• Journal of Korean Society for Quality Management
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• v.23 no.4
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• pp.28-41
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• 1995

We consider the problem of identifying multiple outliers in linear model. The available regression diagnostic methods often do not succeed in detecting multiple outliers because of the masking and swamping effect. Recently, among the various robust estimator of reducing the effect of outliers, LMS(Least Meadian Square) estimator has been to be a suitable method proposed to expose outliers and leverage points. However, as you know it, the data analysis method with LMS estimator is to be taken the median of the squared residuals in the sample which is extracted the sample space. Then this model causes the trouble, for the number of the chosen sample is nCp, i.e. as the size of sample space n is increasing, the number is increasing fastly. And the covariance matrix may be the singular matrix, so that matrix is approching collinearity. Thus we propose a procedure ELMS for the resampling in LMS method and study the size of the effective elementary set in this algorithm.

• Proceedings of the Materials Research Society of Korea Conference
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• 2011.10a
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• pp.16.1-16.1
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• 2011

Gas sensor properties of $WO_3$ nanowire structures have been studied. The sensing layer was prepared by deposition of tungsten metal on porous single wall carbon nanotubes followed by thermal oxidation. The morphology and crystalline quality of $WO_3$ material was investigated by SEM, TEM, XRD and Raman analysis. A highly porous $WO_3$ nanowire structure with a mean diameter of 82 nm was obtained. Response to CO, $NH_3$ and $H_2$ gases diluted in air were investigated in the temperature range of $100{\sim}340^{\circ}C$ The sensor exhibited low response to CO gas and quite high response to $NH_3$ and $H_2$ gases. The highest sensitivity was observed at $250^{\circ}C$ for $NH_3$ and $300^{\circ}C$ for $H_2$. The effect of the diameters of $WO_3$ nanowires on the sensor performance was also studied. The $WO_3$ nanowires sensor with diameter of 40 nm showed quite high sensitivity, fast response and recovery times to $H_2$ diluted in dry air. The sensitivity as a function of detecting gas concentrations and gas sensing mechanism was discussed. The effect of dilution carrier gases, dry air and nitrogen, was examined.

• Communications for Statistical Applications and Methods
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• v.18 no.4
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• pp.413-422
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• 2011

We have used a multifactor dimensionality reduction(MDR) method to study the major gene interaction effect in general; however, without application of the MDR method in continuous data. In light of this, many methods have been suggested such as Expanded MDR, Dummy MDR and SVM MDR. In this paper, we compare the two methods of SVM MDR and D-MDR. In addition, we identify the gene-gene interaction effect of single nucleotide polymorphisms(SNPs) associated with economic traits in Hanwoo(Korean cattle). Lastly, we discuss a new method in consideration of the advantages that the other methods present.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1997.10a
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• pp.177-180
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• 1997

Outliers, unexpected extraordinary observations that look discordant from most observation in a data set are commonplace in various kinds of data analysis. Since the effect of outliers on model identification could be serious, the aim of this paper is to present some ways of handling outliers in given data set and to specify a model in the presence of outliers. A procedure based on neural network which identifies outliers, removes their effects, and specifies a model for the underlying process is proposed. In contrast with traditional parametric methods requiring to estimate the model's structure and parameters before detecting outliers, the proposed procedure is a nonparametric method without the estimation of model's structure and parameters before handling outliers and could be applied for real problems in the presence of outliers. The proposed methodology is performed as followings. Firstly, outliers are detected and the detected outliers replace the prediction values using outliers detection neural network. The data set removing the effect of outliers is retraining using neural network. Therefore the effects of outliers are removed and the modeling precision can be improved. Experimental results show that the proposed method is suitable for predicting data set in the presence of outliers.

• Journal of Ocean Engineering and Technology
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• v.23 no.6
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• pp.32-38
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• 2009

An FMEA for the waterjet-lifter of a DSNM is performed to prevent the occurrence of device failure. A waterjet-lifter raises and transports manganese nodules from the deep-sea floor up to a somewhat elevated place, from which a pin-scraper transports the lifted nodules to the inner space of the DSNM. A concept design for a device using the axiomatic design methodology is shown as the mapping between the functional domain and physical domain. The FMEA for a DSNM is introduced briefly and the rating criteria of severity, occurrence, and detection for the DSNM are defined. The FMEA of the functional requirements of a DSNM device is accomplished. Three kinds of failure modes, as well as their effects and causes, are predicted. Current design control methods for detecting potential failures, such as physical or computational experiments, design confirmation, and mathematical calculation, are described and the recommended actions for several significant causes are suggested.

• Journal of Power Electronics
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• v.8 no.1
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• pp.91-100
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• 2008

The d-q harmonic detecting algorithms are dominant methods to generate current references for active power filters (APF). They are often implemented in the synchronous frame and time domain. This paper researches the frequency characteristics of d-q synchronous transformations, which are closely related to the analysis and design issues of control system. Intuitively, the synchronous transformation is explained with amplitude modulation (AM) in this paper. Then, the synchronous filter is proven to be a time-invariant and linear system, and its transfer function matrix is derived in the stationary frames. These frequency-domain models imply that the synchronous transformation has an equivalent effect of frequency transformation. It is because of this feature, the d-q method achieves band-pass characteristics with the low pass filters in the synchronous frame at run time. To simplify these analytical models, an instantaneous positive-negative sequence frame is proposed as expansion of traditional symmetrical components theory. Furthermore, the synchronous filter is compared with the traditional bind-pass filters based on these frequency-domain analytical models. The d-q harmonic detection methods are also improved to eliminate the inherent coupling effect of synchronous transformation. Typical examples are given to verify previous analysis and comparison. Simulation and experimental results are also provided for verification.

• The Journal of Korean Physical Therapy
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• v.24 no.6
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• pp.405-408
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• 2012

Purpose: We examined the effect of dual-task and single-task training on serial reaction time (SRT) task performance to determine whether SRT is based more on motor or perception in a dual-task. Methods: Forty healthy adults were divided into two groups: the dual-task group (mean age, $21.8{\pm}1.6$ years) and the single-task group (mean age, $21.7{\pm}1.6$ years). SRT task was conducted total 480 trial. The four figures were presented randomly 16 times. A unit was set as 1 block that would repeat 10 times. Thus, there were a total of 160 trials for each of the three color conditions. The dual-task group performed an SRT task while detecting the color of a specific shape. The end of the task, subjects answered the specific shape number; the single-task group only performed the SRT task. The study consisted of three parts: pre-measurement, task performance, and post-measurement. Results: Differences of pre and post reaction time between two group was higher for the dual-task group as compared to the single task group and there was a significant interaction between time and group (p<0.05). Conclusion: Our results indicate that. short term period SRT is not quiet effective under dual-task conditions, individuals need additional cognitive processes to successfully navigate a task This suggests that dual-task training might not be appropriate for motor learning enhancement, at least when the training is over a short period.

• Smart Structures and Systems
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• v.12 no.6
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• pp.619-640
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• 2013

It is highly desirable to explore efficient algorithms for detecting structural damage of large size structural systems with limited input and output measurements. In this paper, a new structural damage detection algorithm based on substructure approach is proposed for large size structural systems with limited input and output measurements. Inter-connection effect between adjacent substructures is treated as 'additional unknown inputs' to substructures. Extended state vector of each substructure and its unknown excitations are estimated by sequential extended Kalman estimator and least-squares estimation, respectively. It is shown that the 'additional unknown inputs' can be estimated by the algorithm without the measurements on the substructure interface DOFs, which is superior to previous substructural identification approaches. Also, structural parameters and unknown excitation are estimated in a sequential manner, which simplifies the identification problem compared with other existing work. Structural damage can be detected from the degradation of the identified substructural element stiffness values. The performances of the proposed algorithm are demonstrated by several numerical examples and a lab experiment. Measurement noise effect is considered. Both the simulation results and experimental data validate that the proposed algorithm is viable for structural damage detection of large size structural systems with limited input and output measurements.

• Smart Structures and Systems
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• v.22 no.3
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• pp.291-302
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• 2018

This paper presents a flexibility based method for damage identification from static measurements in beam-type structures. The response of the beam at the Damaged State is decomposed into the response at the Reference State plus the response at an Incremental State, which represents the effect of damage. The damage is localized by detecting slope discontinuities in the deflection of the structure at the Incremental State. A denoising filtering technique is applied to reduce the effect of experimental noise. The extent of the damage is estimated through comparing the experimental flexural stiffness of the damaged cross-sections with the corresponding values provided by analytical models of cracked beams. The paper illustrates the method by showing a numerical example with two cracks and an experimental case study of a simply supported steel beam with one artificially introduced notch type crack at three damage levels. A Digital Image Correlation system was used to accurately measure the deflections of the beam at a dense measurement grid under a set of point loads. The results indicate that the method can successfully detect and quantify a small damage from the experimental data.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.07a
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• pp.443-446
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• 2001

MI(Magneto-Impedance) sensor which is made by thin films has significantly high detecting sensitivity in weak magnetic field. It also has a merit to be able to build in low power system. Its structure is simple, which makes it easier to prepare a miniature. In this study, its magnetic permeability and anisotropy field(H$\sub$k/) as a function of a thickness of sputtered amorphous CoZrNb thin film with high saturation magnetostriction and excellent soft magnetic property are investigated. In order to make a uniaxial anisotropy, thin film was subjected to post annealing with a static magnetic field with 1KOe intensity at 250, 300, and 320$^{\circ}C$ for 2 hour. Anisotropy field(H$\sub$k/)of thin film is measured by using MH loop tracer. Its magnetic permeability of thin film is measured over the frequency range from 1 MHz to 750MHz. It has shown that the magnetic permeability of amorphous CoZrNb thin film is decreased due to the skin effect with increasing a thickness of CoZrNb thin film, and hence its driving frequency is lowered.