Active Foreground Region Extraction and Tracking for Sports Video Annotation

Automatic video segmentation plays a vital role in sports videos annotation. This paper presents a fully automatic and computationally efficient algorithm for analysis of sports videos. Various methods of automatic shot boundary detection have been proposed to perform automatic video segmentation. These investigations mainly concentrate on detecting fades and dissolves for fast processing of the entire video scene without providing any additional feedback on object relativity within the shots. The goal of the proposed method is to identify regions that perform certain activities in a scene. The model uses some low-level feature video processing algorithms to extract the shot boundaries from a video scene and to identify dominant colours within these boundaries. An object classification method is used for clustering the seed distributions of the dominant colours to homogeneous regions. Using a simple tracking method a classification of these regions to active or static is performed. The efficiency of the proposed framework is demonstrated over a standard video benchmark with numerous types of sport events and the experimental results show that our algorithm can be used with high accuracy for automatic annotation of active regions for sport videos.

SEQUENTIAL DECISIONS AND PREDICTIONS IN NATURAL LANGUAGE PROCESSING

Natural language processing has achieved great success in a wide range of ap- plications, producing both commercial language services and open-source language tools. However, most methods take a static or batch approach, assuming that the model has all information it needs and makes a one-time prediction. In this disser- tation, we study dynamic problems where the input comes in a sequence instead of all at once, and the output must be produced while the input is arriving. In these problems, predictions are often made based only on partial information. We see this dynamic setting in many real-time, interactive applications. These problems usually involve a trade-off between the amount of input received (cost) and the quality of the output prediction (accuracy). Therefore, the evaluation considers both objectives (e.g., plotting a Pareto curve). Our goal is to develop a formal understanding of sequential prediction and decision-making problems in natural language processing and to propose efficient solutions. Toward this end, we present meta-algorithms that take an existent batch model and produce a dynamic model to handle sequential inputs and outputs. Webuild our framework upon theories of Markov Decision Process (MDP), which allows learning to trade off competing objectives in a principled way. The main machine learning techniques we use are from imitation learning and reinforcement learning, and we advance current techniques to tackle problems arising in our settings. We evaluate our algorithm on a variety of applications, including dependency parsing, machine translation, and question answering. We show that our approach achieves a better cost-accuracy trade-off than the batch approach and heuristic-based decision- making approaches. We first propose a general framework for cost-sensitive prediction, where dif- ferent parts of the input come at different costs. We formulate a decision-making process that selects pieces of the input sequentially, and the selection is adaptive to each instance. Our approach is evaluated on both standard classification tasks and a structured prediction task (dependency parsing). We show that it achieves similar prediction quality to methods that use all input, while inducing a much smaller cost. Next, we extend the framework to problems where the input is revealed incremen- tally in a fixed order. We study two applications: simultaneous machine translation and quiz bowl (incremental text classification). We discuss challenges in this set- ting and show that adding domain knowledge eases the decision-making problem. A central theme throughout the chapters is an MDP formulation of a challenging problem with sequential input/output and trade-off decisions, accompanied by a learning algorithm that solves the MDP.

Estimating abundance and spatial distribution patterns of the bubble crab Dotilla fenestrata (Crustacea : Brachyura)

The bubble crab Dotilla fenestrata forms very dense populations on the sand flats of the eastern coast of Inhaca Island, Mozambique, making it an interesting biological model to examine spatial distribution patterns and test the relative efficiency of common sampling methods. Due to its apparent ecological importance within the sandy intertidal community, understanding the factors ruling the dynamics of Dotilla populations is also a key issue. In this study, different techniques of estimating crab density are described, and the trends of spatial distribution of the different population categories are shown. The studied populations are arranged in discrete patches located at the well-drained crests of nearly parallel mega sand ripples. For a given sample size, there was an obvious gain in precision by using a stratified random sampling technique, considering discrete patches as strata, compared to the simple random design. Density average and variance differed considerably among patches since juveniles and ovigerous females were found clumped, with higher densities at the lower and upper shore levels, respectively. Burrow counting was found to be an adequate method for large-scale sampling, although consistently underestimating actual crab density by nearly half. Regression analyses suggested that crabs smaller than 2.9 mm carapace width tend to be undetected in visual burrow counts. A visual survey of sampling plots over several patches of a large Dotilla population showed that crab density varied in an interesting oscillating pattern, apparently following the topography of the sand flat. Patches extending to the lower shore contained higher densities than those mostly covering the higher shore. Within-patch density variability also pointed to the same trend, but the density increment towards the lowest shore level varied greatly among the patches compared.

Hierarchical spatial segregation of two Mediterranean vole species: the role of patch‑network structure and matrix composition

According to ecological theory, the coexistence of competitors in patchy environments may be facilitated by hierarchical spatial segregation along axes of environmental variation, but empirical evidence is limited. Cabrera and water voles show a metapopulation-like structure in Mediterranean farmland, where they are known to segregate along space, habitat, and time axes within habitat patches. Here, we assess whether segregation also occurs among and within landscapes, and how this is influenced by patch-network and matrix composition. We surveyed 75 landscapes, each covering 78 ha, where we mapped all habitat patches potentially suitable for Cabrera and water voles, and the area effectively occupied by each species (extent of occupancy). The relatively large water vole tended to be the sole occupant of landscapes with high habitat amount but relatively low patch density (i.e., with a few large patches), and with a predominantly agricultural matrix, whereas landscapes with high patch density (i.e.,many small patches) and low agricultural cover, tended to be occupied exclusively by the small Cabrera vole. The two species tended to co-occur in landscapes with intermediate patch-network and matrix characteristics, though their extents of occurrence were negatively correlated after controlling for environmental effects. In combination with our previous studies on the Cabrera-water vole system, these findings illustrated empirically the occurrence of hierarchical spatial segregation, ranging from withinpatches to among-landscapes. Overall, our study suggests that recognizing the hierarchical nature of spatial segregation patterns and their major environmental drivers should enhance our understanding of species coexistence in patchy environments.

Moving toward stock units identification based on spatial population structure of marine species in the Mediterranean Sea and adjacent waters through multidisciplinary and holistic approaches for the sustainability of fisheries resources

Investigating stock identity of marine species in a multidisciplinary holistic approach can reveal patterns of complex spatial population structure and signatures of potential local adaptation. The population structure of common sole (Solea solea) in the Mediterranean Sea was delineated using genomic and otolith data, including single nucleotide polymorphisms (SNPs) markers and otolith data. SNPs were correlated with environmental and spatial variables to evaluate the impact of these features on the actual genetic population structure. Integrated holistic approach was applied to combine the tracers with different spatio-temporal scales. SNPs data was also used to illustrate the population structure of European hake (Merluccius merluccius) within the Alboran Sea, extending into the neighboring Mediterranean Sea and Atlantic Ocean. The aim was to identify patterns of neutral and potential adaptive genetic variation by applying seascape genomic framework. Results from both genetic and otolith data suggested significant divergence among putative populations of common sole, confirming a clear separation between Western, Adriatic Sea and Eastern Mediterranean Sea. Evidence of fine-scale population structure in the Western Mediterranean Sea was observed at outlier loci level and in the Adriatic. Our study not only indicates that separation among Mediterranean sole population is led primarily by neutral processes, but it also suggests the presence of local adaptation influenced by environmental and spatial factors. The holistic approach by considering the spatio-temporal scales of variation confirmed that the same pattern of separation between these geographical sites is currently occurring and has occurred for many generations. Results showed the occurrence of population structure in Merluccius merluccius by detecting westward–eastward differentiation among populations and distinct subgroups at a fine geographical scale using outlier SNPs. These results enhance the knowledge of the population structure of commercially relevant species to support the application of spatial stock assessment models, including a redefinition of fishery management units.

Central Auditory Processing Outcome After Stroke In Children.

To investigate central auditory processing in children with unilateral stroke and to verify whether the hemisphere affected by the lesion influenced auditory competence. 23 children (13 male) between 7 and 16 years old were evaluated through speech-in-noise tests (auditory closure); dichotic digit test and staggered spondaic word test (selective attention); pitch pattern and duration pattern sequence tests (temporal processing) and their results were compared with control children. Auditory competence was established according to the performance in auditory analysis ability. Was verified similar performance between groups in auditory closure ability and pronounced deficits in selective attention and temporal processing abilities. Most children with stroke showed an impaired auditory ability in a moderate degree. Children with stroke showed deficits in auditory processing and the degree of impairment was not related to the hemisphere affected by the lesion.

Effects Of Sterilization Methods On The Physical, Chemical, And Biological Properties Of Silk Fibroin Membranes.

Silk fibroin has been widely explored for many biomedical applications, due to its biocompatibility and biodegradability. Sterilization is a fundamental step in biomaterials processing and it must not jeopardize the functionality of medical devices. The aim of this study was to analyze the influence of different sterilization methods in the physical, chemical, and biological characteristics of dense and porous silk fibroin membranes. Silk fibroin membranes were treated by several procedures: immersion in 70% ethanol solution, ultraviolet radiation, autoclave, ethylene oxide, and gamma radiation, and were analyzed by scanning electron microscopy, Fourier-transformed infrared spectroscopy (FTIR), X-ray diffraction, tensile strength and in vitro cytotoxicity to Chinese hamster ovary cells. The results indicated that the sterilization methods did not cause perceivable morphological changes in the membranes and the membranes were not toxic to cells. The sterilization methods that used organic solvent or an increased humidity and/or temperature (70% ethanol, autoclave, and ethylene oxide) increased the silk II content in the membranes: the dense membranes became more brittle, while the porous membranes showed increased strength at break. Membranes that underwent sterilization by UV and gamma radiation presented properties similar to the nonsterilized membranes, mainly for tensile strength and FTIR results.

Nuclear and mitochondrial DNA markers in traceability of retail beef samples

Several characteristics are important in a traceability system of animal products, such as age at slaughter, breed composition, besides information of the productive chain. In general, the certification agent records information about the animals and the system which it came from, although cannot guarantee that the slaughtering, meat processing and distribution are error proof. Besides, there is a differential price, at least at the international market, based on sex and breed composition of the animals. Genetic markers allow identification of characteristics controlled in the beef cattle traceability program, as sex and breed composition, in order to correctly identify and appraise the final product for the consumer. The hypothesis of this study was that the majority beef samples retailed in the local market originate from female with a great participation of zebu breeds. Therefore, the objective of this work was to characterize retail beef samples with DNA markers that identify cattle sex and breed composition. Within 10 beef shops localized in Pirassununga, SP, Brazil, 61 samples were collected, all were genotyped as harboring Bos taurus mitochondrial DNA and 18 were positive for the Y chromosome amplification (male). For the marker sat1711b-Msp I the frequency of the allele A was 0.278 and for the marker Lhr-Hha I the frequency of the allele T was 0.417. The results of sat1711b-Msp I and Lhr-Hha I allelic frequencies are suggestive that the proportion of indicus genome compared with the taurine genome in the market meat is smaller than the observed in the Nellore breed. The procedure described in this study identified sex and subspecies characteristics of beef meat samples, with potential application in meat products certification in special as an auxiliary tool in beef cattle traceability programs.

Mechanical, thermal and morphological properties of glutaraldehyde crosslinked bovine pericardium followed by glutamic acid treatment

Major problems with valve bioprostheses are associated with progressive structural deterioration and calcification, directly associated with the use of glutaraldehyde (GA). This work describes the effects of GA processing and borate/glutamic acid buffer treatment on the mechanical, thermal and morphological properties of 0.5% GA crosslinked bovine pericardium (BP). The results showed that while the treatment of 0.5% GA crosslinked BP with borate/glutamic acid significantly improves the mechanical properties, it had no visible effect on surface morphology. Better surface preservation was only achieved for BP pre-treated with a lower GA concentration followed by the conventional treatment (0.5% GA). Improvements in mechanical properties probably arises from structural changes probably involving the depolymerization of polymeric GA crosslinks and an increase electrostatic interaction due to covalent binding of glutamic acid to free carbonyl groups (Schiff base).The results indicate that the treatment GA crosslinked BP with borate/glutamic acid buffer may be an attractive procedure for the manufacture of heart valve bioprostheses.

UNIQUENESS AND NONUNIQUENESS RESULTS FOR A CERTAIN CLASS OF ALMOST PERIODIC DISTRIBUTIONS

We consider distributions u is an element of S'(R) of the form u(t) = Sigma(n is an element of N) a(n)e(i lambda nt), where (a(n))(n is an element of N) subset of C and Lambda = (lambda n)(n is an element of N) subset of R have the following properties: (a(n))(n is an element of N) is an element of s', that is, there is a q is an element of N such that (n(-q) a(n))(n is an element of N) is an element of l(1); for the real sequence., there are n(0) is an element of N, C > 0, and alpha > 0 such that n >= n(0) double right arrow vertical bar lambda(n)vertical bar >= Cn(alpha). Let I(epsilon) subset of R be an interval of length epsilon. We prove that for given Lambda, (1) if Lambda = O(n(alpha)) with alpha < 1, then there exists epsilon > 0 such that u vertical bar I(epsilon) = 0 double right arrow u 0; (2) if Lambda = O(n) is uniformly discrete, then there exists epsilon > 0 such that u vertical bar I(epsilon) = 0 double right arrow u 0; (3) if alpha > 1 and. is uniformly discrete, then for all epsilon > 0, u vertical bar I(epsilon) = 0 double right arrow u = 0. Since distributions of the above mentioned form are very common in engineering, as in the case of the modeling of ocean waves, signal processing, and vibrations of beams, plates, and shells, those uniqueness and nonuniqueness results have important consequences for identification problems in the applied sciences. We show an identification method and close this article with a simple example to show that the recovery of geometrical imperfections in a cylindrical shell is possible from a measurement of its dynamics.

Stability and ergodicity of piecewise deterministic Markov processes

The main goal of this paper is to establish some equivalence results on stability, recurrence, and ergodicity between a piecewise deterministic Markov process ( PDMP) {X( t)} and an embedded discrete-time Markov chain {Theta(n)} generated by a Markov kernel G that can be explicitly characterized in terms of the three local characteristics of the PDMP, leading to tractable criterion results. First we establish some important results characterizing {Theta(n)} as a sampling of the PDMP {X( t)} and deriving a connection between the probability of the first return time to a set for the discrete-time Markov chains generated by G and the resolvent kernel R of the PDMP. From these results we obtain equivalence results regarding irreducibility, existence of sigma-finite invariant measures, and ( positive) recurrence and ( positive) Harris recurrence between {X( t)} and {Theta(n)}, generalizing the results of [ F. Dufour and O. L. V. Costa, SIAM J. Control Optim., 37 ( 1999), pp. 1483-1502] in several directions. Sufficient conditions in terms of a modified Foster-Lyapunov criterion are also presented to ensure positive Harris recurrence and ergodicity of the PDMP. We illustrate the use of these conditions by showing the ergodicity of a capacity expansion model.

NGC 7097: THE ACTIVE GALACTIC NUCLEUS AND ITS MIRROR, REVEALED BY PRINCIPAL COMPONENT ANALYSIS TOMOGRAPHY

Three-dimensional spectroscopy techniques are becoming more and more popular, producing an increasing number of large data cubes. The challenge of extracting information from these cubes requires the development of new techniques for data processing and analysis. We apply the recently developed technique of principal component analysis (PCA) tomography to a data cube from the center of the elliptical galaxy NGC 7097 and show that this technique is effective in decomposing the data into physically interpretable information. We find that the first five principal components of our data are associated with distinct physical characteristics. In particular, we detect a low-ionization nuclear-emitting region (LINER) with a weak broad component in the Balmer lines. Two images of the LINER are present in our data, one seen through a disk of gas and dust, and the other after scattering by free electrons and/or dust particles in the ionization cone. Furthermore, we extract the spectrum of the LINER, decontaminated from stellar and extended nebular emission, using only the technique of PCA tomography. We anticipate that the scattered image has polarized light due to its scattered nature.

Polarity-Dependent Transcranial Direct Current Stimulation Effects on Central Auditory Processing

Given the polarity dependent effects of transcranial direct current stimulation (tDCS) in facilitating or inhibiting neuronal processing, and tDCS effects on pitch perception, we tested the effects of tDCS on temporal aspects of auditory processing. We aimed to change baseline activity of the auditory cortex using tDCS as to modulate temporal aspects of auditory processing in healthy subjects without hearing impairment. Eleven subjects received 2mA bilateral anodal, cathodal and sham tDCS over auditory cortex in a randomized and counterbalanced order. Subjects were evaluated by the Random Gap Detection Test (RGDT), a test measuring temporal processing abilities in the auditory domain, before and during the stimulation. Statistical analysis revealed a significant interaction effect of time vs. tDCS condition for 4000 Hz and for clicks. Post-hoc tests showed significant differences according to stimulation polarity on RGDT performance: anodal improved 22.5% and cathodal decreased 54.5% subjects' performance, as compared to baseline. For clicks, anodal also increased performance in 29.4% when compared to baseline. tDCS presented polarity-dependent effects on the activity of the auditory cortex, which results in a positive or negative impact in a temporal resolution task performance. These results encourage further studies exploring tDCS in central auditory processing disorders.

Assessment of groundwater recharge and water fluxes of the Guarani Aquifer System, Brazil

The groundwater recharge and water fluxes of the Guarani Aquifer System in the state of Sao Paulo in Brazil were assessed through a numeric model. The study area (6,748 km(2)) comprises Jacar,-Gua double dagger A(0) and Jacar,-Pepira River watersheds, tributaries of the Tiet River in the central region of the state. GIS based tools were used in the storage, processing and analysis of data. Main hydrologic phenomena were selected, leading to a groundwater conceptual model, taking into account the significant outcrops occurring in the study area. Six recharge zones were related to the geologic formation and structures of the semi-confined and phreatic aquifer. The model was calibrated against the baseflows and static water levels of the wells. The results emphasize the strong interaction of groundwater flows between watersheds and the groundwater inflow into the rivers. It has been concluded that lateral groundwater exchanges between basins, the deep discharges to the regional system, and well exploitation were not significant aquifer outflows when compared to the aquifer recharge. The results have shown that the inflows from the river into the aquifer are significant and have the utmost importance since the aquifer is potentially more vulnerable in these places.

Planning and operation of large-scale water distribution systems with preemptive priorities

This paper describes the development of an optimization model for the management and operation of a large-scale, multireservoir water supply distribution system with preemptive priorities. The model considers multiobjectives and hedging rules. During periods of drought, when water supply is insufficient to meet the planned demand, appropriate rationing factors are applied to reduce water supply. In this paper, a water distribution system is formulated as a network and solved by the GAMS modeling system for mathematical programming and optimization. A user-friendly interface is developed to facilitate the manipulation of data and to generate graphs and tables for decision makers. The optimization model and its interface form a decision support system (DSS), which can be used to configure a water distribution system to facilitate capacity expansion and reliability studies. Several examples are presented to demonstrate the utility and versatility of the developed DSS under different supply and demand scenarios, including applications to one of the largest water supply systems in the world, the Sao Paulo Metropolitan Area Water Supply Distribution System in Brazil.