• Nuclear Engineering and Technology
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• v.1 no.2
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• pp.79-85
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• 1969

Determination of a two-point boundary value problem is the key of finding the control function u(f) with the application of the fundamental idea of Minimum principle. The late development shows the discovery of the initial testate vector for the solution of a two-point value problem. As a new technique of determining the optimal control function, Newton's sequential method is examined in this paper.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.161-164
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• 2005

Data mining techniques can be applied to identify patterns of interest in the gene expression data. One goal in mining gene expression data is to determine how the expression of any particular gene might affect the expression of other genes. To find relationships between different genes, association rules have been applied to gene expression data set [1]. A notable limitation of association rule mining method is that only the association in a single profile experiment can be detected. It cannot be used to find rules across different condition profiles or different time point profile experiments. However, with the appearance of time-series microarray data, it became possible to analyze the temporal relationship between genes. In this paper, we analyze the time-series microarray gene expression data to extract the sequential patterns which are similar to the association rules between genes among different time points in the yeast cell cycle. The sequential patterns found in our work can catch the associations between different genes which express or repress at diverse time points. We have applied sequential pattern mining method to time-series microarray gene expression data and discovered a number of sequential patterns from two groups of genes (test, control) and more sequential patterns have been discovered from test group (same CO term group) than from the control group (different GO term group). This result can be a support for the potential of sequential patterns which is capable of catching the biologically meaningful association between genes.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.1 s.256
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• pp.55-61
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• 2007

Recently simulation model becomes an essential tool for analysis and design of a system but it is often expensive and time consuming as it becomes complicate to achieve reliable results. Therefore, high-fidelity simulation model needs to be replaced by an approximate model, the so-called metamodel. Metamodeling techniques include 3 components of sampling, metamodel and validation. Cross-validation approach has been proposed to provide sequnatially new sample point based on cross-validation error but it is very expensive because cross-validation must be evaluated at each stage. To enhance the cross-validation of metamodel, sequential sampling method using candidate points and representative cross-validation is proposed in this paper. The candidate and representative cross-validation approach of sequential sampling is illustrated for two-dimensional domain. To verify the performance of the suggested sampling technique, we compare the accuracy of the metamodels for various mathematical functions with that obtained by conventional sequential sampling strategies such as maximum distance, mean squared error, and maximum entropy sequential samplings. Through this research we team that the proposed approach is computationally inexpensive and provides good prediction performance.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2011.06a
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• pp.535-536
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• 2011

• Nuclear Engineering and Technology
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• v.53 no.12
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• pp.4080-4092
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• 2021

In this study, the performance of sequence tracking methods for multiple interaction events in specific CdZnTe Compton imagers was evaluated using Monte Carlo simulations. The Compton imager consisted of a 6 × 6 array of virtual Frisch-grid CZT crystals, where the dimensions of each crystal were 5 × 5 × 12 mm³. The sequence tracking methods for another Compton imager that consists of two identical CZT crystals arrays were also evaluated. When 662 keV radiation was incident on the detectors, the percentages of the correct sequences determined by the simple comparison and deterministic methods for two sequential interactions were identical (~80%), while those evaluated using the minimum squared difference method (55-59%) and Three Compton method (45-55%) for three sequential interactions, differed from each other. The reconstructed images of a 662 keV point source detected using single and double arrays were evaluated based on their angular resolution and signal-to-noise ratio, and the results showed that the double arrays outperformed single arrays.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.10a
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• pp.299-300
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• 2012

• Journal of the Ergonomics Society of Korea
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• v.30 no.6
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• pp.739-747
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• 2011

Objective: The present study evaluated information presentation methods applicable to a wearable Braille display in terms of performance and satisfaction measures. Background: A Braille display wearable at a finger can improve accessibility of information for the blind by presenting information in real time. Method: A Braille display with six pins operated by DC servomotors was developed to simulate four information presentation methods(active, stationary, simultaneous, and sequential methods). An evaluation experiment was conducted with 16 participants(8 normal and 8 blind participants) by using three objective measures(reaction time, RT, unit: sec; recognition time, CT, unit: sec; correct response percentage, CP) and two subjective measures(overall satisfaction, OS; perception easiness, PE) with a 7-point scale. Results: The average RTs and CTs of the active and stationary methods were significantly shorter than those of the simultaneous and sequential methods for the blind participants. Also, the average CPs, OSs, and PEs of the active and sequential methods were significantly higher than those of the stationary and simultaneous methods. Conclusion: The active and sequential methods were preferred to the other methods for the blind. Application: The performance characteristics identified in the present study for the four braille display methods can be utilized to develop an effective wearable Braille display system.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.792-795
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• 2005

The guide-ways of precision machine tools are one of important element of machine tools. It has usually a pair of surfaces for constraint of one direction with bearing. In the case of precision machine tools, non-contact bearing such as hydrostatic bearing and aerostatic bearing is adopted usually. In this case, profiles of rails has effect on straightness and the clearance of bearing has effect on stiffness of guide way, which changes to higher if clearance changes to smaller. The clearance is varied along moving table according to relative distance of pair of rails. The relative distance of pair of rail can be divided by three properties. First and second properties are straightness of each pair of rail and bearing pad. And, third is parallelism about pair of rails and pairs of bearing pad. There are several methods for measuring straightness of each surface such as reversal method, sequential two point method, and way straightness. These straightness measuring methods are always acquiring deviation of profile from eliminating linear fitted inclined line and don't have the information of parallelism. Therefore, to get the small clearance for high stiffness, the straightness of rail and bearing pad and parallelism about pair of rails and pair of bearing pads are measured for correction such as regrinding, reassembling and lapping. In this research, new and easy method for measuring parallelism of pair of rails is suggested. Two displacement probe and sensor stage, which is carry on the displacement sensor, are needed. The simulation and experiment was accomplished about pair of horizontal guide way to confirm the measurement of parallelism. And, the third probe is added to measure the straightness of each rails by sequential two point method. From the estimation of combined these two methods, it is confirmed that the profiles of a pairs of rails can be measured.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.8
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• pp.175-183
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• 1996

This paper presents three-dimensional robot task using the vision control method. A minimum of two cameras is required to place points on end dffectors of n degree-of-freedom manipulators relative to other bodies. This is accomplished using a sequential estimation scheme that permits placement of these points in each of the two-dimensional image planes of monitoring cameras. Estimation model is developed based on a model that generalizes known three-axis manipulator kinematics to accommodate unknown relative camera position and orientation, etc. This model uses six uncertainty-of-view parameters estimated by the iteration method.

• Communications for Statistical Applications and Methods
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• v.30 no.4
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• pp.369-388
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• 2023

In this paper, we develop the two-step procedure that detects and estimates the position of structural changes for multivariate nonstationary time series, either on mean parameters or second-order structures. We first investigate the presence of mean structural change by monitoring data through the aggregated cumulative sum (CUSUM) type statistic, a sequential procedure identifying the likely position of the change point on its trend. If no mean change point is detected, the proposed method proceeds to scan the second-order structural change by modeling the multivariate nonstationary time series with a multivariate locally stationary Wavelet process, allowing the time-localized auto-correlation and cross-dependence. Under this framework, the estimated dynamic spectral matrices derived from the local wavelet periodogram capture the time-evolving scale-specific auto- and cross-dependence features of data. We then monitor the change point from the lower-dimensional approximated space of the spectral matrices over time by applying the dynamic principal component analysis. Different from existing methods requiring prior information on the type of changes between mean and covariance structures as an input for the implementation, the proposed algorithm provides the output indicating the type of change and the estimated location of its occurrence. The performance of the proposed method is demonstrated in simulations and the analysis of two real finance datasets.