• Journal of the Korean Society for Nondestructive Testing
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• v.31 no.5
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• pp.466-471
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• 2011

Optical coherence tomography(OCT) is an emerging medical diagnostic tool that draws great attention in medical and biological fields. It has a 10-100 times higher spatial resolution than that of the clinical ultrasound but lower imaging depth such as 1-2 mm. In order to image internal organs, OCT needs an endoscopic probe. In this paper, the principle of Fourier-domain optical coherence tomography with high-speed imaging capability was introduced. An OCT endoscope based on MEMS technology was developed. It was attached to the Fourier-domain OCT system to acquire three-dimensional tomographic images of gastrointestinal tract of New Zealand white rabbit. The endoscope had a two-axis scanning mirror that was driven by electrostatic force. The mirror stirred an incident light to sweep two-dimensional plane by scanning. The outer diameter of the endoscope was 6 mm and the mirror diameter was 1.2 mm. A three-dimensional image rendered by 200 two-dimensional tomographs with $200{\times}500$ pixels was displayed within 3.5 seconds. The spatial resolution of the OCT system was 8 ${\mu}m$ in air.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.8
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• pp.869-874
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• 2014

It is possible to fabricate a three-dimensional (3D) shape using the solid freeform fabrication (SFF) technology. However, there are several problems in applying conventional SFF technologies to the direct manufacturing of a product. Hence, multimaterial SFF is gaining attention. Moreover, a 3D circuit device that is different from a conventional two-dimensional PCB can also be fabricated using multimaterial SFF. In this study, a hybrid system using fused deposition modeling and direct writing was designed for 3D circuit device fabrication.

• Journal of Information Technology Services
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• v.14 no.1
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• pp.237-249
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• 2015

The volume of unstructured text data generated by various social media has been increasing rapidly; therefore, use of text mining to support decision making has also been increasing. Especially, issue Clustering-determining a new relation with various issues through clustering-has gained attention from many researchers. However, traditional issue clustering methods can only be performed based on the co-occurrence frequency of issue keywords in many documents. Therefore, an association between issues that have a low co-occurrence frequency cannot be discovered using traditional issue clustering methods, even if those issues are strongly related in other perspectives. Therefore, issue clustering that fits each of criteria needs to be performed by the perspective of analysis and the purpose of use. In this study, a multi-dimensional issue clustering is proposed to overcome the limitation of traditional issue clustering. We assert, specifically in this study, that issue clustering should be performed for a particular purpose. We analyze the results of applying our methodology to two specific perspectives on issue clustering, (i) consumers' interests, and (ii) related R&D terms.

• Journal of Fashion Business
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• v.20 no.1
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• pp.35-52
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• 2016

Yeohlee Teng's 'Urban Nomad' concept stresses high mobility and flexibility in 'Clothing-as-shelter' in order to satisfy the needs of urban dwellers. Yeohlee interprets clothing as a portable environment that protects and shelters urban nomads as well as creates space of clothing as intimate architecture. This study examines Nomadism in Yeohlee's designs since 1981 when she received the attention from the fashion critics, by conducting literary survey as well as case analysis. Nomadism in Yeohlee's work showed the following characterizes. First, 'modular system' deals with the organized dressing system that enables interchanging and layering of separates that function in the fifth season; second, 'organic geometry' describes the architectonic approach to clothing as wearable structure that transforms two dimensional geometry into three dimensional form; third, 'functionalism' refers to the use of technological novel materials, ergonomic clothing construction, and the strategy of using structure as decoration; and fourth, 'reductionism' is the economical approach for realizing Nomadism, which is composed of one-size-fits-all as well as unisex size system and 'zero waste' strategy to maximize use of a piece of cloth.

• Ocean Systems Engineering
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• v.6 no.3
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• pp.217-231
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• 2016

This paper presents a new approach for underwater image analysis using the bi-dimensional empirical mode decomposition (BEMD) technique and the phase congruency information. The BEMD algorithm, fully unsupervised, it is mainly applied to texture extraction and image filtering, which are widely recognized as a difficult and challenging machine vision problem. The phase information is the very stability feature of image. Recent developments in analysis methods on the phase congruency information have received large attention by the image researchers. In this paper, the proposed method is called the EP model that inherits the advantages of the first two algorithms, so this model is suitable for processing underwater image. Moreover, the receiver operating characteristic (ROC) curve is presented in this paper to solve the problem that the threshold is greatly affected by personal experience when underwater image edge detection is performed using the EP model. The EP images are computed using combinations of the Canny detector parameters, and the binaryzation image results are generated accordingly. The ideal EP edge feature extractive maps are estimated using correspondence threshold which is optimized by ROC analysis. The experimental results show that the proposed algorithm is able to avoid the operation error caused by manual setting of the detection threshold, and to adaptively set the image feature detection threshold. The proposed method has been proved to be accuracy and effectiveness by the underwater image processing examples.

• Journal of Electrical Engineering and Technology
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• v.13 no.4
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• pp.1614-1622
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• 2018

The research related to fault diagnosis in permanent magnet synchronous motors (PMSMs) has attracted considerable attention in recent years because various faults such as permanent magnet demagnetization and short-circuited turns can occur and result in unexpected failure of motor related system. Several conventional current and back electromotive force (BEMF) analysis techniques were proposed to detect certain faults in PMSMs; however, they generally deal with a single fault only. On the contrary, cases of multiple faults are common in PMSMs. We propose a fault diagnosis method for PMSMs with single and multiple combined faults. Our method uses three phase BEMF voltages based on the fast Fourier transform (FFT), support vector machine(SVM), and visualization tools for identifying fault types and severities in PMSMs. Principal component analysis (PCA) and t-distributed stochastic neighbor embedding (t-SNE) are used to visualize the high-dimensional data into two-dimensional space. Experimental results show good visualization performance and high classification accuracy to identify fault types and severities for single and multiple faults in PMSMs.

• Journal of Adhesion and Interface
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• v.22 no.3
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• pp.79-84
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• 2021

Graphene has been received a lot of attention as essential parts of future electronic and energy devices. Because of its extraordinary properties contributed from the atomic layer, the interface and surface engineering of graphene are promising approaches for realizing 2D materials-based high-performance devices. Herein, we summarize and introduce recent research trends of the synthesis of graphene through interface engineering for high-performance electronic and energy device applications, and then discuss the challenges and opportunities for achieving high-performance devices in next-generation electronics.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.169-176
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• 2021

Maritime monitoring requirements have been beyond human operators capabilities due to the broadness of the coverage area and the variety of monitoring activities, e.g. illegal migration, or security threats by foreign warships. Abnormal vessel movement can be defined as an unreasonable movement deviation from the usual trajectory, speed, or other traffic parameters. Detection of the abnormal vessel movement requires the operators not only to pay short-term attention but also to have long-term trajectory trace ability. Recent advances in deep learning have shown the potential of deep learning techniques to discover hidden and more complex relations that often lie in low dimensional latent spaces. In this paper, we propose a deep autoencoder-based clustering model for automatic detection of vessel movement anomaly to assist monitoring operators to take actions on the vessel for more investigation. We first generate gridded trajectory images by mapping the raw vessel trajectories into two dimensional matrix. Based on the gridded image input, we test the proposed model along with the other deep autoencoder-based models for the abnormal trajectory data generated through rotation and speed variation from normal trajectories. We show that the proposed model improves detection accuracy for the generated abnormal trajectories compared to the other models.

• Journal of the Korean Society of Physical Medicine
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• v.13 no.1
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• pp.99-105
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• 2018

PURPOSE: The aim of this study was to evaluate the concurrent validity and clinical usefulness of the universal plastic goniometer to measure the range of motion of the internal and external rotation of the hip joint using the three dimensional motion analysis which can analyze the joints and segment movements in the most objective and quantitative method. METHODS: Clinical and kinematic data were collected from thirty individuals using a universal plastic goniometer and a ten camera motion analysis system. Passive hip rotation range was obtained three trials for left and right hip joints using two measure methods simultaneously. RESULTS: There were significant differences between all matching measures of the two measures of internal and external rotation of the hip joint (p<.05). The relationship between the two tests for all measurements of the internal and external rotation of the hip was statistically significant with correlation coefficient form r=.87 to .96. (p<.01). CONCLUSION: Clinical measurement of the internal and external rotation of the hip using a universal plastic goniometer is effective to assess the hip condition. However, application of universal plastic goniometer requires careful attention in more accurate evaluation and research verification of the internal and external rotation of hip joint.

• Communications for Statistical Applications and Methods
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• v.27 no.1
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• pp.15-35
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• 2020

In research on behavioral studies, significant attention has been paid to the stage-sequential process for multiple latent class variables. We now explore the stage-sequential process of multiple latent class variables using the multivariate latent class profile analysis (MLCPA). A latent profile variable, representing the stage-sequential process in MLCPA, is formed by a set of repeatedly measured categorical response variables. This paper proposes the extended MLCPA in order to explain an association between the latent profile variable and the latent group variable as a form of a two-dimensional contingency table. We applied the extended MLCPA to the National Longitudinal Survey on Youth 1997 (NLSY97) data to investigate the association between of developmental progression of depression and substance use behaviors among adolescents who experienced Authoritarian parental styles in their youth.