• The Research Journal of the Costume Culture
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• v.7 no.4
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• pp.139-154
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• 1999

The objectives of this study were to find relationships between ego identity and clothing benefits, and to examine the influence of ego identity, clothing attributes evaluation, and demographic variables on clothing benefits. The subjects were 405 college students(male : 164, female : 241) in Seoul. Six factors of clothing benefit derived by factor analysis : fashion, comfort, social recognition, self-expression, recognized brand, and economy. Males with higher goal-directedness of ego identity had less interest in the benefits of social recognition and recognized brand. The higher the uniqueness of ego identity females had, the higher the social recognition and the lower the comfort. Social recognition of males was influenced by self-acceptance(-), style, and fastener(R²=17.7%). and recognized brand influenced by parents\` education, goal-directedness(-), and allowance(R²=27.5%). Fashion of females was influenced by style, allowance(-), and goal-directedness(-)(R²=18.7%), comfort unfluenced by uniqueness(-), size, and allowance(-)(R²=14.6%), and self-expression influenced by style, allowance, fastener, and interpersonal relation(R²=28.0%). The present findings mean that allowance and ego identity such as goal-directedness, self-acceptance, interpersonal relation were meaningful variables that affect clothing benefits.

• Bulletin of the Korean Chemical Society
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• v.32 no.1
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• pp.239-246
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• 2011

In this study, quantitative and pattern recognition analysis for the quality evaluation of Cimicifugae Rhizoma using HPLC/UV was developed. For quantitative analysis, three major bioactive phenolic compounds were determined. The separation conditions employed for HPLC/UV were optimized using ODS $C_{18}$ column ($250{\times}4.6mm$, $5{\mu}M$) with isocratic elution of acetonitrile and water with 0.1% phosphoric acid as the mobile phase at a flow rate of 1.0 mL/min and a detection wavelength of 323 nm. These methods were fully validated with respect to the linearity, accuracy, precision, recovery, and robustness. The HPLC/UV method was applied successfully to the quantification of three major compounds in the extract of Cimicifugae Rhizoma. The HPLC analytical method for pattern recognition analysis was validated by repeated analysis of twelve reference samples corresponding to five different species of Cimicifugae Rhizoma and seventeen samples purchased from markets. The results indicate that the established HPLC/UV method is suitable for the quantitative analysis and quality control of multi-components in Cimicifugae Rhizoma.

• Physical Therapy Korea
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• v.30 no.4
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• pp.306-313
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• 2023

Background: As social problems due to the acceleration of the aging era and the increase in the elderly population are becoming serious, virtual reality (VR)-based healthcare is emerging as an approach for preventing and managing health issues. Objects: This study used validity and reliability analyses to examine the clinical efficacy that is, the clinical value and usability of a novel VR cognitive evaluation system index that we developed. Methods: We developed a VR cognitive evaluation system based on motion recognition analysis evaluation for individuals aged 65 to 85. After conducting the Korean version of the Mini-Mental State Exam (K-MMSE) cognitive evaluation, the evaluation score was verified through correlation analysis in the VR cognitive evaluation system. To verify the construct validity of the two groups, the Global Deterioration Scale (GDS) grades were categorized into a normal cognitive group (GDS grade 1) and a cognitive impairment group (GDS grades 2 and 3). The data were measured twice to determine the reliability between the two measurements and assess the stability and clinical value of the evaluation system. Results: Our evaluation system had a high correlation of 0.85 with the widely used K-MMSE cognitive evaluation. The system had strong criterion-related validity at the 95% confidence interval. Compared to the average score of GDS grade 1 in the VR cognitive evaluation system, the average score of GDS grades 2 and 3 in the VR cognitive evaluation system was statistically significantly lower while also having strong construct validity at the 95% confidence interval. To measure the reliability of the VR cognitive evaluation system, tests-retests were conducted using the intraclass correlation coefficient (3,1), which equaled 0.923 and was statistically significant. Conclusion: The VR cognitive evaluation system we developed is a valid and reliable clinical tool to distinguish between normal cognitive status and mild cognitive impairment.

• Journal of the Korea Convergence Society
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• v.11 no.6
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• pp.1-6
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• 2020

In this study, research on character recognition, which is one of the fields of computer vision, was conducted. Optical character recognition, which is one of the most widely used character recognition techniques, suffers from decreasing recognition rate if the recognition target deviates from a certain standard and format. Hence, this study aimed to address this limitation by applying deep learning techniques to character recognition. In addition, as most character recognition studies have been limited to English or number recognition, the recognition range has been expanded through additional data training on Korean text. As a result, this study derived a deep learning-based character recognition algorithm for Korean text recognition. The algorithm obtained a score of 0.841 on the 1-NED evaluation method, which is a similar result to that of English recognition. Further, based on the analysis of the results, major issues with Korean text recognition and possible future study tasks are introduced.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.323-327
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• 1996

Gap and thickness difference information between blanks are often necessary for tailored blank welding quality evaluation , optimum welding parameters selection and evaluation of shearing machine, blink allocation device accuracy and clamping device. We develope 3D vision system and camera unit using structured lighting for this purpose. A simple ar d efficient scheme for gap and thickness feature recognition Is developed as well as measurements. Experimental results shows this system measuring accuracy is 10 ${\mu}{\textrm}{m}$ and 16${\mu}{\textrm}{m}$ for gap and thickness difference respectively The data are expexed to be useful for preview gap control.

• International Journal of Contents
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• v.3 no.2
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• pp.1-5
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• 2007

This paper proposes a technique for principal component analysis (PCA) to raise the recognition rate of a front face in a low dimension by hierarchical image and parallel processing structure. The conventional PCA shows a recognition rate of less than 50% in a low dimension (dimensions 1 to 6) when used for facial recognition. In this paper, a face is formed as images of 3 fixed-size levels: the 1st being a region around the nose, the 2nd level a region including the eyes, nose, and mouth, and the 3rd level image is the whole face. PCA of the 3-level images is treated by parallel processing structure, and finally their similarities are combined for high recognition rate in a low dimension. The proposed method under went experimental feasibility study with ORL face database for evaluation of the face recognition function. The experimental demonstration has been done by PCA and the proposed method according to each level. The proposed method showed high recognition of over 50% from dimensions 1 to 6.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.2
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• pp.31-40
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• 2012

Face recognition refers to the process of identifying individuals based on their facial features. It has recently become one of the most popular research areas in the fields of computer vision, machine learning, and pattern recognition because it spans numerous consumer applications, such as access control, surveillance, security, credit-card verification, and criminal identification. However, illumination variation on face generally cause performance degradation of face recognition systems under practical environments. Thus, this paper proposes an novel face recognition system using a fusion approach based on local binary pattern and two-dimensional principal component analysis. To minimize illumination effects, the face image undergoes the local binary pattern operation, and the resultant image are divided into two sub-images. Then, two-dimensional principal component analysis algorithm is separately applied to each sub-images. The individual scores obtained from two sub-images are integrated using a weighted-summation rule, and the fused-score is utilized to classify the unknown user. The performance evaluation of the proposed system was performed using the Yale B database and CMU-PIE database, and the proposed method shows the better recognition results in comparison with existing face recognition techniques.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2509-2528
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• 2019

There are various styles of license plates for different countries and use cases that require style-specific methods. In this paper, we propose and illustrate a multi-style license plate recognition system. The proposed system performs a series of processes for license plate candidates detection, structure classification, character segmentation and character recognition, respectively. Specifically, we introduce a license plate structure classification process to identify its style that precedes character segmentation and recognition processes. We use a K-Nearest Neighbors algorithm with pre-training steps to recognize numbers and characters on multi-style license plates. To show feasibility of our multi-style license plate recognition system, we evaluate our system for multi-style license plates covering single line, double line, different backgrounds and character colors on Korean and the U.S. license plates. For the evaluation of Korean license plate recognition, we used a 50 minutes long input video that contains 138 vehicles of 6 different license plate styles, where each frame of the video is processed through a series of license plate recognition processes. From two experiments results, we show that various LP styles can be recognized under 50 ms processing time and with over 99% accuracy, and can be extended through additional learning and training steps.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.4
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• pp.169-178
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• 2017

Recently, as the interest rate and necessity for security is growing, the demands for a visitor recognition system are being increased. In order to recognize a visitor in visitor recognition systems, the various biometric methods are used. In this paper, we propose a visitor recognition system based on face recognition. The visitor recognition system improves the face recognition performance by integrating several open APIs as a single algorithm and by performing the ensemble of the recognition results. For the performance evaluation, we collected the face data for about five months and measured the performance of the visitor recognition system. As the results of the performance measurement, the visitor recognition system shows a higher face recognition rate than using a single face recognition API, meeting the requirements on performance.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.436-442
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• 2016

There are a lot of sports when you left the victory and the defeat of the match the referee subjective judgment. In particular, TaeKwonDo pumse How accurate a given action? Is important. Objectively evaluate the subjective opinion of victory and defeat in a sporting event and the technology to keep as evidence is required. This study was implemented a system for recognizing Taekwondo executed through the number of motion recognition device. Step Sensor also used to detect a user's location. This study evaluated the rate matching the standard gesture data and the motion data. Through multiple gesture recognition equipment was more accurate assessment of the Taekwondo action.