Displaying publications 1 - 20 of 81 in total

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  1. Fulltext Monte Carlo method with heuristic adjustment for irregularly shaped food product volume measurement
    Siswantoro J, Prabuwono AS, Abdullah A, Idrus B
    ScientificWorldJournal, 2014;2014:683048.
    PMID: 24892069 DOI: 10.1155/2014/683048
    Volume measurement plays an important role in the production and processing of food products. Various methods have been proposed to measure the volume of food products with irregular shapes based on 3D reconstruction. However, 3D reconstruction comes with a high-priced computational cost. Furthermore, some of the volume measurement methods based on 3D reconstruction have a low accuracy. Another method for measuring volume of objects uses Monte Carlo method. Monte Carlo method performs volume measurements using random points. Monte Carlo method only requires information regarding whether random points fall inside or outside an object and does not require a 3D reconstruction. This paper proposes volume measurement using a computer vision system for irregularly shaped food products without 3D reconstruction based on Monte Carlo method with heuristic adjustment. Five images of food product were captured using five cameras and processed to produce binary images. Monte Carlo integration with heuristic adjustment was performed to measure the volume based on the information extracted from binary images. The experimental results show that the proposed method provided high accuracy and precision compared to the water displacement method. In addition, the proposed method is more accurate and faster than the space carving method.
    Matched MeSH terms: Monte Carlo Method*
  2. Stochastic lead time demand estimation via Monte Carlo simulation technique in supply chain planning
    Mahdavi M, Mahdavi M
    Sains Malaysiana, 2014;43:629-636.
    This paper considers a Monte Carlo simulation based method for estimating cycle stocks (production lot-sizing stocks) in a typical batch production system, where a variety of products is scheduled for production at determined periods of time. Delivery time is defined as the maximum lead time and pre-assembly processing time of the product's raw materials in the method. The product's final assembly cycle and delivery time, which were obtained via the production schedule and supply chain simulation, respectively, were both considered to estimate the demand distribution of product based on total duration. Efficient random variates generators were applied to model the lead time of the supply chain's stages. In order to support the performance reliability of the proposed method, a real case study is conducted and numerically analyzed.
    Matched MeSH terms: Monte Carlo Method
  3. Single-machine Integrated Production Preventive Maintenance Scheduling: A Simheuristic Approach
    Nurul Nadiah Abdul Halim, S. Sarifah Radiah Shariff, Siti Meriam Zahari
    MATEMATIKA, 2020;36(2):113-126.
    MyJurnal
    Preventive maintenance (PM) planning becomes a crucial issue in the real world of the manufacturing process. It is important in the manufacturing industry to maintain the optimum level of production and minimize its investments. Thus, this paper focuses on multiple jobs with a single production line by considering stochastic machine breakdown time. The aim of this paper is to propose a good integration of production and PM schedule that will minimize total completion time. In this study, a hybrid method, which is a genetic algorithm (GA), is used with the Monte Carlo simulation (MCS) technique to deal with the uncertain behavior of machine breakdown time. A deterministic model is adopted and tested under different levels of complexity. Its performance is evaluated based on the value of average completion time. The result clearly shows that the proposed integrated production with PM schedule can reduce the average completion time by 11.68% compared to the production scheduling with machine breakdown time.
    Matched MeSH terms: Monte Carlo Method
  4. Fulltext Determination of neutronic parameters of RTP core using mcnp code
    Mohamad Hairie Rabir, Usang, Mark Dennis, Naim Syauqi Hamzah, Julia Abdul Karim, Mohd Amin Sharifuldin Salleh
    Jurnal Sains Nuklear Malaysia, 2013;25(1):45-59.
    MyJurnal
    The 1 MW TRIGA MARK II research reactor at Malaysian Nuclear Agency achieved initial
    criticality on June 28, 1982. The reactor is designed to effectively implement the various fields of
    basic nuclear research, manpower training, and production of radioisotopes. This
    paperdescribes the reactor parameters calculation for the PUSPATI TRIGA REACTOR (RTP);
    focusing on the application of the developed reactor 3D model for criticality calculation,
    analysis of power and neutron flux distribution and depletion study of TRIGA fuel. The 3D
    continuous energy Monte Carlo code MCNP was used to develop a versatile and accurate full
    model of the TRIGA reactor. The consistency and accuracy of the developed RTP MCNP model
    was established by comparing calculations to the experimental results and TRIGLAV
    code.MCNP and TRIGLAV criticality prediction of the critical core loading are in a very good
    agreement with the experimental results.Power peaking factor calculated with TRIGLAV are
    systematically higher than the MCNP but the trends are the same.Depletion calculation by both
    codes show differences especially at high burnup.The results are conservative and can be
    applied to show the reliability of MCNP code and the model both for design and verification of
    the reactor core, and future calculation of its neutronic parameters.
    Matched MeSH terms: Monte Carlo Method
  5. Fulltext The performance of classical and robust logistic regression estimators in the presence of outliers
    Habshah, M., Syaiba, B.A.
    Pertanika Journal of Science & Technology, 2012;20(2):313-325.
    MyJurnal
    It is now evident that the estimation of logistic regression parameters, using Maximum LikelihoodEstimator (MLE), suffers a huge drawback in the presence of outliers. An alternative approach is touse robust logistic regression estimators, such as Mallows type leverage dependent weights estimator(MALLOWS), Conditionally Unbiased Bounded Influence Function estimator (CUBIF), Bianco andYohai estimator (BY), and Weighted Bianco and Yohai estimator (WBY). This paper investigates therobustness of the preceding robust estimators by using real data sets and Monte Carlo simulations. Theresults indicate that the MLE behaves poorly in the presence of outliers. On the other hand, the WBYestimator is more efficient than the other existing robust estimators. Thus, it is suggested that the WBYestimator be employed when outliers are present in the data to obtain a reliable estimate.
    Matched MeSH terms: Monte Carlo Method
  6. Fulltext Power and neutron flux calculation for the puspati triga reactor using MCNP
    Mohamad Hairie Rabir, Julia Abdul Karim, Mohd Amin Sharifuldin Salleh
    Jurnal Sains Nuklear Malaysia, 2012;24(1):22-32.
    MyJurnal
    The Malaysian 1 MW TRIGA MARK II research reactor at Malaysian Nuclear Agency is designed to effectively implement the various fields of basic nuclear research, manpower training, and production of radioisotopes for their use in agriculture, industry, and medicine. This study deals with the calculation of neutron flux and power distribution in PUSPATI TRIGA REACTOR (RTP) 14th core configuration. The 3-D continuous energy Monte Carlo code MCNP was used to develop a versatile and accurate full model of the TRIGA core and fuels. The model represents in detailed all components of the core with literally no physical approximation. Continuous energy cross-section data from the more recent nuclear data as well as S (α, β) thermal neutron scattering functions distributed with the MCNP code were used. Results of calculations are analyzed and discussed.
    Matched MeSH terms: Monte Carlo Method
  7. Fulltext Criticality calculation in triga Mark II puspati reactor using Monte Carlo code
    Jamro, Rafhayudi, Abdul Aziz Mohamed, Megat Harun Al-Rashid, Julia Abd Karim, Hafizal Yazid, Azraf Azman, et al.
    Journal of Nuclear and Related Technologies, 2008;2008(2):65-71.
    MyJurnal
    A Monte Carlo simulation of the Malaysian nuclear reactor has been performed using MCNP Version 5 code. The purpose of the work is the determination of the multiplication factor (k eff ) for TRIGA Mark II research reactor in Malaysia based on Monte Carlo method. This work has been performed to calculate the value of k eff for two cases, which are the control rod either fully withdrawn or fully inserted to construct a complete model of the TRIGA Mark II PUSPATI Reactor (RTP). The RTP core was modeled as close as possible to the real core and the results of k eff from MCNP5 were obtained. When the control-fuel rods were fully inserted, the k eff value indicates the RTP reactor was in the subcritical condition with a value of 0.98370 ± 0.00054. When the control-fuel rods were fully withdrawn the value of k eff value indicates the RTP reactor is in the supercritical condition, that is 1.10773 ± 0.00083.
    Matched MeSH terms: Monte Carlo Method
  8. Analysis of t-year return level for partial duration rainfall series
    Ling WS, Noriszura Ismail
    Sains Malaysiana, 2012;41:1389-1401.
    This paper aims to estimate the Generalized Pareto Distribution (GPD) parameters and predicts the T-year return levels of extreme rainfall events using the Partial Duration Series (PDS) method based on the hourly rainfall data of five stations in Peninsular Malaysia. In particular, the GPD parameters are estimated using five methods namely the method of Moments (MOM), the probability weighted moments (PWM), the L-moments (LMOM), the Trimmed L-moments (TLMOM) and the Maximum Likelihood (ML) and the performance of the T-year return level of each estimation method is analyzed based on the RMSE measure obtained from Monte Carlo simulation. In addition, we suggest the weighted average model, a model which assigns the inverse variance of several methods as weights, to estimate the T-year return level. This paper contributes to the hydrological literatures in terms of three main elements. Firstly, we suggest the use
    of hourly rainfall data as an alternative to provide a more detailed and valuable information for the analysis of extreme rainfall events. Secondly, this study applies five methods of parametric approach for estimating the GPD parameters and predicting the T-year return level. Finally, in this study we propose the weighted average model, a model that assigns the inverse variance of several methods as weights, for the estimation of the T-year return level.
    Matched MeSH terms: Monte Carlo Method
  9. Preliminary study on bayesian extreme rainfall analysis: a case study of Alor Setar, Kedah, Malaysia
    Annazirin Eli, Mardhiyyah Shaffie, Wan Zawiah W
    Sains Malaysiana, 2012;41:1403-1410.
    Statistical modeling of extreme rainfall is essential since the results can often facilitate civil engineers and planners to estimate the ability of building structures to survive under the utmost extreme conditions. Data comprising of annual maximum series (AMS) of extreme rainfall in Alor Setar were fitted to Generalized Extreme Value (GEV) distribution using method of maximum likelihood (ML) and Bayesian Markov Chain Monte Carlo (MCMC) simulations. The weakness of ML method in handling small sample is hoped to be tackled by means of Bayesian MCMC simulations in this study. In order to obtain the posterior densities, non-informative and independent priors were employed. Performances of parameter estimations were verified by conducting several goodness-of-fit tests. The results showed that Bayesian MCMC method was slightly better than ML method in estimating GEV parameters.
    Matched MeSH terms: Monte Carlo Method
  10. Performance of two-samples pseudo-median procedure
    Nor Aishah Ahad, Sharipah Soaad Syed Yahaya, Abdul Rahman Othman
    Sains Malaysiana, 2012;41:1149-1154.
    This article investigates the performance of two-sample pseudo-median based procedure in testing differences between groups. The procedure is a modification of the one-sample Wilcoxon procedure using the pseudo-median of differences between group values as the central measure of location. The test was conducted on two groups with moderate sample
    sizes of symmetric and asymmetric distributions. The performance of the procedure was measured in terms of Type I error and power rates computed via Monte Carlo methods. The performance of the procedure was compared against the t-test and Mann-Whitney-Wilcoxon test. The findings from this study revealed that the pseudo-median procedure performed very
    well in controlling Type I error rates close to the nominal value. The pseudo-median procedure outperformed the MannWhitney-Wilcoxon test and is comparable to the t-test in controlling Type I error and maintaining adequate power.
    Matched MeSH terms: Monte Carlo Method
  11. Sensitivity analysis of the refinement to the mann-whitney test
    Abdul Rahman Othman, Lai CH
    Sains Malaysiana, 2014;43:1095-1100.
    The aim of researchers when comparing two independent groups is to collect large normally distributed samples unless they lack the resources to access them. In these situations, there are a myriad of non-parametric tests to select, of which the Mann Whitney U test is the most commonly used. In spite of its great advantages of usage, the U test is capable of producing inflated Type I error when applied in situation of heterogeneity or distinct variances. This current study will present a viable alternative called the refined Mann-Whitney test (RMW). A Monte Carlo evaluation test is conducted on RMW using artificial data of various combinations of extreme test conditions. This study reviews that the RMW test justified its development by enhancing the performance of the U test. The RMW test is able to control well its Type I error rates even though it has a lower power.
    Matched MeSH terms: Monte Carlo Method
  12. A monte carlo simulation study on high leverage collinearity-enhancing observation and its effect on multicollinearity pattern
    Habshah Midi, Bagheri A, Rahmatullah Imon A
    Sains Malaysiana, 2011;40:1437-1447.
    Outliers in the X-direction or high leverage points are the latest known source of multicollinearity. Multicollinearity is a nonorthogonality of two or more explanatory variables in multiple regression models, which may have important influential impacts on interpreting a fitted regression model. In this paper, we performed Monte Carlo simulation studies to achieve two main objectives. The first objective was to study the effect of certain magnitude and percentage of high leverage points, which are two important issues in tending the high leverage points to be collinearity-enhancing observations, on the multicollinarity pattern of the data. The second objective was to investigate in which situations these points do make different degrees of multicollinearity, such as moderate or severe. According to the simulation results, high leverage points should be in large magnitude for at least two explanatory variables to guarantee that they are the cause of multicollinearity problems. We also proposed some practical Lower Bound (LB) and Upper Bound (UB) for High Leverage Collinearity Influential Measure (HLCIM) which is an essential measure in detecting the degree of multicollinearity. A well-known example is used to confirm the simulation results.
    Matched MeSH terms: Monte Carlo Method
  13. Utilizing 3D Slicer to incorporate tomographic images into GATE Monte Carlo simulation for personalized dosimetry in yttrium-90 radioembolization
    Abdul Hadi MFR, Abdullah AN, Hashikin NAA, Ying CK, Yeong CH, Yoon TL, et al.
    Med Phys, 2022 Dec;49(12):7742-7753.
    PMID: 36098271 DOI: 10.1002/mp.15980
    PURPOSE: Monte Carlo (MC) simulation is an important technique that can help design advanced and challenging experimental setups. GATE (Geant4 application for tomographic emission) is a useful simulation toolkit for applications in nuclear medicine. Transarterial radioembolization is a treatment for liver cancer, where microspheres embedded with yttrium-90 (90 Y) are administered intra-arterially to the tumor. Personalized dosimetry for this treatment may provide higher dosimetry accuracy compared to the conventional partition model (PM) calculation. However, incorporation of three-dimensional tomographic input data into MC simulation is an intricate process. In this article, 3D Slicer, free and open-source software, was utilized for the incorporation of patient tomographic images into GATE to demonstrate the feasibility of personalized dosimetry in hepatic radioembolization with 90 Y.

    METHODS: In this article, the steps involved in importing, segmenting, and registering tomographic images using 3D Slicer were thoroughly described, before importing them into GATE for MC simulation. The absorbed doses estimated using GATE were then compared with that of PM. SlicerRT, a 3D Slicer extension, was then used to visualize the isodose from the MC simulation.

    RESULTS: A workflow diagram consisting of all the steps taken in the utilization of 3D Slicer for personalized dosimetry in 90 Y radioembolization has been presented in this article. In comparison to the MC simulation, the absorbed doses to the tumor and normal liver were overestimated by PM by 105.55% and 20.23%, respectively, whereas for lungs, the absorbed dose estimated by PM was underestimated by 25.32%. These values were supported by the isodose distribution obtained via SlicerRT, suggesting the presence of beta particles outside the volumes of interest. These findings demonstrate the importance of personalized dosimetry for a more accurate absorbed dose estimation compared to PM.

    CONCLUSION: The methodology provided in this study can assist users (especially students or researchers who are new to MC simulation) in navigating intricate steps required in the importation of tomographic data for MC simulation. These steps can also be utilized for other radiation therapy related applications, not necessarily limited to internal dosimetry.

    Matched MeSH terms: Monte Carlo Method
  14. The application of graphene/h-BN metamaterial in medical linear accelerators for reducing neutron leakage in the treatment room
    Hassanpour M, Hassanpour M, Rezaie M, Khezripour S, Faruque MRI, Khandaker MU
    Phys Eng Sci Med, 2023 Sep;46(3):1023-1032.
    PMID: 37219796 DOI: 10.1007/s13246-023-01269-w
    Neutrons can be generated in medical linear accelerators (Linac) due to the interaction of high-energy photons (> 10 MeV) with the components of the accelerator head. The generated photoneutrons may penetrate the treatment room if a suitable neutron shield is not used. This causes a biological risk to the patient and occupational workers. The use of appropriate materials in the barriers surrounding the bunker may be effective in preventing the transmission of neutrons from the treatment room to the outside. In addition, neutrons are present in the treatment room due to leakage in the Linac's head. This study aims to reduce the transmission of neutrons from the treatment room by using graphene/hexagonal boron nitride (h-BN) metamaterial as a neutron shielding material. MCNPX code was used to model three layers of graphene/h-BN metamaterial around the target and other components of the linac, and to investigate its effect on the photon spectrum and photoneutrons. Results indicate that the first layer of a graphene/h-BN metamaterial shield around the target improves photon spectrum quality at low energies, whereas the second and third layers have no significant effect. Regarding neutrons, three layers of the metamaterial results in a 50% reduction in the number of neutrons in the air within the treatment room.
    Matched MeSH terms: Monte Carlo Method
  15. Fulltext A Markov Chain Monte Carlo Approach to Estimate AIDS after HIV Infection
    Apenteng OO, Ismail NA
    PLoS One, 2015;10(7):e0131950.
    PMID: 26147199 DOI: 10.1371/journal.pone.0131950
    The spread of human immunodeficiency virus (HIV) infection and the resulting acquired immune deficiency syndrome (AIDS) is a major health concern in many parts of the world, and mathematical models are commonly applied to understand the spread of the HIV epidemic. To understand the spread of HIV and AIDS cases and their parameters in a given population, it is necessary to develop a theoretical framework that takes into account realistic factors. The current study used this framework to assess the interaction between individuals who developed AIDS after HIV infection and individuals who did not develop AIDS after HIV infection (pre-AIDS). We first investigated how probabilistic parameters affect the model in terms of the HIV and AIDS population over a period of time. We observed that there is a critical threshold parameter, R0, which determines the behavior of the model. If R0 ≤ 1, there is a unique disease-free equilibrium; if R0 < 1, the disease dies out; and if R0 > 1, the disease-free equilibrium is unstable. We also show how a Markov chain Monte Carlo (MCMC) approach could be used as a supplement to forecast the numbers of reported HIV and AIDS cases. An approach using a Monte Carlo analysis is illustrated to understand the impact of model-based predictions in light of uncertain parameters on the spread of HIV. Finally, to examine this framework and demonstrate how it works, a case study was performed of reported HIV and AIDS cases from an annual data set in Malaysia, and then we compared how these approaches complement each other. We conclude that HIV disease in Malaysia shows epidemic behavior, especially in the context of understanding and predicting emerging cases of HIV and AIDS.
    Matched MeSH terms: Monte Carlo Method*
  16. Biological polymeric shielding design for an X-ray laboratory using Monte Carlo codes
    Tajudin SM, Tabbakh F
    Radiol Phys Technol, 2019 Sep;12(3):299-304.
    PMID: 31302871 DOI: 10.1007/s12194-019-00522-w
    Photon irradiation facilities are often shielded using lead despite its toxicity and high cost. In this study, three Monte Carlo codes, EGS5, MCNPX, and Geant4, were utilized to investigate the efficiency of a relatively new polymeric base compound (CnH2n), as a radiation shielding material for photons with energies below 150 keV. The proposed compound with the densities of 6 and 8 g cm-3 were doped with the weight percentages of 8.0 and 15.0% gadolinium. The probabilities of photoelectric effect and Compton scattering were relatively equal at low photon energies, thus the shielding design was optimized using three Monte Carlo codes for the conformity of calculation results. Consequently, 8% Gd-doped polymer with thickness less than 2 cm and density of 6 g cm-3 was adequate for X-ray room shielding to attenuate more than 95% of the 150-keV incident photons. An average dose rate reduction of 88% can be achieved to ensure safety of the radiation area.
    Matched MeSH terms: Monte Carlo Method*
  17. Fulltext The naturally occurring radioactivity of 'scalar energy' pendants and concomitant radiation risk
    Hassan HJ, Hashim S, Mohd Sanusi MS, Jamal MH, Hassan SA, Bradley DA, et al.
    PLoS One, 2021;16(6):e0250528.
    PMID: 34061865 DOI: 10.1371/journal.pone.0250528
    Forming part of a study of radiological risk arising from use of radioactive consumer products, investigation is made of pendants containing naturally occurring radioactive material. Based on use of gamma-ray spectrometry and Monte Carlo (MC) simulations, the study investigates commercially available 'scalar energy pendants'. The doses from these have been simulated using MIRD5 mathematical phantoms, evaluation being made of dose conversion factors (DCFs) and organ dose. Metallic pendants code MP15 were found to contain the greatest activity, at 7043 ± 471 Bq from 232Th, while glass pendants code GP11 were presented the greatest 238U and 40K activity, at 1001 ± 172 and 687 ± 130 Bq respectively. MP15 pendants offered the greatest percentage concentrations of Th, Ce, U and Zr, with means of 25.6 ± 0.06, 5.6 ± 0.005, 1.03 ± 0.04 and 28.5 ± 0.08 respectively, giving rise to an effective dose of 2.8 mSv for a nominal wearing period of 2000 h. Accordingly, these products can give rise to annual doses in excess of the public limit of 1 mSv.
    Matched MeSH terms: Monte Carlo Method*
  18. Evaluation of TOPAS MC tool performance in optical photon transport and radioluminescence-based dosimetry
    Khodaei A, Moradi F, Oresegun A, Zubair HT, Bradley DA, Ibrahim SA, et al.
    Biomed Phys Eng Express, 2024 Aug 28;10(5).
    PMID: 39142303 DOI: 10.1088/2057-1976/ad6f14
    Radiation therapy plays a pivotal role in modern cancer treatment, demanding precise and accurate dose delivery to tumor sites while minimizing harm to surrounding healthy tissues. Monte Carlo simulations have emerged as indispensable tools for achieving this precision, offering detailed insights into radiation transport and interaction at the subatomic level. As the use of scintillation and luminescence dosimetry becomes increasingly prevalent in radiation therapy, there arises a need for validated Monte Carlo tools tailored to optical photon transport applications. In this paper, an evaluation process of the TOPAS (TOol for PArticle Simulation) Monte Carlo tool for Cerenkov light generation, optical photon transport and radioluminescence based dosimetry is presented. Three distinct sources of validation data are utilized: one from a published set of experimental results and two others from simulations performed with the Geant4 code. The methodology employed for evaluation includes the selection of benchmark experiments, making use of opt3 and opt4 Geant4 physics models and simulation setup, with observed slight discrepancies within the calculation uncertainties. Additionally, the complexities and challenges associated with modeling optical photons generation through luminescence or Cerenkov radiation and their transport are discussed. The results of our evaluation suggests that TOPAS can be used to reliably predict Cerenkov generation, luminescence phenomenon and the behavior of optical photons in common dosimetry scenarios.
    Matched MeSH terms: Monte Carlo Method*
  19. Fulltext Monte Carlo dose calculation in dental amalgam phantom
    Aziz MZ, Yusoff AL, Osman ND, Abdullah R, Rabaie NA, Salikin MS
    J Med Phys, 2015 Jul-Sep;40(3):150-5.
    PMID: 26500401 DOI: 10.4103/0971-6203.165080
    It has become a great challenge in the modern radiation treatment to ensure the accuracy of treatment delivery in electron beam therapy. Tissue inhomogeneity has become one of the factors for accurate dose calculation, and this requires complex algorithm calculation like Monte Carlo (MC). On the other hand, computed tomography (CT) images used in treatment planning system need to be trustful as they are the input in radiotherapy treatment. However, with the presence of metal amalgam in treatment volume, the CT images input showed prominent streak artefact, thus, contributed sources of error. Hence, metal amalgam phantom often creates streak artifacts, which cause an error in the dose calculation. Thus, a streak artifact reduction technique was applied to correct the images, and as a result, better images were observed in terms of structure delineation and density assigning. Furthermore, the amalgam density data were corrected to provide amalgam voxel with accurate density value. As for the errors of dose uncertainties due to metal amalgam, they were reduced from 46% to as low as 2% at d80 (depth of the 80% dose beyond Zmax) using the presented strategies. Considering the number of vital and radiosensitive organs in the head and the neck regions, this correction strategy is suggested in reducing calculation uncertainties through MC calculation.
    Matched MeSH terms: Monte Carlo Method
  20. Studies of Charm Quark Diffusion inside Jets Using Pb-Pb and pp Collisions at sqrt[s_{NN}]=5.02  TeV
    Sirunyan AM, Tumasyan A, Adam W, Ambrogi F, Asilar E, Bergauer T, et al.
    Phys Rev Lett, 2020 Sep 04;125(10):102001.
    PMID: 32955327 DOI: 10.1103/PhysRevLett.125.102001
    The first study of charm quark diffusion with respect to the jet axis in heavy ion collisions is presented. The measurement is performed using jets with p_{T}^{jet}>60  GeV/c and D^{0} mesons with p_{T}^{D}>4  GeV/c in lead-lead (Pb-Pb) and proton-proton (pp) collisions at a nucleon-nucleon center-of-mass energy of sqrt[s_{NN}]=5.02  TeV, recorded by the CMS detector at the LHC. The radial distribution of D^{0} mesons with respect to the jet axis is sensitive to the production mechanisms of the meson, as well as to the energy loss and diffusion processes undergone by its parent parton inside the strongly interacting medium produced in Pb-Pb collisions. When compared to Monte Carlo event generators, the radial distribution in pp collisions is found to be well described by pythia, while the slope of the distribution predicted by sherpa is steeper than that of the data. In Pb-Pb collisions, compared to the pp results, the D^{0} meson distribution for 4
    Matched MeSH terms: Monte Carlo Method
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