Optical Flow based on Approximate Nearest Neighbor Field

In this work, we propose an algorithm for optical flow estimation using Approximate Nearest Neighbor Fields (ANNF). Proposed optical flow estimation algorithm consists of two steps, flow initialization using ANNF maps and cost filtering. Flow initialization is done by computing the ANNF map using FeatureMatch between two consecutive frames. The ANNF map obtained represents a noisy optical flow, which is refined by making use of superpixels. The best flow associated with each superpixel is computed by optimizing a cost function. The proposed approach is evaluated on Middlebury and MPI-Sintel optical flow dataset and is found to be comparable with the state of the art methods for optical flow estimation.

Estimation of the components of municipal solid waste settlement

Estimation of the municipal solid waste settlements and the contribution of each of the components are essential in the estimation of the volume of the waste that can be accommodated in a landfill and increase the post-usage of the landfill. This article describes an experimental methodology for estimating and separating primary settlement, settlement owing to creep and biodegradation-induced settlement. The primary settlement and secondary settlement have been estimated and separated based on 100% pore pressure dissipation time and the coefficient of consolidation. Mechanical creep and biodegradation settlements were estimated and separated based on the observed time required for landfill gas production. The results of a series of laboratory triaxial tests, creep tests and anaerobic reactor cell setups were conducted to describe the components of settlement. All the tests were conducted on municipal solid waste (compost reject) samples. It was observed that biodegradation accounted to more than 40% of the total settlement, whereas mechanical creep contributed more than 20% towards the total settlement. The essential model parameters, such as the compression ratio (C-c'), rate of mechanical creep (c), coefficient of mechanical creep (b), rate of biodegradation (d) and the total strain owing to biodegradation (E-DG), are useful parameters in the estimation of total settlements as well as components of settlement in landfill.

Large Diameter Triaxial Tests on Geosynthetic-Reinforced Granular Subbases

The estimation of strength and stiffness of reinforced aggregates is very important for the design and construction of reinforced unpaved/paved road sections. This paper presents the experimental results from static and cyclic triaxial tests carried out on granular subbase samples reinforced with multiple layers of geogrid reinforcement. Aggregates of different size ranges were mixed in calculated proportions by weight to obtain the gradation specified for rural roads. Triaxial samples of 300 mm diameter and 600 mm height were prepared using this sampled aggregate. The strength and stiffness characteristics of this aggregate reinforced with geogrids at different elevations were determined from static and cyclic triaxial tests. Triaxial tests were also carried out on geocell encased aggregates, and the results are compared. From the experimental results it is observed that reinforced systems carried more stresses than unreinforced systems at the same strain level. The beneficial effect increased with increase in the quantity of reinforcement, whereas for geocell reinforcement, the advantage was evident only at higher strains. (C) 2014 American Society of Civil Engineers.

Probable maximum precipitation estimation for catchments in Mahanadi river basin

Probable maximum precipitation (PMP) is a theoretical concept that is widely used by hydrologists to arrive at estimates for probable maximum flood (PMF) that find use in planning, design and risk assessment of high-hazard hydrological structures such as flood control dams upstream of populated areas. The PMP represents the greatest depth of precipitation for a given duration that is meteorologically possible for a watershed or an area at a particular time of year, with no allowance made for long-term climatic trends. Various methods are in use for estimation of PMP over a target location corresponding to different durations. Moisture maximization method and Hershfield method are two widely used methods. The former method maximizes the observed storms assuming that the atmospheric moisture would rise up to a very high value estimated based on the maximum daily dew point temperature. On the other hand, the latter method is a statistical method based on a general frequency equation given by Chow. The present study provides one-day PMP estimates and PMP maps for Mahanadi river basin based on the aforementioned methods. There is a need for such estimates and maps, as the river basin is prone to frequent floods. Utility of the constructed PMP maps in computing PMP for various catchments in the river basin is demonstrated. The PMP estimates can eventually be used to arrive at PMF estimates for those catchments. (C) 2015 The Authors. Published by Elsevier B.V.

Markov chain splitting methods in structural reliability integral estimation

Monte Carlo simulation methods involving splitting of Markov chains have been used in evaluation of multi-fold integrals in different application areas. We examine in this paper the performance of these methods in the context of evaluation of reliability integrals from the point of view of characterizing the sampling fluctuations. The methods discussed include the Au-Beck subset simulation, Holmes-Diaconis-Ross method, and generalized splitting algorithm. A few improvisations based on first order reliability method are suggested to select algorithmic parameters of the latter two methods. The bias and sampling variance of the alternative estimators are discussed. Also, an approximation to the sampling distribution of some of these estimators is obtained. Illustrative examples involving component and series system reliability analyses are presented with a view to bring out the relative merits of alternative methods. (C) 2015 Elsevier Ltd. All rights reserved.

Estimation of Aboveground Phytomass of Plantations Using Digital Photogrammetry and High Resolution Remote Sensing Data

The study follows an approach to estimate phytomass using recent techniques of remote sensing and digital photogrammetry. It involved tree inventory of forest plantations in Bhakra forest range of Nainital district. Panchromatic stereo dataset of Cartosat-1 was evaluated for mean stand height retrieval. Texture analysis and tree-tops detection analyses were done on Quick-Bird PAN data. The composite texture image of mean, variance and contrast with a 5x5 pixel window was found best to separate tree crowns for assessment of crown areas. Tree tops count obtained by local maxima filtering was found to be 83.4 % efficient with an RMSE+/-13 for 35 sample plots. The predicted phytomass ranged from 27.01 to 35.08 t/ha in the case of Eucalyptus sp. while in the case of Tectona grandis from 26.52 to 156 t/ha. The correlation between observed and predicted phytomass in Eucalyptus sp. was 0.468 with an RMSE of 5.12. However, the phytomass predicted in Tectona grandis was fairly strong with R-2=0.65 and RMSE of 9.89 as there was no undergrowth and the crowns were clearly visible. Results of the study show the potential of Cartosat-1 derived DSM and Quick-Bird texture image for the estimation of stand height, stem diameter, tree count and phytomass of important timber species.

Event-triggered sampling using signal extrema for instantaneous amplitude and instantaneous frequency estimation

Event-triggered sampling (ETS) is a new approach towards efficient signal analysis. The goal of ETS need not be only signal reconstruction, but also direct estimation of desired information in the signal by skillful design of event. We show a promise of ETS approach towards better analysis of oscillatory non-stationary signals modeled by a time-varying sinusoid, when compared to existing uniform Nyquist-rate sampling based signal processing. We examine samples drawn using ETS, with events as zero-crossing (ZC), level-crossing (LC), and extrema, for additive in-band noise and jitter in detection instant. We find that extrema samples are robust, and also facilitate instantaneous amplitude (IA), and instantaneous frequency (IF) estimation in a time-varying sinusoid. The estimation is proposed solely using extrema samples, and a local polynomial regression based least-squares fitting approach. The proposed approach shows improvement, for noisy signals, over widely used analytic signal, energy separation, and ZC based approaches (which are based on uniform Nyquist-rate sampling based data-acquisition and processing). Further, extrema based ETS in general gives a sub-sampled representation (relative to Nyquistrate) of a time-varying sinusoid. For the same data-set size captured with extrema based ETS, and uniform sampling, the former gives much better IA and IF estimation. (C) 2015 Elsevier B.V. All rights reserved.

Measurement of Large Dipolar Couplings of a Liquid Crystal with Terminal Phenyl Rings and Estimation of the Order Parameters

NMR spectroscopy is a powerful means of studying liquid-crystalline systems at atomic resolutions. Of the many parameters that can provide information on the dynamics and order of the systems, H-1-C-13 dipolar couplings are an important means of obtaining such information. Depending on the details of the molecular structure and the magnitude of the order parameters, the dipolar couplings can vary over a wide range of values. Thus the method employed to estimate the dipolar couplings should be capable of estimating both large and small dipolar couplings at the same time. For this purpose, we consider here a two-dimensional NMR experiment that works similar to the insensitive nuclei enhanced by polarization transfer (INEPT) experiment in solution. With the incorporation of a modification proposed earlier for experiments with low radio frequency power, the scheme is observed to enable a wide range of dipolar couplings to be estimated at the same time. We utilized this approach to obtain dipolar couplings in a liquid crystal with phenyl rings attached to either end of the molecule, and estimated its local order parameters.

Minimum-Error-Probability CFO Estimation for Multiuser MIMO-OFDM Systems

We consider carrier frequency offset (CFO) estimation in the context of multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems over noisy frequency-selective wireless channels with both single- and multiuser scenarios. We conceived a new approach for parameter estimation by discretizing the continuous-valued CFO parameter into a discrete set of bins and then invoked detection theory, analogous to the minimum-bit-error-ratio optimization framework for detecting the finite-alphabet received signal. Using this radical approach, we propose a novel CFO estimation method and study its performance using both analytical results and Monte Carlo simulations. We obtain expressions for the variance of the CFO estimation error and the resultant BER degradation with the single- user scenario. Our simulations demonstrate that the overall BER performance of a MIMO-OFDM system using the proposed method is substantially improved for all the modulation schemes considered, albeit this is achieved at increased complexity.

Role of the Molar Volume on Estimated Diffusion Coefficients

The role of the molar volume on the estimated diffusion parameters has been speculated for decades. The Matano-Boltzmann method was the first to be developed for the estimation of the variation of the interdiffusion coefficients with composition. However, this could be used only when the molar volume varies ideally or remains constant. Although there are no such systems, this method is still being used to consider the ideal variation. More efficient methods were developed by Sauer-Freise, Den Broeder, and Wagner to tackle this problem. However, there is a lack of research indicating the most efficient method. We have shown that Wagner's method is the most suitable one when the molar volume deviates from the ideal value. Similarly, there are two methods for the estimation of the ratio of intrinsic diffusion coefficients at the Kirkendall marker plane proposed by Heumann and van Loo. The Heumann method, like the Matano-Boltzmann method, is suitable to use only when the molar volume varies more or less ideally or remains constant. In most of the real systems, where molar volume deviates from the ideality, it is safe to use the van Loo method. We have shown that the Heumann method introduces large errors even for a very small deviation of the molar volume from the ideal value. On the other hand, the van Loo method is relatively less sensitive to it. Overall, the estimation of the intrinsic diffusion coefficient is more sensitive than the interdiffusion coefficient.

Minimization Problems Based on Relative alpha-Entropy II: Reverse Projection

In part I of this two-part work, certain minimization problems based on a parametric family of relative entropies (denoted I-alpha) were studied. Such minimizers were called forward I-alpha-projections. Here, a complementary class of minimization problems leading to the so-called reverse I-alpha-projections are studied. Reverse I-alpha-projections, particularly on log-convex or power-law families, are of interest in robust estimation problems (alpha > 1) and in constrained compression settings (alpha < 1). Orthogonality of the power-law family with an associated linear family is first established and is then exploited to turn a reverse I-alpha-projection into a forward I-alpha-projection. The transformed problem is a simpler quasi-convex minimization subject to linear constraints.

Estimation of Parameters for Battery Storage Models

This paper presents a comprehensive and robust strategy for the estimation of battery model parameters from noise corrupted data. The deficiencies of the existing methods for parameter estimation are studied and the proposed parameter estimation strategy improves on earlier methods by working optimally for low as well as high discharge currents, providing accurate estimates even under high levels of noise, and with a wide range of initial values. Testing on different data sets confirms the performance of the proposed parameter estimation strategy.

Biodiesel Exhaust Treatment with HFAC Plasma supported by Red Mud: Study on DeNOx and power consumption

The concentration of Nitrogen Oxides (NOx) in engines which use biodiesel as fuel is higher compared to conventional diesel engine exhaust. In this paper, an attempt has been made to treat this exhaust using a combination of High frequency AC (HFAC) plasma and an industrial waste, Red Mud which shows proclivity towards Nitrogen dioxide (NO2) adsorption. The high frequency AC source in combination with the proposed compact double dielectric plasma reactors is relatively more efficient in converting Nitric Oxide (NO) to NO2. It has been shown that the plasma treated gas enhances the activity of red mud as an adsorbent/catalyst and about 60-72% NOx removal efficiency was observed at a specific energy of 250 J/L. The advantage in this method is the cost effectiveness and abundant availability of the waste red mud in the industry. Further, power estimation studies were carried out using Manley's equation for the two reactors employed in the experiment and a close agreement between experimental and predicted powers was observed. (C) 2015 The Authors. Published by Elsevier Ltd.

Joint Channel Estimation and Data Detection in MIMO-OFDM Systems: A Sparse Bayesian Learning Approach

The impulse response of wireless channels between the N-t transmit and N-r receive antennas of a MIMO-OFDM system are group approximately sparse (ga-sparse), i.e., NtNt the channels have a small number of significant paths relative to the channel delay spread and the time-lags of the significant paths between transmit and receive antenna pairs coincide. Often, wireless channels are also group approximately cluster-sparse (gac-sparse), i.e., every ga-sparse channel consists of clusters, where a few clusters have all strong components while most clusters have all weak components. In this paper, we cast the problem of estimating the ga-sparse and gac-sparse block-fading and time-varying channels in the sparse Bayesian learning (SBL) framework and propose a bouquet of novel algorithms for pilot-based channel estimation, and joint channel estimation and data detection, in MIMO-OFDM systems. The proposed algorithms are capable of estimating the sparse wireless channels even when the measurement matrix is only partially known. Further, we employ a first-order autoregressive modeling of the temporal variation of the ga-sparse and gac-sparse channels and propose a recursive Kalman filtering and smoothing (KFS) technique for joint channel estimation, tracking, and data detection. We also propose novel, parallel-implementation based, low-complexity techniques for estimating gac-sparse channels. Monte Carlo simulations illustrate the benefit of exploiting the gac-sparse structure in the wireless channel in terms of the mean square error (MSE) and coded bit error rate (BER) performance.

Estimation of Power Input to Complex Dielectric Barrier Discharge Reactor Geometries used in NOx Cleaning

Studies were carried out to estimate the power input to Dielectric Barrier Discharge (DBD) reactors powered by AC high voltage in the context of their application in non-thermal plasma cleaning of exhaust gases. Power input to the reactors was determined both theoretically and experimentally. Four different reactor geometries energized with 50 Hz and 1.5 kHz AC excitation were considered for the study. The theoretically estimated power using Manley's equation was found to agree with the experimental results. Results show that the analytically computed capacitance, without including the electrode edge effects, gives sufficiently good results that are matching with the measured values. For complex geometries where analytical calculation of capacitance is often difficult, a novel method of estimating the reactor capacitance, and hence the power input to the reactor, was introduced in this paper. The predicted results were validated with experiments.