864 resultados para binary search
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The challenge of moving past the classic Window Icons Menus Pointer (WIMP) interface, i.e. by turning it ‘3D’, has resulted in much research and development. To evaluate the impact of 3D on the ‘finding a target picture in a folder’ task, we built a 3D WIMP interface that allowed the systematic manipulation of visual depth, visual aides, semantic category distribution of targets versus non-targets; and the detailed measurement of lower-level stimuli features. Across two separate experiments, one large sample web-based experiment, to understand associations, and one controlled lab environment, using eye tracking to understand user focus, we investigated how visual depth, use of visual aides, use of semantic categories, and lower-level stimuli features (i.e. contrast, colour and luminance) impact how successfully participants are able to search for, and detect, the target image. Moreover in the lab-based experiment, we captured pupillometry measurements to allow consideration of the influence of increasing cognitive load as a result of either an increasing number of items on the screen, or due to the inclusion of visual depth. Our findings showed that increasing the visible layers of depth, and inclusion of converging lines, did not impact target detection times, errors, or failure rates. Low-level features, including colour, luminance, and number of edges, did correlate with differences in target detection times, errors, and failure rates. Our results also revealed that semantic sorting algorithms significantly decreased target detection times. Increased semantic contrasts between a target and its neighbours correlated with an increase in detection errors. Finally, pupillometric data did not provide evidence of any correlation between the number of visible layers of depth and pupil size, however, using structural equation modelling, we demonstrated that cognitive load does influence detection failure rates when there is luminance contrasts between the target and its surrounding neighbours. Results suggest that WIMP interaction designers should consider stimulus-driven factors, which were shown to influence the efficiency with which a target icon can be found in a 3D WIMP interface.
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Primordial Quark Nuggets, remnants of the quark-hadron phase transition, may be hiding most of the baryon number in superdense chunks have been discussed for years always from the theoretical point of view. While they seemed originally fragile at intermediate cosmological temperatures, it became increasingly clear that they may survive due to a variety of effects affecting their evaporation (surface and volume) rates. A search of these objects have never been attempted to elucidate their existence. We discuss in this note how to search directly for cosmological fossil nuggets among the small asteroids approaching Earth. `Asteroids` with a high visible-to-infrared flux ratio, constant lightcurves and devoid of spectral features are signals of an actual possible nugget nature. A viable search of very definite primordial quark nugget features can be conducted as a spinoff of the ongoing/forthcoming NEAs observation programmes.
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It is believed that eta Carinae is actually a massive binary system, with the wind-wind interaction responsible for the strong X-ray emission. Although the overall shape of the X-ray light curve can be explained by the high eccentricity of the binary orbit, other features like the asymmetry near periastron passage and the short quasi-periodic oscillations seen at those epochs have not yet been accounted for. In this paper we explain these features assuming that the rotation axis of eta Carinae is not perpendicular to the orbital plane of the binary system. As a consequence, the companion star will face eta Carinae on the orbital plane at different latitudes for different orbital phases and, since both the mass-loss rate and the wind velocity are latitude dependent, they would produce the observed asymmetries in the X-ray flux. We were able to reproduce the main features of the X-ray light curve assuming that the rotation axis of eta Carinae forms an angle of 29 degrees +/- 4 degrees with the axis of the binary orbit. We also explained the short quasi-periodic oscillations by assuming nutation of the rotation axis, with an amplitude of about 5 degrees and a period of about 22 days. The nutation parameters, as well as the precession of the apsis, with a period of about 274 years, are consistent with what is expected from the torques induced by the companion star.
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Background and aim: Knowledge about the genetic factors responsible for noise-induced hearing loss (NIHL) is still limited. This study investigated whether genetic factors are associated or not to susceptibility to NIHL. Subjects and methods: The family history and genotypes were studied for candidate genes in 107 individuals with NIHL, 44 with other causes of hearing impairment and 104 controls. Mutations frequently found among deaf individuals were investigated (35delG, 167delT in GJB2, Delta(GJB6- D13S1830), Delta(GJB6- D13S1854) in GJB6 and A1555G in MT-RNR1 genes); allelic and genotypic frequencies were also determined at the SNP rs877098 in DFNB1, of deletions of GSTM1 and GSTT1 and sequence variants in both MTRNR1 and MTTS1 genes, as well as mitochondrial haplogroups. Results: When those with NIHL were compared with the control group, a significant increase was detected in the number of relatives affected by hearing impairment, of the genotype corresponding to the presence of both GSTM1 and GSTT1 enzymes and of cases with mitochondrial haplogroup L1. Conclusion: The findings suggest effects of familial history of hearing loss, of GSTT1 and GSTM1 enzymes and of mitochondrial haplogroup L1 on the risk of NIHL. This study also described novel sequence variants of MTRNR1 and MTTS1 genes.
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We analyzed ostriches from an equipped farm located in the Brazilian southeast region for the presence of Salmonella spp. This bacterium was investigated in 80 samples of ostrich droppings, 90 eggs, 30 samples of feed and 30 samples of droppings from rodents. Additionally, at slaughter-house this bacterium was investigated in droppings, caecal content, spleen, liver and carcasses from 90 slaughtered ostriches from the studied farm. Also, blood serum of those animals were harvested and submitted to serum plate agglutination using commercial Salmonella Pullorum antigen. No Salmonella spp. was detected in any eggs, caecal content, liver, spleen, carcass and droppings from ostriches and rodents. However, Salmonella Javiana and Salmonella enterica subsp. enterica 4, 12: i:- were isolated from some samples of feed. The serologic test was negative for all samples. Good sanitary farming management and the application of HACCP principles and GMP during the slaughtering process could explain the absence of Salmonella spp. in the tested samples.
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Various popular machine learning techniques, like support vector machines, are originally conceived for the solution of two-class (binary) classification problems. However, a large number of real problems present more than two classes. A common approach to generalize binary learning techniques to solve problems with more than two classes, also known as multiclass classification problems, consists of hierarchically decomposing the multiclass problem into multiple binary sub-problems, whose outputs are combined to define the predicted class. This strategy results in a tree of binary classifiers, where each internal node corresponds to a binary classifier distinguishing two groups of classes and the leaf nodes correspond to the problem classes. This paper investigates how measures of the separability between classes can be employed in the construction of binary-tree-based multiclass classifiers, adapting the decompositions performed to each particular multiclass problem. (C) 2010 Elsevier B.V. All rights reserved.
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A novel technique for selecting the poles of orthonormal basis functions (OBF) in Volterra models of any order is presented. It is well-known that the usual large number of parameters required to describe the Volterra kernels can be significantly reduced by representing each kernel using an appropriate basis of orthonormal functions. Such a representation results in the so-called OBF Volterra model, which has a Wiener structure consisting of a linear dynamic generated by the orthonormal basis followed by a nonlinear static mapping given by the Volterra polynomial series. Aiming at optimizing the poles that fully parameterize the orthonormal bases, the exact gradients of the outputs of the orthonormal filters with respect to their poles are computed analytically by using a back-propagation-through-time technique. The expressions relative to the Kautz basis and to generalized orthonormal bases of functions (GOBF) are addressed; the ones related to the Laguerre basis follow straightforwardly as a particular case. The main innovation here is that the dynamic nature of the OBF filters is fully considered in the gradient computations. These gradients provide exact search directions for optimizing the poles of a given orthonormal basis. Such search directions can, in turn, be used as part of an optimization procedure to locate the minimum of a cost-function that takes into account the error of estimation of the system output. The Levenberg-Marquardt algorithm is adopted here as the optimization procedure. Unlike previous related work, the proposed approach relies solely on input-output data measured from the system to be modeled, i.e., no information about the Volterra kernels is required. Examples are presented to illustrate the application of this approach to the modeling of dynamic systems, including a real magnetic levitation system with nonlinear oscillatory behavior.
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Several real problems involve the classification of data into categories or classes. Given a data set containing data whose classes are known, Machine Learning algorithms can be employed for the induction of a classifier able to predict the class of new data from the same domain, performing the desired discrimination. Some learning techniques are originally conceived for the solution of problems with only two classes, also named binary classification problems. However, many problems require the discrimination of examples into more than two categories or classes. This paper presents a survey on the main strategies for the generalization of binary classifiers to problems with more than two classes, known as multiclass classification problems. The focus is on strategies that decompose the original multiclass problem into multiple binary subtasks, whose outputs are combined to obtain the final prediction.
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Support vector machines (SVMs) were originally formulated for the solution of binary classification problems. In multiclass problems, a decomposition approach is often employed, in which the multiclass problem is divided into multiple binary subproblems, whose results are combined. Generally, the performance of SVM classifiers is affected by the selection of values for their parameters. This paper investigates the use of genetic algorithms (GAs) to tune the parameters of the binary SVMs in common multiclass decompositions. The developed GA may search for a set of parameter values common to all binary classifiers or for differentiated values for each binary classifier. (C) 2008 Elsevier B.V. All rights reserved.
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In this paper, we study binary differential equations a(x, y)dy (2) + 2b(x, y) dx dy + c(x, y)dx (2) = 0, where a, b, and c are real analytic functions. Following the geometric approach of Bruce and Tari in their work on multiplicity of implicit differential equations, we introduce a definition of the index for this class of equations that coincides with the classical Hopf`s definition for positive binary differential equations. Our results also apply to implicit differential equations F(x, y, p) = 0, where F is an analytic function, p = dy/dx, F (p) = 0, and F (pp) not equal aEuro parts per thousand 0 at the singular point. For these equations, we relate the index of the equation at the singular point with the index of the gradient of F and index of the 1-form omega = dy -aEuro parts per thousand pdx defined on the singular surface F = 0.
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The use of liposomes to encapsulate materials has received widespread attention for drug delivery, transfection, diagnostic reagent, and as immunoadjuvants. Phospholipid polymers form a new class of biomaterials with many potential applications in medicine and research. Of interest are polymeric phospholipids containing a diacetylene moiety along their acyl chain since these kinds of lipids can be polymerized by Ultra-Violet (UV) irradiation to form chains of covalently linked lipids in the bilayer. In particular the diacetylenic phosphatidylcholine 1,2-bis(10,12-tricosadiynoyl)- sn-glycero-3-phosphocholine (DC8,9PC) can form intermolecular cross-linking through the diacetylenic group to produce a conjugated polymer within the hydrocarbon region of the bilayer. As knowledge of liposome structures is certainly fundamental for system design improvement for new and better applications, this work focuses on the structural properties of polymerized DC8,9PC:1,2-dimyristoyl-sn-glycero-3-phusphocholine (DMPC) liposomes. Liposomes containing mixtures of DC8,9PC and DMPC, at different molar ratios, and exposed to different polymerization cycles, were studied through the analysis of the electron spin resonance (ESR) spectra of a spin label incorporated into the bilayer, and the calorimetric data obtained from differential scanning calorimetry (DSC) studies. Upon irradiation, if all lipids had been polymerized, no gel-fluid transition would be expected. However, even samples that went through 20 cycles of UV irradiation presented a DSC band, showing that around 80% of the DC8,9PC molecules were not polymerized. Both DSC and ESR indicated that the two different lipids scarcely mix at low temperatures, however few molecules of DMPC are present in DC8,9PC rich domains and vice versa. UV irradiation was found to affect the gel fluid transition of both DMPC and DC8,9PC rich regions, indicating the presence of polymeric units of DC8,9PC in both areas, A model explaining lipids rearrangement is proposed for this partially polymerized system.
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We present the results of searches for dipolar-type anisotropies in different energy ranges above 2.5 x 10(17) eV with the surface detector array of the Pierre Auger Observatory, reporting on both the phase and the amplitude measurements of the first harmonic modulation in the right-ascension distribution. Upper limits on the amplitudes are obtained, which provide the most stringent bounds at present, being below 2% at 99% C.L. for EeV energies. We also compare our results to those of previous experiments as well as with some theoretical expectations. (C) 2011 Elsevier B.V. All rights reserved.
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Brazil`s State of Sao Paulo Research Foundation
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We present parallel algorithms on the BSP/CGM model, with p processors, to count and generate all the maximal cliques of a circle graph with n vertices and m edges. To count the number of all the maximal cliques, without actually generating them, our algorithm requires O(log p) communication rounds with O(nm/p) local computation time. We also present an algorithm to generate the first maximal clique in O(log p) communication rounds with O(nm/p) local computation, and to generate each one of the subsequent maximal cliques this algorithm requires O(log p) communication rounds with O(m/p) local computation. The maximal cliques generation algorithm is based on generating all maximal paths in a directed acyclic graph, and we present an algorithm for this problem that uses O(log p) communication rounds with O(m/p) local computation for each maximal path. We also show that the presented algorithms can be extended to the CREW PRAM model.
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The design of translation invariant and locally defined binary image operators over large windows is made difficult by decreased statistical precision and increased training time. We present a complete framework for the application of stacked design, a recently proposed technique to create two-stage operators that circumvents that difficulty. We propose a novel algorithm, based on Information Theory, to find groups of pixels that should be used together to predict the Output Value. We employ this algorithm to automate the process of creating a set of first-level operators that are later combined in a global operator. We also propose a principled way to guide this combination, by using feature selection and model comparison. Experimental results Show that the proposed framework leads to better results than single stage design. (C) 2009 Elsevier B.V. All rights reserved.