• Journal of the Korean Statistical Society
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• v.23 no.2
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• pp.403-420
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• 1994

An economic design of the $\bar{X}-R$ chart using variable sample size (VSS) scheme is proposed in this paper. In this design the sample size at each sampling time changes according to the values of the previous two sample statistics, sample mean and range. The VSS scheme uses large sample if the sample statistics appear near inside the control limits and smaller sample otherwise. The set of process parameters, such as the sampling interval, control limits and the sample sizes, are chosen to minimize the expected cost per hour. The efficiency of the VSS scheme is compared to the fixed sample size one for cases where there is multiple of assignable causes. Percent reductions of the expected cost in the VSS design are calculated for some given sets of cost parameters. It is shown that the VSS scheme improves the confidence of the procedure and performs statistically better in terms of the number of false alarms and the average time to signal, respectively.

• 대한예방의학회:학술대회논문집
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• 1994.02a
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• pp.651-657
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• 1994

To assess quantitatively the association between benzene exposure and leukemia, we examined the mortality rate of a cohort with occupational exposure to benzene. Cumulative exposure for each cohort member was estimated from historical air-sampling data and, when no sampling data existed, from interpolation on the basis of existing data. The overall standardized mortality ratio (a measure of relative risk multiplied by 100) for leukemia was 337 (95 percent confidence interval, 154 to 641), and that for multiple myeloma was 409 (95 percent confidence interval, 110 to 1047). With stratification according to levels of cumulative exposure, the standardized mortality ratios for leukemia increased from 109 to 322, 1186, and 6637 with increases in cumulative benzene exposure from less than 40 parts per million-years (ppm-years), to 40 to 199, 200 to 399, and 400 or more. respectively. A cumulative benzene exposure of 400 ppm years is equivalent to a mean annual exposure of 10 ppm over a 40-year working lifetime; 10 ppm is the currently enforceable standard in the United States for occupational exposure to benzene. To examine the shape of the exposure-response relation, we performed a conditional logistic-regression analysis, in which 10 controls were matched to each cohort member with leukemia. From this model, it can be calculated that protection from benzene induced leukemia would increase exponentially with any reduction in the permissible exposure limit.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.327-332
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• 2003

A new discretization method for nonlinear system with time-delay is proposed. It is based on the well-known Taylor series expansion and the zero-order hold (ZOH) assumption. We know that a discretization of linear system can be obtained with the ZOH assumption and within the sampling interval. A similar line of thinking is available in nonlinear case. The mathematical structure of the new discretization method is explored and under the structure, the sampled-data representation of nonlinear system including time-delay is computed. Provided that the discrete form of the single input nonlinear system with time-delay is derived, this result is easily extended to nonlinear system with multi-input time-delay. For simplicity two inputs are considered in this study. It is enough to generalize that of multiple inputs. Finally, the time-discretization of non-affine nonlinear system with time-delay is investigated for apply all nonlinear system

• Journal of Korean Academy of Nursing
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• v.36 no.5
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• pp.829-836
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• 2006

Purpose: The purpose of the present study was to identify prevalence of excessive daytime sleepiness(EDS) and its associations with sleep habits, sleep problems, depression, subjective health status and obesity in community dwelling adults. Method: Data was collected from adults aged 20-59 years by random sampling. Subjects completed a questionnaire which was composed of the Epworth Sleepiness Scale, Center for Epidemiologic Studies Depression Scale, and questions that included items about sleep habits, sleep problems, subjective health status and sociodemographic characteristics. Height and weight were measured for calculation of body mass index. The statistical analyses was based on 3,302 adults (51.5% males and 48.5% females). Descriptive statistics, univariate logistic regression and multiple logistic regression were used. Result: The prevalence of EDS was 17.1% Multiple logistic regression showed that the associated factors of EDS were depression, obesity, dissatisfaction with sleep time, irregular sleep, and habitual snoring. Depression was the most significant associated factor(adjusted odds ratio for severe depression=2.27, 95% Confidence Interval=1.73-2.96). Conclusion: EDS is a common symptom in adults. Our finding suggested that persons with a complaint of EDS should be completely assessed for depression and obesity as well as sleep problems.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.26 no.3
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• pp.324-333
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• 2016

Objectives: We aimed to compare the sampling performance of different flow-based impactor samplers for collecting fungal spores and bacteria and to explore the association of the level of bioaerosols with activity patterns of occupants in daycare center settings. Methods: For comparison of sampling performance, two different flow-based samplers (greater than 100 L/min or not) were selected; a low flow-based sampler (one-stage Andersen sampler) and two high flow-based samplers (DUO SAS SUPER 360 sampler, BUCK bio-culture sampler). We collected airborne mold and bacteria in 30 daycare centers with various levels of contaminated air. Three repeat samplings per each sampler were performed. Mold and bacteria were grown for 96 hours at $25{\pm}1^{\circ}C$ and 48 hours at $35{\pm}1^{\circ}C$, respectively. The Andersen and SAS samplers were used for investigating the association between the level of bioaerosols and the activity patterns of occupants in daycares. Particular matters 10($PM_{10}$), temperature, and relative humidity were monitored as well. Samplings were carried out with one-hour interval from 9 to 5 O'clock. For statistical comparisons, Kruskal-Wallis test, Wilcoxon's signed rank test, and multiple regression analysis were carried out. Results: The airborne level of molds by the low flow-based sampler were significantly higher than that of high flow-based samplers (indoor, P=0.037; outdoor, P=0.041). However, no statistical difference was observed in the airborne level of bacteria by each sampler. Also the level of bioaerosols varied by the time, particularly with different activity patterns in daycare centers. The higher level of mold and bacteria were observed in play time in indoor. Similarly, the concentrations of $PM_{10}$ were significantly associated with the level of bioaerosols (P<0.05). Conclusions: Our findings indicate that the flow rate of sampler, rather than total air volume, could be able to affect the results of sampling. Also, the level of airborne mold and bacteria vary behavior patterns of occupants in indoor of daycare settings. Therefore, different samplers with other flow rate may be selected for mold or bacteria sampling, and activity patterns should be considered for bioaerosol sampling as well.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.4
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• pp.344-365
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• 2009

The performance of a tracking system is greatly increased if multiple types of sensors are combined to achieve the objective of the tracking instead of relying on single type of sensor. To conduct the multi-modal tracking, we have previously developed a multi-modal sensor-based tracking model where acoustic sensors mainly track the objects and visual sensors compensate the tracking errors [1]. In this paper, we find a network synchronization problem appearing in the developed tracking system. The problem is caused by the different location and traffic characteristics of multi-modal sensors and non-synchronized arrival of the captured sensor data at a processing server. To effectively deliver the sensor data, we propose a time-based packet aggregation algorithm where the acoustic sensor data are aggregated based on the sampling time and sent to the server. The delivered acoustic sensor data is then compensated by visual images to correct the tracking errors and such a compensation process improves the tracking accuracy in ideal case. However, in real situations, the tracking improvement from visual compensation can be severely degraded due to the aforementioned network synchronization problem, the impact of which is analyzed by simulations in this paper. To resolve the network synchronization problem, we differentiate the service level of sensor traffic based on Weight Round Robin (WRR) scheduling at the routers. The weighting factor allocated to each queue is calculated by a proposed Delay-based Weight Allocation (DWA) algorithm. From the simulations, we show the traffic differentiation model can mitigate the non-synchronization of sensor data. Finally, we analyze expected traffic behaviors of the tracking system in terms of acoustic sampling interval and visual image size.

• Journal of Preventive Medicine and Public Health
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• v.47 no.5
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• pp.266-272
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• 2014

Objectives: The aim of this study was to investigate the relationship between age at cigarette smoking initiation and smoking level among adolescent current smokers. Methods: In 2007, students from one or two classes of the 10th or 11th grade were randomly selected using the probability proportional to size sampling method. In total, 743 current smokers were included. Multiple logistic regression was used to determine the association between age at smoking initiation and smoking level as either frequent, daily, or heavy smokers. Results: The adjusted odds ratios for each smoking level were significantly higher for younger ages of smoking initiation than those for older ages of initiation were (p for trend <0.001). Compared with the students who started smoking in grades 10 to 11, the adjusted odds ratios for frequent, daily, and heavy smokers increased from 2.24 (95% confidence interval [CI], 1.30 to 3.87) to 3.90 (95% CI, 2.02 to 7.56), from 1.56 (95% CI, 0.92 to 2.62) to 3.17 (95% CI, 1.70 to 5.92), and from 2.56 (95% CI, 1.21 to 5.42) to 5.67 (95% CI, 2.61 to 12.30) with younger ages of smoking initiation. Conclusions: Smoking frequency and amount were closely associated with age at smoking initiation. Therefore, smoking prevention programs should be initiated from the young adolescent period.

• Child Health Nursing Research
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• v.28 no.2
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• pp.124-131
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• 2022

Purpose: A tobacco-free campus (TFC) is the most advanced tobacco-control policy for college campuses, but it has rarely been explored in Korea. This study aimed to explore Korean college students' attitudes toward TFC and related factors. Methods: This cross-sectional descriptive study enrolled college students who were taking an elective course on smoking cessation and a healthy lifestyle at a university located in Incheon, Korea. Data were collected from March 1 to December 31, 2019 using a structured questionnaire, and study participants were recruited using convenience sampling. Results: Data on 309 college students were analyzed. Of those participants, 6.1% supported the TFC policy. Multiple logistic regression analysis showed that female gender (adjusted odds ratio [aOR]=5.80, 95% confidence interval [CI]=1.47-22.95), taking the course to quit smoking oneself (aOR=11.03, 95% CI=1.04-117.05), anxiety in the past month (aOR=4.27, 95% CI=1.06-17.31), and being a current smoker (aOR=0.06, 95% CI=0.01-0.70) were statistically significant independent predictors of TFC support. Conclusion: Women, students taking the course to quit smoking themselves, nonsmokers, and students who felt anxious in the past month were more likely to support TFC. Further research with more representative samples is required to examine the characteristics of people who favor TFC.

• The Korean Journal of Applied Statistics
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• v.27 no.4
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• pp.645-653
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• 2014

P-value is the probability of observing a current sample and possibly other samples departing equally or more extremely from the null hypothesis toward postulated alternative hypothesis. When p-value is less than a certain level called ${\alpha}$(= 0:05), researchers claim that the alternative hypothesis is supported empirically. Unfortunately, some findings discovered in that way are not reproducible, partly because the p-value itself is a statistic vulnerable to random variation. Boos and Stefanski (2011) suggests calculating the upper limit of p-value in hypothesis testing, using a bootstrap predictive distribution. To determine the sample size of a replication study, this study proposes thought experiments by simulating boosted bootstrap samples of different sizes from given observations. The method is illustrated for the cases of two-group comparison and multiple linear regression. This study also addresses the reproducibility of the points in the given 95% confidence interval. Numerical examples show that the center point is covered by 95% confidence intervals generated from bootstrap resamples. However, end points are covered with a 50% chance. Hence this study draws the graph of the reproducibility rate for each parameter in the confidence interval.

• Journal of Korean Academy of Nursing
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• v.50 no.4
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• pp.533-540
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• 2020

Purpose: This study aimed to evaluate nursing students' understanding of the prevention of COVID-19, as well as their anxiety towards the disease and their perception of their professional identity in the wake of the pandemic, in Zhengzhou, China. Methods: A cross-sectional study was designed to investigate 474 nursing students by cluster sampling using a stratified questionnaire from February 15 to March 31, 2020. Multiple linear regression was used to identify the factors affecting professional identity. Binary and multiple logistic regression were used to identify the factors affecting anxiety. Results: Responders with a high level of understanding of COVID-19 and frequent use of behavioral strategies for its prevention comprised 93.2% and 30.0% of the cohort, respectively. Professional identity was significantly associated with gender and anxiety (p < .050). The prevalence of anxiety among nursing students was 12.4%. Male (odds ratio [OR] = 2.39; 95% confidence interval [CI] = 1.26~4.52), sophomores (OR = 5.30; 95% CI = 1.61~7.45), and infrequent use of prevention measures (OR = 3.49; 95% CI = 1.16~5.19) had a significant effect on anxiety. Conclusion: Anxiety during the COVID-19 epidemic gives an adverse effect on the professional identity of nursing in students. Nursing education institutions need to provide psychological counseling services for nursing students, in addition to improving their teaching of COVID-19 prevention strategies.