a way to handle conflicting arguments in the context of the extended framework.

Points to consider for prioritizing clinical genetic testing services: a European consensus process oriented at accountability for reasonableness.

Given the cost constraints of the European health-care systems, criteria are needed to decide which genetic services to fund from the public budgets, if not all can be covered. To ensure that high-priority services are available equitably within and across the European countries, a shared set of prioritization criteria would be desirable. A decision process following the accountability for reasonableness framework was undertaken, including a multidisciplinary EuroGentest/PPPC-ESHG workshop to develop shared prioritization criteria. Resources are currently too limited to fund all the beneficial genetic testing services available in the next decade. Ethically and economically reflected prioritization criteria are needed. Prioritization should be based on considerations of medical benefit, health need and costs. Medical benefit includes evidence of benefit in terms of clinical benefit, benefit of information for important life decisions, benefit for other people apart from the person tested and the patient-specific likelihood of being affected by the condition tested for. It may be subject to a finite time window. Health need includes the severity of the condition tested for and its progression at the time of testing. Further discussion and better evidence is needed before clearly defined recommendations can be made or a prioritization algorithm proposed. To our knowledge, this is the first time a clinical society has initiated a decision process about health-care prioritization on a European level, following the principles of accountability for reasonableness. We provide points to consider to stimulate this debate across the EU and to serve as a reference for improving patient management.