A probabilistic integrated object recognition and tracking framework

This paper describes a probabilistic integrated object recognition and tracking framework called PIORT, together with two specific methods derived from it, which are evaluated experimentally in several test video sequences. The first step in the proposed framework is a static recognition module that provides class probabilities for each pixel of the image from a set of local features. These probabilities are updated dynamically and supplied to a tracking decision module capable of handling full and partial occlusions. The two specific methods presented use RGB color features and differ in the classifier implemented: one is a Bayesian method based on maximum likelihood and the other one is based on a neural network. The experimental results obtained have shown that, on one hand, the neural net based approach performs similarly and sometimes better than the Bayesian approach when they are integrated within the tracking framework. And on the other hand, our PIORT methods have achieved better results when compared to other published tracking methods in video sequences taken with a moving camera and including full and partial occlusions of the tracked object.     

Finding multiple solutions in job shop scheduling by niching genetic algorithms

The interest in multimodal optimization methods is increasing in the last years. The objective is to find multiple solutions that allow the expert to choose the solution that better adapts to the actual conditions. Niching methods extend genetic algorithms to domains that require the identification of multiple solutions. There are different niching genetic algorithms: sharing, clearing, crowding and sequential, etc. The aim of this study is to study the applicability and the behavior of several niching genetic algorithms in solving job shop scheduling problems, by establishing a criterion in the use of different methods according to the needs of the expert. We will experiment with different instances of this problem, analyzing the behavior of the algorithms from the efficacy and diversity points of view.     

Immunohistochemistry of neuronal nitric oxide synthase and protein nitration in the striatum of the aged rat

To ascertain the possible implications of the nitric oxide (NO*) producing system in striatal senescence, and by using immunohistochemistry and image-processing approaches, we describe the presence of the enzyme nitric oxide synthase (NOS), the NADPH-diaphorase (NADPH-d) histochemical marker, and nitrotyrosine-derived complexes (N-Tyr) in the striatum of adult and aged rats. The results showed neuronal NOS immunoreactive (nNOS-IR) aspiny medium-sized neurons and nervous fibres in both age groups, with no variation in the percentage of immunoreactive area but a significant decrease in the intensity and in the number of somata with age, which were not related to the observed increase with age of the striatal bundles of the white matter. In addition, NADPH-d activity was detected in neurons with morphology similar to that of the nNOS-IR cells; a decrease in the percentage of area per field and in the number of cells, but an increase in the intensity of staining for the NADPH-d histochemical marker, were detected with age. The number of neuronal NADPH-d somata was higher than for the nNOS-IR ones in both age groups. Moreover, N-Tyr-IR complexes were observed in cells (neurons and glia) and fibres, with a significant increase in the percentage of the area of immunoreaction, related to the increase of white matter, but a decrease in intensity for the aged group. On the other hand, we did not detect the inducible isoform (iNOS) either in adult or in aged rats. Taken together, these results support the contention that NADPH-d staining is not such an unambiguous marker for nNOS, and that increased protein nitration may participate in striatal aging.     

Evaluation of alternatives for the broadcast operation in Kademlia under churn

During recent years, considerable effort has been devoted to the enhancement of Distributed Hash Table (DHT) systems with broadcasting capabilities. Such systems typically provide individual node routing but a broadcast primitive is required for functionalities such as information dissemination or data aggregation. Broadcasting can also be used as the basis for partial keyword searches. Little work has however specifically addressed Kademlia, a well known DHT, used in real applications. Our work exposes the particularities of this system, notably its XOR-based distance metrics, and analytically studies what broadcasting techniques can be applied to it. A model that estimates node coverage as a function of the probability that individual messages reach their destination has been also developed. For validation, several broadcasting algorithms have been implemented and comprehensively evaluated, considering node coverage, messages to nodes ratio, latency and imbalance factor. Moreover, several techniques are proposed to enhance the bare protocols when adverse circumstances such as churn and failure rate conditions are present. These include redundancy, resubmissions or flooding, and also combinations of those. All have been implemented and fully tested. An analysis of the strengths and weaknesses of algorithms and additional techniques, and a discussion on the choices and compromises to make, depending on system characteristics or application priorities, is finally presented.     

Electrode surface treatments in sludge electro-osmosis dewatering

The sewage sludge dewatering produced by wastewater treatment plants (WWTP) is a multifaceted process due to the presence of colloid fractions. Electro-osmosis could be a suitable technique to reduce the water content of the final sludge. Electric fields of 10, 15, and 20?V/cm have been studied for electro-osmosis tests under the pressure of a static or rotating piston, obtaining a dry solids content up to 40–45%, with respect to 25–30% obtained by mechanical methods. In order to optimize the process, the corrosion behavior and the wear of the anodic material appear to be the main critical aspects, due to the high circulating current density and the use of a rotating electrode. We compared the efficiency and the corrosion resistance of dimensionally stable anodes (DSA) with respect to bare stainless steel (AISI 304) and stainless steel coated by PVD technique with TiN, AlTiN, and DLC. Characterization of the anode surfaces by SEM and potentiodynamic tests show that DSA is the most suitable material for our application. However, efficiencies of the electro-osmosis processes have been found comparable, in terms of developed current densities and total energy consumptions, for short-test duration.     

Structural,optical and electrical properties of silicon nanocrystals embedded in SixC1−x/SiC multilayer systems for photovoltaic applications

In this work we present a structural, optical and electrical characterization of Si_xC_1?x/SiC multilayer systems with different silicon content. After the deposition process, an annealing treatment was carried out in order to induce the silicon nanocrystals formation. By means of energy-filtered transmission electron microscopy (EFTEM) we observed the structural morphology of the multilayers and the presence of crystallized silicon nanoprecipitates for samples annealed up to 1100 °C. We discuss the suitability of optical techniques such as Raman scattering and reflectance and transmittance (R&T) for the evaluation of the crystalline fraction of our samples at different silicon excess ranges. In addition, the combination of R&T measurements with simulation has proved to be a useful instrument to confirm the structural properties observed by EFTEM. Finally, we explore the origin of the extremely high current density revealed by electrical measurements, probably due to the presence of an undesired defective SiC_yO_z ternary compound layer, already supported by the structural and optical results. Nevertheless, the variation of the electrical measurements with the silicon amount indicates a small but significant contribution from the multilayers.     

Supercomputing and grid computing on the verification of covering arrays

The Covering Arrays (CAs) are mathematical objects with minimal coverage and maximum cardinality that are a good tool for the design of experiments. A?covering array is an N×k matrix over an alphabet v s.t. each N×k subset contains at least one time each combination from {0,1,??,v?1} ^t , given a positive integer value?t. The process of ensuring that a CA contains each of the v ^t combinations is called verification of CA. In this paper, we present an algorithm for CA verification and its implementation details in three different computation paradigms: (a)?sequential approach (SA); (b)?parallel approach (PA); and (c)?Grid approach (GA). Four different PAs were compared in their performance of verifying a matrix as a CA; the PA with the best performance was included in a different experimentation where the three paradigms, SA, PA, and GA were compared in a benchmark composed by 45 possible CA instances. The results showed the limitations of the different paradigms when solving the verification of CA problem, and points out the necessity of a Grid approach to solve the problem when the size of a CA grows.