• Communications for Statistical Applications and Methods
• /
• v.13 no.2
• /
• pp.285-295
• /
• 2006

As more generic drugs become available, the quality, safety, and efficacy of generic drugs have become a public concern. Specifically, drug interchangeability among generic copies of the same brand-name drug is a safety concern. This research proposes a Bayesian method for assessing bioequivalence between two generic copies of the same brand-name drug from two independent $2{\times}2$ crossover design experiments. Uninformative priors are considered for general use and the posterior distribution of the difference of two generic drug effects is derived from which the highest probability density interval can be evaluated. Examples are presented for illustration.

• Proceedings of the Korean Information Science Society Conference
• /
• 2003.10b
• /
• pp.616-618
• /
• 2003

In this paper particle filter is used as an underlying algorithm to track multiple objects, which are soccer players. Multi-object tracking becomes difficult when two or more players get close to and overlap each other because particles of the filters tend to move to a region of higher posterior probability. To resolve this problem, a blob assignation algorithm which identifies the separated image blobs after occlusion, based on the predicted states according to the dynamic model is suggested. This method performed well on the sequences under general camera work.

• Journal of the Korean Statistical Society
• /
• v.34 no.4
• /
• pp.297-309
• /
• 2005

We consider 'efficiency versus privacy-protection' problem concerned with several well-known randomized response (RR) devices to estimate pro­portion of people bearing a stigmatizing characteristic in a community. The literature of RR on respondent's privacy protection discusses only about response specific jeopardy measures. We propose a measure of jeopardy that is independent of the RR offered by the interviewee and recommend it for using as a technical characteristic of the RR device. For ensuring better cooperation from the interviewees this new measure that depends only on the design parameters of the RR devices may be disclosed to the respondents before producing the RR by implementing the randomization device.

• Journal of Sensor Science and Technology
• /
• v.28 no.5
• /
• pp.277-283
• /
• 2019

In this paper, we propose a distributed fusion estimation for sensor networks using a receding horizon strategy. Communication channels were modelled as Markov jump systems, and a posterior probability distribution for communication channel characteristics was calculated and incorporated into the filter to allow distributed fusion estimation to handle path loss observation situations automatically. To implement distributed fusion estimation, a Kalman-Consensus filter was then used to obtain the average consensus, based on the estimates of sensors randomly distributed across sensor networks. The advantages of the proposed algorithms were then verified using a large-scale sensor network example.

• The Journal of Korea Robotics Society
• /
• v.19 no.2
• /
• pp.213-220
• /
• 2024

Fall detection and prevention technologies play a pivotal role in ensuring the well-being of individuals, particularly those living independently, where falls can result in severe consequences. This paper addresses the challenge of accurate and quick fall detection by proposing a Bayesian probability-based measure applied to surface electromyography (sEMG) signals. The proposed algorithm based on a Bayesian filter that divides the sEMG signal into transient and steady states. The ratio of posterior probabilities, considering the inclusion or exclusion of the transient state, serves as a scale to gauge the dominance of the transient state in the current signal. Experimental results demonstrate that this approach enhances the accuracy and expedites the detection time compared to existing methods. The study suggests broader applications beyond fall detection, anticipating future research in diverse human-robot interface benefiting from the proposed methodology.

• Journal of Korea Water Resources Association
• /
• v.42 no.10
• /
• pp.773-783
• /
• 2009

The effects of rainfall input uncertainty on predictions of stream flow are studied based extended GLUE (Generalized Likelihood Uncertainty Estimation) approach. The uncertainty in the rainfall data is implemented by systematic/non-systematic rainfall measurement analysis in Weida catchment, Germany. PDM (Probability Distribution Model) rainfall runoff model is selected for hydrological representation of the catchment. Using general correction procedure and DUE(Data Uncertainty Engine), feasible rainfall time series are generated. These series are applied to PDM in MC(Monte Carlo) and GLUE method; Posterior distributions of the model parameters are examined and behavioural model parameters are selected for simplified GLUE prediction of stream flow. All predictions are combined to develop ensemble prediction and 90 percentile of ensemble prediction, which are used to show the effects of uncertainty sources of input data and model parameters. The results show acceptable performances in all flow regime, except underestimation of the peak flows. These results are not definite proof of the effects of rainfall uncertainty on parameter estimation; however, extended GLUE approach in this study is a potential method which can include major uncertainty in the rainfall-runoff modelling.

• Journal of Korea Water Resources Association
• /
• v.47 no.8
• /
• pp.671-684
• /
• 2014

Change point analysis is a efficient tool to understand the fundamental information in hydro-meteorological data such as rainfall, discharge, temperature etc. Especially, this fundamental information to change points to future rainfall data identified by reasonable detection skills can affect the prediction of flood and drought occurrence because well detected change points provide a key to resolve the non-stationary or inhomogeneous problem by climate change. Therefore, in this study, the comparative study to assess the performance of the 3 change point detection skills, cumulative sum (CUSUM) method, Bayesian change point (BCP) method, and segmentation by dynamic programming (DP) was performed. After assessment of the performance of the proposed detection skills using the 3 types of the synthetic series, the 2 reasonable detection skills were applied to the observed and future rainfall data at the 5 rainfall gauges in South Korea. Finally, it was suggested that BCP (with 0.9 posterior probability) could be best detection skill and DP could be reasonably recommended through the comparative study. Also it was suggested that BCP (with 0.9 posterior probability) and DP detection skills to find some change points could be reasonable at the North-eastern part in South Korea. In future, the results in this study can be efficiently used to resolve the non-stationary problems in hydrological modeling considering inhomogeneity or nonstationarity.

• Journal of Radiation Protection and Research
• /
• v.31 no.4
• /
• pp.187-195
• /
• 2006

The purpose of this study was to investigate the optimal beam arrangements for hepatic tumors, according to the location of the hepatic tumor and its relationship to organs at risk (OARs). The virtual gross tumor volumes were divided into four groups according to the Couinaud's classification. Several plans were made for each virtual target, and these plans were compared for the normal tissue complication probabilities (NTCP). For group I, NTCP improved as the number of the beam ports increased. However, plans with more than 5 ports had little advantage. For group II, plans with the beam directions from the anterior side showed better results. Group III contained many OARs near the target, which placed restrictions on the beam-directions. Multi-directional plans yielded a higher dose to the OARs than a simple two-port plan using right anterior oblique and posterior beam (RAO/PA). For group IV, a simple RAO/PA port plan was adequate for protection of remaining liver. NTCP can significantly vary between radiotherapy plans when the location of the tumor and its neighboring OARs are taken into consideration. The results in this study of optimal beam arrangements could be a useful set of guidelines for radiotherapy of hepatic tumors.

• Women's Health Nursing
• /
• v.4 no.1
• /
• pp.123-138
• /
• 1998

The purpose of this study was to describe perimenstrual symptom severity levels and perimenstrual distress patterns of women. The study performed the discriminant analysis in which included seven factors : age, pariety, social support, menstrual socialization(mother's symptom, sister's symptom, and menstrual effect), attitude of sex role and depression. The subjects were 283 women that they were not pregnant or lactating, had at least one period in past three months, would understand the purpose of study and willingly accepted the participation. The data analysis was done by pc-SAS program after data collection from Nov. 20, 1997 to Dec. 18, 1997. The descriptive analysis was done to explore general characteristics of the subjects and the stepwise discriminant analysis was done to verify factors in relation to perimenstrual symptom severity levels(severe vs mild menstrual symptom group) and perimenstrual distress patterns(spasmodic vs congestive menstrual symptom group). The instruments were selected for this study from Interpersonal Support Evaluation List(ISEL) by Cohen and Hoberman(1983), Center for Epidemic Studies Depression(CES-D) by Radloff(1977), and Sex Role Attitude Scale by Yunok Suh(1995), Mother's symptom and sister's symptom measurements by Woods, Mitchell & Lentz(1995), and menstrual effect by Brooks-Gun & Ruble(1980). The major findings of this study are as follows : 1. Of the 283 women, 93 women(32.9%) were assessed to severe perimenstrual symptom group and 190 women(67.1%) were assessed to mild perimenstrual symptom group. Results from the stepwise discriminant analysis showed three factors, such as depression, menstrual effect, and age, significantly related to perimenstrual symptom severity and they explained 20% of the total variance. The linear discriminant equation included three factors related to perimenstrual symptom groups was showed(Z=1.445 depression+0.174 menstrual effect-0.054 age). The cutting score(Z) was 2.809. We classified the severe perimenstrual symptom group by more than the cutting score 2.809 and the mild perimenstrual symptom by less or equal than the cutting score 2.809. The correctedness of posterior probability from discriminant equation was 72% as two perimenstrual symptom group classifications. 2. Of the 264 women, 139 women(52.7%) were assessed to spasmodic perimenstrual distress group and women(47.3%) were assessed to congestive perimenstrual distress group. Results from the stepwise discriminant analysis showed two factors, such as depression, age, significantly related to perimenstrual distress groups and they explained 8% of the total variance. The linear discriminant equation included two factors related to perimenstrual distress group was showed(Z=-0.084 age-0.776 depression). The cutting score(Z) was -3.759. We classified the spasmodic perimenstrual distress group by more than cutting score -3.759 and the congestive perimenstrual distress group by less or equal than cutting score -3.759. The correctedness of posterior probability from discriminant equation was 65% as two perimenstrual distress group classifications.

• Nuclear Engineering and Technology
• /
• v.55 no.10
• /
• pp.3913-3923
• /
• 2023

Todays, medium energy resolution detectors are preferably used in radioisotope identification devices(RID) in nuclear and radioactive material categorization. However, there is still a need to develop or enhance « automated identifiers » for the useful RID algorithms. To decide whether any material is SNM or NORM, a key parameter is the better energy resolution of the detector. Although masking, shielding and gain shift/stabilization and other affecting parameters on site are also important for successful operations, the suitability of the RID algorithm is also a critical point to enhance the identification reliability while extracting the features from the spectral analysis. In this study, a RID algorithm based on Bayesian statistical method has been modified for medium energy resolution detectors and applied to the uranium gamma-ray spectra taken by a LaBr3:Ce detector. The present Bayesian RID algorithm covers up to 2000 keV energy range. It uses the peak centroids, the peak areas from the measured gamma-ray spectra. The extraction features are derived from the peak-based Bayesian classifiers to estimate a posterior probability for each isotope in the ANSI library. The program operations were tested under a MATLAB platform. The present peak based Bayesian RID algorithm was validated by using single isotopes(²⁴¹Am, ⁵⁷Co, ¹³⁷Cs, ⁵⁴Mn, ⁶⁰Co), and then applied to five standard nuclear materials(0.32-4.51% at.²³⁵U), as well as natural U- and Th-ores. The ID performance of the RID algorithm was quantified in terms of F-score for each isotope. The posterior probability is calculated to be 54.5-74.4% for ²³⁸U and 4.7-10.5% for ²³⁵U in EC-NRM171 uranium materials. For the case of the more complex gamma-ray spectra from CRMs, the total scoring (ST) method was preferred for its ID performance evaluation. It was shown that the present peak based Bayesian RID algorithm can be applied to identify ²³⁵U and ²³⁸U isotopes in LEU or natural U-Th samples if a medium energy resolution detector is was in the measurements.