• Title/Summary/Keyword: prior 모델

Search Result 575, Processing Time 0.022 seconds

Uncertainty Analysis of Parameters of Spatial Statistical Model Using Bayesian Method for Estimating Spatial Distribution of Probability Rainfall (확률강우량의 공간분포추정에 있어서 Bayesian 기법을 이용한 공간통계모델의 매개변수 불확실성 해석)

  • Seo, Young-Min;Park, Ki-Bum;Kim, Sung-Won
    • Journal of Environmental Science International
    • /
    • v.20 no.12
    • /
    • pp.1541-1551
    • /
    • 2011
  • This study applied the Bayesian method for the quantification of the parameter uncertainty of spatial linear mixed model in the estimation of the spatial distribution of probability rainfall. In the application of Bayesian method, the prior sensitivity analysis was implemented by using the priors normally selected in the existing studies which applied the Bayesian method for the puppose of assessing the influence which the selection of the priors of model parameters had on posteriors. As a result, the posteriors of parameters were differently estimated which priors were selected, and then in the case of the prior combination, F-S-E, the sizes of uncertainty intervals were minimum and the modes, means and medians of the posteriors were similar to the estimates using the existing classical methods. From the comparitive analysis between Bayesian and plug-in spatial predictions, we could find that the uncertainty of plug-in prediction could be slightly underestimated than that of Bayesian prediction.

The Effects of Simulation Training With Hybrid Model for Nursing Students on Nursing Performance Ability and Self Confidence (하이브리드모델 활용 시뮬레이션 교육이 간호학생의 간호수행능력과 자신감에 미치는 효과)

  • Lee, Suk Jeong;Park, Young Mi;Noh, Sang Mi
    • Korean Journal of Adult Nursing
    • /
    • v.25 no.2
    • /
    • pp.170-182
    • /
    • 2013
  • Purpose: This study investigated the effectiveness of simulation training with a hybrid model of student nurses' performance ability and reported self confidence. Methods: A nonequivalent control group with pre-posttest was designed. Data collection was done during the first semester in 2012 at a college of nursing in Seoul. Nursing performance ability and reported self confidence related to taking care of patients with urinary problems were evaluated. The treatment group (n=96) received simulation training of a catheterization procedure with a hybrid model involving standardized patients and a mannequin. Nursing students in the comparison group (n=84) did not receive the simulation training but would receive it prior to their next clinical practicum's. Results: The treatment group showed a significantly higher performance ability and reported self confidence than that of the comparison group. The perceived helpfulness and contentment of the simulation training in experimental group was high. Conclusion: The findings of this study demonstrated that simulation with a hybrid model was effective in teaching skills prior to the clinical experience which suggests that skill development is not dependent on the actual clinical situation. Nurse educators should consider simulation training as a tool beyond that of clinical practicum.

Decision Tree Based Context Clustering with Cross Likelihood Ratio for HMM-based TTS (HMM 기반의 TTS를 위한 상호유사도 비율을 이용한 결정트리 기반의 문맥 군집화)

  • Jung, Chi-Sang;Kang, Hong-Goo
    • The Journal of the Acoustical Society of Korea
    • /
    • v.32 no.2
    • /
    • pp.174-180
    • /
    • 2013
  • This paper proposes a decision tree based context clustering algorithm for HMM-based speech synthesis systems using the cross likelihood ratio with a hierarchical prior (CLRHP). Conventional algorithms tie the context-dependent HMM states that have similar statistical characteristics, but they do not consider the statistical similarity of split child nodes, which does not guarantee the statistical difference between the final leaf nodes. The proposed CLRHP algorithm improves the reliability of model parameters by taking a criterion of minimizing the statistical similarity of split child nodes. Experimental results verify the superiority of the proposed approach to conventional ones.

Prediction Model for the Microstructure and Properties in Weld Heat Affected Zone: II. Prediction Model for the Austenitization Kinetics and Austenite Grain Size Considering the Effect of Ferrite Grain Size in Fe-C-Mn Steel (용접 열영향부 미세조직 및 재질예측 모델링: II. Fe-C-Mn 강에서 페라이트 결정립크기의 영향을 고려한 Austenitization kinetics 및 오스테나이트 결정립크기 예측모델)

  • Ryu, Jong-Geun;Moon, Joon-Oh;Lee, Chang-Hee;Uhm, Sang-Ho;Lee, Jong-Bong;Chang, Woong-Sung
    • Journal of Welding and Joining
    • /
    • v.24 no.1
    • /
    • pp.77-87
    • /
    • 2006
  • Considering ferrite grain size in the base metal, the prediction model for $A_{c3}$ temperature and prior austenite grain size at just above $A_{c3}$ temperature was proposed. In order to predict $A_{c3}$ temperature, the Avrami equation was modified with the variation of ferrite grain size, and its kinetic parameters were measured from non-isothermal data during continuous heating. From calculation using a proposed model, $A_{c3}$ temperatures increased with increasing ferrite grain size and heating rate. Meanwhile, by converting the phase transformation kinetic model that predicts the ferrite grain size from austenite grain size during cooling, a prediction model for prior austenite grain size at just above the $A_{c3}$ temperature during heating was developed.

Prediction of Health Care Cost Using the Hierarchical Condition Category Risk Adjustment Model (위계적 질환군 위험조정모델 기반 의료비용 예측)

  • Han, Ki Myoung;Ryu, Mi Kyung;Chun, Ki Hong
    • Health Policy and Management
    • /
    • v.27 no.2
    • /
    • pp.149-156
    • /
    • 2017
  • Background: This study was conducted to evaluate the performance of the Hierarchical Condition Category (HCC) model, identify potentially high-cost patients, and examine the effects of adding prior utilization to the risk model using Korean claims data. Methods: We incorporated 2 years of data from the National Health Insurance Services-National Sample Cohort. Five risk models were used to predict health expenditures: model 1 (age/sex groups), model 2 (the Center for Medicare and Medicaid Services-HCC with age/sex groups), model 3 (selected 54 HCCs with age/sex groups), model 4 (bed-days of care plus model 3), and model 5 (medication-days plus model 3). We evaluated model performance using $R^2$ at individual level, predictive positive value (PPV) of the top 5% of high-cost patients, and predictive ratio (PR) within subgroups. Results: The suitability of the model, including prior use, bed-days, and medication-days, was better than other models. $R^2$ values were 8%, 39%, 37%, 43%, and 57% with model 1, 2, 3, 4, and 5, respectively. After being removed the extreme values, the corresponding $R^2$ values were slightly improved in all models. PPVs were 16.4%, 25.2%, 25.1%, 33.8%, and 53.8%. Total expenditure was underpredicted for the highest expenditure group and overpredicted for the four other groups. PR had a tendency to decrease from younger group to older group in both female and male. Conclusion: The risk adjustment models are important in plan payment, reimbursement, profiling, and research. Combined prior use and diagnostic data are more powerful to predict health costs and to identify high-cost patients.

Effect of Pretransplant Donor-specific Blood Transfusion on Cardiac Allograft Survival in Rats (실험쥐모델에서 이식전 제공자 전혈 수혈이 이식심장의 생존에 미치는 영향)

  • 서충헌;박만실
    • Journal of Chest Surgery
    • /
    • v.32 no.11
    • /
    • pp.984-988
    • /
    • 1999
  • Background: Donor-specific blood transfusion(DSBT) before organ transplantation has been demonstrated to prolong allograft survival; the mechanism of this effect has remained unclear. Only a few researches have been performed on this subject in our country. Material and Method: To investigate the effect of DSBT, we selected 5 donor recipient combinations using rats of pure strain such as PVG, ACI, and LEW. One ml of donor whole blood was transfused to each recipient through the femoral vein 7 days prior to transplantation. The donor heart was transplanted to the recipient's abdominal vessels heterotopically using modified Ono and Lindsey's microsurgical technique. Five transplantations were done for each combination. Postoperatively, donor heart beat was palpated everyday through the recipent's abdominal wall. Rejection was defined as complete cessation of donor heart beat. Result: The allogeneic heart grafts transplanted from PVG strain to ACI strain(PVG ACI) without DSBT were acutely rejected(mean survival 10.2 days). With pretransplant DSBT, the cardiac allografts in PVG ACI and LEW PVG combinations survived indefinitely(more than 100 days), those in ACI PVG combination survived 12 to 66 days(mean 31.8 days), those in PVG LEW survived 8 to 11 days(mean 10.0 days), and those in ACI LEW survived 7 to 9 days(mean 8.0 days). In brief, DSBT prior to heart transplantation was definitely effective in PVG ACI and LEW PVG combinations and moderately effective in ACI PVG combination, but not effective in PVG LEW and ACI LEW combinations. Conclusion: DSBT prior to heart transplantation showed variable effects, but might prolong cardiac allograft survival indefinitely in some donor recipient strain combinations. The mechanism of this effect should be further investigated.

  • PDF

Prior Industry Experience, Product Attributes and Online Customer Review on New Product Sales: TV Products on Chinese Online Shopping (이전사업경험, 제품속성 및 온라인 고객평가가 제품 매출성과에 미치는 영향: 중국 온라인 쇼핑몰내 TV제품 중심으로)

  • Gao, mingwen;Park, Sangmoon
    • Journal of Technology Innovation
    • /
    • v.24 no.1
    • /
    • pp.85-111
    • /
    • 2016
  • This paper examines the effects of prior industry experience, new product attributes and online customer review on new product sales. Different from prior researches on the volume and valence of customer review on online shopping, this paper investigated multiple factors on new product sales in online shopping mall. Based on 407 TV new products in China online shopping mall, we investigated the relationships of kew factors with new products sales. New products of Incumbent TV manufacturers outsell those of new entrants in TV market. Low initial price and low level of discount rate have positive relationships with new product sales. Technological superiority has positive effect on new product sales but the adoptions of new technological functions show different effects on sales. The volume of online consumer review also has positive relationship with new product sales. This paper suggest some theoretical and practical implications and future research directions.

A State-space Production Assessment Model with a Joint Prior Based on Population Resilience: Illustration with the Common Squid Todarodes pacificus Stock (자원복원력 개념을 적용한 사전확률분포 및 상태공간 잉여생산 평가모델: 살오징어(Todarodes pacificus) 개체군 자원평가)

  • Gim, Jinwoo;Hyun, Saang-Yoon;Yoon, Sang Chul
    • Korean Journal of Fisheries and Aquatic Sciences
    • /
    • v.55 no.2
    • /
    • pp.183-188
    • /
    • 2022
  • It is a difficult task to estimate parameters in even a simple stock assessment model such as a surplus production model, using only data about temporal catch-per-unit-effort (CPUE) (or survey index) and fishery yields. Such difficulty is exacerbated when time-varying parameters are treated as random effects (aka state variables). To overcome the difficulty, previous studies incorporated somewhat subjective assumptions (e.g., B1=K) or informative priors of parameters. A key is how to build an objective joint prior of parameters, reducing subjectivity. Given the limited data on temporal CPUEs and fishery yields from 1999-2020 for common squid Todarodes pacificus, we built a joint prior of only two parameters, intrinsic growth rate (r) and carrying capacity (K), based on the resilience level of the population (Froese et al., 2017), and used a Bayesian state-space production assessment model. We used template model builder (TMB), a R package for implementing the assessment model, and estimating all parameters in the model. The predicted annual biomass was in the range of 0.76×106 to 4.06×106 MT, the estimated MSY was 0.13×106 MT, the estimated r was 0.24, and the estimated K was 2.10×106 MT.

Study on the Material Parameter Extraction of the Overlay Model for the Low Cycle Fatigue(LCF) Analysis (저주기 피로해석을 위한 다층모델의 재료상수 추출에 관한 연구)

  • Kim, Sang-Ho;Kabir, S.M. Humayun;Yeo, Tae-In
    • Transactions of the Korean Society of Automotive Engineers
    • /
    • v.18 no.1
    • /
    • pp.66-73
    • /
    • 2010
  • This work was focused on the material parameter extraction for the isothermal cyclic deformation analysis for which Chaboche(Combined Nonlinear Isotropic and Kinematic Hardening) and Overlay(Multi Linear Hardening) models are normally used. In this study all the parameters were driven especially based on Overlay theories. A simple method is suggested to find out best material parameters for the cyclic deformation analysis prior to the isothermal LCF(Low Cycle Fatigue) analysis. The parameter extraction was done using 400 series stainless steel data which were published in the reference papers. For simple and quick review of the parameters extracted by suggested method, 1D FORTRAN program was developed, and this program could reduce the time for checking the material data tremendously. For the application to FE code ABAQUS user subroutine for the material models was developed by means of UMAT(User Material Subroutine), and the stabilized hysteresis loops obtained by the numerical analysis were in good harmony with test results.

An Empirical Study on Forecasting Model of Popularity Rating for Drama Programs (드라마 시청률 예측모델에 대한 실증적 연구)

  • Lee, Won-Jae;Lee, Nam-Yong;Kim, Jong-Bae
    • Journal of Digital Contents Society
    • /
    • v.13 no.3
    • /
    • pp.325-334
    • /
    • 2012
  • Production of drama programs has been granted as a creative work. Thus Systematic approaches to improving quality of drama programs have hardly been tried. This research is for producing a statistical computing model that is capable of forecasting on popularity rating of drama programs produced by KBS, especially forecasting prior to the broadcasting. For the work, we traced various factors affecting on drama popularity ratings, found the relationships among the factors with a regression analysis work, and created the forecasting model on drama popularity ratings. The research result could be applied for finding proper scales of input factors necessary to drama program productions.