175 resultados para Discrete valued features


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Epoxy systems containing HTBN rubber material and reinforced with E-glass fibres, exposed to a fixed time duration in three separate media were subjected to compressive mode of deformation. The yield stress and fractographic features noted on the compression failed samples are reported in this work. The experiment reveals that the seawater exposed sample exhibits a drop in strength compared to dry (unexposed) sample. This kind of drop is maintained if the media is changed from seawater to distilled water. When HCl is included in seawater. the experiment shows a small rise in strength value. These changes have been attributed to various factors like medium ingress into samples assisting interface failure, the larger-sized Cl- influencing the extent of diffusion of medium into system and finally their participation in the deformation phenomena. The fractographic features reveal interface separations that show either scattered debris or a cleaner surface or display a whitish-coated matrix region depending on whether the tests are done on unexposed samples or on ones following the immersion in the media.

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An entirely different approach for localisation of winding deformation based on terminal measurements is presented. Within the context of this study, winding deformation means, a discrete and specific change externally imposed at a particular position on the winding. The proposed method is based on pre-computing and plotting the complex network-function loci e.g. driving-point impedance (DPI)] at a selected frequency, for a meaningful range of values for each element (increasing and decreasing) of the ladder network which represents the winding. This loci diagram is called the nomogram. After introducing a discrete change, amplitude and phase of DPI are measured. By plotting this single measurement on the nomogram, it is possible to estimate the location and identify the extent of change. In contrast to the existing approach, the proposed method is fast, non-iterative and yields reasonably good localisation. Experimental results for actual transformer windings (interleaved and continuous disc) are presented.

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Syntactic foam made by mechanical mixing of glass hollow spheres in epoxy resin matrix is characterized for compressive properties in the present study. Volume fraction of hollow spheres in the syntactic foam under investigation is kept at 67.8%. Effect of specimen aspect ratio on failure behavior and stress-strain curve of the material is highlighted. Considerable differences are noted in the macroscopic fracture features of the specimen and the stress-strain curve with the variation in specimen aspect ratio, although compressive yield strength values were within a narrow range. Post compression test scanning electron microscopic observations coupled with the macroscopic observations taken during the test helped in explaining the deviation in specimen behavior and in gathering support for the proposed arguments.

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This paper describes the near surface characteristics and vertical variations based on the observations made at 17.5degreesN and 89degreesE from ORV Sagar Kanya in the north Bay of Bengal during the Bay of Bengal Monsoon Experiment (BOBMEX) carried out in July-August 1999. BOBMEX captured both the active and weak phases of convection. SST remained above the convection threshold throughout the BOBMEX. While the response of the SST to atmospheric forcing was clearly observed, the response of the atmosphere to SST changes was not clear. SST decreased during periods of large scale precipitation, and increased during a weak phase of convection. It is shown that the latent heat flux at comparable wind speeds was about 25-50% lower over the Bay during BOBMEX compared to that over the Indian Ocean during other seasons and tropical west Pacific. On the other hand, the largest variations in the surface daily net heat flux are observed over the Bay during BOBMEX. SST predicted using observed surface fluxes showed that 1-D heat balance model works sometime but not always, and horizontal advection is important. The high resolution Vaisala radiosondes launched during BOBMEX could clearly bring out the changes in the vertical structure of the atmosphere between active and weak phases of convection. Convective Available Potential Energy of the surface air decreased,by 2-3 kJ kg(-1) following convection, and recovered in a time period of one or two days. The mid tropospheric relative humidity and water vapor content, and wind direction show the major changes between the active and weak phases of convection.

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Effective feature extraction for robust speech recognition is a widely addressed topic and currently there is much effort to invoke non-stationary signal models instead of quasi-stationary signal models leading to standard features such as LPC or MFCC. Joint amplitude modulation and frequency modulation (AM-FM) is a classical non-parametric approach to non-stationary signal modeling and recently new feature sets for automatic speech recognition (ASR) have been derived based on a multi-band AM-FM representation of the signal. We consider several of these representations and compare their performances for robust speech recognition in noise, using the AURORA-2 database. We show that FEPSTRUM representation proposed is more effective than others. We also propose an improvement to FEPSTRUM based on the Teager energy operator (TEO) and show that it can selectively outperform even FEPSTRUM

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Bid optimization is now becoming quite popular in sponsored search auctions on the Web. Given a keyword and the maximum willingness to pay of each advertiser interested in the keyword, the bid optimizer generates a profile of bids for the advertisers with the objective of maximizing customer retention without compromising the revenue of the search engine. In this paper, we present a bid optimization algorithm that is based on a Nash bargaining model where the first player is the search engine and the second player is a virtual agent representing all the bidders. We make the realistic assumption that each bidder specifies a maximum willingness to pay values and a discrete, finite set of bid values. We show that the Nash bargaining solution for this problem always lies on a certain edge of the convex hull such that one end point of the edge is the vector of maximum willingness to pay of all the bidders. We show that the other endpoint of this edge can be computed as a solution of a linear programming problem. We also show how the solution can be transformed to a bid profile of the advertisers.

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Feature selection is an important first step in regional hydrologic studies (RHYS). Over the past few decades, advances in data collection facilities have resulted in development of data archives on a variety of hydro-meteorological variables that may be used as features in RHYS. Currently there are no established procedures for selecting features from such archives. Therefore, hydrologists often use subjective methods to arrive at a set of features. This may lead to misleading results. To alleviate this problem, a probabilistic clustering method for regionalization is presented to determine appropriate features from the available dataset. The effectiveness of the method is demonstrated by application to regionalization of watersheds in conterminous United States for low flow frequency analysis. Plausible homogeneous regions that are formed by using the proposed clustering method are compared with those from conventional methods of regionalization using L-moment based homogeneity tests. Results show that the proposed methodology is promising for RHYS.

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We consider a fluid queue in discrete time with random service rate. Such a queue has been used in several recent studies on wireless networks where the packets can be arbitrarily fragmented. We provide conditions on finiteness of moments of stationary delay, its Laplace-Stieltjes transform and various approximations under heavy traffic. Results are extended to the case where the wireless link can transmit in only a few slots during a frame.

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In general the objective of accurately encoding the input data and the objective of extracting good features to facilitate classification are not consistent with each other. As a result, good encoding methods may not be effective mechanisms for classification. In this paper, an earlier proposed unsupervised feature extraction mechanism for pattern classification has been extended to obtain an invertible map. The method of bimodal projection-based features was inspired by the general class of methods called projection pursuit. The principle of projection pursuit concentrates on projections that discriminate between clusters and not faithful representations. The basic feature map obtained by the method of bimodal projections has been extended to overcome this. The extended feature map is an embedding of the input space in the feature space. As a result, the inverse map exists and hence the representation of the input space in the feature space is exact. This map can be naturally expressed as a feedforward neural network.