Data dissemination in autonomic wireless sensor networks

In this paper, a new data dissemination algorithm for wireless sensor networks is presented. The key idea of the proposed solution is to combine concepts presented in trajectory-based forwarding with the information provided by the energy map of the network to determine routes in a dynamic fashion, according to the energy level of the sensor nodes. This is an important feature of an autonomic system, which must have the capacity of adapting its behavior according to its available resources. Simulation results revealed that the energy spent with the data dissemination activity can be concentrated on nodes with high-energy reserves, whereas low-energy nodes can use their energy only to perform sensing activity or to receive information addressed to them. In this manner, partitions of the network due to nodes that ran out of energy can be significantly delayed and the network lifetime extended.     

Influence of laminate thickness on composite durability for long term utilisation at intermediate temperature (100–150 °C)

To increase the utilisation of composite material, new domain of application should be investigated such as intermediate temperature (up to 150 °C) for long term utilisation. Under these conditions, oxidation could not be neglected.     

Global sensitivity analysis using polynomial chaos expansions

Global sensitivity analysis (SA) aims at quantifying the respective effects of input random variables (or combinations thereof) onto the variance of the response of a physical or mathematical model. Among the abundant literature on sensitivity measures, the Sobol’ indices have received much attention since they provide accurate information for most models. The paper introduces generalized polynomial chaos expansions (PCE) to build surrogate models that allow one to compute the Sobol’ indices analytically as a post-processing of the PCE coefficients. Thus the computational cost of the sensitivity indices practically reduces to that of estimating the PCE coefficients. An original non intrusive regression-based approach is proposed, together with an experimental design of minimal size. Various application examples illustrate the approach, both from the field of global SA (i.e. well-known benchmark problems) and from the field of stochastic mechanics. The proposed method gives accurate results for various examples that involve up to eight input random variables, at a computational cost which is 2–3 orders of magnitude smaller than the traditional Monte Carlo-based evaluation of the Sobol’ indices.     

Towards a technological ripening index for olive oil fruits

BACKGROUND: The aim of this work was to study the evolution of sugar and oil contents in Frantoio cultivar olives during ripening in order to propose a technological ripening index for olive oil fruits. Olive fruits were picked at nine different farms once a week from the beginning of September to the beginning of December during three crop seasons. RESULTS: As a result of the biochemical phenomenon of oil formation in olive fruits, sugar concentration during ripening was shown to follow a sigmoidal decrease, which recurred periodically in different microclimates over years. This trend resulted to be the cause of an opposite sigmoidal increase in oil content. Experimental data for sugar and oil contents were also statistically related by significant linear relationships. In addition, it was observed that reaching a minimum environmental temperature of ⩽10 °C resulted in a definite minimum asymptotic value for sugars. CONCLUSION: Sugar concentration can be proposed as an accurate, reproducible index for technological ripening of olive oil fruits by the following prediction function: proper ripening degree of olives corresponds to achievement of a constant minimum value for sugar content and, consequently, a constant maximum value for oil content, associated with reduced risk of fermentation activities of olive paste. Copyright © 2009 Society of Chemical Industry     

Phase correction, phase resetting, and phase shifts after subliminal timing perturbations in sensorimotor synchronization.

Recent studies of synchronized finger tapping have shown that perceptually subliminal phase shifts in an auditory sequence are rapidly compensated for in the motor activity (B. H. Repp, 2000a). Experiment 1 used a continuation-tapping task to confirm that this compensation is indeed a phase correction, not an adjustment of the central timekeeper period. Experiments 2–5 revealed that this phase correction occurs even when there is no ordinary sensorimotor asynchrony-when the finger taps are in antiphase or arbitrary phase relative to the auditory sequence (Experiments 2 and 3) or when the tap coinciding with the sequence phase shift is withheld (Experiments 4 and 5). The phase correction observed in the latter conditions was instantaneous, which suggests that phase resetting occurs when the motor activity is discontinuous. A prolonged phase shift suggestive of overcompensation was observed in some conditions, which poses a challenge to pure phase correction models. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Iron-Exchanged Zeolite as Effective Catalysts for Friedel–Crafts Alkylation with Alkyl Halides

Friedel–Crafts alkylation of benzene and ethylbenzene with butyl halides has been investigated in the presence of iron-exchanged zeolites. The catalysts showed high conversions and selectivity for monoalkylated products with tertiary and secondary halides under mild reaction conditions (45–60°C). Alkylation of ethylbenzene with 2-chlorobutane can be achieved in 99% yield and 100% selectivity to the monoalkylated product.     

Demand and generation cost uncertainty modelling in power system optimization studies

This paper describes the formulations and the solution algorithms developed to include uncertainties in the generation cost function and in the demand on DC OPF studies. The uncertainties are modelled by trapezoidal fuzzy numbers and the solution algorithms are based on multiparametric linear programming techniques. These models are a development of an initial formulation detailed in several publications co-authored by the second author of this paper. Now, we developed a more complete model and a more accurate solution algorithm in the sense that it is now possible to capture the widest possible range of values of the output variables reflecting both demand and generation cost uncertainties. On the other hand, when modelling simultaneously demand and generation cost uncertainties, we are representing in a more realistic way the volatility that is currently inherent to power systems. Finally, the paper includes a case study to illustrate the application of these models based on the IEEE 24 bus test system.