Formation Control Driven by Cooperative Object Tracking

In this paper we introduce a formation control loop that maximizes the performance of the cooperative perception of a tracked target by a team of mobile robots, while maintaining the team in formation, with a dynamically adjustable geometry which is a function of the quality of the target perception by the team. In the formation control loop, the controller module is a distributed non-linear model predictive controller and the estimator module fuses local estimates of the target state, obtained by a particle filter at each robot. The two modules and their integration are described in detail, including a real-time database associated to a wireless communication protocol that facilitates the exchange of state data while reducing collisions among team members. Simulation and real robot results for indoor and outdoor teams of different robots are presented. The results highlight how our method successfully enables a team of homogeneous robots to minimize the total uncertainty of the tracked target cooperative estimate while complying with performance criteria such as keeping a pre-set distance between the teammates and the target, avoiding collisions with teammates and/or surrounding obstacles.

Metodologias no Controlo de Compactação em Aterros

O presente trabalho pretende abordar aspectos relacionados com o controlo de compactação em aterros, com base na avaliação de parâmetros “in situ”, tais como: pesos volúmicos, teores em água, graus de compactação e módulos de deformabilidade. Recorrendo aos métodos correntes no controlo de compactação, como o ensaio de carga em placa, gamadensímetro, garrafa e ao ensaio de deflectómetro de impacto portátil. Visa-se comparar os resultados obtidos, nas diferentes condições, de modo a possibilitar alcançar correlações entre os ensaios, bem como determinar aqueles que apresentam maior grau de confiança técnico e vantagens operacionais e económicas. De modo a garantir os índices de qualidade da obra é necessário fazer cumprir os critérios exigidos pelo caderno de encargos, nomeadamente nos parâmetros de avaliação do controlo de compactação, para que estas satisfaçam o seu estado funcional e estrutural. Neste tipo de obras os cadernos de encargos de referência em Portugal são os das Estradas de Portigal (EP) e da Brisa, Auto-estradas de Portugal (Brisa), os quais se baseiam em recomendações de classificações de solos. No contexto experimental, foram efectuados dois estudos com condições e materiais diferentes, em obras pertencentes à empresa Mota-Engil Engenharia e Construções, S.A. Nas campanhas de ensaios foram realizados ensaios “in situ” na obra da Subconcessão do Douro Interior – Lote 6 – IC5 – Troço Murça/ Nó de Pombal nas camadas de sub-base e base num agregado de granulometria extensa, e na obra de modernização do troço ferroviário Bombel e Vidigal a Évora, em solos.

A Clinical Support System Based on Quality of Life Estimation

Quality of life is a concept influenced by social, economic, psychological, spiritual or medical state factors. More specifically, the perceived quality of an individual's daily life is an assessment of their well-being or lack of it. In this context, information technologies may help on the management of services for healthcare of chronic patients such as estimating the patient quality of life and helping the medical staff to take appropriate measures to increase each patient quality of life. This paper describes a Quality of Life estimation system developed using information technologies and the application of data mining algorithms to access the information of clinical data of patients with cancer from Otorhinolaryngology and Head and Neck services of an oncology institution. The system was evaluated with a sample composed of 3013 patients. The results achieved show that there are variables that may be significant predictors for the Quality of Life of the patient: years of smoking (p value 0.049) and size of the tumor (p value < 0.001). In order to assign the variables to the classification of the quality of life the best accuracy was obtained by applying the John Platt's sequential minimal optimization algorithm for training a support vector classifier. In conclusion data mining techniques allow having access to patients additional information helping the physicians to be able to know the quality of life and produce a well-informed clinical decision.

Adaptive modeling and high quality spectral estimation for speech enhancement

In this work an adaptive modeling and spectral estimation scheme based on a dual Discrete Kalman Filtering (DKF) is proposed for speech enhancement. Both speech and noise signals are modeled by an autoregressive structure which provides an underlying time frame dependency and improves time-frequency resolution. The model parameters are arranged to obtain a combined state-space model and are also used to calculate instantaneous power spectral density estimates. The speech enhancement is performed by a dual discrete Kalman filter that simultaneously gives estimates for the models and the signals. This approach is particularly useful as a pre-processing module for parametric based speech recognition systems that rely on spectral time dependent models. The system performance has been evaluated by a set of human listeners and by spectral distances. In both cases the use of this pre-processing module has led to improved results.