• Journal of Hospice and Palliative Care
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• v.5 no.2
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• pp.111-124
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• 2002

Purpose : Although the average life expectancy has increased due to advances in medicine, mortality due to cancer is on an increasing trend. Consequently, the number of terminally ill cancer patients is also on the rise. Predicting the survival period is an important issue in the treatment of terminally ill cancer patients since the choice of treatment would vary significantly by the patents, their families, and physicians according to the expected survival. Therefore, we investigated the prognostic factors for increased mortality risk in terminally ill cancer patients to help treat these patients by predicting the survival period. Methods : We investigated 31 clinical parameters in 157 terminally ill cancer patients admitted to in the Department of Family Medicine, National Health Insurance Corporation Ilsan Hospital between July 1, 2000 and August 31, 2001. We confirmed the patients' survival as of October 31, 2001 based on medical records and personal data. The survival rates and median survival times were estimated by the Kaplan-Meier method and Log-rank test was used to compare the differences between the survival rates according to each clinical parameter. Cox's proportional hazard model was used to determine the most predictive subset from the prognostic factors among many clinical parameters which affect the risk of death. We predicted the mean, median, the first quartile value and third quartile value of the expected lifetimes by Weibull proportional hazard regression model. Results : Out of 157 patients, 79 were male (50.3%). The mean age was $65.1{\pm}13.0$ years in males and was $64.3{\pm}13.7$ years in females. The most prevalent cancer was gastric cancer (36 patients, 22.9%), followed by lung cancer (27, 17.2%), and cervical cancer (20, 12.7%). The survival time decreased with to the following factors; mental change, anorexia, hypotension, poor performance status, leukocytosis, neutrophilia, elevated serum creatinine level, hypoalbuminemia, hyperbilirubinemia, elevated SGPT, prolonged prothrombin time (PT), prolonged activated partial thromboplastin time (aPTT), hyponatremia, and hyperkalemia. Among these factors, poor performance status, neutrophilia, prolonged PT and aPTT were significant prognostic factors of death risk in these patients according to the results of Cox's proportional hazard model. We predicted that the median life expectancy was 3.0 days when all of the above 4 factors were present, $5.7{\sim}8.2$ days when 3 of these 4 factors were present, $11.4{\sim}20.0$ days when 2 of the 4 were present, and $27.9{\sim}40.0$ when 1 of the 4 was present, and 77 days when none of these 4 factors were present. Conclusions : In terminally ill cancer patients, we found that the prognostic factors related to reduced survival time were poor performance status, neutrophilia, prolonged PT and prolonged am. The four prognostic factors enabled the prediction of life expectancy in terminally ill cancer patients.

• Journal of Environmental Health Sciences
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• v.43 no.3
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• pp.223-232
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• 2017

Objectives: In response to increased interest in the safety of children's products, a risk management system is being prepared through exposure assessment of hazardous chemicals. To estimate exposure levels, risk assessors are using deterministic and probabilistic approaches to statistical methodology and a commercialized Monte Carlo simulation based on tools (MCTool) to efficiently support calculation of the probability density functions. This study was conducted to analyze and discuss the usage patterns and problems associated with the results of these two approaches and MCTools used in the case of probabilistic approaches by reviewing research reports related to exposure assessment for children's products. Methods: We collected six research reports on exposure and risk assessment of children's products and summarized the deterministic results and corresponding underlying distributions for exposure dose and concentration results estimated through deterministic and probabilistic approaches. We focused on mechanisms and differences in the MCTools used for decision making with probabilistic distributions to validate the simulation adequacy in detail. Results: The estimation results of exposure dose and concentration from the deterministic approaches were 0.19-3.98 times higher than the results from the probabilistic approach. For the probabilistic approach, the use of lognormal, Student's T, and Weibull distributions had the highest frequency as underlying distributions of the input parameters. However, we could not examine the reasons for the selection of each distribution because of the absence of test-statistics. In addition, there were some cases estimating the discrete probability distribution model as the underlying distribution for continuous variables, such as weight. To find the cause of abnormal simulations, we applied two MCTools used for all reports and described the improper usage routes of MCTools. Conclusions: For transparent and realistic exposure assessment, it is necessary to 1) establish standardized guidelines for the proper use of the two statistical approaches, including notes by MCTool and 2) consider the development of a new software tool with proper configurations and features specialized for risk assessment. Such guidelines and software will make exposure assessment more user-friendly, consistent, and rapid in the future.

• Korean journal of applied entomology
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• v.39 no.2
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• pp.73-82
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• 2000

Two Psyllidae species of Cacopsylla pyricola (Foerster) and C. pyrisuga (Foerster)damaging pear trees have been reported in Korea. However, their ecological characteristics and damagepatterns have not been evaluated yet. To establish basic control measures of C. pyricola, field phenology,overwintering ecology, seasonal fluctuation and temperature-dependent development of C. pyricola wereexamined. C. pyricola overwintered under the bark scale of pear trees as winter form adults and theymoved to fruiting twigs from mid-February. Honeydew produced by C. pyricola nymphs and adults asthey feed caused serious black sooty mold on leaves and fruits. The seasonal occurrence of C. pyricolawas different every year. In 1993, characterized by cold temperature and heavy precipitation, C. pyricolapopulation was maintained highly during growing season. However, the population was decreased rapidlyfrom early July in 1994, year of hot and dry weather condition. In 1995, year of average temperature, thedensity of C. pyricola population was decreased during hot months of July and August, and rebuilt up inSeptember and October. The development periods of C. pyricola eggs were 13.33 days at 15"C, 9.32 daysat 20$^{\circ}$C, 7.82 days at 25"C, 6.60 days at 30$^{\circ}$C, and 7.75 days at 35$^{\circ}$C. The development periods ofnymphs were 33.75 days at 15OC, 23.77 days at 20$^{\circ}$C, 15.21 days at 25"C, and 17.40 days at 30$^{\circ}$C. Theirdevelopment periods and mortalities were increased in higher temperatures. The parameters of nonlineardevelopment model, Weibull and linear development models of Cacopsylla pyricola were estimated.models of Cacopsylla pyricola were estimated.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.8
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• pp.62-68
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• 2016

The feeder cable assembly is an automotive part used for telecommunication. If it malfunctions, the control and safety of the automobile can be put at risk. ALT (Accelerated Life Testing) is a testing process for products in which they are subjected to conditions (stress, strain, temperatures, etc.) in excess of their normal service parameters in an attempt to uncover faults and potential modes of failure in a short amount of time. Failure is caused by defects in the design, process, quality, or application of the part, and these defects are the underlying causes of failure or which initiate a process leading to failure. Thermal shock occurs when a thermal gradient causes different parts of an object to expand by different amounts. Thermal shock testing is performed to determine the ability of parts and components to withstand sudden changes in temperature. In this research, the main causes of failure of the feeder cable assembly were snapping, shorting and electro-pressure resistance failure. Using the Coffin-Manson model for ALT, the normal conditions were from Tmax = $80^{\circ}C$ to Tmin = $-40^{\circ}C$, the accelerated testing conditions were from Tmax = $120^{\circ}C$ to Tmin = $-60^{\circ}C$, the AF (Acceleration Factor) was 2.25 and the testing time was reduced from 1,000 cycles to 444 cycles. Using the Bxlife test, the number of samples was 5, the required life was B0.04%.10years, in the acceleration condition, 747 cycles were obtained. After the thermal shock test under different conditions, the feeder cable assembly was examined by a network analyzer and compared with the Weibull distribution modulus parameter. The results obtained showed good results in acceleration life test mode. For the same reliability rate, the testing time was decreased by a quarter using ALT.

• Journal of Korea Water Resources Association
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• v.32 no.4
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• pp.403-415
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• 1999

This study is to derive the rainfall intensity formula based on the representative probability distribution in Korea. The 11 probability distributions which has been widely used in hydrologic frequency analysis are applied to the annual maximum rainfall. The parameters of each probability distribution are estimated by method of moments, maximum likelihood method and method of probability weighted moments. Four tests such as $x^2$-test, Kolmogorv-Smirnov test, difference test and modified difference test are used to determine the goodness of fit of the distributions. The homogeneous tests (Mann-Whitney U test, Kruskal-Wallis one-way analysis of variance of nonparametric test) are applied to find the stations with rainfall homogeneity. The results of homogeneous tests show that there is no representative appropriate distribution for the whole duration in Korea. The whole region could be divided into five zones for 12-durations. The representative probability distribution of each divided zone for 12-durations was determined. The GEV distribution for I,II,V zones and the 3-parameter Weibull distribution for III,IV zones were determined as the representative probability distribution. The rainfall were obtained from representative probability distribution for the selected return periods. Rainfall intensity formula was determined by linearization technique for the rainfall.