• The Transactions of the Korean Institute of Electrical Engineers B
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• v.54 no.11
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• pp.505-510
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• 2005

On this study, we optimized maximizing the thrust force at the TFLM(Transverse Flux Linear Motor) using design of experiments by the table of orthogonal array and the analysis of means(ANOM), and classified the most contributive design factor maximizing the thrust force at the TFLM by analysis of variance(ANOVA). From now on, we are going to apply the required technique to design various uses and shapes of the TFLM.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2003.05a
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• pp.163-167
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• 2003

A novel method for 3-dimensional dynamic analysis of marine slender structure gas been developed by using Euler parameters. The Euler parameter rotation, which is being widely used in aerospace vehicle dynamics and multi-body dynamics, has been applied to elastic structure analysis. Large deformation of flexible slender structures is described by means of Euler parameters. Euler parameter method is implemented effectively in incremental-iterative algorithm for 3D dynamic analysis. The normalization constraint of Euler parameters is efficiently satisfied by means of a sequential updating method.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.05a
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• pp.786-792
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• 2006

The design of experiment(DOE) with orthogonal arrays is adopted when the engineering design is needed in a discrete design space. In this research, a design process with orthogonal array is peformed to obtain the optimum design which satisfy the frequency target of the steering system. The optimum design is determined from the analysis of means(ANOM) and sensitivity information about design variables is evaluated by the analysis of variance(ANOVA). Interactions between design variables are investigated to achieve additivity which should be valid in using orthogonal array. It is shown that when strong interactions exist, the DOE process with orthogonal array considering interaction is introduced to find out optimum design.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.11
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• pp.180-187
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• 2003

A CAD-based seamless design system for MEMS named DS/MEMS was developed which performs coupled-field analysis, optimal and robust design. DS/MEMS has been developed by means of integrating commercial codes and inhouse code-SolidWorks, FEMAP, ANSYS and CA/MEMS. This strategy results in versatility that means to include various analysis model, corresponding analyses and approximated design sensitivity analysis and user friendliness that design variables are taken to be selectable directly from a CAD model, that the problem is formulated under a window environment and that the manual job during optimization process is almost eliminated. DS/MEMS works on a parametric CAD platform, integrating CAD modeling, analysis, and optimization. Nonlinear programming algorithms, the Taguchi method, and response surface method are made available for optimization. One application problem is taken to illustrate the proposed methodology and show the feasibility of DS/MEMS as a practical tool.

• Proceedings of the Korean Institute of Surface Engineering Conference
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• 2015.11a
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• pp.242-243
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• 2015

Fault detection using optical emission spectra with modified K-means cluster analysis and principal component anal ysis are demonstrated for inductive coupl ed pl asma cl eaning processes. The optical emission spectra from optical emission spectroscopy (OES) are used for measurement. Furthermore, Principal component analysis and K-means cluster analysis algorithm is modified and applied to real-time detection and sensitivity enhancement for fluorocarbon cleaning processes. The proposed techniques show clear improvement of sensitivity and significant noise reduction when they are compared with single wavelength signals measured by OES. These techniques are expected to be applied to various plasma monitoring applications including fault detections as well as chamber cleaning endpoint detection.

• Korean Journal of Human Ecology
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• v.17 no.5
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• pp.1001-1013
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• 2008

The purpose of this study were to make clear the actual state of indoor air quality by cooling in private institute classrooms and to analyze influencing factors on indoor air quality. The measurements of physical elements and observations of architectural characteristics and living conditions were carried out in each 1 classroom of 5 private institutes. Measuring elements were indoor temperature, relative humidity, $PM_{10}$, HCHO, CO, and $CO_2$ concentration. As results, the averages of indoor temperature each classroom were $21.7\sim28.1^{\circ}C$. 3 classrooms were lower than the Maintenance standard($26\sim28^{\circ}C$) of School Health Law. The means of relative humidity were 48$\sim$63%, all classrooms were ranged within the standard(30$\sim$80%). The means of $PM_{10}$ concentration were 2.1 $\sim$ 17 $\mu g/m^3$, all classrooms were kept within the standard(100 $\mu g/m^3$). The means of HCHO concentration were 0.02$\sim$0.16 ppm, 2 classrooms were exceed the standard(0.1 ppm). The means of CO concentration were 1.4$\sim$3.6 ppm, all classrooms were kept within the standard(10ppm). The means of $CO_2$ concentration were 1,593$\sim$3,819 ppm, all classrooms were exceed the standard(1,000ppm). The results of analysis on influencing factors of the physical elements are as follow; the air conditioner set of temperature, personal necessities like hair spray, teacher's smoking in corridor, windows and doors opening time, the number of students, and volume of classroom.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.4
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• pp.900-907
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• 2009

In this research, railway transportation by means of the characteristics of tourism in the selection of railroad tourism and to clarify the difference in IPA is a primary purpose of this research. In addition, the train travel experience would like to clarify the difference in the importance and performance. This research fellows the indication points. First, by means of transportation to select train tourism product is the difference in the importance and performance in the 25 items. Second, the urgent needs to improve part 'Concentrate Here' side of the train, the temperature of the reasonable air-conditioning, and the appropriate means of transport links to the information service has been identified.'Low Priority' side of the entry tourist train operation of the frequency and interval, a total of 26 items, including the efforts of more than the current level of commitment was expected to be unnecessary. Third, according to the experience of sightseeing train railway transportation as a means to help train tourism product selection was the difference in the importance and performance.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2020.11a
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• pp.54-55
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• 2020

In 4th Industrial Revolution, technologies such as artificial intelligence, Internet of Things, and Big data are closely related to the maritime industry, which led to the birth of autonomous vessels. Due to the technical characteristics of the current vessel, the speed cannot be suddenly lowered, so complex communication such as the help of a tug boat, boarding of a pilot, and control of the vessel at the onshore control center is required to berth at the port. In this study, clustering analysis was used to resolve how to establish control criteria for vessels to enter port when autonomous vessels are operating. K-Means clustering was used to quantitatively stage the arrival pattern based on the accumulated AIS(Automatic Identification System) data of the incoming vessel, and the arrival phase using SOG(Speed over Ground), COG(Course over Ground), and ROT(Rate of Turn) Was divided into six phase.

• Translational and Clinical Pharmacology
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• v.25 no.3
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• pp.147-152
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• 2017

This study focused on the role of cytochrome P450 2D6 (CYP2D6) genotypes to predict phenotypes in the metabolism of dextromethorphan. CYP2D6 genotypes and metabolic ratios (MRs) of dextromethorphan were determined in 201 Koreans. Unsupervised clustering algorithms, hierarchical and k-means clustering analysis, and color visualizations of CYP2D6 activity were performed on a subset of 130 subjects. A total of 23 different genotypes were identified, five of which were observed in one subject. Phenotype classifications were based on the means, medians, and standard deviations of the log MR values for each genotype. Color visualization was used to display the mean and median of each genotype as different color intensities. Cutoff values were determined using receiver operating characteristic curves from the k-means analysis, and the data were validated in the remaining subset of 71 subjects. Using the two highest silhouette values, the selected numbers of clusters were three (the best) and four. The findings from the two clustering algorithms were similar to those of other studies, classifying $^*5/^*5$ as a lowest activity group and genotypes containing duplicated alleles (i.e., $CYP2D6^*1/^*2N$) as a highest activity group. The validation of the k-means clustering results with data from the 71 subjects revealed relatively high concordance rates: 92.8% and 73.9% in three and four clusters, respectively. Additionally, color visualization allowed for rapid interpretation of results. Although the clustering approach to predict CYP2D6 phenotype from CYP2D6 genotype is not fully complete, it provides general information about the genotype to phenotype relationship, including rare genotypes with only one subject.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.8
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• pp.731-738
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• 2011

In this paper, we introduce an advanced architecture of K-Means clustering-based polynomial Radial Basis Function Neural Networks (p-RBFNNs) designed with the aid of SSOA (Space Search Optimization Algorithm) and develop a comprehensive design methodology supporting their construction. In order to design the optimized p-RBFNNs, a center value of each receptive field is determined by running the K-Means clustering algorithm and then the center value and the width of the corresponding receptive field are optimized through SSOA. The connections (weights) of the proposed p-RBFNNs are of functional character and are realized by considering three types of polynomials. In addition, a WLSE (Weighted Least Square Estimation) is used to estimate the coefficients of polynomials (serving as functional connections of the network) of each node from output node. Therefore, a local learning capability and an interpretability of the proposed model are improved. The proposed model is illustrated with the use of nonlinear function, NOx called Machine Learning dataset. A comparative analysis reveals that the proposed model exhibits higher accuracy and superb predictive capability in comparison to some previous models available in the literature.