• Journal of Life Science
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• v.29 no.8
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• pp.861-870
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• 2019

This study was undertaken to establish optimum medium compositions for cost-effective mannitol production by Leuconostoc mesenteroides SRCM201425 isolated from kimchi. L. mesenteroides SRCM21425 from kimchi was selected for efficient mannitol production based on fructose analysis and identified by its 16S rRNA gene sequence, as well as by carbohydrate fermentation pattern analysis. To enhance mannitol production by L. mesenteroides SRCM201425, the effects of carbon, nitrogen, and mineral sources on mannitol production were first determined using Plackett-Burman design (PBD). The effects of 11 variables on mannitol production were investigated of which three variables, fructose, sucrose, and peptone, were selected. In the second step, each concentration of fructose, sucrose, and peptone was optimized using a central composite design (CCD) and response surface analysis. The predicted concentrations of fructose, sucrose, and peptone were 38.68 g/l, 30 g/l, and 39.67 g/l, respectively. The mathematical response model was reliable, with a coefficient of determination of $R^2=0.9185$. Mannitol production increased 20-fold as compared with the MRS medium, corresponding to a mannitol yield 97.46% when compared to MRS supplemented with 100 g/l of fructose in flask system. Furthermore, the production in the optimized medium was cost-effective. The findings of this study can be expected to be useful in biological production for catalytic hydrogenation causing byproduct and additional production costs.

• Journal of Korean Society of Forest Science
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• v.110 no.2
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• pp.165-178
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• 2021

Owing to the lack of consistent research on endangered plant species in Korea, there are insufficient data to preservespecies and expand habitats. This study analyzed the preferred habitat and threats to the survival of Aconitum austrokoreense, found on Baekwun Mountain in Gurye-gun, Gwangyang-si, Jeollanam-do Province, and classified as a level two endangered wild plant by the Ministry of Environment, by investigating major environmental factors such as climate, location, soil, and stand structure. By examining five selected sites inhabited by Aconitum austrokoreense on BaekwunMountain, this study found that the habitat had an altitude of 420 to 675 m above sea level and showed a northeast tendency, spreading over a range of inclination angles between 15° and 37°. The average number of plants across the five sites was 156. Site 4 (550 m) had the highest density of 372 plants, with an average height of 0.6 m. The average soil moisture and relative light intensity were 20.48% and 7.34%, respectively. Layer soil was presumed to be sandy loam, characterized by high sand content and good drainage. The habitat had average soil pH of 5.2, average organic matter of 16.46%, average nitrogen of 0.86%, average available phosphate of 11.86 mg/kg, average electrical conductivity of 0.44 dS/m, and average cation exchange capacity of 37.04 cmolc/kg. The total carbon in soil averaged 10.68%. From the analysis of the vegetation structure of sites inhabited by Aconitum austrokoreense, the dominant populations were Pinus koraiensis and Lindera erythrocarpa in Site 1, Magnolia obovata and Carpinus laxiflora in Site 2, Zelkova serrate and Quercus variabilis in Site 3, Staphylea bumalda and Lindera erythrocarpa in Site 4, and Morus bombycis,Styrax japonicus, and Carpinus laxiflora in Site 5. With most habitats located near trails and sap collection sites of Acer pictum, the species were exposed to artificial damage and interference threats.

• Journal of Korean Society of Forest Science
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• v.111 no.4
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• pp.567-582
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• 2022

Chainsaw use for motor-manual timber harvesting in South Korea is associated with worker safety issues. However, forestry operations such as timber harvesting have already been mechanized to reduce hazards to workers and increase productivity. This study analyzed the productivities and costs of felling and processing, felling and processing using an excavator-based stroke harvester for Pinus rigida and Quercus mongolica stands. To efficiently operate the stroke harvester, we developed a regression equation to estimate the productivities of felling and processing, felling, and processing operations,and we conducted sensitivity analysis of the operation costs using DBH and machine utilization. The felling and processing productivity was 6.53 and 4.02 m³/SMH for P. rigida a nd Q. mongolica, respectively, and the cost was 17,983 and 29,210 won/m³, respectively. The felling productivity for P. rigida a nd Q. mongolica wa s 40.9 and 23.0 m³/SMH, respectively, and the cost was 2,667 and 4,743 won/m³, respectively. The processing productivity for P. rigida and Q. mongolica was 8.25 and 7.75 m³/SMH, respectively, and the cost was 15,296 and 16,283 won/m³, respectively. In the developed regression equation, the DBH, traveling distance, and number of cuttings were found to be important factors (p<0.05). Therefore, it is necessary to construct a DB considering the various conditions and species associated with harvester operations, and further research is needed to increase the accuracy of predicting operation productivity and costs.

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.6
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• pp.469-484
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• 2021

Rock mass classification results have a great influence on construction schedule and budget as well as tunnel stability in tunnel design. A total of 3,526 tunnels have been constructed in Korea and the associated techniques in tunnel design and construction have been continuously developed, however, not many studies have been performed on how to assess rock mass quality and grade more accurately. Thus, numerous cases show big differences in the results according to inspectors' experience and judgement. Hence, this study aims to suggest a more reliable rock mass classification (RMR) model using machine learning algorithms, which is surging in availability, through the analyses based on various rock and rock mass information collected from boring investigations. For this, 11 learning parameters (depth, rock type, RQD, electrical resistivity, UCS, V_p, V_s, Young's modulus, unit weight, Poisson's ratio, RMR) from 13 local tunnel cases were selected, 337 learning data sets as well as 60 test data sets were prepared, and 6 machine learning algorithms (DT, SVM, ANN, PCA & ANN, RF, XGBoost) were tested for various hyperparameters for each algorithm. The results show that the mean absolute errors in RMR value from five algorithms except Decision Tree were less than 8 and a Support Vector Machine model is the best model. The applicability of the model, established through this study, was confirmed and this prediction model can be applied for more reliable rock mass classification when additional various data is continuously cumulated.

• Journal of Environmental Impact Assessment
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• v.32 no.2
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• pp.134-145
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• 2023

Currently, the floodplains of major rivers are transforming into various types of waterfront spaces according to the increase in leisure activities and improved accessibility. In general, waterfront activities in river channels tend to be concentrated in summer, and the waterfront activities during this period directly affect water quality. Accordingly, it is necessary to accurately compare and evaluate the characteristics and water quality of waterfront activities during the period when waterfront activities are concentrated. In this study, the following research was conducted to compare and analyze the current status of waterfront activities of users of waterfront areas and the water quality of waterfront areas. First, three waterfront areas were selected for investigation using the information from the Ministry of Environment's water quality measurement network. Second, a survey was conducted on the satisfaction and types of waterfront activities targeting users of waterfront areas. Third, water quality grades were calculated based on monthly water quality measurement factors and compared. Fourth, statistical analysis (one-way analysis of variance) was conducted to see if there was a significant difference in water quality characteristics between periods of high waterfront activity and periods of low waterfront activity using water quality measurement data for the last 5 years. As a result of this analysis, the following conclusions were drawn in this study. First, the use of waterfront activities was investigated in the order of camping, water skiing, fishing, swimming, and rafting. Second, satisfaction factors for waterfront activities were investigated in the order of activity convenience, water quality, waterlandscape, transportation access convenience, and temperature. Third, it was found that satisfaction with water quality in waterfront areas was generally unsatisfactory regardless of the water quality grade presented by the competent authority. Fourth, as a result of comparing the water quality measurement network data of the Ministry of Environment by water quality grade, generally good grades were found, and in particular, there was a difference in grade frequency by season in the BOD category. Fifth, as a result of statistical analysis (one-way ANOVA) of water quality monitoring network data by season, there were statistically significant differences in COD, BOD, TP, and TOC except for DO. Considering the results of these studies, it is judged that it is necessary to prepare a comprehensive management system for water quality improvement in the waterfront zone and to improve water quality during periods of high waterfront activity, and to prepare a water quality forecasting system for waterfront areas in the future.

• Korean Chemical Engineering Research
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• v.61 no.3
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• pp.378-387
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• 2023

Petrochemical is an energy consuming industry that consumes about 30% of total industrial energy consumption and is a representative carbon dioxide (CO₂) emission source. Among them, the Naphtha Cracking Center (NCC), which produces ethylene, propylene, propane and mixed C4, consumes large amounts of energy and emits significant amounts of CO₂. For this reason, an integrated techno economic- environmental impact assessment aimed at reducing energy consumption and environmental impact factors is necessary to ensure efficiency in terms of economics and environment. This study aims to analyze the efficiency of the heat exchanger network used in the existing NCC base on the pinch analysis and select an improvement plan that can reduced energy consumption. In order to reduces the utility consumption in the process, an optimal heat exchanger network considering the high-temperature and low-temperature stream was derived, and the economic evaluation was conducted by considering the trade-off between the reduction in utility consumption and the increase in heat exchanger installation cost. In addition, an environmental impact assessment was conducted on the reduced CO₂ emission in consideration of the environmental aspect, and the economic environmental impact assessment used the payback period to recover the invested funds to come up with an energy saving plan that can be applied based on the actual process. As a result of considering the economic-environmental impact assessment, when the environmental impact assessment was not considered, it was 4.29 months, 3.21 months, and 3.39 months for each case, and when considering the environmental impact assessment, it was 4.24 months, 3.17 months, and 3.35 months for each case. These results appeared equally both when the environmental impact assessment was not include and when it was include. In addition, a sensitivity analysis was conducted for each case to determine how important factors affect the payback period. As a result of the sensitivity analysis, the cost of the heat exchanger was identified as a major factor influencing the overall cost.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.216-217
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• 2022

Gulpur 수력발전 프로젝트는 전력난을 겪고 있는 파키스탄에 102 MW 규모의 수력발전소를 건설하여 30년 동안 운영 관리한 후 파키스탄 정부로 양도하는 IPP(Independent Power Producing) 형식의 투자사업이다. 남동발전과 DL E&C, 롯데건설이 Sponsor로서 출자한 자본금과, ADB, IFC, K-EXIM 등의 대주단로부터의 차입금을 재원으로 하여 소요 사업비를 조달하고 사업을 개발하였다. DL E&C와 롯데건설이 EPC(Engineering, Procurement, Construction)를 수행하였고, 이산이 Design consultant의 역할을 수행하였다. Gulpur 수력발전 프로젝트의 발전형식은 수로식(run-of-river)으로 201 m³/s의 발전유량과 102 MW의 발전 시설용량을 이용하여 연평균예상발전량은 398 GWh이다. 주요 구조물로는 설계 재현빈도 1년의 유수전환시설(가물막이댐 & 가배수터널)과 콘크리트 중력식댐(H 67 m, L 205 m), 도수터널(D 6.7 m, L 215 m, 2기), 옥외형 발전소 (H 51 m, W 60 m, L 38 m, Kaplan 2기)가 있으며, 2015년 10월 착공하여 2020년 3월 상업발전을 시작하였다. 본 프로젝트는 DL E&C의 첫 번째 EPC 해외수력발전 프로젝트이다. 따라서 프로젝트의 성공적 수행을 위한 경제적 설계, 시공의 효율성 및 안정성 확보 등을 위하여 많은 연구를 수행하는 과정에서 다양한 기술 개선을 이룰 수 있었다. 본고에서는 Gulpur 프로젝트를 통하여 도출된 성공 사례들을 소개 및 공유하고자 한다. 첫 번째로 콘크리트 중력식댐 시공을 위한 유수전환시설의 최적 설계빈도를 산정하였다. 일반적으로 유수전환시설의 규모는 설계기준에 제시된 설계 재현빈도를 이용하는데, 해외 설계기준에서는 10년, 국내 설계기준에서는 1~2년으로 다르게 제시되어 있는 문제점이 있다. 유수전환시설의 규모는 프로젝트의 경제성에 큰 영향을 미치기 때문에 최적 설계빈도의 결정이 필요하며, 위험도분석기법(Risk Analysis)과 기대화폐가치법(Expected Monetary Value)을 이용하여 유수전환시설의 최적 설계 재현빈도와 이에 영향을 미치는 인자를 분석하였다. 위험도는 몬테카를로 시뮬레이션으로 산정된 가물막이댐 파괴확률과 재현빈도를 이용하여 산정된 가물막이댐 월류확률을 고려하였으며, 비용 및 피해액으로는 유수전환시설의 공사비, 가물막이댐 파괴시의 재건설비용과 지체보상금, 가물막이댐 월류시의 복구비용을 고려하였다. 이에 대한 연구결과로, 유수전환시설의 사용기간과 월류시의 복구비용이 유수전환시설의 설계 재현기간 결정에 가장 큰 영향을 미치는 것으로 나타났고, 특히 월류시의 복구비용이 작을수록 낮은 설계 재현빈도를 선택하는 것이 타당한 것으로 나타났다. 예를 들어, 유수전환시설의 사용기간이 3 ~ 5년, 복구비용이 0.5 ~ 1.0 mil USD 이하인 조건에서 가물막이시설의 최적 설계빈도는 1년 ~ 2년인 것으로 나타났다. 또한, 유수전환시설의 사용기간은 본댐의 규모와 시공기간 등을 고려하여 결정되는 사항으로 설계자가 임의 조정할 수 없지만, 복구비용은 시공 관리자에 따라 결정되는 부분으로, 적극적 홍수 피해 저감 및 복구방안을 마련하는 것이 프로젝트의 경제성을 향상시킬 수 있다는 것을 알 수 있었다. 두 번째로 프로젝트의 경제성 향상, 홍수기 댐 시공시의 안전성 확보를 위하여 홍수 조기경보시스템(Early Warning System)을 개발 및 활용하였다. 수로식(Run-of-river) 수력발전댐은 대부분 산악지역에 위치하기 때문에 국지성 강우 및 급한 지형 경사로 인하여 돌발홍수(flash flood)의 발생 가능성이 높다. 따라서 시공 중 홍수(월류) 발생을 미리 감지하고 현장에 전파할 수 있는, 수로식(Run-of-river) 수력발전댐 현장을 위한 홍수 조기경보시스템이 필요하며, 이를 리스크 인식, 모니터링 및 경보, 전파 및 연락, 반응 능력 향상의 4가지 부분으로 나누어 구축하였다. 리스크 인식 부분에서는 가물막이댐 월류 발생 상황에 대한 위험도, 취약성, 리스크를 제시하였으며, 모니터링 및 경보 부분에서는 상류 측정수위에서 유도된 현장 예상수위와 실제 현장 측정 수위를 대상으로 경보홍수위와 위험홍수위로 나누어 관리하였다. 전파 및 연락 부분에서는 현장 시공 조직을 활용하여 홍수시를 대비한 비상연락체계도(Emergency communication flow chart)를 운영하였으며, 반응 능력 향상을 위해 비상연락체계도의 팀별 Action plan을 상세화 하였다. 세 번째로 현장의 지질특성과 50여 차례 발파시험으로 현장 고유의 발파진동감쇄곡선을 도출하였으며, 이를 통해 현장의 시공성과 콘크리트 품질 확보를 동시에 달성할 수 있는 방안을 제시하였다. 콘크리트댐 공사에서는 제한된 공기 내에 공사를 완료하기 위해 사면부 굴착과 콘크리트 타설이 동시에 수행될 수밖에 없는 문제점을 가지고 있다. 그러나 신규 콘크리트 타설면 근처에서 발파를 수행하는 경우 발파로 발생되는 탄성파가 일정 수준을 초과하게 되면, 콘크리트 양생에 영향을 주게 된다. 따라서 다수의 현장 발파시험을 통해 발파거리와 최대진동속도의 상관관계 즉, 발파진동감쇄곡선을 도출함으로써 현장의 발파진동특성을 도출할 수 있었다. 또한, 기존 연구 논문들을 통해 콘크리트 재령기간 별 안전진동속도를 선정하고, 해당 안전진동속도를 초과하지 않는 범위에서 콘크리트 타설면과 발파위치의 거리에 따라 1회 발파 가능한 장약량을 산정하여 적용하였다. 이와 같은 체계적인 접근을 통해 콘크리트 타설과 발파 작업 동시 수행에 대한 논란을 해소할 수 있었다.

• Journal of Bio-Environment Control
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• v.5 no.2
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• pp.215-235
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• 1996

The thermal analysis by mathematical model simulation makes it possible to reasonably predict heating and/or cooling requirements of certain greenhouses located under various geographical and climatic environment. It is another advantages of model simulation technique to be able to make it possible to select appropriate heating system, to set up energy utilization strategy, to schedule seasonal crop pattern, as well as to determine new greenhouse ranges. In this study, the control pattern for greenhouse microclimate is categorized as cooling and heating. Dynamic model was adopted to simulate heating requirements and/or energy conservation effectiveness such as energy saving by night-time thermal curtain, estimation of Heating Degree-Hours(HDH), long time prediction of greenhouse thermal behavior, etc. On the other hand, the cooling effects of ventilation, shading, and pad ||||&|||| fan system were partly analyzed by static model. By the experimental work with small size model greenhouse of 1.2m$\times$2.4m, it was found that cooling the greenhouse by spraying cold water directly on greenhouse cover surface or by recirculating cold water through heat exchangers would be effective in greenhouse summer cooling. The mathematical model developed for greenhouse model simulation is highly applicable because it can reflects various climatic factors like temperature, humidity, beam and diffuse solar radiation, wind velocity, etc. This model was closely verified by various weather data obtained through long period greenhouse experiment. Most of the materials relating with greenhouse heating or cooling components were obtained from model greenhouse simulated mathematically by using typical year(1987) data of Jinju Gyeongnam. But some of the materials relating with greenhouse cooling was obtained by performing model experiments which include analyzing cooling effect of water sprayed directly on greenhouse roof surface. The results are summarized as follows : 1. The heating requirements of model greenhouse were highly related with the minimum temperature set for given greenhouse. The setting temperature at night-time is much more influential on heating energy requirement than that at day-time. Therefore It is highly recommended that night- time setting temperature should be carefully determined and controlled. 2. The HDH data obtained by conventional method were estimated on the basis of considerably long term average weather temperature together with the standard base temperature(usually 18.3$^{\circ}C$). This kind of data can merely be used as a relative comparison criteria about heating load, but is not applicable in the calculation of greenhouse heating requirements because of the limited consideration of climatic factors and inappropriate base temperature. By comparing the HDM data with the results of simulation, it is found that the heating system design by HDH data will probably overshoot the actual heating requirement. 3. The energy saving effect of night-time thermal curtain as well as estimated heating requirement is found to be sensitively related with weather condition: Thermal curtain adopted for simulation showed high effectiveness in energy saving which amounts to more than 50% of annual heating requirement. 4. The ventilation performances doting warm seasons are mainly influenced by air exchange rate even though there are some variations depending on greenhouse structural difference, weather and cropping conditions. For air exchanges above 1 volume per minute, the reduction rate of temperature rise on both types of considered greenhouse becomes modest with the additional increase of ventilation capacity. Therefore the desirable ventilation capacity is assumed to be 1 air change per minute, which is the recommended ventilation rate in common greenhouse. 5. In glass covered greenhouse with full production, under clear weather of 50% RH, and continuous 1 air change per minute, the temperature drop in 50% shaded greenhouse and pad ＆ fan systemed greenhouse is 2.6$^{\circ}C$ and.6.1$^{\circ}C$ respectively. The temperature in control greenhouse under continuous air change at this time was 36.6$^{\circ}C$ which was 5.3$^{\circ}C$ above ambient temperature. As a result the greenhouse temperature can be maintained 3$^{\circ}C$ below ambient temperature. But when RH is 80%, it was impossible to drop greenhouse temperature below ambient temperature because possible temperature reduction by pad ||||&|||| fan system at this time is not more than 2.4$^{\circ}C$. 6. During 3 months of hot summer season if the greenhouse is assumed to be cooled only when greenhouse temperature rise above 27$^{\circ}C$, the relationship between RH of ambient air and greenhouse temperature drop($\Delta$T) was formulated as follows : $\Delta$T= -0.077RH＋7.7 7. Time dependent cooling effects performed by operation of each or combination of ventilation, 50% shading, pad ＆ fan of 80% efficiency, were continuously predicted for one typical summer day long. When the greenhouse was cooled only by 1 air change per minute, greenhouse air temperature was 5$^{\circ}C$ above outdoor temperature. Either method alone can not drop greenhouse air temperature below outdoor temperature even under the fully cropped situations. But when both systems were operated together, greenhouse air temperature can be controlled to about 2.0-2.3$^{\circ}C$ below ambient temperature. 8. When the cool water of 6.5-8.5$^{\circ}C$ was sprayed on greenhouse roof surface with the water flow rate of 1.3 liter/min per unit greenhouse floor area, greenhouse air temperature could be dropped down to 16.5-18.$0^{\circ}C$, whlch is about 1$0^{\circ}C$ below the ambient temperature of 26.5-28.$0^{\circ}C$ at that time. The most important thing in cooling greenhouse air effectively with water spray may be obtaining plenty of cool water source like ground water itself or cold water produced by heat-pump. Future work is focused on not only analyzing the feasibility of heat pump operation but also finding the relationships between greenhouse air temperature(T$_{g}$ ), spraying water temperature(T$_{w}$ ), water flow rate(Q), and ambient temperature(T$_{o}$).

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.3
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• pp.70-82
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• 2023

The recent surge of IT and data acquisition is shifting the paradigm in all aspects of life, and these advances are also affecting academic fields. Research topics and methods are being improved through academic exchange and connections. In particular, data-based research methods are employed in various academic fields, including landscape architecture, where continuous research is needed. Therefore, this study aims to investigate the possibility of developing a landscape preference evaluation and prediction model using machine learning, a branch of Artificial Intelligence, reflecting the current situation. To achieve the goal of this study, machine learning techniques were applied to the landscaping field to build a landscape preference evaluation and prediction model to verify the simulation accuracy of the model. For this, wind power facility landscape images, recently attracting attention as a renewable energy source, were selected as the research objects. For analysis, images of the wind power facility landscapes were collected using web crawling techniques, and an analysis dataset was built. Orange version 3.33, a program from the University of Ljubljana was used for machine learning analysis to derive a prediction model with excellent performance. IA model that integrates the evaluation criteria of machine learning and a separate model structure for the evaluation criteria were used to generate a model using kNN, SVM, Random Forest, Logistic Regression, and Neural Network algorithms suitable for machine learning classification models. The performance evaluation of the generated models was conducted to derive the most suitable prediction model. The prediction model derived in this study separately evaluates three evaluation criteria, including classification by type of landscape, classification by distance between landscape and target, and classification by preference, and then synthesizes and predicts results. As a result of the study, a prediction model with a high accuracy of 0.986 for the evaluation criterion according to the type of landscape, 0.973 for the evaluation criterion according to the distance, and 0.952 for the evaluation criterion according to the preference was developed, and it can be seen that the verification process through the evaluation of data prediction results exceeds the required performance value of the model. As an experimental attempt to investigate the possibility of developing a prediction model using machine learning in landscape-related research, this study was able to confirm the possibility of creating a high-performance prediction model by building a data set through the collection and refinement of image data and subsequently utilizing it in landscape-related research fields. Based on the results, implications, and limitations of this study, it is believed that it is possible to develop various types of landscape prediction models, including wind power facility natural, and cultural landscapes. Machine learning techniques can be more useful and valuable in the field of landscape architecture by exploring and applying research methods appropriate to the topic, reducing the time of data classification through the study of a model that classifies images according to landscape types or analyzing the importance of landscape planning factors through the analysis of landscape prediction factors using machine learning.

• Journal of Yeungnam Medical Science
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• v.14 no.2
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• pp.399-414
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• 1997

There are several factors concerning to anemia in chronic renal failure patients. But when rHuEPO is used, most of these factors can be overcome, and the levels of hemoglobin are increased. However, about 10% of the renal failure patients represent rHuEPO-resistant anemia eventhough high dosage of rHuEPO. For these cases, desferrioxamine can be applied to correct rHuEPO resistnacy, and many mechanism of DFO are arguing. So we are going to know whether DFO can be applied to correct anemia of the such patients, how long its effect can be continued. The seven pateients as experimental group(DFO+EPO) who represent refractoriness to rHuEPO and the other seven patients as control group(EPO) were included. Experimental group had lower than 9 g/dL of hemoglobin levels despite high rHuEPO dosage (more than 4000U/Wk) and showed normocytic normochromic anemia. There were no definitve causes of anemia such as hemorrhage or iron deficiency. Control group patients had similar characteristics in age, mean dialysis duration but showed adequate response to rHuEPO. DFO was administered to experimental group for 8 weeks along with rHuEPO(the rHuEPO individual mean dosage had been determined by mean dosage of the previous 6 months. Total mean dosage; 123.5 U/Kg/Wk). After 8 weeks of DFO administration, the hemoglobin and rHuEPO dosage levels were checked for 15 consecutive months. It should be noted that the patients determined their own rHuEPO dosage levels according to hemoglobin levels and economic status. In conrol group, rHuEPO was administered by the same method used in experimental group without DFO through the same period. Fifteen months of observation period after DFO trial were divided as Time I(7 months after DFO trial) and Time II(8 months after Time I). The results are as follows: Before DFO trial, mean hemoglobin level of experimental group was 7.8 g/dL, which is similar level(p>0.05) to control group(mean Hb; 8.2 g/dL). But in experimental group, significantly(p<0.05) higher dosages of rHuEPO(mean; 123.5 U/Kg/Wk) than control group (mean; 41.6 U/Kg/Wk) had been used. It means resistancy to rHuEPO of experimental group. But after DFO trial, the hemoglobin levels of the experimental group were increased significantly(p<0.05), and these effect were continued to Time II.(Time I; mean 8.6g/dL, Time II; mean 8.6g/dL) The effects of DFO to hemoglobin were continued for 15 months after DFO trial with similar degree through Time I, Time II. Also, rHuEPO dosages used in the experimental group were decreased to similar levels of the control group after DFO trial and these effect were also continued for 15 months(Time I; mean 48.1 U/Kg/Wk. Time II; mean 51.8 U/Kg/Wk). In the same period, hemoglobin levels and rHuEPO dosages used in the control group were not changed significantly. Notibly, hemoglobin increment and rHuEPO usage decrement in experimental group were showed maxilly in the 1st month after DFO trial. That is, after the use of DFO, erythopoiesis was enhanced with a reduced rHuEPO dosage. So we think rHuEPO reisistancy can be overcome by DFO therapy. In conclusion, the DFO can improve the anemia caused by chronic renal failure at least over 1 year, and hence, can reduce the dosage of rHuEPO for anemia correction. Additional studies in order to determine the mechanism of DFO on erythropoiesis and careful attention to potential side effects of DFO will be needed.