Han, Kyu-Tae;Kim, Sun Jung;Park, Eun-Cheol;Yoo, Ki-Bong;Kwon, Jeoung A;Kim, Tae Hyun
Journal of Hospice and Palliative Care
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v.18
no.2
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pp.128-135
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2015
Purpose: As the National Health Insurance Service (NHIS) began to cover home oxygen therapy (HOT) services from 2006, it is expected that the new services have contributed to overall positive outcome of patients with chronic obstructive pulmonary disease (COPD). We examined whether the usage of HOT has helped slow down the progression of COPD. Methods: We examined hospital claim data (N=10,798) of COPD inpatients who were treated in 2007~2012. We performed ${\chi}^2$ tests to analyze the differences in the changes to respiratory impairment grades. Multiple logistic regression analysis was used to identify factors that are associated with the use of HOT. Finally, a generalized linear mixed model was used to examine association between the HOT treatment and changes to respiratory impairment grades. Results: A total of 2,490 patients had grade 1 respiratory impairment, and patients with grades 2 or 3 totaled 8,308. The OR for use of HOT was lower in grade 3 patients than others (OR: 0.33, 95% CI: 0.30~0.37). The maintenance/mitigation in all grades, those who used HOT had a higher OR than non-users (OR: 1.41, 95% CI: 1.23~1.61). Conclusion: HOT was effective in maintaining or mitigating the respiratory impairment in COPD patients.
The purpose of this study is to establish a method of estimating the daily urban water demand using statistical model. This method will be used for the development of the efficient management and operation of the water supply facilities. The data used were the daily urban water use, the population, the year lapse and the weather conditions such as temperature, precipitation, relative humidity, etc. Kwangju city was selected for the case study area. The raw data used in this study were rearranged either by month or by season for the purpose of analysis, and the statistical analysis was applied to the data to obtain the regression model. As a result, the multiple linear regression model was developed to estimate the daily urban water use based on the seather condition. The regression constant and the model coefficients were determined for each month of a year. The accuracy of the model was within 3% of average error and within 10% of maximum error. The developed model was found to be useful to the practical operation and management of the water supply facilities.
Objectives: This study was conducted to estimate the health-related quality of life (HRQOL) using EuroQoL-5 Dimension (EQ-5D) and to identify its related factors among urban-dwelling adults. Methods: The data for this study were obtained from 1,134 subjects aged $20\sim91$, who participated in 'Survey on the health status and demand for health' in two cities of Korea (Dong-gu, Gwangju and Suncheon-si, Jeollanamdo). The HRQOL was measured using the EQ-5D instrument and EQ-5D index scores were calculated by two Korean valuation study model using time trade-off method. Results: The mean EQ-5D index scores for all subjects were $0.865{\pm}0.218$ (model A), and $0.921{\pm}0.170$ (model B). The EQ-5D index score was significantly different according to demographic and socioeconomic characteristics (gender, age, marital status, education, occupation, income, and health security system), self-rated health condition, health-related psychological assessments (enough sleep, fatigue rate, stress rate, and degree of satisfaction on the residence). The results of multiple linear regression showed that age, marital status, income, coverage of medical insurance, self-rated health condition, and fatigue rate were significantly related common statistical factors of HRQOL in two Korean valuation study model. Conclusion: Among the adults residing in urban environment, the HRQOL was significantly lower on the subjects with following conditions: higher age, being alone without a spouse as a result of death, divorce or separation, low income, medical aid program, poor self-rated health condition, and chronic fatigue. In order to improve the urban adults' quality of life, healthcare policy and health promotion program must be developed with considerations to factors related to the HRQOL.
O, Cheol;Kim, Won-Gi;Lee, Su-Beom;Lee, Cheong-Won;Kim, Jeong-Wan
Journal of Korean Society of Transportation
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v.25
no.5
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pp.23-32
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2007
Variable message sign (VMS), which is used for providing real-time information on traffic conditions and incidents, is one of the important components of intelligent transportation systems. VMS messages need to meet the requirements with the consideration of human factors that messages should be readable and understandable while driving. This study developed a legibility distance model for VMS messages using in-vehicle differential global positioning data (DGPS). Traffic conditions, highway geometric conditions, and VMS message characteristics were investigated for establishing the legibility model based on multiple linear regression analysis. The height of VMS characters, speed, and the number of lanes were identified as dominant factors affecting the variation of legibility distances. It is expected that the proposed model would play a significant role in designing VMS messages for providing more effective real-time traffic information.
KSCE Journal of Civil and Environmental Engineering Research
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v.26
no.3B
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pp.279-289
/
2006
The reconstruction of low dimension nonlinear behavior from the hydrologic time series has been an active area of research in the last decade. In this study, we present the applications of a powerful state space reconstruction methodology using the method of Support Vector Machines (SVM) to the Great Salt Lake (GSL) volume. SVMs are machine learning systems that use a hypothesis space of linear functions in a Kernel induced higher dimensional feature space. SVMs are optimized by minimizing a bound on a generalized error (risk) measure, rather than just the mean square error over a training set. The utility of this SVM regression approach is demonstrated through applications to the short term forecasts of the biweekly GSL volume. The SVM based reconstruction is used to develop time series forecasts for multiple lead times ranging from the period of two weeks to several months. The reliability of the algorithm in learning and forecasting the dynamics is tested using split sample sensitivity analyses, with a particular interest in forecasting extreme states. Unlike previously reported methodologies, SVMs are able to extract the dynamics using only a few past observed data points (Support Vectors, SV) out of the training examples. Considering statistical measures, the prediction model based on SVM demonstrated encouraging and promising results in a short-term prediction. Thus, the SVM method presented in this study suggests a competitive methodology for the forecast of hydrologic time series.
Meanne P. Andes;Mi-young Roh;Mi Young Lim;Gyeong-Lee Choi;Jung Su Jung;Dongpil Kim
Journal of Bio-Environment Control
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v.32
no.4
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pp.384-395
/
2023
Since transpiration plays a key role in optimal irrigation management, knowledge of the irrigation demand of crops like tomatoes, which are highly susceptible to water stress, is necessary. One way to determine irrigation demand is to measure transpiration, which is affected by environmental factor or growth stage. This study aimed to estimate the transpiration amount of tomatoes and find a suitable model using mathematical and deep learning models using minute-by-minute data. Pearson correlation revealed that observed environmental variables significantly correlate with crop transpiration. Inside air temperature and outside radiation positively correlated with transpiration, while humidity showed a negative correlation. Multiple Linear Regression (MLR), Polynomial Regression model, Artificial Neural Network (ANN), Long short-term Memory (LSTM), and Gated Recurrent Unit (GRU) models were built and compared their accuracies. All models showed potential in estimating transpiration with R2 values ranging from 0.770 to 0.948 and RMSE of 0.495 mm/min to 1.038 mm/min in the test dataset. Deep learning models outperformed the mathematical models; the GRU demonstrated the best performance in the test data with 0.948 R2 and 0.495 mm/min RMSE. The LSTM and ANN closely followed with R2 values of 0.946 and 0.944, respectively, and RMSE of 0.504 m/min and 0.511, respectively. The GRU model exhibited superior performance in short-term forecasts while LSTM for long-term but requires verification using a large dataset. Compared to the FAO56 Penman-Monteith (PM) equation, PM has a lower RMSE of 0.598 mm/min than MLR and Polynomial models degrees 2 and 3 but performed least among all models in capturing variability in transpiration. Therefore, this study recommended GRU and LSTM models for short-term estimation of tomato transpiration in greenhouses.
In cases of fashion businesses operating by consignment, base estimate on quantity of sales is the most essential part of merchandising. This study classified factors influential to sales into factors with systematic influence and factors with unsystematic influence. In order to find out influence of each factor on sales, non-linear regression was used with SPSS package on the basis of actual data on sales for 5 years for sport shoes brand. Major findings of this study are as follows. First, price level had significant negative(-) influence on sales. Second, price expectation effects had significant negative(-) influence on sales. Third, competitor's price effect showed significant negative(-) value. Fourth, day-of-the-week effect showed significant positive(+) effect. The theoretical marketing implications of this study are as follows. First, study on price leads to expansion of the researches from apparels to sport shoes. Field of study on price was enlarged through expansion of variable of study from price level and price expectation effect to promotion, day-of-the-week effect and rainfall effect. Second, quantitative scale of day-of-the-week effect was found and it could be confirmed that there was seasonal differences with day-of-the-week effect. Implications of above findings on marketing managers are as follows. First, it was found that an increase in competitiveness of brand power and a decline in absolute value of competitor's price effect can be realized when new product groups are developed to meet the unsatisfied needs in the market. Second, it was possible to find out the parameters scales of the price response function, making it possible to estimate sales for the next season, and in turn realize increase in rate of sales and profit rate. This research is based on the dynamic price response function, which is rare to find in the apparel business and it academic significance due to its expanding response model which was focused on price in conventional researches to non-systematic variables.
High price equipment is one of the major factors that increases national health expenditure in developed countries. Computerized Tomography(CT), one of the important high price equipment, has been concerns of health service researchers and policy makers in many countries. In Korea, CT, first introduced in 1984, have spreaded nationwide with rapid speed. Though the Committee for Approving Import of High Price Medical Equipment, founded in 1981, tried to regulate the introduction of high price medical equipment including CT, the effort resulted in failure. The exact situation of diffusion of the high price equipment, however, was not yet investigated. We aimed at the description of the diffusion of CT in Korea and analysis of influencing factors on hospitals for the adoption of CT. We mainly used the database of CT, made in 1996 by the National Federation of Medical Insurance for the purpose of insurance payment for CT. Also characteristics of hospitals were gathered from yearbooks published by the central and local governments and by the Korean Hospital Association. We calculated the cumulative number of the CT per one million population year by year. In turn, multiple linear logistic regression was done to find out the contributing factors for the adoption of CT by each hospital. In the logistic regression model, it is regarded as dependent factor whether a hospital retained CT or not in 1988 and 1993. The major categories of the independent factors were hospital characteristics, environmental factors and competitive conditions of hospitals at the period of the adoption. The results are as follows: Number of CT scanners per one million persons in Korea marked more higher level compared with those of most OECD countries. Major influencing factors on the adoption of CT scanners were hospital characteristics, such as hospital referral level, and competitive condition of hospitals, such as number of CT scanners per 10,000 persons in each district where the hospital was located. In Korea, CT diffused with rather rapid speed, comparable with those of the United States and Japan. The major factors contributing on the adoption of CT for hospitals were competitive condition and hospital characteristics rather than regional health care need for CT. In conclusion, a kind of regulating mechanism would be necessary for the prevention of the indiscreet adoption and inefficient use of high price equipment including CT.
Journal of the Korea Academia-Industrial cooperation Society
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v.15
no.12
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pp.7403-7415
/
2014
This study points out a problem that the vehicle rotation area provided in a dead-end parking lot for apartment blocks is misused as unreasonable parking places but accordingly, the edge parking spaces are rarely used for parking. Therefore, this study aims to establish a parking design standard to improve the parking convenience and land-use efficiency by investigating the real parking behaviors and problems identified in the study area, multiple apartment blocks in Haeundae-gu, Busan. This study calculated two simple linear regression models for two mutually exclusive factors, such as the parking convenience and land-use efficiency, respectively, and specified a trade-off point that optimizes both factors. The study results found that parking convenience and land-use efficiency can be improved by not only changing the misused vehicle rotation area to normal parking spaces depending on the usage pattern, but also by increasing the width of the edge parking spaces from 2.3m to 2.6m. Finally, this study suggests two parking design cases for more realistic design applications by considering the parking environment in the dead-end parking lot for apartment blocks.
Exclusive bus lane (EBL) is typically located in the roadway median, and is accessed by weaving across the GPLs(general purpose lanes) before entering from the left lane of the GPLs. To maximize the potential for successful EBL operations, a critical design issue that requires special attention is the length of bus weaving section before entering EBL. The process of developing guidelines for the length of bus weaving section can be supported by a sensitivity analysis of performance measure (safety) with respect to the bus weaving distance. However, field data are difficult to obtain due to inherent complexity in creating performance measure (safety) samples under various interesting flows and bus weaving distance that are keys to research success. In this paper, VISSIM simulation is applied to simulate the operation of roadway weaving areas with EBL, and based on vehicle trajectory data from microscopic traffic simulation models, the Surrogate Safety Assessment Model (SSAM) computes the number of surrogate conflicts (or degree of safety) with respect to the bus weaving distance. Then, a multiple linear regression (MLR) model using safety data (number of surrogate conflicts) is developed. Finally, guidelines for bus weaving distance are established based on the developed MLR. Developed guidelines explicitly indicate that a longer bus weaving distance is required to maintain desired safety as weaving volume increases.
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