• Journal of Korea Water Resources Association
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• v.35 no.2
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• pp.187-194
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• 2002

To improve the accuracy of the areal rainfall estimates over a river basin, the optimal design method of rainfall network was studied using the stochastic characteristics of measured rainfall data. The objective function was constructed with the estimation error of areal rainfall and observation cost of point rainfall and the observation sites with minimum objective function value were selected as the optimal network. As a stochastic variance estimator, kriging model was selected to minimize the error terms. The annual operation cost including the installation cost was considered as the cost terms and an accuracy equivalent parameter was used to combine the error and cost terms. The optimal design method of rainfall network was studied in the Yongdam dam basin whose raingauge numbers need to be enlarged for the optimal rainfall networks of the basin.

• International Journal of Advanced Culture Technology
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• v.7 no.2
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• pp.209-217
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• 2019

Due to the development of artificial intelligence and image recognition technology that play important roles in the field of 4th industry, office automation systems and unmanned automation systems are rapidly spreading in human society. The proposed algorithm first finds the variances of the differences between the tile values constituting the learning characters and the experimental character and then recognizes the experimental character according to the distribution of the three learning characters with the smallest variances. In more detail, for 100 learning data characters and 10 experimental data characters, each character is defined as the number of black pixels belonging to 15 tile areas. For each character constituting the experimental data, the variance of the differences of the tile values of 100 learning data characters is obtained and then arranged in the ascending order. After that, three learning data characters with the minimum variance values are selected, and the final recognition result for the given experimental character is selected according to the distribution of these character types. Moreover, we compare the recognition result with the result made by a neural network of basic structure. It is confirmed that satisfactory recognition results are obtained through the processes that subdivide the learning characters and experiment characters into tile sizes and then select the recognition result using variances.

• Nuclear Engineering and Technology
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• v.55 no.3
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• pp.876-883
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• 2023

Radioactive waste should be solidified before being disposed of in the repository to eliminate liquidity or dispersibility. Cement is a widely used solidifying media for radioactive waste, and cement solidified waste should satisfy the minimum compressive strength of the waste acceptance criteria of a radioactive repository. Although the compressive strength of waste should be measured by the test method provided by the waste acceptance criteria, the method differs depending on the operating repository of different countries. Considering the measured compressive strength changes depending on test conditions, the effect of test conditions should be analyzed to avoid overestimation or underestimation of the compressive strength during disposal. We selected test conditions such as the height-to-diameter ratio, loading rate, and porosity as the main factors affecting the compressive strength of cement solidified radioactive waste. Owing to the large variance in measured compressive strength, the effects of the test conditions were analyzed via statistical analyses using parametric and nonparametric methods. The results showed that the test condition of the lower loading rate, with a height-to-diameter ratio of two, reflected the actual cement content well, while the porosity showed no correlation. The compressive strength assessment method that reflects the large variance of strengths was suggested.

• Journal of muscle and joint health
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• v.20 no.3
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• pp.225-234
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• 2013

Purpose: This purpose of study was to investigate the relationships among functional state, self-efficacy, and life satisfaction in the elderly with decreased visual acuity. Methods: The subjects were 162 elderly people from the G university hospital. Functional state was measured by Late-Life Function and Disability Instrument (LLFDI) and Minimum Data Set-Home Care version 2.0 (MDS HC 2.0). Self-efficacy and Life satisfaction were measured by the tool of Rho & Lee (2011) and Yoon (2007). Data were analyzed using t-test, ANOVA, Pearson's Correlation Coefficient, and logistic regression. Results: The daily life function was significantly associated with self-efficacy and vision decrease. The regression model with these two variables explained 35.6% of the variance of daily life function. IADL was significantly associated with vision decrease, age, gender, and self-efficacy. The regression model with the three variables explained 52.9% of the variance of IADL. Life satisfaction is significantly associated with self-efficacy, daily life function, vision decrease and IADL. The last regression model with the four variables explained 51.8% of the variance of life satisfaction. Conclusion: The levels of functional state, self-efficacy and life satisfaction in the elderly with decreased visual acuity were low. Self-efficacy was an important factor that influences on the functional state and life satisfaction. Therefore, nursing interventions that can enhance the self-efficacy are required in order to increase the functional state and life satisfaction in the elderly with decreased visual acuity.

• Proceedings of the KIEE Conference
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• 2008.04a
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• pp.187-188
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• 2008

주기적으로 제어 성능을 평가하고, 평가 결과에 따라서 제어시스템의 제어기 상수를 최적화하거나 제어 밸브와 같은 제어기기의 문제점들을 사전에 개선하고자하는 노력이 있어왔다. 제어성능 평가방법은 제어목표 값에 대한 추종성을 평가하는 Set Point Analysis 방법을 주로 사용한다. 평가 지표는 Integral Absolute Error(IAE)와 같은 Error Integral 값과 Minimum Variance 방법이 실용적으로 사용된다. 본 논문에서는 평가 대상시스템으로 원자력발전소의 수위 제어시스템중 하나를 선정하고 Control Performance Assessment를 수행하였다. 이를 기반으로 대상 시스템의 제어모델링을 바탕으로 한 Minimum Integral Error를 만족하는 제어기 상수를 구하였으며 새로운 상수를 제어기에 설정한 후 다시 성능을 평가하였다. 평가 결과, 제어시스템의 제어 성능 평가 지표를 사용한 제어 루프의 평가와 예방 조치가 실제적으로 발전소의 안정적 운전에 유용하다는 것을 입증하였다.

• Journal of Broadcast Engineering
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• v.9 no.3
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• pp.207-213
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• 2004

The layered depth image (LDI) is an efficient approach to represent three-dimensional objects with complex geometry for image-based rendering (IBR). LDI contains several attribute values together with multiple layers at each pixel location. In this paper, we propose an efficient preprocessing algorithm to compress depth information of LDI. Considering each depth value as a point in the two-dimensional space, we compute the minimum distance between a straight line passing through the previous two values and the current depth value. Finally, the minimum distance replaces the current attribute value. The proposed algorithm reduces the variance of the depth information , therefore, It Improves the transform and coding efficiency.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.425-426
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• 2008

발전소의 제어 시스템은 제어 기간이 길어짐에 따라 제어 기기의 운전 특성이 변화하므로 최초 설계 및 운전때의 성능과는 다른 제어 특성을 나타낸다. 따라서 주기적으로 제어 성능을 평가하고 평가 결과에 따라서 제어 기기의 성능 개선 작업과 제어 시스템의 제어기 상수 최적화 등의 작업을 통하여 제어 성능을 최적으로 유지하여 제어 목적을 달성하도록 하여야한다. 제어성능 평가기법은 제어 목표 값에 대한 추종성을 평가하는 Set Print Analysis 방법을 주로 사용한다. 평가 지표는 Integral Absolute Error(IAE)와 같은 Error Integral 값과 Minimum Variance방법이 실용적으로 사용된다. 본 논문에서는 Non-Minimum Phase 특성으로 인하여 초기 운전 모드에서 정상 운전 모듈로의 원활한 전환이 어려운 수위 제어 시스템에서 제어 전환을 위한 최적 제어기 상수를 구하기 위하여 CPA 방법을 적용하였다. 일반적으로 제어성 평가는 설정치 변화에 대한 추종성을 평가하지만 본 논문에서는 제어 전환 시의 제어성 평가를 통하여 최적의 제어 전환 상수를 구하고자 하였다. 적용 결과, CPA기법은 설정시 추종성뿐만 아니라 제어 과도에서의 제어 전환 변수의 주종성에 적용하여 제어 전환을 최적화하는데도 유용함을 확인하였다.

• ETRI Journal
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• v.34 no.4
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• pp.511-517
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• 2012

The best linear unbiased estimator (BLUE) is most suitable for practical application and can be determined with knowledge of only the first and second moments of the probability density function. Although the BLUE is an existing algorithm, it is still largely unexplored and has not yet been applied to channel estimation in amplify and forward (AF)-based wireless relay networks (WRNs). In this paper, a BLUE-based algorithm is proposed to estimate the overall channel impulse response between the source and destination of AF strategy-based WRNs. Theoretical mean square error (MSE) performance for the BLUE is derived to show the accuracy of the proposed channel estimation algorithm. In addition, the Cram$\acute{e}$r-Rao lower bound (CRLB) is derived to validate the MSE performance. The proposed BLUE channel estimation algorithm approaches the CRLB as the length of the training sequence and number of relays increases. Further, the BLUE performs better than the linear minimum MSE estimator due to the minimum variance characteristic exhibited by the BLUE, which happens to be a function of signal-to-noise ratio.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.10C
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• pp.991-999
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• 2006

This paper shows that the support growth of an optimum (minimum mean square-error) scalar quantizer for a Laplacian density is logarithmic with the number of quantization points. Specifically, it is shown that, for a unit-variance Laplacian density, the ratio of the support-determining threshold of an optimum quantizer to $\frac 3{\sqrt{2}}1n\frac N 2$ converges to 1, as the number of quantization points grows. Also derived is a limiting upper bound that says that the optimum support cannot exceed the logarithmic growth by more than a constant. These results confirm the logarithmic growth of the optimum support that has previously been derived heuristically.

• The Journal of Natural Sciences
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• v.8 no.1
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• pp.5-15
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• 1995

The equation error formulation in the adaptive IIR filtering provides convergence to a global minimum regardless a local minimum with a large stability margin. However, the equation error formulation suffers from the bias in the coefficient estimates. In this paper, a new algorithm, which does not require a prespecification of the noise variance, is proposed for the equation error formulation. This algorithm is based on the equation error smoothing and provides an unbiased parameter estimate in the presence of white noise. Through simulations, it is demonstrated that the algorithm eliminates the bias in the parameter estimate while retaining good properties of the equation error formulation such as fast convergence speed and the large stability margin.