Assessing and comparing the total antioxidant capacity of commercial beverages: application to beers, wines, waters and soft drinks using TRAP, TEAC and FRAP methods.

This work measures and tries to compare the Antioxidant Capacity (AC) of 50 commercial beverages of different kinds: 6 wines, 12 beers, 18 soft drinks and 14 flavoured waters. Because there is no reference procedure established for this purpose, three different optical methods were used to analyse these samples: Total Radical trapping Antioxidant Parameter (TRAP), Trolox Equivalent Antioxidant Capacity (TEAC) and Ferric ion Reducing Antioxidant Parameter (FRAP). These methods differ on the chemical background and nature of redox system. The TRAP method involves the transfer of hydrogen atoms while TEAC and FRAP involves electron transfer reactions. The AC was also assessed against three antioxidants of reference, Ascorbic acid (AA), Gallic acid (GA) and 6-hydroxy-2,5,7,8-tetramethyl- 2-carboxylic acid (Trolox). The results obtained were analyzed statistically. Anova one-way tests were applied to all results and suggested that methods and standards exhibited significant statistical differences. The possible effect of sample features in the AC, such as gas, flavours, food colouring, sweeteners, acidity regulators, preservatives, stabilizers, vitamins, juice percentage, alcohol percentage, antioxidants and the colour was also investigated. The AC levels seemed to change with brand, kind of antioxidants added, and kind of flavour, depending on the sample. In general, higher ACs were obtained for FRAP as method, and beer for kind of sample, and the standard expressing the smaller AC values was GA.

Decentralized Target Tracking based on Multi-Robot Cooperative Triangulation

Target tracking with bearing-only sensors is a challenging problem when the target moves dynamically in complex scenarios. Besides the partial observability of such sensors, they have limited field of views, occlusions can occur, etc. In those cases, cooperative approaches with multiple tracking robots are interesting, but the different sources of uncertain information need to be considered appropriately in order to achieve better estimates. Even though there exist probabilistic filters that can estimate the position of a target dealing with incertainties, bearing-only measurements bring usually additional problems with initialization and data association. In this paper, we propose a multi-robot triangulation method with a dynamic baseline that can triangulate bearing-only measurements in a probabilistic manner to produce 3D observations. This method is combined with a decentralized stochastic filter and used to tackle those initialization and data association issues. The approach is validated with simulations and field experiments where a team of aerial and ground robots with cameras track a dynamic target.

Combining sparse and dense methods in 6D Visual Odometry

13th International Conference on Autonomous Robot Systems (Robotica), 2013, Lisboa

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.

Reliability of Two Methods for Identifying the Postural Phase of Gait Initiation in Healthy and Post-stroke Subjects

This study aims to compare two methods of assessing the postural phase of gait initiation as to intrasession reliability, in healthy and post-stroke subjects. As a secondary aim, this study aims to analyse anticipatory postural adjustments during gait initiation based on the centre of pressure (CoP) displacements in post-stroke participants. The CoP signal was acquired during gait initiation in fifteen post-stroke subjects and twenty-three healthy controls. Postural phase was identified through a baseline-based method and a maximal displacement based method. In both healthy and post-stroke participants higher intra-class correlation coefficient and lower coefficient of variation values were obtained with the baseline-based method when compared to the maximal displacement based method. Post-stroke participants presented decreased CoP displacement backward and toward the first swing limb compared to controls when the baseline-based method was used. With the maximal displacement based method, there were differences between groups only regarding backward CoP displacement. Postural phase duration in medial-lateral direction was also increased in post-stroke participants when using the maximal displacement based method. The findings obtained indicate that the baseline-based method is more reliable detecting the onset of gait initiation in both groups, while the maximal displacement based method presents greater sensitivity for post-stroke participants.

Homograph ambiguity resolution in front-end design for portuguese TTS systems

In this paper, a module for homograph disambiguation in Portuguese Text-to-Speech (TTS) is proposed. This module works with a part-of-speech (POS) parser, used to disambiguate homographs that belong to different parts-of-speech, and a semantic analyzer, used to disambiguate homographs which belong to the same part-of-speech. The proposed algorithms are meant to solve a significant part of homograph ambiguity in European Portuguese (EP) (106 homograph pairs so far). This system is ready to be integrated in a Letter-to-Sound (LTS) converter. The algorithms were trained and tested with different corpora. The obtained experimental results gave rise to 97.8% of accuracy rate. This methodology is also valid for Brazilian Portuguese (BP), since 95 homographs pairs are exactly the same as in EP. A comparison with a probabilistic approach was also done and results were discussed.

Kalman tracking linear predictor for vowel intelligibility enhancement on european portuguese HMM based speech synthesis

The recent developments on Hidden Markov Models (HMM) based speech synthesis showed that this is a promising technology fully capable of competing with other established techniques. However some issues still lack a solution. Several authors report an over-smoothing phenomenon on both time and frequencies which decreases naturalness and sometimes intelligibility. In this work we present a new vowel intelligibility enhancement algorithm that uses a discrete Kalman filter (DKF) for tracking frame based parameters. The inter-frame correlations are modelled by an autoregressive structure which provides an underlying time frame dependency and can improve time-frequency resolution. The system’s performance has been evaluated using objective and subjective tests and the proposed methodology has led to improved results.

An Open Source BI Approach: Concept Proof Tracking Fleet

É possível assistir nos dias de hoje, a um processo tecnológico evolutivo acentuado por toda a parte do globo. No caso das empresas, quer as pequenas, médias ou de grandes dimensões, estão cada vez mais dependentes dos sistemas informatizados para realizar os seus processos de negócio, e consequentemente à geração de informação referente aos negócios e onde, muitas das vezes, os dados não têm qualquer relacionamento entre si. A maioria dos sistemas convencionais informáticos não são projetados para gerir e armazenar informações estratégicas, impossibilitando assim que esta sirva de apoio como recurso estratégico. Portanto, as decisões são tomadas com base na experiência dos administradores, quando poderiam serem baseadas em factos históricos armazenados pelos diversos sistemas. Genericamente, as organizações possuem muitos dados, mas na maioria dos casos extraem pouca informação, o que é um problema em termos de mercados competitivos. Como as organizações procuram evoluir e superar a concorrência nas tomadas de decisão, surge neste contexto o termo Business Intelligence(BI). A GisGeo Information Systems é uma empresa que desenvolve software baseado em SIG (sistemas de informação geográfica) recorrendo a uma filosofia de ferramentas open-source. O seu principal produto baseia-se na localização geográfica dos vários tipos de viaturas, na recolha de dados, e consequentemente a sua análise (quilómetros percorridos, duração de uma viagem entre dois pontos definidos, consumo de combustível, etc.). Neste âmbito surge o tema deste projeto que tem objetivo de dar uma perspetiva diferente aos dados existentes, cruzando os conceitos BI com o sistema implementado na empresa de acordo com a sua filosofia. Neste projeto são abordados alguns dos conceitos mais importantes adjacentes a BI como, por exemplo, modelo dimensional, data Warehouse, o processo ETL e OLAP, seguindo a metodologia de Ralph Kimball. São também estudadas algumas das principais ferramentas open-source existentes no mercado, assim como quais as suas vantagens/desvantagens relativamente entre elas. Em conclusão, é então apresentada a solução desenvolvida de acordo com os critérios enumerados pela empresa como prova de conceito da aplicabilidade da área Business Intelligence ao ramo de Sistemas de informação Geográfica (SIG), recorrendo a uma ferramenta open-source que suporte visualização dos dados através de dashboards.