Bayesian framework and message passing for joint support and signal recovery of approximately sparse signals

In this paper, we develop a low-complexity message passing algorithm for joint support and signal recovery of approximately sparse signals. The problem of recovery of strictly sparse signals from noisy measurements can be viewed as a problem of recovery of approximately sparse signals from noiseless measurements, making the approach applicable to strictly sparse signal recovery from noisy measurements. The support recovery embedded in the approach makes it suitable for recovery of signals with same sparsity profiles, as in the problem of multiple measurement vectors (MMV). Simulation results show that the proposed algorithm, termed as JSSR-MP (joint support and signal recovery via message passing) algorithm, achieves performance comparable to that of sparse Bayesian learning (M-SBL) algorithm in the literature, at one order less complexity compared to the M-SBL algorithm.

An experimental study on cracking evolution in concrete and cement mortar by the b-value analysis of acoustic emission technique

Notched three point bend (TPB) specimens made with plain concrete and cement mortar were tested under crack mouth opening displacement (CMOD) control at a rate of 0.0004 mm/s and simultaneously acoustic emissions (AE) released were recorded during the experiments. Amplitude distribution analysis of AE released during concrete was carried out to study the development of fracture process in concrete and mortar specimens. The slope of the log-linear frequency-amplitude distribution of AE is known as the AE based b-value. The AE based b-value was computed in terms of physical process of time varying applied load using cumulative frequency distribution (Gutenberg-Richter relationship) and discrete frequency distribution (Aki's method) of AE released during concrete fracture. AE characteristics of plain concrete and cement mortar were studied and discussed and it was observed that the AE based b-value analysis serves as a tool to identify the damage in concrete structural members. (C) 2012 Elsevier Ltd. All rights reserved.

Existence of Value in Stochastic Differential Games of Mixed Type

In this article, we address stochastic differential games of mixed type with both control and stopping times. Under standard assumptions, we show that the value of the game can be characterized as the unique viscosity solution of corresponding Hamilton-Jacobi-Isaacs (HJI) variational inequalities.

A QUADRATIC C degrees INTERIOR PENALTY METHOD FOR LINEAR FOURTH ORDER BOUNDARY VALUE PROBLEMS WITH BOUNDARY CONDITIONS OF THE CAHN-HILLIARD TYPE

We develop a quadratic C degrees interior penalty method for linear fourth order boundary value problems with essential and natural boundary conditions of the Cahn-Hilliard type. Both a priori and a posteriori error estimates are derived. The performance of the method is illustrated by numerical experiments.

Influence limitation in multi-campaign social networks: A Shapley value based approach

We investigate the problem of influence limitation in the presence of competing campaigns in a social network. Given a negative campaign which starts propagating from a specified source and a positive/counter campaign that is initiated, after a certain time delay, to limit the the influence or spread of misinformation by the negative campaign, we are interested in finding the top k influential nodes at which the positive campaign may be triggered. This problem has numerous applications in situations such as limiting the propagation of rumor, arresting the spread of virus through inoculation, initiating a counter-campaign against malicious propaganda, etc. The influence function for the generic influence limitation problem is non-submodular. Restricted versions of the influence limitation problem, reported in the literature, assume submodularity of the influence function and do not capture the problem in a realistic setting. In this paper, we propose a novel computational approach for the influence limitation problem based on Shapley value, a solution concept in cooperative game theory. Our approach works equally effectively for both submodular and non-submodular influence functions. Experiments on standard real world social network datasets reveal that the proposed approach outperforms existing heuristics in the literature. As a non-trivial extension, we also address the problem of influence limitation in the presence of multiple competing campaigns.

Seismic site classification and correlation between standard penetration test N value and shear wave velocity for Lucknow city in Indo-Gangetic basin

Subsurface lithology and seismic site classification of Lucknow urban center located in the central part of the Indo-Gangetic Basin (IGB) are presented based on detailed shallow subsurface investigations and borehole analysis. These are done by carrying out 47 seismic surface wave tests using multichannel analysis of surface waves (MASW) and 23 boreholes drilled up to 30 m with standard penetration test (SPT) N values. Subsurface lithology profiles drawn from the drilled boreholes show low- to medium-compressibility clay and silty to poorly graded sand available till depth of 30 m. In addition, deeper boreholes (depth >150 m) were collected from the Lucknow Jal Nigam (Water Corporation), Government of Uttar Pradesh to understand deeper subsoil stratification. Deeper boreholes in this paper refer to those with depth over 150 m. These reports show the presence of clay mix with sand and Kankar at some locations till a depth of 150 m, followed by layers of sand, clay, and Kankar up to 400 m. Based on the available details, shallow and deeper cross-sections through Lucknow are presented. Shear wave velocity (SWV) and N-SPT values were measured for the study area using MASW and SPT testing. Measured SWV and N-SPT values for the same locations were found to be comparable. These values were used to estimate 30 m average values of N-SPT (N-30) and SWV (V-s(30)) for seismic site classification of the study area as per the National Earthquake Hazards Reduction Program (NEHRP) soil classification system. Based on the NEHRP classification, the entire study area is classified into site class C and D based on V-s(30) and site class D and E based on N-30. The issue of larger amplification during future seismic events is highlighted for a major part of the study area which comes under site class D and E. Also, the mismatch of site classes based on N-30 and V-s(30) raises the question of the suitability of the NEHRP classification system for the study region. Further, 17 sets of SPT and SWV data are used to develop a correlation between N-SPT and SWV. This represents a first attempt of seismic site classification and correlation between N-SPT and SWV in the Indo-Gangetic Basin.

Evaluation of document binarization using eigen value decomposition

A necessary step for the recognition of scanned documents is binarization, which is essentially the segmentation of the document. In order to binarize a scanned document, we can find several algorithms in the literature. What is the best binarization result for a given document image? To answer this question, a user needs to check different binarization algorithms for suitability, since different algorithms may work better for different type of documents. Manually choosing the best from a set of binarized documents is time consuming. To automate the selection of the best segmented document, either we need to use ground-truth of the document or propose an evaluation metric. If ground-truth is available, then precision and recall can be used to choose the best binarized document. What is the case, when ground-truth is not available? Can we come up with a metric which evaluates these binarized documents? Hence, we propose a metric to evaluate binarized document images using eigen value decomposition. We have evaluated this measure on DIBCO and H-DIBCO datasets. The proposed method chooses the best binarized document that is close to the ground-truth of the document.

Channel Hardening-Exploiting Message Passing (CHEMP) Receiver in Large-Scale MIMO Systems

In this paper, we propose a multiple-input multiple-output (MIMO) receiver algorithm that exploits channel hardening that occurs in large MIMO channels. Channel hardening refers to the phenomenon where the off-diagonal terms of the matrix become increasingly weaker compared to the diagonal terms as the size of the channel gain matrix increases. Specifically, we propose a message passing detection (MPD) algorithm which works with the real-valued matched filtered received vector (whose signal term becomes, where is the transmitted vector), and uses a Gaussian approximation on the off-diagonal terms of the matrix. We also propose a simple estimation scheme which directly obtains an estimate of (instead of an estimate of), which is used as an effective channel estimate in the MPD algorithm. We refer to this receiver as the channel hardening-exploiting message passing (CHEMP) receiver. The proposed CHEMP receiver achieves very good performance in large-scaleMIMO systems (e.g., in systems with 16 to 128 uplink users and 128 base station antennas). For the considered large MIMO settings, the complexity of the proposed MPD algorithm is almost the same as or less than that of the minimum mean square error (MMSE) detection. This is because the MPD algorithm does not need a matrix inversion. It also achieves a significantly better performance compared to MMSE and other message passing detection algorithms using MMSE estimate of. Further, we design optimized irregular low density parity check (LDPC) codes specific to the considered large MIMO channel and the CHEMP receiver through EXIT chart matching. The LDPC codes thus obtained achieve improved coded bit error rate performance compared to off-the-shelf irregular LDPC codes.

A detailed numerical study of NOx kinetics in low calorific value H-2/CO syngas flames

The present study provides an extensive and detailed numerical analysis of NO chemical kinetics in low calorific value H-2/CO syngas flames utilizing predictions by five chemical kinetic mechanisms available out of which four deal with H-2/CO while the fifth mechanism (GRI 3.0) additionally accounts for hydrocarbon chemistry. Comparison of predicted axial NO profiles in premixed flat flames with measurements at 1 bar, 3.05 bar and 9.15 bar shows considerably large quantitative differences among the various mechanisms. However, at each pressure, the quantitative reaction path diagrams show similar NO formation pathways for most of the mechanisms. Interestingly, in counterflow diffusion flames, the quantitative reaction path diagrams and sensitivity analyses using the various mechanisms reveal major differences in the NO formation pathways and reaction rates of important reactions. The NNH and N2O intermediate pathways are found to be the major contributors for NO formation in all the reaction mechanisms except GRI 3.0 in syngas diffusion flames. The GRI 3.0 mechanism is observed to predict prompt NO pathway as the major contributing pathway to NO formation. This is attributed to prediction of a large concentration of CH radical by the GRI 3.0 as opposed to a relatively negligible value predicted by all other mechanisms. Also, the back-conversion of NNH into N2O at lower pressures (2-4 bar) was uniquely observed for one of the five mechanisms. The net reaction rates and peak flame temperatures are used to correlate and explain the differences observed in the peak NO] at different pressures. This study identifies key reactions needing assessment and also highlights the need for experimental data in syngas diffusion flames in order to assess and optimize H-2/CO and nitrogen chemistry. Copyright (C) 2014, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved.

Optimal error estimate using mesh equidistribution technique for singularly perturbed system of reaction-diffusion boundary-value problems

In this article, we study the problem of determining an appropriate grading of meshes for a system of coupled singularly perturbed reaction-diffusion problems having diffusion parameters with different magnitudes. The central difference scheme is used to discretize the problem on adaptively generated mesh where the mesh equation is derived using an equidistribution principle. An a priori monitor function is obtained from the error estimate. A suitable a posteriori analogue of this monitor function is also derived for the mesh construction which will lead to an optimal second-order parameter uniform convergence. We present the results of numerical experiments for linear and semilinear reaction-diffusion systems to support the effectiveness of our preferred monitor function obtained from theoretical analysis. (C) 2014 Elsevier Inc. All rights reserved.

High Value of Proton Relaxivity Achieved by Graphene Oxide-Cobalt Ferrite Nanoparticle Composite: A Potential Contrast Agent in Magnetic Resonance Imaging

This work investigates the potential of graphene oxide-cobalt ferrite nanoparticle (GO-CoFe2O4) composite as image contrast enhancing material in Magnetic Resonance Imaging (MRI). In the preset work, GO-CoFe2O4 composites were produced by a two-step synthesis process. In the first step, graphene oxide (GO) was synthesized, and in the second step CoFe2O4 nanoparticles were synthesized in a reaction mixture containing GO to yield graphene GO-CoFe2O4 composite. Proton relaxivity value obtained from the composite was 361 mM(-1)s(-1). This value of proton relaxivity is higher than a majority of reported relaxivity values obtained using several ferrite based contrast agents.

Exploring sand and bentonite - enhanced sand as filter media for nitrate removal

Increasing nitrate concentrations in ground water is deleterious to human health as ingestion of such water can cause methemoglobinemia in infants and even cancer in adults (desirable limit for nitrate as NO3 - 45 mg/L, IS code 10500-1991). Excess nitrate concentrations in ground water is contributed by reason being disposal of sewage and excessive use of fertilizers. Though numerous technologies such as reverse osmosis, ion exchange, electro-dialysis, permeable reactive barriers using zerovalent iron etc exists, nitrate removal continues to be one of challenging issue as nitrate ion is highly mobile within the soil strata. The tapping the denitrification potential of soil denitrifiers which are inherently available in the soil matrix is the most sustainable approach to mitigate accumulation of nitrate in ground water. The insitu denitrification of sand and bentonite enhanced sand (bentonite content = 5%) in presence of easily assimilable organic carbon such as ethanol was studied. Batch studies showed that nitrate reduction by sand follows first order kinetics with a rate constant 5.3x10(-2) hr(-1) and rate constant 4.3 x 10(-2) hr(-1) was obtained for bentonite-enhanced sand (BS) at 25 degrees C. Filter columns (height = 5 cm and diameter = 8.2 cm) were constructed using sand and bentonite-enhanced sand as filter media. The filtration rate through both the filter columns was maintained at average value of 2.60 cm/h. The nitrate removal rates through both the filter media was assessed for solution containing 22.6 mg NO3-N/L concentrations while keeping C/N mass ratio as 3. For sand filter column, the nitrate removal efficiency reached the average value of 97.6% after passing 50 pore volumes of the nitrate solution. For bentonite-enhanced sand filter column, the average nitrate removal efficiency was 83.5%. The time required for effective operation for sand filter bed was 100 hours, while bentonite-enhanced sand filter bed did not require any maturation period as that of sand filter bed for effective performance because the presence of micropores in bentonite increases the hydraulic retention time of the solution inside the filter bed.