• Applied Biological Chemistry
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• v.40 no.4
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• pp.334-341
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• 1997

In the laboratory experiment, concentration and rate of runoff of 7 pesticides were measured under the simulated rainfall. Total runoff rate of metolachlor, alachlor, chlorothalonil, chlorpyrifos, EPN, phorate and captafol were 57.0, 14.2, 13.2, 7.9, 7.2, 7.1 and 2.8%, respectively, and the average runoff concentrations were 940, 399, 55, 7.0, 9.3, 151 and 7.0 ppb, respectively. Significant relationship was observed between the runoff rate and water solubility in the laboratory experiment(r=0.923). Even though not very high, relatively significant results were obtained in other experimental conditions. Based on the results, runoff rate prediction$[Y=0.2812{\times}10exp(0.261logWS-0.366)+0.3594{\times}10exp(-0.545logKoc+1.747)+0.3594{\times}10exp(-0.362log\;Kow+1.105]$ and conversion equations were calculated to investigate the possibility of estimating runoff rate in the field by natural rain. Calculated runoff rate by conversion equation was similar to experimental result with captafol in the field while 6 times higher result was obtained by the prediction equation. Therefore, those prediction and conversion equations derived from the laboratory experiment data and physicochemical properties of the pesticides could be used for the prediction of field runoff rate of pesticides by natural rainfall.

• Journal of Biomedical Engineering Research
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• v.24 no.4
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• pp.293-299
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• 2003

In this paper, the correlation of Pressure drop about the Newtonian and non-Newtonian fluid was investigated experimentally for vibrating intravascular lung assist device (VIVLAD) and we determined correlation equation to make a prediction about Pressure drop for designing VIVLAD. Design conditions to predict the pressure drop of the modules were studied through an experimental modeling before inserting the artificial lung assist device into as venous. Experiments were performed by distilled water, glycerol/water mixed solution(40% glycerol) of Newtonian fluids. and the bovine blood of non-Newtonian fluids. These fluids were flowed outside and parallel of hollow fiber membranes. Also we measured pressure drop according to the number of the fiber membranes which ware inserted into the inside diameter of shell of 3 cm, and developed the prediction equations by curve fitting method based on correlation between the experimental pressure drop and the frontal area or the packing density of device. The result showed that the Pressure drop and the friction factor of the water/glycerol mixed solution were similar to that of bovine blood. It was showed that the water/glycerol mixed solution (40% glycerol) could be used for measuring the pressure drop and the friction factor instead of the bovine blood. Also, we could estimate the prediction equation of pressure drop and friction factor as the function of Packing density at the number of hollow fibers. We obtained the reliance of the prediction equations because the pressure drop and the friction factor measured from the experiments were similar to that from the prediction equation. These results may be used to further usefulness for the design of VIVLAD.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.28 no.1
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• pp.1-6
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• 2016

The effect of reducing wave overtopping by use of the wave return wall was quantitatively analyzed based on physical experiments. The overtopping discharge for the arc seawall and the inclined seawall was measured and compared with the predictive formula that estimates reduction of overtopping by the wave return wall. When the overtopping discharge was relatively large ($q/{\sqrt{gH^3_s}}>10^{-3}$), the agreement in terms of overtopping reduction rate was fairly good between the prediction and the measurement. For the condition of smaller overtopping than the above criterion, however, the discrepancy was large between the predicted and measured result. In this context, it is required to develop a better formula for estimating reduction of wave overtopping by the wave return wall.

• Magazine of the Korea Concrete Institute
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• v.7 no.5
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• pp.164-171
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• 1995

Drying shrinkage and hydration heat are important factors on the initiation of the crack in con crete at early age. Therefore, the stress caused by hydration heat and drying shrinkage should be .analyzed to predict whether the crack occurrs or not. And, mechanical properties of early age concrete is also required for the predicting crack formation In this study, non-destructive test method of resonance frequency was used to find the relation between dynamic modulus and mechanical properties of concrete in early age. Test results were compared with existing equations, and a new equation based on test. results in this study and other data was also proposed

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.57-61
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• 2016

교각 주위에서의 국부세굴은 교각을 지나는 유체의 복잡한 흐름에 의해 발생한다. 이를 해석하기 위하여 많은 난류모형을 이용한 실내실험 및 수치실험을 수행하였으나 발생하는 와류를 하천 규모에서 전부 계산하기는 매우 어려운 문제다. 따라서 국부세굴 관련으로 최대 관심사인 최대 세굴심은 인공지능 기술에 근거한 다양한 기법을 적용해 계산하여 예측하기도 한다. 본 연구에서는 기계학습 분야 중 하나인 서포트 벡터 머신 (Support Vector Machines)을 이용하여 교각주위 국부세굴을 예측하였다. SVM은 본래 초평면을 이용하여 데이터를 분류시키는 기법이나 Vapnik(1995)이 제안한 ${\varepsilon}$ 서포트 벡터 회귀 (${\varepsilon}$-support vector regression)방법을 통해 회귀분석에도 활용할 수 있게 되었다. 학습을 위해 Charbert and Engeldinger (1956), Shen et al. (1969), Jain and Fischer (1979), 그리고 Dey et al. (1995)의 실험 자료를 이용하였고 검증을 위해 Yanmaz and Altinbilek (1991)의 실험 자료를 이용하였다. 커널함수로는 다항식 함수와 방사 기저 함수를 이용하였고 각 계수는 적합한 값을 찾기 위해 시행착오법을 사용하였다. 민감도 분석을 통해 각 계수들 중 ${\varepsilon}$의 변화가 결과에 가장 민감하게 변화를 일으키는 것을 확인하였고 검증 결과 SVM가 충분히 국부세굴을 잘 예측하는 것을 확인하였다.

• The Journal of the Korea Contents Association
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• v.19 no.7
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• pp.436-443
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• 2019

The purpose of this paper is to establish a predictive model by analyzing the influence and correlation of factors affecting the fuel consumption of unmanned helicopters in Captive Flight Test. In this study, a four-factor two-level full factorial experiment was designed and tested using the design of experiments, results were analyzed to derive the main effects and interactions of the factors, and the predictive model was established through regression analysis. It is expected that the results from this study contribute to carrying out Captive Flight Test efficiently and the improvement of the test capability of Electronic Testing Range.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.8
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• pp.741-751
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• 2000

To achieve high performance by exploiting instruction level parallelism aggressively in superscalar processors, it is necessary to overcome the limitation imposed by control dependences and data dependences which prevent instructions from executing parallel. Value prediction is a technique that breaks data dependences by predicting the outcome of an instruction and executes speculatively its data dependent instruction based on the predicted outcome. In this paper, a hybrid value prediction scheme with dynamic classification mechanism is proposed. We design a hybrid predictor by combining the last predictor, a stride predictor and a two-level predictor. The choice of a predictor for each instruction is determined by a dynamic classification mechanism. This makes each predictor utilized more efficiently than the hybrid predictor without dynamic classification mechanism. To show performance improvements of our scheme, we simulate the SPECint95 benchmark set by using execution-driven simulator. The results show that our scheme effect reduce of 45% hardware cost and 16% prediction accuracy improvements comparing with the conventional hybrid prediction scheme and two-level value prediction scheme.

• Journal of the Korea Society of Computer and Information
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• v.14 no.10
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• pp.1-10
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• 2009

Precise branch predictor has a profound impact on system performance in modern processor architectures. Recent works show that prediction latency as well as prediction accuracy has a critical impact on overall system performance as well. However, prediction latency tends to be overlooked. In this paper, we propose Branch Pre-Prediction policy to tolerate branch prediction latency. The proposed solution allows that branch predictor can proceed its prediction without any information from the fetch engine, separating the prediction engine from fetch stage. In addition, we propose newly modified BTE structure to support our solution. The simulation result shows that proposed solution can hide most prediction latency with still providing the same level of prediction accuracy. Furthermore, the proposed solution shows even better performance than the ideal case, that is the predictor which always takes a single cycle prediction latency. In our experiments, IPC improvement is up to 11.92% and 5.15% in average, compared to conventional predictor system.

• Korean Journal of Materials Research
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• v.5 no.5
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• pp.503-511
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• 1995

금속/실리콘계에 대한 이온선 혼합시의 비정질상 및 결정상 형성여부를 예측할 수 있는 모델(ADF Model)과초기 결정상 예측 모델(PDF Model)의 적용을 실험적으로 조사하기 위하여 Ni/Si계에 대한 이온선 혼합을 온도와 이온선량을 변수로 하여 행하였으며 상형ㅅㅇ과정을 해석하였다. 이온선 혼합은 80keV가속기를 이용하여 상온~20$0^{\circ}C$의 온도 범위에서 1.0 $\times$ $10^{15}$Ar^{+}$/$cm^{2}$~2.0 $\times$ $10^{-16}$Ar^{+}$/$cm^{2}$의 이온선량을 변화시키면서 실험하였고, 상분석은 TEM과 GXRD를 이용하였다. Ni/Si게에 대한 ADF값은 0.804로 양의 값을 가지므로 이온선 혼합시 비정실상이 형성되고, $Ni_{2}$Si상이 다른 화합물상보다 훨씬 큰 음의 PDF값을 갖으므로 초기 결정상이 $Ni_{2}$Si가 될 것을 예측하였다. 이러한 예측은 실험결과와 매우 잘 일치하였다. 이상의 연구결과로부터 ADF 및 PDF모델을 이용하여 박막에서 형성되는 상을 보다 정확히 예측할수 잇음을 알 수 있었다.

• Journal of the Korea Convergence Society
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• v.9 no.3
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• pp.15-21
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• 2018

The ocean drifter is a device for observing the ocean weather by floating off the sea surface. The data observed through the drifter is utilized in the ocean weather prediction and oil spill. Observed data may contain incorrect or missing data at the time of observation, and accuracy may be lowered when we use the data. In this paper, we propose a data correction model using recurrent neural networks. We corrected data collected from 7 drifters in 2015 and 8 drifters in 2016, and conducted experiments of drifter moving prediction to reflect the correction results. Experimental results showed that observed data are corrected by 13.9% and improved the performance of the prediction model by 1.4%.