CINXE.COM

<!DOCTYPE html> <html lang="en" dir="ltr"> <head>  <script async src="https://www.googletagmanager.com/gtag/js?id=G-P63WKM1TM1"></script> <script> window.dataLayer = window.dataLayer || []; function gtag(){dataLayer.push(arguments);} gtag('js', new Date()); gtag('config', 'G-P63WKM1TM1'); </script>  <script type="text/javascript" > (function(m,e,t,r,i,k,a){m[i]=m[i]||function(){(m[i].a=m[i].a||[]).push(arguments)}; m[i].l=1*new Date(); for (var j = 0; j < document.scripts.length; j++) {if (document.scripts[j].src === r) { return; }} k=e.createElement(t),a=e.getElementsByTagName(t)[0],k.async=1,k.src=r,a.parentNode.insertBefore(k,a)}) (window, document, "script", "https://mc.yandex.ru/metrika/tag.js", "ym"); ym(55165297, "init", { clickmap:false, trackLinks:true, accurateTrackBounce:true, webvisor:false }); </script> <noscript><div><img src="https://mc.yandex.ru/watch/55165297" style="position:absolute; left:-9999px;" alt="" /></div></noscript>    <title>Search results for: cigarette smoke detection</title> <meta name="description" content="Search results for: cigarette smoke detection"> <meta name="keywords" content="cigarette smoke detection"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none navbar-toggler ml-auto" type="button" data-toggle="collapse" data-target="#navbarMenu" aria-controls="navbarMenu" aria-expanded="false" aria-label="Toggle navigation"> <span class="navbar-toggler-icon"></span> </button> <div class="w-100"> <div class="d-none d-lg-flex flex-row-reverse"> <form method="get" action="https://waset.org/search" class="form-inline my-2 my-lg-0"> <input class="form-control mr-sm-2" type="search" placeholder="Search Conferences" value="cigarette smoke detection" name="q" aria-label="Search"> <button class="btn btn-light my-2 my-sm-0" type="submit"><i class="fas fa-search"></i></button> </form> </div> <div class="collapse navbar-collapse mt-1" id="navbarMenu"> <ul class="navbar-nav ml-auto align-items-center" id="mainNavMenu"> <li class="nav-item"> <a class="nav-link" href="https://waset.org/conferences" title="Conferences in 2024/2025/2026">Conferences</a> </li> <li class="nav-item"> <a class="nav-link" href="https://waset.org/disciplines" title="Disciplines">Disciplines</a> </li> <li class="nav-item"> <a class="nav-link" href="https://waset.org/committees" rel="nofollow">Committees</a> </li> <li class="nav-item dropdown"> <a class="nav-link dropdown-toggle" href="#" id="navbarDropdownPublications" role="button" data-toggle="dropdown" aria-haspopup="true" aria-expanded="false"> Publications </a> <div class="dropdown-menu" aria-labelledby="navbarDropdownPublications"> <a class="dropdown-item" href="https://publications.waset.org/abstracts">Abstracts</a> <a class="dropdown-item" href="https://publications.waset.org">Periodicals</a> <a class="dropdown-item" href="https://publications.waset.org/archive">Archive</a> </div> </li> <li class="nav-item"> <a class="nav-link" href="https://waset.org/page/support" title="Support">Support</a> </li> </ul> </div> </div> </nav> </div> </header> <main> <div class="container mt-4"> <div class="row"> <div class="col-md-9 mx-auto"> <form method="get" action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="cigarette smoke detection"> <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> 3652</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: cigarette smoke detection</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3532</span> Incorporating Multiple Supervised Learning Algorithms for Effective Intrusion Detection</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Umar%20Albalawi">Umar Albalawi</a>, <a href="https://publications.waset.org/abstracts/search?q=Sang%20C.%20Suh"> Sang C. Suh</a>, <a href="https://publications.waset.org/abstracts/search?q=Jinoh%20Kim"> Jinoh Kim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> As internet continues to expand its usage with an enormous number of applications, cyber-threats have significantly increased accordingly. Thus, accurate detection of malicious traffic in a timely manner is a critical concern in today’s Internet for security. One approach for intrusion detection is to use Machine Learning (ML) techniques. Several methods based on ML algorithms have been introduced over the past years, but they are largely limited in terms of detection accuracy and/or time and space complexity to run. In this work, we present a novel method for intrusion detection that incorporates a set of supervised learning algorithms. The proposed technique provides high accuracy and outperforms existing techniques that simply utilizes a single learning method. In addition, our technique relies on partial flow information (rather than full information) for detection, and thus, it is light-weight and desirable for online operations with the property of early identification. With the mid-Atlantic CCDC intrusion dataset publicly available, we show that our proposed technique yields a high degree of detection rate over 99% with a very low false alarm rate (0.4%). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=intrusion%20detection" title="intrusion detection">intrusion detection</a>, <a href="https://publications.waset.org/abstracts/search?q=supervised%20learning" title=" supervised learning"> supervised learning</a>, <a href="https://publications.waset.org/abstracts/search?q=traffic%20classification" title=" traffic classification"> traffic classification</a>, <a href="https://publications.waset.org/abstracts/search?q=computer%20networks" title=" computer networks"> computer networks</a> </p> <a href="https://publications.waset.org/abstracts/5421/incorporating-multiple-supervised-learning-algorithms-for-effective-intrusion-detection" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/5421.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">350</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">3531</span> Music Note Detection and Dictionary Generation from Music Sheet Using Image Processing Techniques</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Muhammad%20Ammar">Muhammad Ammar</a>, <a href="https://publications.waset.org/abstracts/search?q=Talha%20Ali"> Talha Ali</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdul%20Basit"> Abdul Basit</a>, <a href="https://publications.waset.org/abstracts/search?q=Bakhtawar%20Rajput"> Bakhtawar Rajput</a>, <a href="https://publications.waset.org/abstracts/search?q=Zobia%20Sohail"> Zobia Sohail</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Music note detection is an area of study for the past few years and has its own influence in music file generation from sheet music. We proposed a method to detect music notes on sheet music using basic thresholding and blob detection. Subsequently, we created a notes dictionary using a semi-supervised learning approach. After notes detection, for each test image, the new symbols are added to the dictionary. This makes the notes detection semi-automatic. The experiments are done on images from a dataset and also on the captured images. The developed approach showed almost 100% accuracy on the dataset images, whereas varying results have been seen on captured images. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=music%20note" title="music note">music note</a>, <a href="https://publications.waset.org/abstracts/search?q=sheet%20music" title=" sheet music"> sheet music</a>, <a href="https://publications.waset.org/abstracts/search?q=optical%20music%20recognition" title=" optical music recognition"> optical music recognition</a>, <a href="https://publications.waset.org/abstracts/search?q=blob%20detection" title=" blob detection"> blob detection</a>, <a href="https://publications.waset.org/abstracts/search?q=thresholding" title=" thresholding"> thresholding</a>, <a href="https://publications.waset.org/abstracts/search?q=dictionary%20generation" title=" dictionary generation"> dictionary generation</a> </p> <a href="https://publications.waset.org/abstracts/133670/music-note-detection-and-dictionary-generation-from-music-sheet-using-image-processing-techniques" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/133670.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">181</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">3530</span> Efficient Iterative V-BLAST Detection Technique in Wireless Communication System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hwan-Jun%20Choi">Hwan-Jun Choi</a>, <a href="https://publications.waset.org/abstracts/search?q=Sung-Bok%20Choi"> Sung-Bok Choi</a>, <a href="https://publications.waset.org/abstracts/search?q=Hyoung-Kyu%20Song"> Hyoung-Kyu Song</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Recently, among the MIMO-OFDM detection techniques, a lot of papers suggested V-BLAST scheme which can achieve high data rate. Therefore, the signal detection of MIMOOFDM system is important issue. In this paper, efficient iterative VBLAST detection technique is proposed in wireless communication system. The proposed scheme adjusts the number of candidate symbol and iterative scheme based on channel state. According to the simulation result, the proposed scheme has better BER performance than conventional schemes and similar BER performance of the QRD-M with iterative scheme. Moreover complexity of proposed scheme has 50.6 % less than complexity of QRD-M detection with iterative scheme. Therefore the proposed detection scheme can be efficiently used in wireless communication. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=MIMO-OFDM" title="MIMO-OFDM">MIMO-OFDM</a>, <a href="https://publications.waset.org/abstracts/search?q=V-BLAST" title=" V-BLAST"> V-BLAST</a>, <a href="https://publications.waset.org/abstracts/search?q=QR-decomposition" title=" QR-decomposition"> QR-decomposition</a>, <a href="https://publications.waset.org/abstracts/search?q=QRDM" title=" QRDM"> QRDM</a>, <a href="https://publications.waset.org/abstracts/search?q=DFE" title=" DFE"> DFE</a>, <a href="https://publications.waset.org/abstracts/search?q=iterative%20scheme" title=" iterative scheme"> iterative scheme</a>, <a href="https://publications.waset.org/abstracts/search?q=channel%20condition" title=" channel condition"> channel condition</a> </p> <a href="https://publications.waset.org/abstracts/3522/efficient-iterative-v-blast-detection-technique-in-wireless-communication-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/3522.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">3529</span> Combination between Intrusion Systems and Honeypots</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Majed%20Sanan">Majed Sanan</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Rammal"> Mohammad Rammal</a>, <a href="https://publications.waset.org/abstracts/search?q=Wassim%20Rammal"> Wassim Rammal</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Today, security is a major concern. Intrusion Detection, Prevention Systems and Honeypot can be used to moderate attacks. Many researchers have proposed to use many IDSs ((Intrusion Detection System) time to time. Some of these IDS’s combine their features of two or more IDSs which are called Hybrid Intrusion Detection Systems. Most of the researchers combine the features of Signature based detection methodology and Anomaly based detection methodology. For a signature based IDS, if an attacker attacks slowly and in organized way, the attack may go undetected through the IDS, as signatures include factors based on duration of the events but the actions of attacker do not match. Sometimes, for an unknown attack there is no signature updated or an attacker attack in the mean time when the database is updating. Thus, signature-based IDS fail to detect unknown attacks. Anomaly based IDS suffer from many false-positive readings. So there is a need to hybridize those IDS which can overcome the shortcomings of each other. In this paper we propose a new approach to IDS (Intrusion Detection System) which is more efficient than the traditional IDS (Intrusion Detection System). The IDS is based on Honeypot Technology and Anomaly based Detection Methodology. We have designed Architecture for the IDS in a packet tracer and then implemented it in real time. We have discussed experimental results performed: both the Honeypot and Anomaly based IDS have some shortcomings but if we hybridized these two technologies, the newly proposed Hybrid Intrusion Detection System (HIDS) is capable enough to overcome these shortcomings with much enhanced performance. In this paper, we present a modified Hybrid Intrusion Detection System (HIDS) that combines the positive features of two different detection methodologies - Honeypot methodology and anomaly based intrusion detection methodology. In the experiment, we ran both the Intrusion Detection System individually first and then together and recorded the data from time to time. From the data we can conclude that the resulting IDS are much better in detecting intrusions from the existing IDSs. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=security" title="security">security</a>, <a href="https://publications.waset.org/abstracts/search?q=intrusion%20detection" title=" intrusion detection"> intrusion detection</a>, <a href="https://publications.waset.org/abstracts/search?q=intrusion%20prevention" title=" intrusion prevention"> intrusion prevention</a>, <a href="https://publications.waset.org/abstracts/search?q=honeypot" title=" honeypot"> honeypot</a>, <a href="https://publications.waset.org/abstracts/search?q=anomaly-based%20detection" title=" anomaly-based detection"> anomaly-based detection</a>, <a href="https://publications.waset.org/abstracts/search?q=signature-based%20detection" title=" signature-based detection"> signature-based detection</a>, <a href="https://publications.waset.org/abstracts/search?q=cloud%20computing" title=" cloud computing"> cloud computing</a>, <a href="https://publications.waset.org/abstracts/search?q=kfsensor" title=" kfsensor"> kfsensor</a> </p> <a href="https://publications.waset.org/abstracts/40174/combination-between-intrusion-systems-and-honeypots" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/40174.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">382</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">3528</span> Mosaic Augmentation: Insights and Limitations</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Olivia%20A.%20Kjorlien">Olivia A. Kjorlien</a>, <a href="https://publications.waset.org/abstracts/search?q=Maryam%20Asghari"> Maryam Asghari</a>, <a href="https://publications.waset.org/abstracts/search?q=Farshid%20Alizadeh-Shabdiz"> Farshid Alizadeh-Shabdiz</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The goal of this paper is to investigate the impact of mosaic augmentation on the performance of object detection solutions. To carry out the study, YOLOv4 and YOLOv4-Tiny models have been selected, which are popular, advanced object detection models. These models are also representatives of two classes of complex and simple models. The study also has been carried out on two categories of objects, simple and complex. For this study, YOLOv4 and YOLOv4 Tiny are trained with and without mosaic augmentation for two sets of objects. While mosaic augmentation improves the performance of simple object detection, it deteriorates the performance of complex object detection, specifically having the largest negative impact on the false positive rate in a complex object detection case. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=accuracy" title="accuracy">accuracy</a>, <a href="https://publications.waset.org/abstracts/search?q=false%20positives" title=" false positives"> false positives</a>, <a href="https://publications.waset.org/abstracts/search?q=mosaic%20augmentation" title=" mosaic augmentation"> mosaic augmentation</a>, <a href="https://publications.waset.org/abstracts/search?q=object%20detection" title=" object detection"> object detection</a>, <a href="https://publications.waset.org/abstracts/search?q=YOLOV4" title=" YOLOV4"> YOLOV4</a>, <a href="https://publications.waset.org/abstracts/search?q=YOLOV4-Tiny" title=" YOLOV4-Tiny"> YOLOV4-Tiny</a> </p> <a href="https://publications.waset.org/abstracts/162634/mosaic-augmentation-insights-and-limitations" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/162634.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">127</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">3527</span> Long-Range Transport of Biomass Burning Aerosols over South America: A Case Study in the 2019 Amazon Rainforest Wildfires Season</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Angel%20Liduvino%20Vara-Vela">Angel Liduvino Vara-Vela</a>, <a href="https://publications.waset.org/abstracts/search?q=Dirceu%20Luis%20Herdies"> Dirceu Luis Herdies</a>, <a href="https://publications.waset.org/abstracts/search?q=Debora%20Souza%20Alvim"> Debora Souza Alvim</a>, <a href="https://publications.waset.org/abstracts/search?q=Eder%20Paulo%20Vendrasco"> Eder Paulo Vendrasco</a>, <a href="https://publications.waset.org/abstracts/search?q=Silvio%20Nilo%20Figueroa"> Silvio Nilo Figueroa</a>, <a href="https://publications.waset.org/abstracts/search?q=Jayant%20Pendharkar"> Jayant Pendharkar</a>, <a href="https://publications.waset.org/abstracts/search?q=Julio%20Pablo%20Reyes%20Fernandez"> Julio Pablo Reyes Fernandez</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Biomass-burning episodes are quite common in the central Amazon rainforest and represent a dominant source of aerosols during the dry season, between August and October. The increase in the occurrence of fires in 2019 in the world’s largest biomes has captured the attention of the international community. In particular, a rare and extreme smoke-related event occurred in the afternoon of Monday, August 19, 2019, in the most populous city in the Western Hemisphere, the São Paulo Metropolitan Area (SPMA), located in southeastern Brazil. The sky over the SPMA suddenly blackened, with the day turning into night, as reported by several news media around the world. In order to clarify whether or not the smoke that plunged the SPMA into sudden darkness was related to wildfires in the Amazon rainforest region, a set of 48-hour simulations over South America were performed using the Weather Research and Forecasting with Chemistry (WRF-Chem) model at 20 km horizontal resolution, on a daily basis, during the period from August 16 to August 19, 2019. The model results were satisfactorily compared against satellite-based data products and in situ measurements collected from air quality monitoring sites. Although a very strong smoke transport coming from the Amazon rainforest was observed in the middle of the afternoon on August 19, its impact on air quality over the SPMA took place in upper levels far above the surface, where, conversely, low air pollutant concentrations were observed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Amazon%20rainforest" title="Amazon rainforest">Amazon rainforest</a>, <a href="https://publications.waset.org/abstracts/search?q=biomass%20burning%20aerosols" title=" biomass burning aerosols"> biomass burning aerosols</a>, <a href="https://publications.waset.org/abstracts/search?q=S%C3%A3o%20Paulo%20metropolitan%20area" title=" São Paulo metropolitan area"> São Paulo metropolitan area</a>, <a href="https://publications.waset.org/abstracts/search?q=WRF-Chem%20model" title=" WRF-Chem model"> WRF-Chem model</a> </p> <a href="https://publications.waset.org/abstracts/129309/long-range-transport-of-biomass-burning-aerosols-over-south-america-a-case-study-in-the-2019-amazon-rainforest-wildfires-season" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/129309.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">139</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">3526</span> Active Islanding Detection Method Using Intelligent Controller</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kuang-Hsiung%20Tan">Kuang-Hsiung Tan</a>, <a href="https://publications.waset.org/abstracts/search?q=Chih-Chan%20Hu"> Chih-Chan Hu</a>, <a href="https://publications.waset.org/abstracts/search?q=Chien-Wu%20Lan"> Chien-Wu Lan</a>, <a href="https://publications.waset.org/abstracts/search?q=Shih-Sung%20Lin"> Shih-Sung Lin</a>, <a href="https://publications.waset.org/abstracts/search?q=Te-Jen%20Chang"> Te-Jen Chang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> An active islanding detection method using disturbance signal injection with intelligent controller is proposed in this study. First, a DC\AC power inverter is emulated in the distributed generator (DG) system to implement the tracking control of active power, reactive power outputs and the islanding detection. The proposed active islanding detection method is based on injecting a disturbance signal into the power inverter system through the <em>d</em>-axis current which leads to a frequency deviation at the terminal of the <em>RLC</em> load when the utility power is disconnected. Moreover, in order to improve the transient and steady-state responses of the active power and reactive power outputs of the power inverter, and to further improve the performance of the islanding detection method, two probabilistic fuzzy neural networks (PFNN) are adopted to replace the traditional proportional-integral (PI) controllers for the tracking control and the islanding detection. Furthermore, the network structure and the online learning algorithm of the PFNN are introduced in detail. Finally, the feasibility and effectiveness of the tracking control and the proposed active islanding detection method are verified with experimental results. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=distributed%20generators" title="distributed generators">distributed generators</a>, <a href="https://publications.waset.org/abstracts/search?q=probabilistic%20fuzzy%20neural%20network" title=" probabilistic fuzzy neural network"> probabilistic fuzzy neural network</a>, <a href="https://publications.waset.org/abstracts/search?q=islanding%20detection" title=" islanding detection"> islanding detection</a>, <a href="https://publications.waset.org/abstracts/search?q=non-detection%20zone" title=" non-detection zone"> non-detection zone</a> </p> <a href="https://publications.waset.org/abstracts/39253/active-islanding-detection-method-using-intelligent-controller" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/39253.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">389</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">3525</span> Structural Damage Detection Using Sensors Optimally Located</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Carlos%20Alberto%20Riveros">Carlos Alberto Riveros</a>, <a href="https://publications.waset.org/abstracts/search?q=Edwin%20Fabi%C3%A1n%20Garc%C3%ADa"> Edwin Fabián García</a>, <a href="https://publications.waset.org/abstracts/search?q=Javier%20Enrique%20Rivero"> Javier Enrique Rivero</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The measured data obtained from sensors in continuous monitoring of civil structures are mainly used for modal identification and damage detection. Therefore when modal identification analysis is carried out the quality in the identification of the modes will highly influence the damage detection results. It is also widely recognized that the usefulness of the measured data used for modal identification and damage detection is significantly influenced by the number and locations of sensors. The objective of this study is the numerical implementation of two widely known optimum sensor placement methods in beam-like structures <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=optimum%20sensor%20placement" title="optimum sensor placement">optimum sensor placement</a>, <a href="https://publications.waset.org/abstracts/search?q=structural%20damage%20detection" title=" structural damage detection"> structural damage detection</a>, <a href="https://publications.waset.org/abstracts/search?q=modal%20identification" title=" modal identification"> modal identification</a>, <a href="https://publications.waset.org/abstracts/search?q=beam-like%20structures." title=" beam-like structures. "> beam-like structures. </a> </p> <a href="https://publications.waset.org/abstracts/15240/structural-damage-detection-using-sensors-optimally-located" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/15240.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">431</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">3524</span> GPU Based Real-Time Floating Object Detection System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jie%20Yang">Jie Yang</a>, <a href="https://publications.waset.org/abstracts/search?q=Jian-Min%20Meng"> Jian-Min Meng</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A GPU-based floating object detection scheme is presented in this paper which is designed for floating mine detection tasks. This system uses contrast and motion information to eliminate as many false positives as possible while avoiding false negatives. The GPU computation platform is deployed to allow detecting objects in real-time. From the experimental results, it is shown that with certain configuration, the GPU-based scheme can speed up the computation up to one thousand times compared to the CPU-based scheme. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=object%20detection" title="object detection">object detection</a>, <a href="https://publications.waset.org/abstracts/search?q=GPU" title=" GPU"> GPU</a>, <a href="https://publications.waset.org/abstracts/search?q=motion%20estimation" title=" motion estimation"> motion estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=parallel%20processing" title=" parallel processing"> parallel processing</a> </p> <a href="https://publications.waset.org/abstracts/54425/gpu-based-real-time-floating-object-detection-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/54425.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">3523</span> Effect of Smoking on Tear Break-Up Time and Basal Tear Secretion</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kalsoom%20Rani">Kalsoom Rani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Tobacco contains nicotine, which causes addiction to many toxic chemicals. In the world, people consume it in the form of smoke, chew, and sniffing, smoke of it is composed of almost 7000 active chemicals, which are very harmful to human health as well as for eye health, inhalation of tobacco smoke and fumes can accelerate and cause many blinding eye diseases. Dry eye and smoking have not been covered extensively in researches; more studies are required to unveil the relationship between smoking and dry eye. This study was conducted to determine the quantity and quality of tears in smokers. 60 subjects participated in the study, which was divided into two groups on the basis of consumption of cigarettes per day with age matched non smokers of 15-50 years. All participants have gone through a study based questioner, eye examination, and diagnostic 'Dry Eye Tests' for evaporative tears evaluation and measurement of basal tear secretion. Subjects were included in the criteria of 10 cigarettes per day with a minimum duration of 1 year; passive smokers for control groups were excluded. The study was carried out in a Medina Teaching Hospital, Faisalabad, Pakistan, ophthalmology department for the duration of 8 months. Mean values for tear break up time (TBUT), was reported 10sec with SD of +3.74 in controlled group, 5sec with SD + 2.32 in smokers and 4sec SD +3.77 heavy smokers in right eye (RE) and left eye (LE) 10.35sec with SD of +3.88 in controlled 5sec with SD + 2.3 in smokers and much reduced TBUT in heavy smokers was 3.85sec SD+2.20. Smoking has a very strong association with TRUT with a significance of P=.00 both eyes. Mean Schirmer-I value of the subjects was reported 12.6mm with SD + 8.37 in RE and 12.59mm with SD + 8.96 LE. The mean Schirmer-II test value was reported in the right, and left eye with a mean value for control was 20.23mm with SD + 8.93, 20.75mm with SD + 8.84 respectively, and in Smokers 9.90mm with SD + 5.74, and 10.07mm with SD + 6.98, and in heavy smokers 7.7mm, SD + 3.22 and 6.9, SD + 3.50 mm, association with smoking showed p=.001 in RE and .003 in LE. Smoking has deteriorated effect on both evaporative tear and aqueous tear secretion and causing symptoms of dry eye burning, itching, redness, and watering with epithelial cell damage. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=tear%20break-up%20time" title="tear break-up time">tear break-up time</a>, <a href="https://publications.waset.org/abstracts/search?q=basal%20tear%20secretion" title=" basal tear secretion"> basal tear secretion</a>, <a href="https://publications.waset.org/abstracts/search?q=smokers" title=" smokers"> smokers</a>, <a href="https://publications.waset.org/abstracts/search?q=dry%20eye" title=" dry eye"> dry eye</a> </p> <a href="https://publications.waset.org/abstracts/130794/effect-of-smoking-on-tear-break-up-time-and-basal-tear-secretion" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/130794.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">126</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">3522</span> Thermal Neutron Detection Efficiency as a Function of Film Thickness for Front and Back Irradiation Detector Devices Coated with ¹⁰B, ⁶LiF, and Pure Li Thin Films</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Vedant%20Subhash">Vedant Subhash</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper discusses the physics of the detection of thermal neutrons using thin-film coated semiconductor detectors. The thermal neutron detection efficiency as a function of film thickness is calculated for the front and back irradiation detector devices coated with ¹⁰B, ⁶LiF, and pure Li thin films. The detection efficiency for back irradiation devices is 4.15% that is slightly higher than that for front irradiation detectors, 4.0% for ¹⁰B films of thickness 2.4μm. The theoretically calculated thermal neutron detection efficiency using ¹⁰B film thickness of 1.1 μm for the back irradiation device is 3.0367%, which has an offset of 0.0367% from the experimental value of 3.0%. The detection efficiency values are compared and proved consistent with the given calculations. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=detection%20efficiency" title="detection efficiency">detection efficiency</a>, <a href="https://publications.waset.org/abstracts/search?q=neutron%20detection" title=" neutron detection"> neutron detection</a>, <a href="https://publications.waset.org/abstracts/search?q=semiconductor%20detectors" title=" semiconductor detectors"> semiconductor detectors</a>, <a href="https://publications.waset.org/abstracts/search?q=thermal%20neutrons" title=" thermal neutrons"> thermal neutrons</a> </p> <a href="https://publications.waset.org/abstracts/133906/thermal-neutron-detection-efficiency-as-a-function-of-film-thickness-for-front-and-back-irradiation-detector-devices-coated-with-1b-6lif-and-pure-li-thin-films" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/133906.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">3521</span> Incorporating Anomaly Detection in a Digital Twin Scenario Using Symbolic Regression</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Manuel%20Alves">Manuel Alves</a>, <a href="https://publications.waset.org/abstracts/search?q=Angelica%20Reis"> Angelica Reis</a>, <a href="https://publications.waset.org/abstracts/search?q=Armindo%20Lobo"> Armindo Lobo</a>, <a href="https://publications.waset.org/abstracts/search?q=Valdemar%20Leiras"> Valdemar Leiras</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In industry 4.0, it is common to have a lot of sensor data. In this deluge of data, hints of possible problems are difficult to spot. The digital twin concept aims to help answer this problem, but it is mainly used as a monitoring tool to handle the visualisation of data. Failure detection is of paramount importance in any industry, and it consumes a lot of resources. Any improvement in this regard is of tangible value to the organisation. The aim of this paper is to add the ability to forecast test failures, curtailing detection times. To achieve this, several anomaly detection algorithms were compared with a symbolic regression approach. To this end, Isolation Forest, One-Class SVM and an auto-encoder have been explored. For the symbolic regression PySR library was used. The first results show that this approach is valid and can be added to the tools available in this context as a low resource anomaly detection method since, after training, the only requirement is the calculation of a polynomial, a useful feature in the digital twin context. <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=digital%20twin" title=" digital twin"> digital twin</a>, <a href="https://publications.waset.org/abstracts/search?q=industry%204.0" title=" industry 4.0"> industry 4.0</a>, <a href="https://publications.waset.org/abstracts/search?q=symbolic%20regression" title=" symbolic regression"> symbolic regression</a> </p> <a href="https://publications.waset.org/abstracts/151469/incorporating-anomaly-detection-in-a-digital-twin-scenario-using-symbolic-regression" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/151469.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">120</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">3520</span> The Association of Smoking and Body Mass Index with Acne Vulgaris in Adolescents and Young Adults</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Almutazballlah%20Qablan">Almutazballlah Qablan</a>, <a href="https://publications.waset.org/abstracts/search?q=Jihan%20M.%20Muhaidat"> Jihan M. Muhaidat</a>, <a href="https://publications.waset.org/abstracts/search?q=Bana%20Abu%20Rajab"> Bana Abu Rajab</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: Acne vulgaris is the most common skin condition that general practitioners and dermatologists encounter. It represents a chronic inflammatory disease affecting the pilosebaceous unit. Although acne vulgaris is not a life-threatening condition, it has a considerable psychological impact on the affected person. Acne patients have poor body image, low self-esteem, social isolation, and restricted activities. As part of the emotional impact, increased levels of anxiety, anger, depression, and frustration have also been observed in acne patients. (1) In this study, we want to assess the association between two modifiable risk factors; BMI and smoking, regarding acne vulgaris. Methods: A case-control study was conducted at King Abdullah University Hospital in Irbid, north Jordan in 2019/2020. A total number of 163 Acne cases were collected and interviewed by the author; on the other hand, there were 162 control cases. Anthropometric measures for Acne patients and control individuals were taken, and BMI was calculated. Both groups were asked about smoking habits. Data on subjects between 14 and 33 years of age were extracted. The characteristics of people who reported acne were compared with those with no acne using univariate and multivariate analysis. The Statistical Package for Social Sciences (SPSS) was relied on to analyze the collected data. The crosstabs methods (chi-square) and odd ratios were relied on to test the study hypothesis. Results: Cigarette smoking was highly associated with no-acne, with an odds ratio of 0.4 (95% CI: 0.2–0.9), P-value = 0.018. BMI and waterpipe smoking were not significantly associated with acne in the multivariate analysis. Conclusion: Cigarette smoking was found to be protective from Acne. No significant relation between BMI nor waterpipe smoking and the development of Acne Vulgaris. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=acne" title="acne">acne</a>, <a href="https://publications.waset.org/abstracts/search?q=BMI" title=" BMI"> BMI</a>, <a href="https://publications.waset.org/abstracts/search?q=smoking" title=" smoking"> smoking</a>, <a href="https://publications.waset.org/abstracts/search?q=case-control" title=" case-control"> case-control</a> </p> <a href="https://publications.waset.org/abstracts/154973/the-association-of-smoking-and-body-mass-index-with-acne-vulgaris-in-adolescents-and-young-adults" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/154973.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">98</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">3519</span> Fault Detection and Isolation in Attitude Control Subsystem of Spacecraft Formation Flying Using Extended Kalman Filters</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=S.%20Ghasemi">S. Ghasemi</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20Khorasani"> K. Khorasani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, the problem of fault detection and isolation in the attitude control subsystem of spacecraft formation flying is considered. In order to design the fault detection method, an extended Kalman filter is utilized which is a nonlinear stochastic state estimation method. Three fault detection architectures, namely, centralized, decentralized, and semi-decentralized are designed based on the extended Kalman filters. Moreover, the residual generation and threshold selection techniques are proposed for these architectures. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=component" title="component">component</a>, <a href="https://publications.waset.org/abstracts/search?q=formation%20flight%20of%20satellites" title=" formation flight of satellites"> formation flight of satellites</a>, <a href="https://publications.waset.org/abstracts/search?q=extended%20Kalman%20filter" title=" extended Kalman filter"> extended Kalman filter</a>, <a href="https://publications.waset.org/abstracts/search?q=fault%20detection%20and%20isolation" title=" fault detection and isolation"> fault detection and isolation</a>, <a href="https://publications.waset.org/abstracts/search?q=actuator%20fault" title=" actuator fault"> actuator fault</a> </p> <a href="https://publications.waset.org/abstracts/26418/fault-detection-and-isolation-in-attitude-control-subsystem-of-spacecraft-formation-flying-using-extended-kalman-filters" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/26418.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">3518</span> Functional Variants Detection by RNAseq</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Raffaele%20A.%20Calogero">Raffaele A. Calogero</a> </p> <p class="card-text"><strong>Abstract:</strong></p> RNAseq represents an attractive methodology for the detection of functional genomic variants. RNAseq results obtained from polyA+ RNA selection protocol (POLYA) and from exonic regions capturing protocol (ACCESS) indicate that ACCESS detects 10% more coding SNV/INDELs with respect to POLYA. ACCESS requires less reads for coding SNV detection with respect to POLYA. However, if the analysis aims at identifying SNV/INDELs also in the 5’ and 3’ UTRs, POLYA is definitively the preferred method. No particular advantage comes from ACCESS or POLYA in the detection of fusion transcripts. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fusion%20transcripts" title="fusion transcripts">fusion transcripts</a>, <a href="https://publications.waset.org/abstracts/search?q=INDEL" title=" INDEL"> INDEL</a>, <a href="https://publications.waset.org/abstracts/search?q=RNA-seq" title=" RNA-seq"> RNA-seq</a>, <a href="https://publications.waset.org/abstracts/search?q=WES" title=" WES"> WES</a>, <a href="https://publications.waset.org/abstracts/search?q=SNV" title=" SNV"> SNV</a> </p> <a href="https://publications.waset.org/abstracts/57993/functional-variants-detection-by-rnaseq" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/57993.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">288</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">3517</span> Visualized Flow Patterns around and inside a Two-Sided Wind-Catcher in the Presence of Upstream Structures</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20Afshin">M. Afshin</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Sohankar"> A. Sohankar</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Dehghan%20Manshadi"> M. Dehghan Manshadi</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20R.%20Daneshgar"> M. R. Daneshgar</a>, <a href="https://publications.waset.org/abstracts/search?q=G.%20R.%20Dehghan%20Kamaragi"> G. R. Dehghan Kamaragi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, the influence of an upstream structure on the flow pattern within and around the wind-catcher is experimentally investigated by smoke flow visualization techniques. Wind-catchers are an important part of natural ventilation in residential buildings or public places such as shopping centers, libraries, etc. Wind-catchers might be also used in places of high urban densities; hence their potential to provide natural ventilation in this case is dependent on the presence of upstream objects. In this study, the two-sided wind-catcher model was based on a real wind-catcher observed in the city of Yazd, Iran. The present study focuses on the flow patterns inside and outside the isolated two-sided wind-catcher, and on a two-sided wind-catcher in the presence of an upstream structure. The results show that the presence of an upstream structure influences the airflow pattern force and direction. Placing a high upstream object reverses the airflow direction inside the wind-catcher. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=natural%20ventilation" title="natural ventilation">natural ventilation</a>, <a href="https://publications.waset.org/abstracts/search?q=smoke%20flow%20visualization" title=" smoke flow visualization"> smoke flow visualization</a>, <a href="https://publications.waset.org/abstracts/search?q=two-sided%20wind-catcher" title=" two-sided wind-catcher"> two-sided wind-catcher</a>, <a href="https://publications.waset.org/abstracts/search?q=flow%20patterns" title=" flow patterns"> flow patterns</a> </p> <a href="https://publications.waset.org/abstracts/16978/visualized-flow-patterns-around-and-inside-a-two-sided-wind-catcher-in-the-presence-of-upstream-structures" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/16978.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">573</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">3516</span> Calculation of Detection Efficiency of Horizontal Large Volume Source Using Exvol Code</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20Y.%20Kang">M. Y. Kang</a>, <a href="https://publications.waset.org/abstracts/search?q=Euntaek%20Yoon"> Euntaek Yoon</a>, <a href="https://publications.waset.org/abstracts/search?q=H.%20D.%20Choi"> H. D. Choi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> To calculate the full energy (FE) absorption peak efficiency for arbitrary volume sample, we developed and verified the EXVol (Efficiency calculator for EXtended Voluminous source) code which is based on effective solid angle method. EXVol is possible to describe the source area as a non-uniform three-dimensional (x, y, z) source. And decompose and set it into several sets of volume units. Users can equally divide (x, y, z) coordinate system to calculate the detection efficiency at a specific position of a cylindrical volume source. By determining the detection efficiency for differential volume units, the total radiative absolute distribution and the correction factor of the detection efficiency can be obtained from the nondestructive measurement of the source. In order to check the performance of the EXVol code, Si ingot of 20 cm in diameter and 50 cm in height were used as a source. The detector was moved at the collimation geometry to calculate the detection efficiency at a specific position and compared with the experimental values. In this study, the performance of the EXVol code was extended to obtain the detection efficiency distribution at a specific position in a large volume source. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=attenuation" title="attenuation">attenuation</a>, <a href="https://publications.waset.org/abstracts/search?q=EXVol" title=" EXVol"> EXVol</a>, <a href="https://publications.waset.org/abstracts/search?q=detection%20efficiency" title=" detection efficiency"> detection efficiency</a>, <a href="https://publications.waset.org/abstracts/search?q=volume%20source" title=" volume source"> volume source</a> </p> <a href="https://publications.waset.org/abstracts/97158/calculation-of-detection-efficiency-of-horizontal-large-volume-source-using-exvol-code" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/97158.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">185</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">3515</span> Towards Integrating Statistical Color Features for Human Skin Detection</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohd%20Zamri%20Osman">Mohd Zamri Osman</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohd%20Aizaini%20Maarof"> Mohd Aizaini Maarof</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohd%20Foad%20Rohani"> Mohd Foad Rohani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Human skin detection recognized as the primary step in most of the applications such as face detection, illicit image filtering, hand recognition and video surveillance. The performance of any skin detection applications greatly relies on the two components: feature extraction and classification method. Skin color is the most vital information used for skin detection purpose. However, color feature alone sometimes could not handle images with having same color distribution with skin color. A color feature of pixel-based does not eliminate the skin-like color due to the intensity of skin and skin-like color fall under the same distribution. Hence, the statistical color analysis will be exploited such mean and standard deviation as an additional feature to increase the reliability of skin detector. In this paper, we studied the effectiveness of statistical color feature for human skin detection. Furthermore, the paper analyzed the integrated color and texture using eight classifiers with three color spaces of RGB, YCbCr, and HSV. The experimental results show that the integrating statistical feature using Random Forest classifier achieved a significant performance with an F1-score 0.969. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=color%20space" title="color space">color space</a>, <a href="https://publications.waset.org/abstracts/search?q=neural%20network" title=" neural network"> neural network</a>, <a href="https://publications.waset.org/abstracts/search?q=random%20forest" title=" random forest"> random forest</a>, <a href="https://publications.waset.org/abstracts/search?q=skin%20detection" title=" skin detection"> skin detection</a>, <a href="https://publications.waset.org/abstracts/search?q=statistical%20feature" title=" statistical feature"> statistical feature</a> </p> <a href="https://publications.waset.org/abstracts/43485/towards-integrating-statistical-color-features-for-human-skin-detection" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/43485.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">462</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">3514</span> An Earth Mover’s Distance Algorithm Based DDoS Detection Mechanism in SDN</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yang%20Zhou">Yang Zhou</a>, <a href="https://publications.waset.org/abstracts/search?q=Kangfeng%20Zheng"> Kangfeng Zheng</a>, <a href="https://publications.waset.org/abstracts/search?q=Wei%20Ni"> Wei Ni</a>, <a href="https://publications.waset.org/abstracts/search?q=Ren%20Ping%20Liu"> Ren Ping Liu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Software-defined networking (SDN) provides a solution for scalable network framework with decoupled control and data plane. However, this architecture also induces a particular distributed denial-of-service (DDoS) attack that can affect or even overwhelm the SDN network. DDoS attack detection problem has to date been mostly researched as entropy comparison problem. However, this problem lacks the utilization of SDN, and the results are not accurate. In this paper, we propose a DDoS attack detection method, which interprets DDoS detection as a signature matching problem and is formulated as Earth Mover’s Distance (EMD) model. Considering the feasibility and accuracy, we further propose to define the cost function of EMD to be a generalized Kullback-Leibler divergence. Simulation results show that our proposed method can detect DDoS attacks by comparing EMD values with the ones computed in the case without attacks. Moreover, our method can significantly increase the true positive rate of detection. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=DDoS%20detection" title="DDoS detection">DDoS detection</a>, <a href="https://publications.waset.org/abstracts/search?q=EMD" title=" EMD"> EMD</a>, <a href="https://publications.waset.org/abstracts/search?q=relative%20entropy" title=" relative entropy"> relative entropy</a>, <a href="https://publications.waset.org/abstracts/search?q=SDN" title=" SDN"> SDN</a> </p> <a href="https://publications.waset.org/abstracts/90528/an-earth-movers-distance-algorithm-based-ddos-detection-mechanism-in-sdn" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/90528.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">338</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">3513</span> Subjective Evaluation of Mathematical Morphology Edge Detection on Computed Tomography (CT) Images</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Emhimed%20Saffor">Emhimed Saffor</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, the problem of edge detection in digital images is considered. Three methods of edge detection based on mathematical morphology algorithm were applied on two sets (Brain and Chest) CT images. 3x3 filter for first method, 5x5 filter for second method and 7x7 filter for third method under MATLAB programming environment. The results of the above-mentioned methods are subjectively evaluated. The results show these methods are more efficient and satiable for medical images, and they can be used for different other applications. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=CT%20images" title="CT images">CT images</a>, <a href="https://publications.waset.org/abstracts/search?q=Matlab" title=" Matlab"> Matlab</a>, <a href="https://publications.waset.org/abstracts/search?q=medical%20images" title=" medical images"> medical images</a>, <a href="https://publications.waset.org/abstracts/search?q=edge%20detection" title=" edge detection "> edge detection </a> </p> <a href="https://publications.waset.org/abstracts/44926/subjective-evaluation-of-mathematical-morphology-edge-detection-on-computed-tomography-ct-images" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/44926.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">338</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">3512</span> Modified CUSUM Algorithm for Gradual Change Detection in a Time Series Data</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Victoria%20Siriaki%20Jorry">Victoria Siriaki Jorry</a>, <a href="https://publications.waset.org/abstracts/search?q=I.%20S.%20Mbalawata"> I. S. Mbalawata</a>, <a href="https://publications.waset.org/abstracts/search?q=Hayong%20Shin"> Hayong Shin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The main objective in a change detection problem is to develop algorithms for efficient detection of gradual and/or abrupt changes in the parameter distribution of a process or time series data. In this paper, we present a modified cumulative (MCUSUM) algorithm to detect the start and end of a time-varying linear drift in mean value of a time series data based on likelihood ratio test procedure. The design, implementation and performance of the proposed algorithm for a linear drift detection is evaluated and compared to the existing CUSUM algorithm using different performance measures. An approach to accurately approximate the threshold of the MCUSUM is also provided. Performance of the MCUSUM for gradual change-point detection is compared to that of standard cumulative sum (CUSUM) control chart designed for abrupt shift detection using Monte Carlo Simulations. In terms of the expected time for detection, the MCUSUM procedure is found to have a better performance than a standard CUSUM chart for detection of the gradual change in mean. The algorithm is then applied and tested to a randomly generated time series data with a gradual linear trend in mean to demonstrate its usefulness. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=average%20run%20length" title="average run length">average run length</a>, <a href="https://publications.waset.org/abstracts/search?q=CUSUM%20control%20chart" title=" CUSUM control chart"> CUSUM control chart</a>, <a href="https://publications.waset.org/abstracts/search?q=gradual%20change%20detection" title=" gradual change detection"> gradual change detection</a>, <a href="https://publications.waset.org/abstracts/search?q=likelihood%20ratio%20test" title=" likelihood ratio test"> likelihood ratio test</a> </p> <a href="https://publications.waset.org/abstracts/70339/modified-cusum-algorithm-for-gradual-change-detection-in-a-time-series-data" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/70339.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">299</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">3511</span> Particle Size Characteristics of Aerosol Jets Produced by a Low Powered E-Cigarette</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Shajid%20Rahman">Mohammad Shajid Rahman</a>, <a href="https://publications.waset.org/abstracts/search?q=Tarik%20Kaya"> Tarik Kaya</a>, <a href="https://publications.waset.org/abstracts/search?q=Edgar%20Matida"> Edgar Matida</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Electronic cigarettes, also known as e-cigarettes, may have become a tool to improve smoking cessation due to their ability to provide nicotine at a selected rate. Unlike traditional cigarettes, which produce toxic elements from tobacco combustion, e-cigarettes generate aerosols by heating a liquid solution (commonly a mixture of propylene glycol, vegetable glycerin, nicotine and some flavoring agents). However, caution still needs to be taken when using e-cigarettes due to the presence of addictive nicotine and some harmful substances produced from the heating process. Particle size distribution (PSD) and associated velocities generated by e-cigarettes have significant influence on aerosol deposition in different regions of human respiratory tracts. On another note, low actuation power is beneficial in aerosol generating devices since it exhibits a reduced emission of toxic chemicals. In case of e-cigarettes, lower heating powers can be considered as powers lower than 10 W compared to a wide range of powers (0.6 to 70.0 W) studied in literature. Due to the importance regarding inhalation risk reduction, deeper understanding of particle size characteristics of e-cigarettes demands thorough investigation. However, comprehensive study on PSD and velocities of e-cigarettes with a standard testing condition at relatively low heating powers is still lacking. The present study aims to measure particle number count and size distribution of undiluted aerosols of a latest fourth-generation e-cigarette at low powers, within 6.5 W using real-time particle counter (time-of-flight method). Also, temporal and spatial evolution of particle size and velocity distribution of aerosol jets are examined using phase Doppler anemometry (PDA) technique. To the authors’ best knowledge, application of PDA in e-cigarette aerosol measurement is rarely reported. In the present study, preliminary results about particle number count of undiluted aerosols measured by time-of-flight method depicted that an increase of heating power from 3.5 W to 6.5 W resulted in an enhanced asymmetricity in PSD, deviating from log-normal distribution. This can be considered as an artifact of rapid vaporization, condensation and coagulation processes on aerosols caused by higher heating power. A novel mathematical expression, combining exponential, Gaussian and polynomial (EGP) distributions, was proposed to describe asymmetric PSD successfully. The value of count median aerodynamic diameter and geometric standard deviation laid within a range of about 0.67 μm to 0.73 μm, and 1.32 to 1.43, respectively while the power varied from 3.5 W to 6.5 W. Laser Doppler velocimetry (LDV) and PDA measurement suggested a typical centerline streamwise mean velocity decay of aerosol jet along with a reduction of particle sizes. In the final submission, a thorough literature review, detailed description of experimental procedure and discussion of the results will be provided. Particle size and turbulent characteristics of aerosol jets will be further examined, analyzing arithmetic mean diameter, volumetric mean diameter, volume-based mean diameter, streamwise mean velocity and turbulence intensity. The present study has potential implications in PSD simulation and validation of aerosol dosimetry model, leading to improving related aerosol generating devices. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=E-cigarette%20aerosol" title="E-cigarette aerosol">E-cigarette aerosol</a>, <a href="https://publications.waset.org/abstracts/search?q=laser%20doppler%20velocimetry" title=" laser doppler velocimetry"> laser doppler velocimetry</a>, <a href="https://publications.waset.org/abstracts/search?q=particle%20size%20distribution" title=" particle size distribution"> particle size distribution</a>, <a href="https://publications.waset.org/abstracts/search?q=particle%20velocity" title=" particle velocity"> particle velocity</a>, <a href="https://publications.waset.org/abstracts/search?q=phase%20Doppler%20anemometry" title=" phase Doppler anemometry"> phase Doppler anemometry</a> </p> <a href="https://publications.waset.org/abstracts/185259/particle-size-characteristics-of-aerosol-jets-produced-by-a-low-powered-e-cigarette" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/185259.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">49</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">3510</span> Acne Vulgaris Association with Smoking and Body Mass Index in Jordanian Young Adults</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Almutazballlah%20Bassam%20Qablan">Almutazballlah Bassam Qablan</a>, <a href="https://publications.waset.org/abstracts/search?q=Jihan%20M.%20Muhaidat"> Jihan M. Muhaidat</a>, <a href="https://publications.waset.org/abstracts/search?q=bana%20Abu%20Rajab"> bana Abu Rajab</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: Acne vulgaris is considered one of the most common skin conditions encountered by dermatologists. It is a chronic inflammation affecting the pilosebaceous unit. Although acne vulgaris is not fatal, it leads to permanent scarring and disfigurement, and even without scarring, it has a huge effect on patients, causing negative health outcomes. Acne vulgaris patients experience psychological, and emotional ramifications as those with chronic health problems; they feel depressed, angry, anxious, and confused. Although acne is a popular disease, many thoughts and myths are still discussed about its origins and triggering factors. These myths can make you feel guilt as if you were somehow responsible for your acne. In this case control study, we want to define the relationship between two modifiable risk factors ;BMI and smoking, with acne vulgaris. Methods: A case-control study was conducted at King Abdullah University Hospital in Ramtha, Jordan in 2019/2020. A total number of 325 participants between 14 and 33 years of age were interviewed by the authors; including 163 acne vulgaris cases and 162 controls without acne vulgaris. Anthropometric measures and smoking for Acne patients and control participants were the independent variables used to assess acne. Univariate and multivariate analysis were used to compare the characteristics of people who reported acne with those with no acne. The collected data analyzed by using the Statistical Package for Social Sciences (SPSS). Results: Cigarette smoking was highly associated with controls; odds ratio 0.4 (95% CI: 0.2–0.9) , P-value = 0.018. BMI and waterpipe smoking were statistically insignificant with acne in the multivariate analysis. Conclusion: We found that cigarette smoking was protective against Acne. There was a statistically insignificant relation between BMI, waterpipe smoking and the development of Acne Vulgaris. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=acne" title="acne">acne</a>, <a href="https://publications.waset.org/abstracts/search?q=adolescents" title=" adolescents"> adolescents</a>, <a href="https://publications.waset.org/abstracts/search?q=BMI" title=" BMI"> BMI</a>, <a href="https://publications.waset.org/abstracts/search?q=smoking" title=" smoking"> smoking</a>, <a href="https://publications.waset.org/abstracts/search?q=case-control" title=" case-control"> case-control</a>, <a href="https://publications.waset.org/abstracts/search?q=risk%20factors" title=" risk factors"> risk factors</a> </p> <a href="https://publications.waset.org/abstracts/158827/acne-vulgaris-association-with-smoking-and-body-mass-index-in-jordanian-young-adults" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/158827.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">3509</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">3508</span> An Architectural Model for APT Detection</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nam-Uk%20Kim">Nam-Uk Kim</a>, <a href="https://publications.waset.org/abstracts/search?q=Sung-Hwan%20Kim"> Sung-Hwan Kim</a>, <a href="https://publications.waset.org/abstracts/search?q=Tai-Myoung%20Chung"> Tai-Myoung Chung</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Typical security management systems are not suitable for detecting APT attack, because they cannot draw the big picture from trivial events of security solutions. Although SIEM solutions have security analysis engine for that, their security analysis mechanisms need to be verified in academic field. Although this paper proposes merely an architectural model for APT detection, we will keep studying on correlation analysis mechanism in the future. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=advanced%20persistent%20threat" title="advanced persistent threat">advanced persistent threat</a>, <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=data%20mining" title=" data mining "> data mining </a> </p> <a href="https://publications.waset.org/abstracts/23009/an-architectural-model-for-apt-detection" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/23009.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">528</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">3507</span> Lane Detection Using Labeling Based RANSAC Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yeongyu%20Choi">Yeongyu Choi</a>, <a href="https://publications.waset.org/abstracts/search?q=Ju%20H.%20Park"> Ju H. Park</a>, <a href="https://publications.waset.org/abstracts/search?q=Ho-Youl%20Jung"> Ho-Youl Jung</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we propose labeling based RANSAC algorithm for lane detection. Advanced driver assistance systems (ADAS) have been widely researched to avoid unexpected accidents. Lane detection is a necessary system to assist keeping lane and lane departure prevention. The proposed vision based lane detection method applies Canny edge detection, inverse perspective mapping (IPM), K-means algorithm, mathematical morphology operations and 8 connected-component labeling. Next, random samples are selected from each labeling region for RANSAC. The sampling method selects the points of lane with a high probability. Finally, lane parameters of straight line or curve equations are estimated. Through the simulations tested on video recorded at daytime and nighttime, we show that the proposed method has better performance than the existing RANSAC algorithm in various environments. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Canny%20edge%20detection" title="Canny edge detection">Canny edge detection</a>, <a href="https://publications.waset.org/abstracts/search?q=k-means%20algorithm" title=" k-means algorithm"> k-means algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=RANSAC" title=" RANSAC"> RANSAC</a>, <a href="https://publications.waset.org/abstracts/search?q=inverse%20perspective%20mapping" title=" inverse perspective mapping"> inverse perspective mapping</a> </p> <a href="https://publications.waset.org/abstracts/92894/lane-detection-using-labeling-based-ransac-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/92894.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">244</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">3506</span> The Impact of Informal Care on Health Behavior among Older People with Chronic Diseases: A Study in China Using Propensity Score Matching</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hong%20Wu">Hong Wu</a>, <a href="https://publications.waset.org/abstracts/search?q=Naiji%20Lu"> Naiji Lu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Improvement of health behavior among people with chronic diseases is vital for increasing longevity and enhancing quality of life. This paper researched the causal effects of informal care on the compliance with doctor’s health advices – smoking control, dietetic regulation, weight control and keep exercising – among older people with chronic diseases in China, which is facing the challenge of aging. We addressed the selection bias by using propensity score matching in the estimation process. We used the 2011-2012 national baseline data of the China Health and Retirement Longitudinal Study. Our results showed informal care can help improve health behavior of older people. First, informal care improved the compliance of smoking controls: whether smoke, frequency of smoking, and the time lag between wake up and the first cigarette was all lower for these older people with informal care; Second, for dietetic regulation, older people with informal care had more meals every day than older people without informal care; Third, three variables: BMI, whether gain weight and whether lose weight were used to measure the outcome of weight control. There were no significant difference between group with informal care and that without for BMI and the possibility of losing weight. Older people with informal care had lower possibility of gain weight than that without; Last, for the advice of keeping exercising, informal care increased the probability of walking exercise, however, the difference between groups for moderate and vigorous exercise were not significant. Our results indicate policy makers who aim to decrease accidents should take informal care to elders into account and provide an appropriate policy to meet the demand of informal care. Our birth policy and postponed retirement policy may decrease the informal caregiving hours, so adjustments of these policies are important and urgent to meet the current situation of aged tendency of population. In addition, government could give more support to develop organizations to provide formal care, such as nursing home. We infer that formal care is also useful for health behavior improvements. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=chronic%20diseases" title="chronic diseases">chronic diseases</a>, <a href="https://publications.waset.org/abstracts/search?q=compliance" title=" compliance"> compliance</a>, <a href="https://publications.waset.org/abstracts/search?q=CHARLS" title=" CHARLS"> CHARLS</a>, <a href="https://publications.waset.org/abstracts/search?q=health%20advice" title=" health advice"> health advice</a>, <a href="https://publications.waset.org/abstracts/search?q=informal%20care" title=" informal care"> informal care</a>, <a href="https://publications.waset.org/abstracts/search?q=older%20people" title=" older people"> older people</a>, <a href="https://publications.waset.org/abstracts/search?q=propensity%20score%20matching" title=" propensity score matching"> propensity score matching</a> </p> <a href="https://publications.waset.org/abstracts/69798/the-impact-of-informal-care-on-health-behavior-among-older-people-with-chronic-diseases-a-study-in-china-using-propensity-score-matching" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/69798.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">405</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3505</span> Efficient Ground Targets Detection Using Compressive Sensing in Ground-Based Synthetic-Aperture Radar (SAR) Images</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Gherbi%20Nabil">Gherbi Nabil</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Detection of ground targets in SAR radar images is an important area for radar information processing. In the literature, various algorithms have been discussed in this context. However, most of them are of low robustness and accuracy. To this end, we discuss target detection in SAR images based on compressive sensing. Firstly, traditional SAR image target detection algorithms are discussed, and their limitations are highlighted. Secondly, a compressive sensing method is proposed based on the sparsity of SAR images. Next, the detection problem is solved using Multiple Measurements Vector configuration. Furthermore, a robust Alternating Direction Method of Multipliers (ADMM) is developed to solve the optimization problem. Finally, the detection results obtained using raw complex data are presented. Experimental results on real SAR images have verified the effectiveness of the proposed algorithm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=compressive%20sensing" title="compressive sensing">compressive sensing</a>, <a href="https://publications.waset.org/abstracts/search?q=raw%20complex%20data" title=" raw complex data"> raw complex data</a>, <a href="https://publications.waset.org/abstracts/search?q=synthetic%20aperture%20radar" title=" synthetic aperture radar"> synthetic aperture radar</a>, <a href="https://publications.waset.org/abstracts/search?q=ADMM" title=" ADMM"> ADMM</a> </p> <a href="https://publications.waset.org/abstracts/191958/efficient-ground-targets-detection-using-compressive-sensing-in-ground-based-synthetic-aperture-radar-sar-images" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/191958.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">19</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">3504</span> Stereo Camera Based Speed-Hump Detection Process for Real Time Driving Assistance System in the Daytime</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hyun-Koo%20Kim">Hyun-Koo Kim</a>, <a href="https://publications.waset.org/abstracts/search?q=Yong-Hun%20Kim"> Yong-Hun Kim</a>, <a href="https://publications.waset.org/abstracts/search?q=Soo-Young%20Suk"> Soo-Young Suk</a>, <a href="https://publications.waset.org/abstracts/search?q=Ju%20H.%20Park"> Ju H. Park</a>, <a href="https://publications.waset.org/abstracts/search?q=Ho-Youl%20Jung"> Ho-Youl Jung</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents an effective speed hump detection process at the day-time. we focus only on round types of speed humps in the day-time dynamic road environment. The proposed speed hump detection scheme consists mainly of two process as stereo matching and speed hump detection process. Our proposed process focuses to speed hump detection process. Speed hump detection process consist of noise reduction step, data fusion step, and speed hemp detection step. The proposed system is tested on Intel Core CPU with 2.80 GHz and 4 GB RAM tested in the urban road environments. The frame rate of test videos is 30 frames per second and the size of each frame of grabbed image sequences is 1280 pixels by 670 pixels. Using object-marked sequences acquired with an on-vehicle camera, we recorded speed humps and non-speed humps samples. Result of the tests, our proposed method can be applied in real-time systems by computation time is 13 ms. For instance; our proposed method reaches 96.1 %. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=data%20fusion" title="data fusion">data fusion</a>, <a href="https://publications.waset.org/abstracts/search?q=round%20types%20speed%20hump" title=" round types speed hump"> round types speed hump</a>, <a href="https://publications.waset.org/abstracts/search?q=speed%20hump%20detection" title=" speed hump detection"> speed hump detection</a>, <a href="https://publications.waset.org/abstracts/search?q=surface%20filter" title=" surface filter"> surface filter</a> </p> <a href="https://publications.waset.org/abstracts/15368/stereo-camera-based-speed-hump-detection-process-for-real-time-driving-assistance-system-in-the-daytime" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/15368.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">510</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">3503</span> DCDNet: Lightweight Document Corner Detection Network Based on Attention Mechanism</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kun%20Xu">Kun Xu</a>, <a href="https://publications.waset.org/abstracts/search?q=Yuan%20Xu"> Yuan Xu</a>, <a href="https://publications.waset.org/abstracts/search?q=Jia%20Qiao"> Jia Qiao</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The document detection plays an important role in optical character recognition and text analysis. Because the traditional detection methods have weak generalization ability, and deep neural network has complex structure and large number of parameters, which cannot be well applied in mobile devices, this paper proposes a lightweight Document Corner Detection Network (DCDNet). DCDNet is a two-stage architecture. The first stage with Encoder-Decoder structure adopts depthwise separable convolution to greatly reduce the network parameters. After introducing the Feature Attention Union (FAU) module, the second stage enhances the feature information of spatial and channel dim and adaptively adjusts the size of receptive field to enhance the feature expression ability of the model. Aiming at solving the problem of the large difference in the number of pixel distribution between corner and non-corner, Weighted Binary Cross Entropy Loss (WBCE Loss) is proposed to define corner detection problem as a classification problem to make the training process more efficient. In order to make up for the lack of Dataset of document corner detection, a Dataset containing 6620 images named Document Corner Detection Dataset (DCDD) is made. Experimental results show that the proposed method can obtain fast, stable and accurate detection results on DCDD. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=document%20detection" title="document detection">document detection</a>, <a href="https://publications.waset.org/abstracts/search?q=corner%20detection" title=" corner detection"> corner detection</a>, <a href="https://publications.waset.org/abstracts/search?q=attention%20mechanism" title=" attention mechanism"> attention mechanism</a>, <a href="https://publications.waset.org/abstracts/search?q=lightweight" title=" lightweight"> lightweight</a> </p> <a href="https://publications.waset.org/abstracts/152145/dcdnet-lightweight-document-corner-detection-network-based-on-attention-mechanism" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/152145.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">354</span> </span> </div> </div> <ul class="pagination"> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=cigarette%20smoke%20detection&page=4" rel="prev">&lsaquo;</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=cigarette%20smoke%20detection&page=1">1</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=cigarette%20smoke%20detection&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=cigarette%20smoke%20detection&page=3">3</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=cigarette%20smoke%20detection&page=4">4</a></li> <li class="page-item active"><span class="page-link">5</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=cigarette%20smoke%20detection&page=6">6</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=cigarette%20smoke%20detection&page=7">7</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=cigarette%20smoke%20detection&page=8">8</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=cigarette%20smoke%20detection&page=9">9</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=cigarette%20smoke%20detection&page=10">10</a></li> <li class="page-item disabled"><span class="page-link">...</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=cigarette%20smoke%20detection&page=121">121</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=cigarette%20smoke%20detection&page=122">122</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=cigarette%20smoke%20detection&page=6" rel="next">&rsaquo;</a></li> </ul> </div> </main> <footer> <div id="infolinks" class="pt-3 pb-2"> <div class="container"> <div style="background-color:#f5f5f5;" class="p-3"> <div class="row"> <div class="col-md-2"> <ul class="list-unstyled"> About <li><a href="https://waset.org/page/support">About Us</a></li> <li><a href="https://waset.org/page/support#legal-information">Legal</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/WASET-16th-foundational-anniversary.pdf">WASET celebrates its 16th foundational anniversary</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Account <li><a href="https://waset.org/profile">My Account</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Explore <li><a href="https://waset.org/disciplines">Disciplines</a></li> <li><a href="https://waset.org/conferences">Conferences</a></li> <li><a href="https://waset.org/conference-programs">Conference Program</a></li> <li><a href="https://waset.org/committees">Committees</a></li> <li><a href="https://publications.waset.org">Publications</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Research <li><a href="https://publications.waset.org/abstracts">Abstracts</a></li> <li><a href="https://publications.waset.org">Periodicals</a></li> <li><a href="https://publications.waset.org/archive">Archive</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Open Science <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Science-Philosophy.pdf">Open Science Philosophy</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Science-Award.pdf">Open Science Award</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Society-Open-Science-and-Open-Innovation.pdf">Open Innovation</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Postdoctoral-Fellowship-Award.pdf">Postdoctoral Fellowship Award</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Scholarly-Research-Review.pdf">Scholarly Research Review</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Support <li><a href="https://waset.org/page/support">Support</a></li> <li><a href="https://waset.org/profile/messages/create">Contact Us</a></li> <li><a href="https://waset.org/profile/messages/create">Report Abuse</a></li> </ul> </div> </div> </div> </div> </div> <div class="container text-center"> <hr style="margin-top:0;margin-bottom:.3rem;"> <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank" class="text-muted small">Creative Commons Attribution 4.0 International License</a> <div id="copy" class="mt-2">© 2024 World Academy of Science, Engineering and Technology</div> </div> </footer> <a href="javascript:" id="return-to-top"><i class="fas fa-arrow-up"></i></a> <div class="modal" id="modal-template"> <div class="modal-dialog"> <div class="modal-content"> <div class="row m-0 mt-1"> <div class="col-md-12"> <button type="button" class="close" data-dismiss="modal" aria-label="Close"><span aria-hidden="true">×</span></button> </div> </div> <div class="modal-body"></div> </div> </div> </div> <script src="https://cdn.waset.org/static/plugins/jquery-3.3.1.min.js"></script> <script src="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/js/bootstrap.bundle.min.js"></script> <script src="https://cdn.waset.org/static/js/site.js?v=150220211556"></script> <script> jQuery(document).ready(function() { /*jQuery.get("https://publications.waset.org/xhr/user-menu", function (response) { jQuery('#mainNavMenu').append(response); });*/ jQuery.get({ url: "https://publications.waset.org/xhr/user-menu", cache: false }).then(function(response){ jQuery('#mainNavMenu').append(response); }); }); </script> </body> </html>