Taking advantage of metadata semantics: the case of learning-object-based lesson graphs

Learning objects (LOs) are pieces of educational material characterized with a valuable amount of information about their content and usage. This additional information is defined as a set of metadata generally following the IEEE LOM specification. This specification also serves to characterize the relations existing between LOs. LOs whose relations are explicit are regarded as the nodes of a lesson graph. Link types and LO metadata constitute the lesson graph semantics. This article proposes to take advantage of lesson graph semantics using a context diffusion approach. It consists in diffusing the metadata-based processes along the edges of the lesson graph. This technique aims at coping with the metadata processing issues arising when some graph metadata are missing, incorrect, or incomplete. This article also presents a three-layer extensible framework for easing the use of context diffusion in a graph. As part of the framework, two original types of metadata processes are introduced. The first one takes advantage of the metadata attribute similarities between related LOs. The second one focuses on the lesson graph consistency. The framework and the application examples were implemented as an open-source Java library used in the lesson graph authoring tool LessonMapper2. During the lesson authoring process, we show that the framework can bring support not only for generating and validating metadata, but also for retrieving LOs.     

Some approaches for relational databases flexible querying

One of the main objectives of third generation databases is to design database management systems which provide users with more and more functionalities. In such a wide context, various proposals have been made in order to introduce some kind of explicit or implicit flexibility into user queries. In this paper, we propose a classification of the various approaches dealing with imprecise queries. Moreover, we show that the approach based on fuzzy sets is powerful enough to answer a wide range of imprecise queries in an appropriate way and to support the expression of the capabilities available in the other classes of solutions. An outline of an SQL-like language allowing for a variety of imprecise queries is also presented.     

Navigation with constraints for an autonomous mobile robot

This paper describes a navigation planning algorithm for a robot capable of autonomous navigation in a structured, partially known and dynamic environment. This algorithm is applied to a discrete workspace composed of a network of places and roads. The environment specification associates temporal constraints with any element of the network, and recharge or relocalisation possibilities with places. A mission specification associates several constraints with each navigation task (energy, time, position uncertainty and distance).

The algorithm computes an optimal path for each navigation task according to the optimization criterion and constraints. We introduce the notion of efficient path applied to a new best first search algorithm solving a multiple constraints problem. The path determination relies on a state representation adapted to deal with environment constraints. We then prove that the complexity chracteristics of our algorithm are similar to those of the A* algorithm.

The planner described in this paper has been implemented on a Spare station for a Robuter mobile platform equipped with ultra-sonic range sensors and an active stereo vision system. It was developed for the MITHRA family of autonomous surveillance robots as part of project EUREKA EU 110.     

Modeling and Rendering of Heterogeneous Granular Materials: Granite Application

Light‐matter interactions is one of the most important factors of realistic rendering. While a lot of work has already been performed in the light transport and simulation area, we believe that “virtual materials” have not yet been studied enough to achieve a high degree of realism. Some good models exist in order to take into account homogeneous materials. However, there are only a few studies of heterogeneous granular materials. In this paper, we propose a method based on mimicking natural phenomena to take into account these materials. Our study focuses on granite, which can be considered as a heterogeneous agglomerate of individually homogeneous grains. First we present a nucleation/growth process inspired technique giving a full 3D model of granite. Then, we use a rendering process taking into account each material component and subsurface scattering in a simple way.     

Analytic approximation of the jitter incurred by CBR traffics in IP networks

In this paper, an analytic approximation is derived for the end-to-end delay-jitter incurred by a periodic traffic with constant packet size. The single node case is considered first. It is assumed that the periodic traffic is multiplexed with a background packet stream under the FCFS service discipline. The processes governing the packet arrivals and the packet sizes of the background traffic are assumed to be general renewal processes. A very simple analytical approximation is derived and its accuracy is assessed by means of event-driven simulations. This approximation is then extended to the multiple node case yielding a simple analytical approximation of the end-to-end jitter. This approximation is shown to be fairly accurate in the light to moderate traffic conditions typically encountered in IP core networks.     

PEM fuel cell voltage transient response to a thermal perturbation

This paper describes a transient model predicting PEMFC voltage response to a step change in the cooling water temperature. Its objectives are to put forward the main transport parameters and their corresponding time scales. The fuel cell is assumed isothermal with a time constant τ_t. The temperature variations result from the production of heat by the exothermic chemical reaction and by internal heat dissipation, and from heat transfer with the cooling circuit. The effects of temperature on fuel cell performances are taken into account through the variations in its thermodynamic voltage, in the kinetics of the half-reactions, and in the membrane ionic resistance. A dynamic and one-dimensional simulation of water transport in the membrane by electroosmotic drag and by diffusion is carried out: the relative humidity of gases varies with the cell temperature under the assumption that their specific humidity (i.e., the vapor content in the gas diffusion layers) remains unchanged.Two time constants characterize mass transfer in the membrane by water diffusion (τ_d) and by electroosmosis (τ_e). The Péclet number Pe which is equal to the ratio between τ_d and τ_e allows the comparison of the magnitude of these two transport mechanisms, both depending on current density and on the other operating conditions.The results of the model are compared to a set of experimental results obtained with a cell composed of a Nafion 115 membrane, and fed by hydrogen and pure oxygen. The average current density is 4000 A m⁻². In these conditions, the smallest time constant is the one characterizing the fuel cell thermal response τ_t (16 s). Therefore, the fuel cell voltage response to a temperature step occurs in two stages, the first one corresponding to the thermal regime. The second stage concerns water transport in the membrane; the best fit between numerical and experimental results yields to a Péclet number of about 16, which makes electroosmosis the most significant phenomenon.     

Cholinergic drug effects on a delayed conditional discrimination task in the rat

The centrally acting cholinergic antagonist scopolamine (0.025-0.10 mg/kg ip) and the peripherally acting cholinergic antagonist methyl-scopolamine (0.01-0.10 mg/kg) dose dependently impaired discriminability independent of delay in a delayed conditional discrimination task that precludes use of mediating behavior. This indicates that scopolamine does not specifically affect working memory. Drugs that enhance cholinergic transmission neither improved discriminability nor attenuated scopolamine-induced impairments. In a post hoc analysis scopolamine was found to impair discriminability in a delay-dependent manner in rats that performed at a high level in pretest sessions. Methyl-scopolamine impaired performance independently of delay in these rats. The authors suggest that a ceiling effect at short delays produced this Drug x Delay interaction of scopolamine in the best performing rats.     

Determination of the adequate minimum model complexity required in anaerobic bioprocesses using experimental data

BACKGROUND: Modelling of anaerobic bioprocesses requires adequate conciliation between model accuracy and complexity. Anaerobic digestion is a highly complex biocatalysed process in which organic (waste) materials are converted into biogas. Complex mathematical models of the process can be difficult to manage, while too simplistic models may be insufficient for specific applications. RESULTS: A technique based on principal component analysis (PCA) is presented to assess the most adequate complexity in anaerobic bioprocess models using preliminary data. The technique is applied to experimental data from a continuously operated pilot‐scale anaerobic digestion process treating diluted wine and to process simulation data generated by a highly complex model (ADM1). The results obtained suggest that models incorporating only four reactions can describe most of the experimental data variability. Similarly, a simplification of the highly complex modified ADM1 used to a four‐reaction model could attain equivalent simulation accuracy. A set of possible four‐reaction networks was evaluated using the PCA information and a best candidate network of reactions is obtained. CONCLUSION: The developed PCA‐based tool allows for the assessment of the adequate complexity in mathematical models of anaerobic digestion of ethanol, a process that appears describable with a high level of accuracy by considering only four biological reactions. Copyright © 2008 Society of Chemical Industry     

Multiobjective evolutionary optimization of the size, shape, and position parameters of radial basis function networks for function approximation

This paper presents a multiobjective evolutionary algorithm to optimize radial basis function neural networks (RBFNNs) in order to approach target functions from a set of input-output pairs. The procedure allows the application of heuristics to improve the solution of the problem at hand by including some new genetic operators in the evolutionary process. These new operators are based on two well-known matrix transformations: singular value decomposition (SVD) and orthogonal least squares (OLS), which have been used to define new mutation operators that produce local or global modifications in the radial basis functions (RBFs) of the networks (the individuals in the population in the evolutionary procedure). After analyzing the efficiency of the different operators, we have shown that the global mutation operators yield an improved procedure to adjust the parameters of the RBFNNs.