Kim, Gyu-Seon;Kim, Hun-Kyom;Lee, Sang-Cheol;Kim, Seung-Jin
Proceedings of the Korea Concrete Institute Conference
/
2008.04a
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pp.569-572
/
2008
A series of the field inspection and the test have been performed on 297 existing bridges, in order to evaluate the bridges since 1995. In this study, based on the test results of the in-depth inspection, the identification of the extent of the chloride content and the incidence of the carbonation depth was conducted, and construction age and member type, environment condition were considered in this analysis. According to simple regression of the tested carbonation depth, the carbonation rate coefficient of the bridges in metropolises was estimated 5.41 and greater than 3.89 and 1.91 in case of marine condition and etc respectively. After measuring chloride content in concrete member, it was concluded that the chloride content of the bridges in marine condition was 4.7 times greater than the others. Especially, slabs had the most highly chloride content and it was estimated 0.709 $kg/m^3$
Kim, Jun-Woo;Lee, Eun-Hee;Ko, Kyoung-Hee;Kim, Suhn-Yeop
The Journal of Korean Academy of Orthopedic Manual Physical Therapy
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v.16
no.1
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pp.1-8
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2010
Purpose : This study aimed to examine the relationships among five clinical measures for functional alignment of the lower extremity. Methods : Thirty healthy subjects (15 males and 15 females) were recruited for the study. The five clinical measures of functional alignment of the lower extremity included navicular drop, quadriceps angle, internal rotation of hip, and anterior and lateral pelvic tilt angles. The level of navicular drop was calculated by the difference between the height of the navicular bone in the sitting (non-weight bearing) and standing (weight bearing) positions. The quadriceps angle and internal rotation of hip were measured using a standard goniometer with photographic markers while the subjects were lying in a prone position on a table with their knee at $90^{\circ}$ flexion. Anterior and lateral pelvic tilt angles were determined using a inclinometer. Results : Correlation and a simple linear regression analysis were used to assess relationships between the clinical measures. There were significant correlations between navicular drop and quadriceps angle (p<.05), between navicular drop and internal rotation of hip (p<.05), and between quadriceps angle and internal rotation of hip (p<.01). In simple linear regression analysis, the navicular drop appeared to be a factor affecting the quadriceps angle and internal rotation of hip (p<.05). The findings suggest that navicular drop has a great impact on lower extremity alignment. Conclusion : This study might help us to examine lower extremity function and clarify its role as a potential injury risk factor.
Tae, Young Sook;Kang, Eun-Sil;Lee, Myung Hwa;Park, Geum Ja
Korean Journal of Adult Nursing
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v.12
no.4
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pp.741-757
/
2000
This study was undertaken to develop an instrument to be used for measuring the concept of quality of life of Korean patients with cancer multidimensionary and correctly. It can contribute in holistic nursing care for Korean cancer patients and also provide and validate basic data to help oncology nurses measure the outcome of nursing intervention correctly. To develop this instrument, the researchers first estabilished a conceptual framework based on the results of qualitative data analysis and indepth interview method Development of the scale was conducted using a method in which 31 items were assessed by subjects' self report using linear analogue scales. The subjects were 79 D.M. patients, 103 patients with acute illness, and 91 cancer patients residing in Busan, Korea. Data were collected during the period from July, 24 to August 14, 2000. This instrument consisted of 31 items with a self report scale. This instrument covered 4 dimensions of cancer patients : 1) physical wellbeing 2) psychological wellbeing 3) social wellbeing and 4)spiritual wellbeing. Each item had a possible score of 10. The reliability of the scale was tested with Cronbach's alpha. Validity was evaluated by examining the relationships of this scale, Youn's Quality of Life Questionnare scores and the Simple Quality of Life scale. Two separate runs of multiple regression were used to predict scores on the Simple Quality of Life measurement. Further validation was obtained by examining the correlation between the instrument subscores and Youn's Quality of Life measurement subscore for convergence of this scale. Examination of the discriminant. power of the instrument was done using ANOVA test. The results are summarized as follows: 1. The reliability of the instrument for the quality of life was 0.8321(Cronbach's alpha.), physical wellbeing dimension 0.6343, psychological wellbeing dimension 0.6501, spiritual wellbeing dimension 0.5883. 2. This instrument had a high correlation with Youn's Quality of Life measurement(r= 0.636) in cancer patients, whereas it had a low correlation with Simple Quality of Life measurement(r=0.455) in cancer patients. In the D.M. patients, the instrument correlated with both the Youn's Quality of Life measurement and Simple Quality of life measurement(r=0.313, r= 0.407) and in the acute stage patients, the instrument had no correlation. 3. Multiple regression of individual items on the Simple Quality of Life scores accounted for 56.8% of the variance in the Simple Quality of Life measurement, whereas, Youn's Quality of Life measurement scores accounts for 31.7%. 4. The correlations collected from the three group had the same patterns of variations but especially the instrument developed in this study had higher disciminant power than that of Youn's Quality of Life Measurement.
The purpose of this study is to analyze the efficiency in management of general hospitals and investigate the major factors on efficiency. Specifically, the management of each general hospital is evaluated by using Data Envelopment Analysis(DEA) technique which is a nonparametric statistical method for measurement of efficiency. Then, the influencing factors are investigated through analyses of Decision-Tree Model and Tobit Regression. The target hospitals were general hospitals in which bed sizes are between 200 and 500 among a total of 276 general hospitals. The main data of financial indicators were collected from 48 hospitals, and it was analyzed by using two statistical models. For Model I, three input and two output variables were used for efficiency evaluation. In particular, three input variables were the number of medical doctors, the number of paramedical personnel, and the bed size. And, two output variables were the numbers of inpatients and outpatients per year, adjusted by bed-size. The results of DEA analysis showed that only seven out of 48 hospitals(15%) turned out to be efficient. The decision-tree analysis also showed that there were six significant influencing factors for Model I. Six factors for Model I were Bed Occupancy Rate, Cost per Adjusted Inpatient, New Visit Ratio of Outpatients, Retired Ratio, Net Profit to Gross Revenues, Net Profit to Total Assets. In addition, the management efficiency of hospital is proved to increase as profit and patient-induced indicators increase and cost-related indicators decrease, by the Tobit regression model of independent variables derived from the decision-tree analysis. This study may be contributable to the development of analytic methodology regarding the efficiency of hospital management in that it suggests the synthetic measures by utilizing DEA model instead of suggesting simple ratio-analyzing results.
Journal of Korean Library and Information Science Society
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v.47
no.3
/
pp.365-382
/
2016
In this paper, impact of science and technology information service quality satisfaction and perceived importance on the user loyalty was studied to find the way of improvement of information service quality. To analyze the impact among service quality variables, the research questions and hypothesis are set and statistical analysis on 641 survey answers was conducted. The correlation between satisfaction and perceived importance regarding each service quality item was high. Relationship between satisfaction of every item of the service quality and overall satisfaction was verified by multiple regression analysis. As a result, the five out of seven independent variables are statistically significant influence to the dependent variable. Relationship between the perceived importance and loyalty for each item was verified by multiple regression analysis was confirmed that the four out of seven independent variables are statistically significant influence to the dependent variable. The overall satisfaction is having an effect on loyalty verified through simple regression analysis.
320 national groundwater monitoring stations have been constructed since 1995 and groundwater levels are measured automatically 4 times a day at each well. It has a difficulty to estimate an average recharge rate of watershed using the recharge rate of the monitoring site because of the lack of its representative on converting a point recharge rate into a spatial one. In this study, the relations between site characteristics (topography, hydraulics, geology, facilities, etc.) and recharge rates of 223 monitoring sites, which were selected using cluster analysis, were analyzed using statistical methods, and finally, regression models were constructed for a recharge rate estimation of non-measured areas. The independent variables for these simple regression models, 1) width of adjacent stream, 2) distance to the nearest stream, 3) topographic slope, and 4) rock type, are proposed using analysis of variance. These models have lots of advantages such as an easy data collection from topographic and geologic maps, a few input variables, and also simplicity in use. Suitability analysis from the comparison between estimation values and original ones at monitoring sites shows that these models are useful for a groundwater recharge estimation.
Area of software measurement in software engineering is active more than thirty years. There is a huge collection of researches but still no concrete software development effort and cost estimation model. If we want to measure the effort and cost of a software project, we need to estimate the size of the software. A number of software metrics are identified in the literature; the most frequently cited measures are LOC (line of code) and FPA (function point analysis). The FPA approach has features that overcome the major problems with using LOC as a measure of system size. This paper presents simple linear regression model that related software development effort to software size measured in FP. The model is derived from the plotting of the effort and FP relation. The experimental data are collected from 789 software development projects that were recently developed under the various development environments and development methods. Also, the model is compare with other regression analysis model. The presented model has the best estimation ability among the software effort estimation models.
This study analyzes the effects between stock returns and interest rate spread, difference between long-term and short-term interest rate through the polynomial linear regression analysis. The existing research concentrated on the business forecast through the interest rate spread focusing on the US market. The previous studies verified the interest rate spread based on the leading indicators of business forecast by moderating the period of long-term/short-term interest rates and analyzing the degree of leading. After the 7th reform of composite indices of business indicators in Korea of 2006, the interest rate spread was included in the items of composing the business leading indicators, which is utilized till today. Nevertheless, there are a few research on stock returns of each industry and interest rate spread in domestic stock market. Therefore, this study analyzed the stock returns of each industry and interest rate spread targeting Korean stock market. This study selected the long-term/short-term interest rates with high causality through the regression analysis, and then understood the correlations with each leading period and industry. To overcome the limitation of the simple linear regression analysis, polynomial linear regression analysis is used, which raised explanatory power. As a result, the high causality was verified when using differences between returns of corporate bond(AA-) without guarantee for three years by leading six months and call rate returns as interest rate spread. In addition, analyzing the stock returns of each industry, the relation between the relevant interest rate spread and returns of the automobile industry was the closest. This study is significant in the aspect of verifying the causality of interest rate spread, business forecast, and stock returns in Korea. Even though it could be limited to forecast the stock price by using only the interest rate spread, it would be working as a strong factor when it is properly utilized with other various factors.
Purpose: The development of assistive devices has allowed for the performance of capsule endoscopy in children. Anticipating the capsule's transit time could affect the efficacy of the investigation and potentially minimize the fasting period. This study determined the predictors of small bowel transit time for small-bowel capsule endoscopy in children and adolescents with inflammatory bowel disease. Methods: We retrospectively examined children and adolescents with inflammatory bowel disease who underwent capsule endoscopy by the age 18 at a Japanese tertiary care children's hospital. Small bowel transit time predictors were analyzed using multiple regression with explanatory variables. Results: Overall, 92 patients, aged 1-17 years, with inflammatory bowel disease (63 Crohn's disease and 29 ulcerative colitis cases) were examined for factors affecting small bowel transit time. In the simple regression analysis, diagnosis, age, height, weight, serum albumin, general anesthesia, and small intestine lesions were significantly associated with small bowel transit time. In the multiple regression analyses, serum albumin (partial regression coefficient: -58.9, p=0.008), general anesthesia (partial regression coefficient: 127, p<0.001), and small intestine lesions (partial regression coefficient: 30.1, p=0.037) showed significant associations with small bowel transit time. Conclusion: Hypoalbuminemia, the use of general anesthesia for endoscopic delivery of the capsule, and small intestine lesions appeared to be predictors of prolonged small bowel transit time in children and adolescents with inflammatory bowel disease. Expecting the finishing time may improve examination with a fasting period reduction, which benefits both patients and caregivers.
We have been implemented simple statistical pattern recognition methods for harmful gases classification using gas sensors array fabricated by MEMS (Micro Electro Mechanical System) technology. The performance of pattern recognition method as a gas classifier is highly dependent on the choice of pre-processing techniques for sensor and sensors array signals and optimal classification algorithms among the various classification techniques. We carried out pre-processing for each sensor's signal as well as sensors array signals to extract features for each gas. We adapted simple statistical pattern recognition algorithms, which were PCA (Principal Component Analysis) for visualization of patterns clustering and MLR (Multi-Linear Regression) for real-time system implementation, to classify harmful gases. Experimental results of adapted pattern recognition methods with pre-processing techniques have been shown good clustering performance and expected easy implementation for real-time sensing system.
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