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combination</title> <meta name="description" content="Search results for: spectral combination"> <meta name="keywords" content="spectral combination"> <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 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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 combination"> <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> 3801</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: spectral combination</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3801</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">396</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">3800</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">3799</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">453</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">3798</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">3797</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">408</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">3796</span> Non-Local Simultaneous Sparse Unmixing for Hyperspectral Data</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fanqiang%20Kong">Fanqiang Kong</a>, <a href="https://publications.waset.org/abstracts/search?q=Chending%20Bian"> Chending Bian</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Sparse unmixing is a promising approach in a semisupervised fashion by assuming that the observed pixels of a hyperspectral image can be expressed in the form of linear combination of only a few pure spectral signatures (end members) in an available spectral library. However, the sparse unmixing problem still remains a great challenge at finding the optimal subset of endmembers for the observed data from a large standard spectral library, without considering the spatial information. Under such circumstances, a sparse unmixing algorithm termed as non-local simultaneous sparse unmixing (NLSSU) is presented. In NLSSU, the non-local simultaneous sparse representation method for endmember selection of sparse unmixing, is used to finding the optimal subset of endmembers for the similar image patch set in the hyperspectral image. And then, the non-local means method, as a regularizer for abundance estimation of sparse unmixing, is used to exploit the abundance image non-local self-similarity. Experimental results on both simulated and real data demonstrate that NLSSU outperforms the other algorithms, with a better spectral unmixing accuracy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=hyperspectral%20unmixing" title="hyperspectral unmixing">hyperspectral unmixing</a>, <a href="https://publications.waset.org/abstracts/search?q=simultaneous%20sparse%20representation" title=" simultaneous sparse representation"> simultaneous sparse representation</a>, <a href="https://publications.waset.org/abstracts/search?q=sparse%20regression" title=" sparse regression"> sparse regression</a>, <a href="https://publications.waset.org/abstracts/search?q=non-local%20means" title=" non-local means"> non-local means</a> </p> <a href="https://publications.waset.org/abstracts/71689/non-local-simultaneous-sparse-unmixing-for-hyperspectral-data" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/71689.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">246</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">3795</span> Downscaling Grace Gravity Models Using Spectral Combination Techniques for Terrestrial Water Storage and Groundwater Storage Estimation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Farzam%20Fatolazadeh">Farzam Fatolazadeh</a>, <a href="https://publications.waset.org/abstracts/search?q=Kalifa%20Goita"> Kalifa Goita</a>, <a href="https://publications.waset.org/abstracts/search?q=Mehdi%20Eshagh"> Mehdi Eshagh</a>, <a href="https://publications.waset.org/abstracts/search?q=Shusen%20Wang"> Shusen Wang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Gravity Recovery and Climate Experiment (GRACE) is a satellite mission with twin satellites for the precise determination of spatial and temporal variations in the Earth’s gravity field. The products of this mission are monthly global gravity models containing the spherical harmonic coefficients and their errors. These GRACE models can be used for estimating terrestrial water storage (TWS) variations across the globe at large scales, thereby offering an opportunity for surface and groundwater storage (GWS) assessments. Yet, the ability of GRACE to monitor changes at smaller scales is too limited for local water management authorities. This is largely due to the low spatial and temporal resolutions of its models (~200,000 km2 and one month, respectively). High-resolution GRACE data products would substantially enrich the information that is needed by local-scale decision-makers while offering the data for the regions that lack adequate in situ monitoring networks, including northern parts of Canada. Such products could eventually be obtained through downscaling. In this study, we extended the spectral combination theory to simultaneously downscale spatiotemporally the 3o spatial coarse resolution of GRACE to 0.25o degrees resolution and monthly coarse resolution to daily resolution. This method combines the monthly gravity field solution of GRACE and daily hydrological model products in the form of both low and high-frequency signals to produce high spatiotemporal resolution TWSA and GWSA products. The main contribution and originality of this study are to comprehensively and simultaneously consider GRACE and hydrological variables and their uncertainties to form the estimator in the spectral domain. Therefore, it is predicted that we reach downscale products with an acceptable accuracy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=GRACE%20satellite" title="GRACE satellite">GRACE satellite</a>, <a href="https://publications.waset.org/abstracts/search?q=groundwater%20storage" title=" groundwater storage"> groundwater storage</a>, <a href="https://publications.waset.org/abstracts/search?q=spectral%20combination" title=" spectral combination"> spectral combination</a>, <a href="https://publications.waset.org/abstracts/search?q=terrestrial%20water%20storage" title=" terrestrial water storage"> terrestrial water storage</a> </p> <a href="https://publications.waset.org/abstracts/166919/downscaling-grace-gravity-models-using-spectral-combination-techniques-for-terrestrial-water-storage-and-groundwater-storage-estimation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/166919.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">83</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">3794</span> Tree Species Classification Using Effective Features of Polarimetric SAR and Hyperspectral Images</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Milad%20Vahidi">Milad Vahidi</a>, <a href="https://publications.waset.org/abstracts/search?q=Mahmod%20R.%20Sahebi"> Mahmod R. Sahebi</a>, <a href="https://publications.waset.org/abstracts/search?q=Mehrnoosh%20Omati"> Mehrnoosh Omati</a>, <a href="https://publications.waset.org/abstracts/search?q=Reza%20Mohammadi"> Reza Mohammadi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Forest management organizations need information to perform their work effectively. Remote sensing is an effective method to acquire information from the Earth. Two datasets of remote sensing images were used to classify forested regions. Firstly, all of extractable features from hyperspectral and PolSAR images were extracted. The optical features were spectral indexes related to the chemical, water contents, structural indexes, effective bands and absorption features. Also, PolSAR features were the original data, target decomposition components, and SAR discriminators features. Secondly, the particle swarm optimization (PSO) and the genetic algorithms (GA) were applied to select optimization features. Furthermore, the support vector machine (SVM) classifier was used to classify the image. The results showed that the combination of PSO and SVM had higher overall accuracy than the other cases. This combination provided overall accuracy about 90.56%. The effective features were the spectral index, the bands in shortwave infrared (SWIR) and the visible ranges and certain PolSAR features. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=hyperspectral" title="hyperspectral">hyperspectral</a>, <a href="https://publications.waset.org/abstracts/search?q=PolSAR" title=" PolSAR"> PolSAR</a>, <a href="https://publications.waset.org/abstracts/search?q=feature%20selection" title=" feature selection"> feature selection</a>, <a href="https://publications.waset.org/abstracts/search?q=SVM" title=" SVM"> SVM</a> </p> <a href="https://publications.waset.org/abstracts/95461/tree-species-classification-using-effective-features-of-polarimetric-sar-and-hyperspectral-images" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/95461.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">416</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">3793</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">3792</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">447</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">3791</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">3790</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">3789</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">3788</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">3787</span> Spectral Efficiency Improvement in 5G Systems by Polyphase Decomposition</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Wilson%20Enr%C3%ADquez">Wilson Enríquez</a>, <a href="https://publications.waset.org/abstracts/search?q=Daniel%20Cardenas"> Daniel Cardenas</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This article proposes a filter bank format combined with the mathematical tool called polyphase decomposition and the discrete Fourier transform (DFT) with the purpose of improving the performance of the fifth-generation communication systems (5G). We started with a review of the literature and the study of the filter bank theory and its combination with DFT in order to improve the performance of wireless communications since it reduces the computational complexity of these communication systems. With the proposed technique, several experiments were carried out in order to evaluate the structures in 5G systems. Finally, the results are presented in graphical form in terms of bit error rate against the ratio bit energy/noise power spectral density (BER vs. Eb / No). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=multi-carrier%20system%20%285G%29" title="multi-carrier system (5G)">multi-carrier system (5G)</a>, <a href="https://publications.waset.org/abstracts/search?q=filter%20bank" title=" filter bank"> filter bank</a>, <a href="https://publications.waset.org/abstracts/search?q=polyphase%20decomposition" title=" polyphase decomposition"> polyphase decomposition</a>, <a href="https://publications.waset.org/abstracts/search?q=FIR%20equalizer" title=" FIR equalizer"> FIR equalizer</a> </p> <a href="https://publications.waset.org/abstracts/142477/spectral-efficiency-improvement-in-5g-systems-by-polyphase-decomposition" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/142477.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">203</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">3786</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">3785</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">3784</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">3783</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">3782</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">3781</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">3780</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">3779</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">3778</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">535</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">3777</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">3776</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> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3775</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">3774</span> Discrimination Between Bacillus and Alicyclobacillus Isolates in Apple Juice by Fourier Transform Infrared Spectroscopy and Multivariate Analysis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Murada%20Alholy">Murada Alholy</a>, <a href="https://publications.waset.org/abstracts/search?q=Mengshi%20Lin"> Mengshi Lin</a>, <a href="https://publications.waset.org/abstracts/search?q=Omar%20Alhaj"> Omar Alhaj</a>, <a href="https://publications.waset.org/abstracts/search?q=Mahmoud%20Abugoush"> Mahmoud Abugoush</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Alicyclobacillus is a causative agent of spoilage in pasteurized and heat-treated apple juice products. Differentiating between this genus and the closely related Bacillus is crucially important. In this study, Fourier transform infrared spectroscopy (FT-IR) was used to identify and discriminate between four Alicyclobacillus strains and four Bacillus isolates inoculated individually into apple juice. Loading plots over the range of 1350 and 1700 cm-1 reflected the most distinctive biochemical features of Bacillus and Alicyclobacillus. Multivariate statistical methods (e.g. principal component analysis (PCA) and soft independent modeling of class analogy (SIMCA)) were used to analyze the spectral data. Distinctive separation of spectral samples was observed. This study demonstrates that FT-IR spectroscopy in combination with multivariate analysis could serve as a rapid and effective tool for fruit juice industry to differentiate between Bacillus and Alicyclobacillus and to distinguish between species belonging to these two genera. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=alicyclobacillus" title="alicyclobacillus">alicyclobacillus</a>, <a href="https://publications.waset.org/abstracts/search?q=bacillus" title=" bacillus"> bacillus</a>, <a href="https://publications.waset.org/abstracts/search?q=FT-IR" title=" FT-IR"> FT-IR</a>, <a href="https://publications.waset.org/abstracts/search?q=spectroscopy" title=" spectroscopy"> spectroscopy</a>, <a href="https://publications.waset.org/abstracts/search?q=PCA" title=" PCA"> PCA</a> </p> <a href="https://publications.waset.org/abstracts/29542/discrimination-between-bacillus-and-alicyclobacillus-isolates-in-apple-juice-by-fourier-transform-infrared-spectroscopy-and-multivariate-analysis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/29542.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">489</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">3773</span> The Use of Remotely Sensed Data to Extract Wetlands Area in the Cultural Park of Ahaggar, South of Algeria</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Y.%20Fekir">Y. Fekir</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20Mederbal"> K. Mederbal</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20A.%20Hammadouche"> M. A. Hammadouche</a>, <a href="https://publications.waset.org/abstracts/search?q=D.%20Anteur"> D. Anteur</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The cultural park of the Ahaggar, occupying a large area of Algeria, is characterized by a rich wetlands area to be preserved and managed both in time and space. The management of a large area, by its complexity, needs large amounts of data, which for the most part, are spatially localized (DEM, satellite images and socio-economic information...), where the use of conventional and traditional methods is quite difficult. The remote sensing, by its efficiency in environmental applications, became an indispensable solution for this kind of studies. Remote sensing imaging data have been very useful in the last decade in very interesting applications. They can aid in several domains such as the detection and identification of diverse wetland surface targets, topographical details, and geological features... In this work, we try to extract automatically wetlands area using multispectral remotely sensed data on-board the Earth Observing 1 (EO-1) and Landsat satellite. Both are high-resolution multispectral imager with a 30 m resolution. The instrument images an interesting surface area. We have used images acquired over the several area of interesting in the National Park of Ahaggar in the south of Algeria. An Extraction Algorithm is applied on the several spectral index obtained from combination of different spectral bands to extract wetlands fraction occupation of land use. The obtained results show an accuracy to distinguish wetlands area from the other lad use themes using a fine exploitation on spectral index. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=multispectral%20data" title="multispectral data">multispectral data</a>, <a href="https://publications.waset.org/abstracts/search?q=EO1" title=" EO1"> EO1</a>, <a href="https://publications.waset.org/abstracts/search?q=landsat" title=" landsat"> landsat</a>, <a href="https://publications.waset.org/abstracts/search?q=wetlands" title=" wetlands"> wetlands</a>, <a href="https://publications.waset.org/abstracts/search?q=Ahaggar" title=" Ahaggar"> Ahaggar</a>, <a href="https://publications.waset.org/abstracts/search?q=Algeria" title=" Algeria"> Algeria</a> </p> <a href="https://publications.waset.org/abstracts/17160/the-use-of-remotely-sensed-data-to-extract-wetlands-area-in-the-cultural-park-of-ahaggar-south-of-algeria" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/17160.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">377</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">3772</span> A Spectral Decomposition Method for Ordinary Differential Equation Systems with Constant or Linear Right Hand Sides</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=R.%20B.%20Ogunrinde">R. B. Ogunrinde</a>, <a href="https://publications.waset.org/abstracts/search?q=C.%20C.%20Jibunoh"> C. C. Jibunoh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, a spectral decomposition method is developed for the direct integration of stiff and nonstiff homogeneous linear (ODE) systems with linear, constant, or zero right hand sides (RHSs). The method does not require iteration but obtains solutions at any random points of t, by direct evaluation, in the interval of integration. All the numerical solutions obtained for the class of systems coincide with the exact theoretical solutions. In particular, solutions of homogeneous linear systems, i.e. with zero RHS, conform to the exact analytical solutions of the systems in terms of t. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=spectral%20decomposition" title="spectral decomposition">spectral decomposition</a>, <a href="https://publications.waset.org/abstracts/search?q=linear%20RHS" title=" linear RHS"> linear RHS</a>, <a href="https://publications.waset.org/abstracts/search?q=homogeneous%20linear%20systems" title=" homogeneous linear systems"> homogeneous linear systems</a>, <a href="https://publications.waset.org/abstracts/search?q=eigenvalues%20of%20the%20Jacobian" title=" eigenvalues of the Jacobian"> eigenvalues of the Jacobian</a> </p> <a href="https://publications.waset.org/abstracts/54215/a-spectral-decomposition-method-for-ordinary-differential-equation-systems-with-constant-or-linear-right-hand-sides" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/54215.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">330</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%20combination&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=spectral%20combination&page=3">3</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=spectral%20combination&page=4">4</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=spectral%20combination&page=5">5</a></li> <li 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