• 제목/요약/키워드: 확률 분석

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Evaluation of Setup Uncertainty on the CTV Dose and Setup Margin Using Monte Carlo Simulation (몬테칼로 전산모사를 이용한 셋업오차가 임상표적체적에 전달되는 선량과 셋업마진에 대하여 미치는 영향 평가)

  • Cho, Il-Sung;Kwark, Jung-Won;Cho, Byung-Chul;Kim, Jong-Hoon;Ahn, Seung-Do;Park, Sung-Ho
    • Progress in Medical Physics
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    • v.23 no.2
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    • pp.81-90
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    • 2012
  • The effect of setup uncertainties on CTV dose and the correlation between setup uncertainties and setup margin were evaluated by Monte Carlo based numerical simulation. Patient specific information of IMRT treatment plan for rectal cancer designed on the VARIAN Eclipse planning system was utilized for the Monte Carlo simulation program including the planned dose distribution and tumor volume information of a rectal cancer patient. The simulation program was developed for the purpose of the study on Linux environment using open source packages, GNU C++ and ROOT data analysis framework. All misalignments of patient setup were assumed to follow the central limit theorem. Thus systematic and random errors were generated according to the gaussian statistics with a given standard deviation as simulation input parameter. After the setup error simulations, the change of dose in CTV volume was analyzed with the simulation result. In order to verify the conventional margin recipe, the correlation between setup error and setup margin was compared with the margin formula developed on three dimensional conformal radiation therapy. The simulation was performed total 2,000 times for each simulation input of systematic and random errors independently. The size of standard deviation for generating patient setup errors was changed from 1 mm to 10 mm with 1 mm step. In case for the systematic error the minimum dose on CTV $D_{min}^{stat{\cdot}}$ was decreased from 100.4 to 72.50% and the mean dose $\bar{D}_{syst{\cdot}}$ was decreased from 100.45% to 97.88%. However the standard deviation of dose distribution in CTV volume was increased from 0.02% to 3.33%. The effect of random error gave the same result of a reduction of mean and minimum dose to CTV volume. It was found that the minimum dose on CTV volume $D_{min}^{rand{\cdot}}$ was reduced from 100.45% to 94.80% and the mean dose to CTV $\bar{D}_{rand{\cdot}}$ was decreased from 100.46% to 97.87%. Like systematic error, the standard deviation of CTV dose ${\Delta}D_{rand}$ was increased from 0.01% to 0.63%. After calculating a size of margin for each systematic and random error the "population ratio" was introduced and applied to verify margin recipe. It was found that the conventional margin formula satisfy margin object on IMRT treatment for rectal cancer. It is considered that the developed Monte-carlo based simulation program might be useful to study for patient setup error and dose coverage in CTV volume due to variations of margin size and setup error.

The Analysis of Risk Factors of Pulmonary Tuberculosis Patients Failed in Retreatment (재치료실패 폐결핵 환자의 위험인자 분석)

  • Kim, Hyoung-Soo;Lee, Won-Jin;Kong, Seok-Jun;Shon, Mal-Hyun
    • Tuberculosis and Respiratory Diseases
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    • v.49 no.6
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    • pp.684-690
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    • 2000
  • Background : The most common cause of treatment failure of pulmonary tuberculosis is early stoppage of treatment or irregular medication. The most important aspect of a retreatment is regular medication provided over a long period. Inadequate treatment may cause drug resistance and prolong the duration of chemotherapy. This study analyzed the risk factors of pulmonary tuberculosis patients, who failed in retreatment, and to use the results as basic data in the management of intractable tuberculosis patients with improving the rate of retreatment success. Methods : We performed a retroactive study of 62 pulmonary tuberculosis patients in retreatment at National Mokpo Tuberculosis Hospital from Jan. 1994 to Dec. 1995. The patients were separated into two groups: group I was retreatment failure and group II was retreatrnent success. For the analysis of risk factors in retreatment failure, we compared the difference between the two groups and tested the confidence limit about results of the results by independent t-test, ${\chi}^2$ test and Fisher's exact test. Results : The treatment failure rate of retreatment patients was 13(21%), and treatment success 49(79%). No significant difference (p>0.05)in age, sex, number of treatment, irregular rate of treatment, extent of the disease & cavitary lesion on the chest X-ray, number of resistance drugs, number of used drugs to medication, number of sensitive bactericidal drugs to medication, rate of sensitive drugs to medication and resisiance to INH & RFP had not significant difference. was found. However, the number of treatment was $2.4{\pm}0.8$ in group I and $1.6{\pm}0.9$ in group II, and had showing a significant difference(p<0.05) between the two groups. Conclusion : The risk factor of retreatment failure was more irregular previous treatment the irregularity of the previous treatment. For reducing the retreatment failure of pulmonary tuberculosis, greater efforts are needed more need to be done to prevent failure of first treatment.

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Determination of proper ground motion prediction equation for reasonable evaluation of the seismic reliability in the water supply systems (상수도 시스템 지진 신뢰성의 합리적 평가를 위한 적정 지반운동예측식 결정)

  • Choi, Jeongwook;Kang, Doosun;Jung, Donghwi;Lee, Chanwook;Yoo, Do Guen;Jo, Seong-Bae
    • Journal of Korea Water Resources Association
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    • v.53 no.9
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    • pp.661-670
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    • 2020
  • The water supply system has a wider installation range and various components of it than other infrastructure, making it difficult to secure stability against earthquakes. Therefore, it is necessary to develop methods for evaluating the seismic performance of water supply systems. Ground Motion Prediction Equation (GMPE) is used to evaluate the seismic performance (e.g, failure probability) for water supply facilities such as pump, water tank, and pipes. GMPE is calculated considering the independent variables such as the magnitude of the earthquake and the ground motion such as PGV (Peak Ground Velocity) and PGA (Peak Ground Acceleration). Since the large magnitude earthquake data has not accumulated much to date in Korea, this study tried to select a suitable GMPE for the domestic earthquake simulation by using the earthquake data measured in Korea. To this end, GMPE formula is calculated based on the existing domestic earthquake and presented the results. In the future, it is expected that the evaluation will be more appropriate if the determined GMPE is used when evaluating the seismic performance of domestic waterworks. Appropriate GMPE can be directly used to evaluate hydraulic seismic performance of water supply networks. In other words, it is possible to quantify the damage rate of a pipeline during an earthquake through linkage with the pipe failure probability model, and it is possible to derive more reasonable results when estimating the water outage or low-pressure area due to pipe damages. Finally, the quantifying result of the seismic performance can be used as a design criteria for preparing an optimal restoration plan and proactive seismic design of pipe networks to minimize the damage in the event of an earthquake.

Characteristics of the Maximum Glow Intensity According to the Thermoluminescent Phosphors used in the Absorbed Dose Measurement of the Radiation Therapy (방사선치료 선량 측정에 사용되는 열형광체에 따른 최대 형광 강도 특성)

  • Kang, Suman;Im, Inchul;Park, Cheolwoo;Lee, Mihyeon;Lee, Jaeseung
    • Journal of the Korean Society of Radiology
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    • v.8 no.4
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    • pp.181-187
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    • 2014
  • The purpose of this study were to analyze the characteristic of the glow curves in order to the glow temperature of the thermoluminescent dosimeters (TLDs) for the absorbed dose measurement of the radiation therapy. In this study, we was used the TLDs of the LiF:Mg${\cdot}$Ti, LiF:Mg${\cdot}$Cu${\cdot}$P, $CaF_2$:Dy, $CaF_2$:Mn (Thermo Fisher Scientific Inc., USA). The source-to-solid dry phantom (RW3 slab, IBA Dosmetry, Germany) surface distance was set at 100 cm, and the exposure dose of 100 MU (monitor unit) was used 6- and 15-MV X-rays, and 6- and 12-MeV electron beams in the reference depth, respectively. After the radiations exposure, we were to analyze the glow curves by using the TL reader (Hashaw 3500, Thermo Fisher Scientific Inc., USA) at the fixed heating rate of $15^{\circ}C/sec$ from $50^{\circ}C$ to $260^{\circ}C$. The glow peaks, the trapping level in the captured electrons and holes combined with the emitted light, were discovered the two or three peak. When the definite increasing the temperature of the TLDs, the maximum glow peak representing the glow temperature was follow as; $LiF:Mg{\cdot}Ti$: $185.5{\pm}1.3^{\circ}C$, $LiF:Mg{\cdot}Ti$: $135.0{\pm}5.1^{\circ}C$, $CaF_2$:Dy: $144.0{\pm}1.6^{\circ}C$, $CaF_2$:Mn: $294.3{\pm}3.8^{\circ}C$, respectively. Because the glow emission probability of the captured electrons depend on the heating temperature after the exposure radiation, TLDs by applying the fixed heating rate, the accuracy of measurement will be able to improve within the absorbed dose measurement of the radiation therapy.

Risk Ranking Analysis for the City-Gas Pipelines in the Underground Laying Facilities (지하매설물 중 도시가스 지하배관에 대한 위험성 서열화 분석)

  • Ko, Jae-Sun;Kim, Hyo
    • Fire Science and Engineering
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    • v.18 no.1
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    • pp.54-66
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    • 2004
  • In this article, we are to suggest the hazard-assessing method for the underground pipelines, and find out the pipeline-maintenance schemes of high efficiency in cost. Three kinds of methods are applied in order to refer to the approaching methods of listing the hazards for the underground pipelines: the first is RBI(Risk Based Inspection), which firstly assess the effect of the neighboring population, the dimension, thickness of pipe, and working time. It enables us to estimate quantitatively the risk exposure. The second is the scoring system which is based on the environmental factors of the buried pipelines. Last we quantify the frequency of the releases using the present THOMAS' theory. In this work, as a result of assessing the hazard of it using SPC scheme, the hazard score related to how the gas pipelines erodes indicate the numbers from 30 to 70, which means that the assessing criteria define well the relative hazards of actual pipelines. Therefore. even if one pipeline region is relatively low score, it can have the high frequency of leakage due to its longer length. The acceptable limit of the release frequency of pipeline shows 2.50E-2 to 1.00E-l/yr, from which we must take the appropriate actions to have the consequence to be less than the acceptable region. The prediction of total frequency using regression analysis shows the limit operating time of pipeline is the range of 11 to 13 years, which is well consistent with that of the actual pipeline. Concludingly, the hazard-listing scheme suggested in this research will be very effectively applied to maintaining the underground pipelines.

Severity of Comorbidities among Suicidal Attempters Classified by the Forms of Psychiatric Follow-up (자살시도자의 정신건강의학과 치료 연계 형태에 따른 동반질병 심각도의 차이)

  • Lee, Hyeok;Oh, Seung-Taek;Kim, Min-Kyeong;Lee, Seon-Koo;Seok, Jeong-Ho;Choi, Won-Jung;Lee, Byung Ook
    • Korean Journal of Psychosomatic Medicine
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    • v.24 no.1
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    • pp.74-82
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    • 2016
  • Objectives : Suicide attempters have impaired decision making and are at high risk of reattempt. Therefore it is important to refer them to psychiatric treatment. Especially, People with medical comorbidity are at higher risk of suicidal attempt and mortality. The aim of this study was to investigate the characteristics of suicidal attempters and to analyze the influence of the medical comorbidity on decision to receive psychiatric treatment after visit to an emergency department. Methods : One hundred and thirty two patients, who visited the emergency room of a general hospital in Gyeonggi-do between January, 2012 and December, 2012 were enrolled as the subjects of this study. After reviewing each subject's medical records retrospectively, demographic and clinical factors were analyzed. Results : Regardless of the engagement type, either via admission or outpatient clinic, the determinant factors of psychiatric treatment engagement were psychiatric diagnosis, employment status, previous psychiatric treatment history, and previous attempt history. Comparison of severity of medical comorbidity(Charlson Comorbidity Index) showed that suicide attempters who received psychiatric treatment via admission or refused the treatment tended to have higher level of medical comorbidity than who received psychiatric treatment via outpatient department. Conclusions : Our findings showed that medical comorbidity of suicide attempters affected the decision to accept psychiatric treatment. All psychiatrists should evaluate the presence and the severity of medical comorbidity of the suicide attempters and consider implementing more intervention for the medically ill attempters who are willing to discharge against advice.

Temperature Data-Based Assessment of the Marginal Heading Dates and the Growth Duration of Rice in the Regions of North Korea (북한 지역의 기온 자료를 활용한 벼 출수 한계기 및 재배 기간 분석)

  • Yang, Woonho;Kang, Shingu;Kim, Sukjin;Choi, Jong-Seo;Park, Jeong-Hwa
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.20 no.4
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    • pp.284-295
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    • 2018
  • The safe and late marginal heading dates (SMHD, LMHD), cropping probability, and growth duration of rice were assessed using temperature data in the 27 regions of North Korea. The medians of SMHD and LMHD ranged Jul. 16 and Jul. 27 in Hyesan to Aug. 18 and Aug. 28 in Haeju, respectively, except Changjin, Pungsan, and Samjiyon that did not show any of the SMHD and LMHD. The medians of the days from early marginal transplanting date (EMTD) to heading date ranged 51 days in Hyesan to 109 days in Pyongyang for SMHD and those were delayed by 9~15 days for LMHD, compared to SMHD. Nineteen regions (Kaesong, Haeju, Yongyon, Singye, Sariwon, Nampo, Pyongyang, Anju, Kusong, Sinuiju, Changjon, Wonsan, Hamhung, Pyonggang, Yangdok, Huichon, Supung, Sinpo, Kanggye) and additional four regions (Kimchaek, Chongjin, Sonbong, Chunggang) had the rice cropping probability higher than 80% when analyzed based on the SMHD and LMHD, respectively. The representative SMHD ranged Jul. 24 for Pyonggang to Aug. 12 for Haeju. Compared to the days from EMTD to SMHD, those from EMTD to LMHD were delayed by 9~17 days. When applied SMHD, thirteen regions (Yangdok, Kanggye, Huichon, Supung, Yongyon, Kusong, Anju, Sinuiju, Singye, Pyongyang, Kaesong, Nampo, Sariwon) had the appropriate range of cumulative temperature during grain filling (CT) for grain yield and quality. Sinpo, Hamhung, Pyonggang, Wonsan, Changjon, and Haeju had the CT higher than $1,300^{\circ}C$. It is supposed that rice cropping could be extended to the regions where LMHD-applied cropping probability was higher than 80%. Delaying the heading date than SMHD could be also considered in the regions where the days to SMHD is small but CT is large.

Prediction of a hit drama with a pattern analysis on early viewing ratings (초기 시청시간 패턴 분석을 통한 대흥행 드라마 예측)

  • Nam, Kihwan;Seong, Nohyoon
    • Journal of Intelligence and Information Systems
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    • v.24 no.4
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    • pp.33-49
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    • 2018
  • The impact of TV Drama success on TV Rating and the channel promotion effectiveness is very high. The cultural and business impact has been also demonstrated through the Korean Wave. Therefore, the early prediction of the blockbuster success of TV Drama is very important from the strategic perspective of the media industry. Previous studies have tried to predict the audience ratings and success of drama based on various methods. However, most of the studies have made simple predictions using intuitive methods such as the main actor and time zone. These studies have limitations in predicting. In this study, we propose a model for predicting the popularity of drama by analyzing the customer's viewing pattern based on various theories. This is not only a theoretical contribution but also has a contribution from the practical point of view that can be used in actual broadcasting companies. In this study, we collected data of 280 TV mini-series dramas, broadcasted over the terrestrial channels for 10 years from 2003 to 2012. From the data, we selected the most highly ranked and the least highly ranked 45 TV drama and analyzed the viewing patterns of them by 11-step. The various assumptions and conditions for modeling are based on existing studies, or by the opinions of actual broadcasters and by data mining techniques. Then, we developed a prediction model by measuring the viewing-time distance (difference) using Euclidean and Correlation method, which is termed in our study similarity (the sum of distance). Through the similarity measure, we predicted the success of dramas from the viewer's initial viewing-time pattern distribution using 1~5 episodes. In order to confirm that the model is shaken according to the measurement method, various distance measurement methods were applied and the model was checked for its dryness. And when the model was established, we could make a more predictive model using a grid search. Furthermore, we classified the viewers who had watched TV drama more than 70% of the total airtime as the "passionate viewer" when a new drama is broadcasted. Then we compared the drama's passionate viewer percentage the most highly ranked and the least highly ranked dramas. So that we can determine the possibility of blockbuster TV mini-series. We find that the initial viewing-time pattern is the key factor for the prediction of blockbuster dramas. From our model, block-buster dramas were correctly classified with the 75.47% accuracy with the initial viewing-time pattern analysis. This paper shows high prediction rate while suggesting audience rating method different from existing ones. Currently, broadcasters rely heavily on some famous actors called so-called star systems, so they are in more severe competition than ever due to rising production costs of broadcasting programs, long-term recession, aggressive investment in comprehensive programming channels and large corporations. Everyone is in a financially difficult situation. The basic revenue model of these broadcasters is advertising, and the execution of advertising is based on audience rating as a basic index. In the drama, there is uncertainty in the drama market that it is difficult to forecast the demand due to the nature of the commodity, while the drama market has a high financial contribution in the success of various contents of the broadcasting company. Therefore, to minimize the risk of failure. Thus, by analyzing the distribution of the first-time viewing time, it can be a practical help to establish a response strategy (organization/ marketing/story change, etc.) of the related company. Also, in this paper, we found that the behavior of the audience is crucial to the success of the program. In this paper, we define TV viewing as a measure of how enthusiastically watching TV is watched. We can predict the success of the program successfully by calculating the loyalty of the customer with the hot blood. This way of calculating loyalty can also be used to calculate loyalty to various platforms. It can also be used for marketing programs such as highlights, script previews, making movies, characters, games, and other marketing projects.

Affective Polarization, Policy versus Party: The 2020 US Presidential Election (정서적 양극화, 정책인가 아니면 정당인가: 2020 미대선 사례)

  • Kang, Miongsei
    • Analyses & Alternatives
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    • v.6 no.2
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    • pp.79-115
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    • 2022
  • This study aims to account for electoral choice in the 2020 presidential election by focusing on social identity which forms the basis for core partisan groups. Two views compete to explain the origins of polarization, policy versus party. One emphasizes policy as more influential in choosing presidential candidates. This follows the tradition of retrospective voting theory in which voters' choice rely on government performance. Incumbent president whose performance proves well are rewarded to be reelected. Policy performance is based on measures around distinctive preferences for government spending. Republican Individuals prefer individual responsibility to government support, while Democratic counterparts support government support. Another perspective put an emphasis on the role partisanship which favors in-party members and disfavors partisan out-groups. Interparty animosity plays the key role in determining electoral behavior. This study relies on the Views of the Electorate Research (VOTER) Survey which provides a panel data of several waves from 2011 to 2020. A comparative evaluation of two views highlights three findings. First, policy matters. Policy preferences of voters are the primary drives of political behavior. Electoral outcomes in 2020 turned out to be the results of policy considerations of voters. 53.7 percent of voters tilted toward individual responsibility voted for Trump, whereas 70.4 percent of those favorable views of government support than individual responsibility voted for Biden. Thus effects of policy correspond to a positive difference of 26.4 percent points. Second, partisanship effects are of similar extent in influencing electoral choice of candidates: Democrats are less likely to vote for Trump by 42.4 percent points, while Republicans are less likely to vote for Biden by 48.7 percent points. Third, animosity of Republicans toward Democrat core groups creates 26.5 percent points of favoring Trump over Biden. Democrat animosity toward Republican core groups creates a positive difference of 13.7 percent points of favoring Biden.

Preliminary Inspection Prediction Model to select the on-Site Inspected Foreign Food Facility using Multiple Correspondence Analysis (차원축소를 활용한 해외제조업체 대상 사전점검 예측 모형에 관한 연구)

  • Hae Jin Park;Jae Suk Choi;Sang Goo Cho
    • Journal of Intelligence and Information Systems
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    • v.29 no.1
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    • pp.121-142
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    • 2023
  • As the number and weight of imported food are steadily increasing, safety management of imported food to prevent food safety accidents is becoming more important. The Ministry of Food and Drug Safety conducts on-site inspections of foreign food facilities before customs clearance as well as import inspection at the customs clearance stage. However, a data-based safety management plan for imported food is needed due to time, cost, and limited resources. In this study, we tried to increase the efficiency of the on-site inspection by preparing a machine learning prediction model that pre-selects the companies that are expected to fail before the on-site inspection. Basic information of 303,272 foreign food facilities and processing businesses collected in the Integrated Food Safety Information Network and 1,689 cases of on-site inspection information data collected from 2019 to April 2022 were collected. After preprocessing the data of foreign food facilities, only the data subject to on-site inspection were extracted using the foreign food facility_code. As a result, it consisted of a total of 1,689 data and 103 variables. For 103 variables, variables that were '0' were removed based on the Theil-U index, and after reducing by applying Multiple Correspondence Analysis, 49 characteristic variables were finally derived. We build eight different models and perform hyperparameter tuning through 5-fold cross validation. Then, the performance of the generated models are evaluated. The research purpose of selecting companies subject to on-site inspection is to maximize the recall, which is the probability of judging nonconforming companies as nonconforming. As a result of applying various algorithms of machine learning, the Random Forest model with the highest Recall_macro, AUROC, Average PR, F1-score, and Balanced Accuracy was evaluated as the best model. Finally, we apply Kernal SHAP (SHapley Additive exPlanations) to present the selection reason for nonconforming facilities of individual instances, and discuss applicability to the on-site inspection facility selection system. Based on the results of this study, it is expected that it will contribute to the efficient operation of limited resources such as manpower and budget by establishing an imported food management system through a data-based scientific risk management model.