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Search results for: spectral analysis
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text-center" style="font-size:1.6rem;">Search results for: spectral analysis</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">28230</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">28229</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">28228</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">353</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">28227</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">28226</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">28225</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">28224</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">28223</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">28222</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">405</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">28221</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">28220</span> Spectral Analysis of Heart Rate Variability for Normal and Preeclamptic Pregnants</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abdulnasir%20Hossen">Abdulnasir Hossen</a>, <a href="https://publications.waset.org/abstracts/search?q=Alaa%20Barhoum"> Alaa Barhoum</a>, <a href="https://publications.waset.org/abstracts/search?q=Deepali%20Jaju"> Deepali Jaju</a>, <a href="https://publications.waset.org/abstracts/search?q=V.%20Gowri"> V. Gowri</a>, <a href="https://publications.waset.org/abstracts/search?q=L.%20Al-Kharusi"> L. Al-Kharusi</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Hassan"> M. Hassan</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20Al-Hashmi"> K. Al-Hashmi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Preeclampsia is a pregnancy disorder associated with increase in blood pressure and excess amount of protein in the urine. HRV analysis has been used by many researchers to identify preeclamptic pregnancy from normal pregnancy. A study in this regard to identify preeclamptic pregnancy in Oman from normal pregnant was conducted on 40 subjects (20 patients and 20 normal). The subjects were collected from two hospitals in Oman. A Fast Fourier transform (FFT) spectral analysis has shown that patients with preeclamptic pregnancy have a reduction in the power of the HF band and an increase in the power of the LF band of HRV compared with subjects with normal pregnancy. The accuracy of identification obtained was 80%. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=preelampsia" title="preelampsia">preelampsia</a>, <a href="https://publications.waset.org/abstracts/search?q=pregnancy%20hypertension" title=" pregnancy hypertension"> pregnancy hypertension</a>, <a href="https://publications.waset.org/abstracts/search?q=normal%20pregnant" title=" normal pregnant"> normal pregnant</a>, <a href="https://publications.waset.org/abstracts/search?q=FFT" title=" FFT"> FFT</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=HRV" title=" HRV"> HRV</a> </p> <a href="https://publications.waset.org/abstracts/17998/spectral-analysis-of-heart-rate-variability-for-normal-and-preeclamptic-pregnants" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/17998.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">556</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">28219</span> Spectral Coherence Analysis between Grinding Interaction Forces and the Relative Motion of the Workpiece and the Cutting Tool</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abdulhamit%20Donder">Abdulhamit Donder</a>, <a href="https://publications.waset.org/abstracts/search?q=Erhan%20Ilhan%20Konukseven"> Erhan Ilhan Konukseven</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Grinding operation is performed in order to obtain desired surfaces precisely in machining process. The needed relative motion between the cutting tool and the workpiece is generally created either by the movement of the cutting tool or by the movement of the workpiece or by the movement of both of them as in our case. For all these cases, the coherence level between the movements and the interaction forces is a key influential parameter for efficient grinding. Therefore, in this work, spectral coherence analysis has been performed to investigate the coherence level between grinding interaction forces and the movement of the workpiece on our robotic-grinding experimental setup in METU Mechatronics Laboratory. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=coherence%20analysis" title="coherence analysis">coherence analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=correlation" title=" correlation"> correlation</a>, <a href="https://publications.waset.org/abstracts/search?q=FFT" title=" FFT"> FFT</a>, <a href="https://publications.waset.org/abstracts/search?q=grinding" title=" grinding"> grinding</a>, <a href="https://publications.waset.org/abstracts/search?q=hanning%20window" title=" hanning window"> hanning window</a>, <a href="https://publications.waset.org/abstracts/search?q=machining" title=" machining"> machining</a>, <a href="https://publications.waset.org/abstracts/search?q=Piezo%20actuator" title=" Piezo actuator"> Piezo actuator</a>, <a href="https://publications.waset.org/abstracts/search?q=reverse%20arrangements%20test" title=" reverse arrangements test"> reverse arrangements test</a>, <a href="https://publications.waset.org/abstracts/search?q=spectral%20analysis" title=" spectral analysis"> spectral analysis</a> </p> <a href="https://publications.waset.org/abstracts/51057/spectral-coherence-analysis-between-grinding-interaction-forces-and-the-relative-motion-of-the-workpiece-and-the-cutting-tool" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/51057.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">405</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">28218</span> Quantitative Assessment of Road Infrastructure Health Using High-Resolution Remote Sensing Data</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Wang%20Zhaoming">Wang Zhaoming</a>, <a href="https://publications.waset.org/abstracts/search?q=Shao%20Shegang"> Shao Shegang</a>, <a href="https://publications.waset.org/abstracts/search?q=Chen%20Xiaorong"> Chen Xiaorong</a>, <a href="https://publications.waset.org/abstracts/search?q=Qi%20Yanan"> Qi Yanan</a>, <a href="https://publications.waset.org/abstracts/search?q=Tian%20Lei"> Tian Lei</a>, <a href="https://publications.waset.org/abstracts/search?q=Wang%20Jian"> Wang Jian</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study conducts a comparative analysis of the spectral curves of asphalt pavements at various aging stages to improve road information extraction from high-resolution remote sensing imagery. By examining the distinguishing capabilities and spectral characteristics, the research aims to establish a pavement information extraction methodology based on China's high-resolution satellite images. The process begins by analyzing the spectral features of asphalt pavements to construct a spectral assessment model suitable for evaluating pavement health. This model is then tested at a national highway traffic testing site in China, validating its effectiveness in distinguishing different pavement aging levels. The study's findings demonstrate that the proposed model can accurately assess road health, offering a valuable tool for road maintenance planning and infrastructure management. <p class="card-text"><strong>Keywords:</strong> <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=asphalt%20pavement%20aging" title=" asphalt pavement aging"> asphalt pavement aging</a>, <a href="https://publications.waset.org/abstracts/search?q=high-resolution%20remote%20sensing" title=" high-resolution remote sensing"> high-resolution remote sensing</a>, <a href="https://publications.waset.org/abstracts/search?q=pavement%20health%20assessment" title=" pavement health assessment"> pavement health assessment</a> </p> <a href="https://publications.waset.org/abstracts/189326/quantitative-assessment-of-road-infrastructure-health-using-high-resolution-remote-sensing-data" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/189326.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">21</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">28217</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">28216</span> Pd(II) Complex with 4-Bromo-2,6-Bis-Hydroxymethyl-Phenol and Nikotinamid: Synthesis and Spectral Analysis </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=%C3%96zlen%20Altun">Özlen Altun</a>, <a href="https://publications.waset.org/abstracts/search?q=Zeliha%20Yoru%C3%A7"> Zeliha Yoruç</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In the present study, the reactions involving 4-Bromo-2,6-bis-hydroxymethyl-phenol (BBHMP) and nikotinamide (NA) in the presence Pd (II) ion were investigated. Optimum conditions for the reactions were established as pH 7 and λ = 450 nm. According to absorbance measurements, the mole ratio of BBHMP : NA : Pd2+ was found as 1 : 2 : 2. As a result of physico-chemical, spectrophotometric and thermal analysis results, the reactions of BBHMP and NA with Pd (II) is complexation reactions and one molecule BBHMP and two molecules of NA react with two molecules of metal (II) ion. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=4-Bromo-2" title="4-Bromo-2">4-Bromo-2</a>, <a href="https://publications.waset.org/abstracts/search?q=6-bis-hydroxymethyl-phenol" title="6-bis-hydroxymethyl-phenol">6-bis-hydroxymethyl-phenol</a>, <a href="https://publications.waset.org/abstracts/search?q=nicotinamide" title=" nicotinamide"> nicotinamide</a>, <a href="https://publications.waset.org/abstracts/search?q=Pd%28II%29" title=" Pd(II)"> Pd(II)</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=synthesis" title=" synthesis"> synthesis</a> </p> <a href="https://publications.waset.org/abstracts/82499/pdii-complex-with-4-bromo-26-bis-hydroxymethyl-phenol-and-nikotinamid-synthesis-and-spectral-analysis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/82499.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">165</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">28215</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">28214</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">28213</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">28212</span> Spectral Re-Evaluation of the Magnetic Basement Depth over Yola Arm of Upper Benue Trough Nigeria Using Aeromagnetic Data</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Emberga%20Terhemb%20Opara%20Alexander">Emberga Terhemb Opara Alexander</a>, <a href="https://publications.waset.org/abstracts/search?q=Selemo%20Alexader"> Selemo Alexader</a>, <a href="https://publications.waset.org/abstracts/search?q=Onyekwuru%20Samuel"> Onyekwuru Samuel</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The aeromagnetic data have been used to re-evaluate parts of the Upper Benue Trough Nigeria using spectral analysis technique in order to appraise the mineral accumulation potential of the area. The regional field was separated with a first order polynomial using polyfit program. The residual data was subdivided into 24 spectral blocks using OASIS MONTAJ software program. Two prominent magnetic depth source layers were identified. The deeper source depth values obtained ranges from 1.56km to 2.92km with an average depth of 2.37km as the magnetic basement depth while for the shallower sources, the depth values ranges from -1.17km to 0.98km with an average depth of 0.55km. The shallow depth source is attributed to the volcanic rocks that intruded the sedimentary formation and this could possibly be responsible for the mineralization found in parts of the study area. <p class="card-text"><strong>Keywords:</strong> <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=Upper%20Benue%20Trough" title=" Upper Benue Trough"> Upper Benue Trough</a>, <a href="https://publications.waset.org/abstracts/search?q=magnetic%20basement%20depth" title=" magnetic basement depth"> magnetic basement depth</a>, <a href="https://publications.waset.org/abstracts/search?q=aeromagnetic" title=" aeromagnetic"> aeromagnetic</a> </p> <a href="https://publications.waset.org/abstracts/27913/spectral-re-evaluation-of-the-magnetic-basement-depth-over-yola-arm-of-upper-benue-trough-nigeria-using-aeromagnetic-data" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/27913.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">28211</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">28210</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">28209</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">28208</span> Electronic Spectral Function of Double Quantum Dots–Superconductors Nanoscopic Junction</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rajendra%20Kumar">Rajendra Kumar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We study the Electronic spectral density of a double coupled quantum dots sandwich between superconducting leads, where one of the superconducting leads (QD1) are connected with left superconductor lead and (QD1) also connected right superconductor lead. (QD1) and (QD2) are coupling to each other. The electronic spectral density through a quantum dots between superconducting leads having s-wave symmetry of the superconducting order parameter. Such junction is called superconducting –quantum dot (S-QD-S) junction. For this purpose, we have considered a renormalized Anderson model that includes the double coupled of the superconducting leads with the quantum dots level and an attractive BCS-type effective interaction in superconducting leads. We employed the Green’s function technique to obtain superconducting order parameter with the BCS framework and Ambegaoker-Baratoff formalism to analyze the electronic spectral density through such (S-QD-S) junction. It has been pointed out that electronic spectral density through such a junction is dominated by the attractive the paring interaction in the leads, energy of the level on the dot with respect to Fermi energy and also on the coupling parameter of the two in an essential way. On the basis of numerical analysis we have compared the theoretical results of electronic spectral density with the recent transport existing theoretical analysis. QDs is the charging energy that may give rise to effects based on the interplay of Coulomb repulsion and superconducting correlations. It is, therefore, an interesting question to ask how the discrete level spectrum and the charging energy affect the DC and AC Josephson transport between two superconductors coupled via a QD. In the absence of a bias voltage, a finite DC current can be sustained in such an S-QD-S by the DC Josephson effect. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=quantum%20dots" title="quantum dots">quantum dots</a>, <a href="https://publications.waset.org/abstracts/search?q=S-QD-S%20junction" title=" S-QD-S junction"> S-QD-S junction</a>, <a href="https://publications.waset.org/abstracts/search?q=BCS%20superconductors" title=" BCS superconductors"> BCS superconductors</a>, <a href="https://publications.waset.org/abstracts/search?q=Anderson%20model" title=" Anderson model"> Anderson model</a> </p> <a href="https://publications.waset.org/abstracts/3977/electronic-spectral-function-of-double-quantum-dots-superconductors-nanoscopic-junction" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/3977.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">374</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">28207</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">28206</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">28205</span> A Combined Feature Extraction and Thresholding Technique for Silence Removal in Percussive Sounds </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=B.%20Kishore%20Kumar">B. Kishore Kumar</a>, <a href="https://publications.waset.org/abstracts/search?q=Pogula%20Rakesh"> Pogula Rakesh</a>, <a href="https://publications.waset.org/abstracts/search?q=T.%20Kishore%20Kumar"> T. Kishore Kumar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The music analysis is a part of the audio content analysis used to analyze the music by using the different features of audio signal. In music analysis, the first step is to divide the music signal to different sections based on the feature profiles of the music signal. In this paper, we present a music segmentation technique that will effectively segmentize the signal and thresholding technique to remove silence from the percussive sounds produced by percussive instruments, which uses two features of music, namely signal energy and spectral centroid. The proposed method impose thresholds on both the features which will vary depends on the music signal. Depends on the threshold, silence part is removed and the segmentation is done. The effectiveness of the proposed method is analyzed using MATLAB. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=percussive%20sounds" title="percussive sounds">percussive sounds</a>, <a href="https://publications.waset.org/abstracts/search?q=spectral%20centroid" title=" spectral centroid"> spectral centroid</a>, <a href="https://publications.waset.org/abstracts/search?q=spectral%20energy" title=" spectral energy"> spectral energy</a>, <a href="https://publications.waset.org/abstracts/search?q=silence%20removal" title=" silence removal"> silence removal</a>, <a href="https://publications.waset.org/abstracts/search?q=feature%20extraction" title=" feature extraction"> feature extraction</a> </p> <a href="https://publications.waset.org/abstracts/25510/a-combined-feature-extraction-and-thresholding-technique-for-silence-removal-in-percussive-sounds" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/25510.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">593</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">28204</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">28203</span> Optimized Real Ground Motion Scaling for Vulnerability Assessment of Building Considering the Spectral Uncertainty and Shape</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chen%20Bo">Chen Bo</a>, <a href="https://publications.waset.org/abstracts/search?q=Wen%20Zengping"> Wen Zengping</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Based on the results of previous studies, we focus on the research of real ground motion selection and scaling method for structural performance-based seismic evaluation using nonlinear dynamic analysis. The input of earthquake ground motion should be determined appropriately to make them compatible with the site-specific hazard level considered. Thus, an optimized selection and scaling method are established including the use of not only Monte Carlo simulation method to create the stochastic simulation spectrum considering the multivariate lognormal distribution of target spectrum, but also a spectral shape parameter. Its applications in structural fragility analysis are demonstrated through case studies. Compared to the previous scheme with no consideration of the uncertainty of target spectrum, the method shown here can make sure that the selected records are in good agreement with the median value, standard deviation and spectral correction of the target spectrum, and greatly reveal the uncertainty feature of site-specific hazard level. Meanwhile, it can help improve computational efficiency and matching accuracy. Given the important infection of target spectrum’s uncertainty on structural seismic fragility analysis, this work can provide the reasonable and reliable basis for structural seismic evaluation under scenario earthquake environment. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ground%20motion%20selection" title="ground motion selection">ground motion selection</a>, <a href="https://publications.waset.org/abstracts/search?q=scaling%20method" title=" scaling method"> scaling method</a>, <a href="https://publications.waset.org/abstracts/search?q=seismic%20fragility%20analysis" title=" seismic fragility analysis"> seismic fragility analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=spectral%20shape" title=" spectral shape"> spectral shape</a> </p> <a href="https://publications.waset.org/abstracts/47118/optimized-real-ground-motion-scaling-for-vulnerability-assessment-of-building-considering-the-spectral-uncertainty-and-shape" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/47118.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">292</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">28202</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">28201</span> An Adaptive Dimensionality Reduction Approach for Hyperspectral Imagery Semantic Interpretation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Akrem%20Sellami">Akrem Sellami</a>, <a href="https://publications.waset.org/abstracts/search?q=Imed%20Riadh%20Farah"> Imed Riadh Farah</a>, <a href="https://publications.waset.org/abstracts/search?q=Basel%20Solaiman"> Basel Solaiman</a> </p> <p class="card-text"><strong>Abstract:</strong></p> With the development of HyperSpectral Imagery (HSI) technology, the spectral resolution of HSI became denser, which resulted in large number of spectral bands, high correlation between neighboring, and high data redundancy. However, the semantic interpretation is a challenging task for HSI analysis due to the high dimensionality and the high correlation of the different spectral bands. In fact, this work presents a dimensionality reduction approach that allows to overcome the different issues improving the semantic interpretation of HSI. Therefore, in order to preserve the spatial information, the Tensor Locality Preserving Projection (TLPP) has been applied to transform the original HSI. In the second step, knowledge has been extracted based on the adjacency graph to describe the different pixels. Based on the transformation matrix using TLPP, a weighted matrix has been constructed to rank the different spectral bands based on their contribution score. Thus, the relevant bands have been adaptively selected based on the weighted matrix. The performance of the presented approach has been validated by implementing several experiments, and the obtained results demonstrate the efficiency of this approach compared to various existing dimensionality reduction techniques. Also, according to the experimental results, we can conclude that this approach can adaptively select the relevant spectral improving the semantic interpretation of HSI. <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=dimensionality%20reduction" title=" dimensionality reduction"> dimensionality reduction</a>, <a href="https://publications.waset.org/abstracts/search?q=feature%20extraction" title=" feature extraction"> feature extraction</a>, <a href="https://publications.waset.org/abstracts/search?q=hyperspectral%20imagery" title=" hyperspectral imagery"> hyperspectral imagery</a>, <a href="https://publications.waset.org/abstracts/search?q=semantic%20interpretation" title=" semantic interpretation"> semantic interpretation</a> </p> <a href="https://publications.waset.org/abstracts/55370/an-adaptive-dimensionality-reduction-approach-for-hyperspectral-imagery-semantic-interpretation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/55370.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> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">‹</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%20analysis&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=spectral%20analysis&page=3">3</a></li> <li class="page-item"><a class="page-link" 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