Analysing the behaviour of robot teams through relational sequential pattern mining

This report outlines the use of a relational representation in a Multi-Agent domain to model the behaviour of the whole system. A desired property in this systems is the ability of the team members to work together to achieve a common goal in a cooperative manner. The aim is to define a systematic method to verify the effective collaboration among the members of a team and comparing the different multi-agent behaviours. Using external observations of a Multi-Agent System to analyse, model, recognize agent behaviour could be very useful to direct team actions. In particular, this report focuses on the challenge of autonomous unsupervised sequential learning of the team's behaviour from observations. Our approach allows to learn a symbolic sequence (a relational representation) to translate raw multi-agent, multi-variate observations of a dynamic, complex environment, into a set of sequential behaviours that are characteristic of the team in question, represented by a set of sequences expressed in first-order logic atoms. We propose to use a relational learning algorithm to mine meaningful frequent patterns among the relational sequences to characterise team behaviours. We compared the performance of two teams in the RoboCup four-legged league environment, that have a very different approach to the game. One uses a Case Based Reasoning approach, the other uses a pure reactive behaviour.Comment: 25 page

ICA as a preprocessing technique for classification

In this paper we propose the use of the independent component analysis (ICA) [1] technique for improving the classification rate of decision trees and multilayer perceptrons [2], [3]. The use of an ICA for the preprocessing stage, makes the structure of both classifiers simpler, and therefore improves the generalization properties. The hypothesis behind the proposed preprocessing is that an ICA analysis will transform the feature space into a space where the components are independent, and aligned to the axes and therefore will be more adapted to the way that a decision tree is constructed. Also the inference of the weights of a multilayer perceptron will be much easier because the gradient search in the weight space will follow independent trajectories. The result is that classifiers are less complex and on some databases the error rate is lower. This idea is also applicable to regressio

New solutions in the ferrates(VI) process with the use of SnО₂–modified electrodes

Изучены особенности образования ферратов(VI) из соединений Fe(III) в растворах с различным ионным составом на инертных SnО₂-электродах, легированных Ru, Pt, Pd и Sb. Установлено, что изменением природы и содержания легирующего металла можно целенаправленно регулировать электро-каталитические свойства анодов, в частности величину перенапряжения выделения О₂. Показана принципиальная возможность электрохимического окисления на поверхности электрода и химического окисления в объеме раствора частиц Fe(ОН)₃ и Fe(ОН)₄. Разработаны рекомендации для синтеза ферратов(VI) с использованием анодов, обеспечивающих длительный режим работы без ухудшения их эксплуатационных характеристик.Disadvantages of traditional synthesis methods of ferrates (VI) - promising green oxidants - stimulate the search of new technological solutions which meet the requirements of modern production. The purpose of this work was to study the ferrates (VI) formation from Fe (III) compounds in solutions with different pH on inert SnО₂ electrodes doped with Pt, Ru, Pd, and Sb. The influence of the nature and the content of the alloying metal on the electrocatalytic properties of the electrode was studied by the stationary voltammetry method, as well as by determining the current yields of hypochlorite and sodium chlorate during the electrolysis of a slightly alkaline NaCl solution. Coatings based on SnО₂, doped with palladium and platinum, show maximal electrocatalytic activity according to ClO – synthesis. It has been established that the oxygen evolution overvoltage on the electrodes with comparable dopant concentrations increases in the Ru-Pd-Pt-Sb series. It has been shown that for effective synthesis of ferrates (VI), flat Ti anodes of a large area with an electroactive layer based on SnО₂-Sb2О₃ should be used. It is noted that electrochemical oxidation of Fe (III) in Fe (VI) is more energetically favorable on these electrodes than О₂ evolution, which opens up new possibilities for these processes in ferrate (VI) synthesis technology. We have shown the principal possibility of increasing the productivity of the Fe (VI) process due to the direct interaction of the Fe(ОН)₃ and Fe(ОН)₄− particles in the solution volume with ClO− anions generated on an inert electrode when Сl− anions are preliminarily added to the system. Technological solutions have been proposed to increase the life of inert electrodes when 5-10% TiO2 is introduced into the SnО₂ matrix, providing a long-term operating mode without degradation of their performance characteristics

Adaptive query-based sampling of distributed collections

As part of a Distributed Information Retrieval system a de-scription of each remote information resource, archive or repository is usually stored centrally in order to facilitate resource selection. The ac-quisition ofprecise resourcedescriptionsistherefore animportantphase in Distributed Information Retrieval, as the quality of such represen-tations will impact on selection accuracy, and ultimately retrieval per-formance. While Query-Based Sampling is currently used for content discovery of uncooperative resources, the application of this technique is dependent upon heuristic guidelines to determine when a sufficiently accurate representation of each remote resource has been obtained. In this paper we address this shortcoming by using the Predictive Likelihood to provide both an indication of thequality of an acquired resource description estimate, and when a sufficiently good representation of a resource hasbeen obtained during Query-Based Sampling

Parsimonious Kernel Fisher Discrimination

By applying recent results in optimization transfer, a new algorithm for kernel Fisher Discriminant Analysis is provided that makes use of a non-smooth penalty on the coefficients to provide a parsimonious solution. The algorithm is simple, easily programmed and is shown to perform as well as or better than a number of leading machine learning algorithms on a substantial benchmark. It is then applied to a set of extreme small-sample-size problems in virtual screening where it is found to be less accurate than a currently leading approach but is still comparable in a number of cases

Camera distortion self-calibration using the plumb-line constraint and minimal Hough entropy

In this paper we present a simple and robust method for self-correction of camera distortion using single images of scenes which contain straight lines. Since the most common distortion can be modelled as radial distortion, we illustrate the method using the Harris radial distortion model, but the method is applicable to any distortion model. The method is based on transforming the edgels of the distorted image to a 1-D angular Hough space, and optimizing the distortion correction parameters which minimize the entropy of the corresponding normalized histogram. Properly corrected imagery will have fewer curved lines, and therefore less spread in Hough space. Since the method does not rely on any image structure beyond the existence of edgels sharing some common orientations and does not use edge fitting, it is applicable to a wide variety of image types. For instance, it can be applied equally well to images of texture with weak but dominant orientations, or images with strong vanishing points. Finally, the method is performed on both synthetic and real data revealing that it is particularly robust to noise.Comment: 9 pages, 5 figures Corrected errors in equation 1

Minimal mean-square error for 3D MIMO beamforming weighting

This paper is a postprint of a paper submitted to and accepted for publication in [journal] and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at the IET Digital Librar

Modeling the Cognitive Task Load and Performance of Naval Operators

Abstract. Operators on naval ships have to act in dynamic, critical and highdemand task environments. For these environments, a cognitive task load (CTL) model has been proposed as foundation of three operator support functions: adaptive task allocation, cognitive aids and resource feedback. This paper presents the construction of such a model as a Bayesian network with probability relationships between CTL and performance. The network is trained and tested with two datasets: operator performance with an adaptive user interface in a lab-setting and operator performance on a high-tech sailing ship. The “Naïve Bayesian network ” tuned out to be the best choice, providing performance estimations with 86 % and 74 % accuracy for respectively the lab and ship data. Overall, the resulting model nicely generalizes over the two datasets. It will be used to estimate operator performance under momentary CTL-conditions, and to set the thresholds of the load-mitigation strategies for the three support functions

Automatic Detection of Laryngeal Pathology on Sustained Vowels Using Short-Term Cepstral Parameters: Analysis of Performance and Theoretical Justification

The majority of speech signal analysis procedures for automatic detection of laryngeal pathologies mainly rely on parameters extracted from time domain processing. Moreover, calculation of these parameters often requires prior pitch period estimation; therefore, their validity heavily depends on the robustness of pitch detection. Within this paper, an alternative approach based on cepstral- domain processing is presented which has the advantage of not requiring pitch estimation, thus providing a gain in both simplicity and robustness. While the proposed scheme is similar to solutions based on Mel-frequency cepstral parameters, already present in literature, it has an easier physical interpretation while achieving similar performance standards