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filtering</title> <meta name="description" content="Search results for: energy filtering"> <meta name="keywords" content="energy filtering"> <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="energy filtering"> <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> 8704</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: energy filtering</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8704</span> Additive White Gaussian Noise Filtering from ECG by Wiener Filter and Median Filter: A Comparative Study</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hossein%20Javidnia">Hossein Javidnia</a>, <a href="https://publications.waset.org/abstracts/search?q=Salehe%20Taheri"> Salehe Taheri</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Electrocardiogram (ECG) is the recording of the heart’s electrical potential versus time. ECG signals are often contaminated with noise such as baseline wander and muscle noise. As these signals have been widely used in clinical studies to detect heart diseases, it is essential to filter these noises. In this paper we compare performance of Wiener Filtering and Median Filtering methods to filter Additive White Gaussian (AWG) noise with the determined signal to noise ratio (SNR) ranging from 3 to 5 dB applied to long-term ECG recordings samples. Root mean square error (RMSE) and coefficient of determination (R2) between the filtered ECG and original ECG was used as the filter performance indicator. Experimental results show that Wiener filter has better noise filtering performance than Median filter. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ECG%20noise%20filtering" title="ECG noise filtering">ECG noise filtering</a>, <a href="https://publications.waset.org/abstracts/search?q=Wiener%20filtering" title=" Wiener filtering"> Wiener filtering</a>, <a href="https://publications.waset.org/abstracts/search?q=median%20filtering" title=" median filtering"> median filtering</a>, <a href="https://publications.waset.org/abstracts/search?q=Gaussian%20noise" title=" Gaussian noise"> Gaussian noise</a>, <a href="https://publications.waset.org/abstracts/search?q=filtering%20performance" title=" filtering performance"> filtering performance</a> </p> <a href="https://publications.waset.org/abstracts/9623/additive-white-gaussian-noise-filtering-from-ecg-by-wiener-filter-and-median-filter-a-comparative-study" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/9623.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">529</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">8703</span> Image Enhancement Algorithm of Photoacoustic Tomography Using Active Contour Filtering</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Prasannakumar%20Palaniappan">Prasannakumar Palaniappan</a>, <a href="https://publications.waset.org/abstracts/search?q=Dong%20Ho%20Shin"> Dong Ho Shin</a>, <a href="https://publications.waset.org/abstracts/search?q=Chul%20Gyu%20Song"> Chul Gyu Song</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The photoacoustic images are obtained from a custom developed linear array photoacoustic tomography system. The biological specimens are imitated by conducting phantom tests in order to retrieve a fully functional photoacoustic image. The acquired image undergoes the active region based contour filtering to remove the noise and accurately segment the object area for further processing. The universal back projection method is used as the image reconstruction algorithm. The active contour filtering is analyzed by evaluating the signal to noise ratio and comparing it with the other filtering methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=contour%20filtering" title="contour filtering">contour filtering</a>, <a href="https://publications.waset.org/abstracts/search?q=linear%20array" title=" linear array"> linear array</a>, <a href="https://publications.waset.org/abstracts/search?q=photoacoustic%20tomography" title=" photoacoustic tomography"> photoacoustic tomography</a>, <a href="https://publications.waset.org/abstracts/search?q=universal%20back%20projection" title=" universal back projection"> universal back projection</a> </p> <a href="https://publications.waset.org/abstracts/40626/image-enhancement-algorithm-of-photoacoustic-tomography-using-active-contour-filtering" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/40626.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">400</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">8702</span> Real-Time Visualization Using GPU-Accelerated Filtering of LiDAR Data</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sa%C5%A1o%20Pe%C4%8Dnik">Sašo Pečnik</a>, <a href="https://publications.waset.org/abstracts/search?q=Borut%20%C5%BDalik"> Borut Žalik</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents a real-time visualization technique and filtering of classified LiDAR point clouds. The visualization is capable of displaying filtered information organized in layers by the classification attribute saved within LiDAR data sets. We explain the used data structure and data management, which enables real-time presentation of layered LiDAR data. Real-time visualization is achieved with LOD optimization based on the distance from the observer without loss of quality. The filtering process is done in two steps and is entirely executed on the GPU and implemented using programmable shaders. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=filtering" title="filtering">filtering</a>, <a href="https://publications.waset.org/abstracts/search?q=graphics" title=" graphics"> graphics</a>, <a href="https://publications.waset.org/abstracts/search?q=level-of-details" title=" level-of-details"> level-of-details</a>, <a href="https://publications.waset.org/abstracts/search?q=LiDAR" title=" LiDAR"> LiDAR</a>, <a href="https://publications.waset.org/abstracts/search?q=real-time%20visualization" title=" real-time visualization"> real-time visualization</a> </p> <a href="https://publications.waset.org/abstracts/16857/real-time-visualization-using-gpu-accelerated-filtering-of-lidar-data" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/16857.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">308</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">8701</span> 3D Guided Image Filtering to Improve Quality of Short-Time Binned Dynamic PET Images Using MRI Images</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tabassum%20Husain">Tabassum Husain</a>, <a href="https://publications.waset.org/abstracts/search?q=Shen%20Peng%20Li"> Shen Peng Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhaolin%20Chen"> Zhaolin Chen</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper evaluates the usability of 3D Guided Image Filtering to enhance the quality of short-time binned dynamic PET images by using MRI images. Guided image filtering is an edge-preserving filter proposed to enhance 2D images. The 3D filter is applied on 1 and 5-minute binned images. The results are compared with 15-minute binned images and the Gaussian filtering. The guided image filter enhances the quality of dynamic PET images while also preserving important information of the voxels. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=dynamic%20PET%20images" title="dynamic PET images">dynamic PET images</a>, <a href="https://publications.waset.org/abstracts/search?q=guided%20image%20filter" title=" guided image filter"> guided image filter</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20enhancement" title=" image enhancement"> image enhancement</a>, <a href="https://publications.waset.org/abstracts/search?q=information%20preservation%20filtering" title=" information preservation filtering"> information preservation filtering</a> </p> <a href="https://publications.waset.org/abstracts/152864/3d-guided-image-filtering-to-improve-quality-of-short-time-binned-dynamic-pet-images-using-mri-images" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/152864.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">132</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">8700</span> The Evaluation of the Performance of Different Filtering Approaches in Tracking Problem and the Effect of Noise Variance </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Javad%20Mollakazemi">Mohammad Javad Mollakazemi</a>, <a href="https://publications.waset.org/abstracts/search?q=Farhad%20Asadi"> Farhad Asadi</a>, <a href="https://publications.waset.org/abstracts/search?q=Aref%20Ghafouri"> Aref Ghafouri</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Performance of different filtering approaches depends on modeling of dynamical system and algorithm structure. For modeling and smoothing the data the evaluation of posterior distribution in different filtering approach should be chosen carefully. In this paper different filtering approaches like filter KALMAN, EKF, UKF, EKS and smoother RTS is simulated in some trajectory tracking of path and accuracy and limitation of these approaches are explained. Then probability of model with different filters is compered and finally the effect of the noise variance to estimation is described with simulations results. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Gaussian%20approximation" title="Gaussian approximation">Gaussian approximation</a>, <a href="https://publications.waset.org/abstracts/search?q=Kalman%20smoother" title=" Kalman smoother"> Kalman smoother</a>, <a href="https://publications.waset.org/abstracts/search?q=parameter%20estimation" title=" parameter estimation"> parameter estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=noise%20variance" title=" noise variance"> noise variance</a> </p> <a href="https://publications.waset.org/abstracts/14553/the-evaluation-of-the-performance-of-different-filtering-approaches-in-tracking-problem-and-the-effect-of-noise-variance" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/14553.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">439</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">8699</span> Application of Artificial Immune Systems Combined with Collaborative Filtering in Movie Recommendation System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Pei-Chann%20Chang">Pei-Chann Chang</a>, <a href="https://publications.waset.org/abstracts/search?q=Jhen-Fu%20Liao"> Jhen-Fu Liao</a>, <a href="https://publications.waset.org/abstracts/search?q=Chin-Hung%20Teng"> Chin-Hung Teng</a>, <a href="https://publications.waset.org/abstracts/search?q=Meng-Hui%20Chen"> Meng-Hui Chen</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This research combines artificial immune system with user and item based collaborative filtering to create an efficient and accurate recommendation system. By applying the characteristic of antibodies and antigens in the artificial immune system and using Pearson correlation coefficient as the affinity threshold to cluster the data, our collaborative filtering can effectively find useful users and items for rating prediction. This research uses MovieLens dataset as our testing target to evaluate the effectiveness of the algorithm developed in this study. The experimental results show that the algorithm can effectively and accurately predict the movie ratings. Compared to some state of the art collaborative filtering systems, our system outperforms them in terms of the mean absolute error on the MovieLens dataset. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=artificial%20immune%20system" title="artificial immune system">artificial immune system</a>, <a href="https://publications.waset.org/abstracts/search?q=collaborative%20filtering" title=" collaborative filtering"> collaborative filtering</a>, <a href="https://publications.waset.org/abstracts/search?q=recommendation%20system" title=" recommendation system"> recommendation system</a>, <a href="https://publications.waset.org/abstracts/search?q=similarity" title=" similarity"> similarity</a> </p> <a href="https://publications.waset.org/abstracts/5057/application-of-artificial-immune-systems-combined-with-collaborative-filtering-in-movie-recommendation-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/5057.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">536</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">8698</span> Speed up Vector Median Filtering by Quasi Euclidean Norm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Vinai%20K.%20Singh">Vinai K. Singh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> For reducing impulsive noise without degrading image contours, median filtering is a powerful tool. In multiband images as for example colour images or vector fields obtained by optic flow computation, a vector median filter can be used. Vector median filters are defined on the basis of a suitable distance, the best performing distance being the Euclidean. Euclidean distance is evaluated by using the Euclidean norms which is quite demanding from the point of view of computation given that a square root is required. In this paper an optimal piece-wise linear approximation of the Euclidean norm is presented which is applied to vector median filtering. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=euclidean%20norm" title="euclidean norm">euclidean norm</a>, <a href="https://publications.waset.org/abstracts/search?q=quasi%20euclidean%20norm" title=" quasi euclidean norm"> quasi euclidean norm</a>, <a href="https://publications.waset.org/abstracts/search?q=vector%20median%20filtering" title=" vector median filtering"> vector median filtering</a>, <a href="https://publications.waset.org/abstracts/search?q=applied%20mathematics" title=" applied mathematics"> applied mathematics</a> </p> <a href="https://publications.waset.org/abstracts/21942/speed-up-vector-median-filtering-by-quasi-euclidean-norm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/21942.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">474</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">8697</span> Building and Tree Detection Using Multiscale Matched Filtering</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abdullah%20H.%20%C3%96zcan">Abdullah H. Özcan</a>, <a href="https://publications.waset.org/abstracts/search?q=Dilara%20Hisar"> Dilara Hisar</a>, <a href="https://publications.waset.org/abstracts/search?q=Yetkin%20Sayar"> Yetkin Sayar</a>, <a href="https://publications.waset.org/abstracts/search?q=Cem%20%C3%9Cnsalan"> Cem Ünsalan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this study, an automated building and tree detection method is proposed using DSM data and true orthophoto image. A multiscale matched filtering is used on DSM data. Therefore, first watershed transform is applied. Then, Otsu’s thresholding method is used as an adaptive threshold to segment each watershed region. Detected objects are masked with NDVI to separate buildings and trees. The proposed method is able to detect buildings and trees without entering any elevation threshold. We tested our method on ISPRS semantic labeling dataset and obtained promising results. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=building%20detection" title="building detection">building detection</a>, <a href="https://publications.waset.org/abstracts/search?q=local%20maximum%20filtering" title=" local maximum filtering"> local maximum filtering</a>, <a href="https://publications.waset.org/abstracts/search?q=matched%20filtering" title=" matched filtering"> matched filtering</a>, <a href="https://publications.waset.org/abstracts/search?q=multiscale" title=" multiscale"> multiscale</a> </p> <a href="https://publications.waset.org/abstracts/59277/building-and-tree-detection-using-multiscale-matched-filtering" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/59277.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">320</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8696</span> A Reconfigurable Microstrip Patch Antenna with Polyphase Filter for Polarization Diversity and Cross Polarization Filtering Operation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Lakhdar%20Zaid">Lakhdar Zaid</a>, <a href="https://publications.waset.org/abstracts/search?q=Albane%20Sangiovanni"> Albane Sangiovanni</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A reconfigurable microstrip patch antenna with polyphase filter for polarization diversity and cross polarization filtering operation is presented in this paper. In our approach, a polyphase filter is used to obtain the four 90° phase shift outputs to feed a square microstrip patch antenna. The antenna can be switched between four states of polarization in transmission as well as in receiving mode. Switches are interconnected with the polyphase filter network to produce left-hand circular polarization, right-hand circular polarization, horizontal linear polarization, and vertical linear polarization. Additional advantage of using polyphase filter is its filtering capability for cross polarization filtering in right-hand circular polarization and left-hand circular polarization operation. The theoretical and simulated results demonstrated that polyphase filter is a good candidate to drive microstrip patch antenna to accomplish polarization diversity and cross polarization filtering operation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=active%20antenna" title="active antenna">active antenna</a>, <a href="https://publications.waset.org/abstracts/search?q=polarization%20diversity" title=" polarization diversity"> polarization diversity</a>, <a href="https://publications.waset.org/abstracts/search?q=patch%20antenna" title=" patch antenna"> patch antenna</a>, <a href="https://publications.waset.org/abstracts/search?q=polyphase%20filter" title=" polyphase filter"> polyphase filter</a> </p> <a href="https://publications.waset.org/abstracts/59013/a-reconfigurable-microstrip-patch-antenna-with-polyphase-filter-for-polarization-diversity-and-cross-polarization-filtering-operation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/59013.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">411</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">8695</span> EEG Signal Processing Methods to Differentiate Mental States</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sun%20H.%20Hwang">Sun H. Hwang</a>, <a href="https://publications.waset.org/abstracts/search?q=Young%20E.%20Lee"> Young E. Lee</a>, <a href="https://publications.waset.org/abstracts/search?q=Yunhan%20Ga"> Yunhan Ga</a>, <a href="https://publications.waset.org/abstracts/search?q=Gilwon%20Yoon"> Gilwon Yoon</a> </p> <p class="card-text"><strong>Abstract:</strong></p> EEG is a very complex signal with noises and other bio-potential interferences. EOG is the most distinct interfering signal when EEG signals are measured and analyzed. It is very important how to process raw EEG signals in order to obtain useful information. In this study, the EEG signal processing techniques such as EOG filtering and outlier removal were examined to minimize unwanted EOG signals and other noises. The two different mental states of resting and focusing were examined through EEG analysis. A focused state was induced by letting subjects to watch a red dot on the white screen. EEG data for 32 healthy subjects were measured. EEG data after 60-Hz notch filtering were processed by a commercially available EOG filtering and our presented algorithm based on the removal of outliers. The ratio of beta wave to theta wave was used as a parameter for determining the degree of focusing. The results show that our algorithm was more appropriate than the existing EOG filtering. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=EEG" title="EEG">EEG</a>, <a href="https://publications.waset.org/abstracts/search?q=focus" title=" focus"> focus</a>, <a href="https://publications.waset.org/abstracts/search?q=mental%20state" title=" mental state"> mental state</a>, <a href="https://publications.waset.org/abstracts/search?q=outlier" title=" outlier"> outlier</a>, <a href="https://publications.waset.org/abstracts/search?q=signal%20processing" title=" signal processing"> signal processing</a> </p> <a href="https://publications.waset.org/abstracts/62057/eeg-signal-processing-methods-to-differentiate-mental-states" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/62057.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">283</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">8694</span> Study of Adaptive Filtering Algorithms and the Equalization of Radio Mobile Channel</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Said%20Elkassimi">Said Elkassimi</a>, <a href="https://publications.waset.org/abstracts/search?q=Said%20Safi"> Said Safi</a>, <a href="https://publications.waset.org/abstracts/search?q=B.%20Manaut"> B. Manaut</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presented a study of three algorithms, the equalization algorithm to equalize the transmission channel with ZF and MMSE criteria, application of channel Bran A, and adaptive filtering algorithms LMS and RLS to estimate the parameters of the equalizer filter, i.e. move to the channel estimation and therefore reflect the temporal variations of the channel, and reduce the error in the transmitted signal. So far the performance of the algorithm equalizer with ZF and MMSE criteria both in the case without noise, a comparison of performance of the LMS and RLS algorithm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adaptive%20filtering%20second%20equalizer" title="adaptive filtering second equalizer">adaptive filtering second equalizer</a>, <a href="https://publications.waset.org/abstracts/search?q=LMS" title=" LMS"> LMS</a>, <a href="https://publications.waset.org/abstracts/search?q=RLS%20%20Bran%20A" title=" RLS Bran A"> RLS Bran A</a>, <a href="https://publications.waset.org/abstracts/search?q=Proakis%20%28B%29%20MMSE" title=" Proakis (B) MMSE"> Proakis (B) MMSE</a>, <a href="https://publications.waset.org/abstracts/search?q=ZF" title=" ZF"> ZF</a> </p> <a href="https://publications.waset.org/abstracts/32853/study-of-adaptive-filtering-algorithms-and-the-equalization-of-radio-mobile-channel" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/32853.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">313</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">8693</span> Efficient Filtering of Graph Based Data Using Graph Partitioning</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nileshkumar%20Vaishnav">Nileshkumar Vaishnav</a>, <a href="https://publications.waset.org/abstracts/search?q=Aditya%20Tatu"> Aditya Tatu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> An algebraic framework for processing graph signals axiomatically designates the graph adjacency matrix as the shift operator. In this setup, we often encounter a problem wherein we know the filtered output and the filter coefficients, and need to find out the input graph signal. Solution to this problem using direct approach requires O(N3) operations, where N is the number of vertices in graph. In this paper, we adapt the spectral graph partitioning method for partitioning of graphs and use it to reduce the computational cost of the filtering problem. We use the example of denoising of the temperature data to illustrate the efficacy of the approach. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=graph%20signal%20processing" title="graph signal processing">graph signal processing</a>, <a href="https://publications.waset.org/abstracts/search?q=graph%20partitioning" title=" graph partitioning"> graph partitioning</a>, <a href="https://publications.waset.org/abstracts/search?q=inverse%20filtering%20on%20graphs" title=" inverse filtering on graphs"> inverse filtering on graphs</a>, <a href="https://publications.waset.org/abstracts/search?q=algebraic%20signal%20processing" title=" algebraic signal processing"> algebraic signal processing</a> </p> <a href="https://publications.waset.org/abstracts/59397/efficient-filtering-of-graph-based-data-using-graph-partitioning" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/59397.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">311</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">8692</span> Towards the Enhancement of Thermoelectric Properties by Controlling the Thermoelectrical Nature of Grain Boundaries in Polycrystalline Materials</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Angel%20Fabian%20Mijangos">Angel Fabian Mijangos</a>, <a href="https://publications.waset.org/abstracts/search?q=Jaime%20Alvarez%20Quintana"> Jaime Alvarez Quintana</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Waste heat occurs in many areas of daily life because world’s energy consumption is inefficient. In general, generating 1 watt of power requires about 3 watt of energy input and involves dumping into the environment the equivalent of about 2 watts of power in the form of heat. Therefore, an attractive and sustainable solution to the energy problem would be the development of highly efficient thermoelectric devices which could help to recover this waste heat. This work presents the influence on the thermoelectric properties of metallic, semiconducting, and dielectric nanoparticles added into the grain boundaries of polycrystalline antimony (Sb) and bismuth (Bi) matrixes in order to obtain p- and n-type thermoelectric materials, respectively, by hot pressing methods. Results show that thermoelectric properties are significantly affected by the electrical and thermal nature as well as concentration of nanoparticles. Nevertheless, by optimizing the amount of the nanoparticles on the grain boundaries, an oscillatory behavior in ZT as function of the concentration of the nanoscale constituents is present. This effect is due to energy filtering mechanism which module the quantity of charge transport in the system and affects thermoelectric properties. Accordingly, a ZTmax can be accomplished through the addition of the appropriate amount of nanoparticles into the grain boundaries region. In this case, till three orders of amelioration on ZT is reached in both systems compared with the reference sample of each one. This approach paves the way to pursuit high performance thermoelectric materials in a simple way and opens a new route towards the enhancement of the thermoelectric figure of merit. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=energy%20filtering" title="energy filtering">energy filtering</a>, <a href="https://publications.waset.org/abstracts/search?q=grain%20boundaries" title=" grain boundaries"> grain boundaries</a>, <a href="https://publications.waset.org/abstracts/search?q=thermoelectric" title=" thermoelectric"> thermoelectric</a>, <a href="https://publications.waset.org/abstracts/search?q=nanostructured%20materials" title=" nanostructured materials"> nanostructured materials</a> </p> <a href="https://publications.waset.org/abstracts/32997/towards-the-enhancement-of-thermoelectric-properties-by-controlling-the-thermoelectrical-nature-of-grain-boundaries-in-polycrystalline-materials" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/32997.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">255</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">8691</span> Denoising of Magnetotelluric Signals by Filtering </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rodrigo%20Montufar-Chaveznava">Rodrigo Montufar-Chaveznava</a>, <a href="https://publications.waset.org/abstracts/search?q=Fernando%20Brambila-Paz"> Fernando Brambila-Paz</a>, <a href="https://publications.waset.org/abstracts/search?q=Ivette%20Caldelas"> Ivette Caldelas</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we present the advances corresponding to the denoising processing of magnetotelluric signals using several filters. In particular, we use the most common spatial domain filters such as median and mean, but we are also using the Fourier and wavelet transform for frequency domain filtering. We employ three datasets obtained at the different sampling rate (128, 4096 and 8192 bps) and evaluate the mean square error, signal-to-noise relation, and peak signal-to-noise relation to compare the kernels and determine the most suitable for each case. The magnetotelluric signals correspond to earth exploration when water is searched. The object is to find a denoising strategy different to the one included in the commercial equipment that is employed in this task. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=denoising" title="denoising">denoising</a>, <a href="https://publications.waset.org/abstracts/search?q=filtering" title=" filtering"> filtering</a>, <a href="https://publications.waset.org/abstracts/search?q=magnetotelluric%20signals" title=" magnetotelluric signals"> magnetotelluric signals</a>, <a href="https://publications.waset.org/abstracts/search?q=wavelet%20transform" title=" wavelet transform"> wavelet transform</a> </p> <a href="https://publications.waset.org/abstracts/91383/denoising-of-magnetotelluric-signals-by-filtering" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/91383.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">370</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">8690</span> Localization of Buried People Using Received Signal Strength Indication Measurement of Wireless Sensor</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Feng%20Tao">Feng Tao</a>, <a href="https://publications.waset.org/abstracts/search?q=Han%20Ye"> Han Ye</a>, <a href="https://publications.waset.org/abstracts/search?q=Shaoyi%20Liao"> Shaoyi Liao</a> </p> <p class="card-text"><strong>Abstract:</strong></p> City constructions collapse after earthquake and people will be buried under ruins. Search and rescue should be conducted as soon as possible to save them. Therefore, according to the complicated environment, irregular aftershocks and rescue allow of no delay, a kind of target localization method based on RSSI (Received Signal Strength Indication) is proposed in this article. The target localization technology based on RSSI with the features of low cost and low complexity has been widely applied to nodes localization in WSN (Wireless Sensor Networks). Based on the theory of RSSI transmission and the environment impact to RSSI, this article conducts the experiments in five scenes, and multiple filtering algorithms are applied to original RSSI value in order to establish the signal propagation model with minimum test error respectively. Target location can be calculated from the distance, which can be estimated from signal propagation model, through improved centroid algorithm. Result shows that the localization technology based on RSSI is suitable for large-scale nodes localization. Among filtering algorithms, mixed filtering algorithm (average of average, median and Gaussian filtering) performs better than any other single filtering algorithm, and by using the signal propagation model, the minimum error of distance between known nodes and target node in the five scene is about 3.06m. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=signal%20propagation%20model" title="signal propagation model">signal propagation model</a>, <a href="https://publications.waset.org/abstracts/search?q=centroid%20algorithm" title=" centroid algorithm"> centroid algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=localization" title=" localization"> localization</a>, <a href="https://publications.waset.org/abstracts/search?q=mixed%20filtering" title=" mixed filtering"> mixed filtering</a>, <a href="https://publications.waset.org/abstracts/search?q=RSSI" title=" RSSI"> RSSI</a> </p> <a href="https://publications.waset.org/abstracts/75284/localization-of-buried-people-using-received-signal-strength-indication-measurement-of-wireless-sensor" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/75284.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">300</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">8689</span> Computational Modeling of Load Limits of Carbon Fibre Composite Laminates Subjected to Low-Velocity Impact Utilizing Convolution-Based Fast Fourier Data Filtering Algorithms </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Farhat%20Imtiaz">Farhat Imtiaz</a>, <a href="https://publications.waset.org/abstracts/search?q=Umar%20Farooq"> Umar Farooq</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this work, we developed a computational model to predict ply level failure in impacted composite laminates. Data obtained from physical testing from flat and round nose impacts of 8-, 16-, 24-ply laminates were considered. Routine inspections of the tested laminates were carried out to approximate ply by ply inflicted damage incurred. Plots consisting of load–time, load–deflection, and energy–time history were drawn to approximate the inflicted damages. Impact test generated unwanted data logged due to restrictions on testing and logging systems were also filtered. Conventional filters (built-in, statistical, and numerical) reliably predicted load thresholds for relatively thin laminates such as eight and sixteen ply panels. However, for relatively thick laminates such as twenty-four ply laminates impacted by flat nose impact generated clipped data which can just be de-noised using oscillatory algorithms. The literature search reveals that modern oscillatory data filtering and extrapolation algorithms have scarcely been utilized. This investigation reports applications of filtering and extrapolation of the clipped data utilising fast Fourier Convolution algorithm to predict load thresholds. Some of the results were related to the impact-induced damage areas identified with Ultrasonic C-scans and found to be in acceptable agreement. Based on consistent findings, utilizing of modern data filtering and extrapolation algorithms to data logged by the existing machines has efficiently enhanced data interpretations without resorting to extra resources. The algorithms could be useful for impact-induced damage approximations of similar cases. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fibre%20reinforced%20laminates" title="fibre reinforced laminates">fibre reinforced laminates</a>, <a href="https://publications.waset.org/abstracts/search?q=fast%20Fourier%20algorithms" title=" fast Fourier algorithms"> fast Fourier algorithms</a>, <a href="https://publications.waset.org/abstracts/search?q=mechanical%20testing" title=" mechanical testing"> mechanical testing</a>, <a href="https://publications.waset.org/abstracts/search?q=data%20filtering%20and%20extrapolation" title=" data filtering and extrapolation"> data filtering and extrapolation</a> </p> <a href="https://publications.waset.org/abstracts/94686/computational-modeling-of-load-limits-of-carbon-fibre-composite-laminates-subjected-to-low-velocity-impact-utilizing-convolution-based-fast-fourier-data-filtering-algorithms" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/94686.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">135</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">8688</span> The Problem of Child Exploitation on Twitter: A Socio-Anthropological Perspective on Content Filtering Gaps</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Samig%20Ibayev">Samig Ibayev</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This research addresses the problem of illegal child abuse content on the Twitter platform bypassing filtering systems and appearing before users from a social-anthropological perspective. Although the wide access opportunities provided by social media platforms to their users are beneficial in many ways, it is seen that they contain gaps that pave the way for the spread of harmful and illegal content. The aim of the study is to examine the inadequacies of the current content filtering mechanisms of the Twitter platform, to understand the psychological effects of young users unintentionally encountering such content and the social dimensions of this situation. The research was conducted with a qualitative approach and was conducted using digital ethnography, content analysis and user experiences on the Twitter platform. Digital ethnography was used to observe the frequency of child abuse content on the platform and how these contents were presented. The content analysis method was used to reveal the gaps in Twitter's current filtering mechanisms. In addition, detailed information was collected on the extent of psychological effects and how the perception of trust in social media changed through interviews with young users exposed to such content. The main contributions of the research are to highlight the weaknesses in the content moderation and filtering mechanisms of social media platforms, to reveal the negative effects of illegal content on users, and to offer suggestions for preventing the spread of such content. As a result, it is suggested that platforms such as Twitter should improve their content filtering policies in order to increase user security and fulfill their social responsibilities. This research aims to create significant awareness about social media content management and ethical responsibilities on digital platforms. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Twitter" title="Twitter">Twitter</a>, <a href="https://publications.waset.org/abstracts/search?q=child%20exploitation" title=" child exploitation"> child exploitation</a>, <a href="https://publications.waset.org/abstracts/search?q=content%20filtering" title=" content filtering"> content filtering</a>, <a href="https://publications.waset.org/abstracts/search?q=digital%20ethnography" title=" digital ethnography"> digital ethnography</a>, <a href="https://publications.waset.org/abstracts/search?q=social%20anthropology" title=" social anthropology"> social anthropology</a> </p> <a href="https://publications.waset.org/abstracts/194155/the-problem-of-child-exploitation-on-twitter-a-socio-anthropological-perspective-on-content-filtering-gaps" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/194155.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">10</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">8687</span> Reduction of Speckle Noise in Echocardiographic Images: A Survey</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=Saida%20Khachira"> Saida Khachira</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohamed%20Ben%20Slima"> Mohamed Ben Slima</a>, <a href="https://publications.waset.org/abstracts/search?q=Ahmed%20Ben%20Hamida"> Ahmed Ben Hamida</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Speckle noise is a main characteristic of cardiac ultrasound images, it corresponding to grainy appearance that degrades the image quality. For this reason, the ultrasound images are difficult to use automatically in clinical use, then treatments are required for this type of images. Then a filtering procedure of these images is necessary to eliminate the speckle noise and to improve the quality of ultrasound images which will be then segmented to extract the necessary forms that exist. In this paper, we present the importance of the pre-treatment step for segmentation. This work is applied to cardiac ultrasound images. In a first step, a comparative study of speckle filtering method will be presented and then we use a segmentation algorithm to locate and extract cardiac structures. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=medical%20image%20processing" title="medical image processing">medical image processing</a>, <a href="https://publications.waset.org/abstracts/search?q=ultrasound%20images" title=" ultrasound images"> ultrasound images</a>, <a href="https://publications.waset.org/abstracts/search?q=Speckle%20noise" title=" Speckle noise"> Speckle noise</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20enhancement" title=" image enhancement"> image enhancement</a>, <a href="https://publications.waset.org/abstracts/search?q=speckle%20filtering" title=" speckle filtering"> speckle filtering</a>, <a href="https://publications.waset.org/abstracts/search?q=segmentation" title=" segmentation"> segmentation</a>, <a href="https://publications.waset.org/abstracts/search?q=snakes" title=" snakes"> snakes</a> </p> <a href="https://publications.waset.org/abstracts/19064/reduction-of-speckle-noise-in-echocardiographic-images-a-survey" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/19064.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">530</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">8686</span> Recommendations for Data Quality Filtering of Opportunistic Species Occurrence Data</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Camille%20Van%20Eupen">Camille Van Eupen</a>, <a href="https://publications.waset.org/abstracts/search?q=Dirk%20Maes"> Dirk Maes</a>, <a href="https://publications.waset.org/abstracts/search?q=Marc%20Herremans"> Marc Herremans</a>, <a href="https://publications.waset.org/abstracts/search?q=Kristijn%20R.%20R.%20Swinnen"> Kristijn R. R. Swinnen</a>, <a href="https://publications.waset.org/abstracts/search?q=Ben%20Somers"> Ben Somers</a>, <a href="https://publications.waset.org/abstracts/search?q=Stijn%20Luca"> Stijn Luca</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In ecology, species distribution models are commonly implemented to study species-environment relationships. These models increasingly rely on opportunistic citizen science data when high-quality species records collected through standardized recording protocols are unavailable. While these opportunistic data are abundant, uncertainty is usually high, e.g., due to observer effects or a lack of metadata. Data quality filtering is often used to reduce these types of uncertainty in an attempt to increase the value of studies relying on opportunistic data. However, filtering should not be performed blindly. In this study, recommendations are built for data quality filtering of opportunistic species occurrence data that are used as input for species distribution models. Using an extensive database of 5.7 million citizen science records from 255 species in Flanders, the impact on model performance was quantified by applying three data quality filters, and these results were linked to species traits. More specifically, presence records were filtered based on record attributes that provide information on the observation process or post-entry data validation, and changes in the area under the receiver operating characteristic (AUC), sensitivity, and specificity were analyzed using the Maxent algorithm with and without filtering. Controlling for sample size enabled us to study the combined impact of data quality filtering, i.e., the simultaneous impact of an increase in data quality and a decrease in sample size. Further, the variation among species in their response to data quality filtering was explored by clustering species based on four traits often related to data quality: commonness, popularity, difficulty, and body size. Findings show that model performance is affected by i) the quality of the filtered data, ii) the proportional reduction in sample size caused by filtering and the remaining absolute sample size, and iii) a species ‘quality profile’, resulting from a species classification based on the four traits related to data quality. The findings resulted in recommendations on when and how to filter volunteer generated and opportunistically collected data. This study confirms that correctly processed citizen science data can make a valuable contribution to ecological research and species conservation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=citizen%20science" title="citizen science">citizen science</a>, <a href="https://publications.waset.org/abstracts/search?q=data%20quality%20filtering" title=" data quality filtering"> data quality filtering</a>, <a href="https://publications.waset.org/abstracts/search?q=species%20distribution%20models" title=" species distribution models"> species distribution models</a>, <a href="https://publications.waset.org/abstracts/search?q=trait%20profiles" title=" trait profiles"> trait profiles</a> </p> <a href="https://publications.waset.org/abstracts/138428/recommendations-for-data-quality-filtering-of-opportunistic-species-occurrence-data" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/138428.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">8685</span> A Recommender System Fusing Collaborative Filtering and User’s Review Mining</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Seulbi%20Choi">Seulbi Choi</a>, <a href="https://publications.waset.org/abstracts/search?q=Hyunchul%20Ahn"> Hyunchul Ahn</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Collaborative filtering (CF) algorithm has been popularly used for recommender systems in both academic and practical applications. It basically generates recommendation results using users’ numeric ratings. However, the additional use of the information other than user ratings may lead to better accuracy of CF. Considering that a lot of people are likely to share their honest opinion on the items they purchased recently due to the advent of the Web 2.0, user's review can be regarded as the new informative source for identifying user's preference with accuracy. Under this background, this study presents a hybrid recommender system that fuses CF and user's review mining. Our system adopts conventional memory-based CF, but it is designed to use both user’s numeric ratings and his/her text reviews on the items when calculating similarities between users. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Recommender%20system" title="Recommender system">Recommender system</a>, <a href="https://publications.waset.org/abstracts/search?q=Collaborative%20filtering" title=" Collaborative filtering"> Collaborative filtering</a>, <a href="https://publications.waset.org/abstracts/search?q=Text%20mining" title=" Text mining"> Text mining</a>, <a href="https://publications.waset.org/abstracts/search?q=Review%20mining" title=" Review mining"> Review mining</a> </p> <a href="https://publications.waset.org/abstracts/54867/a-recommender-system-fusing-collaborative-filtering-and-users-review-mining" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/54867.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">356</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">8684</span> Context-Aware Recommender System Using Collaborative Filtering, Content-Based Algorithm and Fuzzy Rules</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Xochilt%20Ramirez-Garcia">Xochilt Ramirez-Garcia</a>, <a href="https://publications.waset.org/abstracts/search?q=Mario%20Garcia-Valdez"> Mario Garcia-Valdez</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Contextual recommendations are implemented in Recommender Systems to improve user satisfaction, recommender system makes accurate and suitable recommendations for a particular situation reaching personalized recommendations. The context provides information relevant to the Recommender System and is used as a filter for selection of relevant items for the user. This paper presents a Context-aware Recommender System, which uses techniques based on Collaborative Filtering and Content-Based, as well as fuzzy rules, to recommend items inside the context. The dataset used to test the system is Trip Advisor. The accuracy in the recommendations was evaluated with the Mean Absolute Error. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=algorithms" title="algorithms">algorithms</a>, <a href="https://publications.waset.org/abstracts/search?q=collaborative%20filtering" title=" collaborative filtering"> collaborative filtering</a>, <a href="https://publications.waset.org/abstracts/search?q=intelligent%20systems" title=" intelligent systems"> intelligent systems</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20logic" title=" fuzzy logic"> fuzzy logic</a>, <a href="https://publications.waset.org/abstracts/search?q=recommender%20systems" title=" recommender systems"> recommender systems</a> </p> <a href="https://publications.waset.org/abstracts/32865/context-aware-recommender-system-using-collaborative-filtering-content-based-algorithm-and-fuzzy-rules" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/32865.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">422</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">8683</span> The Study of Heat and Mass Transfer for Ferrous Materials' Filtration Drying</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Dmytro%20Symak">Dmytro Symak</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Drying is a complex technologic, thermal and energy process. Energy cost of drying processes in many cases is the most costly stage of production, and can be over 50% of total costs. As we know, in Ukraine over 85% of Portland cement is produced moist, and the finished product energy costs make up to almost 60%. During the wet cement production, energy costs make up over 5500 kJ / kg of clinker, while during the dry only 3100 kJ / kg, that is, switching to a dry Portland cement will allow result into double cutting energy costs. Therefore, to study raw materials drying process in the manufacture of Portland cement is very actual task. The fine ferrous materials drying (small pyrites, red mud, clay Kyoko) is recommended to do by filtration method, that is one of the most intense. The essence of filtration method drying lies in heat agent filtering through a stationary layer of wet material, which is located on the perforated partition, in the "layer-dispersed material - perforated partition." For the optimum drying purposes, it is necessary to establish the dependence of pressure loss in the layer of dispersed material, and the values of heat and mass transfer, depending on the speed of the gas flow filtering. In our research, the experimentally determined pressure loss in the layer of dispersed material was generalized based on dimensionless complexes in the form and coefficients of heat exchange. We also determined the relation between the coefficients of mass and heat transfer. As a result of theoretic and experimental investigations, it was possible to develop a methodology for calculating the optimal parameters for the thermal agent and the main parameters for the filtration drying installation. The comparison of calculated by known operating expenses methods for the process of small pyrites drying in a rotating drum and filtration method shows to save up to 618 kWh per 1,000 kg of dry material and 700 kWh during filtration drying clay. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=drying" title="drying">drying</a>, <a href="https://publications.waset.org/abstracts/search?q=cement" title=" cement"> cement</a>, <a href="https://publications.waset.org/abstracts/search?q=heat%20and%20mass%20transfer" title=" heat and mass transfer"> heat and mass transfer</a>, <a href="https://publications.waset.org/abstracts/search?q=filtration%20method" title=" filtration method"> filtration method</a> </p> <a href="https://publications.waset.org/abstracts/43737/the-study-of-heat-and-mass-transfer-for-ferrous-materials-filtration-drying" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/43737.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">262</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">8682</span> Evaluation of Sensor Pattern Noise Estimators for Source Camera Identification </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Benjamin%20Anderson-Sackaney">Benjamin Anderson-Sackaney</a>, <a href="https://publications.waset.org/abstracts/search?q=Amr%20Abdel-Dayem"> Amr Abdel-Dayem</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents a comprehensive survey of recent source camera identification (SCI) systems. Then, the performance of various sensor pattern noise (SPN) estimators was experimentally assessed, under common photo response non-uniformity (PRNU) frameworks. The experiments used 1350 natural and 900 flat-field images, captured by 18 individual cameras. 12 different experiments, grouped into three sets, were conducted. The results were analyzed using the receiver operator characteristic (ROC) curves. The experimental results demonstrated that combining the basic SPN estimator with a wavelet-based filtering scheme provides promising results. However, the phase SPN estimator fits better with both patch-based (BM3D) and anisotropic diffusion (AD) filtering schemes. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=sensor%20pattern%20noise" title="sensor pattern noise">sensor pattern noise</a>, <a href="https://publications.waset.org/abstracts/search?q=source%20camera%20identification" title=" source camera identification"> source camera identification</a>, <a href="https://publications.waset.org/abstracts/search?q=photo%20response%20non-uniformity" title=" photo response non-uniformity"> photo response non-uniformity</a>, <a href="https://publications.waset.org/abstracts/search?q=anisotropic%20diffusion" title=" anisotropic diffusion"> anisotropic diffusion</a>, <a href="https://publications.waset.org/abstracts/search?q=peak%20to%20correlation%20energy%20ratio" title=" peak to correlation energy ratio"> peak to correlation energy ratio</a> </p> <a href="https://publications.waset.org/abstracts/63183/evaluation-of-sensor-pattern-noise-estimators-for-source-camera-identification" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/63183.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">441</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">8681</span> PDDA: Priority-Based, Dynamic Data Aggregation Approach for Sensor-Based Big Data Framework</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Lutful%20Karim">Lutful Karim</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohammed%20S.%20Al-kahtani"> Mohammed S. Al-kahtani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Sensors are being used in various applications such as agriculture, health monitoring, air and water pollution monitoring, traffic monitoring and control and hence, play the vital role in the growth of big data. However, sensors collect redundant data. Thus, aggregating and filtering sensors data are significantly important to design an efficient big data framework. Current researches do not focus on aggregating and filtering data at multiple layers of sensor-based big data framework. Thus, this paper introduces (i) three layers data aggregation and framework for big data and (ii) a priority-based, dynamic data aggregation scheme (PDDA) for the lowest layer at sensors. Simulation results show that the PDDA outperforms existing tree and cluster-based data aggregation scheme in terms of overall network energy consumptions and end-to-end data transmission delay. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=big%20data" title="big data">big data</a>, <a href="https://publications.waset.org/abstracts/search?q=clustering" title=" clustering"> clustering</a>, <a href="https://publications.waset.org/abstracts/search?q=tree%20topology" title=" tree topology"> tree topology</a>, <a href="https://publications.waset.org/abstracts/search?q=data%20aggregation" title=" data aggregation"> data aggregation</a>, <a href="https://publications.waset.org/abstracts/search?q=sensor%20networks" title=" sensor networks"> sensor networks</a> </p> <a href="https://publications.waset.org/abstracts/47419/pdda-priority-based-dynamic-data-aggregation-approach-for-sensor-based-big-data-framework" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/47419.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">346</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">8680</span> Adaptive Filtering in Subbands for Supervised Source Separation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bruna%20Luisa%20Ramos%20Prado%20Vasques">Bruna Luisa Ramos Prado Vasques</a>, <a href="https://publications.waset.org/abstracts/search?q=Mariane%20Rembold%20Petraglia"> Mariane Rembold Petraglia</a>, <a href="https://publications.waset.org/abstracts/search?q=Antonio%20Petraglia"> Antonio Petraglia</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper investigates MIMO (Multiple-Input Multiple-Output) adaptive filtering techniques for the application of supervised source separation in the context of convolutive mixtures. From the observation that there is correlation among the signals of the different mixtures, an improvement in the NSAF (Normalized Subband Adaptive Filter) algorithm is proposed in order to accelerate its convergence rate. Simulation results with mixtures of speech signals in reverberant environments show the superior performance of the proposed algorithm with respect to the performances of the NLMS (Normalized Least-Mean-Square) and conventional NSAF, considering both the convergence speed and SIR (Signal-to-Interference Ratio) after convergence. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adaptive%20filtering" title="adaptive filtering">adaptive filtering</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-rate%20processing" title=" multi-rate processing"> multi-rate processing</a>, <a href="https://publications.waset.org/abstracts/search?q=normalized%20subband%20adaptive%20filter" title=" normalized subband adaptive filter"> normalized subband adaptive filter</a>, <a href="https://publications.waset.org/abstracts/search?q=source%20separation" title=" source separation"> source separation</a> </p> <a href="https://publications.waset.org/abstracts/78300/adaptive-filtering-in-subbands-for-supervised-source-separation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/78300.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">435</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">8679</span> E-Learning Recommender System Based on Collaborative Filtering and Ontology</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=John%20Tarus">John Tarus</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhendong%20Niu"> Zhendong Niu</a>, <a href="https://publications.waset.org/abstracts/search?q=Bakhti%20Khadidja"> Bakhti Khadidja</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In recent years, e-learning recommender systems has attracted great attention as a solution towards addressing the problem of information overload in e-learning environments and providing relevant recommendations to online learners. E-learning recommenders continue to play an increasing educational role in aiding learners to find appropriate learning materials to support the achievement of their learning goals. Although general recommender systems have recorded significant success in solving the problem of information overload in e-commerce domains and providing accurate recommendations, e-learning recommender systems on the other hand still face some issues arising from differences in learner characteristics such as learning style, skill level and study level. Conventional recommendation techniques such as collaborative filtering and content-based deal with only two types of entities namely users and items with their ratings. These conventional recommender systems do not take into account the learner characteristics in their recommendation process. Therefore, conventional recommendation techniques cannot make accurate and personalized recommendations in e-learning environment. In this paper, we propose a recommendation technique combining collaborative filtering and ontology to recommend personalized learning materials to online learners. Ontology is used to incorporate the learner characteristics into the recommendation process alongside the ratings while collaborate filtering predicts ratings and generate recommendations. Furthermore, ontological knowledge is used by the recommender system at the initial stages in the absence of ratings to alleviate the cold-start problem. Evaluation results show that our proposed recommendation technique outperforms collaborative filtering on its own in terms of personalization and recommendation accuracy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=collaborative%20filtering" title="collaborative filtering">collaborative filtering</a>, <a href="https://publications.waset.org/abstracts/search?q=e-learning" title=" e-learning"> e-learning</a>, <a href="https://publications.waset.org/abstracts/search?q=ontology" title=" ontology"> ontology</a>, <a href="https://publications.waset.org/abstracts/search?q=recommender%20system" title=" recommender system"> recommender system</a> </p> <a href="https://publications.waset.org/abstracts/64364/e-learning-recommender-system-based-on-collaborative-filtering-and-ontology" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/64364.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">380</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">8678</span> A Filtering Algorithm for a Nonlinear State-Space Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abdullah%20Eqal%20Al%20Mazrooei">Abdullah Eqal Al Mazrooei</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Kalman filter is a famous algorithm that utilizes to estimate the state in the linear systems. It has numerous applications in technology and science. Since of the most of applications in real life can be described by nonlinear systems. So, Kalman filter does not work with the nonlinear systems because it is suitable to linear systems only. In this work, a nonlinear filtering algorithm is presented which is suitable to use with the special kinds of nonlinear systems. This filter generalizes the Kalman filter. This means that this filter also can be used for the linear systems. Our algorithm depends on a special linearization of the second degree. We introduced the nonlinear algorithm with a bilinear state-space model. A simulation example is presented to illustrate the efficiency of the algorithm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kalman%20filter" title="Kalman filter">Kalman filter</a>, <a href="https://publications.waset.org/abstracts/search?q=filtering%20algorithm" title=" filtering algorithm"> filtering algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=nonlinear%20systems" title=" nonlinear systems"> nonlinear systems</a>, <a href="https://publications.waset.org/abstracts/search?q=state-space%20model" title=" state-space model"> state-space model</a> </p> <a href="https://publications.waset.org/abstracts/74331/a-filtering-algorithm-for-a-nonlinear-state-space-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/74331.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">376</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">8677</span> Tracking Filtering Algorithm Based on ConvLSTM</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ailing%20Yang">Ailing Yang</a>, <a href="https://publications.waset.org/abstracts/search?q=Penghan%20Song"> Penghan Song</a>, <a href="https://publications.waset.org/abstracts/search?q=Aihua%20Cai"> Aihua Cai</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The nonlinear maneuvering target tracking problem is mainly a state estimation problem when the target motion model is uncertain. Traditional solutions include Kalman filtering based on Bayesian filtering framework and extended Kalman filtering. However, these methods need prior knowledge such as kinematics model and state system distribution, and their performance is poor in state estimation of nonprior complex dynamic systems. Therefore, in view of the problems existing in traditional algorithms, a convolution LSTM target state estimation (SAConvLSTM-SE) algorithm based on Self-Attention memory (SAM) is proposed to learn the historical motion state of the target and the error distribution information measured at the current time. The measured track point data of airborne radar are processed into data sets. After supervised training, the data-driven deep neural network based on SAConvLSTM can directly obtain the target state at the next moment. Through experiments on two different maneuvering targets, we find that the network has stronger robustness and better tracking accuracy than the existing tracking methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=maneuvering%20target" title="maneuvering target">maneuvering target</a>, <a href="https://publications.waset.org/abstracts/search?q=state%20estimation" title=" state estimation"> state estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=Kalman%20filter" title=" Kalman filter"> Kalman filter</a>, <a href="https://publications.waset.org/abstracts/search?q=LSTM" title=" LSTM"> LSTM</a>, <a href="https://publications.waset.org/abstracts/search?q=self-attention" title=" self-attention"> self-attention</a> </p> <a href="https://publications.waset.org/abstracts/164893/tracking-filtering-algorithm-based-on-convlstm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/164893.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">177</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">8676</span> Hierarchical Filtering Method of Threat Alerts Based on Correlation Analysis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Xudong%20He">Xudong He</a>, <a href="https://publications.waset.org/abstracts/search?q=Jian%20Wang"> Jian Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Jiqiang%20Liu"> Jiqiang Liu</a>, <a href="https://publications.waset.org/abstracts/search?q=Lei%20Han"> Lei Han</a>, <a href="https://publications.waset.org/abstracts/search?q=Yang%20Yu"> Yang Yu</a>, <a href="https://publications.waset.org/abstracts/search?q=Shaohua%20Lv"> Shaohua Lv</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Nowadays, the threats of the internet are enormous and increasing; however, the classification of huge alert messages generated in this environment is relatively monotonous. It affects the accuracy of the network situation assessment, and also brings inconvenience to the security managers to deal with the emergency. In order to deal with potential network threats effectively and provide more effective data to improve the network situation awareness. It is essential to build a hierarchical filtering method to prevent the threats. In this paper, it establishes a model for data monitoring, which can filter systematically from the original data to get the grade of threats and be stored for using again. Firstly, it filters the vulnerable resources, open ports of host devices and services. Then use the entropy theory to calculate the performance changes of the host devices at the time of the threat occurring and filter again. At last, sort the changes of the performance value at the time of threat occurring. Use the alerts and performance data collected in the real network environment to evaluate and analyze. The comparative experimental analysis shows that the threat filtering method can effectively filter the threat alerts effectively. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=correlation%20analysis" title="correlation analysis">correlation analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=hierarchical%20filtering" title=" hierarchical filtering"> hierarchical filtering</a>, <a href="https://publications.waset.org/abstracts/search?q=multisource%20data" title=" multisource data"> multisource data</a>, <a href="https://publications.waset.org/abstracts/search?q=network%20security" title=" network security"> network security</a> </p> <a href="https://publications.waset.org/abstracts/88123/hierarchical-filtering-method-of-threat-alerts-based-on-correlation-analysis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/88123.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">201</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">8675</span> Harmonic Mitigation and Total Harmonic Distortion Reduction in Grid-Connected PV Systems: A Case Study Using Real-Time Data and Filtering Techniques</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Atena%20Tazikeh%20Lemeski">Atena Tazikeh Lemeski</a>, <a href="https://publications.waset.org/abstracts/search?q=Ismail%20Ozdamar"> Ismail Ozdamar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study presents a detailed analysis of harmonic distortion in a grid-connected photovoltaic (PV) system using real-time data captured from a solar power plant. Harmonics introduced by inverters in PV systems can degrade power quality and lead to increased Total Harmonic Distortion (THD), which poses challenges such as transformer overheating, increased power losses, and potential grid instability. This research addresses these issues by applying Fast Fourier Transform (FFT) to identify significant harmonic components and employing notch filters to target specific frequencies, particularly the 3rd harmonic (150 Hz), which was identified as the largest contributor to THD. Initial analysis of the unfiltered voltage signal revealed a THD of 21.15%, with prominent harmonic peaks at 150 Hz, 250 Hz and 350 Hz, corresponding to the 3rd, 5th, and 7th harmonics, respectively. After implementing the notch filters, the THD was reduced to 5.72%, demonstrating the effectiveness of this approach in mitigating harmonic distortion without affecting the fundamental frequency. This paper provides practical insights into the application of real-time filtering techniques in PV systems and their role in improving overall grid stability and power quality. The results indicate that targeted harmonic mitigation is crucial for the sustainable integration of renewable energy sources into modern electrical grids. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=grid-connected%20photovoltaic%20systems" title="grid-connected photovoltaic systems">grid-connected photovoltaic systems</a>, <a href="https://publications.waset.org/abstracts/search?q=fast%20Fourier%20transform" title=" fast Fourier transform"> fast Fourier transform</a>, <a href="https://publications.waset.org/abstracts/search?q=harmonic%20filtering" title=" harmonic filtering"> harmonic filtering</a>, <a href="https://publications.waset.org/abstracts/search?q=inverter-induced%20harmonics" title=" inverter-induced harmonics"> inverter-induced harmonics</a> </p> <a href="https://publications.waset.org/abstracts/192300/harmonic-mitigation-and-total-harmonic-distortion-reduction-in-grid-connected-pv-systems-a-case-study-using-real-time-data-and-filtering-techniques" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/192300.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">34</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=energy%20filtering&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=energy%20filtering&page=3">3</a></li> <li class="page-item"><a class="page-link" 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