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simulated</title> <meta name="description" content="Search results for: Monte Carlo simulated"> <meta name="keywords" content="Monte Carlo simulated"> <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="Monte Carlo simulated"> <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> 2095</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: Monte Carlo simulated</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2095</span> 2D Monte Carlo Simulation of Grain Growth under Transient Conditions</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=K.%20R.%20Phaneesh">K. R. Phaneesh</a>, <a href="https://publications.waset.org/abstracts/search?q=Anirudh%20Bhat"> Anirudh Bhat</a>, <a href="https://publications.waset.org/abstracts/search?q=G.%20Mukherjee"> G. Mukherjee</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20T.%20Kashyap"> K. T. Kashyap</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Extensive Monte Carlo Potts model simulations were performed on 2D square lattice to investigate the effects of simulated higher temperatures effects on grain growth kinetics. A range of simulation temperatures (KTs) were applied on a matrix of size 10002 with Q-state 64, dispersed with a wide range of second phase particles, ranging from 0.001 to 0.1, and then run to 100,000 Monte Carlo steps. The average grain size, the largest grain size and the grain growth exponent were evaluated for all particle fractions and simulated temperatures. After evaluating several growth parameters, the critical temperature for a square lattice, with eight nearest neighbors, was found to be KTs = 0.4. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=average%20grain%20size" title="average grain size">average grain size</a>, <a href="https://publications.waset.org/abstracts/search?q=critical%20temperature" title=" critical temperature"> critical temperature</a>, <a href="https://publications.waset.org/abstracts/search?q=grain%20growth%20exponent" title=" grain growth exponent"> grain growth exponent</a>, <a href="https://publications.waset.org/abstracts/search?q=Monte%20Carlo%20steps" title=" Monte Carlo steps"> Monte Carlo steps</a> </p> <a href="https://publications.waset.org/abstracts/26332/2d-monte-carlo-simulation-of-grain-growth-under-transient-conditions" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/26332.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">523</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">2094</span> Simulation of the Large Hadrons Collisions Using Monte Carlo Tools</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=E.%20Al%20Daoud">E. Al Daoud</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In many cases, theoretical treatments are available for models for which there is no perfect physical realization. In this situation, the only possible test for an approximate theoretical solution is to compare with data generated from a computer simulation. In this paper, Monte Carlo tools are used to study and compare the elementary particles models. All the experiments are implemented using 10000 events, and the simulated energy is 13 TeV. The mean and the curves of several variables are calculated for each model using MadAnalysis 5. Anomalies in the results can be seen in the muons masses of the minimal supersymmetric standard model and the two Higgs doublet model. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Feynman%20rules" title="Feynman rules">Feynman rules</a>, <a href="https://publications.waset.org/abstracts/search?q=hadrons" title=" hadrons"> hadrons</a>, <a href="https://publications.waset.org/abstracts/search?q=Lagrangian" title=" Lagrangian"> Lagrangian</a>, <a href="https://publications.waset.org/abstracts/search?q=Monte%20Carlo" title=" Monte Carlo"> Monte Carlo</a>, <a href="https://publications.waset.org/abstracts/search?q=simulation" title=" simulation"> simulation</a> </p> <a href="https://publications.waset.org/abstracts/63496/simulation-of-the-large-hadrons-collisions-using-monte-carlo-tools" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/63496.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">317</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">2093</span> Statistical Study and Simulation of 140 Kv X– Ray Tube by Monte Carlo</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mehdi%20Homayouni">Mehdi Homayouni</a>, <a href="https://publications.waset.org/abstracts/search?q=Karim%20Adinehvand"> Karim Adinehvand</a>, <a href="https://publications.waset.org/abstracts/search?q=Bakhtiar%20Azadbakht"> Bakhtiar Azadbakht</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this study, we used Monte Carlo code (MCNP4C) that is a general method, for simulation, electron source and electric field, a disc source with 0.05 cm radius in direct of anode are used, radius of disc source show focal spot of X-ray tube that here is 0.05 cm. In this simulation, the anode is from tungsten with 18.9 g/cm3 density and angle of the anode is 18°. We simulated X-ray tube for 140 kv. For increasing of speed data acquisition, we use F5 tally. With determination the exact position of F5 tally in the program, outputs are acquired. In this spectrum the start point is about 0.02 Mev, the absorption edges are about 0.06 Mev and 0.07 Mev, and average energy is about 0.05 Mev. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=X-spectrum" title="X-spectrum">X-spectrum</a>, <a href="https://publications.waset.org/abstracts/search?q=simulation" title=" simulation"> simulation</a>, <a href="https://publications.waset.org/abstracts/search?q=Monte%20Carlo" title=" Monte Carlo"> Monte Carlo</a>, <a href="https://publications.waset.org/abstracts/search?q=tube" title=" tube"> tube</a> </p> <a href="https://publications.waset.org/abstracts/32738/statistical-study-and-simulation-of-140-kv-x-ray-tube-by-monte-carlo" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/32738.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">722</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">2092</span> Fusion Neutron Generator Dosimetry and Applications for Medical, Security, and Industry</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kaouther%20Bergaui">Kaouther Bergaui</a>, <a href="https://publications.waset.org/abstracts/search?q=Nafaa%20Reguigui"> Nafaa Reguigui</a>, <a href="https://publications.waset.org/abstracts/search?q=Charles%20Gary"> Charles Gary</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Characterization and the applications of deuterium-deuterium (DD) neutron generator developed by Adelphie technology and acquired by the National Centre of Nuclear Science and Technology (NCNST) were presented in this work. We study the performance of the neutron generator in terms of neutron yield, production efficiency, and the ionic current as a function of the acceleration voltage at various RF powers. We provide the design and optimization of the PGNAA chamber and thus give insight into the capabilities of the planned PGNAA facility. Additional non-destructive techniques were studied employing the DD neutron generator, such as PGNAA and neutron radiography: The PGNAA is used for determining the concentration of 10B in Si and SiO2 matrices by using a germanium detector HPGe and the results obtained are compared with PGNAA system using a Sodium Iodide detector (NaI (Tl)); Neutron radiography facility was tested and simulated, using a camera device CCD and simulated by the Monte Carlo code; and the explosive detection system (EDS) also simulated using the Monte Carlo code. The study allows us to show that the new models of DD neutron generators are feasible and that superior-quality neutron beams could be produced and used for various applications. The feasibility of Boron neutron capture therapy (BNCT) for cancer treatment using a neutron generator was assessed by optimizing Beam Shaping Assembly (BSA) on a phantom using Monte-Carlo (MCNP6) simulations. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=neutron%20generator%20deuterium-deuterium" title="neutron generator deuterium-deuterium">neutron generator deuterium-deuterium</a>, <a href="https://publications.waset.org/abstracts/search?q=Monte%20Carlo%20method" title=" Monte Carlo method"> Monte Carlo method</a>, <a href="https://publications.waset.org/abstracts/search?q=radiation" title=" radiation"> radiation</a>, <a href="https://publications.waset.org/abstracts/search?q=neutron%20flux" title=" neutron flux"> neutron flux</a>, <a href="https://publications.waset.org/abstracts/search?q=neutron%20activation%20analysis" title=" neutron activation analysis"> neutron activation analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=born" title=" born"> born</a>, <a href="https://publications.waset.org/abstracts/search?q=neutron%20radiography" title=" neutron radiography"> neutron radiography</a>, <a href="https://publications.waset.org/abstracts/search?q=explosive%20detection" title=" explosive detection"> explosive detection</a>, <a href="https://publications.waset.org/abstracts/search?q=BNCT" title=" BNCT"> BNCT</a> </p> <a href="https://publications.waset.org/abstracts/160335/fusion-neutron-generator-dosimetry-and-applications-for-medical-security-and-industry" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/160335.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">193</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">2091</span> Monte Carlo Pathwise Sensitivities for Barrier Options with Application to Coco-Bond Calibration</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Thomas%20Gerstner">Thomas Gerstner</a>, <a href="https://publications.waset.org/abstracts/search?q=Bastian%20von%20Harrach"> Bastian von Harrach</a>, <a href="https://publications.waset.org/abstracts/search?q=Daniel%20Roth"> Daniel Roth</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Monte Carlo pathwise sensitivities approach is well established for smooth payoff functions. In this work, we present a new Monte Carlo algorithm that is able to calculate the pathwise sensitivities for discontinuous payoff functions. Our main tool is the one-step survival idea of Glasserman and Staum. Although this technique yields to new terms per observation, while differentiating, the algorithm is still efficient. As an application, we use the results for a two-dimensional calibration of a Coco-Bond, which we model with different types of discretely monitored barrier options. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Monte%20Carlo" title="Monte Carlo">Monte Carlo</a>, <a href="https://publications.waset.org/abstracts/search?q=discretely%20monitored%20barrier%20options" title=" discretely monitored barrier options"> discretely monitored barrier options</a>, <a href="https://publications.waset.org/abstracts/search?q=pathwise%20sensitivities" title=" pathwise sensitivities"> pathwise sensitivities</a>, <a href="https://publications.waset.org/abstracts/search?q=Coco-Bond" title=" Coco-Bond"> Coco-Bond</a> </p> <a href="https://publications.waset.org/abstracts/77164/monte-carlo-pathwise-sensitivities-for-barrier-options-with-application-to-coco-bond-calibration" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/77164.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">358</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">2090</span> Monte Carlo Simulations of LSO/YSO for Dose Evaluation in Photon Beam Radiotherapy</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=H.%20Donya">H. Donya</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Monte Carlo (MC) techniques play a fundamental role in radiotherapy. A two non-water-equivalent of different media were used to evaluate the dose in water. For such purpose, Lu2SiO5 (LSO) and Y2SiO5 (YSO) orthosilicates scintillators are chosen for MC simulation using Penelope code. To get higher efficiency in dose calculation, variance reduction techniques are discussed. Overall results of this investigation ensured that the LSO/YSO bi-media a good combination to tackle over-response issue in dynamic photon radiotherapy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Lu2SiO5%20%28LSO%29%20and%20Y2SiO5%20%28YSO%29%20orthosilicates" title="Lu2SiO5 (LSO) and Y2SiO5 (YSO) orthosilicates">Lu2SiO5 (LSO) and Y2SiO5 (YSO) orthosilicates</a>, <a href="https://publications.waset.org/abstracts/search?q=Monte%20Carlo" title=" Monte Carlo"> Monte Carlo</a>, <a href="https://publications.waset.org/abstracts/search?q=correlated%20sampling" title=" correlated sampling"> correlated sampling</a>, <a href="https://publications.waset.org/abstracts/search?q=radiotherapy" title=" radiotherapy"> radiotherapy</a> </p> <a href="https://publications.waset.org/abstracts/43580/monte-carlo-simulations-of-lsoyso-for-dose-evaluation-in-photon-beam-radiotherapy" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/43580.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">407</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">2089</span> A Dose Distribution Approach Using Monte Carlo Simulation in Dosimetric Accuracy Calculation for Treating the Lung Tumor</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Md%20Abdullah%20Al%20Mashud">Md Abdullah Al Mashud</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Tariquzzaman"> M. Tariquzzaman</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Jahangir%20Alam"> M. Jahangir Alam</a>, <a href="https://publications.waset.org/abstracts/search?q=Tapan%20Kumar%20Godder"> Tapan Kumar Godder</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Mahbubur%20Rahman"> M. Mahbubur Rahman</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents a Monte Carlo (MC) method-based dose distributions on lung tumor for 6 MV photon beam to improve the dosimetric accuracy for cancer treatment. The polystyrene which is tissue equivalent material to the lung tumor density is used in this research. In the empirical calculations, TRS-398 formalism of IAEA has been used, and the setup was made according to the ICRU recommendations. The research outcomes were compared with the state-of-the-art experimental results. From the experimental results, it is observed that the proposed based approach provides more accurate results and improves the accuracy than the existing approaches. The average %variation between measured and TPS simulated values was obtained 1.337±0.531, which shows a substantial improvement comparing with the state-of-the-art technology. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=lung%20tumour" title="lung tumour">lung tumour</a>, <a href="https://publications.waset.org/abstracts/search?q=Monte%20Carlo" title=" Monte Carlo"> Monte Carlo</a>, <a href="https://publications.waset.org/abstracts/search?q=polystyrene" title=" polystyrene"> polystyrene</a>, <a href="https://publications.waset.org/abstracts/search?q=Elekta%20synergy" title=" Elekta synergy"> Elekta synergy</a>, <a href="https://publications.waset.org/abstracts/search?q=Monaco%20planning%20system" title=" Monaco planning system"> Monaco planning system</a> </p> <a href="https://publications.waset.org/abstracts/83204/a-dose-distribution-approach-using-monte-carlo-simulation-in-dosimetric-accuracy-calculation-for-treating-the-lung-tumor" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/83204.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">445</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">2088</span> Comparison of FNTD and OSLD Detectors' Responses to Light Ion Beams Using Monte Carlo Simulations and Exprimental Data</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20R.%20Akbari">M. R. Akbari</a>, <a href="https://publications.waset.org/abstracts/search?q=H.%20Yousefnia"> H. Yousefnia</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Ghasemi"> A. Ghasemi </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Al2O3:C,Mg fluorescent nuclear track detector (FNTD) and Al2O3:C optically stimulated luminescence detector (OSLD) are becoming two of the applied detectors in ion dosimetry. Therefore, the response of these detectors to hadron beams is highly of interest in radiation therapy (RT) using ion beams. In this study, these detectors' responses to proton and Helium-4 ion beams were compared using Monte Carlo simulations. The calculated data for proton beams were compared with Markus ionization chamber (IC) measurement (in water phantom) from M.D. Anderson proton therapy center. Monte Carlo simulations were performed via the FLUKA code (version 2011.2-17). The detectors were modeled in cylindrical shape at various depths of the water phantom without shading each other for obtaining relative depth dose in the phantom. Mono-energetic parallel ion beams in different incident energies (100 MeV/n to 250 MeV/n) were collided perpendicularly on the phantom surface. For proton beams, the results showed that the simulated detectors have over response relative to IC measurements in water phantom. In all cases, there were good agreements between simulated ion ranges in the water with calculated and experimental results reported by the literature. For proton, maximum peak to entrance dose ratio in the simulated water phantom was 4.3 compared with about 3 obtained from IC measurements. For He-4 ion beams, maximum peak to entrance ratio calculated by both detectors was less than 3.6 in all energies. Generally, it can be said that FLUKA is a good tool to calculate Al2O3:C,Mg FNTD and Al2O3:C OSLD detectors responses to therapeutic proton and He-4 ion beams. It can also calculate proton and He-4 ion ranges with a reasonable accuracy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=comparison" title="comparison">comparison</a>, <a href="https://publications.waset.org/abstracts/search?q=FNTD%20and%20OSLD%20detectors%20response" title=" FNTD and OSLD detectors response"> FNTD and OSLD detectors response</a>, <a href="https://publications.waset.org/abstracts/search?q=light%20ion%20beams" title=" light ion beams"> light ion beams</a>, <a href="https://publications.waset.org/abstracts/search?q=Monte%20Carlo%20simulations" title=" Monte Carlo simulations"> Monte Carlo simulations</a> </p> <a href="https://publications.waset.org/abstracts/7133/comparison-of-fntd-and-osld-detectors-responses-to-light-ion-beams-using-monte-carlo-simulations-and-exprimental-data" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/7133.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">343</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">2087</span> Comparative Study of Dose Calculation Accuracy in Bone Marrow Using Monte Carlo Method</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Marzieh%20Jafarzadeh">Marzieh Jafarzadeh</a>, <a href="https://publications.waset.org/abstracts/search?q=Fatemeh%20Rezaee"> Fatemeh Rezaee</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Introduction: The effect of ionizing radiation on human health can be effective for genomic integrity and cell viability. It also increases the risk of cancer and malignancy. Therefore, X-ray behavior and absorption dose calculation are considered. One of the applicable tools for calculating and evaluating the absorption dose in human tissues is Monte Carlo simulation. Monte Carlo offers a straightforward way to simulate and integrate, and because it is simple and straightforward, Monte Carlo is easy to use. The Monte Carlo BEAMnrc code is one of the most common diagnostic X-ray simulation codes used in this study. Method: In one of the understudy hospitals, a certain number of CT scan images of patients who had previously been imaged were extracted from the hospital database. BEAMnrc software was used for simulation. The simulation of the head of the device with the energy of 0.09 MeV with 500 million particles was performed, and the output data obtained from the simulation was applied for phantom construction using CT CREATE software. The percentage of depth dose (PDD) was calculated using STATE DOSE was then compared with international standard values. Results and Discussion: The ratio of surface dose to depth dose (D/Ds) in the measured energy was estimated to be about 4% to 8% for bone and 3% to 7% for bone marrow. Conclusion: MC simulation is an efficient and accurate method for simulating bone marrow and calculating the absorbed dose. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Monte%20Carlo" title="Monte Carlo">Monte Carlo</a>, <a href="https://publications.waset.org/abstracts/search?q=absorption%20dose" title=" absorption dose"> absorption dose</a>, <a href="https://publications.waset.org/abstracts/search?q=BEAMnrc" title=" BEAMnrc"> BEAMnrc</a>, <a href="https://publications.waset.org/abstracts/search?q=bone%20marrow" title=" bone marrow"> bone marrow</a> </p> <a href="https://publications.waset.org/abstracts/135306/comparative-study-of-dose-calculation-accuracy-in-bone-marrow-using-monte-carlo-method" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/135306.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">213</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">2086</span> Simulation of 140 Kv X– Ray Tube by MCNP4C Code </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Amin%20Sahebnasagh">Amin Sahebnasagh</a>, <a href="https://publications.waset.org/abstracts/search?q=Karim%20Adinehvand"> Karim Adinehvand</a>, <a href="https://publications.waset.org/abstracts/search?q=Bakhtiar%20Azadbakht"> Bakhtiar Azadbakht</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this study, we used Monte Carlo code (MCNP4C) that is a general method, for simulation, electron source and electric field, a disc source with 0.05 cm radius in direct of anode are used, radius of disc source show focal spot of x-ray tube that here is 0.05 cm. In this simulation, anode is from tungsten with 18.9 g/cm3 density and angle of anode is 180. we simulated x-ray tube for 140 kv. For increasing of speed data acquisition we use F5 tally. With determination the exact position of F5 tally in program, outputs are acquired. In this spectrum the start point is about 0.02 Mev, the absorption edges are about 0.06 Mev and 0.07 Mev and average energy is about 0.05 Mev. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=x-spectrum" title="x-spectrum">x-spectrum</a>, <a href="https://publications.waset.org/abstracts/search?q=simulation" title=" simulation"> simulation</a>, <a href="https://publications.waset.org/abstracts/search?q=Monte%20Carlo" title=" Monte Carlo"> Monte Carlo</a>, <a href="https://publications.waset.org/abstracts/search?q=MCNP4C%20code" title=" MCNP4C code"> MCNP4C code</a> </p> <a href="https://publications.waset.org/abstracts/23579/simulation-of-140-kv-x-ray-tube-by-mcnp4c-code" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/23579.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">646</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">2085</span> The Contribution of Edgeworth, Bootstrap and Monte Carlo Methods in Financial Data</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Edlira%20Donefski">Edlira Donefski</a>, <a href="https://publications.waset.org/abstracts/search?q=Tina%20Donefski"> Tina Donefski</a>, <a href="https://publications.waset.org/abstracts/search?q=Lorenc%20Ekonomi"> Lorenc Ekonomi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Edgeworth Approximation, Bootstrap, and Monte Carlo Simulations have considerable impacts on achieving certain results related to different problems taken into study. In our paper, we have treated a financial case related to the effect that has the components of a cash-flow of one of the most successful businesses in the world, as the financial activity, operational activity, and investment activity to the cash and cash equivalents at the end of the three-months period. To have a better view of this case, we have created a vector autoregression model, and after that, we have generated the impulse responses in the terms of asymptotic analysis (Edgeworth Approximation), Monte Carlo Simulations, and residual bootstrap based on the standard errors of every series created. The generated results consisted of the common tendencies for the three methods applied that consequently verified the advantage of the three methods in the optimization of the model that contains many variants. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=autoregression" title="autoregression">autoregression</a>, <a href="https://publications.waset.org/abstracts/search?q=bootstrap" title=" bootstrap"> bootstrap</a>, <a href="https://publications.waset.org/abstracts/search?q=edgeworth%20expansion" title=" edgeworth expansion"> edgeworth expansion</a>, <a href="https://publications.waset.org/abstracts/search?q=Monte%20Carlo%20method" title=" Monte Carlo method"> Monte Carlo method</a> </p> <a href="https://publications.waset.org/abstracts/135149/the-contribution-of-edgeworth-bootstrap-and-monte-carlo-methods-in-financial-data" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/135149.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">153</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2084</span> Monte Carlo Methods and Statistical Inference of Multitype Branching Processes</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ana%20Staneva">Ana Staneva</a>, <a href="https://publications.waset.org/abstracts/search?q=Vessela%20Stoimenova"> Vessela Stoimenova</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A parametric estimation of the MBP with Power Series offspring distribution family is considered in this paper. The MLE for the parameters is obtained in the case when the observable data are incomplete and consist only with the generation sizes of the family tree of MBP. The parameter estimation is calculated by using the Monte Carlo EM algorithm. The estimation for the posterior distribution and for the offspring distribution parameters are calculated by using the Bayesian approach and the Gibbs sampler. The article proposes various examples with bivariate branching processes together with computational results, simulation and an implementation using R. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bayesian" title="Bayesian">Bayesian</a>, <a href="https://publications.waset.org/abstracts/search?q=branching%20processes" title=" branching processes"> branching processes</a>, <a href="https://publications.waset.org/abstracts/search?q=EM%20algorithm" title=" EM algorithm"> EM algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=Gibbs%20sampler" title=" Gibbs sampler"> Gibbs sampler</a>, <a href="https://publications.waset.org/abstracts/search?q=Monte%20Carlo%20methods" title=" Monte Carlo methods"> Monte Carlo methods</a>, <a href="https://publications.waset.org/abstracts/search?q=statistical%20estimation" title=" statistical estimation"> statistical estimation</a> </p> <a href="https://publications.waset.org/abstracts/63592/monte-carlo-methods-and-statistical-inference-of-multitype-branching-processes" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/63592.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">2083</span> An Estimating Parameter of the Mean in Normal Distribution by Maximum Likelihood, Bayes, and Markov Chain Monte Carlo Methods</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Autcha%20Araveeporn">Autcha Araveeporn</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper is to compare the parameter estimation of the mean in normal distribution by Maximum Likelihood (ML), Bayes, and Markov Chain Monte Carlo (MCMC) methods. The ML estimator is estimated by the average of data, the Bayes method is considered from the prior distribution to estimate Bayes estimator, and MCMC estimator is approximated by Gibbs sampling from posterior distribution. These methods are also to estimate a parameter then the hypothesis testing is used to check a robustness of the estimators. Data are simulated from normal distribution with the true parameter of mean 2, and variance 4, 9, and 16 when the sample sizes is set as 10, 20, 30, and 50. From the results, it can be seen that the estimation of MLE, and MCMC are perceivably different from the true parameter when the sample size is 10 and 20 with variance 16. Furthermore, the Bayes estimator is estimated from the prior distribution when mean is 1, and variance is 12 which showed the significant difference in mean with variance 9 at the sample size 10 and 20. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bayes%20method" title="Bayes method">Bayes method</a>, <a href="https://publications.waset.org/abstracts/search?q=Markov%20chain%20Monte%20Carlo%20method" title=" Markov chain Monte Carlo method"> Markov chain Monte Carlo method</a>, <a href="https://publications.waset.org/abstracts/search?q=maximum%20likelihood%20method" title=" maximum likelihood method"> maximum likelihood method</a>, <a href="https://publications.waset.org/abstracts/search?q=normal%20distribution" title=" normal distribution"> normal distribution</a> </p> <a href="https://publications.waset.org/abstracts/51087/an-estimating-parameter-of-the-mean-in-normal-distribution-by-maximum-likelihood-bayes-and-markov-chain-monte-carlo-methods" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/51087.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">356</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2082</span> Using Monte Carlo Model for Simulation of Rented Housing in Mashhad, Iran</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Rahim%20Rahnama">Mohammad Rahim Rahnama</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The study employs Monte Carlo method for simulation of rented housing in Mashhad second largest city in Iran. A total number of 334 rental residential units in Mashhad, including both apartments and houses (villa), were randomly selected from advertisements placed in Khorasan Newspapers during the months of July and August of 2015. In order to simulate the monthly rent price, the rent index was calculated through combining the mortgage and the rent price. In the next step, the relation between the variables of the floor area and that of the number of bedrooms for each unit, in both apartments and houses(villa), was calculated through multivariate regression using SPSS and was coded in XML. The initial model was called using simulation button in SPSS and was simulated using triangular and binominal algorithms. The findings revealed that the average simulated rental index was 548.5$ per month. Calculating the sensitivity of rental index to a number of bedrooms we found that firstly, 97% of units have three bedrooms, and secondly as the number of bedrooms increases from one to three, for the rent price of less than 200$, the percentage of units having one bedroom decreases from 10% to 0. Contrariwise, for units with the rent price of more than 571.4$, the percentage of bedrooms increases from 37% to 48%. In the light of these findings, it becomes clear that planning to build rental residential units, overseeing the rent prices, and granting subsidies to rental residential units, for apartments with two bedrooms, present a felicitous policy for regulating residential units in Mashhad. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mashhad" title="Mashhad">Mashhad</a>, <a href="https://publications.waset.org/abstracts/search?q=Monte%20Carlo" title=" Monte Carlo"> Monte Carlo</a>, <a href="https://publications.waset.org/abstracts/search?q=simulation" title=" simulation"> simulation</a>, <a href="https://publications.waset.org/abstracts/search?q=rent%20price" title=" rent price"> rent price</a>, <a href="https://publications.waset.org/abstracts/search?q=residential%20unit" title=" residential unit"> residential unit</a> </p> <a href="https://publications.waset.org/abstracts/62954/using-monte-carlo-model-for-simulation-of-rented-housing-in-mashhad-iran" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/62954.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">275</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">2081</span> Study of Transport in Electronic Devices with Stochastic Monte Carlo Method: Modeling and Simulation along with Submicron Gate (Lg=0.5um)</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=N.%20Massoum">N. Massoum</a>, <a href="https://publications.waset.org/abstracts/search?q=B.%20Bouazza"> B. Bouazza</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we have developed a numerical simulation model to describe the electrical properties of GaInP MESFET with submicron gate (Lg = 0.5 µm). This model takes into account the three-dimensional (3D) distribution of the load in the short channel and the law effect of mobility as a function of electric field. Simulation software based on a stochastic method such as Monte Carlo has been established. The results are discussed and compared with those of the experiment. The result suggests experimentally that, in a very small gate length in our devices (smaller than 40 nm), short-channel tunneling explains the degradation of transistor performance, which was previously enhanced by velocity overshoot. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Monte%20Carlo%20simulation" title="Monte Carlo simulation">Monte Carlo simulation</a>, <a href="https://publications.waset.org/abstracts/search?q=transient%20electron%20transport" title=" transient electron transport"> transient electron transport</a>, <a href="https://publications.waset.org/abstracts/search?q=MESFET%20device" title=" MESFET device"> MESFET device</a>, <a href="https://publications.waset.org/abstracts/search?q=simulation%20software" title=" simulation software"> simulation software</a> </p> <a href="https://publications.waset.org/abstracts/19931/study-of-transport-in-electronic-devices-with-stochastic-monte-carlo-method-modeling-and-simulation-along-with-submicron-gate-lg05um" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/19931.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">2080</span> Kinetic Monte Carlo Simulation of ZnSe Homoepitaxial Growth and Characterization</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hamid%20Khachab">Hamid Khachab</a>, <a href="https://publications.waset.org/abstracts/search?q=Yamani%20Abdelkafi"> Yamani Abdelkafi</a>, <a href="https://publications.waset.org/abstracts/search?q=Mouna%20Barhmi"> Mouna Barhmi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The epitaxial growth has great important in the fabricate of the new semi-conductors devices and upgrading many factors, such as the quality of crystallization and efficiency with their deferent types and the most effective epitaxial technique is the molecular beam epitaxial. The MBE growth modeling allows to confirm the experiments results out by atomic beam and to analyze the microscopic phenomena. In of our work, we determined the growth processes specially the ZnSe epitaxial technique by Kinetic Monte Carlo method and we also give observations that are made in real time at the growth temperature using reflection high energy electron diffraction (RHEED) and photoemission current. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=molecular%20beam%20epitaxy" title="molecular beam epitaxy">molecular beam epitaxy</a>, <a href="https://publications.waset.org/abstracts/search?q=II-VI" title=" II-VI"> II-VI</a>, <a href="https://publications.waset.org/abstracts/search?q=morpholy" title=" morpholy"> morpholy</a>, <a href="https://publications.waset.org/abstracts/search?q=photoemission" title=" photoemission"> photoemission</a>, <a href="https://publications.waset.org/abstracts/search?q=RHEED" title=" RHEED"> RHEED</a>, <a href="https://publications.waset.org/abstracts/search?q=simulation" title=" simulation"> simulation</a>, <a href="https://publications.waset.org/abstracts/search?q=kinetic%20Monte%20Carlo" title=" kinetic Monte Carlo"> kinetic Monte Carlo</a>, <a href="https://publications.waset.org/abstracts/search?q=ZnSe" title=" ZnSe"> ZnSe</a> </p> <a href="https://publications.waset.org/abstracts/20695/kinetic-monte-carlo-simulation-of-znse-homoepitaxial-growth-and-characterization" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/20695.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">490</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">2079</span> A Novel Meta-Heuristic Algorithm Based on Cloud Theory for Redundancy Allocation Problem under Realistic Condition</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=H.%20Mousavi">H. Mousavi</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Sharifi"> M. Sharifi</a>, <a href="https://publications.waset.org/abstracts/search?q=H.%20Pourvaziri"> H. Pourvaziri</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Redundancy Allocation Problem (RAP) is a well-known mathematical problem for modeling series-parallel systems. It is a combinatorial optimization problem which focuses on determining an optimal assignment of components in a system design. In this paper, to be more practical, we have considered the problem of redundancy allocation of series system with interval valued reliability of components. Therefore, during the search process, the reliabilities of the components are considered as a stochastic variable with a lower and upper bounds. In order to optimize the problem, we proposed a simulated annealing based on cloud theory (CBSAA). Also, the Monte Carlo simulation (MCS) is embedded to the CBSAA to handle the random variable components’ reliability. This novel approach has been investigated by numerical examples and the experimental results have shown that the CBSAA combining MCS is an efficient tool to solve the RAP of systems with interval-valued component reliabilities. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=redundancy%20allocation%20problem" title="redundancy allocation problem">redundancy allocation problem</a>, <a href="https://publications.waset.org/abstracts/search?q=simulated%20annealing" title=" simulated annealing"> simulated annealing</a>, <a href="https://publications.waset.org/abstracts/search?q=cloud%20theory" title=" cloud theory"> cloud theory</a>, <a href="https://publications.waset.org/abstracts/search?q=monte%20carlo%20simulation" title=" monte carlo simulation"> monte carlo simulation</a> </p> <a href="https://publications.waset.org/abstracts/33681/a-novel-meta-heuristic-algorithm-based-on-cloud-theory-for-redundancy-allocation-problem-under-realistic-condition" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/33681.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">412</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">2078</span> Simulation as a Problem-Solving Spotter for System Reliability</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Wheyming%20Tina%20Song">Wheyming Tina Song</a>, <a href="https://publications.waset.org/abstracts/search?q=Chi-Hao%20Hong"> Chi-Hao Hong</a>, <a href="https://publications.waset.org/abstracts/search?q=Peisyuan%20Lin"> Peisyuan Lin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> An important performance measure for stochastic manufacturing networks is the system reliability, defined as the probability that the production output meets or exceeds a specified demand. The system parameters include the capacity of each workstation and numbers of the conforming parts produced in each workstation. We establish that eighteen archival publications, containing twenty-one examples, provide incorrect values of the system reliability. The author recently published the Song Rule, which provides the correct analytical system-reliability value; it is, however, computationally inefficient for large networks. In this paper, we use Monte Carlo simulation (implemented in C and Flexsim) to provide estimates for the above-mentioned twenty-one examples. The simulation estimates are consistent with the analytical solution for small networks but is computationally efficient for large networks. We argue here for three advantages of Monte Carlo simulation: (1) understanding stochastic systems, (2) validating analytical results, and (3) providing estimates even when analytical and numerical approaches are overly expensive in computation. Monte Carlo simulation could have detected the published analysis errors. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Monte%20Carlo%20simulation" title="Monte Carlo simulation">Monte Carlo simulation</a>, <a href="https://publications.waset.org/abstracts/search?q=analytical%20results" title=" analytical results"> analytical results</a>, <a href="https://publications.waset.org/abstracts/search?q=leading%20digit%20rule" title=" leading digit rule"> leading digit rule</a>, <a href="https://publications.waset.org/abstracts/search?q=standard%20error" title=" standard error"> standard error</a> </p> <a href="https://publications.waset.org/abstracts/66317/simulation-as-a-problem-solving-spotter-for-system-reliability" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/66317.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">362</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">2077</span> Dynamic Fault Tree Analysis of Dynamic Positioning System through Monte Carlo Approach</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=A.%20S.%20Cheliyan">A. S. Cheliyan</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20K.%20Bhattacharyya"> S. K. Bhattacharyya </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Dynamic Positioning System (DPS) is employed in marine vessels of the offshore oil and gas industry. It is a computer controlled system to automatically maintain a ship’s position and heading by using its own thrusters. Reliability assessment of the same can be analyzed through conventional fault tree. However, the complex behaviour like sequence failure, redundancy management and priority of failing of events cannot be analyzed by the conventional fault trees. The Dynamic Fault Tree (DFT) addresses these shortcomings of conventional Fault Tree by defining additional gates called dynamic gates. Monte Carlo based simulation approach has been adopted for the dynamic gates. This method of realistic modeling of DPS gives meaningful insight into the system reliability and the ability to improve the same. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=dynamic%20positioning%20system" title="dynamic positioning system">dynamic positioning system</a>, <a href="https://publications.waset.org/abstracts/search?q=dynamic%20fault%20tree" title=" dynamic fault tree"> dynamic fault tree</a>, <a href="https://publications.waset.org/abstracts/search?q=Monte%20Carlo%20simulation" title=" Monte Carlo simulation"> Monte Carlo simulation</a>, <a href="https://publications.waset.org/abstracts/search?q=reliability%20assessment" title=" reliability assessment "> reliability assessment </a> </p> <a href="https://publications.waset.org/abstracts/58683/dynamic-fault-tree-analysis-of-dynamic-positioning-system-through-monte-carlo-approach" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/58683.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">773</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">2076</span> A Computational Study of the Electron Transport in HgCdTe Bulk Semiconductor</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=N.%20Dahbi">N. Dahbi</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Daoudi"> M. Daoudi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper deals with the use of computational method based on Monte Carlo simulation in order to investigate the transport phenomena of the electron in HgCdTe narrow band gap semiconductor. Via this method we can evaluate the time dependence of the transport parameters: velocity, energy and mobility of electrons through matter (HgCdTe). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Monte%20Carlo" title="Monte Carlo">Monte Carlo</a>, <a href="https://publications.waset.org/abstracts/search?q=transport%20parameters" title=" transport parameters"> transport parameters</a>, <a href="https://publications.waset.org/abstracts/search?q=HgCdTe" title=" HgCdTe"> HgCdTe</a>, <a href="https://publications.waset.org/abstracts/search?q=computational%20mechanics" title=" computational mechanics"> computational mechanics</a> </p> <a href="https://publications.waset.org/abstracts/4221/a-computational-study-of-the-electron-transport-in-hgcdte-bulk-semiconductor" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/4221.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">2075</span> A Strategy for the Application of Second-Order Monte Carlo Algorithms to Petroleum Exploration and Production Projects</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Obioma%20Uche">Obioma Uche</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Due to the recent volatility in oil & gas prices as well as increased development of non-conventional resources, it has become even more essential to critically evaluate the profitability of petroleum prospects prior to making any investment decisions. Traditionally, simple Monte Carlo (MC) algorithms have been used to randomly sample probability distributions of economic and geological factors (e.g. price, OPEX, CAPEX, reserves, productive life, etc.) in order to obtain probability distributions for profitability metrics such as Net Present Value (NPV). In recent years, second-order MC algorithms have been shown to offer an advantage over simple MC techniques due to the added consideration of uncertainties associated with the probability distributions of the relevant variables. Here, a strategy for the application of the second-order MC technique to a case study is demonstrated to analyze its effectiveness as a tool for portfolio management. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Monte%20Carlo%20algorithms" title="Monte Carlo algorithms">Monte Carlo algorithms</a>, <a href="https://publications.waset.org/abstracts/search?q=portfolio%20management" title=" portfolio management"> portfolio management</a>, <a href="https://publications.waset.org/abstracts/search?q=profitability" title=" profitability"> profitability</a>, <a href="https://publications.waset.org/abstracts/search?q=risk%20analysis" title=" risk analysis"> risk analysis</a> </p> <a href="https://publications.waset.org/abstracts/56718/a-strategy-for-the-application-of-second-order-monte-carlo-algorithms-to-petroleum-exploration-and-production-projects" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/56718.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">332</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">2074</span> Evaluation of Reliability Indices Using Monte Carlo Simulation Accounting Time to Switch</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sajjad%20Asefi">Sajjad Asefi</a>, <a href="https://publications.waset.org/abstracts/search?q=Hossein%20Afrakhte"> Hossein Afrakhte</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents the evaluation of reliability indices of an electrical distribution system using Monte Carlo simulation technique accounting Time To Switch (TTS) for each section. In this paper, the distribution system has been assumed by accounting random repair time omission. For simplicity, we have assumed the reliability analysis to be based on exponential law. Each segment has a specified rate of failure (λ) and repair time (r) which will give us the mean up time and mean down time of each section in distribution system. After calculating the modified mean up time (MUT) in years, mean down time (MDT) in hours and unavailability (U) in h/year, TTS have been added to the time which the system is not available, i.e. MDT. In this paper, we have assumed the TTS to be a random variable with Log-Normal distribution. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=distribution%20system" title="distribution system">distribution system</a>, <a href="https://publications.waset.org/abstracts/search?q=Monte%20Carlo%20simulation" title=" Monte Carlo simulation"> Monte Carlo simulation</a>, <a href="https://publications.waset.org/abstracts/search?q=reliability" title=" reliability"> reliability</a>, <a href="https://publications.waset.org/abstracts/search?q=repair%20time" title=" repair time"> repair time</a>, <a href="https://publications.waset.org/abstracts/search?q=time%20to%20switch%20%28TTS%29" title=" time to switch (TTS)"> time to switch (TTS)</a> </p> <a href="https://publications.waset.org/abstracts/75199/evaluation-of-reliability-indices-using-monte-carlo-simulation-accounting-time-to-switch" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/75199.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">426</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">2073</span> Ethanol Chlorobenzene Dosimetr Usage for Measuring Dose of the Intraoperative Linear Electron Accelerator System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mojtaba%20Barzegar">Mojtaba Barzegar</a>, <a href="https://publications.waset.org/abstracts/search?q=Alireza%20Shirazi"> Alireza Shirazi</a>, <a href="https://publications.waset.org/abstracts/search?q=Saied%20Rabi%20Mahdavi"> Saied Rabi Mahdavi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Intraoperative radiation therapy (IORT) is an innovative treatment modality that the delivery of a large single dose of radiation to the tumor bed during the surgery. The radiotherapy success depends on the absorbed dose delivered to the tumor. The achievement better accuracy in patient treatment depends upon the measured dose by standard dosimeter such as ionization chamber, but because of the high density of electric charge/pulse produced by the accelerator in the ionization chamber volume, the standard correction factor for ion recombination Ksat calculated with the classic two-voltage method is overestimated so the use of dose/pulse independent dosimeters such as chemical Fricke and ethanol chlorobenzene (ECB) dosimeters have been suggested. Dose measurement is usually calculated and calibrated in the Zmax. Ksat calculated by comparison of ion chamber response and ECB dosimeter at each applicator degree, size, and dose. The relative output factors for IORT applicators have been calculated and compared with experimentally determined values and the results simulated by Monte Carlo software. The absorbed doses have been calculated and measured with statistical uncertainties less than 0.7% and 2.5% consecutively. The relative differences between calculated and measured OF’s were up to 2.5%, for major OF’s the agreement was better. In these conditions, together with the relative absorbed dose calculations, the OF’s could be considered as an indication that the IORT electron beams have been well simulated. These investigations demonstrate the utility of the full Monte Carlo simulation of accelerator head with ECB dosimeter allow us to obtain detailed information of clinical IORT beams. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=intra%20operative%20radiotherapy" title="intra operative radiotherapy">intra operative radiotherapy</a>, <a href="https://publications.waset.org/abstracts/search?q=ethanol%20chlorobenzene" title=" ethanol chlorobenzene"> ethanol chlorobenzene</a>, <a href="https://publications.waset.org/abstracts/search?q=ksat" title=" ksat"> ksat</a>, <a href="https://publications.waset.org/abstracts/search?q=output%20factor" title=" output factor"> output factor</a>, <a href="https://publications.waset.org/abstracts/search?q=monte%20carlo%20simulation" title=" monte carlo simulation "> monte carlo simulation </a> </p> <a href="https://publications.waset.org/abstracts/29851/ethanol-chlorobenzene-dosimetr-usage-for-measuring-dose-of-the-intraoperative-linear-electron-accelerator-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/29851.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">479</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">2072</span> Microdosimetry in Biological Cells: A Monte Carlo Method </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hamidreza%20Jabal%20Ameli">Hamidreza Jabal Ameli</a>, <a href="https://publications.waset.org/abstracts/search?q=Anahita%20Movahedi"> Anahita Movahedi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Purpose: In radionuclide therapy, radioactive atoms are coupled to monoclonal antibodies (mAbs) for treating cancer tumor while limiting radiation to healthy tissues. We know that tumoral and normal tissues are not equally sensitive to radiation. In fact, biological effects such as cellular repair processes or the presence of less radiosensitive cells such as hypoxic cells should be taken account. For this reason, in this paper, we want to calculate biological effect dose (BED) inside tumoral area and healthy cells around tumors. Methods: In this study, deposited doses of a radionuclide, gold-198, inside cells lattice and surrounding healthy tissues were calculated with Monte Carlo method. The elemental compositions and density of malignant and healthy tissues were obtained from ICRU Report 44. For reaching to real condition of oxygen effects, the necrosis and hypoxia area inside tumors has been assessed. Results: With regard to linear-quadratic expression which was defined in Monte Carlo, results showed that a large amount of BED is deposited in the well-oxygenated part of the hypoxia area compared to necrosis area. Moreover, there is a significant difference between the curves of absorbed dose with BED and without BED. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=biological%20dose" title="biological dose">biological dose</a>, <a href="https://publications.waset.org/abstracts/search?q=monte%20carlo" title=" monte carlo"> monte carlo</a>, <a href="https://publications.waset.org/abstracts/search?q=hypoxia" title=" hypoxia"> hypoxia</a>, <a href="https://publications.waset.org/abstracts/search?q=radionuclide%20therapy" title=" radionuclide therapy"> radionuclide therapy</a> </p> <a href="https://publications.waset.org/abstracts/20538/microdosimetry-in-biological-cells-a-monte-carlo-method" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/20538.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">487</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">2071</span> An Insite to the Probabilistic Assessment of Reserves in Conventional Reservoirs</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sai%20%20Sudarshan">Sai Sudarshan</a>, <a href="https://publications.waset.org/abstracts/search?q=Harsh%20Vyas"> Harsh Vyas</a>, <a href="https://publications.waset.org/abstracts/search?q=Riddhiman%20%20Sherlekar"> Riddhiman Sherlekar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The oil and gas industry has been unwilling to adopt stochastic definition of reserves. Nevertheless, Monte Carlo simulation methods have gained acceptance by engineers, geoscientists and other professionals who want to evaluate prospects or otherwise analyze problems that involve uncertainty. One of the common applications of Monte Carlo simulation is the estimation of recoverable hydrocarbon from a reservoir.Monte Carlo Simulation makes use of random samples of parameters or inputs to explore the behavior of a complex system or process. It finds application whenever one needs to make an estimate, forecast or decision where there is significant uncertainty. First, the project focuses on performing Monte-Carlo Simulation on a given data set using U. S Department of Energy’s MonteCarlo Software, which is a freeware e&p tool. Further, an algorithm for simulation has been developed for MATLAB and program performs simulation by prompting user for input distributions and parameters associated with each distribution (i.e. mean, st.dev, min., max., most likely, etc.). It also prompts user for desired probability for which reserves are to be calculated. The algorithm so developed and tested in MATLAB further finds implementation in Python where existing libraries on statistics and graph plotting have been imported to generate better outcome. With PyQt designer, codes for a simple graphical user interface have also been written. The graph so plotted is then validated with already available results from U.S DOE MonteCarlo Software. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=simulation" title="simulation">simulation</a>, <a href="https://publications.waset.org/abstracts/search?q=probability" title=" probability"> probability</a>, <a href="https://publications.waset.org/abstracts/search?q=confidence%20interval" title=" confidence interval"> confidence interval</a>, <a href="https://publications.waset.org/abstracts/search?q=sensitivity%20analysis" title=" sensitivity analysis"> sensitivity analysis</a> </p> <a href="https://publications.waset.org/abstracts/53559/an-insite-to-the-probabilistic-assessment-of-reserves-in-conventional-reservoirs" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/53559.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">382</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2070</span> Estimation of Normalized Glandular Doses Using a Three-Layer Mammographic Phantom </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kuan-Jen%20Lai">Kuan-Jen Lai</a>, <a href="https://publications.waset.org/abstracts/search?q=Fang-Yi%20Lin"> Fang-Yi Lin</a>, <a href="https://publications.waset.org/abstracts/search?q=Shang-Rong%20Huang"> Shang-Rong Huang</a>, <a href="https://publications.waset.org/abstracts/search?q=Yun-Zheng%20Zeng"> Yun-Zheng Zeng</a>, <a href="https://publications.waset.org/abstracts/search?q=Po-Chieh%20Hsu"> Po-Chieh Hsu</a>, <a href="https://publications.waset.org/abstracts/search?q=Jay%20Wu"> Jay Wu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The normalized glandular dose (DgN) estimates the energy deposition of mammography in clinical practice. The Monte Carlo simulations frequently use uniformly mixed phantom for calculating the conversion factor. However, breast tissues are not uniformly distributed, leading to errors of conversion factor estimation. This study constructed a three-layer phantom to estimated more accurate of normalized glandular dose. In this study, MCNP code (Monte Carlo N-Particles code) was used to create the geometric structure. We simulated three types of target/filter combinations (Mo/Mo, Mo/Rh, Rh/Rh), six voltages (25 ~ 35 kVp), six HVL parameters and nine breast phantom thicknesses (2 ~ 10 cm) for the three-layer mammographic phantom. The conversion factor for 25%, 50% and 75% glandularity was calculated. The error of conversion factors compared with the results of the American College of Radiology (ACR) was within 6%. For Rh/Rh, the difference was within 9%. The difference between the 50% average glandularity and the uniform phantom was 7.1% ~ -6.7% for the Mo/Mo combination, voltage of 27 kVp, half value layer of 0.34 mmAl, and breast thickness of 4 cm. According to the simulation results, the regression analysis found that the three-layer mammographic phantom at 0% ~ 100% glandularity can be used to accurately calculate the conversion factors. The difference in glandular tissue distribution leads to errors of conversion factor calculation. The three-layer mammographic phantom can provide accurate estimates of glandular dose in clinical practice. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Monte%20Carlo%20simulation" title="Monte Carlo simulation">Monte Carlo simulation</a>, <a href="https://publications.waset.org/abstracts/search?q=mammography" title=" mammography"> mammography</a>, <a href="https://publications.waset.org/abstracts/search?q=normalized%20glandular%20dose" title=" normalized glandular dose"> normalized glandular dose</a>, <a href="https://publications.waset.org/abstracts/search?q=glandularity" title=" glandularity"> glandularity</a> </p> <a href="https://publications.waset.org/abstracts/97111/estimation-of-normalized-glandular-doses-using-a-three-layer-mammographic-phantom" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/97111.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">189</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">2069</span> Simulation of Gamma Rays Attenuation Coefficient for Some common Shielding Materials Using Monte Carlo Program</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Cherief%20Houria">Cherief Houria</a>, <a href="https://publications.waset.org/abstracts/search?q=Fouka%20Mourad"> Fouka Mourad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this work, the simulation of the radiation attenuation is carried out in a photon detector consisting of different common shielding material using a Monte Carlo program called PTM. The aim of the study is to investigate the effect of atomic weight and the thickness of shielding materials on the gamma radiation attenuation ability. The linear attenuation coefficients of Aluminum (Al), Iron (Fe), and lead (Pb) elements were evaluated at photons energy of 661:7KeV that are considered to be emitted from a standard radioactive point source Cs 137. The experimental measurements have been performed for three materials to obtain these linear attenuation coefficients, using a Gamma NaI(Tl) scintillation detector. Our results have been compared with the simulation results of the linear attenuation coefficient using the XCOM database and Geant4 codes and reveal that they are well agreed with both simulation data. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=gamma%20photon" title="gamma photon">gamma photon</a>, <a href="https://publications.waset.org/abstracts/search?q=Monte%20Carlo%20program" title=" Monte Carlo program"> Monte Carlo program</a>, <a href="https://publications.waset.org/abstracts/search?q=radiation%20attenuation" title=" radiation attenuation"> radiation attenuation</a>, <a href="https://publications.waset.org/abstracts/search?q=shielding%20material" title=" shielding material"> shielding material</a>, <a href="https://publications.waset.org/abstracts/search?q=the%20linear%20attenuation%20coefficient" title=" the linear attenuation coefficient"> the linear attenuation coefficient</a> </p> <a href="https://publications.waset.org/abstracts/132610/simulation-of-gamma-rays-attenuation-coefficient-for-some-common-shielding-materials-using-monte-carlo-program" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/132610.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">203</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2068</span> A Novel Probablistic Strategy for Modeling Photovoltaic Based Distributed Generators </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Engy%20A.%20Mohamed">Engy A. Mohamed</a>, <a href="https://publications.waset.org/abstracts/search?q=Y.%20G.%20Hegazy"> Y. G. Hegazy </a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents a novel algorithm for modeling photovoltaic based distributed generators for the purpose of optimal planning of distribution networks. The proposed algorithm utilizes sequential Monte Carlo method in order to accurately consider the stochastic nature of photovoltaic based distributed generators. The proposed algorithm is implemented in MATLAB environment and the results obtained are presented and discussed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=comulative%20distribution%20function" title="comulative distribution function">comulative distribution function</a>, <a href="https://publications.waset.org/abstracts/search?q=distributed%20generation" title=" distributed generation"> distributed generation</a>, <a href="https://publications.waset.org/abstracts/search?q=Monte%20Carlo" title=" Monte Carlo"> Monte Carlo</a> </p> <a href="https://publications.waset.org/abstracts/28459/a-novel-probablistic-strategy-for-modeling-photovoltaic-based-distributed-generators" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/28459.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">584</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">2067</span> Bayesian Using Markov Chain Monte Carlo and Lindley's Approximation Based on Type-I Censored Data</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Al%20Omari%20Moahmmed%20Ahmed">Al Omari Moahmmed Ahmed</a> </p> <p class="card-text"><strong>Abstract:</strong></p> These papers describe the Bayesian Estimator using Markov Chain Monte Carlo and Lindley’s approximation and the maximum likelihood estimation of the Weibull distribution with Type-I censored data. The maximum likelihood method can’t estimate the shape parameter in closed forms, although it can be solved by numerical methods. Moreover, the Bayesian estimates of the parameters, the survival and hazard functions cannot be solved analytically. Hence Markov Chain Monte Carlo method and Lindley’s approximation are used, where the full conditional distribution for the parameters of Weibull distribution are obtained via Gibbs sampling and Metropolis-Hastings algorithm (HM) followed by estimate the survival and hazard functions. The methods are compared to Maximum Likelihood counterparts and the comparisons are made with respect to the Mean Square Error (MSE) and absolute bias to determine the better method in scale and shape parameters, the survival and hazard functions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=weibull%20distribution" title="weibull distribution">weibull distribution</a>, <a href="https://publications.waset.org/abstracts/search?q=bayesian%20method" title=" bayesian method"> bayesian method</a>, <a href="https://publications.waset.org/abstracts/search?q=markov%20chain%20mote%20carlo" title=" markov chain mote carlo"> markov chain mote carlo</a>, <a href="https://publications.waset.org/abstracts/search?q=survival%20and%20hazard%20functions" title=" survival and hazard functions"> survival and hazard functions</a> </p> <a href="https://publications.waset.org/abstracts/31291/bayesian-using-markov-chain-monte-carlo-and-lindleys-approximation-based-on-type-i-censored-data" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/31291.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">479</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">2066</span> A New Method to Estimate the Low Income Proportion: Monte Carlo Simulations</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Encarnaci%C3%B3n%20%C3%81lvarez">Encarnación Álvarez</a>, <a href="https://publications.waset.org/abstracts/search?q=Rosa%20M.%20Garc%C3%ADa-Fern%C3%A1ndez"> Rosa M. García-Fernández</a>, <a href="https://publications.waset.org/abstracts/search?q=Juan%20F.%20Mu%C3%B1oz"> Juan F. Muñoz</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Estimation of a proportion has many applications in economics and social studies. A common application is the estimation of the low income proportion, which gives the proportion of people classified as poor into a population. In this paper, we present this poverty indicator and propose to use the logistic regression estimator for the problem of estimating the low income proportion. Various sampling designs are presented. Assuming a real data set obtained from the European Survey on Income and Living Conditions, Monte Carlo simulation studies are carried out to analyze the empirical performance of the logistic regression estimator under the various sampling designs considered in this paper. Results derived from Monte Carlo simulation studies indicate that the logistic regression estimator can be more accurate than the customary estimator under the various sampling designs considered in this paper. The stratified sampling design can also provide more accurate results. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=poverty%20line" title="poverty line">poverty line</a>, <a href="https://publications.waset.org/abstracts/search?q=risk%20of%20poverty" title=" risk of poverty"> risk of poverty</a>, <a href="https://publications.waset.org/abstracts/search?q=auxiliary%20variable" title=" auxiliary variable"> auxiliary variable</a>, <a href="https://publications.waset.org/abstracts/search?q=ratio%20method" title=" ratio method"> ratio method</a> </p> <a href="https://publications.waset.org/abstracts/8876/a-new-method-to-estimate-the-low-income-proportion-monte-carlo-simulations" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/8876.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 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