Coordinating Java agents over the WWW

We introduce Jada, a programming toolkit for coordinating agents written in Java. Coordination among either concurrent threads or distributed Java objects is achieved via shared object spaces. By exchanging objects through object spaces, Java agents or applets can exchange data or synchronize their actions over the Internet, a LAN, a single host, or even inside a Javaenabled browser. The access to an object space is performed using a set of methods of an ObjectSpace object. Such operations inspired by the Linda language are powerful enough to solve several coordination problems. Moreover, we show how Jada can be used as a coordination kernel for more complex coordination architectures.     

Synthesis and glutathione S-transferase structure-affinity relationships of nonpeptide and peptidase-stable glutathione analogues

A series of nonpeptidic glutathione analogues where the peptide bonds were replaced by simple carbon-carbon bonds or isosteric E double bonds were prepared. The optimal length for the two alkyl chains on either side of the mercaptomethyl group was evaluated using structure-affinity relationships. Affinities of the analogues 14a-f, 23, and 25 were evaluated for a recombinant GST enzyme using a new affinity chromatography method previously developed in our laboratory. Analysis of these analogues gives an additional understanding for GST affinity requirements: (a) the carbon skeleton must conserve that of glutathione since analogue 14a showed the best affinity (IC50 = 5.2 microM); (b) the GST G site is not able to accommodate a chain length elongation of one methylene group (no affinity for analogues 14c,f); (c) a one-methylene group chain length reduction is tolerated, much more for the "Glu side" (14d, IC50 = 10.1 microM) than for the "Gly side" (14b, IC50 = 1800 microM); (d) the mercaptomethyl group must remain at position 5 as shown from the null affinity of the 6-mercaptomethyl analogue 14e; (e) the additional peptide isosteric E double bond (25) or hydroxyl derivative (23) in 14e did not help to retrieve affinity. This work reveals useful information for the design of new selective nonpeptidic and peptidase-stable glutathione analogues.     

Effect of loading rate on the tensile behaviour of concrete: description of the physical mechanisms

Founded upon several works carried out by the Laboratoire Central des Ponts et Chaussées on the dynamic behaviour of concrete (already published), and upon new ideas about this subject, this article attempts to further develop the analysis of the physical mechanisms. In particular to investigate how the Stéfan effect, the cracking process, and the inertia forces participate together in the dynamic behaviour of a specimen subjected to a uniaxial tensile test. These mechanisms can be summed up as follows:

1. At strain rates smaller than approximately 1 s^?1, the main physical mechanism is a viscous mechanism that may be regarded as similar to the Stéfan effect. This mechanism counters both a microcracking localization, leading to an increase of concrete tensile strength, and the macrocrack propagation that leads to failure of the specimen.
2. At strain rates greater than or equal to approximately 10s^?1, the forces of inertia become preponderant. They counter microcracking localization and in particular macrocrack propagation.

     

Two is better than one: A diploid genotype for neural networks

In nature the genotype of many organisms exhibits diploidy, i.e., it includes two copies of every gene. In this paper we describe the results of simulations comparing the behavior of haploid and diploid populations of ecological neural networks living in both fixed and changing environments. We show that diploid genotypes create more variability in fitness in the population than haploid genotypes and buffer better environmental change; as a consequence, if one wants to obtain good results for both average and peak fitness in a single population one should choose a diploid population with an appropriate mutation rate. Some results of our simulations parallel biological findings.     

Global estimates of evapotranspiration and gross primary production based on MODIS and global meteorology data

The simulation of gross primary production (GPP) at various spatial and temporal scales remains a major challenge for quantifying the global carbon cycle. We developed a light use efficiency model, called EC-LUE, driven by only four variables: normalized difference vegetation index (NDVI), photosynthetically active radiation (PAR), air temperature, and the Bowen ratio of sensible to latent heat flux. The EC-LUE model may have the most potential to adequately address the spatial and temporal dynamics of GPP because its parameters (i.e., the potential light use efficiency and optimal plant growth temperature) are invariant across the various land cover types. However, the application of the previous EC-LUE model was hampered by poor prediction of Bowen ratio at the large spatial scale. In this study, we substituted the Bowen ratio with the ratio of evapotranspiration (ET) to net radiation, and revised the RS-PM (Remote Sensing-Penman Monteith) model for quantifying ET. Fifty-four eddy covariance towers, including various ecosystem types, were selected to calibrate and validate the revised RS-PM and EC-LUE models. The revised RS-PM model explained 82% and 68% of the observed variations of ET for all the calibration and validation sites, respectively. Using estimated ET as input, the EC-LUE model performed well in calibration and validation sites, explaining 75% and 61% of the observed GPP variation for calibration and validation sites respectively.Global patterns of ET and GPP at a spatial resolution of 0.5° latitude by 0.6° longitude during the years 2000-2003 were determined using the global MERRA dataset (Modern Era Retrospective-Analysis for Research and Applications) and MODIS (Moderate Resolution Imaging Spectroradiometer). The global estimates of ET and GPP agreed well with the other global models from the literature, with the highest ET and GPP over tropical forests and the lowest values in dry and high latitude areas. However, comparisons with observed GPP at eddy flux towers showed significant underestimation of ET and GPP due to lower net radiation of MERRA dataset. Applying a procedure to correct the systematic errors of global meteorological data would improve global estimates of GPP and ET. The revised RS-PM and EC-LUE models will provide the alternative approaches making it possible to map ET and GPP over large areas because (1) the model parameters are invariant across various land cover types and (2) all driving forces of the models may be derived from remote sensing data or existing climate observation networks.     

Solving job shop scheduling with setup times through constraint-based iterative sampling: an experimental analysis

This paper presents a heuristic algorithm for solving a job-shop scheduling problem with sequence dependent setup times and min/max separation constraints among the activities (SDST-JSSP/max). The algorithm relies on a core constraint-based search procedure, which generates consistent orderings of activities that require the same resource by incrementally imposing precedence constraints on a temporally feasible solution. Key to the effectiveness of the search procedure is a conflict sampling method biased toward selection of most critical conflicts and coupled with a non-deterministic choice heuristic to guide the base conflict resolution process. This constraint-based search is then embedded within a larger iterative-sampling search framework to broaden search space coverage and promote solution optimization. The efficacy of the overall heuristic algorithm is demonstrated empirically both on a set of previously studied job-shop scheduling benchmark problems with sequence dependent setup times and by introducing a new benchmark with setups and generalized precedence constraints.     

Experimental evaluation of pheromone models in ACOPlan

In this paper the system ACOPlan for planning with non uniform action cost is introduced and analyzed. ACOPlan is a planner based on the ant colony optimization framework, in which a colony of planning ants searches for near optimal solution plans with respect to an overall plan cost metric. This approach is motivated by the strong similarity between the process used by artificial ants to build solutions and the methods used by state?Cbased planners to search solution plans. Planning ants perform a stochastic and heuristic based search by interacting through a pheromone model. The proposed heuristic and pheromone models are presented and compared through systematic experiments on benchmark planning domains. Experiments are also provided to compare the quality of ACOPlan solution plans with respect to state of the art satisficing planners. The analysis of the results confirm the good performance of the Action?CAction pheromone model and points out the promising performance of the novel Fuzzy?CLevel?CAction pheromone model. The analysis also suggests general principles for designing performant pheromone models for planning and further extensions of ACOPlan to other optimization models.     

Maximum Likelihood Estimation of the Cox–Ingersoll–Ross Model Using Particle Filters

This paper shows how to build in a computationally efficient way a maximum simulated likelihood procedure to estimate the Cox–Ingersoll–Ross model from multivariate time series. The advantage of this estimator is that it takes into account the exact likelihood function while avoiding the huge computational burden associated with MCMC methods and without the ad hoc assumption that certain bond yields are measured without error. The proposed methodology is implemented and tested on simulated data. For realistic parameter values the estimator seems to have good small sample properties, compared to the popular quasi maximum likelihood approach, even using moderate simulation sizes. The effect of simulation errors does not seem to undermine the estimation procedure.     

Model-based cold-start speed control scheme for spark ignition engines

This paper presents a model-based control scheme to the cold-start speed control in spark ignition (SI) engines. The multi-variable control algorithm is developed with the purpose of improving the transient performance of the starting engine speed: the control inputs are the fuel injection, the throttle and the spark advance (SA), while the engine speed and the air mass flow rate are the measured signals. The fuel injection is performed with a dual sampling rate system: the cycle-based fuel injection command is individually adjusted for each cylinder by using a TDC (top dead center)-based air charge estimation. The desired performance for speed regulation is achieved by using a coordinated control of SA and throttle operation. The speed error convergence of the closed loop system is proved for simplified, second-order model with a time-delay, and the robustness with respect to parameter uncertainties is investigated. The performance and the robustness with respect to modeling uncertainties of the proposed control scheme are tested using an industrial engine simulator with six cylinders.     

RUSHES—an annotation and retrieval engine for multimedia semantic units

Multimedia analysis and reuse of raw un-edited audio visual content known as rushes is gaining acceptance by a large number of research labs and companies. A set of research projects are considering multimedia indexing, annotation, search and retrieval in the context of European funded research, but only the FP6 project RUSHES is focusing on automatic semantic annotation, indexing and retrieval of raw and un-edited audio-visual content. Even professional content creators and providers as well as home-users are dealing with this type of content and therefore novel technologies for semantic search and retrieval are required. In this paper, we present a summary of the most relevant achievements of the RUSHES project, focusing on specific approaches for automatic annotation as well as the main features of the final RUSHES search engine.