Learning vector quantization with training data selection

In this paper, we propose a method that selects a subset of the training data points to update LVQ prototypes. The main goal is to conduct the prototypes to converge at a more convenient location, diminishing misclassification errors. The method selects an update set composed by a subset of points considered to be at the risk of being captured by another class prototype. We associate the proposed methodology to a weighted norm, instead of the Euclidean, in order to establish different levels of relevance for the input attributes. The technique was implemented on a controlled experiment and on Web available data sets.     

美国商务部长Carlos M.Gutierrez的致辞

我高兴地向2007中国国际机床展览会(CIMT)的主办方和参与者表示祝贺。本届展览会将是促进美中两国贸易发展的重要活动之一。我感谢你们的参与。这个展览会是您得以见识美国机床工业制造的诸多创新产品的良机。     

Learning Structure from Data and Its Application to Ozone Prediction

In this paper we propose an algorithm for structure learning in predictive expert systems based on a probabilistic network representation. The idea is to have the simplest structure (minimum number of links) with acceptable predictive capability. The algorithm starts by building a tree structure based on measuring mutual information between pairs of variables, and then it adds links as necessary to obtain certain predictive performance. We have applied this method for ozone prediction in México City, where the ozone level is used as a global indicator for the air quality in different parts of the city. It is important to predict the ozone level a day, or at least several hours in advance, to reduce the health hazards and industrial losses that occur when the ozone reaches emergency levels. We obtained as a first approximation a tree-structured dependency model for predicting ozone in one part of the city. We observe that even with only three parameters, its estimations are acceptable.A causal network representation and the structure learning techniques produced some very interesting results for the ozone prediction problem. Firstly, we got some insight into the dependence structure of the phenomena. Secondly, we got an indication of which are the important and not so important variables for ozone forecasting. Taking this into account, the measurement and computational costs for ozone prediction could be reduced. And thirdly, we have obtained satisfactory short term ozone predictions based on a small set of the most important parameters.     

Energy-aware lazy scheduling algorithm for energy-harvesting sensor nodes

The main problem in dealing with energy-harvesting (EH) sensor nodes is represented by the scarcity and non-stationarity of powering, due to the nature of the renewable energy sources. In this work, the authors address the problem of task scheduling in processors located in sensor nodes powered by EH sources. Some interesting solutions have appeared in the literature in the recent past, as the lazy scheduling algorithm (LSA), which represents a performing mix of scheduling effectiveness and ease of implementation. With the aim of achieving a more efficient and conservative management of energy resources, a new improved LSA solution is here proposed. Indeed, the automatic ability of foreseeing at run-time the task energy starving (i.e. the impossibility of finalizing a task due to the lack of power) is integrated within the original LSA approach. Moreover, some modifications have been applied in order to reduce the LSA computational complexity and thus maximizing the amount of energy available for task execution. The resulting technique, namely energy-aware LSA, has then been tested in comparison with the original one, and a relevant performance improvement has been registered both in terms of number of executable tasks and in terms of required computational burden.     

Flexible electronics: Prediction of substrate deformation during different steps of the lithography process

A numerical model was developed to simulate the micro-deformations of a polymeric substrate due to lithographic processing of different layers of a transistor-like structure. The results of the model were validated with the results from experiments. The model, a mechanical-thermal-hygroscopic model, takes into account the dimensional effects of temperature, moisture and stresses. It also includes the temperature dependent visco-elastic behaviour of the polymer substrate. The model can be used to predict overlay accuracies between different functional layers introduced by the lithographic process. It can also be used to understand the underlying processes such that it provides a tool to improve the overlay accuracy during actual processing.     

Mix design and performance analysis of asphalt concretes with electric arc furnace slag

The paper presents the results of a laboratory study, aimed at verifying the possibility to use two particular typologies of electric arc furnace (EAF) steel slags, in substitution of the natural aggregates, in the composition of wearing course asphalt concrete for flexible pavements. The experimental research has been articulated in a preliminary study of the chemical, leaching, physical, and mechanical properties of the EAF steel slag, and in the following mix design and performance characterisation of the bituminous conglomerates, through gyratory compaction tests, permanent deformations tests, Stiffness Modulus tests at various temperatures, fatigue tests and indirect tensile strength tests. All the mixtures with EAF slag have satisfied the requisites for acceptance in the road sector technical standards, thus resulting as suitable for use in the construction of road infrastructures, moreover presenting higher mechanical characteristics than those of the corresponding asphalts with full natural aggregate.     

Post-cracking behaviour of steel and macro-synthetic fibre-reinforced concretes

The present paper describes the results of an experimental investigation on the performances of concrete specimens reinforced with either steel or macro-synthetic fibres under three-point bending. Steel fibres are often used to improve the flexural toughness of concrete and are used in various structural applications while synthetic fibres are more often used to reduce crack opening due to shrinkage. Macro-synthetic fibres have been proposed more recently with the aim of creating an alternative to steel fibres in structural applications but their use is still limited.In the tests performed, specimens cast with the same concrete mix, but containing different dosages of either steel or macro-synthetic fibres, were used and compared. In general steel fibres were more efficient in increasing the toughness of concrete than macro-synthetic fibres, even though their results were significantly more scattered.Test results were used to calculate the parameters of stress-crack opening relations via inverse analysis using a cracked hinge model. This numerical model provided results, in terms of force-Crack Mouth Opening Displacement (CMOD) curves, in very good agreement with the experimental data.