985 resultados para binary data


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Multi-access techniques are widely used in computer networking and distributed multiprocessor systems. On-the-fly arbitration schemes permit one of the many contenders to access the medium without collisions. Serial arbitration is cost effective but is slow and hence unsuitable for high-speed multiprocessor environments supporting very high data transfer rates. A fully parallel arbitration scheme takes less time but is not practically realisable for large numbers of contenders. In this paper, a generalised parallel-serial scheme is proposed which significantly reduces the arbitration time and is practically realisable.

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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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Matrix decompositions, where a given matrix is represented as a product of two other matrices, are regularly used in data mining. Most matrix decompositions have their roots in linear algebra, but the needs of data mining are not always those of linear algebra. In data mining one needs to have results that are interpretable -- and what is considered interpretable in data mining can be very different to what is considered interpretable in linear algebra. --- The purpose of this thesis is to study matrix decompositions that directly address the issue of interpretability. An example is a decomposition of binary matrices where the factor matrices are assumed to be binary and the matrix multiplication is Boolean. The restriction to binary factor matrices increases interpretability -- factor matrices are of the same type as the original matrix -- and allows the use of Boolean matrix multiplication, which is often more intuitive than normal matrix multiplication with binary matrices. Also several other decomposition methods are described, and the computational complexity of computing them is studied together with the hardness of approximating the related optimization problems. Based on these studies, algorithms for constructing the decompositions are proposed. Constructing the decompositions turns out to be computationally hard, and the proposed algorithms are mostly based on various heuristics. Nevertheless, the algorithms are shown to be capable of finding good results in empirical experiments conducted with both synthetic and real-world data.

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This paper presents a cautious argument for re-thinking both the nature and the centrality of the one-to-one teacher/student relationship in contemporary pedagogy. A case is made that learning in and for our times requires us to broaden our understanding of pedagogical relations beyond the singularity of the teacher/student binary and to promote the connected teacher as better placed to lead learning for these times. The argument proceeds in three parts: first, a characterization of our times as defined increasingly by the digital knowledge explosion of Big Data; second, a re-thinking of the nature of pedagogical relationships in the context of Big Data; and third, an account of the ways in which leaders can support their teachers to become more effective in leading learning by being more closely connected to their professional colleagues.

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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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Self-tracking, the process of recording one's own behaviours, thoughts and feelings, is a popular approach to enhance one's self-knowledge. While dedicated self-tracking apps and devices support data collection, previous research highlights that the integration of data constitutes a barrier for users. In this study we investigated how members of the Quantified Self movement---early adopters of self-tracking tools---overcome these barriers. We conducted a qualitative analysis of 51 videos of Quantified Self presentations to explore intentions for collecting data, methods for integrating and representing data, and how intentions and methods shaped reflection. The findings highlight two different intentions---striving for self-improvement and curiosity in personal data---which shaped how these users integrated data, i.e. the effort required. Furthermore, we identified three methods for representing data---binary, structured and abstract---which influenced reflection. Binary representations supported reflection-in-action, whereas structured and abstract representations supported iterative processes of data collection, integration and reflection. For people tracking out of curiosity, this iterative engagement with personal data often became an end in itself, rather than a means to achieve a goal. We discuss how these findings contribute to our current understanding of self-tracking amongst Quantified Self members and beyond, and we conclude with directions for future work to support self-trackers with their aspirations.

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Template matching is concerned with measuring the similarity between patterns of two objects. This paper proposes a memory-based reasoning approach for pattern recognition of binary images with a large template set. It seems that memory-based reasoning intrinsically requires a large database. Moreover, some binary image recognition problems inherently need large template sets, such as the recognition of Chinese characters which needs thousands of templates. The proposed algorithm is based on the Connection Machine, which is the most massively parallel machine to date, using a multiresolution method to search for the matching template. The approach uses the pyramid data structure for the multiresolution representation of templates and the input image pattern. For a given binary image it scans the template pyramid searching the match. A binary image of N × N pixels can be matched in O(log N) time complexity by our algorithm and is independent of the number of templates. Implementation of the proposed scheme is described in detail.

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The phase equilibrium studies of organic system, involving resorcinol (R) and p-dimethylaminobenzaldehyde (DMAB), reveal the formation of a 1:1 molecular complex with two eutectics. The heat of mixing, entropy of fusion, roughness parameter, interfacial energy, and the excess thermodynamic functions were calculated based on enthalpy of fusion data determined via differential scanning calorimetric (DSC) method. X-ray powder diffraction studies confirm that the eutectics are not simple mechanical mixture of the components under investigation. The spectroscopic investigations (IR and NMR) suggest the occurrence of hydrogen bonding between the components forming the molecular complex. The dielectric measurements, carried out on hot-pressed addition compound (molecular complex), show higher dielectric constant at 320 K than that of individual components. The microstructural investigations of eutectic and addition compound indicate dendritic and faceted morphological features. (C) 2000 Elsevier Science B.V. All rights reserved.

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The electrical capacitance and resistance of the binary liquid mixture cyclohexane + acetonitrile are measured in the one phase and two phase regions at spot frequencies between 5 kHz and 100 kHz. This sample has a very low gravity affected (∼0.6 mK) region. In one phase region the capacitance data show a sharp, ∼0.7% increase above background within 0.5 degrees of Tc whereas the resistance has a smooth increase of ∼1.5% above background in a (T−Tc) range of 4 degrees. Two phase values of capacitance and resistance from the coexisting phases are used to determine the critical parameters Tc (critical temperature), Rc (resistance at Tc) and Cc (capacitance at Tc). A precise knowledge of these parameters reduces the uncertainty on the critical exponent 0 for C and R. The one phase capacitance data fit to an (1 - α) exponent in a limited temperature range of 0.2 degrees. Resistance data strongly support an (1 - α) exponent over the entire 5 degree range.

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Reorganizing a dataset so that its hidden structure can be observed is useful in any data analysis task. For example, detecting a regularity in a dataset helps us to interpret the data, compress the data, and explain the processes behind the data. We study datasets that come in the form of binary matrices (tables with 0s and 1s). Our goal is to develop automatic methods that bring out certain patterns by permuting the rows and columns. We concentrate on the following patterns in binary matrices: consecutive-ones (C1P), simultaneous consecutive-ones (SC1P), nestedness, k-nestedness, and bandedness. These patterns reflect specific types of interplay and variation between the rows and columns, such as continuity and hierarchies. Furthermore, their combinatorial properties are interlinked, which helps us to develop the theory of binary matrices and efficient algorithms. Indeed, we can detect all these patterns in a binary matrix efficiently, that is, in polynomial time in the size of the matrix. Since real-world datasets often contain noise and errors, we rarely witness perfect patterns. Therefore we also need to assess how far an input matrix is from a pattern: we count the number of flips (from 0s to 1s or vice versa) needed to bring out the perfect pattern in the matrix. Unfortunately, for most patterns it is an NP-complete problem to find the minimum distance to a matrix that has the perfect pattern, which means that the existence of a polynomial-time algorithm is unlikely. To find patterns in datasets with noise, we need methods that are noise-tolerant and work in practical time with large datasets. The theory of binary matrices gives rise to robust heuristics that have good performance with synthetic data and discover easily interpretable structures in real-world datasets: dialectical variation in the spoken Finnish language, division of European locations by the hierarchies found in mammal occurrences, and co-occuring groups in network data. In addition to determining the distance from a dataset to a pattern, we need to determine whether the pattern is significant or a mere occurrence of a random chance. To this end, we use significance testing: we deem a dataset significant if it appears exceptional when compared to datasets generated from a certain null hypothesis. After detecting a significant pattern in a dataset, it is up to domain experts to interpret the results in the terms of the application.

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In the present work the integral diffusion coefficients are estimated by using the diaphragm cell technique. The diffusion coefficients are measured at various compositions for two sets binary systems: one of cyclohexane and n-paraffinic alcohols and the other of methylcyclohexane and n-paraffinic alcohols. The alcohols used are seven members of homologous series of n-paraffinic alcohols from ethanol to octanol. The maximum possible error in the experimental diffusion coefficient could be 8% for both the cyclohexane-n-alkyl alcohol system and methylcyclohexane-n-alkyl alcohol system. A correlation for each of the two sets of binary systems is given. The maximum deviation in the correlations was less than 6.5 and 3.5% for cyclohexane-n-alkyl alcohols and methylcyclohexane-n-alkyl alcohols, respectively.

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A molecular theory of dielectric relaxation in a dense binary dipolar liquid is presented. The theory takes into account the effects of intra- and interspecies intermolecular interactions. It is shown that the relaxation is, in general, nonexponential. In certain limits, we recover the biexponential form traditionally used to analyze the experimental data of dielectric relaxation in a binary mixture. However, the relaxation times are widely different from the prediction of the noninteracting rotational diffusion model of Debye for a binary system. Detailed numerical evaluation of the frequency-dependent dielectric function epsilon-(omega) is carried out by using the known analytic solution of the mean spherical approximation (MSA) model for the two-particle direct correlation function for a polar mixture. A microscopic expression for both wave vector (k) and frequency (omega) dependent dielectric function, epsilon-(k,omega), of a binary mixture is also presented. The theoretical predictions on epsilon-(omega) (= epsilon-(k = 0, omega)) have been compared with the available experimental results. In particular, the present theory offers a molecular explanation of the phenomenon of fusing of the two relaxation channels of the neat liquids, observed by Schallamach many years ago.

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The mutual diffusion coefficients for binary liquid systems of benzene-n-alkyl alcohol at various compositions have been determined by the diaphragm cell method at 28-degrees-C. The alcohols used were the members of n-paraffinic alcohols ranging from C1 to C8. The maximum possible experimental error is 14%. The data were fitted with a generalized correlation, giving the deviation from the experimental data to within 2.75%, on average.

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The electrical resistance of the binary liquid system cyclohexane + acetic anhydride is measured, in the critical region, both in the pure mixture and when the mixture is doped with small amounts (≈ 100 ppm) of H2O/D2O impurities.T c was approached to aboutt=3×10−6 wheret=(T −T c )/T c . The critical exponentb ≈ 0.35 in the fit of the resistance data to the equationdR/dT ∼t −b does not seem to be affected appreciably by the impurities. There is a sign reversal ofdR/dt in the non-critical region. Binary liquid systems seem to violate the universality of the critical resistivity.

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The pressure dependence of critical parameters xc, Tc, and β have been analysed in four systems namely cyclohexane + acetic anhydride, n-heptane + acetic anhydride, methanol + n-heptane, and carbon disulphide + acetonitrile. The separation temperature was found to increase linearly with pressure the value of dTc/dP being 28 mK, 11 mK, 22 mK, and 25 mK respectively. These are in fair agreement with earlier measurements available for two systems. For the methanol + n-heptane system dTc/dP is apparently not consistent with the value predicted from the specific heat and thermal expansion data.Die Druckabhängigkeit der kritischen Parameter xc, Tc und β ist in den vier Systemen Cyclohexan + Essigsäureanhydrid, n-Heptan + Essigsäureanhydrid, Methanol + n-Heptan und Schwefelkohlenstoff + Acetonitril analysiert worden. Es wurde gefunden, daß die kritische Temperatur linear mit dem Druck ansteigt. Die Werte für dTc/dP betragen 28 mK, 11 mK, 22 mK und 25 mK. Sie sind in guter überein-stimmung mit früheren Messungen an zweien dieser Systeme. Für Methanol + n-Heptan stimmt der Wert für dT/dP offensichtlich nicht mit Werten, die mit Hilfe von Daten für die spezifische Wärme und die thermische Ausdehnung vorhergesagt wurden, überein.