Adaptive learning in multiagent systems: a forecasting methodology based on error analysis

Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is a multi-agent electricity market simu-lator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM pro-vides several dynamic strategies for agents’ behaviour. This paper presents a method that aims to provide market players strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses an auxiliary forecasting tool, e.g. an Artificial Neural Net-work, to predict the electricity market prices, and analyses its forecasting error patterns. Through the recognition of such patterns occurrence, the method predicts the expected error for the next forecast, and uses it to adapt the actual forecast. The goal is to approximate the forecast to the real value, reducing the forecasting error.

Desenvolvimento e validação de um sistema de recolha de sinal eletromiográfico baseado em placa de aquisição

A eletromiografia é, hoje em dia, uma das técnicas mais utilizadas no estudo dos músculos, estando presente em áreas como a medicina, a biomecânica e a fisiologia, possibilitando o desenvolvimento científico e contribuindo para proporcionar melhorias na qualidade da vida humana. Sendo assim, este trabalho apresenta um protótipo de um aparelho de aquisição de sinais eletromiográficos, explicando também toda a teoria, técnicas, componentes utilizadas e softwares que estiveram presentes na sua implementação. De uma forma sucinta, para a aquisição do sinal eletromiográfico usou-se uma placa de aquisição NI-USB 6009 e para a visualização do mesmo recorreu-se ao software LabVIEW. Para validar o sinal adquirido com o equipamento desenvolvido, utilizou-se um outro equipamento, o Biopac MP36 Student Lab System, fazendo-se assim recolhas de sinais eletromiográficos com ambos os equipamentos. Os sinais recolhidos pelos dois equipamentos foram analisados no software Acknowledge 3.9.0 (Biopac Systems, Inc.), podendo observar-se os espetros de frequência correspondentes a cada sinal e retirar valores para posterior análise estatística. Feita essa análise, concluiu-se que não foram detetadas diferenças significativas entre os sinais eletromiográficos recolhidos com ambos os equipamentos, validando-se assim, o equipamento desenvolvido.

Analysis of tongue shape and motion in speech production using statistical modeling

The mechanisms of speech production are complex and have been raising attention from researchers of both medical and computer vision fields. In the speech production mechanism, the articulator’s study is a complex issue, since they have a high level of freedom along this process, namely the tongue, which instigates a problem in its control and observation. In this work it is automatically characterized the tongues shape during the articulation of the oral vowels of Portuguese European by using statistical modeling on MR-images. A point distribution model is built from a set of images collected during artificially sustained articulations of Portuguese European sounds, which can extract the main characteristics of the motion of the tongue. The model built in this work allows under standing more clearly the dynamic speech events involved during sustained articulations. The tongue shape model built can also be useful for speech rehabilitation purposes, specifically to recognize the compensatory movements of the articulators during speech production.

A few what-ifs on using statistical analysis of stochastic simulation runs to extract timeliness properties

Modern real-time systems, with a more flexible and adaptive nature, demand approaches for timeliness evaluation based on probabilistic measures of meeting deadlines. In this context, simulation can emerge as an adequate solution to understand and analyze the timing behaviour of actual systems. However, care must be taken with the obtained outputs under the penalty of obtaining results with lack of credibility. Particularly important is to consider that we are more interested in values from the tail of a probability distribution (near worst-case probabilities), instead of deriving confidence on mean values. We approach this subject by considering the random nature of simulation output data. We will start by discussing well known approaches for estimating distributions out of simulation output, and the confidence which can be applied to its mean values. This is the basis for a discussion on the applicability of such approaches to derive confidence on the tail of distributions, where the worst-case is expected to be.

From simulation to statistical analysis: timeliness assessment of ethernet/IP-based distributed systems

A number of characteristics are boosting the eagerness of extending Ethernet to also cover factory-floor distributed real-time applications. Full-duplex links, non-blocking and priority-based switching, bandwidth availability, just to mention a few, are characteristics upon which that eagerness is building up. But, will Ethernet technologies really manage to replace traditional Fieldbus networks? Ethernet technology, by itself, does not include features above the lower layers of the OSI communication model. In the past few years, it is particularly significant the considerable amount of work that has been devoted to the timing analysis of Ethernet-based technologies. It happens, however, that the majority of those works are restricted to the analysis of sub-sets of the overall computing and communication system, thus without addressing timeliness at a holistic level. To this end, we are addressing a few inter-linked research topics with the purpose of setting a framework for the development of tools suitable to extract temporal properties of Commercial-Off-The-Shelf (COTS) Ethernet-based factory-floor distributed systems. This framework is being applied to a specific COTS technology, Ethernet/IP. In this paper, we reason about the modelling and simulation of Ethernet/IP-based systems, and on the use of statistical analysis techniques to provide usable results. Discrete event simulation models of a distributed system can be a powerful tool for the timeliness evaluation of the overall system, but particular care must be taken with the results provided by traditional statistical analysis techniques.

Bit error models

The use of bit error models in communication simulation has been widely studied. In this technical report we present three models: the Independent Channel Model; the Gilbert-Elliot Model and the Burst-Error Periodic Model.

Some reflections on acquisition, processing and analysis of statistical data in forest soils

Beyond the classical statistical approaches (determination of basic statistics, regression analysis, ANOVA, etc.) a new set of applications of different statistical techniques has increasingly gained relevance in the analysis, processing and interpretation of data concerning the characteristics of forest soils. This is possible to be seen in some of the recent publications in the context of Multivariate Statistics. These new methods require additional care that is not always included or refered in some approaches. In the particular case of geostatistical data applications it is necessary, besides to geo-reference all the data acquisition, to collect the samples in regular grids and in sufficient quantity so that the variograms can reflect the spatial distribution of soil properties in a representative manner. In the case of the great majority of Multivariate Statistics techniques (Principal Component Analysis, Correspondence Analysis, Cluster Analysis, etc.) despite the fact they do not require in most cases the assumption of normal distribution, they however need a proper and rigorous strategy for its utilization. In this work, some reflections about these methodologies and, in particular, about the main constraints that often occur during the information collecting process and about the various linking possibilities of these different techniques will be presented. At the end, illustrations of some particular cases of the applications of these statistical methods will also be presented.

Classification Performance of Multilayer Perceptrons with Different Risk Functionals

In the present paper we assess the performance of information-theoretic inspired risks functionals in multilayer perceptrons with reference to the two most popular ones, Mean Square Error and Cross-Entropy. The information-theoretic inspired risks, recently proposed, are: HS and HR2 are, respectively, the Shannon and quadratic Rényi entropies of the error; ZED is a risk reflecting the error density at zero errors; EXP is a generalized exponential risk, able to mimic a wide variety of risk functionals, including the information-thoeretic ones. The experiments were carried out with multilayer perceptrons on 35 public real-world datasets. All experiments were performed according to the same protocol. The statistical tests applied to the experimental results showed that the ubiquitous mean square error was the less interesting risk functional to be used by multilayer perceptrons. Namely, mean square error never achieved a significantly better classification performance than competing risks. Cross-entropy and EXP were the risks found by several tests to be significantly better than their competitors. Counts of significantly better and worse risks have also shown the usefulness of HS and HR2 for some datasets.

Study of the Reliability of Statistical Timing Analysis for Real-Time Systems

Presented at 23rd International Conference on Real-Time Networks and Systems (RTNS 2015). 4 to 6, Nov, 2015, Main Track. Lille, France.

Testing Nelder-Mead Based Repulsion Algorithms for Multiple Roots of Nonlinear Systems via a Two-Level Factorial Design of Experiments

This paper addresses the challenging task of computing multiple roots of a system of nonlinear equations. A repulsion algorithm that invokes the Nelder-Mead (N-M) local search method and uses a penalty-type merit function based on the error function, known as 'erf', is presented. In the N-M algorithm context, different strategies are proposed to enhance the quality of the solutions and improve the overall efficiency. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm.