• Applied Chemistry for Engineering
• /
• v.21 no.4
• /
• pp.357-365
• /
• 2010

Combinatorial synthesis, which has been adopted as an efficient method for deriving a leading compound in pharmaceutical chemistry, is recently being applied in various fields along with the rapid development of analysis and examination technology. It is especially attracting much attention as an efficient strategy to secure various potent compounds rapidly in the areas of developing new materials where the relationship between the chemical structure and the property is not revealed. Several reports and reviews have already been published for the combinatorial chemistry and combinatorial synthesis. This report briefly introduces trends in the combinatorial development of new materials and discusses the cases of developing organic luminescent materials.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2016.05a
• /
• pp.180-180
• /
• 2016

최근 기후변화로 인한 국지성 집중호우의 영향으로 재해의 다양화, 대형화 하고 있다. 그 중, 산지하천에서 발생하는 재해로는 토석류 재해가 있다. 일반적으로 토석류 재해는 발생시기, 발생 위치, 발생규모 등을 예측하기 어렵다는 특징을 가지고 있기 때문에 토석류 재해의 피해를 저감시키기 위해서 국내에서는 사방사업을 주로 실시하고 있다. 사방사업에 이용되는 사방댐은 투과형 사방댐과 불투과형 사방댐으로 크게 분류된다. 불투과형 사방댐은 전체적인 토석류의 양을 줄여주는 역할을 하며, 투과형 사방댐은 바위, 토사 등을 물과 분리하여 토석류의 위력을 감소시키는 역할을 한다. 이러한 투과형 사방댐과 불투과형 사방댐의 장점을 이용하여 적절히 조합한다면 토석류 유출저감 효과를 극대화 시킬 수 있을 것으로 보인다. 본 연구에서는 조합형 사방댐의 저감효과를 검증하기 위해 다기능을 사방댐을 설계하였다. 설계한 사방댐은 중력식 콘크리트 사방댐, 버트리스, 브레이커의 3가지 파트로 구성 하였다. 실험에 활용하기 위한 모형을 각각 분리하여 제작하고, 각각의 조합에 따라 가장 높은 저감효과를 내는 조합을 찾기 위해 토석류 모형실험을 실시하였다.

• KIPS Transactions on Software and Data Engineering
• /
• v.12 no.3
• /
• pp.133-140
• /
• 2023

The performance of lithium ion batteries depends on the usage environment and the combination ratio of cathode materials. In order to develop a high-performance lithium-ion battery, it is necessary to manufacture the battery and measure its performance while varying the cathode material ratio. However, it takes a lot of time and money to directly develop batteries and measure their performance for all combinations of variables. Therefore, research to predict the performance of a battery using an artificial intelligence model has been actively conducted. However, since measurement experiments were conducted with the same battery in the existing published battery data, the cathode material combination ratio was fixed and was not included as a data attribute. In this paper, we define a training data model required to develop an artificial intelligence model that can predict battery performance according to the combination ratio of cathode materials. We analyzed the factors that can affect the performance of lithium-ion batteries and defined the mass of each cathode material and battery usage environment (cycle, current, temperature, time) as input data and the battery power and capacity as target data. In the battery data in different experimental environments, each battery data maintained a unique pattern, and the battery classification model showed that each battery was classified with an error of about 2%.

• Journal of the Korea Society of Computer and Information
• /
• v.15 no.11
• /
• pp.215-224
• /
• 2010

Most chronic diseases are complex diseases which are caused by interactions of several genes. Studies on finding SNPs and gene-gene interactions involved in the development of complex diseases can contribute to prevention and treatment of the diseases. Previous studies mostly concentrate on finding only the set of SNPs involved. In this study we suggest a way to see how these SNPs interact using boolean expressions. The proposed method consists of two stages. In the first stage we find the set of SNPs involved in the development of diseases using mutual information based on entropy. In the second stage we find the highest accuracy boolean expression that consists of the SNP set obtained in the first stage. We experimented with clinical data to demonstrate the effectiveness of the proposed method. We also compared the differences between our method and the previous results on the SNP associations studies.

• Korean Journal of Construction Engineering and Management
• /
• v.23 no.6
• /
• pp.21-29
• /
• 2022

Productivity estimation of construction operations is crucial to successful project delivery. Especially in the preconstruction phase, the adequacy and effectiveness of plans directly affect the actual performance of operations. Currently, productivity estimation is conducted by referring to existing references such as the Construction Standard Production Rate. However, it is difficult to promptly apply changing conditions of operations when using such references. Moreover, it is difficult to deduce the optimal combination of construction machinery for the given condition. This paper presents a simple simulation model that can be used to generate productivity data that considers site conditions and construction equipment combination. The suggested method is expected to be used as a decision making assisting tool for practitioners who rely on estimations using the Construction Standard Production Rate when establishing construction plans using heavy machinery such as backhoes, loaders and dumptrucks.

• Journal of the Korean Geosynthetics Society
• /
• v.19 no.3
• /
• pp.9-21
• /
• 2020

In this study, the design method of the combined sheet pile was considered in the coastal landfill where sandy and clayey soils are mixed, and the behavior in excavation was analyzed. It was confirmed from the elasto-plastic analysis that the predicted behavior of the temporary facilities of earth retaining differs according to the type of the combined sheet pile method (Built up, Interlocking, Welding) and the analysis method (soldier pile method, continuous wall method). In the case of sheet pile member force, the results of the continuous wall analysis method predicted the most conservative results. When the stress ratio (calculation/allowance) of each member was analyzed based on the maximum member force of the combined sheet pile method, the maximum value was obtained for bending moment in the side pile and combined stress in the case of the strut. As a result of finite element analysis, the member force of the side pile was the largest in the short-term effective stress analysis condition, while the compressive force of the strut was large in the consolidation analysis. When comparing the results of the elasto-plastic analysis and the finite element analysis, the shear force of the side pile and the axial force of the strut were greatly evaluated in the elasto-plastic analysis, and the bending moment of the side pile was the largest in the short-term effective stress condition of the finite element analysis. In addition, the displacement of the side pile was predicted to be greater in the finite element analysis than in the elasto-plastic analysis.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.26 no.4A
• /
• pp.647-657
• /
• 2006

Probabilistic Risk Assessment considering statistically random variables is performed for the preliminary design of a Cable Stayed Bridge, which is Prestressed Concrete Bridge consisted of cable and plate girders, based on the method of Working Stress Design and Strength Design. Component reliabilities of cables and girders have been evaluated using the response surface of the design variables at the selected critical sections based on the maximum shear, positive and negative moment locations. Response Surface Method (RSM) is successfully applied for reliability analyses for this relatively small probability of failure of the complex structure, which is hard to obtain through Monte-Carlo Simulations. or through First Order Second Moment Method that can not easily calculate the derivative terms of implicit limit state functions. For the analysis of system reliability, parallel resistance system consisting of cables and plate girder is changed into series connection system and the result of system reliability of total structure is presented. As a system reliability, the upper and lower probabilities of failure for the structural system have been evaluated and compared with the suggested prediction method for the combination of failure modes. The suggested prediction method for the combination of failure modes reveals the unexpected combinations of element failures in significantly reduced time and efforts compared with the previous permutation method or system reliability analysis method, which calculates upper and lower bound failure probabilities.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.32 no.5B
• /
• pp.267-272
• /
• 2012

To reduce the flood risk caused by unexpected heavy rainfall, many prediction methods for flood have been developed. A major constituent of flood prediction is an accurate rainfall estimation which is an input of hydrologic models. In this study, a regional-scale weather model which can provide relatively longer lead time for flood mitigation compared to the Nowcasting based on radar system will be introduced and applied to the Chongmi river basin located in central part of South Korea. The duration of application of a regional weather model is from July 11 to July 23 in 2006. The estimated rainfall amounts were compared with observations from rain gauges (Sangkeuk, Samjook, and Sulsung). For this rainfall event at Chongmi river basin, Thomson and Kain-Frisch Schemes for microphysics and cumulus parameterization, respectively, were selected as optimal physical conditions to present rainfall fall amount in terms of Mean Absolute Relative Errors (MARE>0.45).

• The Journal of the Acoustical Society of Korea
• /
• v.3 no.2
• /
• pp.46-58
• /
• 1984

본 논문은 한국어 음성 인식을 위한 유성음, 무성음, 묵음 식별에 관한 연구이다. 주어진 음성 구간을 3가지 음성 신호 부류로 식별하기 위하여 패턴 인식 방법을 사용하였다. 여기에 사용한 분석 파 라메타는 음성 신호의 영교차율, 대수 에너지, 정규화 된 첫 번째 자동 상관 계수, 선형 예측 분석에서 얻은 첫 번째 예측 계수, 그리고 예측 오차의 에너지이다. 한편 측정된 파라메타들이 다차원 가우스 확 률 밀도 함수에 따라 분산되었다는 가정하에서 어어진 최소 거리 법칙에 기본을 두고 음성 구간을 결정 하였다. 측정된 파라메타들을 여러 가지 방법으로 조합하여 식별한 결과 영교차율, 첫 번째 예측계수, 예측 오차의 에너지를 측정 파라메타로 사용했을 때 1%보다 적은 식별 오차율을 얻었다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2022.11a
• /
• pp.371-373
• /
• 2022

e커머스 풀필먼트 비즈니스에서 수요예측은 매우 중요하다. 이는 고객의 온라인 주문정보를 바탕으로 풀필먼트 창고 내에서의 적정 피킹, 패킹 인력과 배송을 위한 차량의 적정규모도 산정하여 관련 비용 및 자원들 관리에 활용되기 때문이다. 특히 예측결과에 따라 인력 운영비용 및 배송에도 영향을 미치기 때문에 그 중요성이 날이 갈수록 커지고 있는 상황이다. 이런 이유로 e커머스 풀필먼트 비즈니스에 활용하기 위한 특화된 수요예측 방법이 필요하다. 본 연구에서 제안하는 멀티 조합 수요예측 기술은 풀필먼트 비즈니스에 가장 중요한 요소인 피킹과 패킹을 위한 적정 작업 인력 확보를 하고 이를 통해 안정적인 상품 출고가 가능해진다.