957 resultados para binary hyperplane
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e argue that the extraordinary fact that all three known millisecond pulsars are very close to the galactic plane implies that there must be ~100 potentially observable millisecond pulsars within ~4 kpc from the Sun. Our other main conclusion is that the dipole magnetic fields or old neutron stars probably saturate around 5 x 108 gauss.
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A simple equation to predict the breakdown voltages for binary mixtures (Vmix) of electronegative gases (SF6, CCl2F2) and buffer gases (N2, N2O, CO2, air) under uniform electric field has been proposed. Values of Vmix evaluated using this equation for mixtures of SF6-N2, SF6-air, SF6-N2O, SF6-CO2 and CCl2F2-N2 over a wide range of pd show an excellent agreement with the experimentally measured data available in the literature.
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Combustion behaviour of ammonium perchlorate-potassium perchlorate pellets is studied using Crawford strand burners. At low concentrations of potassium perchlorate (up to 30 percent potassium perchlorate) the burning rate of ammonium perchlorate-potassium perchlorate condensed mixtures increases with potassium perchlorate content. Above 40 percent potassium perchlorate content, combustion sustenance becomes difficult. Decomposition products of ammonium perchlorate sensitize the melting and subsequent decomposition of potassium perchlorate. The results are explained in terms of the melt layer thickness, flame temperature and the resultant surface temperature, and heat wave penetration into the solid. The study suggests the importance of melt layer on the burning surface in the deflagration behaviour of ammonium perchlorate-potassium perchlorate condensed mixtures
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Quantization formats of four digital holographic codes (Lohmann,Lee, Burckhardt and Hsueh-Sawchuk) are evaluated. A quantitative assessment is made from errors in both the Fourier transform and image domains. In general, small errors in the Fourier amplitude or phase alone do not guarantee high image fidelity. From quantization considerations, the Lee hologram is shown to be the best choice for randomly phase coded objects. When phase coding is not feasible, the Lohmann hologram is preferable as it is easier to plot.
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The low-frequency (5–100 kHz) dielectric constant epsilon (Porson) has been measured in the temperature range 7 × 10−5 < t = (T − Tc)/Tc < 8 × 10−2. Near Tc an exponent ≈0.11 characterizes the power law behaviour of Image consistent with the theoretically predicted t−α singularity. However, over the full range of t an exponent ≈0.35 is obtained.
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Construction of Huffman binary codes for WLN symbols is described for the compression of a WLN file. Here, a parenthesized representation of the tree structure is used for computer encoding.
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This paper presents an effective classification method based on Support Vector Machines (SVM) in the context of activity recognition. Local features that capture both spatial and temporal information in activity videos have made significant progress recently. Efficient and effective features, feature representation and classification plays a crucial role in activity recognition. For classification, SVMs are popularly used because of their simplicity and efficiency; however the common multi-class SVM approaches applied suffer from limitations including having easily confused classes and been computationally inefficient. We propose using a binary tree SVM to address the shortcomings of multi-class SVMs in activity recognition. We proposed constructing a binary tree using Gaussian Mixture Models (GMM), where activities are repeatedly allocated to subnodes until every new created node contains only one activity. Then, for each internal node a separate SVM is learned to classify activities, which significantly reduces the training time and increases the speed of testing compared to popular the `one-against-the-rest' multi-class SVM classifier. Experiments carried out on the challenging and complex Hollywood dataset demonstrates comparable performance over the baseline bag-of-features method.
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Analyzing statistical dependencies is a fundamental problem in all empirical science. Dependencies help us understand causes and effects, create new scientific theories, and invent cures to problems. Nowadays, large amounts of data is available, but efficient computational tools for analyzing the data are missing. In this research, we develop efficient algorithms for a commonly occurring search problem - searching for the statistically most significant dependency rules in binary data. We consider dependency rules of the form X->A or X->not A, where X is a set of positive-valued attributes and A is a single attribute. Such rules describe which factors either increase or decrease the probability of the consequent A. A classical example are genetic and environmental factors, which can either cause or prevent a disease. The emphasis in this research is that the discovered dependencies should be genuine - i.e. they should also hold in future data. This is an important distinction from the traditional association rules, which - in spite of their name and a similar appearance to dependency rules - do not necessarily represent statistical dependencies at all or represent only spurious connections, which occur by chance. Therefore, the principal objective is to search for the rules with statistical significance measures. Another important objective is to search for only non-redundant rules, which express the real causes of dependence, without any occasional extra factors. The extra factors do not add any new information on the dependence, but can only blur it and make it less accurate in future data. The problem is computationally very demanding, because the number of all possible rules increases exponentially with the number of attributes. In addition, neither the statistical dependency nor the statistical significance are monotonic properties, which means that the traditional pruning techniques do not work. As a solution, we first derive the mathematical basis for pruning the search space with any well-behaving statistical significance measures. The mathematical theory is complemented by a new algorithmic invention, which enables an efficient search without any heuristic restrictions. The resulting algorithm can be used to search for both positive and negative dependencies with any commonly used statistical measures, like Fisher's exact test, the chi-squared measure, mutual information, and z scores. According to our experiments, the algorithm is well-scalable, especially with Fisher's exact test. It can easily handle even the densest data sets with 10000-20000 attributes. Still, the results are globally optimal, which is a remarkable improvement over the existing solutions. In practice, this means that the user does not have to worry whether the dependencies hold in future data or if the data still contains better, but undiscovered dependencies.
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The possibility of observing gravitational spin precession due to spin-orbit coupling in a binary pulsar system is considered. An analysis is presented which can aid in delineating the relevant physical effects from pulse-structure data. In this analysis, it is assumed that the pulsar radiation emanates from a cone whose axis is tilted with respect to the axis of rotation. It is found that the time-averaged pulse width and polarization sweep vary periodically with time and that this variation has a periodicity of the order of the spin-precession frequency averaged over a complete revolution. It is concluded that for an orbital period of about 180 years, it suffices to measure polarization data with an accuracy of a few parts in 100 over a period of six months to a year in order to uncover the effects of spin precession. The consistency of the analysis is checked, and the calculations are applied to a recently discovered binary pulsar.
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The signal-to-noise (S/N) ratio in the reconstructed image from a binary hologram has been quantitatively related to the amplitude and phase quantization levels. The S/N ratio increases monotonically with increasing number of quantization levels. This observation is further supported by experimental results.
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The system CS2 + CH3NO2 shows β=0.315±0.004 over 10-6<ε=|T-Tc| / Tc<2�10-1 with no indication of a classical value ½ even far away from Tc. The diameter shows a curvature and is of the form �c+b ε+fε7 / 8exp(-gεh).
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Electrical resistance measurements are reported on the binary liquid mixtures CS2 + CH3CN and CS2 + CH3NO2 with special reference to the critical region. Impurity conduction seems to be the dominant mechanism for charge transport. For the liquid mixture filled at the critical composition, the resistance of the system aboveT c follows the relationR=R c−A(T−T c) b withb=0·6±0·1. BelowT c the conductivities of the two phases obey a relation σ2−σ1=B(T c−T)β with β=0·34±0·02, the exponent of the transport coefficient being the same as the exponent of the order parameter, an equilibrium property.
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Two different designs for negative binary adder-subtracter are compared. Ono design uses the method of a hybrid-carry—borrow, while the other 11303 the method of polarization and addition.
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For five binary liquid systems CS2+CH3CN, CS2+CH3NO2, CS2+(CH3CO)2O, C6H12+(CH3CO)2O, n-C7H16+(CH3CO)2O, the electrical resistance has been measured near the critical solution temperatures. The behaviour is universal. Below Tc, the conductivities of the two phases follow σ1−σ2 β, where = T−Tc Tc with β≈0.35. In the one phase region with b≈0.35±0.1 and is positive in some cases and negative in others.