• Journal of the Korean Institute of Landscape Architecture
• /
• v.38 no.4
• /
• pp.25-34
• /
• 2010

This study was conducted to develop evaluation indicators to improve athletic performance and operational management of golf courses and the results of the research are as follows. Through theoretical research and a preliminary professional survey, 15 on-going evaluations of golf course composition and operational management and 55 sub-evaluation indices were rejected while 10 on-going evaluations and 52 sub-evaluation indicators were reconfigured as final for environmental-friendliness, level of member services, level of human service of game personnel, difficulties of course, management level of the course, fairness of operational management, accessibility and location characteristic, traditions and ambiance of the golf club, quality of course, and course layout. When analyzing the important decision factors in golf course user preference evaluation indicators, the following contributed in the order of higher to lower contributions: the management level of the course, excellence of the course, level of human services for personnel, course layout and environmental-friendliness. When identifying the path coefficient of golf course evaluation indicators, the curvature of a hole and the length of the course had a causal effect on the 'course layout' section. Tournament facilities and various shot values had a causal relationship with 'excellence of the course', in the order of higher to lower, and convenience of waiting and fair allocation of reservations for 'fairness of operational management'. The history of the golf course and its environmental characteristics, history and culture of the region have relatively higher causal effects on 'traditions of the golf club' and geographical conditions on 'accessibility and location characteristics', pesticide and fertilizer usage and water pollution on 'environmental-friendliness', and member benefit and kindness of employees on 'level of member services'. The kindness and expertise of the game personnel had a relatively higher causal effect on the 'level of human services of game personnel', the location of tenning area, and location of OB and hazards on 'difficulties of course', and rough conditions and obstacles management on 'management level of the course'. There is a need to complete a systematic evaluation index system for golf course user preferences through future studies for a more detailed assessment, as well as a process to verify these evaluation indicators by application to domestic and international golf courses.

• 한국노년학
• /
• v.41 no.2
• /
• pp.271-284
• /
• 2021

This study was conducted to derive factors that affect the satisfaction of home visiting health care services and to develop effective community care models by using the results of Seoul's outreach service which is the basis for Korean community care. The population of the study was the elderly aged 65 and 70 who participated in the Seoul's outreach community services 3rd stage (July 2017 - June 2018) and 4th stage (July 2018 to June 2019). 2,200 people were extracted by the proportional allocation method and home visit interviews were conducted on them. Subjects were divided into sub-groups based on chronic disease prevalence, and logistic regression was conducted to derive factors that affect the satisfaction of home visiting health care services. The results demonstrated that the elderly without chronic diseases were more satisfied when they received health education and counseling services, the elderly with one chronic disease were more satisfied when they received Community resource-linked services. In the case of elderly people with two or more chronic diseases, the service satisfaction level is increased when health condition assessment and Community resource-linked services are provided. Regardless of whether or not they have chronic diseases, service delivery time was a factor that increased satisfaction in home visiting health care. And the degree of explanation understanding was a factor that increased satisfaction for both single and complex chronic patients. Home Visiting health care services based on the community is a key component of the ongoing community care. In order to increase the sustainability and effectiveness of community care in the future, Community-oriented health care services based on the degree of chronic diseases of the elderly should be provided. In order to provide more effective services, however, it is necessary (1) to establish a linkage system to share health information of the subject held by the National Health Insurance Service to local governments and (2) to provide capacity-building education for visiting nurses to improve the quality of home visiting health care services. It is hoped that this study will be us ed as bas ic data for the successful settlement of community care.

• Journal of the Korean earth science society
• /
• v.43 no.3
• /
• pp.367-385
• /
• 2022

This study evaluates the temperature and precipitation results in East Asia simulated from the Hadley Centre Global Environmental Model version 3 regional climate model (HadGEM3-RA) developed by the UK Met Office. The HadGEM3-RA is conducted in the Coordinated Regional climate Downscaling Experiment-East Asia (CORDEX-EA) Phase II domain for 15 year (2000-2014). The spatial distribution of rainbands produced from the HadGEM3-RA by the summer monsoon is in good agreement with the Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation of water resources (APRODITE) data over the East Asia. But, precipitation amount is overestimated in Southeast Asia and underestimated over the Korean Peninsula. In particular, the simulated summer rainfall and APRODITE data show the least correlation coefficient and the maximum value of root mean square error in South Korea. Prediction of temperature in Southeast Asia shows underestimation with a maximum error during winter season, while it appears the largest underestimation in South Korea during spring season. In order to evaluate local predictability, the time series of temperature and precipitation compared to the ASOS data of the Seoul Meteorological Station is similar to the spatial average verification results in which the summer precipitation and winter temperature underestimate. Especially, the underestimation of the rainfall increases when the amounts of precipitation increase in summer. The winter temperature tends to underestimate at low temperature, while it overestimates at high temperature. The results of the extreme climate index comparison show that heat wave is overestimated and heavy rainfall is underestimated. The HadGEM3-RA simulated with a horizontal resolution of 25 km shows limitations in the prediction of mesoscale convective system and topographic precipitation. This study indicates that improvement of initial data, horizontal resolution, and physical process are necessary to improve predictability of regional climate model.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.50 no.4
• /
• pp.20-36
• /
• 2022

This study aims to provide basic data for high-quality street tree management by setting reasonable management items and appropriate unit prices by reviewing the adequacy of current street tree management. Currently, street tree management items, except for street tree pruning, use general landscape tree quantity per unit for the street tree management quantity per unit. KEPCO (Korea Electric Power Corporation) applied pruning items from standard electric production infrastructure and carried out the activities at an average unit price of 51% lower for heavy pruning and 39% lower for light pruning than the standard estimate. This was judged to be a level that could not maintain or increase the quality of street tree management. It was determined that an appropriate standard unit price for street tree management was necessary. To improve the quantity per unit for the proper management of street trees, it was necessary to review costs in the field. However, due to the absence of data on actual construction costs in the domestic landscape field, detailed items of the US RSMeans Building Construction Cost Data (RSMeans) were reviewed, and the actual construction costs were calculated by applying personal domestic expenses. As a result, the standard of the estimated unit showed a good ratio of 107% for heavy pruning of street tree pruning compared to the actual construction cost, but light pruning was underestimated with a 59% ratio. Shrub pruning was 82%, weeding was 92%, tree fertilization was 87%, and windbreak wall installation was 91% under-engineered. In addition, it was also confirmed that the watering by sprinkler trucks and chemical spraying were over-designed compared to the actual construction cost at the rates of 118% and 124%, respectively. Due to the specificity of the street trees, the increase in personal expenses and the input cost of equipment, such as road safety controls, were judged to be the main cause of the underestimation of items. Therefore, it is necessary to add items related to street trees and general landscape trees to the landscape maintenance items of the standard of the estimated unit.

• Journal of Korean Society of Environmental Engineers
• /
• v.38 no.12
• /
• pp.656-661
• /
• 2016

Manufacturing membrane materials with high selectivity and permeability is quite desirable but practically not possible, since the permeability and selectivity are usually inversely proportional. From the viewpoint of reducing the cost of $CO_2$ capture, module performance is even more important than the performance of membrane materials itself, which is affected by the permeance of the membrane (P, stagecut) and selectivity (S). As a typical example, when the mixture with a composition of 13% $CO_2$ and 87% of $N_2$ is fed into the module with 10% stage cut and selectivity 5, in the 10 parts of the permeate, $CO_2$ represents 4.28 parts and $N_2$ represents 5.72 parts. In this case, the $CO_2$ concentration in the permeate is 42.8% and the recovery rate of $CO_2$ in this first separation appears as 4.28/13 = 32.9%. When permeance and selectivity are doubled, however, from 10% to 20% and from 5 to 10, respectively, the $CO_2$ concentration in the permeant becomes 64.5% and the recovery rate is 12.9/13 = 99.2%. Since in this case, most of the $CO_2$ is separated, this may be the ideal condition. For a given feed concentration, the $CO_2$ concentration in the separated gas decreases if permeance is larger than the threshold value for complete recovery at a given selectivity. Conversely, for a given permeance, increasing the selectivity over the threshold value does not improve the process further. For a given initial feed gas concentration, if permeance or selectivity is larger than that required for the complete separation of $CO_2$, the process becomes less efficient. From all these considerations, we can see that there exists an optimum design for a given set of conditions.

• Progress in Medical Physics
• /
• v.23 no.1
• /
• pp.62-69
• /
• 2012

The dose re-calculation process using Megavoltage cone-beam CT images is inevitable process to perform the Adaptive Radiation Therapy (ART). The purpose of this study is to improve dose re-calculation accuracy using MVCBCT images by applying intensity calibration method and three dimensional rigid body transform and filtering process. The three dimensional rigid body transform and Gaussian smoothing filtering process to MVCBCT Rando phantom images was applied to reduce image orientation error and the noise of the MVCBCT images. Then, to obtain the predefined modification level for intensity calibration, the cheese phantom images from kilo-voltage CT (kV CT), MVCBCT was acquired. From these cheese phantom images, the calibration table for MVCBCT images was defined from the relationship between Hounsfield Units (HUs) of kV CT and MVCBCT images at the same electron density plugs. The intensity of MVCBCT images from Rando phantom was calibrated using the predefined modification level as discussed above to have the intensity of the kV CT images to make the two images have the same intensity range as if they were obtained from the same modality. Finally, the dose calculation using kV CT, MVCBCT with/without intensity calibration was applied using radiation treatment planning system. As a result, the percentage difference of dose distributions between dose calculation based on kVCT and MVCBCT with intensity calibration was reduced comparing to the percentage difference of dose distribution between dose calculation based on kVCT and MVCBCT without intensity calibration. For head and neck, lung images, the percentage difference between kV CT and non-calibrated MVCBCT images was 1.08%, 2.44%, respectively. In summary, our method has quantitatively improved the accuracy of dose calculation and could be a useful solution to enhance the dose calculation accuracy using MVCBCT images.

• Environmental and Resource Economics Review
• /
• v.14 no.1
• /
• pp.167-199
• /
• 2005

The following policy implications can be drawn from this study: 1) The Air Pollution Emission Amount Report published by the Ministry of Environment since 1991 classifies industries into 4 sectors, i. e., heating, manufacturing, transportation and power generation. Currently, the usability of report is very low and extra efforts should be given to refine the current statistics and to improve the industrial classification. 2) Big pollution industries are as follows - s7, s17 and s20. The current air pollution control policy for these sectors compared to other sectors are found to be inefficient. This finding should be noted in the implementation of future air pollution policy. 3) s10 and s17 are found to be a big polluting industrial sector and its pollution reduction effect is also significant. 4) The effect of emission coefficient (${\Delta}f$) has the biggest impact on the reduction of emission amount change and the effect of economic growth coefficient (${\Delta}y$) has the biggest impact on the increase of emission volume. The effect of production technology factor (${\Delta}D$) and the effect of the change of the final demand structure (${\Delta}u$) are insignificant in terms of the change of emission volume. 5) Further studies on emission estimation techniques on each industry sector and the economic analysis are required to promote effective enforcement of the total volume control system of air pollutants, the differential management of pollution causing industrial sectors and the integration of environment and economy. 6) Korea's economic growth in 1990 is not pollution-driven in terms of the Barry Commoner's hypothesis, even though the overall industrial structure and the demand structure are not environmentally friendly. It indicates that environmental policies for the improvement of air quality depend mainly on the government initiatives and systematic national level consideration of industrial structures and the development of green technologies are not fully incorporated.

• Korean Journal of Animal Reproduction
• /
• v.21 no.3
• /
• pp.293-302
• /
• 1997

Follicular oocytes of Grade I and II were collected from 2~6 mm ovarian follicles and matured in vitro (IVM) for 24 hrs in TCM-199 su, pp.emented with 35$\mu\textrm{g}$/ml FSH, 10$\mu\textrm{g}$/ml LH, and 1$\mu\textrm{g}$/ml estradiol-17$\beta$ at 39$^{\circ}C$ under 5% CO2 in air. They were fretilized in vitro (IVF) by epididymal spermatozoa capacitated with heparin for 12 hrs. The zygotes were then co-cultured in vitro with bovine oviducted epithelial cells (BOEC) for 7 to 9 days. The optimal time for IVM, the successful enucleation of IVM oocytes by micromanipulation at different oocyte ages after IVM, and the ideal culture system for IVM for effective IVF and in vitro development of IVM-IVF embryos was examined for in vitro production of nuclear recipient oocytes and nuclear donor embryos. To improve the efficiency of nuclear transplantation (NT) of IVF embryo into IVM follicular oocytes, this study evaluated the optimal electric condition and oocytes age for activation of IVM oocytes and in vitro development of NT embryos. In vitro development of NT embryos with preactivation or non-preactivation in enucleation oocytes, cell number of IVN-IVF embryos, and NT embryos wre also examined. The results obtained were as follows; 1. The most suitable enucleation time was at 24 hpm (83.3%) rather than that of 28 hpm(69.6%) and 32 hpm(50.0%). 2. There was no difference among the fusion rates of NT embryos at the voltages of 0.75, 1.0 and 1.5 kV/cm, but the in vitro development rates to morule and blastocyst were significantly (P<0.05) higher at the voltage of 0.75(12.5%) and 1.0kV/cm (12.6%) compared to 1.5kV/cm(0%). 3. No significant difference in activation rates were seen in NT embryos stimulated for 30, 60 and 120 $\mu$sec (71.7, 85.2 and 71.9%, respectively), but the in vitro development rates to morulae and blastocyst were significantly (P<0.05) higher in the oocytes stimulated for 30 $\mu$sec (11.6%) and 60 $\mu$sec(10.7%) than 120 $\mu$sec(0.0%). 4. The fusion rates (71.0 and 87.3%) and the in vitro development rates (9.1 and 12.7%) to morula and blastocyst were seen in the NT embryos stimulated at 28 and 32 hpm under the condition of 1.0 kV/ml, 60 $\mu$sec. However, at 24 hpm the fusion rates were 64.8% and the in vitro development to morula and blastocyst were not seen. 5. The fusion rates between the 8~12, 13~17 and 18~22-cell stage of IVM-IVF embryos were not significantly different. The in vitro development rates of the fused embryos to morula and blastocyst which were received from a blastomere of 8~12, 13~17 and 18~22-cell stages of IVM-IVF embryos were 14.9, 8.3 and 6.5%, respectively. 6. The in vitro development rate of the enucleated recipient oocytes with preactivation (24.2%) to morula and blastocyst was significantly (P<0.05) higher than that of non-preactivation (12.8%). 7. The cell numbers of NT blastocyst and IVM-IVF blastocyst cultured during 7~9 days were 63$\pm$11 and 119$\pm$23, and then their the mean cell cycle number were 5.98 and 6.89, respectively.

• Management & Information Systems Review
• /
• v.37 no.3
• /
• pp.83-113
• /
• 2018

The purpose of this study to empirically examine a smart work investment and job performance by change resistance. Firstly, There investigates mediating role of the communication between the smart work investment and the job performance. Secondly, It will identify the job productivity differences through a level of organizational change resistance that reduced smart work investment. The smart work is to provide the flexibility of time and location and is a working method to improve a work productivity of organization members. The introduction of smart work means the adoption of new organizational culture, institution and technology and requires a novel change of a custom and pattern on existing organization culture and institution because of transformation form of communication and collaboration. The method of this study adopts a structural equation model to test a mediating effect of communication and a moderating effect of change resistance level. This model confirms whether smart work investments provide a positive impact on communication and organizational productivity. In addition, I will classify a change resistance level of smart work by cluster analysis and then check a critical path difference of job productivity between each group. As a result, The organizational IT, institution and culture on the smart work investment appeared to important influencers in communication and also had a direct influence of individual performance. Also, The three independent variables of smart work investment have an indirect influence of individual and organizational performance through communication mediating variables. However, the organizational IT and institution as independent variables do not provide direct influence of organization performance. Nevertheless, two independent variables of organizational IT and institution have an indirect influence the organization performance through communication mediating variables. As a result of confirming a productivity of three groups on organization resistance, there was a difference the individual and organizational performance among groups. The low-level group of organizational resistance showed high coefficient value of performance compared to other groups. The group analysis implications, The smart work investment appeared significantly to revise the institution first, build culture secondly and advanced technology lastly. The theoretical implication from this study contributes an extension of social science theory through socio-technical systems, institution, culture, change resistance and job performance based on smart work. The practical implications explain the smart work success in step-by-step investment rather than radical investment as level management of change resistance. In future research, the smart work performance between private and public firms will analyze a difference of the organizational culture, institution, technology and performance.

• Journal of Intelligence and Information Systems
• /
• v.28 no.1
• /
• pp.69-88
• /
• 2022

One of the characteristics of South Korea's economic structure is that it is highly dependent on exports. Thus, many businesses are closely related to the global economy and diplomatic situation. In addition, small and medium-sized enterprises(SMEs) specialized in exporting are struggling due to the spread of COVID-19. Therefore, this study aimed to develop a model to forecast exports for next year to support SMEs' export strategy and decision making. Also, this study proposed a strategy to recommend promising export countries of each item based on the forecasting model. We analyzed important variables used in previous studies such as country-specific, item-specific, and macro-economic variables and collected those variables to train our prediction model. Next, through the exploratory data analysis(EDA) it was found that exports, which is a target variable, have a highly skewed distribution. To deal with this issue and improve predictive performance, we suggest a separated learning method. In a separated learning method, the whole dataset is divided into homogeneous subgroups and a prediction algorithm is applied to each group. Thus, characteristics of each group can be more precisely trained using different input variables and algorithms. In this study, we divided the dataset into five subgroups based on the exports to decrease skewness of the target variable. After the separation, we found that each group has different characteristics in countries and goods. For example, In Group 1, most of the exporting countries are developing countries and the majority of exporting goods are low value products such as glass and prints. On the other hand, major exporting countries of South Korea such as China, USA, and Vietnam are included in Group 4 and Group 5 and most exporting goods in these groups are high value products. Then we used LightGBM(LGBM) and Exponential Moving Average(EMA) for prediction. Considering the characteristics of each group, models were built using LGBM for Group 1 to 4 and EMA for Group 5. To evaluate the performance of the model, we compare different model structures and algorithms. As a result, it was found that the separated learning model had best performance compared to other models. After the model was built, we also provided variable importance of each group using SHAP-value to add explainability of our model. Based on the prediction model, we proposed a second-stage recommendation strategy for potential export countries. In the first phase, BCG matrix was used to find Star and Question Mark markets that are expected to grow rapidly. In the second phase, we calculated scores for each country and recommendations were made according to ranking. Using this recommendation framework, potential export countries were selected and information about those countries for each item was presented. There are several implications of this study. First of all, most of the preceding studies have conducted research on the specific situation or country. However, this study use various variables and develops a machine learning model for a wide range of countries and items. Second, as to our knowledge, it is the first attempt to adopt a separated learning method for exports prediction. By separating the dataset into 5 homogeneous subgroups, we could enhance the predictive performance of the model. Also, more detailed explanation of models by group is provided using SHAP values. Lastly, this study has several practical implications. There are some platforms which serve trade information including KOTRA, but most of them are based on past data. Therefore, it is not easy for companies to predict future trends. By utilizing the model and recommendation strategy in this research, trade related services in each platform can be improved so that companies including SMEs can fully utilize the service when making strategies and decisions for exports.