• Journal of Korea Water Resources Association
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• v.51 no.7
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• pp.607-616
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• 2018

Flow regime-based ANFIS Dam Inflow Prediction (FADIP) model is developed and compared with ANFIS Dam Inflow Prediction (ADIP) model in this study. The selected study area is the Chungju and Soyang multi-purpose dam watersheds in South Korea. The dam inflow, precipitation and monthly weather forecast information are used as input variables of the models. The training and validation periods of the models are 1987~2010 for Chungju and 1984~2010 for Soyang dam watershed. The testing periods for both watersheds are 2011~2016. The results of training and validation indicate that FADIP has better training ability than ADIP for predicting dam inflow in normal and low flow regimes. In the result of testing, ADIP shows low predictability of dam inflow in the low flow regime due to the model tuning on all flow regime together. However, FADIP demonstrates the improved accuracy over the entire period compared to ADIP, especially during the normal and low flow seasons. It is concluded that FADIP is valuable for the prediction of dam inflow in the case of drought years, and useful for water supply management of the multi-purpose dam.

• Korea Journal of Hospital Management
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• v.16 no.4
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• pp.35-66
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• 2011

This study analyzed efficiency by utilizing DEA analytical technique centering on materials for 2009 of 20 major university hospitals in capital area. Input variables were utilized professor & full-time doctor, resident, nurse & number of bed hospitals. Output variables were analyzed by dividing number of annual outpatients & number of annual inpatients, and annually total outpatient profit & inpatient profit into a model of the standard for number of patients and the standard for medical profit. DEA analysis was elicited efficiency score by applying CCR, BCC, BFG, scale profit, and SE model. Through t-test after eliciting efficiency score, the implications were suggested by comparing efficiency between DMU in Seoul and DMU in capital area, by comparing between high-class general hospitals and general hospitals, and by comparing between high-class general hospitals in Seoul and 5 big hospitals. As a result of analysis, the major university hospitals in capital area showed high efficiency as a whole close to "1," but indicated low efficiency relatively in CCR field. Thus, the expansion in scale within capital area was indicated to reach the limit. Second, in a model of analyzing the standard for number of patients, the medical institutions, which are being operated efficiently, were indicated to be 10 DMUs. In the standard for medical profit, 12 DMUs were analyzed to be operated efficiently. Third, the efficiency in general hospital was higher than high-class general hospital. Thus, the efficiency of operation was indicated to be more important than scale. Also, large high-class hospitals(big 5) where are located in downtown Seoul showed the higher efficiency than other general high-class general hospitals, but were indicating very low efficiency in some DMUs. Fourth, as a result of generalizing and evaluating the number of patients and the medical profit, the efficient DMU was indicated to be more when analyzing on the basis of medical profit than the standard for number of patients. Thus, major university hospitals in capital area were indicated to make more effort for section in medical profit. Based on the analytical results of efficiency, a strategy for reinforcing efficiency in inefficient DMU was indicated to be needed a strategy of creating customers for promoting number of patients and a strategy for making operation efficient for increasing profitability.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1183-1193
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• 2021

Low flow affects various fields such as river water supply management and planning, and irrigation water. A sufficient period of flow data is required to calculate the Flow Duration Curve. However, in order to calculate the Flow Duration Curve, it is essential to secure flow data for more than 30 years. However, in the case of rivers below the national river unit, there is no long-term flow data or there are observed data missing for a certain period in the middle, so there is a limit to calculating the Flow Duration Curve for each river. In the past, statistical-based methods such as Multiple Regression Analysis and ARIMA models were used to predict sulfur in the unmeasured watershed, but recently, the demand for machine learning and deep learning models is increasing. Therefore, in this study, we present the DNN technique, which is a machine learning technique that fits the latest paradigm. The DNN technique is a method that compensates for the shortcomings of the ANN technique, such as difficult to find optimal parameter values in the learning process and slow learning time. Therefore, in this study, the Flow Duration Curve applicable to the unmeasured watershed is calculated using the DNN model. First, the factors affecting the Flow Duration Curve were collected and statistically significant variables were selected through multicollinearity analysis between the factors, and input data were built into the machine learning model. The effectiveness of machine learning techniques was reviewed through statistical verification.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.1-21
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• 2021

As the global business environment changes, uncertainties in technology development and market needs increase, and competition among companies intensifies, interests and demands for R&D activities of individual companies are increasing. In order to cope with these environmental changes, R&D companies are strengthening R&D investment as one of the means to enhance the qualitative competitiveness of R&D while paying more attention to facility investment. As a result, facilities or R&D investment elements are inevitably a burden for R&D companies to bear future uncertainties. It is true that the management strategy of increasing investment in R&D as a means of enhancing R&D capability is highly uncertain in terms of corporate performance. In this study, the structural factors that influence the R&D capabilities of companies are explored in terms of technology management capabilities, R&D capabilities, and corporate classification attributes by utilizing data mining techniques, and the characteristics these individual factors present according to the level of R&D capabilities are analyzed. This study also showed cluster analysis and experimental results based on evidence data for all domestic R&D companies, and is expected to provide important implications for corporate management strategies to enhance R&D capabilities of individual companies. For each of the three viewpoints, detailed evaluation indexes were composed of 7, 2, and 4, respectively, to quantitatively measure individual levels in the corresponding area. In the case of technology management capability and R&D capability, the sub-item evaluation indexes that are being used by current domestic technology evaluation agencies were referenced, and the final detailed evaluation index was newly constructed in consideration of whether data could be obtained quantitatively. In the case of corporate classification attributes, the most basic corporate classification profile information is considered. In particular, in order to grasp the homogeneity of the R&D competency level, a comprehensive score for each company was given using detailed evaluation indicators of technology management capability and R&D capability, and the competency level was classified into five grades and compared with the cluster analysis results. In order to give the meaning according to the comparative evaluation between the analyzed cluster and the competency level grade, the clusters with high and low trends in R&D competency level were searched for each cluster. Afterwards, characteristics according to detailed evaluation indicators were analyzed in the cluster. Through this method of conducting research, two groups with high R&D competency and one with low level of R&D competency were analyzed, and the remaining two clusters were similar with almost high incidence. As a result, in this study, individual characteristics according to detailed evaluation indexes were analyzed for two clusters with high competency level and one cluster with low competency level. The implications of the results of this study are that the faster the replacement cycle of professional managers who can effectively respond to changes in technology and market demand, the more likely they will contribute to enhancing R&D capabilities. In the case of a private company, it is necessary to increase the intensity of input of R&D capabilities by enhancing the sense of belonging of R&D personnel to the company through conversion to a corporate company, and to provide the accuracy of responsibility and authority through the organization of the team unit. Since the number of technical commercialization achievements and technology certifications are occurring both in the case of contributing to capacity improvement and in case of not, it was confirmed that there is a limit in reviewing it as an important factor for enhancing R&D capacity from the perspective of management. Lastly, the experience of utility model filing was identified as a factor that has an important influence on R&D capability, and it was confirmed the need to provide motivation to encourage utility model filings in order to enhance R&D capability. As such, the results of this study are expected to provide important implications for corporate management strategies to enhance individual companies' R&D capabilities.

• Journal of Life Science
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• v.12 no.4
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• pp.433-441
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• 2002

There has been an increasing public concern about environmental safety and human health of field crops while customer consumes more and more field crops, to which overdose and residual chemicals were applied. As a solution for the problems, construction of sustainable agroecosystem is spreading out to pursuit the economic value of agricultural management as well as to meet environment concern. Public has extended their understanding on the preservation of environment and safeness of agricultural products, and governmental policy toward sustainable agriculture drives rapid increase of the production of sustainable agricultural products. Under this circumstances, it is time to encourage more consumption and to activate market system for the sustainable agricultural products. This study was initiated to diagnose the problems and future direction of domestic sustainable agriculture by analyzing the overall opinions of consumer on the sustainable agriculture. The results are as follows: The pursuit of low input management is a prerequisite to creat high valued agricultural products, and serious consideration should be taken to produce clean crops using natural products. Consummers are willing to pay 10∼50% more prices if the products get certified by official eco-label programs. It is believed that practice of sustainable agriculture using biopesticide and natural pesticide would accelerate the rapid extension of this pro-environmental agricultural management. To activate production and consumption of sustainable agricultural products correct informations on safety should be addressed to customer, and confidence has to be brought about from customer. This could be done by obtaining various and efficient distribution route, product competency for quality, upgraded sales strategy, maximum utilization of certificate system, and practice of recall system, so on.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.10
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• pp.89-100
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• 2018

The precedent study stage of defense programs is a project stage that is conducted to support the determination of an efficient acquisition method of the weapon system determined by the requirement. In this study, the FTA/FMEA technique was used in the safety analysis process to identify elements to be conducted in the precedent study stage and a methodology for deriving the key review elements through conceptualization and tailoring was suggested. To supplement the key elements derived from the existing research, it is necessary to analyze various events that may arise from key elements. To accomplish this, the HAZOP technique for safety analysis in other industrial fields was used to supplement the results of kdy element derivation. We analyzed and modeled the execution procedure by establishing input/output information and association with the key elements of the precedent study stage derived by linking HAZOP/FTA/FMEA techniques. In addition, performance maturity was evaluated for performance of precedent study, and a risk-based response manual was generated based on inter-working information with key elements with low maturity. Based on the results of this study, it is possible to meet the performance, cost, and schedule of the project implementation through application of the key elements and procedures and the risk management response manual in the precedent study stage of the defense program.

• Health Policy and Management
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• v.8 no.1
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• pp.15-51
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• 1998

compensation is a major function of human resources management. The hospital industry is characterized by its remarkable labor intensity and human resource input by unit. That is why the hospital industry has a higher level of wage/cost ration. The issues of how much the hospital personnel's direct financial compensation amounts to and how the organizational and other factors generate compensation differentiation, are central problems for research in hospitals. But there have been few approaches to study staff compensation in hospitals, its magnitude and inter-hospital relative compensation amounts for the same personnel. A worker who moves from low-wage to a high-wage employer can usually increase his or her pay without change in job description. This means in the cases of same jobs, relative importance is different for each hospitals. The purpse of this study were to find the compensation levels of hospital personnel and to determine the factors affecting compensation levels of hospital personnel. The unit of analysis is the hospital and 145 hospitals were studied for nurse(RN), medical technoloist(MT), managerial personnel(MP) and 100 hospitals for medical doctor(MD). In this study the definitions of direct financial compensation are before tax, excluding employer's contriution and total annual remuneration received by the employee. Main findings of the research can be summarized as follows. 1. Direct financial compensation of hospital personnel are MD 45,056,000 won, RN 9,222,000 won, MT 9,513,000 won and MP 9,185,000 won in the starting year's employment in hospital. 2. According to determinants of hospital personnel compensations, there are no statistical significant variables to determine the level of MD's compensation. Wlith RN and MT's compensation level, the greater the patient revenue per 100 hospital beds, the higher the RN compensation and the tertiary hospital's compensation is much more than other types of hospitals. The location of hospital is another determinant factor for the MT's compensation level. Hospitals that are in the uban area have lower compensation level than rural area. There are the same results in MP with MT. Conclusions can be drawn from the results of the study. First, the wage differentiation of MD and other health personnel still remains and the differentiation existed in inter and intra job personnel of hospitals. Second, determinants of hospital personnel personnel compensation level are patient revenue, location, and type of hospital level.

• Journal of KIISE:Computing Practices and Letters
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• v.7 no.5
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• pp.510-521
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• 2001

Image retrieval system should be construct for searching fast, efficient image be extract the accurate feature information of image with more massive and more complex characteristics. Image retrieval system are essential differences between image databases and traditional databases. These differences lead to interesting new issues in searching of image, data modeling. So, cause us to consider new generation method of database, efficient retrieval method of image. In this paper, To extract feature information of edge using in searching from input image, we was performed to extract the edge by convolution Laplacian mask and input image, and we implemented the annotation-based and content-based image retrieval system for searching fast, efficient image by generation image database from extracting feature information of edge and metadata. We can improve the performance of the image contents retrieval, because the annotation-based and content-based image retrieval system is using image index which is made up of the content-based edge feature extract information represented in the low level of image and annotation-based edge feature information represented in the high level of image. As a conclusion, image retrieval system proposed in this paper is possible the accurate management of the accumulated information for the image contents and the information sharing and reuse of image because the proposed method do construct the image database by metadata.

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.3
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• pp.191-208
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• 2024

In this study, a hydro-mechanical-damage coupled analysis model was developed to evaluate the structural safety of radioactive waste disposal structures. The Mazars damage model, widely used to model the fracture behavior of brittle materials such as rocks or concrete, was coupled with conventional hydro-mechanical analysis and the developed model was verified via theoretical solutions from literature. To derive the numerical input values for damage-coupled analysis, uniaxial compressive strength and Brazilian tensile strength tests were performed on concrete samples made using the mix ratio of the disposal concrete silo cured under dry and saturated conditions. The input factors derived from the laboratory-scale experiments were applied to a two-dimensional finite element model of the concrete silos at the Wolseong Nuclear Environmental Management Center in Gyeongju and numerical analysis was conducted to analyze the effects of damage consideration, analysis technique, and waste loading conditions. The hydro-mechanical-damage coupled model developed in this study will be applied to the long-term behavior and stability analysis of deep geological repositories for high-level radioactive waste disposal.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.17 no.4
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• pp.252-261
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• 2012

To determine the temporal variations of submarine groundwater discharge (SGD) and SGD-driven nutrients inputs, we measured the seepage rate and the nutrient concentrations of pore water/groundwater in Bangdu Bay of Jeju Island at two and three month intervals from September 2009 to September 2010. The seepage rate of groundwater ranged from 0 to 330 cm/day (average ~170 cm/day) during the five sampling periods, which increased sharply from high tide to low tide due to changes in hydraulic pressure gradient between water table in land and water sea level in the coastal ocean by the tidal cycles. The submarine inputs of groundwater were also relatively higher in summer than in winter. The nutrient fluxes from SGD were about 90~100%, 70~95%, and 65~100% of the total input (except from open ocean waters) for dissolved inorganic nitrogen (DIN), phosphorus (DIP), and silicate (DSi), respectively, potentially supporting about 0.9~33 g $carbon/m^2/day$ of new primary production in Baugdu Bay. Thus, our study suggests that SGD-driven nutrients may play an important role in the eutrophication and biological production in the coastal ocean of Jeju Island.