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detection</title> <meta name="description" content="Search results for: intent detection"> <meta name="keywords" content="intent 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 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action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="intent 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> 3631</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: intent detection</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3631</span> Looking Elsewhere for Job: Relationship between Procedural Justice and Survivors’ Turnover Intent in Consolidated Nigeria Banks</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fasanmi%20Samuel%20Sunday">Fasanmi Samuel Sunday</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The study examines the relationship between procedural justice and turnover intent among survivors in a consolidated Nigeria bank. Opinions of eight hundred and eighty five staff of First City Monumental Bank and Finbank who survived the consolidated process were conveniently sampled using battery of tests. Two hypotheses were tested for this study. Results revealed that procedural justice and demographic variables (sex, age, previous banking job experience, and year of work experience) were significantly, independently and jointly influence turnover intent among survivors in consolidated banks in Nigeria. Also, there was a significant relationship between procedural justice and turnover intent among survivors in a consolidated bank in Nigeria. It was recommended that if the workers perceived the process of downsizing to be fair, they tend to reason with their management and coast along with the process rather than increasing in their turnover intent which will eventually drastically reduce the profitability matrix which the banks desired so desperately. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=bankers" title="bankers">bankers</a>, <a href="https://publications.waset.org/abstracts/search?q=procedural%20justice" title=" procedural justice"> procedural justice</a>, <a href="https://publications.waset.org/abstracts/search?q=sex" title=" sex"> sex</a>, <a href="https://publications.waset.org/abstracts/search?q=turnover%20intent" title=" turnover intent"> turnover intent</a> </p> <a href="https://publications.waset.org/abstracts/15576/looking-elsewhere-for-job-relationship-between-procedural-justice-and-survivors-turnover-intent-in-consolidated-nigeria-banks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/15576.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">513</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">3630</span> Assertion-Driven Test Repair Based on Priority Criteria</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ruilian%20Zhao">Ruilian Zhao</a>, <a href="https://publications.waset.org/abstracts/search?q=Shukai%20Zhang"> Shukai Zhang</a>, <a href="https://publications.waset.org/abstracts/search?q=Yan%20Wang"> Yan Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Weiwei%20Wang"> Weiwei Wang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Repairing broken test cases is an expensive and challenging task in evolving software systems. Although an automated repair technique with intent preservation has been proposed, but it does not take into account the association between test repairs and assertions, leading to a large number of irrelevant candidates and decreasing the repair capability. This paper proposes an assertion-driven test repair approach. Furthermore, an intent-oriented priority criterion is raised to guide the repair candidate generation, making the repairs closer to the intent of the test. In more detail, repair targets are determined through post-dominance relations between assertions and the methods that directly cause compilation errors. Then, test repairs are generated from the target in a bottom-up way, guided by the intent-oriented priority criteria. Finally, the generated repair candidates are prioritized to match the original test intent. The approach is implemented and evaluated on the benchmark of 4 open-source programs and 91 broken test cases. The result shows that the approach can fix 89% (81/91) of broken test cases, which is more effective than the existing intentpreserved test repair approach, and our intent-oriented priority criteria work well. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=test%20repair" title="test repair">test repair</a>, <a href="https://publications.waset.org/abstracts/search?q=test%20intent" title=" test intent"> test intent</a>, <a href="https://publications.waset.org/abstracts/search?q=software%20test" title=" software test"> software test</a>, <a href="https://publications.waset.org/abstracts/search?q=test%20case%20evolution" title=" test case evolution"> test case evolution</a> </p> <a href="https://publications.waset.org/abstracts/166462/assertion-driven-test-repair-based-on-priority-criteria" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/166462.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">129</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">3629</span> The Roles of Pay Satisfaction and Intent to Leave on Counterproductive Work Behavior among Non-Academic University Employees </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abiodun%20Musbau%20Lawal">Abiodun Musbau Lawal</a>, <a href="https://publications.waset.org/abstracts/search?q=Sunday%20Samson%20Babalola"> Sunday Samson Babalola</a>, <a href="https://publications.waset.org/abstracts/search?q=Uzor%20Friday%20Ordu"> Uzor Friday Ordu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Issue of employees counterproductive work behavior in government owned organization in emerging economies has continued to be a major concern. This study investigated the factors of pay satisfaction, intent to leave and age as predictors of counterproductive work behavior among non-academic employee in a Nigerian federal government owned university. A sample of 200 non-academic employees completed questionnaires. Hierarchical multiple regression was conducted to determine the contribution of each of the predictor variables on the criterion variable on counterproductive work behavior. Results indicate that age of participants (β = -.18; p < .05) significantly independently predicted CWB by accounting for 3% of the explained variance. Addition of pay satisfaction (β = -.14; p < .05) significantly accounted for 5% of the explained variance, while intent to leave (β = -.17; p < .05) further resulted in 8% of the explained variance in counterproductive work behavior. The importance of these findings with regards to reduction in counterproductive work behavior is highlighted. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=counterproductive" title="counterproductive">counterproductive</a>, <a href="https://publications.waset.org/abstracts/search?q=work%20behaviour" title=" work behaviour"> work behaviour</a>, <a href="https://publications.waset.org/abstracts/search?q=pay%20satisfaction" title=" pay satisfaction"> pay satisfaction</a>, <a href="https://publications.waset.org/abstracts/search?q=intent%20to%20leave" title=" intent to leave"> intent to leave</a> </p> <a href="https://publications.waset.org/abstracts/57766/the-roles-of-pay-satisfaction-and-intent-to-leave-on-counterproductive-work-behavior-among-non-academic-university-employees" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/57766.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">384</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">3628</span> The Impact of Level and Consequence of Service Co-Recovery on Post-Recovery Satisfaction and Repurchase Intent</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chia-Ching%20Tsai">Chia-Ching Tsai</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In service delivery, interpersonal interaction is the key to customer satisfaction, and apparently, the factor of human is critical in service delivery. Besides, customers quite care about the consequences of co-recovery. Thus, this research focuses on service failure caused by other customers and uses a 2x2 factorial design to investigate the impact of consequence and level of service co-recovery on post-recovery satisfaction and repurchase intent. 150 undergraduates were recruited as participants, and assigned to one of the four cells randomly. Every participant was requested to read the scenario and then rated the post-recovery satisfaction and repurchase intent. The results show that under the condition of failed co-recovery, level of co-recovery has no effect on post-recovery satisfaction, while under the condition of successful co-recovery, high-level co-recovery causes significantly higher post-recovery satisfaction than low-level co-recovery. Moreover, post-recovery satisfaction has significantly positive impact on repurchase intent. In the system of service delivery, customers interact with other customers frequently. Therefore, comparing with the literature, this research focuses on the service failure caused by other customers. This research also supplies a better understanding of customers’ view on consequences of different levels of co-recovery, which is helpful for the practitioners to make use of co-recovery. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=service%20failure" title="service failure">service failure</a>, <a href="https://publications.waset.org/abstracts/search?q=service%20co-recovery" title=" service co-recovery"> service co-recovery</a>, <a href="https://publications.waset.org/abstracts/search?q=consequence%20of%20co-recovery" title=" consequence of co-recovery"> consequence of co-recovery</a>, <a href="https://publications.waset.org/abstracts/search?q=level%20of%20co-recovery" title=" level of co-recovery"> level of co-recovery</a>, <a href="https://publications.waset.org/abstracts/search?q=post-recovery%20satisfaction" title=" post-recovery satisfaction"> post-recovery satisfaction</a>, <a href="https://publications.waset.org/abstracts/search?q=repurchase%20intent" title=" repurchase intent"> repurchase intent</a> </p> <a href="https://publications.waset.org/abstracts/78948/the-impact-of-level-and-consequence-of-service-co-recovery-on-post-recovery-satisfaction-and-repurchase-intent" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/78948.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">420</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">3627</span> Modeling False Statements in Texts</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Francielle%20A.%20Vargas">Francielle A. Vargas</a>, <a href="https://publications.waset.org/abstracts/search?q=Thiago%20A.%20S.%20Pardo"> Thiago A. S. Pardo</a> </p> <p class="card-text"><strong>Abstract:</strong></p> According to the standard philosophical definition, lying is saying something that you believe to be false with the intent to deceive. For deception detection, the FBI trains its agents in a technique named statement analysis, which attempts to detect deception based on parts of speech (i.e., linguistics style). This method is employed in interrogations, where the suspects are first asked to make a written statement. In this poster, we model false statements using linguistics style. In order to achieve this, we methodically analyze linguistic features in a corpus of fake news in the Portuguese language. The results show that they present substantial lexical, syntactic and semantic variations, as well as punctuation and emotion distinctions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=deception%20detection" title="deception detection">deception detection</a>, <a href="https://publications.waset.org/abstracts/search?q=linguistics%20style" title=" linguistics style"> linguistics style</a>, <a href="https://publications.waset.org/abstracts/search?q=computational%20linguistics" title=" computational linguistics"> computational linguistics</a>, <a href="https://publications.waset.org/abstracts/search?q=natural%20language%20processing" title=" natural language processing"> natural language processing</a> </p> <a href="https://publications.waset.org/abstracts/129388/modeling-false-statements-in-texts" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/129388.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">218</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">3626</span> Changes in Knowledge and Awareness for a Community-Based Cancer Screening Educational Program</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shenghui%20Wu">Shenghui Wu</a>, <a href="https://publications.waset.org/abstracts/search?q=Patricia%20Chalela"> Patricia Chalela</a>, <a href="https://publications.waset.org/abstracts/search?q=Amelie%20G.%20Ramirez"> Amelie G. Ramirez</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: Cervical cancer (CC), colorectal cancer (CRC), and breast cancer (BC) are diseases that can be prevented/detected through early test. Through educational programs, individuals can become better informed about these cancers and understand the importance of screening and early detection. A community-based educational program was developed to improve knowledge and awareness toward the screening of the three cancer types in a South Texas underserved population. Methods: Residents living in Laredo, Texas were invited to participate in the present study. From January 2020 to April 2021, participants were recruited using social media and flyer distributions in general community. Participants received a free live web cancer education presentation delivered by bilingual community health educators, and online pre- and post-education surveys for CC, CRC, and BC separately. Pre-post changes in knowledge for individual items were compared using McNemar’s chi-squared tests. Results: Overall, participants demonstrated increases in CC (n=237), CRC (n=59), and BC (n=56) screening knowledge and awareness after receiving the cancer screening education (Ps<0.05). After receiving the cancer screening education, 85-97% of participants had an intent to talk to a healthcare provider about CC/CRC/BC screening, 88-97% had an intent to get a CC/CRC/BC screening test in the next 12 months or at the next routine appointment, and 90-97% had an intent to talk about CC/CRC/BC with their family members or friends. Conclusion: A community-based educational program can help increase knowledge and awareness about cervical, colorectal, and breast cancer screening, promote positive changes in population's knowledge and awareness about the benefits of cancer screening. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cervical%20cancer" title="cervical cancer">cervical cancer</a>, <a href="https://publications.waset.org/abstracts/search?q=colorectal%20cancer" title=" colorectal cancer"> colorectal cancer</a>, <a href="https://publications.waset.org/abstracts/search?q=breast%20cancer" title=" breast cancer"> breast cancer</a>, <a href="https://publications.waset.org/abstracts/search?q=educational%20program" title=" educational program"> educational program</a>, <a href="https://publications.waset.org/abstracts/search?q=health%20knowledge" title=" health knowledge"> health knowledge</a>, <a href="https://publications.waset.org/abstracts/search?q=awareness" title=" awareness"> awareness</a>, <a href="https://publications.waset.org/abstracts/search?q=Hispanics" title=" Hispanics"> Hispanics</a>, <a href="https://publications.waset.org/abstracts/search?q=screening" title=" screening"> screening</a>, <a href="https://publications.waset.org/abstracts/search?q=health%20education" title=" health education"> health education</a> </p> <a href="https://publications.waset.org/abstracts/158066/changes-in-knowledge-and-awareness-for-a-community-based-cancer-screening-educational-program" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/158066.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">107</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">3625</span> Socio Economic Deprivation, Institutional Outlay and the Intent of Mobile Snatching and Street Assaults in Pakistan</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Asad%20Salahuddin">Asad Salahuddin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Crime rates seem to be severely augmenting over the past several years in Pakistan which has perpetuated concerns as to what, when and how this upsurge will be eradicated. State institutions are posed to be in utmost perplexity, given the enormity of worsening law and order situation, compelling government on the flip side to expend more resources in strengthening institutions to confront crime, whereas, the economy has been confronted with massive energy crisis, mass unemployment and considerable inflation which has rendered most of the people into articulate apprehension as to how to satisfy basic necessities. A framework to investigate the variability in the rising street crimes, as affected by social and institutional outcomes, has been established using a cross-sectional study. Questionnaire, entailing 7 sections incorporating numerous patterns of behavior and history of involvement in different crimes for potential street criminals was observed as data collection instrument. In order to specifically explicate the intent of street crimes on micro level, various motivational and de-motivational factors that stimulate people to resort to street crimes were scrutinized. Intent of mobile snatching and intent of street assault as potential dependent variables were examined using numerous variables that influence the occurrence and intent of these crimes using ordered probit along with ordered logit and tobit as competing models. Model Estimates asserts that intent of mobile snatching has been significantly enhanced owing to perceived judicial inefficiency and lower ability of police reforms to operate effectively, which signifies the inefficiency of institutions that are entitled to deliver justice and maintaining law and order respectively. Whereas, intent of street assaults, as an outcome, affirms that people with lack of self-stability and severe childhood punishments were more tempted to be involved in violent acts. Hence, it is imperative for government to render better resources in form of training, equipment and improved salaries to police and judiciary in order to enhance their abilities and potential to curb inflating crime. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=deprivation" title="deprivation">deprivation</a>, <a href="https://publications.waset.org/abstracts/search?q=street%20assault" title=" street assault"> street assault</a>, <a href="https://publications.waset.org/abstracts/search?q=self%20control" title=" self control"> self control</a>, <a href="https://publications.waset.org/abstracts/search?q=police%20reform" title=" police reform"> police reform</a> </p> <a href="https://publications.waset.org/abstracts/14796/socio-economic-deprivation-institutional-outlay-and-the-intent-of-mobile-snatching-and-street-assaults-in-pakistan" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/14796.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">427</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">3624</span> One-Shot Text Classification with Multilingual-BERT</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hsin-Yang%20Wang">Hsin-Yang Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20M.%20A.%20Salam"> K. M. A. Salam</a>, <a href="https://publications.waset.org/abstracts/search?q=Ying-Jia%20Lin"> Ying-Jia Lin</a>, <a href="https://publications.waset.org/abstracts/search?q=Daniel%20Tan"> Daniel Tan</a>, <a href="https://publications.waset.org/abstracts/search?q=Tzu-Hsuan%20Chou"> Tzu-Hsuan Chou</a>, <a href="https://publications.waset.org/abstracts/search?q=Hung-Yu%20Kao"> Hung-Yu Kao</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Detecting user intent from natural language expression has a wide variety of use cases in different natural language processing applications. Recently few-shot training has a spike of usage on commercial domains. Due to the lack of significant sample features, the downstream task performance has been limited or leads to an unstable result across different domains. As a state-of-the-art method, the pre-trained BERT model gathering the sentence-level information from a large text corpus shows improvement on several NLP benchmarks. In this research, we are proposing a method to change multi-class classification tasks into binary classification tasks, then use the confidence score to rank the results. As a language model, BERT performs well on sequence data. In our experiment, we change the objective from predicting labels into finding the relations between words in sequence data. Our proposed method achieved 71.0% accuracy in the internal intent detection dataset and 63.9% accuracy in the HuffPost dataset. Acknowledgment: This work was supported by NCKU-B109-K003, which is the collaboration between National Cheng Kung University, Taiwan, and SoftBank Corp., Tokyo. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=OSML" title="OSML">OSML</a>, <a href="https://publications.waset.org/abstracts/search?q=BERT" title=" BERT"> BERT</a>, <a href="https://publications.waset.org/abstracts/search?q=text%20classification" title=" text classification"> text classification</a>, <a href="https://publications.waset.org/abstracts/search?q=one%20shot" title=" one shot"> one shot</a> </p> <a href="https://publications.waset.org/abstracts/135007/one-shot-text-classification-with-multilingual-bert" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/135007.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">101</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">3623</span> The Impact of Quality of Life on Satisfaction and Intent to Return for Distance Running</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chin-Huang%20Huang">Chin-Huang Huang</a>, <a href="https://publications.waset.org/abstracts/search?q=Chun-Chu%20Yeh"> Chun-Chu Yeh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Physical activities have a positive impact on individuals’ health and well-being. They also play an important role in promoting quality of life (QoL). The distance running enhances participants’ life satisfaction and provides positive experiences in physical activity. This study aims to measure the perception of QoL and to find the effect on satisfaction and intent to return for distance runners. Exploratory factor analysis is carried out to extract four major factorial dimensions of QoL, including multiple functions, spiritual, physical and cognitive factors. The main factors of QoL will be introduced into the regression function on satisfaction and return intention. The results show that the QoL factors including multiple functions, spiritual, physical and cognitive factors have a positive and significant impact on satisfaction for participants. The multiple functions and physical factors are also significantly positively correlated to the intent of return for runners. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=quality%20of%20life" title="quality of life">quality of life</a>, <a href="https://publications.waset.org/abstracts/search?q=physical%20activity" title=" physical activity"> physical activity</a>, <a href="https://publications.waset.org/abstracts/search?q=distance%20running" title=" distance running"> distance running</a>, <a href="https://publications.waset.org/abstracts/search?q=satisfaction" title=" satisfaction"> satisfaction</a> </p> <a href="https://publications.waset.org/abstracts/64300/the-impact-of-quality-of-life-on-satisfaction-and-intent-to-return-for-distance-running" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/64300.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">465</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">3622</span> A Machine Learning Approach to Detecting Evasive PDF Malware</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Vareesha%20Masood">Vareesha Masood</a>, <a href="https://publications.waset.org/abstracts/search?q=Ammara%20Gul"> Ammara Gul</a>, <a href="https://publications.waset.org/abstracts/search?q=Nabeeha%20Areej"> Nabeeha Areej</a>, <a href="https://publications.waset.org/abstracts/search?q=Muhammad%20Asif%20Masood"> Muhammad Asif Masood</a>, <a href="https://publications.waset.org/abstracts/search?q=Hamna%20Imran"> Hamna Imran</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The universal use of PDF files has prompted hackers to use them for malicious intent by hiding malicious codes in their victim’s PDF machines. Machine learning has proven to be the most efficient in identifying benign files and detecting files with PDF malware. This paper has proposed an approach using a decision tree classifier with parameters. A modern, inclusive dataset CIC-Evasive-PDFMal2022, produced by Lockheed Martin’s Cyber Security wing is used. It is one of the most reliable datasets to use in this field. We designed a PDF malware detection system that achieved 99.2%. Comparing the suggested model to other cutting-edge models in the same study field, it has a great performance in detecting PDF malware. Accordingly, we provide the fastest, most reliable, and most efficient PDF Malware detection approach in this paper. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=PDF" title="PDF">PDF</a>, <a href="https://publications.waset.org/abstracts/search?q=PDF%20malware" title=" PDF malware"> PDF malware</a>, <a href="https://publications.waset.org/abstracts/search?q=decision%20tree%20classifier" title=" decision tree classifier"> decision tree classifier</a>, <a href="https://publications.waset.org/abstracts/search?q=random%20forest%20classifier" title=" random forest classifier"> random forest classifier</a> </p> <a href="https://publications.waset.org/abstracts/172206/a-machine-learning-approach-to-detecting-evasive-pdf-malware" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/172206.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">91</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">3621</span> Efficient Signal Detection Using QRD-M Based on Channel Condition in MIMO-OFDM System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jae-Jeong%20Kim">Jae-Jeong Kim</a>, <a href="https://publications.waset.org/abstracts/search?q=Ki-Ro%20Kim"> Ki-Ro Kim</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> In this paper, we propose an efficient signal detector that switches M parameter of QRD-M detection scheme is proposed for MIMO-OFDM system. The proposed detection scheme calculates the threshold by 1-norm condition number and then switches M parameter of QRD-M detection scheme according to channel information. If channel condition is bad, the parameter M is set to high value to increase the accuracy of detection. If channel condition is good, the parameter M is set to low value to reduce complexity of detection. Therefore, the proposed detection scheme has better trade off between BER performance and complexity than the conventional detection scheme. The simulation result shows that the complexity of proposed detection scheme is lower than QRD-M detection scheme with similar BER performance. <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=QRD-M" title=" QRD-M"> QRD-M</a>, <a href="https://publications.waset.org/abstracts/search?q=channel%20condition" title=" channel condition"> channel condition</a>, <a href="https://publications.waset.org/abstracts/search?q=BER" title=" BER"> BER</a> </p> <a href="https://publications.waset.org/abstracts/3518/efficient-signal-detection-using-qrd-m-based-on-channel-condition-in-mimo-ofdm-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/3518.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">370</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3620</span> Reduced Complexity of ML Detection Combined with DFE</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jae-Hyun%20Ro">Jae-Hyun Ro</a>, <a href="https://publications.waset.org/abstracts/search?q=Yong-Jun%20Kim"> Yong-Jun Kim</a>, <a href="https://publications.waset.org/abstracts/search?q=Chang-Bin%20Ha"> Chang-Bin Ha</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> In multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) systems, many detection schemes have been developed to improve the error performance and to reduce the complexity. Maximum likelihood (ML) detection has optimal error performance but it has very high complexity. Thus, this paper proposes reduced complexity of ML detection combined with decision feedback equalizer (DFE). The error performance of the proposed detection scheme is higher than the conventional DFE. But the complexity of the proposed scheme is lower than the conventional ML detection. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=detection" title="detection">detection</a>, <a href="https://publications.waset.org/abstracts/search?q=DFE" title=" DFE"> DFE</a>, <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=ML" title=" ML"> ML</a> </p> <a href="https://publications.waset.org/abstracts/42215/reduced-complexity-of-ml-detection-combined-with-dfe" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/42215.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">610</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">3619</span> Cigarette Smoke Detection Based on YOLOV3</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Wei%20Li">Wei Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Tuo%20Yang"> Tuo Yang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In order to satisfy the real-time and accurate requirements of cigarette smoke detection in complex scenes, a cigarette smoke detection technology based on the combination of deep learning and color features was proposed. Firstly, based on the color features of cigarette smoke, the suspicious cigarette smoke area in the image is extracted. Secondly, combined with the efficiency of cigarette smoke detection and the problem of network overfitting, a network model for cigarette smoke detection was designed according to YOLOV3 algorithm to reduce the false detection rate. The experimental results show that the method is feasible and effective, and the accuracy of cigarette smoke detection is up to 99.13%, which satisfies the requirements of real-time cigarette smoke detection in complex scenes. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=deep%20learning" title="deep learning">deep learning</a>, <a href="https://publications.waset.org/abstracts/search?q=computer%20vision" title=" computer vision"> computer vision</a>, <a href="https://publications.waset.org/abstracts/search?q=cigarette%20smoke%20detection" title=" cigarette smoke detection"> cigarette smoke detection</a>, <a href="https://publications.waset.org/abstracts/search?q=YOLOV3" title=" YOLOV3"> YOLOV3</a>, <a href="https://publications.waset.org/abstracts/search?q=color%20feature%20extraction" title=" color feature extraction"> color feature extraction</a> </p> <a href="https://publications.waset.org/abstracts/159151/cigarette-smoke-detection-based-on-yolov3" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/159151.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">87</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">3618</span> An Architecture for New Generation of Distributed Intrusion Detection System Based on Preventive Detection</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=H.%20Benmoussa">H. Benmoussa</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20A.%20El%20Kalam"> A. A. El Kalam</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Ait%20Ouahman"> A. Ait Ouahman</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The design and implementation of intrusion detection systems (IDS) remain an important area of research in the security of information systems. Despite the importance and reputation of the current intrusion detection systems, their efficiency and effectiveness remain limited as they should include active defense approach to allow anticipating and predicting intrusions before their occurrence. Consequently, they must be readapted. For this purpose we suggest a new generation of distributed intrusion detection system based on preventive detection approach and using intelligent and mobile agents. Our architecture benefits from mobile agent features and addresses some of the issues with centralized and hierarchical models. Also, it presents advantages in terms of increasing scalability and flexibility. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Intrusion%20Detection%20System%20%28IDS%29" title="Intrusion Detection System (IDS)">Intrusion Detection System (IDS)</a>, <a href="https://publications.waset.org/abstracts/search?q=preventive%20detection" title=" preventive detection"> preventive detection</a>, <a href="https://publications.waset.org/abstracts/search?q=mobile%20agents" title=" mobile agents"> mobile agents</a>, <a href="https://publications.waset.org/abstracts/search?q=distributed%20architecture" title=" distributed architecture"> distributed architecture</a> </p> <a href="https://publications.waset.org/abstracts/18239/an-architecture-for-new-generation-of-distributed-intrusion-detection-system-based-on-preventive-detection" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/18239.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">583</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">3617</span> Video Based Ambient Smoke Detection By Detecting Directional Contrast Decrease</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Omair%20Ghori">Omair Ghori</a>, <a href="https://publications.waset.org/abstracts/search?q=Anton%20Stadler"> Anton Stadler</a>, <a href="https://publications.waset.org/abstracts/search?q=Stefan%20Wilk"> Stefan Wilk</a>, <a href="https://publications.waset.org/abstracts/search?q=Wolfgang%20Effelsberg"> Wolfgang Effelsberg</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Fire-related incidents account for extensive loss of life and material damage. Quick and reliable detection of occurring fires has high real world implications. Whereas a major research focus lies on the detection of outdoor fires, indoor camera-based fire detection is still an open issue. Cameras in combination with computer vision helps to detect flames and smoke more quickly than conventional fire detectors. In this work, we present a computer vision-based smoke detection algorithm based on contrast changes and a multi-step classification. This work accelerates computer vision-based fire detection considerably in comparison with classical indoor-fire detection. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=contrast%20analysis" title="contrast analysis">contrast analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=early%20fire%20detection" title=" early fire detection"> early fire detection</a>, <a href="https://publications.waset.org/abstracts/search?q=video%20smoke%20detection" title=" video smoke detection"> video smoke detection</a>, <a href="https://publications.waset.org/abstracts/search?q=video%20surveillance" title=" video surveillance"> video surveillance</a> </p> <a href="https://publications.waset.org/abstracts/52006/video-based-ambient-smoke-detection-by-detecting-directional-contrast-decrease" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/52006.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">447</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3616</span> Intrusion Detection Techniques in NaaS in the Cloud: A Review </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rashid%20Mahmood">Rashid Mahmood</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The network as a service (NaaS) usage has been well-known from the last few years in the many applications, like mission critical applications. In the NaaS, prevention method is not adequate as the security concerned, so the detection method should be added to the security issues in NaaS. The authentication and encryption are considered the first solution of the NaaS problem whereas now these are not sufficient as NaaS use is increasing. In this paper, we are going to present the concept of intrusion detection and then survey some of major intrusion detection techniques in NaaS and aim to compare in some important fields. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=IDS" title="IDS">IDS</a>, <a href="https://publications.waset.org/abstracts/search?q=cloud" title=" cloud"> cloud</a>, <a href="https://publications.waset.org/abstracts/search?q=naas" title=" naas"> naas</a>, <a href="https://publications.waset.org/abstracts/search?q=detection" title=" detection"> detection</a> </p> <a href="https://publications.waset.org/abstracts/36475/intrusion-detection-techniques-in-naas-in-the-cloud-a-review" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/36475.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">320</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3615</span> Multichannel Object Detection with Event Camera</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rafael%20Iliasov">Rafael Iliasov</a>, <a href="https://publications.waset.org/abstracts/search?q=Alessandro%20Golkar"> Alessandro Golkar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Object detection based on event vision has been a dynamically growing field in computer vision for the last 16 years. In this work, we create multiple channels from a single event camera and propose an event fusion method (EFM) to enhance object detection in event-based vision systems. Each channel uses a different accumulation buffer to collect events from the event camera. We implement YOLOv7 for object detection, followed by a fusion algorithm. Our multichannel approach outperforms single-channel-based object detection by 0.7% in mean Average Precision (mAP) for detection overlapping ground truth with IOU = 0.5. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=event%20camera" title="event camera">event camera</a>, <a href="https://publications.waset.org/abstracts/search?q=object%20detection%20with%20multimodal%20inputs" title=" object detection with multimodal inputs"> object detection with multimodal inputs</a>, <a href="https://publications.waset.org/abstracts/search?q=multichannel%20fusion" title=" multichannel fusion"> multichannel fusion</a>, <a href="https://publications.waset.org/abstracts/search?q=computer%20vision" title=" computer vision"> computer vision</a> </p> <a href="https://publications.waset.org/abstracts/190247/multichannel-object-detection-with-event-camera" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/190247.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">27</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">3614</span> [Keynote]: No-Trust-Zone Architecture for Securing Supervisory Control and Data Acquisition</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Michael%20Okeke">Michael Okeke</a>, <a href="https://publications.waset.org/abstracts/search?q=Andrew%20Blyth"> Andrew Blyth</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Supervisory Control And Data Acquisition (SCADA) as the state of the art Industrial Control Systems (ICS) are used in many different critical infrastructures, from smart home to energy systems and from locomotives train system to planes. Security of SCADA systems is vital since many lives depend on it for daily activities and deviation from normal operation could be disastrous to the environment as well as lives. This paper describes how No-Trust-Zone (NTZ) architecture could be incorporated into SCADA Systems in order to reduce the chances of malicious intent. The architecture is made up of two distinctive parts which are; the field devices such as; sensors, PLCs pumps, and actuators. The second part of the architecture is designed following lambda architecture, which is made up of a detection algorithm based on Particle Swarm Optimization (PSO) and Hadoop framework for data processing and storage. Apache Spark will be a part of the lambda architecture for real-time analysis of packets for anomalies detection. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=industrial%20control%20system%20%28ics" title="industrial control system (ics">industrial control system (ics</a>, <a href="https://publications.waset.org/abstracts/search?q=no-trust-zone%20%28ntz%29" title=" no-trust-zone (ntz)"> no-trust-zone (ntz)</a>, <a href="https://publications.waset.org/abstracts/search?q=particle%20swarm%20optimisation%20%28pso%29" title=" particle swarm optimisation (pso)"> particle swarm optimisation (pso)</a>, <a href="https://publications.waset.org/abstracts/search?q=supervisory%20control%20and%20data%20acquisition%20%28scada%29" title=" supervisory control and data acquisition (scada)"> supervisory control and data acquisition (scada)</a>, <a href="https://publications.waset.org/abstracts/search?q=swarm%20intelligence%20%28SI%29" title=" swarm intelligence (SI)"> swarm intelligence (SI)</a> </p> <a href="https://publications.waset.org/abstracts/53994/keynote-no-trust-zone-architecture-for-securing-supervisory-control-and-data-acquisition" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/53994.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">345</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">3613</span> Securing Web Servers by the Intrusion Detection System (IDS)</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yousef%20Farhaoui">Yousef Farhaoui </a> </p> <p class="card-text"><strong>Abstract:</strong></p> An IDS is a tool which is used to improve the level of security. We present in this paper different architectures of IDS. We will also discuss measures that define the effectiveness of IDS and the very recent works of standardization and homogenization of IDS. At the end, we propose a new model of IDS called BiIDS (IDS Based on the two principles of detection) for securing web servers and applications by the Intrusion Detection System (IDS). <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=architectures" title=" architectures"> architectures</a>, <a href="https://publications.waset.org/abstracts/search?q=characteristic" title=" characteristic"> characteristic</a>, <a href="https://publications.waset.org/abstracts/search?q=tools" title=" tools"> tools</a>, <a href="https://publications.waset.org/abstracts/search?q=security" title=" security"> security</a>, <a href="https://publications.waset.org/abstracts/search?q=web%20server" title=" web server"> web server</a> </p> <a href="https://publications.waset.org/abstracts/13346/securing-web-servers-by-the-intrusion-detection-system-ids" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/13346.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">418</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">3612</span> Suggestion for Malware Detection Agent Considering Network Environment</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ji-Hoon%20Hong">Ji-Hoon Hong</a>, <a href="https://publications.waset.org/abstracts/search?q=Dong-Hee%20Kim"> Dong-Hee Kim</a>, <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=Tai-Myoung%20Chung"> Tai-Myoung Chung</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Smartphone users are increasing rapidly. Accordingly, many companies are running BYOD (Bring Your Own Device: Policies to bring private-smartphones to the company) policy to increase work efficiency. However, smartphones are always under the threat of malware, thus the company network that is connected smartphone is exposed to serious risks. Most smartphone malware detection techniques are to perform an independent detection (perform the detection of a single target application). In this paper, we analyzed a variety of intrusion detection techniques. Based on the results of analysis propose an agent using the network IDS. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=android%20malware%20detection" title="android malware detection">android malware detection</a>, <a href="https://publications.waset.org/abstracts/search?q=software-defined%20network" title=" software-defined network"> software-defined network</a>, <a href="https://publications.waset.org/abstracts/search?q=interaction%20environment" title=" interaction environment"> interaction environment</a>, <a href="https://publications.waset.org/abstracts/search?q=android%20malware%20detection" title=" android malware detection"> android malware detection</a>, <a href="https://publications.waset.org/abstracts/search?q=software-defined%20network" title=" software-defined network"> software-defined network</a>, <a href="https://publications.waset.org/abstracts/search?q=interaction%20environment" title=" interaction environment"> interaction environment</a> </p> <a href="https://publications.waset.org/abstracts/39330/suggestion-for-malware-detection-agent-considering-network-environment" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/39330.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">433</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">3611</span> Improved Skin Detection Using Colour Space and Texture</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Medjram%20Sofiane">Medjram Sofiane</a>, <a href="https://publications.waset.org/abstracts/search?q=Babahenini%20Mohamed%20Chaouki"> Babahenini Mohamed Chaouki</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohamed%20Benali%20Yamina"> Mohamed Benali Yamina</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Skin detection is an important task for computer vision systems. A good method for skin detection means a good and successful result of the system. The colour is a good descriptor that allows us to detect skin colour in the images, but because of lightings effects and objects that have a similar colour skin, skin detection becomes difficult. In this paper, we proposed a method using the YCbCr colour space for skin detection and lighting effects elimination, then we use the information of texture to eliminate the false regions detected by the YCbCr colour skin model. <p class="card-text"><strong>Keywords:</strong> <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=YCbCr" title=" YCbCr"> YCbCr</a>, <a href="https://publications.waset.org/abstracts/search?q=GLCM" title=" GLCM"> GLCM</a>, <a href="https://publications.waset.org/abstracts/search?q=texture" title=" texture"> texture</a>, <a href="https://publications.waset.org/abstracts/search?q=human%20skin" title=" human skin"> human skin</a> </p> <a href="https://publications.waset.org/abstracts/19039/improved-skin-detection-using-colour-space-and-texture" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/19039.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">459</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">3610</span> 3rd Generation Modular Execution: A Global Breakthrough in Modular Facility Construction System </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sean%20Bryner%20S.%20Rey">Sean Bryner S. Rey</a>, <a href="https://publications.waset.org/abstracts/search?q=Eric%20Tanjutco"> Eric Tanjutco</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Modular execution strategies are performed to address the various challenges of any projects and are implemented on each project phase that covers Engineering, Procurement, Fabrication and Construction. It was until the recent years that the intent to surpass mechanical modularization approach were conceptualized to give solution to much greater demands of project components such as site location and adverse weather condition, material sourcing, construction schedule, safety risks and overall plot layout and allocation. The intent of this paper is to introduce the 3rd Generation Modular Execution with an overview of its advantages on project execution and will give emphasis on Engineering, Construction, Operation and Maintenance. Most importantly, the paper will present the key differentiator of 3rd Gen modular execution against other conventional project execution and the merits it bears for the industry. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=3rd%20generation%20modular" title="3rd generation modular">3rd generation modular</a>, <a href="https://publications.waset.org/abstracts/search?q=process%20block" title=" process block"> process block</a>, <a href="https://publications.waset.org/abstracts/search?q=construction" title=" construction"> construction</a>, <a href="https://publications.waset.org/abstracts/search?q=operation%20%26%20maintenance" title=" operation & maintenance"> operation & maintenance</a> </p> <a href="https://publications.waset.org/abstracts/43879/3rd-generation-modular-execution-a-global-breakthrough-in-modular-facility-construction-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/43879.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">475</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">3609</span> Real-Time Detection of Space Manipulator Self-Collision</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Zhang%20Xiaodong">Zhang Xiaodong</a>, <a href="https://publications.waset.org/abstracts/search?q=Tang%20Zixin"> Tang Zixin</a>, <a href="https://publications.waset.org/abstracts/search?q=Liu%20Xin"> Liu Xin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In order to avoid self-collision of space manipulators during operation process, a real-time detection method is proposed in this paper. The manipulator is fitted into a cylinder enveloping surface, and then the detection algorithm of collision between cylinders is analyzed. The collision model of space manipulator self-links can be detected by using this algorithm in real-time detection during the operation process. To ensure security of the operation, a safety threshold is designed. The simulation and experiment results verify the effectiveness of the proposed algorithm for a 7-DOF space manipulator. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=space%20manipulator" title="space manipulator">space manipulator</a>, <a href="https://publications.waset.org/abstracts/search?q=collision%20detection" title=" collision detection"> collision detection</a>, <a href="https://publications.waset.org/abstracts/search?q=self-collision" title=" self-collision"> self-collision</a>, <a href="https://publications.waset.org/abstracts/search?q=the%20real-time%20collision%20detection" title=" the real-time collision detection"> the real-time collision detection</a> </p> <a href="https://publications.waset.org/abstracts/23258/real-time-detection-of-space-manipulator-self-collision" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/23258.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">469</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">3608</span> Iris Detection on RGB Image for Controlling Side Mirror</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Norzalina%20Othman">Norzalina Othman</a>, <a href="https://publications.waset.org/abstracts/search?q=Nurul%20Na%E2%80%99imy%20Wan"> Nurul Na’imy Wan</a>, <a href="https://publications.waset.org/abstracts/search?q=Azliza%20Mohd%20Rusli"> Azliza Mohd Rusli</a>, <a href="https://publications.waset.org/abstracts/search?q=Wan%20Noor%20Syahirah%20Meor%20Idris"> Wan Noor Syahirah Meor Idris</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Iris detection is a process where the position of the eyes is extracted from the face images. It is a current method used for many applications such as for security purpose and drowsiness detection. This paper proposes the use of eyes detection in controlling side mirror of motor vehicles. The eyes detection method aims to make driver easy to adjust the side mirrors automatically. The system will determine the midpoint coordinate of eyes detection on RGB (color) image and the input signal from y-coordinate will send it to controller in order to rotate the angle of side mirror on vehicle. The eye position was cropped and the coordinate of midpoint was successfully detected from the circle of iris detection using Viola Jones detection and circular Hough transform methods on RGB image. The coordinate of midpoint from the experiment are tested using controller to determine the angle of rotation on the side mirrors. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=iris%20detection" title="iris detection">iris detection</a>, <a href="https://publications.waset.org/abstracts/search?q=midpoint%20coordinates" title=" midpoint coordinates"> midpoint coordinates</a>, <a href="https://publications.waset.org/abstracts/search?q=RGB%20images" title=" RGB images"> RGB images</a>, <a href="https://publications.waset.org/abstracts/search?q=side%20mirror" title=" side mirror"> side mirror</a> </p> <a href="https://publications.waset.org/abstracts/8133/iris-detection-on-rgb-image-for-controlling-side-mirror" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/8133.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">423</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">3607</span> Automatic Vehicle Detection Using Circular Synthetic Aperture Radar Image</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Leping%20Chen">Leping Chen</a>, <a href="https://publications.waset.org/abstracts/search?q=Daoxiang%20An"> Daoxiang An</a>, <a href="https://publications.waset.org/abstracts/search?q=Xiaotao%20Huang"> Xiaotao Huang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Automatic vehicle detection using synthetic aperture radar (SAR) image has been widely researched, as well as using optical remote sensing images. However, most researches treat the detection as an independent problem, failing to make full use of SAR data information. In circular SAR (CSAR), the two long borders of vehicle will shrink if the imaging surface is set higher than the reference one. Based on above variance, an automatic vehicle detection using CSAR image is proposed to enhance detection ability under complex environment, such as vehicles’ closely packing, which confuses the detector. The detection method uses the multiple images generated by different height plane to obtain an energy-concentrated image for detecting and then uses the maximally stable extremal regions method (MSER) to detect vehicles. A result of vehicles’ detection is given to verify the effectiveness and correctness of proposed method. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=circular%20SAR" title="circular SAR">circular SAR</a>, <a href="https://publications.waset.org/abstracts/search?q=vehicle%20detection" title=" vehicle detection"> vehicle detection</a>, <a href="https://publications.waset.org/abstracts/search?q=automatic" title=" automatic"> automatic</a>, <a href="https://publications.waset.org/abstracts/search?q=imaging" title=" imaging"> imaging</a> </p> <a href="https://publications.waset.org/abstracts/84548/automatic-vehicle-detection-using-circular-synthetic-aperture-radar-image" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/84548.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">367</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">3606</span> Adaptive CFAR Analysis for Non-Gaussian Distribution</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bouchemha%20Amel">Bouchemha Amel</a>, <a href="https://publications.waset.org/abstracts/search?q=Chachoui%20Takieddine"> Chachoui Takieddine</a>, <a href="https://publications.waset.org/abstracts/search?q=H.%20Maalem"> H. Maalem</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Automatic detection of targets in a modern communication system RADAR is based primarily on the concept of adaptive CFAR detector. To have an effective detection, we must minimize the influence of disturbances due to the clutter. The detection algorithm adapts the CFAR detection threshold which is proportional to the average power of the clutter, maintaining a constant probability of false alarm. In this article, we analyze the performance of two variants of adaptive algorithms CA-CFAR and OS-CFAR and we compare the thresholds of these detectors in the marine environment (no-Gaussian) with a Weibull distribution. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=CFAR" title="CFAR">CFAR</a>, <a href="https://publications.waset.org/abstracts/search?q=threshold" title=" threshold"> threshold</a>, <a href="https://publications.waset.org/abstracts/search?q=clutter" title=" clutter"> clutter</a>, <a href="https://publications.waset.org/abstracts/search?q=distribution" title=" distribution"> distribution</a>, <a href="https://publications.waset.org/abstracts/search?q=Weibull" title=" Weibull"> Weibull</a>, <a href="https://publications.waset.org/abstracts/search?q=detection" title=" detection"> detection</a> </p> <a href="https://publications.waset.org/abstracts/21359/adaptive-cfar-analysis-for-non-gaussian-distribution" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/21359.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">588</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">3605</span> Intrusion Detection Techniques in Mobile Adhoc Networks: A Review</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rashid%20Mahmood">Rashid Mahmood</a>, <a href="https://publications.waset.org/abstracts/search?q=Muhammad%20Junaid%20Sarwar"> Muhammad Junaid Sarwar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Mobile ad hoc networks (MANETs) use has been well-known from the last few years in the many applications, like mission critical applications. In the (MANETS) prevention method is not adequate as the security concerned, so the detection method should be added to the security issues in (MANETs). The authentication and encryption is considered the first solution of the MANETs problem where as now these are not sufficient as MANET use is increasing. In this paper we are going to present the concept of intrusion detection and then survey some of major intrusion detection techniques in MANET and aim to comparing in some important fields. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=MANET" title="MANET">MANET</a>, <a href="https://publications.waset.org/abstracts/search?q=IDS" title=" IDS"> IDS</a>, <a href="https://publications.waset.org/abstracts/search?q=intrusions" title=" intrusions"> intrusions</a>, <a href="https://publications.waset.org/abstracts/search?q=signature" title=" signature"> signature</a>, <a href="https://publications.waset.org/abstracts/search?q=detection" title=" detection"> detection</a>, <a href="https://publications.waset.org/abstracts/search?q=prevention" title=" prevention"> prevention</a> </p> <a href="https://publications.waset.org/abstracts/32173/intrusion-detection-techniques-in-mobile-adhoc-networks-a-review" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/32173.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">379</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">3604</span> Plant Disease Detection Using Image Processing and Machine Learning</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sanskar">Sanskar</a>, <a href="https://publications.waset.org/abstracts/search?q=Abhinav%20Pal"> Abhinav Pal</a>, <a href="https://publications.waset.org/abstracts/search?q=Aryush%20Gupta"> Aryush Gupta</a>, <a href="https://publications.waset.org/abstracts/search?q=Sushil%20Kumar%20Mishra"> Sushil Kumar Mishra</a> </p> <p class="card-text"><strong>Abstract:</strong></p> One of the critical and tedious assignments in agricultural practices is the detection of diseases on vegetation. Agricultural production is very important in today’s economy because plant diseases are common, and early detection of plant diseases is important in agriculture. Automatic detection of such early diseases is useful because it reduces control efforts in large productive farms. Using digital image processing and machine learning algorithms, this paper presents a method for plant disease detection. Detection of the disease occurs on different leaves of the plant. The proposed system for plant disease detection is simple and computationally efficient, requiring less time than learning-based approaches. The accuracy of various plant and foliar diseases is calculated and presented in this paper. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=plant%20diseases" title="plant diseases">plant diseases</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20processing" title=" image processing"> image processing</a>, <a href="https://publications.waset.org/abstracts/search?q=deep%20learning" title=" deep learning"> deep learning</a> </p> <a href="https://publications.waset.org/abstracts/194420/plant-disease-detection-using-image-processing-and-machine-learning" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/194420.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">7</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">3603</span> A Comparative Study of Virus Detection Techniques</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sulaiman%20Al%20amro">Sulaiman Al amro</a>, <a href="https://publications.waset.org/abstracts/search?q=Ali%20Alkhalifah"> Ali Alkhalifah</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The growing number of computer viruses and the detection of zero day malware have been the concern for security researchers for a large period of time. Existing antivirus products (AVs) rely on detecting virus signatures which do not provide a full solution to the problems associated with these viruses. The use of logic formulae to model the behaviour of viruses is one of the most encouraging recent developments in virus research, which provides alternatives to classic virus detection methods. In this paper, we proposed a comparative study about different virus detection techniques. This paper provides the advantages and drawbacks of different detection techniques. Different techniques will be used in this paper to provide a discussion about what technique is more effective to detect computer viruses. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=computer%20viruses" title="computer viruses">computer viruses</a>, <a href="https://publications.waset.org/abstracts/search?q=virus%20detection" title=" virus detection"> virus detection</a>, <a href="https://publications.waset.org/abstracts/search?q=signature-based" title=" signature-based"> signature-based</a>, <a href="https://publications.waset.org/abstracts/search?q=behaviour-based" title=" behaviour-based"> behaviour-based</a>, <a href="https://publications.waset.org/abstracts/search?q=heuristic-based" title=" heuristic-based "> heuristic-based </a> </p> <a href="https://publications.waset.org/abstracts/28688/a-comparative-study-of-virus-detection-techniques" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/28688.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">484</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">3602</span> The Effect of Pixelation on Face Detection: Evidence from Eye Movements </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kaewmart%20Pongakkasira">Kaewmart Pongakkasira</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study investigated how different levels of pixelation affect face detection in natural scenes. Eye movements and reaction times, while observers searched for faces in natural scenes rendered in different ranges of pixels, were recorded. Detection performance for coarse visual detail at lower pixel size (3 x 3) was better than with very blurred detail carried by higher pixel size (9 x 9). The result is consistent with the notion that face detection relies on gross detail information of face-shape template, containing crude shape structure and features. In contrast, detection was impaired when face shape and features are obscured. However, it was considered that the degradation of scenic information might also contribute to the effect. In the next experiment, a more direct measurement of the effect of pixelation on face detection, only the embedded face photographs, but not the scene background, will be filtered. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=eye%20movements" title="eye movements">eye movements</a>, <a href="https://publications.waset.org/abstracts/search?q=face%20detection" title=" face detection"> face detection</a>, <a href="https://publications.waset.org/abstracts/search?q=face-shape%20information" title=" face-shape information"> face-shape information</a>, <a href="https://publications.waset.org/abstracts/search?q=pixelation" title=" pixelation"> pixelation</a> </p> <a href="https://publications.waset.org/abstracts/54704/the-effect-of-pixelation-on-face-detection-evidence-from-eye-movements" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/54704.pdf" target="_blank" class="btn btn-primary 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