CINXE.COM

<!DOCTYPE html> <html lang="en" dir="ltr"> <head>  <script async src="https://www.googletagmanager.com/gtag/js?id=G-P63WKM1TM1"></script> <script> window.dataLayer = window.dataLayer || []; function gtag(){dataLayer.push(arguments);} gtag('js', new Date()); gtag('config', 'G-P63WKM1TM1'); </script>  <script type="text/javascript" > (function(m,e,t,r,i,k,a){m[i]=m[i]||function(){(m[i].a=m[i].a||[]).push(arguments)}; m[i].l=1*new Date(); for (var j = 0; j < document.scripts.length; j++) {if (document.scripts[j].src === r) { return; }} k=e.createElement(t),a=e.getElementsByTagName(t)[0],k.async=1,k.src=r,a.parentNode.insertBefore(k,a)}) (window, document, "script", "https://mc.yandex.ru/metrika/tag.js", "ym"); ym(55165297, "init", { clickmap:false, trackLinks:true, accurateTrackBounce:true, webvisor:false }); </script> <noscript><div><img src="https://mc.yandex.ru/watch/55165297" style="position:absolute; left:-9999px;" alt="" /></div></noscript>    <title>Search results for: spectral kurtosis</title> <meta name="description" content="Search results for: spectral kurtosis"> <meta name="keywords" content="spectral kurtosis"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none navbar-toggler ml-auto" type="button" data-toggle="collapse" data-target="#navbarMenu" aria-controls="navbarMenu" aria-expanded="false" aria-label="Toggle navigation"> <span class="navbar-toggler-icon"></span> </button> <div class="w-100"> <div class="d-none d-lg-flex flex-row-reverse"> <form method="get" action="https://waset.org/search" class="form-inline my-2 my-lg-0"> <input class="form-control mr-sm-2" type="search" placeholder="Search Conferences" value="spectral kurtosis" name="q" aria-label="Search"> <button class="btn btn-light my-2 my-sm-0" type="submit"><i class="fas fa-search"></i></button> </form> </div> <div class="collapse navbar-collapse mt-1" id="navbarMenu"> <ul class="navbar-nav ml-auto align-items-center" id="mainNavMenu"> <li class="nav-item"> <a class="nav-link" href="https://waset.org/conferences" title="Conferences in 2024/2025/2026">Conferences</a> </li> <li class="nav-item"> <a class="nav-link" href="https://waset.org/disciplines" title="Disciplines">Disciplines</a> </li> <li class="nav-item"> <a class="nav-link" href="https://waset.org/committees" rel="nofollow">Committees</a> </li> <li class="nav-item dropdown"> <a class="nav-link dropdown-toggle" href="#" id="navbarDropdownPublications" role="button" data-toggle="dropdown" aria-haspopup="true" aria-expanded="false"> Publications </a> <div class="dropdown-menu" aria-labelledby="navbarDropdownPublications"> <a class="dropdown-item" href="https://publications.waset.org/abstracts">Abstracts</a> <a class="dropdown-item" href="https://publications.waset.org">Periodicals</a> <a class="dropdown-item" href="https://publications.waset.org/archive">Archive</a> </div> </li> <li class="nav-item"> <a class="nav-link" href="https://waset.org/page/support" title="Support">Support</a> </li> </ul> </div> </div> </nav> </div> </header> <main> <div class="container mt-4"> <div class="row"> <div class="col-md-9 mx-auto"> <form method="get" action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="spectral kurtosis"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 781</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: spectral kurtosis</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">781</span> Application of Envelope Spectrum Analysis and Spectral Kurtosis to Diagnose Debris Fault in Bearing Using Acoustic Signals</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Henry%20Ogbemudia%20Omoregbee">Henry Ogbemudia Omoregbee</a>, <a href="https://publications.waset.org/abstracts/search?q=Mabel%20Usunobun%20Olanipekun"> Mabel Usunobun Olanipekun</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Debris fault diagnosis based on acoustic signals in rolling element bearing running at low speed and high radial loads are more of low amplitudes, particularly in the case of debris faults whose signals necessitate high sensitivity analyses. As the rollers in the bearing roll over debris trapped in grease used to lubricate the bearings, the envelope signal created by amplitude demodulation carries additional diagnostic information that is not available through ordinary spectrum analysis of the raw signal. The kurtosis value obtained for three different scenarios (debris induced, outer crack induced, and a normal good bearing) couldn't be used to easily identify whether the used bearings were defective or not. It was established in this work that the envelope spectrum analysis detected the fault signature and its harmonics induced in the debris bearings when bandpass filtering of the raw signal with the frequency band specified by kurtogram and spectral kurtosis was made. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=rolling%20bearings" title="rolling bearings">rolling bearings</a>, <a href="https://publications.waset.org/abstracts/search?q=rolling%20element%20bearing%20noise" title=" rolling element bearing noise"> rolling element bearing noise</a>, <a href="https://publications.waset.org/abstracts/search?q=bandpass%20filtering" title=" bandpass filtering"> bandpass filtering</a>, <a href="https://publications.waset.org/abstracts/search?q=harmonics" title=" harmonics"> harmonics</a>, <a href="https://publications.waset.org/abstracts/search?q=envelope%20spectrum%20analysis" title=" envelope spectrum analysis"> envelope spectrum analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=spectral%20kurtosis" title=" spectral kurtosis"> spectral kurtosis</a> </p> <a href="https://publications.waset.org/abstracts/169008/application-of-envelope-spectrum-analysis-and-spectral-kurtosis-to-diagnose-debris-fault-in-bearing-using-acoustic-signals" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/169008.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">86</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">780</span> Bi-Dimensional Spectral Basis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abdelhamid%20Zerroug">Abdelhamid Zerroug</a>, <a href="https://publications.waset.org/abstracts/search?q=Mlle%20Ismahene%20Sehili"> Mlle Ismahene Sehili</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Spectral methods are usually applied to solve uni-dimensional boundary value problems. With the advantage of the creation of multidimensional basis, we propose a new spectral method for bi-dimensional problems. In this article, we start by creating bi-spectral basis by different ways, we developed also a new relations to determine the expressions of spectral coefficients in different partial derivatives expansions. Finally, we propose the principle of a new bi-spectral method for the bi-dimensional problems. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=boundary%20value%20problems" title="boundary value problems">boundary value problems</a>, <a href="https://publications.waset.org/abstracts/search?q=bi-spectral%20methods" title=" bi-spectral methods"> bi-spectral methods</a>, <a href="https://publications.waset.org/abstracts/search?q=bi-dimensional%20Legendre%20basis" title=" bi-dimensional Legendre basis"> bi-dimensional Legendre basis</a>, <a href="https://publications.waset.org/abstracts/search?q=spectral%20method" title=" spectral method"> spectral method</a> </p> <a href="https://publications.waset.org/abstracts/38573/bi-dimensional-spectral-basis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/38573.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">395</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">779</span> Estimation of Endogenous Brain Noise from Brain Response to Flickering Visual Stimulation Magnetoencephalography Visual Perception Speed</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alexander%20N.%20Pisarchik">Alexander N. Pisarchik</a>, <a href="https://publications.waset.org/abstracts/search?q=Parth%20Chholak"> Parth Chholak</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Intrinsic brain noise was estimated via magneto-encephalograms (MEG) recorded during perception of flickering visual stimuli with frequencies of 6.67 and 8.57 Hz. First, we measured the mean phase difference between the flicker signal and steady-state event-related field (SSERF) in the occipital area where the brain response at the flicker frequencies and their harmonics appeared in the power spectrum. Then, we calculated the probability distribution of the phase fluctuations in the regions of frequency locking and computed its kurtosis. Since kurtosis is a measure of the distribution’s sharpness, we suppose that inverse kurtosis is related to intrinsic brain noise. In our experiments, the kurtosis value varied among subjects from K = 3 to K = 5 for 6.67 Hz and from 2.6 to 4 for 8.57 Hz. The majority of subjects demonstrated leptokurtic kurtosis (K < 3), i.e., the distribution tails approached zero more slowly than Gaussian. In addition, we found a strong correlation between kurtosis and brain complexity measured as the correlation dimension, so that the MEGs of subjects with higher kurtosis exhibited lower complexity. The obtained results are discussed in the framework of nonlinear dynamics and complex network theories. Specifically, in a network of coupled oscillators, phase synchronization is mainly determined by two antagonistic factors, noise, and the coupling strength. While noise worsens phase synchronization, the coupling improves it. If we assume that each neuron and each synapse contribute to brain noise, the larger neuronal network should have stronger noise, and therefore phase synchronization should be worse, that results in smaller kurtosis. The described method for brain noise estimation can be useful for diagnostics of some brain pathologies associated with abnormal brain noise. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=brain" title="brain">brain</a>, <a href="https://publications.waset.org/abstracts/search?q=flickering" title=" flickering"> flickering</a>, <a href="https://publications.waset.org/abstracts/search?q=magnetoencephalography" title=" magnetoencephalography"> magnetoencephalography</a>, <a href="https://publications.waset.org/abstracts/search?q=MEG" title=" MEG"> MEG</a>, <a href="https://publications.waset.org/abstracts/search?q=visual%20perception" title=" visual perception"> visual perception</a>, <a href="https://publications.waset.org/abstracts/search?q=perception%20time" title=" perception time"> perception time</a> </p> <a href="https://publications.waset.org/abstracts/104073/estimation-of-endogenous-brain-noise-from-brain-response-to-flickering-visual-stimulation-magnetoencephalography-visual-perception-speed" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/104073.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">148</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">778</span> Asymptotic Spectral Theory for Nonlinear Random Fields</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Karima%20Kimouche">Karima Kimouche</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we consider the asymptotic problems in spectral analysis of stationary causal random fields. We impose conditions only involving (conditional) moments, which are easily verifiable for a variety of nonlinear random fields. Limiting distributions of periodograms and smoothed periodogram spectral density estimates are obtained and applications to the spectral domain bootstrap are given. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=spatial%20nonlinear%20processes" title="spatial nonlinear processes">spatial nonlinear processes</a>, <a href="https://publications.waset.org/abstracts/search?q=spectral%20estimators" title=" spectral estimators"> spectral estimators</a>, <a href="https://publications.waset.org/abstracts/search?q=GMC%20condition" title=" GMC condition"> GMC condition</a>, <a href="https://publications.waset.org/abstracts/search?q=bootstrap%20method" title=" bootstrap method"> bootstrap method</a> </p> <a href="https://publications.waset.org/abstracts/12479/asymptotic-spectral-theory-for-nonlinear-random-fields" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/12479.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">451</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">777</span> On a Generalization of the Spectral Dichotomy Method of a Matrix With Respect to Parabolas</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mouhamadou%20Dosso">Mouhamadou Dosso</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents methods of spectral dichotomy of a matrix which compute spectral projectors on the subspace associated with the eigenvalues external to the parabolas described by a general equation. These methods are modifications of the one proposed in [A. N. Malyshev and M. Sadkane, SIAM J. MATRIX ANAL. APPL. 18 (2), 265-278, 1997] which uses the spectral dichotomy method of a matrix with respect to the imaginary axis. Theoretical and algorithmic aspects of the methods are developed. Numerical results obtained by applying methods presented on matrices are reported. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=spectral%20dichotomy%20method" title="spectral dichotomy method">spectral dichotomy method</a>, <a href="https://publications.waset.org/abstracts/search?q=spectral%20projector" title=" spectral projector"> spectral projector</a>, <a href="https://publications.waset.org/abstracts/search?q=eigensubspaces" title=" eigensubspaces"> eigensubspaces</a>, <a href="https://publications.waset.org/abstracts/search?q=eigenvalue" title=" eigenvalue"> eigenvalue</a> </p> <a href="https://publications.waset.org/abstracts/159807/on-a-generalization-of-the-spectral-dichotomy-method-of-a-matrix-with-respect-to-parabolas" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/159807.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">94</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">776</span> Numerical Simulation of the Kurtosis Effect on the EHL Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=S.%20Gao">S. Gao</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Srirattayawong"> S. Srirattayawong</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this study, a computational fluid dynamics (CFD) model has been developed for studying the effect of surface roughness profile on the EHL problem. The cylinders contact geometry, meshing and calculation of the conservation of mass and momentum equations are carried out by using the commercial software packages ICEMCFD and ANSYS Fluent. The user defined functions (UDFs) for density, viscosity and elastic deformation of the cylinders as the functions of pressure and temperature have been defined for the CFD model. Three different surface roughness profiles are created and incorporated into the CFD model. It is found that the developed CFD model can predict the characteristics of fluid flow and heat transfer in the EHL problem, including the leading parameters such as the pressure distribution, minimal film thickness, viscosity, and density changes. The obtained results show that the pressure profile at the center of the contact area directly relates to the roughness amplitude. The rough surface with kurtosis value over 3 influences the fluctuated shape of pressure distribution higher than other cases. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=CFD" title="CFD">CFD</a>, <a href="https://publications.waset.org/abstracts/search?q=EHL" title=" EHL"> EHL</a>, <a href="https://publications.waset.org/abstracts/search?q=kurtosis" title=" kurtosis"> kurtosis</a>, <a href="https://publications.waset.org/abstracts/search?q=surface%20roughness" title=" surface roughness"> surface roughness</a> </p> <a href="https://publications.waset.org/abstracts/17247/numerical-simulation-of-the-kurtosis-effect-on-the-ehl-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/17247.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">320</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">775</span> Channel Sounding and PAPR Reduction in OFDM for WiMAX Using Software Defined Radio </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=B.%20Siva%20Kumar%20Reddy">B. Siva Kumar Reddy</a>, <a href="https://publications.waset.org/abstracts/search?q=B.%20Lakshmi"> B. Lakshmi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> WiMAX is a high speed broadband wireless access technology that adopted OFDM/OFDMA techniques to supply higher data rates with high spectral efficiency. However, OFDM suffers in view of high Peak to Average Power Ratio (PAPR) and high affect to synchronization errors. In this paper, the high PAPR problem is solved by using phase modulation to get Constant Envelop Orthogonal Frequency Division Multiplexing (CE-OFDM). The synchronization failures are brought down by employing a frequency lock loop, Poly phase clock synchronizer, Costas loop and blind equalizers such as Constant Modulus Algorithm (CMA) equalizer and Sign Kurtosis Maximization Adaptive Algorithm (SKMAA) equalizers. The WiMAX physical layer is executed on Software Defined Radio (SDR) prototype by utilizing USRP N210 as hardware and GNU Radio as software plat-forms. A SNR estimation is performed on the signal received through USRP N210. To empathize wireless propagation in specific environments, a sliding correlator wireless channel sounding system is designed by using SDR testbed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=BER" title="BER">BER</a>, <a href="https://publications.waset.org/abstracts/search?q=CMA%20equalizer" title=" CMA equalizer"> CMA equalizer</a>, <a href="https://publications.waset.org/abstracts/search?q=Kurtosis%20equalizer" title=" Kurtosis equalizer"> Kurtosis equalizer</a>, <a href="https://publications.waset.org/abstracts/search?q=GNU%20Radio" title=" GNU Radio"> GNU Radio</a>, <a href="https://publications.waset.org/abstracts/search?q=OFDM%2FOFDMA" title=" OFDM/OFDMA"> OFDM/OFDMA</a>, <a href="https://publications.waset.org/abstracts/search?q=USRP%20N210" title=" USRP N210"> USRP N210</a> </p> <a href="https://publications.waset.org/abstracts/14909/channel-sounding-and-papr-reduction-in-ofdm-for-wimax-using-software-defined-radio" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/14909.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">349</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">774</span> Spectral Clustering for Manufacturing Cell Formation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yessica%20Nataliani">Yessica Nataliani</a>, <a href="https://publications.waset.org/abstracts/search?q=Miin-Shen%20Yang"> Miin-Shen Yang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Cell formation (CF) is an important step in group technology. It is used in designing cellular manufacturing systems using similarities between parts in relation to machines so that it can identify part families and machine groups. There are many CF methods in the literature, but there is less spectral clustering used in CF. In this paper, we propose a spectral clustering algorithm for machine-part CF. Some experimental examples are used to illustrate its efficiency. Overall, the spectral clustering algorithm can be used in CF with a wide variety of machine/part matrices. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=group%20technology" title="group technology">group technology</a>, <a href="https://publications.waset.org/abstracts/search?q=cell%20formation" title=" cell formation"> cell formation</a>, <a href="https://publications.waset.org/abstracts/search?q=spectral%20clustering" title=" spectral clustering"> spectral clustering</a>, <a href="https://publications.waset.org/abstracts/search?q=grouping%20efficiency" title=" grouping efficiency"> grouping efficiency</a> </p> <a href="https://publications.waset.org/abstracts/72294/spectral-clustering-for-manufacturing-cell-formation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/72294.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">407</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">773</span> A Posteriori Analysis of the Spectral Element Discretization of Heat Equation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chor%20Nejmeddine">Chor Nejmeddine</a>, <a href="https://publications.waset.org/abstracts/search?q=Ines%20Ben%20Omrane"> Ines Ben Omrane</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohamed%20Abdelwahed"> Mohamed Abdelwahed</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we present a posteriori analysis of the discretization of the heat equation by spectral element method. We apply Euler's implicit scheme in time and spectral method in space. We propose two families of error indicators, both of which are built from the residual of the equation and we prove that they satisfy some optimal estimates. We present some numerical results which are coherent with the theoretical ones. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=heat%20equation" title="heat equation">heat equation</a>, <a href="https://publications.waset.org/abstracts/search?q=spectral%20elements%20discretization" title=" spectral elements discretization"> spectral elements discretization</a>, <a href="https://publications.waset.org/abstracts/search?q=error%20indicators" title=" error indicators"> error indicators</a>, <a href="https://publications.waset.org/abstracts/search?q=Euler" title=" Euler"> Euler</a> </p> <a href="https://publications.waset.org/abstracts/4041/a-posteriori-analysis-of-the-spectral-element-discretization-of-heat-equation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/4041.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">306</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">772</span> Matrix Valued Difference Equations with Spectral Singularities</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Serifenur%20Cebesoy">Serifenur Cebesoy</a>, <a href="https://publications.waset.org/abstracts/search?q=Yelda%20Aygar"> Yelda Aygar</a>, <a href="https://publications.waset.org/abstracts/search?q=Elgiz%20Bairamov"> Elgiz Bairamov</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this study, we examine some spectral properties of non-selfadjoint matrix-valued difference equations consisting of a polynomial type Jost solution. The aim of this study is to investigate the eigenvalues and spectral singularities of the difference operator L which is expressed by the above-mentioned difference equation. Firstly, thanks to the representation of polynomial type Jost solution of this equation, we obtain asymptotics and some analytical properties. Then, using the uniqueness theorems of analytic functions, we guarantee that the operator L has a finite number of eigenvalues and spectral singularities. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=asymptotics" title="asymptotics">asymptotics</a>, <a href="https://publications.waset.org/abstracts/search?q=continuous%20spectrum" title=" continuous spectrum"> continuous spectrum</a>, <a href="https://publications.waset.org/abstracts/search?q=difference%20equations" title=" difference equations"> difference equations</a>, <a href="https://publications.waset.org/abstracts/search?q=eigenvalues" title=" eigenvalues"> eigenvalues</a>, <a href="https://publications.waset.org/abstracts/search?q=jost%20functions" title=" jost functions"> jost functions</a>, <a href="https://publications.waset.org/abstracts/search?q=spectral%20singularities" title=" spectral singularities"> spectral singularities</a> </p> <a href="https://publications.waset.org/abstracts/32256/matrix-valued-difference-equations-with-spectral-singularities" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/32256.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">446</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">771</span> A Novel Spectral Index for Automatic Shadow Detection in Urban Mapping Based on WorldView-2 Satellite Imagery</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kaveh%20Shahi">Kaveh Shahi</a>, <a href="https://publications.waset.org/abstracts/search?q=Helmi%20Z.%20M.%20Shafri"> Helmi Z. M. Shafri</a>, <a href="https://publications.waset.org/abstracts/search?q=Ebrahim%20Taherzadeh"> Ebrahim Taherzadeh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In remote sensing, shadow causes problems in many applications such as change detection and classification. It is caused by objects which are elevated, thus can directly affect the accuracy of information. For these reasons, it is very important to detect shadows particularly in urban high spatial resolution imagery which created a significant problem. This paper focuses on automatic shadow detection based on a new spectral index for multispectral imagery known as Shadow Detection Index (SDI). The new spectral index was tested on different areas of World-View 2 images and the results demonstrated that the new spectral index has a massive potential to extract shadows effectively and automatically. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=spectral%20index" title="spectral index">spectral index</a>, <a href="https://publications.waset.org/abstracts/search?q=shadow%20detection" title=" shadow detection"> shadow detection</a>, <a href="https://publications.waset.org/abstracts/search?q=remote%20sensing%20images" title=" remote sensing images"> remote sensing images</a>, <a href="https://publications.waset.org/abstracts/search?q=World-View%202" title=" World-View 2"> World-View 2</a> </p> <a href="https://publications.waset.org/abstracts/13500/a-novel-spectral-index-for-automatic-shadow-detection-in-urban-mapping-based-on-worldview-2-satellite-imagery" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/13500.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">538</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">770</span> Vulnerability Assessment of Reinforced Concrete Frames Based on Inelastic Spectral Displacement</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chao%20Xu">Chao Xu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Selecting ground motion intensity measures reasonably is one of the very important issues to affect the input ground motions selecting and the reliability of vulnerability analysis results. In this paper, inelastic spectral displacement is used as an alternative intensity measure to characterize the ground motion damage potential. The inelastic spectral displacement is calculated based modal pushover analysis and inelastic spectral displacement based incremental dynamic analysis is developed. Probability seismic demand analysis of a six story and an eleven story RC frame are carried out through cloud analysis and advanced incremental dynamic analysis. The sufficiency and efficiency of inelastic spectral displacement are investigated by means of regression and residual analysis, and compared with elastic spectral displacement. Vulnerability curves are developed based on inelastic spectral displacement. The study shows that inelastic spectral displacement reflects the impact of different frequency components with periods larger than fundamental period on inelastic structural response. The damage potential of ground motion on structures with fundamental period prolonging caused by structural soften can be caught by inelastic spectral displacement. To be compared with elastic spectral displacement, inelastic spectral displacement is a more sufficient and efficient intensity measure, which reduces the uncertainty of vulnerability analysis and the impact of input ground motion selection on vulnerability analysis result. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=vulnerability" title="vulnerability">vulnerability</a>, <a href="https://publications.waset.org/abstracts/search?q=probability%20seismic%20demand%20analysis" title=" probability seismic demand analysis"> probability seismic demand analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=ground%20motion%20intensity%20measure" title=" ground motion intensity measure"> ground motion intensity measure</a>, <a href="https://publications.waset.org/abstracts/search?q=sufficiency" title=" sufficiency"> sufficiency</a>, <a href="https://publications.waset.org/abstracts/search?q=efficiency" title=" efficiency"> efficiency</a>, <a href="https://publications.waset.org/abstracts/search?q=inelastic%20time%20history%20analysis" title=" inelastic time history analysis"> inelastic time history analysis</a> </p> <a href="https://publications.waset.org/abstracts/48653/vulnerability-assessment-of-reinforced-concrete-frames-based-on-inelastic-spectral-displacement" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/48653.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">354</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">769</span> Investigating the Potential of Spectral Bands in the Detection of Heavy Metals in Soil</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Golayeh%20Yousefi">Golayeh Yousefi</a>, <a href="https://publications.waset.org/abstracts/search?q=Mehdi%20Homaee"> Mehdi Homaee</a>, <a href="https://publications.waset.org/abstracts/search?q=Ali%20Akbar%20Norouzi"> Ali Akbar Norouzi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Ongoing monitoring of soil contamination by heavy metals is critical for ecosystem stability and environmental protection, and food security. The conventional methods of determining these soil contaminants are time-consuming and costly. Spectroscopy in the visible near-infrared (VNIR) - short wave infrared (SWIR) region is a rapid, non-destructive, noninvasive, and cost-effective method for assessment of soil heavy metals concentration by studying the spectral properties of soil constituents. The aim of this study is to derive spectral bands and important ranges that are sensitive to heavy metals and can be used to estimate the concentration of these soil contaminants. In other words, the change in the spectral properties of spectrally active constituents of soil can lead to the accurate identification and estimation of the concentration of these compounds in soil. For this purpose, 325 soil samples were collected, and their spectral reflectance curves were evaluated at a range of 350-2500 nm. After spectral preprocessing operations, the partial least-squares regression (PLSR) model was fitted on spectral data to predict the concentration of Cu and Ni. Based on the results, the spectral range of Cu- sensitive spectra were 480, 580-610, 1370, 1425, 1850, 1920, 2145, and 2200 nm, and Ni-sensitive ranges were 543, 655, 761, 1003, 1271, 1415, 1903, 2199 nm. Finally, the results of this study indicated that the spectral data contains a lot of information that can be applied to identify the soil properties, such as the concentration of heavy metals, with more detail. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=heavy%20metals" title="heavy metals">heavy metals</a>, <a href="https://publications.waset.org/abstracts/search?q=spectroscopy" title=" spectroscopy"> spectroscopy</a>, <a href="https://publications.waset.org/abstracts/search?q=spectral%20bands" title=" spectral bands"> spectral bands</a>, <a href="https://publications.waset.org/abstracts/search?q=PLS%20regression" title=" PLS regression"> PLS regression</a> </p> <a href="https://publications.waset.org/abstracts/160387/investigating-the-potential-of-spectral-bands-in-the-detection-of-heavy-metals-in-soil" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/160387.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">84</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">768</span> Spectral Domain Fast Multipole Method for Solving Integral Equations of One and Two Dimensional Wave Scattering </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Ahmad">Mohammad Ahmad</a>, <a href="https://publications.waset.org/abstracts/search?q=Dayalan%20Kasilingam"> Dayalan Kasilingam</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, a spectral domain implementation of the fast multipole method is presented. It is shown that the aggregation, translation, and disaggregation stages of the fast multipole method (FMM) can be performed using the spectral domain (SD) analysis. The spectral domain fast multipole method (SD-FMM) has the advantage of eliminating the near field/far field classification used in conventional FMM formulation. The study focuses on the application of SD-FMM to one-dimensional (1D) and two-dimensional (2D) electric field integral equation (EFIE). The case of perfectly conducting strip, circular and square cylinders are numerically analyzed and compared with the results from the standard method of moments (MoM). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=electric%20field%20integral%20equation" title="electric field integral equation">electric field integral equation</a>, <a href="https://publications.waset.org/abstracts/search?q=fast%20multipole%20method" title=" fast multipole method"> fast multipole method</a>, <a href="https://publications.waset.org/abstracts/search?q=method%20of%20moments" title=" method of moments"> method of moments</a>, <a href="https://publications.waset.org/abstracts/search?q=wave%20scattering" title=" wave scattering"> wave scattering</a>, <a href="https://publications.waset.org/abstracts/search?q=spectral%20domain" title=" spectral domain"> spectral domain</a> </p> <a href="https://publications.waset.org/abstracts/65787/spectral-domain-fast-multipole-method-for-solving-integral-equations-of-one-and-two-dimensional-wave-scattering" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/65787.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">406</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">767</span> The Properties of Risk-based Approaches to Asset Allocation Using Combined Metrics of Portfolio Volatility and Kurtosis: Theoretical and Empirical Analysis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Maria%20Debora%20Braga">Maria Debora Braga</a>, <a href="https://publications.waset.org/abstracts/search?q=Luigi%20Riso"> Luigi Riso</a>, <a href="https://publications.waset.org/abstracts/search?q=Maria%20Grazia%20Zoia"> Maria Grazia Zoia</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Risk-based approaches to asset allocation are portfolio construction methods that do not rely on the input of expected returns for the asset classes in the investment universe and only use risk information. They include the Minimum Variance Strategy (MV strategy), the traditional (volatility-based) Risk Parity Strategy (SRP strategy), the Most Diversified Portfolio Strategy (MDP strategy) and, for many, the Equally Weighted Strategy (EW strategy). All the mentioned approaches were based on portfolio volatility as a reference risk measure but in 2023, the Kurtosis-based Risk Parity strategy (KRP strategy) and the Minimum Kurtosis strategy (MK strategy) were introduced. Understandably, they used the fourth root of the portfolio-fourth moment as a proxy for portfolio kurtosis to work with a homogeneous function of degree one. This paper contributes mainly theoretically and methodologically to the framework of risk-based asset allocation approaches with two steps forward. First, a new and more flexible objective function considering a linear combination (with positive coefficients that sum to one) of portfolio volatility and portfolio kurtosis is used to alternatively serve a risk minimization goal or a homogeneous risk distribution goal. Hence, the new basic idea consists in extending the achievement of typical risk-based approaches’ goals to a combined risk measure. To give the rationale behind operating with such a risk measure, it is worth remembering that volatility and kurtosis are expressions of uncertainty, to be read as dispersion of returns around the mean and that both preserve adherence to a symmetric framework and consideration for the entire returns distribution as well, but also that they differ from each other in that the former captures the “normal” / “ordinary” dispersion of returns, while the latter is able to catch the huge dispersion. Therefore, the combined risk metric that uses two individual metrics focused on the same phenomena but differently sensitive to its intensity allows the asset manager to express, in the context of an objective function by varying the “relevance coefficient” associated with the individual metrics, alternatively, a wide set of plausible investment goals for the portfolio construction process while serving investors differently concerned with tail risk and traditional risk. Since this is the first study that also implements risk-based approaches using a combined risk measure, it becomes of fundamental importance to investigate the portfolio effects triggered by this innovation. The paper also offers a second contribution. Until the recent advent of the MK strategy and the KRP strategy, efforts to highlight interesting properties of risk-based approaches were inevitably directed towards the traditional MV strategy and SRP strategy. Previous literature established an increasing order in terms of portfolio volatility, starting from the MV strategy, through the SRP strategy, arriving at the EQ strategy and provided the mathematical proof for the “equalization effect” concerning marginal risks when the MV strategy is considered, and concerning risk contributions when the SRP strategy is considered. Regarding the validity of similar conclusions when referring to the MK strategy and KRP strategy, the development of a theoretical demonstration is still pending. This paper fills this gap. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=risk%20parity" title="risk parity">risk parity</a>, <a href="https://publications.waset.org/abstracts/search?q=portfolio%20kurtosis" title=" portfolio kurtosis"> portfolio kurtosis</a>, <a href="https://publications.waset.org/abstracts/search?q=risk%20diversification" title=" risk diversification"> risk diversification</a>, <a href="https://publications.waset.org/abstracts/search?q=asset%20allocation" title=" asset allocation"> asset allocation</a> </p> <a href="https://publications.waset.org/abstracts/171372/the-properties-of-risk-based-approaches-to-asset-allocation-using-combined-metrics-of-portfolio-volatility-and-kurtosis-theoretical-and-empirical-analysis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/171372.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">65</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">766</span> Surface Topography Measurement by Confocal Spectral Interferometry</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=A.%20Manallah">A. Manallah</a>, <a href="https://publications.waset.org/abstracts/search?q=C.%20Meier"> C. Meier</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Confocal spectral interferometry (CSI) is an innovative optical method for determining microtopography of surfaces and thickness of transparent layers, based on the combination of two optical principles: confocal imaging, and spectral interferometry. Confocal optical system images at each instant a single point of the sample. The whole surface is reconstructed by plan scanning. The interference signal generated by mixing two white-light beams is analyzed using a spectrometer. In this work, five ‘rugotests’ of known standard roughnesses are investigated. The topography is then measured and illustrated, and the equivalent roughness is determined and compared with the standard values. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=confocal%20spectral%20interferometry" title="confocal spectral interferometry">confocal spectral interferometry</a>, <a href="https://publications.waset.org/abstracts/search?q=nondestructive%20testing" title=" nondestructive testing"> nondestructive testing</a>, <a href="https://publications.waset.org/abstracts/search?q=optical%20metrology" title=" optical metrology"> optical metrology</a>, <a href="https://publications.waset.org/abstracts/search?q=surface%20topography" title=" surface topography"> surface topography</a>, <a href="https://publications.waset.org/abstracts/search?q=roughness" title=" roughness"> roughness</a> </p> <a href="https://publications.waset.org/abstracts/70452/surface-topography-measurement-by-confocal-spectral-interferometry" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/70452.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">276</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">765</span> Spectral Clustering from the Discrepancy View and Generalized Quasirandomness</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Marianna%20Bolla">Marianna Bolla</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The aim of this paper is to compare spectral, discrepancy, and degree properties of expanding graph sequences. As we can prove equivalences and implications between them and the definition of the generalized (multiclass) quasirandomness of Lovasz–Sos (2008), they can be regarded as generalized quasirandom properties akin to the equivalent quasirandom properties of the seminal Chung-Graham-Wilson paper (1989) in the one-class scenario. Since these properties are valid for deterministic graph sequences, irrespective of stochastic models, the partial implications also justify for low-dimensional embedding of large-scale graphs and for discrepancy minimizing spectral clustering. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=generalized%20random%20graphs" title="generalized random graphs">generalized random graphs</a>, <a href="https://publications.waset.org/abstracts/search?q=multiway%20discrepancy" title=" multiway discrepancy"> multiway discrepancy</a>, <a href="https://publications.waset.org/abstracts/search?q=normalized%20modularity%20spectra" title=" normalized modularity spectra"> normalized modularity spectra</a>, <a href="https://publications.waset.org/abstracts/search?q=spectral%20clustering" title=" spectral clustering"> spectral clustering</a> </p> <a href="https://publications.waset.org/abstracts/95238/spectral-clustering-from-the-discrepancy-view-and-generalized-quasirandomness" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/95238.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">197</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">764</span> A Time-Varying and Non-Stationary Convolution Spectral Mixture Kernel for Gaussian Process</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kai%20Chen">Kai Chen</a>, <a href="https://publications.waset.org/abstracts/search?q=Shuguang%20Cui"> Shuguang Cui</a>, <a href="https://publications.waset.org/abstracts/search?q=Feng%20Yin"> Feng Yin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Gaussian process (GP) with spectral mixture (SM) kernel demonstrates flexible non-parametric Bayesian learning ability in modeling unknown function. In this work a novel time-varying and non-stationary convolution spectral mixture (TN-CSM) kernel with a significant enhancing of interpretability by using process convolution is introduced. A way decomposing the SM component into an auto-convolution of base SM component and parameterizing it to be input dependent is outlined. Smoothly, performing a convolution between two base SM component yields a novel structure of non-stationary SM component with much better generalized expression and interpretation. The TN-CSM perfectly allows compatibility with the stationary SM kernel in terms of kernel form and spectral base ignored and confused by previous non-stationary kernels. On synthetic and real-world datatsets, experiments show the time-varying characteristics of hyper-parameters in TN-CSM and compare the learning performance of TN-CSM with popular and representative non-stationary GP. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Gaussian%20process" title="Gaussian process">Gaussian process</a>, <a href="https://publications.waset.org/abstracts/search?q=spectral%20mixture" title=" spectral mixture"> spectral mixture</a>, <a href="https://publications.waset.org/abstracts/search?q=non-stationary" title=" non-stationary"> non-stationary</a>, <a href="https://publications.waset.org/abstracts/search?q=convolution" title=" convolution"> convolution</a> </p> <a href="https://publications.waset.org/abstracts/131675/a-time-varying-and-non-stationary-convolution-spectral-mixture-kernel-for-gaussian-process" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/131675.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">196</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">763</span> Spectral Assessing of Topographic Effects on Seismic Behavior of Trapezoidal Hill</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20Amelsakhi">M. Amelsakhi</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Sohrabi-Bidar"> A. Sohrabi-Bidar</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Shareghi"> A. Shareghi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> One of the most important issues about the structural damages caused by earthquake is the evaluating of the spectral response of the site on which the construction is built. This fact has demonstrated during many earlier earthquakes and many researchers’ reports have concerned with it. According to these reports, features of the site materials and geometry of the ground surface are considered the main factors. This study concentrates on the specific form of topographies like hills. Assessing of spectral responses of different points on the hills and beside demonstrates considerable differences between 1D and 2D methods of geotechnical analyses. A general trend of amplifications on the top of the hills and de-amplifications near the toe of the hills has been appeared within the acceleration, velocity and displacement response spectrums of horizontal motion. Evaluating of spectral responses of different sizes of the hills revealed that as much as the hill-size enlarges differences between spectral responses of 1D and 2D analyses transfers to longer range of periods and becomes wider. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=topography%20effect" title="topography effect">topography effect</a>, <a href="https://publications.waset.org/abstracts/search?q=amplification%20ratio" title=" amplification ratio"> amplification ratio</a>, <a href="https://publications.waset.org/abstracts/search?q=response%20spectrum" title=" response spectrum"> response spectrum</a>, <a href="https://publications.waset.org/abstracts/search?q=earth%20resources%20engineering" title=" earth resources engineering"> earth resources engineering</a> </p> <a href="https://publications.waset.org/abstracts/7842/spectral-assessing-of-topographic-effects-on-seismic-behavior-of-trapezoidal-hill" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/7842.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">239</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">762</span> Dual-Channel Multi-Band Spectral Subtraction Algorithm Dedicated to a Bilateral Cochlear Implant</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fathi%20Kallel">Fathi Kallel</a>, <a href="https://publications.waset.org/abstracts/search?q=Ahmed%20Ben%20Hamida"> Ahmed Ben Hamida</a>, <a href="https://publications.waset.org/abstracts/search?q=Christian%20Berger-Vachon"> Christian Berger-Vachon</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, a Speech Enhancement Algorithm based on Multi-Band Spectral Subtraction (MBSS) principle is evaluated for Bilateral Cochlear Implant (BCI) users. Specifically, dual-channel noise power spectral estimation algorithm using Power Spectral Densities (PSD) and Cross Power Spectral Densities (CPSD) of the observed signals is studied. The enhanced speech signal is obtained using Dual-Channel Multi-Band Spectral Subtraction ‘DC-MBSS’ algorithm. For performance evaluation, objective speech assessment test relying on Perceptual Evaluation of Speech Quality (PESQ) score is performed to fix the optimal number of frequency bands needed in DC-MBSS algorithm. In order to evaluate the speech intelligibility, subjective listening tests are assessed with 3 deafened BCI patients. Experimental results obtained using French Lafon database corrupted by an additive babble noise at different Signal-to-Noise Ratios (SNR) showed that DC-MBSS algorithm improves speech understanding for single and multiple interfering noise sources. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=speech%20enhancement" title="speech enhancement">speech enhancement</a>, <a href="https://publications.waset.org/abstracts/search?q=spectral%20substracion" title=" spectral substracion"> spectral substracion</a>, <a href="https://publications.waset.org/abstracts/search?q=noise%20estimation" title=" noise estimation"> noise estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=cochlear%20impalnt" title=" cochlear impalnt"> cochlear impalnt</a> </p> <a href="https://publications.waset.org/abstracts/18785/dual-channel-multi-band-spectral-subtraction-algorithm-dedicated-to-a-bilateral-cochlear-implant" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/18785.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">549</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">761</span> Outdoor Anomaly Detection with a Spectroscopic Line Detector</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=O.%20J.%20G.%20Somsen">O. J. G. Somsen</a> </p> <p class="card-text"><strong>Abstract:</strong></p> One of the tasks of optical surveillance is to detect anomalies in large amounts of image data. However, if the size of the anomaly is very small, limited information is available to distinguish it from the surrounding environment. Spectral detection provides a useful source of additional information and may help to detect anomalies with a size of a few pixels or less. Unfortunately, spectral cameras are expensive because of the difficulty of separating two spatial in addition to one spectral dimension. We investigate the possibility of modifying a simpler spectral line detector for outdoor detection. This may be especially useful if the area of interest forms a line, such as the horizon. We use a monochrome CCD that also enables detection into the near infrared. A simple camera is attached to the setup to determine which part of the environment is spectrally imaged. Our preliminary results indicate that sensitive detection of very small targets is indeed possible. Spectra could be taken from the various targets by averaging columns in the line image. By imaging a set of lines of various width we found narrow lines that could not be seen in the color image but remained visible in the spectral line image. A simultaneous analysis of the entire spectra can produce better results than visual inspection of the line spectral image. We are presently developing calibration targets for spatial and spectral focusing and alignment with the spatial camera. This will present improved results and more use in outdoor application <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=anomaly%20detection" title="anomaly detection">anomaly detection</a>, <a href="https://publications.waset.org/abstracts/search?q=spectroscopic%20line%20imaging" title=" spectroscopic line imaging"> spectroscopic line imaging</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20analysis" title=" image analysis"> image analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=outdoor%20detection" title=" outdoor detection "> outdoor detection </a> </p> <a href="https://publications.waset.org/abstracts/34329/outdoor-anomaly-detection-with-a-spectroscopic-line-detector" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/34329.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">481</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">760</span> Approach Based on Fuzzy C-Means for Band Selection in Hyperspectral Images</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Diego%20Saqui">Diego Saqui</a>, <a href="https://publications.waset.org/abstracts/search?q=Jos%C3%A9%20H.%20Saito"> José H. Saito</a>, <a href="https://publications.waset.org/abstracts/search?q=Jos%C3%A9%20R.%20Campos"> José R. Campos</a>, <a href="https://publications.waset.org/abstracts/search?q=L%C3%BAcio%20A.%20de%20C.%20Jorge"> Lúcio A. de C. Jorge</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Hyperspectral images and remote sensing are important for many applications. A problem in the use of these images is the high volume of data to be processed, stored and transferred. Dimensionality reduction techniques can be used to reduce the volume of data. In this paper, an approach to band selection based on clustering algorithms is presented. This approach allows to reduce the volume of data. The proposed structure is based on Fuzzy C-Means (or K-Means) and NWHFC algorithms. New attributes in relation to other studies in the literature, such as kurtosis and low correlation, are also considered. A comparison of the results of the approach using the Fuzzy C-Means and K-Means with different attributes is performed. The use of both algorithms show similar good results but, particularly when used attributes variance and kurtosis in the clustering process, however applicable in hyperspectral images. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=band%20selection" title="band selection">band selection</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20c-means" title=" fuzzy c-means"> fuzzy c-means</a>, <a href="https://publications.waset.org/abstracts/search?q=k-means" title=" k-means"> k-means</a>, <a href="https://publications.waset.org/abstracts/search?q=hyperspectral%20image" title=" hyperspectral image"> hyperspectral image</a> </p> <a href="https://publications.waset.org/abstracts/50614/approach-based-on-fuzzy-c-means-for-band-selection-in-hyperspectral-images" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/50614.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">407</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">759</span> A Hybrid Image Fusion Model for Generating High Spatial-Temporal-Spectral Resolution Data Using OLI-MODIS-Hyperion Satellite Imagery</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yongquan%20Zhao">Yongquan Zhao</a>, <a href="https://publications.waset.org/abstracts/search?q=Bo%20Huang"> Bo Huang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Spatial, Temporal, and Spectral Resolution (STSR) are three key characteristics of Earth observation satellite sensors; however, any single satellite sensor cannot provide Earth observations with high STSR simultaneously because of the hardware technology limitations of satellite sensors. On the other hand, a conflicting circumstance is that the demand for high STSR has been growing with the remote sensing application development. Although image fusion technology provides a feasible means to overcome the limitations of the current Earth observation data, the current fusion technologies cannot enhance all STSR simultaneously and provide high enough resolution improvement level. This study proposes a Hybrid Spatial-Temporal-Spectral image Fusion Model (HSTSFM) to generate synthetic satellite data with high STSR simultaneously, which blends the high spatial resolution from the panchromatic image of Landsat-8 Operational Land Imager (OLI), the high temporal resolution from the multi-spectral image of Moderate Resolution Imaging Spectroradiometer (MODIS), and the high spectral resolution from the hyper-spectral image of Hyperion to produce high STSR images. The proposed HSTSFM contains three fusion modules: (1) spatial-spectral image fusion; (2) spatial-temporal image fusion; (3) temporal-spectral image fusion. A set of test data with both phenological and land cover type changes in Beijing suburb area, China is adopted to demonstrate the performance of the proposed method. The experimental results indicate that HSTSFM can produce fused image that has good spatial and spectral fidelity to the reference image, which means it has the potential to generate synthetic data to support the studies that require high STSR satellite imagery. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=hybrid%20spatial-temporal-spectral%20fusion" title="hybrid spatial-temporal-spectral fusion">hybrid spatial-temporal-spectral fusion</a>, <a href="https://publications.waset.org/abstracts/search?q=high%20resolution%20synthetic%20imagery" title=" high resolution synthetic imagery"> high resolution synthetic imagery</a>, <a href="https://publications.waset.org/abstracts/search?q=least%20square%20regression" title=" least square regression"> least square regression</a>, <a href="https://publications.waset.org/abstracts/search?q=sparse%20representation" title=" sparse representation"> sparse representation</a>, <a href="https://publications.waset.org/abstracts/search?q=spectral%20transformation" title=" spectral transformation"> spectral transformation</a> </p> <a href="https://publications.waset.org/abstracts/74667/a-hybrid-image-fusion-model-for-generating-high-spatial-temporal-spectral-resolution-data-using-oli-modis-hyperion-satellite-imagery" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/74667.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">235</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">758</span> The Effectiveness of Energy Index Technique in Bearing Condition Monitoring</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Faisal%20Alshammari">Faisal Alshammari</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdulmajid%20Addali"> Abdulmajid Addali</a>, <a href="https://publications.waset.org/abstracts/search?q=Mosab%20Alrashed"> Mosab Alrashed</a>, <a href="https://publications.waset.org/abstracts/search?q=Taihiret%20Alhashan"> Taihiret Alhashan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The application of acoustic emission techniques is gaining popularity, as it can monitor the condition of gears and bearings and detect early symptoms of a defect in the form of pitting, wear, and flaking of surfaces. Early detection of these defects is essential as it helps to avoid major failures and the associated catastrophic consequences. Signal processing techniques are required for early defect detection – in this article, a time domain technique called the Energy Index (EI) is used. This article presents an investigation into the Energy Index’s effectiveness to detect early-stage defect initiation and deterioration, and compares it with the common r.m.s. index, Kurtosis, and the Kolmogorov-Smirnov statistical test. It is concluded that EI is a more effective technique for monitoring defect initiation and development than other statistical parameters. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=acoustic%20emission" title="acoustic emission">acoustic emission</a>, <a href="https://publications.waset.org/abstracts/search?q=signal%20processing" title=" signal processing"> signal processing</a>, <a href="https://publications.waset.org/abstracts/search?q=kurtosis" title=" kurtosis"> kurtosis</a>, <a href="https://publications.waset.org/abstracts/search?q=Kolmogorov-Smirnov%20test" title=" Kolmogorov-Smirnov test"> Kolmogorov-Smirnov test</a> </p> <a href="https://publications.waset.org/abstracts/62143/the-effectiveness-of-energy-index-technique-in-bearing-condition-monitoring" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/62143.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">366</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">757</span> Multi-Temporal Urban Land Cover Mapping Using Spectral Indices</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mst%20Ilme%20Faridatul">Mst Ilme Faridatul</a>, <a href="https://publications.waset.org/abstracts/search?q=Bo%20Wu"> Bo Wu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Multi-temporal urban land cover mapping is of paramount importance for monitoring urban sprawl and managing the ecological environment. For diversified urban activities, it is challenging to map land covers in a complex urban environment. Spectral indices have proved to be effective for mapping urban land covers. To improve multi-temporal urban land cover classification and mapping, we evaluate the performance of three spectral indices, e.g. modified normalized difference bare-land index (MNDBI), tasseled cap water and vegetation index (TCWVI) and shadow index (ShDI). The MNDBI is developed to evaluate its performance of enhancing urban impervious areas by separating bare lands. A tasseled cap index, TCWVI is developed to evaluate its competence to detect vegetation and water simultaneously. The ShDI is developed to maximize the spectral difference between shadows of skyscrapers and water and enhance water detection. First, this paper presents a comparative analysis of three spectral indices using Landsat Enhanced Thematic Mapper (ETM), Thematic Mapper (TM) and Operational Land Imager (OLI) data. Second, optimized thresholds of the spectral indices are imputed to classify land covers, and finally, their performance of enhancing multi-temporal urban land cover mapping is assessed. The results indicate that the spectral indices are competent to enhance multi-temporal urban land cover mapping and achieves an overall classification accuracy of 93-96%. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=land%20cover" title="land cover">land cover</a>, <a href="https://publications.waset.org/abstracts/search?q=mapping" title=" mapping"> mapping</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-temporal" title=" multi-temporal"> multi-temporal</a>, <a href="https://publications.waset.org/abstracts/search?q=spectral%20indices" title=" spectral indices"> spectral indices</a> </p> <a href="https://publications.waset.org/abstracts/103491/multi-temporal-urban-land-cover-mapping-using-spectral-indices" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/103491.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">153</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">756</span> Discrete Estimation of Spectral Density for Alpha Stable Signals Observed with an Additive Error</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=R.%20Sabre">R. Sabre</a>, <a href="https://publications.waset.org/abstracts/search?q=W.%20Horrigue"> W. Horrigue</a>, <a href="https://publications.waset.org/abstracts/search?q=J.%20C.%20Simon"> J. C. Simon</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper is interested in two difficulties encountered in practice when observing a continuous time process. The first is that we cannot observe a process over a time interval; we only take discrete observations. The second is the process frequently observed with a constant additive error. It is important to give an estimator of the spectral density of such a process taking into account the additive observation error and the choice of the discrete observation times. In this work, we propose an estimator based on the spectral smoothing of the periodogram by the polynomial Jackson kernel reducing the additive error. In order to solve the aliasing phenomenon, this estimator is constructed from observations taken at well-chosen times so as to reduce the estimator to the field where the spectral density is not zero. We show that the proposed estimator is asymptotically unbiased and consistent. Thus we obtain an estimate solving the two difficulties concerning the choice of the instants of observations of a continuous time process and the observations affected by a constant error. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=spectral%20density" title="spectral density">spectral density</a>, <a href="https://publications.waset.org/abstracts/search?q=stable%20processes" title=" stable processes"> stable processes</a>, <a href="https://publications.waset.org/abstracts/search?q=aliasing" title=" aliasing"> aliasing</a>, <a href="https://publications.waset.org/abstracts/search?q=periodogram" title=" periodogram"> periodogram</a> </p> <a href="https://publications.waset.org/abstracts/118023/discrete-estimation-of-spectral-density-for-alpha-stable-signals-observed-with-an-additive-error" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/118023.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">138</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">755</span> Spectral Analysis Applied to Variables of Oil Wells Profiling</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Suzana%20Leit%C3%A3o%20Russo">Suzana Leitão Russo</a>, <a href="https://publications.waset.org/abstracts/search?q=Mayara%20Laysa%20de%20Oliveira%20Silva"> Mayara Laysa de Oliveira Silva</a>, <a href="https://publications.waset.org/abstracts/search?q=Jos%C3%A9%20Augusto%20Andrade%20Filho"> José Augusto Andrade Filho</a>, <a href="https://publications.waset.org/abstracts/search?q=Vitor%20Hugo%20Simon"> Vitor Hugo Simon</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Currently, seismic methods and prospecting methods are commonly applied in the oil industry and, according to the information reported every day; oil is a source of non-renewable energy. It is easier to understand why the ownership of areas of oil extraction is coveted by many nations. It is necessary to think about ways that will enable the maximization of oil production. The technique of spectral analysis can be used to analyze the behavior of the variables already defined in oil well the profile. The main objective is to verify the series dependence of variables, and to model the variables using the frequency domain to observe the model residuals. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=oil" title="oil">oil</a>, <a href="https://publications.waset.org/abstracts/search?q=well" title=" well"> well</a>, <a href="https://publications.waset.org/abstracts/search?q=spectral%20analysis" title=" spectral analysis"> spectral analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=oil%20extraction" title=" oil extraction"> oil extraction</a> </p> <a href="https://publications.waset.org/abstracts/19979/spectral-analysis-applied-to-variables-of-oil-wells-profiling" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/19979.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">534</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">754</span> Features of Normative and Pathological Realizations of Sibilant Sounds for Computer-Aided Pronunciation Evaluation in Children</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Zuzanna%20Miodonska">Zuzanna Miodonska</a>, <a href="https://publications.waset.org/abstracts/search?q=Michal%20Krecichwost"> Michal Krecichwost</a>, <a href="https://publications.waset.org/abstracts/search?q=Pawel%20Badura"> Pawel Badura</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Sigmatism (lisping) is a speech disorder in which sibilant consonants are mispronounced. The diagnosis of this phenomenon is usually based on the auditory assessment. However, the progress in speech analysis techniques creates a possibility of developing computer-aided sigmatism diagnosis tools. The aim of the study is to statistically verify whether specific acoustic features of sibilant sounds may be related to pronunciation correctness. Such knowledge can be of great importance while implementing classifiers and designing novel tools for automatic sibilants pronunciation evaluation. The study covers analysis of various speech signal measures, including features proposed in the literature for the description of normative sibilants realization. Amplitudes and frequencies of three fricative formants (FF) are extracted based on local spectral maxima of the friction noise. Skewness, kurtosis, four normalized spectral moments (SM) and 13 mel-frequency cepstral coefficients (MFCC) with their 1st and 2nd derivatives (13 Delta and 13 Delta-Delta MFCC) are included in the analysis as well. The resulting feature vector contains 51 measures. The experiments are performed on the speech corpus containing words with selected sibilant sounds (/ʃ, ʒ/) pronounced by 60 preschool children with proper pronunciation or with natural pathologies. In total, 224 /ʃ/ segments and 191 /ʒ/ segments are employed in the study. The Mann-Whitney U test is employed for the analysis of stigmatism and normative pronunciation. Statistically, significant differences are obtained in most of the proposed features in children divided into these two groups at p < 0.05. All spectral moments and fricative formants appear to be distinctive between pathology and proper pronunciation. These metrics describe the friction noise characteristic for sibilants, which makes them particularly promising for the use in sibilants evaluation tools. Correspondences found between phoneme feature values and an expert evaluation of the pronunciation correctness encourage to involve speech analysis tools in diagnosis and therapy of sigmatism. Proposed feature extraction methods could be used in a computer-assisted stigmatism diagnosis or therapy systems. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=computer-aided%20pronunciation%20evaluation" title="computer-aided pronunciation evaluation">computer-aided pronunciation evaluation</a>, <a href="https://publications.waset.org/abstracts/search?q=sigmatism%20diagnosis" title=" sigmatism diagnosis"> sigmatism diagnosis</a>, <a href="https://publications.waset.org/abstracts/search?q=speech%20signal%20analysis" title=" speech signal analysis"> speech signal analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=statistical%20verification" title=" statistical verification"> statistical verification</a> </p> <a href="https://publications.waset.org/abstracts/65569/features-of-normative-and-pathological-realizations-of-sibilant-sounds-for-computer-aided-pronunciation-evaluation-in-children" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/65569.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">301</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">753</span> Comparative Analysis of Spectral Estimation Methods for Brain-Computer Interfaces</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rafik%20Djemili">Rafik Djemili</a>, <a href="https://publications.waset.org/abstracts/search?q=Hocine%20Bourouba"> Hocine Bourouba</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20C.%20Amara%20Korba"> M. C. Amara Korba</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we present a method in order to classify EEG signals for Brain-Computer Interfaces (BCI). EEG signals are first processed by means of spectral estimation methods to derive reliable features before classification step. Spectral estimation methods used are standard periodogram and the periodogram calculated by the Welch method; both methods are compared with Logarithm of Band Power (logBP) features. In the method proposed, we apply Linear Discriminant Analysis (LDA) followed by Support Vector Machine (SVM). Classification accuracy reached could be as high as 85%, which proves the effectiveness of classification of EEG signals based BCI using spectral methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=brain-computer%20interface" title="brain-computer interface">brain-computer interface</a>, <a href="https://publications.waset.org/abstracts/search?q=motor%20imagery" title=" motor imagery"> motor imagery</a>, <a href="https://publications.waset.org/abstracts/search?q=electroencephalogram" title=" electroencephalogram"> electroencephalogram</a>, <a href="https://publications.waset.org/abstracts/search?q=linear%20discriminant%20analysis" title=" linear discriminant analysis"> linear discriminant analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=support%20vector%20machine" title=" support vector machine"> support vector machine</a> </p> <a href="https://publications.waset.org/abstracts/6971/comparative-analysis-of-spectral-estimation-methods-for-brain-computer-interfaces" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/6971.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">499</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">752</span> Spectral Broadening in an InGaAsP Optical Waveguide with χ(3) Nonlinearity Including Two Photon Absorption</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Keigo%20Matsuura">Keigo Matsuura</a>, <a href="https://publications.waset.org/abstracts/search?q=Isao%20Tomita"> Isao Tomita</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We have studied a method to widen the spectrum of optical pulses that pass through an InGaAsP waveguide for application to broadband optical communication. In particular, we have investigated the competitive effect between spectral broadening arising from nonlinear refraction (optical Kerr effect) and shrinking due to two photon absorption in the InGaAsP waveguide with chi^(3) nonlinearity. The shrunk spectrum recovers broadening by the enhancement effect of the nonlinear refractive index near the bandgap of InGaAsP with a bandgap wavelength of 1490 nm. The broadened spectral width at around 1525 nm (196.7 THz) becomes 10.7 times wider than that at around 1560 nm (192.3 THz) without the enhancement effect, where amplified optical pulses with a pulse width of 2 ps and a peak power of 10 W propagate through a 1-cm-long InGaAsP waveguide with a cross-section of 4 um^2. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=InGaAsP%20waveguide" title="InGaAsP waveguide">InGaAsP waveguide</a>, <a href="https://publications.waset.org/abstracts/search?q=Chi%5E%283%29%20nonlinearity" title=" Chi^(3) nonlinearity"> Chi^(3) nonlinearity</a>, <a href="https://publications.waset.org/abstracts/search?q=spectral%20broadening" title=" spectral broadening"> spectral broadening</a>, <a href="https://publications.waset.org/abstracts/search?q=photon%20absorption" title=" photon absorption "> photon absorption </a> </p> <a href="https://publications.waset.org/abstracts/13656/spectral-broadening-in-an-ingaasp-optical-waveguide-with-kh3-nonlinearity-including-two-photon-absorption" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/13656.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">634</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=spectral%20kurtosis&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=spectral%20kurtosis&page=3">3</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=spectral%20kurtosis&page=4">4</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=spectral%20kurtosis&page=5">5</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=spectral%20kurtosis&page=6">6</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=spectral%20kurtosis&page=7">7</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=spectral%20kurtosis&page=8">8</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=spectral%20kurtosis&page=9">9</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=spectral%20kurtosis&page=10">10</a></li> <li class="page-item disabled"><span class="page-link">...</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=spectral%20kurtosis&page=26">26</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=spectral%20kurtosis&page=27">27</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=spectral%20kurtosis&page=2" rel="next">&rsaquo;</a></li> </ul> </div> </main> <footer> <div id="infolinks" class="pt-3 pb-2"> <div class="container"> <div style="background-color:#f5f5f5;" class="p-3"> <div class="row"> <div class="col-md-2"> <ul class="list-unstyled"> About <li><a href="https://waset.org/page/support">About Us</a></li> <li><a href="https://waset.org/page/support#legal-information">Legal</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/WASET-16th-foundational-anniversary.pdf">WASET celebrates its 16th foundational anniversary</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Account <li><a href="https://waset.org/profile">My Account</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Explore <li><a href="https://waset.org/disciplines">Disciplines</a></li> <li><a href="https://waset.org/conferences">Conferences</a></li> <li><a href="https://waset.org/conference-programs">Conference Program</a></li> <li><a href="https://waset.org/committees">Committees</a></li> <li><a href="https://publications.waset.org">Publications</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Research <li><a href="https://publications.waset.org/abstracts">Abstracts</a></li> <li><a href="https://publications.waset.org">Periodicals</a></li> <li><a href="https://publications.waset.org/archive">Archive</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Open Science <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Science-Philosophy.pdf">Open Science Philosophy</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Science-Award.pdf">Open Science Award</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Society-Open-Science-and-Open-Innovation.pdf">Open Innovation</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Postdoctoral-Fellowship-Award.pdf">Postdoctoral Fellowship Award</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Scholarly-Research-Review.pdf">Scholarly Research Review</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Support <li><a href="https://waset.org/page/support">Support</a></li> <li><a href="https://waset.org/profile/messages/create">Contact Us</a></li> <li><a href="https://waset.org/profile/messages/create">Report Abuse</a></li> </ul> </div> </div> </div> </div> </div> <div class="container text-center"> <hr style="margin-top:0;margin-bottom:.3rem;"> <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank" class="text-muted small">Creative Commons Attribution 4.0 International License</a> <div id="copy" class="mt-2">© 2024 World Academy of Science, Engineering and Technology</div> </div> </footer> <a href="javascript:" id="return-to-top"><i class="fas fa-arrow-up"></i></a> <div class="modal" id="modal-template"> <div class="modal-dialog"> <div class="modal-content"> <div class="row m-0 mt-1"> <div class="col-md-12"> <button type="button" class="close" data-dismiss="modal" aria-label="Close"><span aria-hidden="true">×</span></button> </div> </div> <div class="modal-body"></div> </div> </div> </div> <script src="https://cdn.waset.org/static/plugins/jquery-3.3.1.min.js"></script> <script src="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/js/bootstrap.bundle.min.js"></script> <script src="https://cdn.waset.org/static/js/site.js?v=150220211556"></script> <script> jQuery(document).ready(function() { /*jQuery.get("https://publications.waset.org/xhr/user-menu", function (response) { jQuery('#mainNavMenu').append(response); });*/ jQuery.get({ url: "https://publications.waset.org/xhr/user-menu", cache: false }).then(function(response){ jQuery('#mainNavMenu').append(response); }); }); </script> </body> </html>