Search results for: Zulkurnain Abdul-Malek

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Abdul-Malek</title> <meta name="description" content="Search results for: Zulkurnain Abdul-Malek"> <meta name="keywords" content="Zulkurnain Abdul-Malek"> <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 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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="Zulkurnain Abdul-Malek"> <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> 4</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: Zulkurnain Abdul-Malek</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">4</span> Characterization of Thermal Images Due to Aging of H.V Glass Insulators Using Thermographic Scanning</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nasir%20A.%20Al-Geelani">Nasir A. Al-Geelani</a>, <a href="https://publications.waset.org/abstracts/search?q=Zulkurnain%20Abdul-Malek"> Zulkurnain Abdul-Malek</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Afendi%20M.%20Piah"> M. Afendi M. Piah</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This research paper investigation is carried out in the laboratory on single units of transmission line glass insulator characterized by different thermal images, which aimed to find out the age of the insulators. The tests were carried out on virgin and aged insulators using the thermography scan. Various samples having different periods of aging 20, 15, and 5 years from a 132 kV transmission line which have exhibited a different degree of corrosion. The second group of insulator samples was relatively mild aged insulators, while the third group was lightly aged; finally, the fourth group was the brand new insulators. The results revealed a strong correlation between the aging and the thermal images captured by the infrared camera. This technique can be used to monitor the aging of high voltage insulators as a precaution to avoid disaster. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=glass%20insulator" title="glass insulator">glass insulator</a>, <a href="https://publications.waset.org/abstracts/search?q=infrared%20camera" title=" infrared camera"> infrared camera</a>, <a href="https://publications.waset.org/abstracts/search?q=corona%20diacharge" title=" corona diacharge"> corona diacharge</a>, <a href="https://publications.waset.org/abstracts/search?q=transmission%20lines" title=" transmission lines"> transmission lines</a>, <a href="https://publications.waset.org/abstracts/search?q=thermograpy" title=" thermograpy"> thermograpy</a>, <a href="https://publications.waset.org/abstracts/search?q=surface%20discharge" title=" surface discharge"> surface discharge</a> </p> <a href="https://publications.waset.org/abstracts/98959/characterization-of-thermal-images-due-to-aging-of-hv-glass-insulators-using-thermographic-scanning" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/98959.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">160</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">3</span> Characterization of InP Semiconductor Quantum Dot Laser Diode after Am-Be Neutron Irradiation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abdulmalek%20Marwan%20Rajkhan">Abdulmalek Marwan Rajkhan</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20S.%20Al%20Ghamdi"> M. S. Al Ghamdi</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohammed%20Damoum"> Mohammed Damoum</a>, <a href="https://publications.waset.org/abstracts/search?q=Essam%20Banoqitah"> Essam Banoqitah</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper is about the Am-Be neutron source irradiation of the InP Quantum Dot Laser diode. A QD LD was irradiated for 24 hours and 48 hours. The laser underwent IV characterization experiments before and after the first and second irradiations. A computer simulation using GAMOS helped in analyzing the given results from IV curves. The results showed an improvement in the QD LD series resistance, current density, and overall ideality factor at all measured temperatures. This is explained by the activation of the QD LD Indium composition to Strontium, ionization of the compound QD LD materials, and the energy deposited to the QD LD. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=quantum%20dot%20laser%20diode%20irradiation" title="quantum dot laser diode irradiation">quantum dot laser diode irradiation</a>, <a href="https://publications.waset.org/abstracts/search?q=effect%20of%20radiation%20on%20QD%20LD" title=" effect of radiation on QD LD"> effect of radiation on QD LD</a>, <a href="https://publications.waset.org/abstracts/search?q=Am-Be%20irradiation%20effect%20on%20SC%20QD%20LD" title=" Am-Be irradiation effect on SC QD LD"> Am-Be irradiation effect on SC QD LD</a> </p> <a href="https://publications.waset.org/abstracts/178642/characterization-of-inp-semiconductor-quantum-dot-laser-diode-after-am-be-neutron-irradiation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/178642.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">61</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">2</span> Two-Stage Flowshop Scheduling with Unsystematic Breakdowns</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fawaz%20Abdulmalek">Fawaz Abdulmalek</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The two-stage flowshop assembly scheduling problem is considered in this paper. There are more than one parallel machines at stage one and an assembly machine at stage two. The jobs will be processed into the flowshop based on Johnson rule and two extensions of Johnson rule. A simulation model of the two-stage flowshop is constructed where both machines at stage one are subject to random failures. Three simulation experiments will be conducted to test the effect of the three job ranking rules on the makespan. Johnson Largest heuristic outperformed both Johnson rule and Johnson Smallest heuristic for two performed experiments for all scenarios where each experiments having five scenarios. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=flowshop%20scheduling" title="flowshop scheduling">flowshop scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=random%20failures" title=" random failures"> random failures</a>, <a href="https://publications.waset.org/abstracts/search?q=johnson%20rule" title=" johnson rule"> johnson rule</a>, <a href="https://publications.waset.org/abstracts/search?q=simulation" title=" simulation"> simulation</a> </p> <a href="https://publications.waset.org/abstracts/72036/two-stage-flowshop-scheduling-with-unsystematic-breakdowns" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/72036.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">339</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">1</span> Prediction of Formation Pressure Using Artificial Intelligence Techniques</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abdulmalek%20Ahmed">Abdulmalek Ahmed</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Formation pressure is the main function that affects drilling operation economically and efficiently. Knowing the pore pressure and the parameters that affect it will help to reduce the cost of drilling process. Many empirical models reported in the literature were used to calculate the formation pressure based on different parameters. Some of these models used only drilling parameters to estimate pore pressure. Other models predicted the formation pressure based on log data. All of these models required different trends such as normal or abnormal to predict the pore pressure. Few researchers applied artificial intelligence (AI) techniques to predict the formation pressure by only one method or a maximum of two methods of AI. The objective of this research is to predict the pore pressure based on both drilling parameters and log data namely; weight on bit, rotary speed, rate of penetration, mud weight, bulk density, porosity and delta sonic time. A real field data is used to predict the formation pressure using five different artificial intelligence (AI) methods such as; artificial neural networks (ANN), radial basis function (RBF), fuzzy logic (FL), support vector machine (SVM) and functional networks (FN). All AI tools were compared with different empirical models. AI methods estimated the formation pressure by a high accuracy (high correlation coefficient and low average absolute percentage error) and outperformed all previous. The advantage of the new technique is its simplicity, which represented from its estimation of pore pressure without the need of different trends as compared to other models which require a two different trend (normal or abnormal pressure). Moreover, by comparing the AI tools with each other, the results indicate that SVM has the advantage of pore pressure prediction by its fast processing speed and high performance (a high correlation coefficient of 0.997 and a low average absolute percentage error of 0.14%). In the end, a new empirical correlation for formation pressure was developed using ANN method that can estimate pore pressure with a high precision (correlation coefficient of 0.998 and average absolute percentage error of 0.17%). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Artificial%20Intelligence%20%28AI%29" title="Artificial Intelligence (AI)">Artificial Intelligence (AI)</a>, <a href="https://publications.waset.org/abstracts/search?q=Formation%20pressure" title=" Formation pressure"> Formation pressure</a>, <a href="https://publications.waset.org/abstracts/search?q=Artificial%20Neural%20Networks%20%28ANN%29" title=" Artificial Neural Networks (ANN)"> Artificial Neural Networks (ANN)</a>, <a href="https://publications.waset.org/abstracts/search?q=Fuzzy%20Logic%20%28FL%29" title=" Fuzzy Logic (FL)"> Fuzzy Logic (FL)</a>, <a href="https://publications.waset.org/abstracts/search?q=Support%20Vector%20Machine%20%28SVM%29" title=" Support Vector Machine (SVM)"> Support Vector Machine (SVM)</a>, <a href="https://publications.waset.org/abstracts/search?q=Functional%20Networks%20%28FN%29" title=" Functional Networks (FN)"> Functional Networks (FN)</a>, <a href="https://publications.waset.org/abstracts/search?q=Radial%20Basis%20Function%20%28RBF%29" title=" Radial Basis Function (RBF)"> Radial Basis Function (RBF)</a> </p> <a href="https://publications.waset.org/abstracts/95931/prediction-of-formation-pressure-using-artificial-intelligence-techniques" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/95931.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">149</span> </span> </div> </div> </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 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Search results for: Zulkurnain Abdul-Malek