Capacity bounds for the Gaussian X channel

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.

Analysis of size quantization and temperature effects on the threshold voltage of thin silicon film double-gate metal-oxide-semiconductor field-effect transistor (MOSFET)

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.

Construction of Block Orthogonal STBCs and Reducing Their Sphere Decoding Complexity

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.

Capturability of augmented proportional navigation (APN) guidance with nonlinear engagement dynamics

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.

Hydro-mechanical characterization of Barmer 1 bentonite from Rajasthan, India

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.

Minimizing total weighted tardiness on heterogeneous batch processors with incompatible job families

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.

Generative Maximum Entropy Learning for Multiclass Classification

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.

Analysis of Annular Plug Nozzle Flowfield

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.

Skip Decision and Reference Frame Selection for Low-Complexity H.264/AVC Surveillance Video Coding

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.

Exploration of supersonic confined mixing layer: Effect of dissimilar gases at different temperatures

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.

Re-analysis of cryoEM data on HCV IRES bound to 40S subunit of human ribosome integrated with recent structural information suggests new contact regions between ribosomal proteins and HCV RNA

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.

Influence of curvature on the device physics of thin film transistors on flexible substrates

Thin film transistors (TFTs) on elastomers promise flexible electronics with stretching and bending. Recently, there have been several experimental studies reporting the behavior of TFTs under bending and buckling. In the presence of stress, the insulator capacitance is influenced due to two reasons. The first is the variation in insulator thickness depending on the Poisson ratio and strain. The second is the geometric influence of the curvature of the insulator-semiconductor interface during bending or buckling. This paper models the role of curvature on TFT performance and brings to light an elegant result wherein the TFT characteristics is dependent on the area under the capacitance-distance curve. The paper compares models with simulations and explains several experimental findings reported in literature. (C) 2014 AIP Publishing LLC.

Bearing capacity of circular foundations reinforced with geogrid sheets

The ultimate bearing capacity of a circular footing, placed over a soil mass which is reinforced with horizontal layers of circular reinforcement sheets, has been determined by using the upper bound theorem of the limit analysis in conjunction with finite elements and linear optimization. For performing the analysis, three different soil media have been separately considered, namely, (i) fully granular, (ii) cohesive frictional, and (iii) fully cohesive with an additional provision to account for an increase of cohesion with depth. The reinforcement sheets are assumed to be structurally strong to resist axial tension but without having any resistance to bending; such an approximation usually holds good for geogrid sheets. The shear failure between the reinforcement sheet and adjoining soil mass has been considered. The increase in the magnitudes of the bearing capacity factors (N-c and N-gamma) with an inclusion of the reinforcement has been computed in terms of the efficiency factors eta(c) and eta(gamma). The results have been obtained (i) for different values of phi in case of fully granular (c=0) and c-phi soils, and (ii) for different rates (m) at which the cohesion increases with depth for a purely cohesive soil (phi=0 degrees). The critical positions and corresponding optimum diameter of the reinforcement sheets, for achieving the maximum bearing capacity, have also been established. The increase in the bearing capacity with an employment of the reinforcement increases continuously with an increase in phi. The improvement in the bearing capacity becomes quite extensive for two layers of the reinforcements as compared to the single layer of the reinforcement. The results obtained from the study are found to compare well with the available theoretical and experimental data reported in literature. (C) 2014 The Japanese Geotechnical Society. Production and hosting by Elsevier B.V. All rights reserved.

Seismic Bearing Capacity of Shallow Embedded Foundations on a Sloping Ground Surface

By using the lower-bound theorem of the limit analysis in conjunction with finite elements and nonlinear optimization, bearing-capacity factors, N-c and N-gamma q, with an inclusion of pseudostatic horizontal seismic body forces, have been determined for a shallow embedded horizontal strip footing placed on sloping ground surface. The variation of N-c and N-gamma q with changes in slope angle (beta) for different values of seismic acceleration coefficient (k(h)) has been obtained. The analysis reveals that irrespective of ground inclination and the embedment depth of the footing, the factors N-c and N-gamma q decrease quite considerably with an increase in k(h). As compared with N-c, the factor N-gamma q is affected more extensively with changes in k(h) and beta. Unlike most of the results reported in literature for the seismic case, the present computational results take into account the shear resistance of soil mass above the footing level. An increase in the depth of the embedment leads to an increase in the magnitudes of both N-c and N-gamma q. (C) 2014 American Society of Civil Engineers.

Analysis on the atomization characteristics of aviation biofuel discharging from simplex swirl atomizer

The atomization characteristics of aviation biofuel discharging from a simplex swirl atomizer into quiescent atmospheric air are studied. The aviation biofuel is a mixture of 90% commercially available camelina-derived biofuel and 10% VonSol-53 (aromatics). The experiments are conducted in a spray test facility at varying fuel flow rate conditions. The measured characteristics include atomizer flow number, spray cone angle, breakup length of liquid sheet, wavelength of undulations on liquid sheet, and spray droplet size. The characteristics of biofuel sheet breakup are deduced from the captured images of biofuel spray. The measurements of spray droplet size distribution are obtained using Spraytec. The experimentally measured characteristics of the biofuel sheet breakup are compared with the predictions obtained from the liquid film breakup model proposed by Senecal et al. (1999). The measurements of wavelength and breakup length of the biofuel sheet discharging from the simplex swirl atomizer agree well with the model predictions. The model-predicted droplet size for the biofuel spray is significantly higher than the experimentally measured Sauter mean diameter (SMD). The spray droplets formed from the liquid sheet breakup undergo secondary atomization until 35-45 mm from the atomizer exit and thereafter the SMD increases downstream due to the combined effect of fuel evaporation and droplet coalescence. A good comparison is observed between the experimentally measured SMD of the biofuel spray and the predictions obtained using the empirical correlation reported in literature for sprays discharging from simplex swirl atomizers. (C) 2015 Elsevier Ltd. All rights reserved.