• Bulletin of the Korean Chemical Society
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• v.28 no.5
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• pp.805-810
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• 2007

Molecular recognition for a specific cation depending on the change of the oxidation state of the metal catalyst component contained in the hydrogel network has been studied in a self-oscillating hydrogel. The selfoscillating hydrogels are synthesized by the copolymerization of N-isopropylacrylamide (NIPAAm), lead methacrylic acid (Pb(MAA)2), and Ru(bpy)3 2+ monomer as a metal catalyst component. The recognition for a specific cation (in this study, Ca2+ has been used) is characterized by the adsorbed amount of Ca2+ into the gel. The recognition of the gels for Ca2+ is higher at the temperature below the LCST, and also higher at the oxidized state than at reduced state of the metal catalyst component which corresponds to a more swollen state. Moreover, a propagating wave induced by a periodic change of the oxidation state with the diffusion phenomena in the oscillating hydrogel shows a possibility for temporal and site-specific molecular recognition due to the local swelling of the gel.

• Journal of Family Resource Management and Policy Review
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• v.13 no.4
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• pp.73-93
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• 2009

The purpose of this study was to examine retirees' attitudes towards change of living standards. The data were drawn from the 2007 Korean Retiree Survey, as carried out by the Korean Investors Education Foundation. The major findings are as follows: 1) Some retirees were not well-prepared for retirement, i.e., they lacked financial consultation, had low personal financial literacy, and lacked sufficient wealth. Retirees suffered from health difficulties, loneliness or a sense of alienation, family conflict, or lack of pastimes. 2) Certain groups recognized the change of living standards for retirees as either positive or negative. Retirees who recognized the change of living standards as negative were not well-prepared for retirement, had low personal financial literacy, and lacked sufficient wealth. They also suffered from health difficulties, loneliness or a sense of alienation, family conflict, or lack of pastimes. 3) There was a strong probability for the negative recognition group not to be well-prepared for retirement, having low personal financial literacy, and lacking in sufficient wealth. There was a strong probability for the negative recognition group to suffer from health difficulties or lack of pastimes. Based on these findings, this research suggests that retirees should prepare for retirement with a positive attitude.

• Journal of Fashion Business
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• v.20 no.4
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• pp.50-71
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• 2016

This study analyzed the recognition rate of QR codes printed by digital transfer textile printing for mobile application. The purpose was to identify conditions that increase recognition rates of QR codes printed on textile, in order to increase utility of QR codes in the textile and fashion industries. The study focused on differences in the color of the QR codes and denier, which is a unit of textile fineness measurement, of the textile on which the QR codes were printed. And the recognition rates of QR codes according to the color and denier were analyzed. According to the result of this study, the colors of QR codes had an effect on the recognition of the codes by mobile applications. Specifically, strong contrast, i.e., bright background and relatively dark module, increased the recognition rate of the QR codes. Digital transfer textile printing tend to change the hue of red and yellow and increase brightness, and change in the printed colors also had an effect on the recognition rate of QR codes. There was a clear difference in the color and recognition rate of the printed QR code according to the denier of the textile, and this suggests denier has an effect on the recognition rate. The findings in this study can provide basic data for future research on QR codes digital printed on textile.

• Proceedings of the IEEK Conference
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• 2000.11c
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• pp.121-124
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• 2000

In this paper, we propose a pen gesture recognition system for user interface in multimedia terminal which requires fast processing time and high recognition rate. It is realtime and interaction system between graphic and text module. Text editing in recognition system is performed by pen gesture in graphic module or direct editing in text module, and has all 14 editing functions. The pen gesture recognition is performed by searching classification features that extracted from input strokes at pen gesture model. The pen gesture model has been constructed by classification features, ie, cross number, direction change, direction code number, position relation, distance ratio information about defined 15 types. The proposed recognition system has obtained 98% correct recognition rate and 30msec average processing time in a recognition experiment.

• Journal of Multimedia Information System
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• v.6 no.1
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• pp.15-22
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• 2019

There are many ways to perform face recognition. The first step of face recognition is the face detection step. If the face is not found in the first step, the face recognition fails. Face detection research has many difficulties because it can be varied according to face size change, left and right rotation and up and down rotation, side face and front face, facial expression, and light condition. In this study, facial features are extracted and the extracted features are geometrically reconstructed in order to improve face recognition rate in extracted face region. Also, it is aimed to adjust face angle using reconstructed facial feature vector, and to improve recognition rate for each face angle. In the recognition attempt using the result after the geometric reconstruction, both the up and down and the left and right facial angles have improved recognition performance.

• Journal of Korea Multimedia Society
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• v.17 no.5
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• pp.556-565
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• 2014

This paper proposes a method to track object of real-time video transferred through single web-camera and to recognize risk-situation and human actions. The proposed method recognizes human basic actions that human can do in daily life and finds risk-situation such as faint and falling down to classify usual action and risk-situation. The proposed method models the background, obtains the difference image between input image and the modeled background image, extracts human object from input image, tracts object's motion and recognizes human actions. Tracking object uses the moment information of extracting object and the characteristic of object's recognition is moment's change and ratio of object's size between frames. Actions classified are four actions of walking, waling diagonally, sitting down, standing up among the most actions human do in daily life and suddenly falling down is classified into risk-situation. To test the proposed method, we applied it for eight participants from a video of a web-cam, classify human action and recognize risk-situation. The test result showed more than 97 percent recognition rate for each action and 100 percent recognition rate for risk-situation by the proposed method.

• The KIPS Transactions:PartB
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• v.13B no.1 s.104
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• pp.53-62
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• 2006

Object recognition techniques using principal component analysis are disposed to be decreased recognition rate when lighting change of image happens. The purpose of this thesis is to propose an object recognition technique using new PCA analysis method that discriminates an object in database even in the case that the variation of illumination in training images exists. And the object recognition algorithm proposed here represents more enhanced recognition rate using improved k-Nearest Neighbor. In this thesis, we proposed an object recognition algorithm which creates object space by pre-processing and being learned image using histogram equalization and median filter. By spreading histogram of test image using histogram equalization, the effect to change of illumination is reduced. This method is stronger to change of illumination than basic PCA method and normalization, and almost removes effect of illumination, therefore almost maintains constant good recognition rate. And, it compares ingredient projected test image into object space with distance of representative value and recognizes after representative value of each object in model image is made. Each model images is used in recognition unit about some continual input image using improved k-Nearest Neighbor in this thesis because existing method have many errors about distance calculation.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.4
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• pp.343-348
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• 2014

Face recognition system has advanctage to automatically recognize a person without causing repulsion at deteciton process. However, the face recognition system has a drawback to show lower perfomance according to illumination variation unlike the other biometric systems using fingerprint and iris. Therefore, this paper proposed a robust face recogntion method against illumination varition by slective fusion technique using both visible and infrared faces based on fuzzy linear disciment analysis(fuzzy-LDA). In the first step, both the visible image and infrared image are divided into four bands using wavelet transform. In the second step, Euclidean distance is calculated at each subband. In the third step, recognition rate is determined at each subband using the Euclidean distance calculated in the second step. And then, weights are determined by considering the recognition rate of each band. Finally, a fusion face recognition is performed and robust recognition results are obtained.

• Korean Journal of Computational Design and Engineering
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• v.4 no.1
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• pp.43-51
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• 1999

Producing the relevant information (features) from the CAD models of CAM, called feature recognition or extraction, is the essential stage for the integration of CAD and CAM. Most feature recognition methods, however, have problems in the recognition of intersecting features because they do not handle the intersection geometry properly. In this paper, we propose a machining feature recognition algorithm, which has a solid model consisting of orthogonal primitives as input. The algorithm calculates candidate features and constitutes the Intersection Geometry Matrix which is necessary to represent the spatial relation of candidate features. Finally, it recognizes machining features from the proposed candidate features dividing and growing systems using half space and Boolean operation. The algorithm has the following characteristics: Though the geometry of part is complex due to the intersections of design primitives, it can recognize the necessary machining features. In addition, it creates the Maximal Feature Volumes independent of the machining sequences at the feature recognition stage so that it can easily accommodate the change of decision criteria of machining orders.

• Journal of the Korea Safety Management & Science
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• v.8 no.1
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• pp.131-144
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• 2006

Quality system management adapted by small and medium enterprises in Kangwon province to enhance the competitiveness was studied. Variance analysis on several questionnaire answers was performed. Motives for acquiring the accreditation, such as product export, adjustment to international trend, enhancement of brand/product recognition, CEO's mind change, and management innovation, have been changed significantly among business types. Mind changes after the accreditations were setting company's first priority on quality, enhanced recognition on compliance of in-house standards and regulations, employee's performance with the recognition of quality. Amongst service problems to maintain the ace reditations were difficulties in maintaining the recognition of the company's finality management, labor increase to maintain the ISO 9000 enforcement team, and financial burden to keep the accreditation. Quality recognition after the accreditations was significantly improved in setting company's first priority on quality, enhanced recognition on compliance of in-house standards and regulations, employee's performance with the recognition of quality.