There has been continuous efforts to manage the water resources for the required water quality criterion at river channel in Korea. However, we could not obtain the partial improvement only for the point source pollutant such as, wastewater from urban and industrial site through the water quality management. Therefore, it is strongly needed that the Best Management Practice(BMP) throughout the river basin for water quality management including non-point source pollutant loads. This problem should be resolved by recognizing the non-point source pollutant loads from upstream river basin to the outlet depends on the land use and soil type characteristic of the river basin using the computer simulation by distributed parameter model based on the detailed investigation and the application of Geographic Information System(GIS). Used in this study, Annualized Agricultural Non-Point Source Pollution (AnnAGNPS) model is a tool suitable for long term evaluation of the effects of BMPs and can be used for un gauged watershed simulation of runoff and sediment yield. Now applications of model are in progress. So we just describe the limited result. However If well have done modeling and have investigated of propriety of model, well achieve our final goal of this study.
Not only the government, but private corporations have contributed a lot to growth and development of culture. Corporations have mainly made charitable, dispensational Macenat activities which are separate from their business activities. Such an one-sided and charitable method of supporting culture cannot last long - Part of the reason why the number of corporations supporting culture is decreasing lies in it. In order to have sustainable partnership with culture, first, corporations should figure out needs of the other party. Second, the activities of corporations to support culture should be corporate citizenship activities which are linked to their business activities. In particular, the existing concepts of CSR and CSV have some limits. CSR separates business activities of corporations and their social contribution activities, and CSV mainly assumes corporate social activities helpful to their business activities. But, the concept of corporate citizenship suggested in this study assumes corporate activities where corporations do their best not only in their business activities, but in solution of social problems. Accordingly, searching for the ways to practice corporate citizenship, this study analyzed global agendas of UN, UNESCO, and UCLG which suggest sustainable development with culture and corporate citizenship activities related with culture among corporations in Korea and other countries. The findings and hints of the analysis are as follows. First, corporate citizenship activities can contribute to building of unique images of corporations and improvement of brand identities. Second, such activities can help corporations to be born again as life style companies by using local cultures and their attractiveness. Third, corporations should have partnership with cultural associations creating shared values and provide them with continuous and stable support. And, cultural associations should try to grow with corporations through efforts to develop attractive contents and programs harmonious with management purposes of corporations.
Kim, Il Jung;Kim, Woo Soon;Kim, Joon Young;Chae, Hee Su;Woo, Ji Yeong;Do, Kyung Min;Lim, Sung Hoon;Shin, Min Soo;Lee, Ji Eun;Kim, Heung Nam
Journal of Korean Society for Quality Management
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v.50
no.4
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pp.647-664
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2022
Purpose: The purpose of this study is to derive major policies that domestic small and medium-sized manufacturing companies should consider to maximize productivity and quality improvement by utilizing manufacturing data and AI, and to find priorities and implications. Methods: In this study, domestic and international issues and literature review by country were conducted to derive major considerations such as manufacturing AI technology, manufacturing AI talent, manufacturing AI data and manufacturing AI ecosystem. Additionally, the questionnaire survey targeting 46 experts of manufacturing data and AI industry were conducted. Finally, the major considerations and detailed factors importance were derived by applying the Analytic Hierarchy Process (AHP). Results: As a result of the study, it was found that 'manufacturing AI technology', 'manufacturing AI talent', 'manufacturing AI data', and 'manufacturing AI ecosystem' exist as key considerations for domestic manufacturing AI. After empirical analysis, the importance of the four key considerations was found to be 'manufacturing AI ecosystem (0.272)', 'manufacturing AI data (0.265)', 'manufacturing AI technology (0.233)', and 'manufacturing AI talent (0.230)'. The importance of the derived four viewpoints is maintained at a similar level. In addition, looking at the detailed variables with the highest importance for each of the four perspectives, 'Best Practice', 'manufacturing data quality management regime, 'manufacturing data collection infrastructure', and 'manufacturing AI manpower level of solution providers' were found. Conclusion: For the sustainable growth of the domestic manufacturing AI ecosystem, it should be possible to develop and promote manufacturing AI policies in a balanced way by considering all four derived viewpoints. This paper is expected to be used as an effective guideline when developing policies for upgrading manufacturing through domestic manufacturing data and AI in the future.
Due to COVID-19 and soaring participation of individual investors, large-scale transactions exceeding system capacity limits have been reported frequently in the capital market. The capital market IT systems, which the impact of system failure is very critical, have encountered unexpectedly tremendous transactions in 2020, resulting in a sharp increase in system failures. Despite the fact that many companies maintained large-scale system capacity planning policies, recent transaction influx suggests that a new approach to capacity planning is required. Therefore, this study developed capital market IT system capacity planning models using machine learning techniques and analyzed those performances. In addition, the performance of the best proposed model was improved by using sentiment index that can promptly reflect the behavior of investors. The model uses empirical data including the COVID-19 period, and has high performance and stability that can be used in practice. In practical significance, this study maximizes the cost-efficiency of a company, but also presents optimal parameters in consideration of the practical constraints involved in changing the system. Additionally, by proving that the sentiment index can be used as a major variable in system capacity planning, it shows that the sentiment index can be actively used for various other forecasting demands.
Determination of the cause of malignant pleural effusions is important for treatment and management, especially in cases of unknown primaries. There are limited biomarkers available for prediction of the cause of malignant pleural effusion in clinical practice. Hence, we evaluated pleural levels of five tumor biomarkers (CEA, AFP, CA125, CA153 and CA199) in predicting the cause of malignant pleural effusion in a retrospective study. Kruskal-Wallis or Mann-Whitney U tests were carried out to compare levels of tumor markers in pleural effusion among different forms of neoplasia - lung squamous cell carcinoma, adenocarcinoma, or small cell carcinoma, mesothelioma, breast cancer, lymphoma/leukemia and miscellaneous. Receiver operator characteristic analysis was performed to evaluate sensitivity and specificity of biomarkers. The Kruskal-Wallis test showed significant differences in levels of pleural effusion CEA (P<0.01), AFP (P<0.01), CA153 (P<0.01) and CA199 (P<0.01), but not CA125 (P>0.05), among the seven groups. Receiver operator characteristic analysis showed that, compared with other four tumor markers, CA153 was the best biomarker in diagnosing malignant pleural effusions of lung adenocarcinoma (area under curve (AUC): 0.838 (95%confidence interval: 0.787, 0.888); cut-off value: 10.2U/ml; sensitivity: 73.2% (64.4-80.8)%, specificity: 85.2% (77.8-90.8)%), lung squamous cell carcinoma (AUC: 0.716 (0.652, 0.780); cut-off value: 14.2U/ml; sensitivity: 57.6% (50.7-64.3)%, specificity: 91.2% (76.3-98.0)%), and small-cell lung cancer (AUC: 0.812 (0.740, 0.884); cut-off value: 9.7U/ml; sensitivity: 61.5% (55.0-67.8)%, specificity: 94.1% (71.2-99.0)%); CEA was the best biomarker in diagnosing MPEs of mesothelioma (AUC: 0.726 (0.593, 0.858); cut-off value: 1.43ng/ml; sensitivity: 83.7% (78.3-88.2)%, specificity: 61.1% (35.8-82.6)%) and lymphoma/leukemia (AUC: 0.923 (0.872, 0.974); cut-off value: 1.71ng/ml; sensitivity: 82.8% (77.4-87.3)%, specificity: 92.3% (63.9-98.7)%). Thus CA153 and CEA appear to be good biomarkers in diagnosing different causes of malignant pleural effusion. Our findings implied that the two tumor markers may improve the diagnosis and treatment for effusions of unknown primaries.
BACKGROUND/OBJECTIVES: This study aimed to investigate cancer-specific survival (CSS) and associated risk factors in elderly gastric cancer (EGC) patients. SUBJECTS/METHODS: EGC patients (≥ 70 yrs) who underwent curative gastrectomy between January 2013 and December 2017 at our hospital were included. Clinicopathologic characteristics and survival data were collected. Receiver operating characteristic (ROC) analysis was used to extract the best cutoff point for body mass index (BMI). A Cox proportional hazards model was used to determine the risk factors for CSS. RESULTS: In total, 290 EGC patients were included, with a median age of 74.7 yrs. The median follow-up time was 31 (1-77) mon. The postoperative 1-yr, 3-yr and 5-yr CSS rates were 93.7%, 75.9% and 65.1%, respectively. Univariate analysis revealed risk factors for CSS, including age (hazard ratio [HR] = 1.08; 95% confidence interval [CI], 1.01-1.15), intensive care unit (ICU) admission (HR = 1.73; 95% CI, 1.08-2.79), nutritional risk screening (NRS 2002) score ≥ 5 (HR = 2.33; 95% CI, 1.49-3.75), and preoperative prognostic nutrition index score < 45 (HR = 2.06; 95% CI, 1.27-3.33). The ROC curve showed that the best BMI cutoff value was 20.6 kg/m2. Multivariate analysis indicated that a BMI ≤ 20.6 kg/m2 (HR = 2.30; 95% CI, 1.36-3.87), ICU admission (HR = 1.97; 95% CI, 1.17-3.30) and TNM stage (stage II: HR = 5.56; 95% CI, 1.59-19.43; stage III: HR = 16.20; 95% CI, 4.99-52.59) were significantly associated with CSS. CONCLUSIONS: Low BMI (≤ 20.6 kg/m2), ICU admission and advanced pathological TNM stages (II and III) are independent risk factors for CSS in EGC patients after curative gastrectomy. Nutrition support, better perioperative management and early diagnosis would be helpful for better survival.
Two major issues of the blood bank management are quality assurance and inventory control. Recently, in Korea blood donation has gained popularity increasingly to allow considerable improvement of the quality assurance with respect to blood collection, transportation, storage, component preparation skills and hematological tests. Nevertheless the inventory control, the other issue of blood bank management, has been neglected so far. For the supply of blood by donation barely meets the demand, the blood bank policy on the inventory control has been 'the more the better.' The shortage itself by no means unnecessitate inventory control. In fact, in spite of shortage, no small amount of blood is outdated. The efficient blood inventory control makes it possible to economize the blood usage in the practice of state-of-the-art medical care. For the efficient blood inventory control in Korean hospitals, this tudy is to develop formulae forecasting the standard blood inventory level and suggest a set of policies improving the blood inventory control. For this study informations of $A^+$ whole bloods and packed cells inventory control were collected from a University Hospital and the Central Blood Bank of the Korean Red Cross. Using this informations, 1,461 daily blood inventory records were formulated.48 varieties of blood inventory control environment were identified on the basis of selected combinations of 4 inventory control variables-crossmatch, transfusion, inhospital donation and age of bloods from external supply. In order to decide the optimal blood inventory level for each environment, simulation models were designed to calculate the measures of performance of each environment. After the decision of 48 optimal blood inventory levels, stepwise multiple regression analysis was started where the independent variables were 4 inventory control variables and the dependent variable was optimal inventory level of each environment. Finally the standard blood inventory level decision rule was developed using the backward elimination procedure to select the best regression equation. And the effective alternatives of the issuing policy and crossmatch release period were suggested according to the measures of performance under the condition of the standard blood inventory level. The results of this study' were as follows ; 1. The formulae to calculate the standard blood inventory level($S^*$)was $S^*=2.8617X(d)^{0.9342}$ where d is the mean daily crossmatch(demand) for a blood type. 2. The measures of performace - outdate rate, average period of storage, mean age of transfused bloods, and mean daily available inventory level - were improved after maintenance of the standard inventory level in comparison with the present system. 3. Issuing policy of First In-First Out(FIFO) decreased the outdate rate, while Last In-First Out(LIFO) decreased the mean age of transfused bloods. The decrease of the crossmatch release period reduced the outdate rate and the mean age of transfused bloods.
Korean Journal of Construction Engineering and Management
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v.19
no.2
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pp.38-49
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2018
Since the ratification of the Paris Agreement (COP21), the government is continuously strengthening policies for the reduction of greenhouse gas of the construction industry in accordance with the growing importance of reducing greenhouse gas and obligation of the government. Especially, the government emphasizes the need to improve the energy performance of old public buildings. Since 2014, the government is running a pilot project in which the government supports the construction cost of the green remodeling project of old public buildings and it is intended to develop the best practice of green remodeling and activate the green remodeling in the private sector. In this study, we analyzed the economical efficiency of the old public buildings by each level through green remodeling and conducted building related investigation and equipment measurement to plan the alternatives of the corresponding buildings. The improvement plan is a green remodeling plan that integrates alternatives. Five improvement plans were developed for each level to analyze the economic feasibility of each plan. As for the analysis method, the first energy demand amount calculation and the LCC analysis were performed through ECO2. In the LCC aspect, the improved 3/4 plan (middle level plan) was the most excellent and results were obtained in the order of the highest cost plan followed by the lowest cost plan. As a result, it is expected that it can be utilized as a basic data for future green remodeling performance plan and economic feasibility analysis in the future.
This study calculated meta Malmquist indices and their bootstraped estimates and then decomposed them into technical efficiency change(TEC), technology change(TC), pure technology catch up(PTCU), frontoer catch up(FCU), using annual data set of general hospitals from year 2007 to 2011 collected by Korean Hospital Association and then analyzed productivity change and technology gap of Korean general hospitals. The results and implications were as follows below. First, public general hospitals showed higher meta technical efficiencies than private general hospitals while exhibited lower technology gap ratio which meant a few large private general hospitals led the whole general hospitals. Second, group productivity of private general hospitals increased larger than public general hospitals due to the differences of PTCU rather than FCU. But, there was no statistically significant differences for technical efficiency, productivity change, technology gap. Thus, public general hospitals played the same role as the private general hospitals in terms of the number of patients treated. But, considering financial hardships of public general hospitals, public hospitals needed to share and learn medical and managerial skills of the best practice of private general hospitals.
Sung-Man, Lim;Han-Sol, Kim;Ha-Na, Choi;Na-Eun, Lee;Seong-Un, Kim
Journal of the Korean Society of Earth Science Education
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v.15
no.3
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pp.322-334
/
2022
This study attempted to understand the difficulties experienced in program development and class operation of instructors in the hands-on science class and the needs for training based on them. For this study, an online survey was conducted on 193 instructors in the hands-on science class in 2022, and interviews were conducted on 13 instructors. As a result, the difficulties of developing programs for hands-on science class instructors were due to lack of class content, lack of program development budget, lack of equipment necessary for class operation, and difficulty in applying various educational methods such as discussion and practice. The preferred training contents were in the order of the latest science and technology, reconstruction methods of existing programs, and regional specialization technology. In addition, it was found that the difficulties experienced by instructors in class management stemmed from the method of operating hands-on science classes using experience kits. Accordingly, instructor education should be provided in the direction of helping instructors to provide the best education in the situation of the hands-on science classroom.
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