Solução de navegação inercial para o sistema plasys

Neste trabalho faz-se uma pesquisa e análise dos conceitos associados à navegação inercial para estimar a distância percorrida por uma pessoa. Foi desenvolvida uma plataforma de hardware para implementar os algoritmos de navegação inercial e estudar a marcha humana. Os testes efetuados permitiram adaptar os algoritmos de navegação inercial para humanos e testar várias técnicas para reduzir o erro na estimativa da distância percorrida. O sistema desenvolvido é um sistema modular que permite estudar o efeito da inserção de novos sensores. Desta forma foram adaptados os algoritmos de navegação para permitir a utilização da informação dos sensores de força colocados na planta do pé do utilizador. A partir desta arquitetura foram efetuadas duas abordagens para o cálculo da distância percorrida por uma pessoa. A primeira abordagem estima a distância percorrida considerando o número de passos. A segunda abordagem faz uma estimação da distância percorrida com base nos algoritmos de navegação inercial. Foram realizados um conjunto de testes para comparar os erros na estimativa da distância percorrida pelas abordagens efetuadas. A primeira abordagem obteve um erro médio de 4,103% em várias cadências de passo. Este erro foi obtido após sintonia para o utilizador em questão. A segunda abordagem obteve um erro de 9,423%. De forma a reduzir o erro recorreu-se ao filtro de Kalman o que levou a uma redução do erro para 9,192%. Por fim, recorreu-se aos sensores de força que permitiram uma redução para 8,172%. A segunda abordagem apesar de ter um erro maior não depende do utilizador pois não necessita de sintonia dos parâmetros para estimar a distância para cada pessoa. Os testes efetuados permitiram, através dos sensores de força, testar a importância da força sentida pela planta do pé para aferir a fase do ciclo de marcha. Esta capacidade permite reduzir os erros na estimativa da distância percorrida e obter uma maior robustez neste tipo de sistemas.

Psychosocial Morbidity and its Correlates in Cancer Patients of the Mediterranean Area: Findings from the Southern European Psycho-Oncology Study

BACKGROUND: A few and partial data are available on psychosocial morbidity among cancer patients in Mediterranean countries. As a part of a more general investigation (Southern European Psycho-Oncology Study-SEPOS), the rate of psychosocial morbidity and its correlation with clinical and cultural variables were examined in cancer patients in Italy, Portugal and Spain. METHODS: A convenience sample of cancer outpatients with good performance status and no cognitive impairment were approached. The Hospital Anxiety-Depression scale (HAD-S), the Mini-Mental Adjustment to Cancer scale (Mini-MAC), and the Cancer Worries Inventory (CWI) were used to measure psychological morbidity, coping strategies and concerns about illness. RESULTS: Of 277 patients, 34% had pathological scores ("borderline cases" plus "true cases") on HAD-S Anxiety and 24.9% on HAD-S Depression. Total psychiatric "caseness" was 28.5% and 16.6%, according to different HAD cut-offs (14 and 19, respectively). Significant relationships of HAD-S Anxiety, HAD-S Depression, HAD-S Total score, with Mini-MAC Hopeless and Anxious Preoccupation, and CWI score were found. No differences emerged between countries on psychosocial morbidity, while some differences emerged between the countries on coping mechanisms. Furthermore, Fatalism, Avoidance and marginally Hopeless were higher compared to studies carried out in English-speaking countries. LIMITATIONS: The relatively small sample size and the good performance status prevent us to generalize data on patients with different cancer sites and advanced phase of illness. CONCLUSIONS: One-third of the patients presented anxiety and depressive morbidity, with significant differences in characteristics of coping in Mediterranean countries in comparison with English-speaking countries.

Standard commercial education robotic platform: intermediate solution to teaching robotics

Teaching robotics to students at the beginning of their studies has become a huge challenge. Simulation environments can be an effective solution to that challenge where students can interact with simulated robots and have the first contact with robotic constraints. From our previous experience with simulation environments it was possible to observe that students with lower background knowledge in robotics where able to deal with a limited number of constraints, implement a simulated robotic platform and study several sensors. The question is: after this first phase what should be the best approach? Should the student start developing their own hardware? Hardware development is a very important part of an engineer's education but it can also be a difficult phase that could lead to discouragement and loss of motivation in some students. Considering the previous constraints and first year engineering students’ high abandonment rate it is important to develop teaching strategies to deal with this problem in a feasible way. The solution that we propose is the integration of a low-cost standard robotic platform WowWee Rovio as an intermediate solution between the simulation phase and the stage where the students can develop their own robots. This approach will allow the students to keep working in robotic areas such as: cooperative behaviour, perception, navigation and data fusion. The propose approach proved to be a motivation step not only for the students but also for the teachers. Students and teachers were able to reach an agreement between the level of demand imposed by the teachers and satisfaction/motivation of the students.

Multi-robot cooperative stereo for outdoor scenarios

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

New integrative computational approaches unveil the Saccharomyces cerevisiae pheno-metabolomic fermentative profile and allow strain selection for winemaking

During must fermentation by Saccharomyces cerevisiae strains thousands of volatile aroma compounds are formed. The objective of the present work was to adapt computational approaches to analyze pheno-metabolomic diversity of a S. cerevisiae strain collection with different origins. Phenotypic and genetic characterization together with individual must fermentations were performed, and metabolites relevant to aromatic profiles were determined. Experimental results were projected onto a common coordinates system, revealing 17 statistical-relevant multi-dimensional modules, combining sets of most-correlated features of noteworthy biological importance. The present method allowed, as a breakthrough, to combine genetic, phenotypic and metabolomic data, which has not been possible so far due to difficulties in comparing different types of data. Therefore, the proposed computational approach revealed as successful to shed light into the holistic characterization of S. cerevisiae pheno-metabolome in must fermentative conditions. This will allow the identification of combined relevant features with application in selection of good winemaking strains.

Meliponini neotropicais: o gênero Partamona Schwarz, 1939 (Hymenoptera, Apidae, Apinae) - bionomia e biogeografia

This work, dedicated to the study of nesting habits of the species of the Neotropical genus Partamona Schwarz, is a sequence to the taxonomic revision recently published elsewhere. A total of 214 nests and nest aggregations of 18 species [Partamona epiphytophila Pedro & Camargo, 2003; P. testacea (Klug, 1807); P. mourei Camargo, 1980; P. vicina Camargo, 1980; P. auripennis Pedro & Camargo, 2003; P. combinata Pedro & Camargo, 2003; P. chapadicola Pedro & Camargo, 2003; P. nhambiquara Pedro & Camargo, 2003; P. ferreirai Pedro & Camargo, 2003; P. pearsoni (Schwarz, 1938); P. gregaria Pedro & Camargo, 2003; P. batesi Pedro & Camargo, 2003; P. ailyae Camargo, 1980; P. cupira (Smith, 1863); P. mulata Moure in Camargo, 1980; P. seridoensis Pedro & Camargo, 2003; P. criptica Pedro & Camargo, 2003; P. helleri (Friese, 1900)] were studied , including data about habitat, substrate, structural characteristics, construction materials and behavior. The descriptions of the nests are illustrated with 48 drawings. Partial data of the nests of P. bilineata (Say, 1837), P. xanthogastra Pedro & Camargo, 1997, P. orizabaensis (Strand, 1919), P. peckolti (Friese, 1901), P. aequatoriana Camargo, 1980, P. musarum (Cockerell, 1917) and P. rustica Pedro & Camargo, 2003 are also presented. Nests of P. grandipennis (Schwarz, 1951), P. yungarum Pedro & Camargo, 2003, P. subtilis Pedro & Camargo, 2003, P. vitae Pedro & Camargo, 2003, P. nigrior (Cockerell, 1925), P. sooretamae Pedro & Camargo, 2003 and P. littoralis Pedro & Camargo, 2003 are unknown. The species of Partamona build notable nest entrance structures, with special surfaces for incoming / exiting bees; some of them are extremely well-elaborated and ornamented, serving as flight orientation targets. All species endemic to western Ecuador to Mexico with known nesting habits (P. orizabaensis, P. peckolti, P. xanthogastra, P. bilineata, P. aequatoriana and P. musarum) build their nests in several substrates, non-associated with termitaria, such as cavities and crevices in walls, among roots of epiphytes and in bases of palm leaves, in abandoned bird nests, under bridges, and in other protected places, except P. peckolti that occasionally occupies termite nests. In South America, on the eastern side of the Andes, only P. epiphytophila and P. helleri nest among roots of epiphytes and other substrates, non-associated with termitaria. All other species studied (P. batesi, P. gregaria, P. pearsoni, P. ferreirai, P. chapadicola, P. nhambiquara, P. vicina, P. mourei, P. auripennis, P. combinata, P. cupira, P. mulata, P. ailyae, P. seridoensis, P. criptica and P. rustica) nest inside active termite nests, whether epigeous or arboreous. The only species that builds obligate subterranean nests, associated or not with termite or ant nests (Atta spp.) is P. testacea. Nests of Partamona have one vestibular chamber (autapomorphic for the genus) closely adjacent to the entrance, filled with a labyrinth of anastomosing pillars and connectives, made of earth and resins. One principal chamber exists for food and brood, but in some species one or more additional chambers are filled with food storage pots. In nests of P. vicina, there is one atrium or "false nest", between the vestibule and the brood chamber, which contains involucral sheaths, cells and empty pots. All structures of the nest are supported by permanent pillars made of earth and resins (another autapomorphy of the genus). The characters concerning nesting habits were coded and combined with morphological and biogeographic data, in order to hypothesize the evolutive scenario of the genus using cladistic methodology. The phylogenetic hypothesis presented is the following: (((((P. bilineata (P. grandipennis, P. xanthogastra)) (P. orizabaensis, P. peckolti)) (P. aequatoriana, P. musarum)) P. epiphytophila, P. yungarum, P. subtilis, P. vitae) (((((P. testacea (P. mourei, P. vicina)) (P. nigrior (P. auripennis, P. combinata))) (P. ferreirai (P. pearsoni (P. gregaria (P. batesi (P. chapadicola, P. nhambiquara)))))) ((((P. ailyae, P. sooretamae) P. cupira, P. mulata) P. seridoensis) P. criptica, P. rustica, P. littoralis)) P. helleri))). One area cladogram is presented. Dates of some vicariance / cladogenesis events are suggested. For bilineata / epiphytophila group, which inhabits the Southwestern Amazonia and the Chocó-Mexican biogeographical components, the origin of ancestral species is attributed to the Middle Miocene, when the transgressions of the Maracaibo and Paranense seas isolated the tropical northwestern South America from the eastern continental land mass. The next cladogenic event in the history of the bilineata / epiphytophila group is attributed to the Plio-Pleistocene, when the Ecuadorian Andes reached more than 3000 m, and the ancestral species was fragmented in two populations, one occupying the western Andes (ancestral species of the bilineata subgroup) and other the southwestern Amazon (ancestral species of the epiphytophila subgroup). Other aspects of the history of Partamona are also discussed.

Heel and toe clearance estimation for gait analysis using wireless inertial sensors.

Tripping is considered a major cause of fall in older people. Therefore, foot clearance (i.e., height of the foot above ground during swing phase) could be a key factor to better understand the complex relationship between gait and falls. This paper presents a new method to estimate clearance using a foot-worn and wireless inertial sensor system. The method relies on the computation of foot orientation and trajectory from sensors signal data fusion, combined with the temporal detection of toe-off and heel-strike events. Based on a kinematic model that automatically estimates sensor position relative to the foot, heel and toe trajectories are estimated. 2-D and 3-D models are presented with different solving approaches, and validated against an optical motion capture system on 12 healthy adults performing short walking trials at self-selected, slow, and fast speed. Parameters corresponding to local minimum and maximum of heel and toe clearance were extracted and showed accuracy ± precision of 4.1 ± 2.3 cm for maximal heel clearance and 1.3 ± 0.9 cm for minimal toe clearance compared to the reference. The system is lightweight, wireless, easy to wear and to use, and provide a new and useful tool for routine clinical assessment of gait outside a dedicated laboratory.

Recent advances in remote sensing image processing

Remote sensing image processing is nowadays a mature research area. The techniques developed in the field allow many real-life applications with great societal value. For instance, urban monitoring, fire detection or flood prediction can have a great impact on economical and environmental issues. To attain such objectives, the remote sensing community has turned into a multidisciplinary field of science that embraces physics, signal theory, computer science, electronics, and communications. From a machine learning and signal/image processing point of view, all the applications are tackled under specific formalisms, such as classification and clustering, regression and function approximation, image coding, restoration and enhancement, source unmixing, data fusion or feature selection and extraction. This paper serves as a survey of methods and applications, and reviews the last methodological advances in remote sensing image processing.

Land use/cover classification in the Brazilian Amazon using satellite images

Land use/cover classification is one of the most important applications in remote sensing. However, mapping accurate land use/cover spatial distribution is a challenge, particularly in moist tropical regions, due to the complex biophysical environment and limitations of remote sensing data per se. This paper reviews experiments related to land use/cover classification in the Brazilian Amazon for a decade. Through comprehensive analysis of the classification results, it is concluded that spatial information inherent in remote sensing data plays an essential role in improving land use/cover classification. Incorporation of suitable textural images into multispectral bands and use of segmentation‑based method are valuable ways to improve land use/cover classification, especially for high spatial resolution images. Data fusion of multi‑resolution images within optical sensor data is vital for visual interpretation, but may not improve classification performance. In contrast, integration of optical and radar data did improve classification performance when the proper data fusion method was used. Among the classification algorithms available, the maximum likelihood classifier is still an important method for providing reasonably good accuracy, but nonparametric algorithms, such as classification tree analysis, have the potential to provide better results. However, they often require more time to achieve parametric optimization. Proper use of hierarchical‑based methods is fundamental for developing accurate land use/cover classification, mainly from historical remotely sensed data.

Robust Detection of Incumbents in Cognitive Radio Networks Using Groups

Cognitive radio is a wireless technology aimed at improvingthe efficiency use of the radio-electric spectrum, thus facilitating a reductionin the load on the free frequency bands. Cognitive radio networkscan scan the spectrum and adapt their parameters to operate in the unoccupiedbands. To avoid interfering with licensed users operating on a givenchannel, the networks need to be highly sensitive, which is achieved byusing cooperative sensing methods. Current cooperative sensing methodsare not robust enough against occasional or continuous attacks. This articleoutlines a Group Fusion method that takes into account the behavior ofusers over the short and long term. On fusing the data, the method is basedon giving more weight to user groups that are more unanimous in their decisions.Simulations have been performed in a dynamic environment withinterferences. Results prove that when attackers are present (both reiterativeor sporadic), the proposed Group Fusion method has superior sensingcapability than other methods.

Social network extraction and analysis based on multimodal dyadic interaction

Social interactions are a very important component in people"s lives. Social network analysis has become a common technique used to model and quantify the properties of social interactions. In this paper, we propose an integrated framework to explore the characteristics of a social network extracted from multimodal dyadic interactions. For our study, we used a set of videos belonging to New York Times" Blogging Heads opinion blog. The Social Network is represented as an oriented graph, whose directed links are determined by the Influence Model. The links" weights are a measure of the"influence" a person has over the other. The states of the Influence Model encode automatically extracted audio/visual features from our videos using state-of-the art algorithms. Our results are reported in terms of accuracy of audio/visual data fusion for speaker segmentation and centrality measures used to characterize the extracted social network.

Preparation and thermal decomposition of copper(II), zinc(II) and cadmium(II) chelates with 8-hydroxyquinoline

When the compounds are heated in an inert atmosphere it can be verified the consecutive partial sublimation, fusion, partial volatilization and partial thermal decomposition of the anhydrous complexes. When in an oxidating atmosphere the above process is only verified to Cu(II) chelates. Anhydrous copper(II) complexes present a monoclinic structure in the b form and the volatilized compound in a a form. Zinc(II) and cadmium(II) hydrated complexes are isomorphous and they present different cell dimensions from those reported previously.

Review of Robust Cooperative Spectrum Sensing Techniques for Cognitive Radio Networks

Cognitive radio networks sense spectrum occupancy and manage themselvesto operate in unused bands without disturbing licensed users. The detection capability of aradio system can be enhanced if the sensing process is performed jointly by a group of nodesso that the effects of wireless fading and shadowing can be minimized. However, taking acollaborative approach poses new security threats to the system as nodes can report falsesensing data to reach a wrong decision. This paper makes a review of secure cooperativespectrum sensing in cognitive radio networks. The main objective of these protocols is toprovide an accurate resolution about the availability of some spectrum channels, ensuring thecontribution from incapable users as well as malicious ones is discarded. Issues, advantagesand disadvantages of such protocols are investigated and summarized.

Study of ligand-based virtual screening tools in computer-aided drug design

Virtual screening is a central technique in drug discovery today. Millions of molecules can be tested in silico with the aim to only select the most promising and test them experimentally. The topic of this thesis is ligand-based virtual screening tools which take existing active molecules as starting point for finding new drug candidates. One goal of this thesis was to build a model that gives the probability that two molecules are biologically similar as function of one or more chemical similarity scores. Another important goal was to evaluate how well different ligand-based virtual screening tools are able to distinguish active molecules from inactives. One more criterion set for the virtual screening tools was their applicability in scaffold-hopping, i.e. finding new active chemotypes. In the first part of the work, a link was defined between the abstract chemical similarity score given by a screening tool and the probability that the two molecules are biologically similar. These results help to decide objectively which virtual screening hits to test experimentally. The work also resulted in a new type of data fusion method when using two or more tools. In the second part, five ligand-based virtual screening tools were evaluated and their performance was found to be generally poor. Three reasons for this were proposed: false negatives in the benchmark sets, active molecules that do not share the binding mode, and activity cliffs. In the third part of the study, a novel visualization and quantification method is presented for evaluation of the scaffold-hopping ability of virtual screening tools.

A mixture of experts network structure construction algorithm for modelling and control

This paper introduces a new fast, effective and practical model structure construction algorithm for a mixture of experts network system utilising only process data. The algorithm is based on a novel forward constrained regression procedure. Given a full set of the experts as potential model bases, the structure construction algorithm, formed on the forward constrained regression procedure, selects the most significant model base one by one so as to minimise the overall system approximation error at each iteration, while the gate parameters in the mixture of experts network system are accordingly adjusted so as to satisfy the convex constraints required in the derivation of the forward constrained regression procedure. The procedure continues until a proper system model is constructed that utilises some or all of the experts. A pruning algorithm of the consequent mixture of experts network system is also derived to generate an overall parsimonious construction algorithm. Numerical examples are provided to demonstrate the effectiveness of the new algorithms. The mixture of experts network framework can be applied to a wide variety of applications ranging from multiple model controller synthesis to multi-sensor data fusion.