99 resultados para Emotions in literature


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Due to the inherent feedback in a decision feedback equalizer (DFE) the minimum mean square error (MMSE) or Wiener solution is not known exactly. The main difficulty in such analysis is due to the propagation of the decision errors, which occur because of the feedback. Thus in literature, these errors are neglected while designing and/or analyzing the DFEs. Then a closed form expression is obtained for Wiener solution and we refer this as ideal DFE (IDFE). DFE has also been designed using an iterative and computationally efficient alternative called least mean square (LMS) algorithm. However, again due to the feedback involved, the analysis of an LMS-DFE is not known so far. In this paper we theoretically analyze a DFE taking into account the decision errors. We study its performance at steady state. We then study an LMS-DFE and show the proximity of LMS-DFE attractors to that of the optimal DFE Wiener filter (obtained after considering the decision errors) at high signal to noise ratios (SNR). Further, via simulations we demonstrate that, even at moderate SNRs, an LMS-DFE is close to the MSE optimal DFE. Finally, we compare the LMS DFE attractors with IDFE via simulations. We show that an LMS equalizer outperforms the IDFE. In fact, the performance improvement is very significant even at high SNRs (up to 33%), where an IDFE is believed to be closer to the optimal one. Towards the end, we briefly discuss the tracking properties of the LMS-DFE.

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A rigorous lower bound solution, with the usage of the finite elements limit analysis, has been obtained for finding the ultimate bearing capacity of two interfering strip footings placed on a sandy medium. Smooth as well as rough footingsoil interfaces are considered in the analysis. The failure load for an interfering footing becomes always greater than that for a single isolated footing. The effect of the interference on the failure load (i) for rough footings becomes greater than that for smooth footings, (ii) increases with an increase in phi, and (iii) becomes almost negligible beyond S/B>3. Compared with various theoretical and experimental results reported in literature, the present analysis generally provides the lowest magnitude of the collapse load. Copyright (c) 2011 John Wiley & Sons, Ltd.

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Maintaining population diversity throughout generations of Genetic Algorithms (GAs) is key to avoid premature convergence. Redundant solutions is one cause for the decreasing population diversity. To prevent the negative effect of redundant solutions, we propose a framework that is based on the multi-parents crossover (MPX) operator embedded in GAs. Because MPX generates diversified chromosomes with good solution quality, when a pair of redundant solutions is found, we would generate a new offspring by using the MPX to replace the redundant chromosome. Three schemes of MPX will be examined and will be compared against some algorithms in literature when we solve the permutation flowshop scheduling problems, which is a strong NP-Hard sequencing problem. The results indicate that our approach significantly improves the solution quality. This study is useful for researchers who are trying to avoid premature convergence of evolutionary algorithms by solving the sequencing problems.

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Confined supersonic mixing layer is explored through model-free simulations. Both two- and three-dimensional spatio-temporal simulations were carried out employing higher order finite difference scheme as well as finite volume scheme based on open source software (OpenFOAM) to understand the effect of three-dimensionality on the development of mixing layer. It is observed that although the instantaneous structures exhibit three-dimensional features, the average pressure and velocities are predominantly two-dimensional. The computed wall pressures match well with experimental results fairly well, although three-dimensional simulation underpredicts the wall pressure in the downstream direction. The self-similarity of the velocity profiles is obtained within the duct length for all the simulations. Although the mixing layer thicknesses differ among different simulations, their growth rate is nearly the same. Significant differences are observed for species and temperature distribution between two- and three-dimensional calculations, and two-dimensional calculations do not match the experimental observation of smooth variations in species mass fraction profiles as reported in literature. Reynolds stress distribution for three-dimensional calculations show profiles with less peak values compared to two-dimensional calculations; while normal stress anisotropy is higher for three-dimensional case.

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We consider bounds for the capacity region of the Gaussian X channel (XC), a system consisting of two transmit-receive pairs, where each transmitter communicates with both the receivers. We first classify the XC into two classes, the strong XC and the mixed XC. In the strong XC, either the direct channels are stronger than the cross channels or vice-versa, whereas in the mixed XC, one of the direct channels is stronger than the corresponding cross channel and vice-versa. After this classification, we give outer bounds on the capacity region for each of the two classes. This is based on the idea that when one of the messages is eliminated from the XC, the rate region of the remaining three messages are enlarged. We make use of the Z channel, a system obtained by eliminating one message and its corresponding channel from the X channel, to bound the rate region of the remaining messages. The outer bound to the rate region of the remaining messages defines a subspace in R-+(4) and forms an outer bound to the capacity region of the XC. Thus, the outer bound to the capacity region of the XC is obtained as the intersection of the outer bounds to the four combinations of the rate triplets of the XC. Using these outer bounds on the capacity region of the XC, we derive new sum-rate outer bounds for both strong and mixed Gaussian XCs and compare them with those existing in literature. We show that the sum-rate outer bound for strong XC gives the sum-rate capacity in three out of the four sub-regions of the strong Gaussian XC capacity region. In case of mixed Gaussian XC, we recover the recent results in 11] which showed that the sum-rate capacity is achieved in two out of the three sub-regions of the mixed XC capacity region and give a simple alternate proof of the same.

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In this paper, we analyze the combined effects of size quantization and device temperature variations (T = 50K to 400 K) on the intrinsic carrier concentration (n(i)), electron concentration (n) and thereby on the threshold voltage (V-th) for thin silicon film (t(si) = 1 nm to 10 nm) based fully-depleted Double-Gate Silicon-on-Insulator MOSFETs. The threshold voltage (V-th) is defined as the gate voltage (V-g) at which the potential at the center of the channel (Phi(c)) begins to saturate (Phi(c) = Phi(c(sat))). It is shown that in the strong quantum confinement regime (t(si) <= 3nm), the effects of size quantization far over-ride the effects of temperature variations on the total change in band-gap (Delta E-g(eff)), intrinsic carrier concentration (n(i)), electron concentration (n), Phi(c(sat)) and the threshold voltage (V-th). On the other hand, for t(si) >= 4 nm, it is shown that size quantization effects recede with increasing t(si), while the effects of temperature variations become increasingly significant. Through detailed analysis, a physical model for the threshold voltage is presented both for the undoped and doped cases valid over a wide-range of device temperatures, silicon film thicknesses and substrate doping densities. Both in the undoped and doped cases, it is shown that the threshold voltage strongly depends on the channel charge density and that it is independent of incomplete ionization effects, at lower device temperatures. The results are compared with the published work available in literature, and it is shown that the present approach incorporates quantization and temperature effects over the entire temperature range. We also present an analytical model for V-th as a function of device temperature (T). (C) 2013 AIP Publishing LLC.

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Construction of high rate Space Time Block Codes (STBCs) with low decoding complexity has been studied widely using techniques such as sphere decoding and non Maximum-Likelihood (ML) decoders such as the QR decomposition decoder with M paths (QRDM decoder). Recently Ren et al., presented a new class of STBCs known as the block orthogonal STBCs (BOSTBCs), which could be exploited by the QRDM decoders to achieve significant decoding complexity reduction without performance loss. The block orthogonal property of the codes constructed was however only shown via simulations. In this paper, we give analytical proofs for the block orthogonal structure of various existing codes in literature including the codes constructed in the paper by Ren et al. We show that codes formed as the sum of Clifford Unitary Weight Designs (CUWDs) or Coordinate Interleaved Orthogonal Designs (CIODs) exhibit block orthogonal structure. We also provide new construction of block orthogonal codes from Cyclic Division Algebras (CDAs) and Crossed-Product Algebras (CPAs). In addition, we show how the block orthogonal property of the STBCs can be exploited to reduce the decoding complexity of a sphere decoder using a depth first search approach. Simulation results of the decoding complexity show a 30% reduction in the number of floating point operations (FLOPS) of BOSTBCs as compared to STBCs without the block orthogonal structure.

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Proportional Navigation (PN) and its variants are widely used guidance philosophies. However, in the presence of target maneuver, PN guidance law is effective only for a restrictive set of initial geometries. To account for target maneuvers, the concept of Augmented Proportional Navigation (APN) guidance law was introduced and analyzed in a linearized interceptor-target engagement framework presented in literature. However, there is no work in the literature, that addresses the capturability performance of the APN guidance law in a nonlinear engagement framework. This paper presents such an analysis and obtains the conditions for capturability. It also shows that a shorter time of interception is obtained when APN is formulated in the nonlinear framework as proposed in this paper. Simulation results are given to support the theoretical findings.

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The conceptual model for deep geological disposal of high level nuclear waste (HLW) is based on multiple barrier system consisting of natural and engineered barriers. Buffer/backfill material is regarded as the most important engineered barrier in HLW repositories. Due to large swelling ability, cation adsorption capacity, and low permeability bentonite is considered as suitable buffer material in HLW repositories. Japan has identified Kunigel VI bentonite, South Korea - Kyungju bentonite, China - GMZ bentonite, Belgium - FoCa clay, Sweden - MX-80 bentonite, Spain - FEBEX bentonite and Canada - Avonseal bentonite as candidate bentonite buffer for deep geological repository program. An earlier study on Indian bentonites by one of the authors suggested that bentonite from Barmer district of Rajasthan (termed Barmer 1 bentonite), India is suited for use as buffer material in deep geological repositories. However, the hydro-mechanical properties of the Barmer 1 bentonite are unavailable. This paper characterizes Barmer 1 bentonite for hydro-mechanical properties, such as, swell pressure, saturated permeability, soil water characteristic curve (SWCC) and unconfined compression strength at different dry densities. The properties of Barmer 1 bentonite were compared with bentonite buffers reported in literature and equations for designing swell pressure and saturated permeability coefficient of bentonite buffers were arrived at. (C) 2013 Elsevier B.V. All rights reserved.

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In this paper, we address a scheduling problem for minimizing total weighted tardiness. The background for the paper is derived from the automobile gear manufacturing process. We consider the bottleneck operation of heat treatment stage of gear manufacturing. Real-life scenarios like unequal release times, incompatible job families, nonidentical job sizes, heterogeneous batch processors, and allowance for job splitting have been considered. We have developed a mathematical model which takes into account dynamic starting conditions. The problem considered in this study is NP-hard in nature, and hence heuristic algorithms have been proposed to address it. For real-life large-size problems, the performance of the proposed heuristic algorithms is evaluated using the method of estimated optimal solution available in literature. Extensive computational analyses reveal that the proposed heuristic algorithms are capable of consistently obtaining near-optimal statistically estimated solutions in very reasonable computational time.

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Maximum entropy approach to classification is very well studied in applied statistics and machine learning and almost all the methods that exists in literature are discriminative in nature. In this paper, we introduce a maximum entropy classification method with feature selection for large dimensional data such as text datasets that is generative in nature. To tackle the curse of dimensionality of large data sets, we employ conditional independence assumption (Naive Bayes) and we perform feature selection simultaneously, by enforcing a `maximum discrimination' between estimated class conditional densities. For two class problems, in the proposed method, we use Jeffreys (J) divergence to discriminate the class conditional densities. To extend our method to the multi-class case, we propose a completely new approach by considering a multi-distribution divergence: we replace Jeffreys divergence by Jensen-Shannon (JS) divergence to discriminate conditional densities of multiple classes. In order to reduce computational complexity, we employ a modified Jensen-Shannon divergence (JS(GM)), based on AM-GM inequality. We show that the resulting divergence is a natural generalization of Jeffreys divergence to a multiple distributions case. As far as the theoretical justifications are concerned we show that when one intends to select the best features in a generative maximum entropy approach, maximum discrimination using J-divergence emerges naturally in binary classification. Performance and comparative study of the proposed algorithms have been demonstrated on large dimensional text and gene expression datasets that show our methods scale up very well with large dimensional datasets.

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The flowfields associated with truncated annular plug nozzles of varying lengths are studied both experimentally and using computational tools. The nozzles are designed to observe wake structure transition for the range of pressure ratios considered. A classification of the open wake regime is proposed for comparing and analyzing the plug flowfields. The three-dimensional relief experienced by the annular plug flow leads to greater wave interactions on the plug surface as compared with linear plug flow, resulting in a delayed transition of the base wake. The Reynolds averaged Navier-Stokes based solvers employed in the studies could predict the plug surface flow accurately, whereas they exhibited limitations with regard to plug base flow predictions. Based on the experimental data generated, an empirical model for predicting closed wake base pressure is proposed and compared with other models available in literature.

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H. 264/advanced video coding surveillance video encoders use the Skip mode specified by the standard to reduce bandwidth. They also use multiple frames as reference for motion-compensated prediction. In this paper, we propose two techniques to reduce the bandwidth and computational cost of static camera surveillance video encoders without affecting detection and recognition performance. A spatial sampler is proposed to sample pixels that are segmented using a Gaussian mixture model. Modified weight updates are derived for the parameters of the mixture model to reduce floating point computations. A storage pattern of the parameters in memory is also modified to improve cache performance. Skip selection is performed using the segmentation results of the sampled pixels. The second contribution is a low computational cost algorithm to choose the reference frames. The proposed reference frame selection algorithm reduces the cost of coding uncovered background regions. We also study the number of reference frames required to achieve good coding efficiency. Distortion over foreground pixels is measured to quantify the performance of the proposed techniques. Experimental results show bit rate savings of up to 94.5% over methods proposed in literature on video surveillance data sets. The proposed techniques also provide up to 74.5% reduction in compression complexity without increasing the distortion over the foreground regions in the video sequence.

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The growth rate of high-speed mixing layer between two dissimilar gases is explored through the model free simulation results. To analyse the cause for the higher mixing layer growth rate in comparison to the existing values reported in literature, the results were compared with the model free simulations of mixing of two high-speed streams of nitrogen (similar gas) at matched temperature and density. The analysis indicates that pressure and density fluctuations no longer remain correlated completely for the mixing layer formed between two dissimilar gases at different temperatures in contrast to the complete pressure density correlation for similar gases. It has been observed that the correlation between temperature and density fluctuations is near -1.0 for dissimilar gases in the mixing layer region and is much higher than for similar gases. It is concluded that mixing layer of similar gases shows a decrease in growth rate due to compressibility effect, while that of dissimilar gases shows a decrease due to dominant temperature effect on density.

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In this study, we combine available high resolution structural information on eukaryotic ribosomes with low resolution cryo-EM data on the Hepatitis C Viral RNA (IRES) human ribosome complex. Aided further by the prediction of RNA-protein interactions and restrained docking studies, we gain insights on their interaction at the residue level. We identified the components involved at the major and minor contact regions, and propose that there are energetically favorable local interactions between 40S ribosomal proteins and IRES domains. Domain II of the IRES interacts with ribosomal proteins S5 and S25 while the pseudoknot and the downstream domain IV region bind to ribosomal proteins S26, S28 and S5. We also provide support using UV cross-linking studies to validate our proposition of interaction between the S5 and IRES domains II and IV. We found that domain IIIe makes contact with the ribosomal protein S3a (S1e). Our model also suggests that the ribosomal protein S27 interacts with domain IIIc while S7 has a weak contact with a single base RNA bulge between junction IIIabc and IIId. The interacting residues are highly conserved among mammalian homologs while IRES RNA bases involved in contact do not show strict conservation. IRES RNA binding sites for S25 and S3a show the best conservation among related viral IRESs. The new contacts identified between ribosomal proteins and RNA are consistent with previous independent studies on RNA-binding properties of ribosomal proteins reported in literature, though information at the residue level is not available in previous studies.