Earticle

본 연구는 SSARR모형을 이용해 금강유역의 미호천 유역에 대하여 홍수모의예측을 수행하였다. 먼저 모형의 매개변수의 특성을 알고, 범위를 설정하기 위해 모형의 매개변수에 대한 민감도 분석을 실시하였다. 매개변수 보정을 위하여 유전자 알고리즘, 패턴탐색, SCE-UA등의 최적화 방법을 이용하였고, 목적함수로는 WSSR과 SSR를 적용하였으며, 최적화 방법과 목적함수에 따른 결과를 비교, 분석하였다. 본 연구 결과 최적화 방법으로는 패턴탐색이, 목적함수로는 WSSR을 사용하였을 때, 홍수 예측이 가장 정확하였다. 본 연구 결과를 활용하여 각 모형의 매개변수를 최적화한다면, 홍수 예측 및 홍수 예경보와 같은 의사결정에 유용하게 활용 될 수 있을 것이다.

This study used SSARR model to predict the flood hydrograph for the Miho stream in the Geum river basin. First, we performed the sensitivity analysis on the parameters of SSARR model to know the characteristics of the parameters and set the range. For the parameter calibration, optimization methods such as genetic algorithm, pattern search and SCE-UA were used. WSSR and SSR were applied as objective functions, and the results of optimization method and objective function were compared and analyzed. As a result of this study, flood prediction was most accurate when using pattern search as an optimization method and WSSR as an objective function. If the parameters are optimized based on the results of this study, it can be helpful for decision making such as flood prediction and flood warning.

Objective To investigate whether motor evoked potential (MEP) amplitude ratio measurements are sufficiently objective to assess functional activities of the extremities. We also delineated the distribution between the presence or absence of MEPs and the Medical Research Council (MRC) scale for muscle strength of the extremities.Methods We enrolled 183 patients with first-ever unilateral hemiplegia after stroke. The MEP parameters were amplitude ratio (amplitude of affected side/amplitude of unaffected side) recorded at the first dorsal interosseous (FDI) and tibialis anterior (TA) muscles. We performed frequency analyses using the MRC scale for muscle strength and the presence or absence of evoked MEPs. Change on the MRC scale, hand function tests (HFTs), and the Modified Barthel Index (MBI) subscore were compared between the evoked MEP and absent MEP groups using the independent t-test. Receiver operating characteristic curves were used to determine the optimal cutoff scores for the MEP amplitude ratio using the HFT results and MBI subscores. Correlations between the MEP amplitude ratio and the MRC scale, HFTs, and MBI subscore were analyzed. Results About 10% of patients with MRC scale grades 0?2 showed evoked MEPs at the FDI muscle, and 4% of patients with MRC scale grades 3?5 did not show MEPs. About 18% of patients with MRC scale grades 0?2 showed evoked MEPs at the TA muscle, and 4% of patients with MRC scale grades 3?5 did not show MEPs. MEP amplitude increased with increasing MRC scale grade. The evoked MEP group had more significant changes on the MRC scale, HFT, and the climbing stair score on the MBI than those in the group without MEPs. Larger MEP amplitude ratios were observed in patients who had more difficulty with the HFTs and ambulation. The MEP amplitude ratio was significantly correlated with the MRC scale, HFT, and MBI subscore.Conclusion We conclude that the MEP amplitude ratio may be useful to predict functional status of the extremities in patients who suffered stroke.

파형 역산은 탄성파 탐사 자료로부터 지구 내부의 변수들을 추정하여 지하구조를 복원시키는 기술이다. 이 기술은 석유탐사단계에서 유망구조가 되는 암염 돔과 같은 특정한 구조를 찾는데 중요한 역할을 하고 있다. 본 논문에서는 일반적인 목적함수와 로그 목적함수를 L2-norm, L1-norm을 모두 적용하여 파형 역산을 비교 연구해 보았다. 비교 연구를 위해 중앙에 고속도층이 있는 간단한 모델에 대해서 두 가지 목적함수를 적용하여 파형 역산을 시행하였다. 역산이 진행됨에 따라 오차 감소의 안정성과 역산 결과의 정확성을 비교했다. 파형 역산의 결과에 따르면 두 가지 방법의 정확성은 우열을 가리기 어려웠다. 그러나 오차의 안정성의 경우 로그 목적함수를 사용한 역산이 더 나은 결과를 보였다.

Waveform inversion involves the estimation of the parameters of a postulated earth model from a set of observation data. This process is essential for geophysical exploration finding specific structures, such as a salt dome which implies the potential existence of the oil and gas. In this study, we compare the conventional objective function to the logarithmic objective function applying both L2-norm and L1-norm in the waveform inversion. We test a simple velocity model including high velocity region. We have focused on stability of decreasing error and accuracy of inverted result. This study shows that there was little difference in the accuracy of the inverted results between two methods. However, the waveform inversion with the logarithmic objective function gives us better result in terms of stability of decreasing error.

오일 및 CO2 가격을 반영한 CO2 자극공법의 최적 설계안을 검토하기 위하여 본 수치 연구를 수행하였다. 주입설계 최적화를 위하여 순현가와 연계된 목적함수를 정의하고 Computer Modeling Group의 최적화 도구인 CMOST를 이용하였다. 복수의 CO2-오일 가격 시나리오를 설정하고 순현재가치를 기준으로 자극공법의 생산성에 영향을 주는 주입량과 soaking 시간 등의 설계 인자들을 최적화하였다. 본 연구 결과에 따르면 CO2 가격이 상승하면서 주입량이 감소하였으며 이는 두 번째 단계에서 더 크게 나타났다. CO2 가격이 높을수록 주입의 효율성을 고려하여 첫 번째 단계에서 가능한 많은 양을 생산하는 것이 적절하였다. 오일 가격이 증가하면서 첫 번째 단계의 주입설계는 거의 변하지 않는다. soaking 시간의 경우 경향성이 뚜렷하지 않았으며 생산성에 미치는 영향도 매우 작았다.

This numerical study was undertaken to investigate optimal design of CO2 stimulation considering oil and CO2 prices. For injection design optimization, objective function associated with net present value (NPV) was defined. CMOST, the optimization tool of Computer Modeling Group, is used to determine optimum cases. Design parameters such as injection volume and soaking time, which are known to affect the performance of CO2 stimulation, were optimized in terms of NPV through different scenarios of oil and CO2 prices. Results from the study indicated that optimum injection volume was declined at higher cost of CO2, especially in the second cycle. For higher CO2 price, it was better to maximize production of the first cycle for improving the efficiency of injection. As oil price increases, there were no changes of injection scheme in the first cycle. Soaking time had no clear tendency related with operating condition and affected production performance very slightly.

본 연구는 주관적 인지기능의 감소가 객관적 인지기능, 우울, 불안에 미치는 영향을 알아보고자 실시되었다. 65세 이상 노인에게 한국판 치매 설문 도구로 주관적 인지기능을 조사하여 주관적 인지기능 감소군(28명), 정상군(52명)으로 구분하였다. 두 집단에 6개월 간격으로 2회 객관적 인지기능, 우울, 불안을 조사하였다. 두 집단의 인지기능, 우울, 불안은 paired t-test, 공분산 분석으로 분석하였다. 연령을 통제한 후, 1차와 2차 조사 모두에서 주관적 인지기능 감소군의 주관적 인지기능, 즉시회상, 지연회상, 단어유창성, 우울, 불안점수가 정상군보다 통계적으로 유의미하게 감소하여 있었다. 1차와 2차 조사 모두에서 주관적 인지기능 감소군의 인지기능과 우울, 불안이 정상군보다 감소하여 있다는 사실은 인지기능 감소가 일시적인 현상이 아니라 실제로 인지기능의 변화가 일어나고 있음을 의미한다.

This study aims to investigate change of cognitive function, depression and anxiety according to time interval to identify whether subjective cognitive function is related to cognitive decline. Elderly adults aged 65 years or older visit a public healthcare center were divided into a subjective cognitive impairment group (n=28) and a normal group (n=52) based on the Korean Dementia Screening Questionnaire. The two groups’ objective cognitive function depression and anxiety at the baseline and 6-month follow-up were compared. Both groups’ objective cognitive function, depression and anxiety were then analyzed with paired t-tests and ANCOVA. After controlling for age, the two groups showed significant differences in subjective cognitive function, immediate recall, delayed recall, word fluency, depression, and anxiety at the baseline and 6 month follow-up. The fact that the differences in cognitive function, depression and anxiety at baseline are maintained over six months suggests that these changes are not transient but that cognitive impairment is indeed occurring.

This paper proposes a Modified Differential Evolution (MDE) for solving multi-objective load dispatch (MOLD) problem where transmission power losses are considered. MDE is an improved version of conventional Differential Evolution (CDE) in which the mutation operation of the CDE is improved by using five differential solutions instead of three ones similar to CDE. In the MOLD problem, three cases of dispatch including economic dispatch, emission dispatch and multi-objective dispatch are carried out by considering fuel cost function, emission function and both fuel cost and emission functions. In the third case of dispatch, there is a price penalty factor employed to determine the best compromise solution instead of using Fuzzy-based mechanism similar to other studies. The performance of MDE is verified by testing on two systems with three units and one system with six units. In the two systems, the fuel cost and emission from MDE are compared to those from CDE and other existing meta-heuristic algorithms, and the analysis on the result comparison indicates that the MDE is a promising algorithm for solving the MOLD problem.

It is necessary to develop an efficient optimization technique to perform optimum designs which have given design spaces, discrete design values and several design goals. As optimization techniques, direct search method and stochastic search method are widely used in designing of ship structures. The merit of the direct search method is to search the optimum points rapidly by considering the search direction, step size and convergence limit. And the merit of the stochastic search method is to obtain the global optimum points well by spreading points randomly entire the design spaces. In this paper, Pareto Strategy (PS) multi-objective function method is developed by considering the search direction based on Pareto optimal points, the step size, the convergence limit and the random number generation. The success points between just before and current Pareto optimal points are considered. PS method can also apply to the single objective function problems, and can consider the discrete design variables such as plate thickness, longitudinal space, web height and web space. The optimum design results are compared with existing Random Search (RS) multi-objective function method and Evolutionary Strategy (ES) multi-objective function method by performing the optimum designs of double bottom structure and double hull tanker which have discrete design values. Its superiority and effectiveness are shown by comparing the optimum results with those of RS method and ES method.

Since randomness and uncertainties of design parameters are inherent, the robust design has gained an ever increasing importance in mechanical engineering. The robustness is assessed by the measure of performance variability around mean value, which is called as standard deviation. Hence, constraints in robust optimization problem can be approached as probability constraints in reliability based optimization. Then, the FOSM (first order second moment) method or the AFOSM (advanced first order second moment) method can be used to calculate the mean values and the standard deviations of functions describing constraints and object. Among two methods, AFOSM method has some advantage over FOSM method in evaluation of probability. Nevertheless, it is difficult to obtain the mean value and the standard deviation of objective function using AFOSM method, because it requires that the mean value of function is always positive. This paper presented a special technique to overcome this weakness of AFOSM method. The mean value and the standard deviation of objective function by the proposed method are reliable as shown in examples compared with results by FOSM method.

We consider multiobjective fractional programming problems with generalized invexity. An equivalent multiobjective programming problem is formulated by using a modification of the objective function due to Antczak. We give relations between a multiobjective fractional programming problem and an equivalent multiobjective fractional problem which has a modified objective function. And we present modified vector saddle point theorems.

The present study aims to predict the heat transfer characteristics around a square cylinder with different corner radii using multivariate adaptive regression splines (MARS). Further, the MARS-generated objective function is optimized by particle swarm optimization. The data for the prediction are taken from the recently published article by the present authors [P. Dey, A. Sarkar, A.K. Das, Development of GEP and ANN model to predict the unsteady forced convection over a cylinder, Neural Comput. Appl. (2015) 1-13]. Further, the MARS model is compared with artificial neural network and gene expression programming. It has been found that the MARS model is very efficient in predicting the heat transfer characteristics. It has also been found that MARS is more efficient than artificial neural network and gene expression programming in predicting the forced convection data, and also particle swarm optimization can efficiently optimize the heat transfer rate.

Controlling traffic lights at a bottleneck, in [5] a time of open passage is called optimal, if it minimizes the first moment of the asymptotic distribution of the queue length. The discussion of the first moment as function of the time of open passage is based on an analysis of the behavior of a fixed point when varying control parameters and delivers theoretical and computational aspects of the traffic problem.

The problem of model reference adaptive control for the discrete time system is considered and the global stability of the overall system is shown. It extends the results of Choi's to the plants and models whose transfer functions have arbitrary gains and the method presented here makes the output error and the conftroller parameter error converge to zero. The scheme presented in this paper is simulated and gives good results.

In this paper, we consider a convex optimization problem with a convex integrable objective function and a geometric constraint set. We characterize the solution set of the problem when we know its one solution.

Fuzzy clustering has been playing an important role in solving many problems. Fuzzy c-Means(FCM) algorithm is most frequently used for fuzzy clustering. But some fixed point of FCM algorithm, know as Tucker's counter example, is not a reasonable solution. Moreover, FCM algorithm is impossible to perform the on-line learning since it is basically a batch learning scheme. This paper presents unsupervised learning networks as an attempt to improve shortcomings of the conventional clustering algorithm. This model integrates optimization function of FCM algorithm into unsupervised learning networks. The learning rule of the proposed scheme is a result of formal derivation based on the gradient descent procedure of a fuzzy objective function. Using the result of formal derivation, two algorithms of fuzzy cluster analysis, the batch learning version and on-line learning version, are devised. They are tested on several data sets and compared with FCM. The experimental results show that the proposed algorithms find out the reasonable solution on Tucker's counter example.

Flexible AC Transmission System (FACTS) application study on enhancing the flexibility of AC power system has continued to make progress. A thyristor-controlled series capacitor (TCSC) is a useful FACTS device that can control the power flow by adjusting line impedances and minimize the loss of power flow and voltage drop in a transmission system by adjusting line impedances. Reduced power flow loss leads to increased loadability, low system loss, and improved stability of the power system. This study proposes the optimal location and compensation rate method for TCSCs, by considering both the power system loss and voltage drop of transmission systems. The proposed method applies a multi-objective function consisting of a minimizing function for power flow loss and voltage drop. The effectiveness of the proposed method is demonstrated using IEEE 14- and a 30-bus system.

.