• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.6
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• pp.982-989
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• 2010

This paper shows accuracy comparison results of reliability estimation methods for one-shot systems such as ammunitions. Quantal-response data, following a binomial distribution at each sampling time, characterizes lifetimes of one-shot systems. Various quantal-response data of different sample sizes are simulated using lifetime data randomly sampled from assumed weibull distributions with different shape parameters but the identical scale parameter in this paper. Then, reliability estimation methods in open literature are applied to the simulated quantal-response data to estimate true reliability over time. Rankings in estimation accuracy for different sample sizes are determined using t-test of SSE. Furthermore, MSE at each time, including both bias and variance of estimated reliability metrics for each method are analyzed to investigate how much both bias and variance contribute the SSE. From the MSE analysis, MSE provides reliability estimation trend for each method. Parametric estimation method provides more accurate reliability estimation results than the other methods for most of sample sizes.

• Journal of the Korean Statistical Society
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• v.32 no.2
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• pp.121-150
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• 2003

The National Health Interview Survey (NHIS) is one of the surveys used to assess the health status of the US population. One indicator of the nation's health is the total number of doctor visits made by the household members in the past year, There is a substantial nonresponse among the sampled households, and the main issue we address here is that the nonrespones mechanism should not be ignored because respondents and nonrespondents differ. It is standard practice to summarize the number of doctor visits by the binary variable of no doctor visit versus at least one doctor visit by a household for each of the fifty states and the District of Columbia. We consider a nonignorable nonresponse model that expresses uncertainty about ignorability through the ratio of odds of a household doctor visit among respondents to the odds of doctor visit among all households. This is a hierarchical model in which a nonignorable nonresponse model is centered on an ignorable nonresponse model. Another feature of this model is that it permits us to "borrow strength" across states as in small area estimation; this helps because some of the parameters are weakly identified. However, for simplicity we assume that the hyperparameters are fixed but unknown, and these hyperparameters are estimated by the EM algorithm; thereby making our method Bayes empirical Bayes. Our main result is that for some of the states the nonresponse mechanism can be considered non-ignorable, and that 95% credible intervals of the probability of a household doctor visit and the probability that a household responds shed important light on the NHIS.

• Clinical and Experimental Vaccine Research
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• v.13 no.1
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• pp.28-34
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• 2024

Purpose: Coronavirus disease 2019 (COVID-19) is a highly formidable disease. Globally, multiple vaccines have been developed to prevent and manage this disease. However, the periodic mutations of severe acute respiratory syndrome coronavirus 2 variants cast doubt on the effectiveness of commonly used vaccines in mitigating severe disease in the Indian population. This study aimed to assess the effectiveness of the BBV152 vaccine and ChAdOx1-S vaccine in preventing severe forms of the disease. Materials and Methods: This retrospective study, based on hospital records, was conducted on 204 vaccinated COVID-19 patients using a consecutive sampling approach. Data on their vaccination status, comorbidities, and high-resolution computed tomography lung reports' computed tomography severity scores were extracted from their medical records. Fisher's exact test and binomial logistic regression analysis were employed to assess the independent associations of various factors with the dependent variables. Results: Of the 204 records, 57.9% represented males, with a mean age of 61.5±9.8 years. Both vaccines demonstrated effective protection against severe illness (90.2%), with BBV152 offering slightly better protection compared to ChAdOx1-S. Male gender, partial vaccination, comorbid conditions, and the type of vaccine were identified as independent predictors of severe lung involvement. Conclusion: This study indicates that both vaccines were highly effective (90%) in preventing severe forms of the disease in fully vaccinated individuals. When comparing the two vaccines, BBV152 was slightly more effective than ChAdOx1-S in preventing severe COVID-19.

• Korean journal of applied entomology
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• v.24 no.1 s.62
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• pp.29-33
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• 1985

Every plant in $990m^2$ onion field was inspected for damages by the onion maggot. Maps were constructed every ten days to show which plants were infested and which were not from April 11 to May 21, 1984. The maps were sectioned into squares one of which contains 80 onion plants and the counts of damaged onions in each square were fitted to poisson and negative binomial distribution and tested by chi-square. We argue that the satisfactory fitness of the expected negative binomial $[P(x^2)>0.05]$ provided a useful description of the spatial distribution patterns of the damaged onions. Edge effect was tested by the differences of damage ratio and variance/mean ratio (${\sigma}^2/m$) between edge and center part. The result showed that the damage ratioes and variances of all the periods, ${\sigma}^2/m$ values after May 1 were greater in edge part than in center part. Again, the maps were sectioned into four blocks and the squares (sample units) were sectioned into quadrants. By application of the variance component technique, it was suggested that $2{\sim}8$ sample units for 5% sampling error and $1{\sim}2$ sample units for 10% error should be sampled randomly to estimate the damage ratio when $2{\sim}3$ quadrants were inspected.

• Culinary science and hospitality research
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• v.22 no.3
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• pp.240-253
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• 2016

The purpose of this study is to predict factors influencing participant demand for the temple stays and to help find alternatives for temple stay marketing strategies. Specifically, the study sought to examine input variables on the visit frequency of temple visitors who partook in temple food. Research subjects were temple stay participants with experience with temple food. Through convenience sampling method, 300 self-administered questionnaires were distributed to participants at 4 temple stays in Seoul. Of the 278 questionnaires collected, 232 (83%) were used for research analysis. Given that the requirement that proper model for analysing the collected data be applied, the Truncated Negative Binomial(TNB) Poisson model, which is useful for analysing count data that are truncated at '0' and overcrowded with a certain value, was selected fort his study. Study results found that, for temple stay food revitalization, the most crucial item for temple food proponents to recognize is natural food ingredients. The degree of affection was higher among respondents over 40 years of groups and with incomes over 40 million won or more than others. In addition, unmarried and male were higher than married and female, and the Christian population in the temple food demand higher impact than Shamanism community. This match should be a priority to establish an in-depth public relations policy of targeted marketing of consumers according to various demographic characteristics. Active and aggressive efforts to expand food inspection are required to promote the healthy image of the temple food to the fragmentation of consumer marketing hierarchy.

• Korean Journal of Social Welfare
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• v.67 no.3
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• pp.253-280
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• 2015

This study reconsiders the concept of publicness by raising a question about the problems which the recent marketization of social services in South Korea. The existing perspective on publicness, however, is insufficient to account for the entire Long-term care market because only public organizations have publicness. Accordingly, this study presents 'integrated publicness', particularly 'dimensional publicness' and 'normative publicness'. A disproportional stratified sampling procedure was used to consider ownership. A merged dataset combining surveys from 248 Long-term Care facilities and on-line resources was used and analyzed by multiple regression, negative binomial regression and multiple imputation analysis. The analysis results suggest as follows. First, ownership publicness appeared more effective in the overall. Second, the regulations on the government funding did not show effective, and the regulation on evaluation system showed the effect. Third, professionalization of normative publicness showed a negative effect on service structure and showed a positive effect on service process. Lastly, user of free services whose public accountability was identified to be effective on service structure and outcome. These findings suggest that not only existing ownership but also dimensional publicness and normative publicness showed an effect on service quality. In this respect, this is important as the performance produced by empirical models of integrated publicness, in this situation that the outcome of marketization is insignificant.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.1-18
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• 2014

Over the past years RFID/SN has been an elementary technology in a diversity of applications for the ubiquitous environments, especially for Internet of Things. However, one of obstacles for widespread deployment of RFID technology is the inherent unreliability of the RFID data streams by tag readers. In particular, the problem of false readings such as lost readings and mistaken readings needs to be treated by RFID middleware systems because false readings ultimately degrade the quality of application services due to the dirty data delivered by middleware systems. As a result, for the higher quality of services, an RFID middleware system is responsible for intelligently dealing with false readings for the delivery of clean data to the applications in accordance with the tag reading environment. One of popular techniques used to compensate false readings is a sliding window filter. In a sliding window scheme, it is evident that determining optimal window size intelligently is a nontrivial important task in RFID middleware systems in order to reduce false readings, especially in mobile environments. In this paper, for the purpose of reducing false readings by intelligent window adaption, we propose a new adaptive RFID data cleaning scheme based on window sliding for a single tag. Unlike previous works based on a binomial sampling model, we introduce the weight averaging. Our insight starts from the need to differentiate the past readings and the current readings, since the more recent readings may indicate the more accurate tag transitions. Owing to weight averaging, our scheme is expected to dynamically adapt the window size in an efficient manner even for non-homogeneous reading patterns in mobile environments. In addition, we analyze reading patterns in the window and effects of decreased window so that a more accurate and efficient decision on window adaption can be made. With our scheme, we can expect to obtain the ultimate goal that RFID middleware systems can provide applications with more clean data so that they can ensure high quality of intended services.