• The Korean Journal of Applied Statistics
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• v.30 no.6
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• pp.931-941
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• 2017

Typical Nonparametric methods for randomized block design with replications are two methods proposed by Mack (1981) and Mack and Skillings (1980). This method is likely to cause information loss because it uses the average of repeated observations instead of each repeated observation in the processing of each block. In order to compensate for this, we proposed a test method using linear placement statistics, which is a score function applied to the joint placement method proposed by Chung and Kim (2007). Monte Carlo simulation study is adapted to compare the power with previous methods.

• Journal of Information Technology Applications and Management
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• v.27 no.1
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• pp.173-186
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• 2020

This study examines the effect of congruity between product and TV reality show on purchase intention of Chinese consumers. A total of 110 respondents from Chinese consumers were collected using online surveys. The results were analyzed by SPSS 22.0. Multiple Linear Regression and process analysis were used to test the hypotheses. This article found that congruity between product and TV reality show, attitude toward product placement and recall of product affected consumers' purchase intention. In addition, the frequency of consumer watching TV reality show and familiarity of product moderated the attitude toward product placement and recall of product. This study provides useful implications for sponsors to select product placement as one of their marketing promotion tool.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.1114-1119
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• 1995

This paper presents the development of estimation model and control method based on the new computer vision. This proposed control method is accomplished using a sequential estimation scheme that permits placement of the rigid body in each of the two-dimensional image planes of monitoring cameras. Estimation model with six parameters is developed based on a model that generalizes known 4-axis scara robot kinematics to accommodate unknown relative camera position and orientation, etc. Based on the estimated parameters,depending on each camers the joint angle of robot is estimated by the iteration method. The method is tested experimentally in two ways, the estimation model test and a three-dimensional rigid body placement task. Three results show that control scheme used is precise and robust. This feature can open the door to a range of application of multi-axis robot such as assembly and welding.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.11
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• pp.100-107
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• 1998

This paper presents the development of estimation model and control method based on the new robot vision. This proposed control method is accomplished using the sequential estimation scheme that permits placement of the rigid body in each of the two-dimensional image planes of monitoring cameras. Estimation model with six parameters is developed based on the model that generalizes known 4-axis scara robot kinematics to accommodate unknown relative camera position and orientation, etc. Based on the estimated parameters, depending on each camera the joint angle of robot is estimated by the iteration method. The method is experimentally tested in two ways, the estimation model test and a three-dimensional rigid body placement task. Three results show that control scheme used is precise and robust. This feature can open the door to a range of application of multi-axis robot such as assembly and welding.

• Proceedings of the KIEE Conference
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• summer
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• pp.171-173
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• 2004

This paper presents the selection of optimal placement for STATCOM (Static synchronous Compensator) which is one of the FACTS (Flexible Alternating Current Transmission System) devices, considering line contingency. Line contingency ranking is gotten by using sensitivity of load margin. According to line contingency ranking line contingency was considered. And IOP (Index for selecting optimal Placement of STATCOM) is calculated by the variation of each bus's reactive mum for several line contingencies. The bus where has the biggest value of lOP is the most optimal placement to install STATCOM for voltage stability. IPLAN is used to program this part which get IOP. This study is carried out on the modified IEEE14 Bus Test System to confirm the efficiency of the method.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.03a
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• pp.1452-1457
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• 2010

Recently, coal ash is used as resources to make controlled low-strength material (CLSM) which a self-compacted, cementitious material used primarily as a backfill in lieu of compacted fill. Pozzolanic reaction is strongly related with self-cementation of coal ashes. However, this reaction depends on pozzolanic content in fill materials and is disappeared in 2-3 days after placement of coal ash fill. Therefore, state of coal ash fill is commonly very loose and not appropriate for foundations of structures without special treatments. In this study, a coal ash placement device was developed to place coal ashes effectively to improve density of coal ash fills. The device consists of a ribbon type mixer to obtain homogeneous materials mixture and a piston type pump for density control of fill materials. Based on several laboratory test results, more stable coal ash fill state can be obtained with controlling placement pressure.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.8
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• pp.471-480
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• 2003

The design of a measurement system to perform Harmonic State Estimation (HSE) is a very complex problem. Among the reasons for its complexity are the system size, conflicting requirements of estimator accuracy, reliability in the presence of transducer noise and data communication failures, adaptability to change in the network topology and cost minimization. In particular, the number of harmonic instruments available is always limited. Therefore, a systematic procedure is needed to design the optimal placement of measurement points. This paper presents a new HSE algorithm which is based on an optimal placement of measurement points using Genetic Algorithms (GAs) which is widely used in areas such as: optimization of the objective function, learning of neural networks, tuning of fuzzy membership functions, machine learning, system identification and control. This HSE has been applied to the Simulation Test Power System for the validation of the new HSE algorithm. The study results have indicated an economical and effective method for optimal placement of measurement points using Genetic Algorithms (GAs) in the Harmonic State Estimation (HSE).

• Journal of Electrical Engineering and Technology
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• v.12 no.3
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• pp.996-1006
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• 2017

Phasor Measurement Unit (PMU) placement is a crucial problem for State Estimation (SE) of the power system, which can ensure that the power network is fully observed. Further, the observation reliability problem of the system has been concerned in the operation conditions. In this paper, based on modified weighted adjacent matrix ($A_w$), an optimal placement method is proposed to solve simultaneously two problems involving the optimal PMU placement problem and the observation reliability enhancement problem of the system. The purpose of the proposed method is to achieve both the minimum total cost and the maximum observation reliability, with a focus on increasing the security of observability, strengthening the observation reliability of buses as well as enhancing the effectiveness of redundancy. Simulations on IEEE 14, 24, 30 and 57 bus test systems are presented to justify the methodology. The results of this study show that the proposed method is not only ensuring the power network having the observability effectively but also enhancing significantly the observation reliability. Therefore, it can be a useful tool for SE of the power system.

• The Korean Journal of Applied Statistics
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• v.19 no.3
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• pp.565-578
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• 2006

Repeated measurement data between two group is often used in the field of medicine study. In this paper, we suggest a method for comparison of the trend between two groups based on repeated measurement data. First, we estimate regression coefficient of linear regression model from each subject and generate samples using the regression coefficient estimated previous. And then, we test the difference between two groups by unpaired t-test, Wilcoxon rank sum test and placement test using generated samples. Monte Carlo Simulation is adapted to examine the power and experimental significance levels of several methods in various combinations.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.10a
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• pp.542-549
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• 2004

The compressive strength of concrete is commonly used criterion in producing concrete. However, the tests on the compressive strength are complicated and time-consuming. More importantly, it is too late to make improvement even if the test result does not satisfy the required strength, since the test is usually performed at the 28th day after the placement of concrete at the construction site. Therefore, accurate and realistic strength estimation before the placement of concrete is being highly required. In this study, the estimation of the compressive strength of concrete was performed by probabilistic neural network (PNN) on the basis of concrete mix proportions. The estimation performance of PNN was improved by considering the correlation between input data and targeted output value. Adaptive probabilistic neural network (APNN) was proposed to automatically calculate the smoothing parameter in the conventional PNN by using the scheme of dynamic decay adjustment algorithm. The conventional PNN and APNN were applied to predict the compressive strength of concrete using actual test data of a concrete company. APNN showed better results than the conventional PNN in predicting the compressive strength of concrete.