Purpose: Recently, many quality issues are aroused in military forces, such as failures in K-series weapons, combat boots defects and 40mm ammunition explosion accident. To address these problems, this paper suggests to use so called, Defense Quality Score, which is based on Taguchi loss function and developed in this research. Methods: Current defense specification states only the minimum requirement to produce the military supplies. Therefore, it is not easy to indue the continuous quality improvement of the supplies. This research suggests to use the defense quality score which measures the current status of defense supplies'quality characteristics. Results: We applied the defense quality score concept into the hot pepper sauce and long time stockpiled ammunition. We first categorize the quality characteristics into three categories, then assign the certain amount of score based on the importance of the characteristics. Lastly, we applied the modified Taguchi loss function to calculate the achieved score of the characteristics. The perfect score is 100 and the closer to the score, the better product it indicates. Conclusions: In this research, we developed the modified Taguchi loss function to apply into the korean defense supplies. The loss function is utilized to calculate the achieved level of satisfaction of the supplies based on the defense specifications. The application of defense quality score may help to stimulate the continuous quality improvement and encourage the good will quality competition among the military providers.
The theory and practice of water quality scoring and indexing are introduced. The monthly water analysis data are available for six stations long the down-stream Han River whthin the areal boundary of the Special City of Seoul. The data cover the period between 1975 and 1979 inclusive and contain the analytical findings on 37 water constituents including DO, BOD, temperature, total solids and etc. Sic parameters are selected form the 37 items, that, to the judgement of the writer, best reflect the water quality of the Han River. They are; dissolved oxggen saturation, pH, fecal coliform, total solids, BOD and nitrate+ammonia. For each of the six parameters, a subscore function is developed and graphically presented to facilitate the transform of a measurment of the arameter to a subscore on a common score(e.G. 0-100) The score of a sample is calculated as a fuction of the six subscores, using four different approaches; (1) the unweighted arithmetic water quality score, (2) the weighted arithmetic water quality score, (3)the unweighted multiplicative score and (4) the reduced (total) score. Independent of these calculated scores, the experts' score which is calculated by averaging the ratings of water quality experts is obtained and compared with each of the four calculated scores by means of the least square method. The experts' score compares most favorably with the "reduced" score with the correlation coefficient of 0.956 : therefore this method of water quality scoring is adopted to calculate the Han River water quality scores and indices. Water quality index data for Guiri, ukdo, Pokwangdong, Noryangjin, Yongdungpo and Kayang Stations, 1975-1979 are as follow: The overall water quality index data of the Han River between Guiri and Kayang Stations are found; 47.3 in 1976, 48.0 in 1977, 48.5 in 1978 and 54.7 in 1979, indicating the general trend towards water quality improvent in this part of the river, in terms of the increased water quality index by average 1.85 points per year during this period. Finally the optimum sampling frequencies distributed among the six stations, using an equation which takes into account the coefficients of variation of the water quality scores and indices arec calculated.alculated.
Park, Chan Yong;Lee, Kyung Hag;Lee, Na Yun;Kim, Su Ji;Cho, Hyun Min;Lee, Chan Kyu
Journal of Trauma and Injury
/
v.30
no.4
/
pp.126-130
/
2017
Purpose: Preventable Trauma Death Rate (PTDR) using Trauma and Injury Severity Score (TRISS) has been most widely used as a quality indicator in South Korea. However, this method has a small number of deaths corresponding to the denominator. Therefore, it is difficult to check the change of quality improvement for annual mortality, and there is a disadvantage that variation is severe. Therefore, we attempted to improve the quality of the mortality evaluation by reducing the variation by applying the PARK Index (preventable major trauma death rate, PMTDR) which can increase the number of denominator significantly. And the Save score (S-score) was also examined as another quality indicator. Methods: In the PARK Index, the denominator is number of all patients who have survival probability (Ps) larger than 0.25. Numerator is the number of deaths among these. The PARK Index includes only patients with ISS >15. The S-score is calculated in the same way as the W-score, but the S-score includes only patients with ISS >15, which is a difference from the W-score. Results: PARK Index decreased annually and was 12.9 (37/287) in 2014, 9.6 (33/343) in 2015, and 7.3 (52/709) in 2016. S-score increased annually and was -0.29 in 2014, 4.21 in 2015, and 8.75 in 2016. Conclusions: PARK Index and S-score improved annually. This shows that both quality indicators are improving year by year. PARK Index (PMTDR) has 9.5-fold increase in denominator overall compared to PTDR by TRISS. The S-score used only ISS >15 patients as a denominator. Therefore, there is an advantage that the numerical value change is larger than the W-score. In addition, S-score is not affected by the ratio of major trauma patients to minor trauma patients.
The purpose of this study was to provide a basis for nursing intervention to enhance quality if life in women having hysterectomies. Data was collected using a self-report questionnaire from 205 women having hysterectomies at the outpatient clinics of four general hospitals and a mail survey in Pusan City. Reliability of eight instrument's was tested with Cronbach's alpha which ranged from .601-.901. The data were analyzed by percentage, mean, SD, Pearson's Correlation and Stepwise Multiple Regression by using the SPSS 7.5 WIN Program. The results are as follows: 1) The average score for the quality of life was 74.33(score range 23-92). 2) There was a significant correlation between the predictive variables on quality of life. The most significant correlation was sexual identity(r=.516, p=.000). 3) When quality if life score was entered into the equation as the dependent variable, 7variables explaining 54.5% of the variation in quality if life score. Sexual identity was the main predictor of quality of life and accounted for 24.6% of the variance in quality of life. 4) When physical domain score was entered into equation as the dependent variable, 5variables explaining 29.2% of the variation in physical domain score. 5) When psychological domain score was entered into the equation as the dependent variable, 5variables explaining 46.0% of the variation in psychological domain score. 6) When sexual life domain score was entered into the equation as the dependent variable, 6variables explaining 39.4% of the variation in sexual life domain score. In conclusion, sexual identity, pre-operational symptom, sense of loss, spouse's support, age, professional support, coping behavior were identified as important variables in the quality of life in women having hysterectomies.
The Journal of Korean Society for Radiation Therapy
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v.8
no.1
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pp.149-159
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1996
This descriptive correlational study was undertaken in order to investigate the relationship of family support and personality with quality of life in patients receiving radiotherapy for cervix cancer and to provide basic data to help them improve a better quality of life. The subjects for this study Were 80 out-patients undergoing a radiation therapy at C university hospital in K-city, from April, 1992 to October, 1994. The data were obtained using a convenience sampling technique. The tools used for this study were Ro's quality of life scale, Kang's family support scale and Wallston & others health locus of control scale. The collected data were analyzed by the SAS program using percentage, mean, standard deviation, pearson's correlation coefficients. The result were as follows : 1. The total average score of the quality of life of the subjects was 138.95(minimum score 121-maximum score 164), item mean score(range 1-5) was 2.95. The total average score of the family support of the subjects was 32.55 (minimum score 16-maximum score 47), item mean score(range 1-5) was 2.95 The total average score of the health locus of control of the subjects was 37.00 (minimum score 24-maximum score 49), item mean score (range 1-6) was 3.36. 2 The results of the analysis of the relationship between the quality of life scale and the health locus of control were as follows : the total average score in the quality of life of internal locus of control scale was 136.97, the total average score in the quality of life of external locus of control scale was 144.90. 3. There was a significant positive correlation between the health locus of control and the quality of life(r = 0.2927, p<0.01). The result of the analysis of the relationship between the each factor in the quality of life and health locus of control were as follows : There were significant differences between the health locus of control and emotional state factor(r=0.1514, p<0.01), economic life factor(r=0.2560, p<0.05), self-esteem factor(r=0.2289, p<0.05), physical state and function factor(r=0.1455, p<0.05), relationship with neighbors factor(r=0.0754, p<0.05), relationship with family factor (r=0.3324, p<0.01). 4. There was a significant positive correlation between the family support and the quality of life(r=0.459, p<0.001). The result of the analysis of the relationship between the each factor in the quality of life and family support were as follows : there were significant differences between family support and emotional state factor (r=0.3891, p<0.01), self-esteem factor(r=0.2661, p<0.05), relationship with family factor (r=0.4353, p<0.001).
The purposed of the study was to assess customer satisfaction concerning foodservice quality characteristics by using developed DINESERV model for university employee foodservices. Specially, it was intended to develop the tool which assesses the differences between customer importance and perceptions of customer with actual foodservice delivery by university employee foodservices. Questionnaires were distributed to 300 un9iversity employees. Total 230 university employees responded with a usable response rate of 67.7%. Statistical data analysis was completed using SAS programs for descriptive analysis and t-test. The results of the study are as follows: 1) Employees´first choice was distance when they select foodserveices. They answered their preference as the first factor when they order menu in the foodservices. The first complain factor concerning university foodservices was the taste of food. 2) Customers did not satisfied with the foodservice quality of university employee foodservices. Importance mean score of service quality was 3.81 out of 5 but percption mean score of service quality was 3.10. Importance mean score of food quality was 4.11 out of 5 but perception mean score of food quality was 2.96. 3) Customers´satisfaction of service quality by dimensions were as following order: assurance > reliability > responsiveness > empathy > tangibles. And customers´satisfaction of food quality by dimensions were as following order: nutrition > food > price > sanitation. There were no significant difference about customer satisfaction between contracted management and self-operated.
Hong, Yeon Hee;Lee, Jang Mi;Kim, Seul Ki;Youm, Hye Won;Jee, Byung Chul
Clinical and Experimental Reproductive Medicine
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v.47
no.2
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pp.140-146
/
2020
Objective: To investigate whether the degree of post-warming embryo or blastocyst development is associated with clinical pregnancy in vitrified embryo or blastocyst transfer cycles. Methods: Ninety-six vitrified cleavage-stage embryos and 58 vitrified blastocyst transfer cycles were selected. All transfer cycles were performed from February 2011 to March 2019, and all vitrified embryos or blastocysts were warmed from 4 PM to 6 PM and then transferred the next morning from 9 AM to 10 AM. The scores of the cleavage-stage embryos and blastocysts were assessed at warming and at transfer using the modified Steer method and the Gardner method, respectively. The mean embryo or blastocyst score, score of the single top-quality embryo or blastocyst, and the difference in the score between warming and transfer were compared between nonpregnant and pregnant women. Results: In the cleavage-stage embryo transfer cycles, both the top-quality embryo score at transfer and the difference in the score between warming and transfer were significantly associated with clinical pregnancy. A top-quality embryo score at transfer of ≥ 60.0 (area under the curve [AUC], 0.673; 95% confidence interval [CI], 0.531-0.815) and a difference in the score between warming and transfer of ≥ 23.0 (AUC, 0.675; 95% CI, 0.514-0.835) were significant predictors of clinical pregnancy. In blastocyst transfer cycles, the top-quality blastocyst score at transfer was the only significant factor associated with clinical pregnancy. A top-quality blastocyst score at transfer of ≥ 38.3 was a significant predictor of clinical pregnancy (AUC, 0.666; 95% CI, 0.525-0.807). Conclusion: The top-quality embryo score at transfer and the degree of post-warming embryo development were associated with clinical pregnancy in vitrified cleavage-stage embryo transfer cycles. In vitrified blastocyst transfer cycles, the top-quality blastocyst score at transfer was the only significant factor affecting clinical pregnancy.
Purpose: This study was to identify the relationships among the depression, social support and quality of life of the elderly in rural areas. Method: The subjects of this study were 199 people aged over 60 who had been living in three rural area. Data were collected through a questionnaire survey from the 10th of July to the 10th of August 2003. Collected data were analyzed using descriptive statistics, t-test, ANOVA. Duncan's multiple-range test, Pearson's correlation coefficient and multiple stepwise regression with SPSS & SAS. Result: The average depression score was 11.09. As for the score of social support by supporter, the score of spouse' support was 13.36 out of 18 points, children's support 13.27, friends' support 11.40, neighbors' support 10.21 and siblings' support 10.20. The average score of quality of life was 132.26 out of 220 points. As for the score of the sub-areas of quality of life, the score was highest in economic status(32.18) and lowest in neighbor relationship (16.42). The score of quality of life was negatively correlated with the score of depression (r=-.014) and positively with the score of social support (r=.338). The suitable regression from the results of the multiple regression analysis to investigate factors influencing quality of life was expressed by y=58.341-$0.361x_1$+$1.492x_2$ ($x_1$: social support, $x_2$: depression) and $R^2$=.327. Conclusion: These results suggest that elderly people in rural areas with high quality of life is likely to be low in depression and high in social support. Therefore, it is necessary to develop health promotion programs in due consideration of depression and social support in order to enhance the quality of life of elderly people in rural areas.
Purpose: This study was to evaluate the quality of online health information related to infants and preschoolers accessible through mobile applications and websites. Methods: Using combinations of the terms 'infant', 'preschooler', and 'health' as the main keyword or categories, the researchers searched relevant mobile applications and websites in Korean application markets and popular search engines. Twelve mobile application and 14 websites were finally selected according to our inclusion criteria and evaluated using DISCERN instrument. Results: The overall quality score of online health information available through mobile applications was 2.00 of 5 points, the reliability score was 2.15, and the quality score was 1.76. The overall quality score of online health information available through websites was 2.29, the reliability score was 2.40, and the quality score was 1.82. Conclusion: The quality of online health information related to young children was found to be low and to have potentially significant drawbacks according to DISCERN criteria. Therefore, it is necessary to establish a system to evaluate and regulate the quality of online health information. Additionally, factors that readers can use to judge the quality of health information, such as references and the benefit versus risks of the information, should be provided.
Objectives: The objective of this study was to examine whether dietary quality varies among different age groups and geographic areas, and whether the difference between geographic areas varies across several age groups in Korea. Methods: The subjects were 14,170 subjects who participated in the 2013-2015 Korea National Health and Nutrition Examination Survey. The dietary quality was assessed using the Korean Health Eating Index (KHEI). Age groups were categorized into six groupings, and areas were categorized into urban and rural according to their administrative districts. The effect of area on the KHEI score was analyzed by multiple linear regression analysis. Results: The KHEI was the lowest in the 20-30s group (57.7 ± 0.4 score for 20s and 61.2 ± 0.3 score for 30s) and increased with age (p<0.001), showing the highest score in the 60s (67.9 ± 0.3 score), and then decreased again in the 70s and older (64.6 ± 0.3 score). As a result of comparing the KHEI score by area, the urban areas had higher KHEI scores than did the rural areas (63.5 ± 0.2 score for urban area and 62.2 ± 0.4 score for rural area, p=0.002). The difference between areas was dependent on the age group, showing a significant difference for subjects who were aged from 50s and older (p=0.002 for 50s, p<0.001 for 60s and p<0.001 for 70s and older). After adjusting for confounding factors, the effect of area on the KHEI score was only shown for those subjects in the over 60 years old group (p=0.035 for 60s and p<0.001 for 70s and older). Conclusions: The dietary quality differed according to the age group and geographic area. The dietary quality was lower for younger people than that for older people, and in rural areas compared to that in urban areas, and especially for older adults. The area factor was a very important factor for the dietary quality.
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