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In this paper two Soft Sensors, for the estimation of pollutants in the output flow of a Sour Water Stripping plant, are described. The plant operates in a large refinery in Italy. The Soft Sensors have been implemented by non linear data-driven approaches, by using neural networks. In order to face the issue of different sampling intervals of process and quality variables, a deep learning approach...
Stereo matching is the key problem in many stereo vison based 3D applications. One of the factors make local stereo matching time-consuming is that every pixel has the same disparity range as the pre-set one, which should be larger than all possible disparities. An improper pre-set disparity range may lead to redundant computation for some pixels and inadequate computation for some others. In this...
We present two approaches for leveraging correlations in learning the utilities of non-cooperative agents' competing in a game: correlation and coalition utility learning. In the former, we estimate the correlations between agents using constrained Feasible Generalized Least Squares with noise estimation and then use the estimated correlations to generate a correlation utility function for each agent...
In this work, a new methodology to estimate the respiratory air flow rate from pulmonary sounds is proposed. Previously in the literature, it has been suggested to use the auto-regressive model to estimate the flow rate from pulmonary sounds, moreover, it has been presented that sounds are more correlated with the flow rate in certain frequency bands. In this work, on the other hand, the optimal auto-regressive...
In this paper, the relevance of deep neural network (DNN) is studied in big data scenarios, specifically for prognostics applications. It is observed that fault predictions can be performed more efficiently when DNN is used with a pre-processing step. A novel hierarchical dimension reduction (HDR) approach is therefore proposed as a pre-processing step to DNN. This two-step approach is shown to be...
With the rapid deployment of the high speed railway (HSR), the wireless communication in HSR has been one of the indispensable scenarios in the fifth generation (5G) communications. In order to improve the performance of the orthogonal frequency division multiplexing (OFDM) system in the HSR scenarios, we propose an enhanced linear minimum mean square error channel estimation scheme based on multi-path...
Image registration plays a major role in many areas such as remote sensing, astronomy, biomedical imaging, and so on. Our main contribution in this paper is to present a new subpixel image registration that aligns translated of pair images. This algorithm combines well-known phase correlation technique with the differential methods of the optical flow field, especially the Locus-Kanade technique to...
This informational collection is utilized to anticipate the odds of an event of heart assault for a patient. In the season of cutting edge smartphones contributing 12 attributes is not feasible. We play out the product metric examination on the given informational collection. In view of the investigation of information we try to bring the total number of attributes into a small figure and in the end,...
Spearman's rank relationship coefficient is a nonparametric (dispersion free) rank measurement. Spearman's coefficient is not a measure of the direct relationship between two factors, as a few ”analysts” proclaim. Pearson's relationship coefficient is the covariance of the two factors separated by the result of their standard deviations. The possibility of the paper is to look at the estimations of...
Axon diameter estimation has been a focus of the diffusion MRI community for the past decade. The main argument has been that while diffusion models always overestimate the true axon diameter, their estimation still correlates with changes in true value. Until now, this remains more as a discussion point. The aim of this paper is to clarify this hypothesis using a recently acquired cat spinal cord...
The estimation of the noise power is a core issue in wireless communication systems. In broadcasting, every OFDM frame starts with a preamble symbol, which facilitates the noise power estimation. However, the performance of preamble-based noise estimation schemes worsens in fast-changing environments and cannot efficiently track the noise variation well. In order to track the noise variation symbol...
Lifetime distribution characteristics of FEOL/MOL/ BEOL time-dependent breakdown (TDDB) with defect clustering conditions were investigated by using a recently proposed two-step probability plot. This method was proposed to estimate parameters of the lifetime distribution function that is based on the defect clustering concept, and has two shape parameters. In the first step, the clustering parameter...
The main role in the task of process remote sensing data of the Earth surface are played algorithms of forming and classification those data. From the statistical point of view the solution is based on the maximum-likelihood method. The paper presents analytical equations for likelihood coefficients and the structural scheme of their forming in the solution of radar signal recognition. To analyze...
We present a modification to time-delay and phase-shift estimators used in ultrasound imaging methods. In this modification, we selectively eliminate covariance terms from the estimator corresponding to channel signal pairs that have low coherence. We demonstrate this modification in simulation and phantom experiments in the application of color flow imaging. We demonstrate this technique in application...
This paper studies a class of binary matrices with correlations between distinct columnsequal to zero or one, which has reported comparable performance with random matrices inrecent studies of compressed sensing. For such matrix, we analyze its structure propertyand provide an improved performance estimation.
Friend recommendation has been one of the most challenging problems as the social networks grow rapidly, due to the needs of seeking people who are acquaintances in real life or share the common interests. In this paper, we tackle the problem by treating it as a link prediction task and propose a hybrid algorithm that exploits the existing friendship links, users' history ratings and the tags annotated...
Direct Sequence Spread Spectrum (DSSS) signal has been widely used because of its low signal-to-noise ratio, strong anti-interference, low interception rate and multi-path effect. It is gradually replacing the traditional communications, and widely used in modern military and commercial communications systems. Therefore, the corresponding direct-communication communication reconnaissance technology...
Traditional kernelized correlation filter tracking methods use the target position in the current frame to estimate the moving target initial position in the next frame. For fast moving target, these methods lose the target easily. To cope with this problem, a novel scale-adaptive regression position prediction tracking approach is proposed. This algorithm employs regression prediction method to predict...
The Wiener filter is a well-known signal processing method for improving a noisy signal's quality. The Wiener filter requires either knowledge of or estimates of the power spectra of the signal-of-interest and of the undesired noise, leading to implementation challenges. In this paper, we show how a recently-developed second-order signal quantity termed the panorama can be employed to compute the...
We further delay embedding framework application to multiple time series for extraction of their potential causal interactions. We introduce a novel geometric model-free causality measure that can efficiently detect linear and nonlinear causal interactions between time series with no prior information or parameter estimation. Using multivariate delay embedding, we construct a point cloud from a set...
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