• Journal of Korea Multimedia Society
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• v.13 no.1
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• pp.47-57
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• 2010

The object detection is essential for identifying objects, location information, and user context-aware in the image. In this paper, we propose a robust object detection system. The System linearly transforms learning data obtained from the background images to Principal components. It organizes the Eigen-background with the selected Principal components which are able to discriminate between foreground and background. The Fuzzy-C-means (FCM) carries out clustering for images with inputs from the Eigen-background information and classifies them into objects and backgrounds. It used various patterns of backgrounds as learning data in order to implement a system applicable even to the changing environments, Our system was able to effectively detect partial movements of a human body, as well as to discriminate between objects and backgrounds removing noises and shadows without anyone frame image for fixed background.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.1
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• pp.27-34
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• 2013

Background subtraction is one of the key techniques for automatic video content analysis, especially in the tasks of visual detection and tracking of moving object. In this paper, we present a new sample-based technique for background extraction that provides background image as well as background model. To handle both high-frequency and low-frequency events at the same time, multiple interval background models are adopted. The main innovation concerns the use of a confidence factor to select the best model from the multiple interval background models. To our knowledge, it is the first time that a confidence factor is used for merging several background models in the field of background extraction. Experimental results revealed that our approach based on multiple interval sampling works well in complicated situations containing various speed moving objects with environmental changes.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.1
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• pp.111-121
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• 2011

Intelligent video analysis systems require techniques which can predict accidents and provide alarms to the monitoring personnel. In this paper, we present an abnormal behavior analysis technique based on adaptive background generation. More specifically, abnormal behaviors include fence climbing, abandoned objects, fainting persons, and loitering persons. The proposed video analysis system consists of (i) background generation and (ii) abnormal behavior analysis modules. For robust background generation, the proposed system updates static regions by detecting motion changes at each frame. In addition, noise and shadow removal steps are also were added to improve the accuracy of the object detection. The abnormal behavior analysis module extracts object information, such as centroid, silhouette, size, and trajectory. As the result of the behavior analysis function objects' behavior is configured and analyzed based on the a priori specified scenarios, such as fence climbing, abandoning objects, fainting, and loitering. In the experimental results, the proposed system was able to detect the moving object and analyze the abnormal behavior in complex environments.

• Journal of the Ergonomics Society of Korea
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• v.31 no.5
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• pp.695-704
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• 2012

Objective: The purpose of this study was to investigate major factors influencing adoption of smartphone to promote its use by older adults. Background: Despite increasing proportion of elderly people and elderly market, the proportion of elderly smartphone user is still relatively small compared to whole smartphone users. Thus, we need to find out major factors influencing adoption of smartphone to increase proportion of elderly smartphone users. Method: Seven major factors were extracted from 36 survey questions using factor analysis. Regression analysis was also applied to determine specific factors affecting intention of use based on user versus non-user of smartphone, age, gender, and educational background. Results: As results of factor analysis and regression analysis, major factors influencing adoption of smartphone for elderly users were significantly different according to gender, age, educational background based on smartphone users or non-users. Conclusion: The result of this study identified major factors influencing adoption of smartphone for the elderly and provided basic information related to adoption of smartphone according to elderly people's characteristics. Consequently, we can expect to reduce the information gap and to improve quality of life for the elderly. Application: The development and marketing strategy could be applied differently based on the factors influencing adoption of smartphone. It is also possible to develop a prediction model for smartphone adoption according to elderly users' characteristics.

• Journal of the Korean Magnetic Resonance Society
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• v.17 no.2
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• pp.81-85
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• 2013

Various fluorine-containing materials are used in electronic devices like LCD display panels and Li-ion batteries. The structural conformation of fluorine in fluorinated materials is an important contributing factor that influences the chemical and physical properties. The conformation can be changed by heat and stress during manufacture or use. Understanding the conformational changes is critical for understanding the performance and durability of electronic devices. Solid-state NMR spectroscopy could be widely used for the analysis of various fluorine-containing materials for electronic devices. However, conventional CPMAS probes cannot be used for in-situ analysis of fluorine-containing electronic devices like LCD panels and Li-ion batteries. In this paper, we show the design, construction, and optimization of a $^{19}F-^{13}C$ double-resonance solid-state NMR probe for a 400MHz wide-bore magnet with a flat square coil for in-situ analysis of fluorine-containing electronic devices without observing fluorine background signals. This custom-built probe does not show any fluorine background signals, and can have higher efficiency for lossy samples.

• Journal of Broadcast Engineering
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• v.22 no.6
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• pp.724-733
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• 2017

Conventional methods of automatically recording Go game positions do not properly consider obstacles (hand or object) on a Go board during the Go game. If the Go board is blocked by obstacles, the position of a Go stone may not be correctly recognized, or the sequences of moves may be stored differently from the actual one. In the proposed algorithm, only the complete Go board image without obstacles is stored as a background image and the obstacle is recognized by comparing the background image with the current input image. To eliminate the phenomenon that the shadow is mistaken as obstacles, this paper proposes the new obstacle detection method based on the gradient image instead of the simple differential image. When there is no obstacle on the Go board, the background image is updated. Finally, the successive background images are compared to recognize the position and type of the Go stone. Experimental results show that the proposed algorithm has more than 95% recognition rate in general illumination environment.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.185-189
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• 2004

For face recognition system, a face detector which can find exact face region from complex image is needed. Many face detection algorithms have been developed under the assumption that background of the source image is quite simple . this means that face region occupy more than a quarter of the area of the source image or the background is one-colored. Color-based face detection is fast but can't be applicable to the images of which the background color is similar to face color. And the algorithm using neural network needs so many non-face data for training and doesn't guarantee general performance. In this paper, A multi-scale, multi-face detection algorithm using PCA is suggested. This algorithm can find most multi-scaled faces contained in static images with small number of training data in reasonable time.

• Journal of Mechanical Science and Technology
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• v.17 no.1
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• pp.64-76
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• 2003

In this work, a new penalty formulation is proposed for the analysis of Mindlin-Reissner plates by using the element-free Galerkin method. A penalized weak form for the Mindlin-Reissner Plates is constructed through the exterior penalty method to enforce the essential boundary conditions of rotations as well as transverse displacements. In the numerical examples, some typical problems of Mindlin-Reissner plates are analyzed, and parametric studies on the order of integration and the size of influence domain are also carried out. The effect of the types of background cells on the accuracy of numerical solutions is observed and a proper type of background cell for obtaining optimal accuracy is suggested. Further, optimal order of integration and basis order of Moving Least Squares approximation are suggested to efficiently handle the irregularly distributed nodes through the triangular type of background cells. From the numerical tests, it is identified that unlike the finite element method, the proposed element-free Galerkin method with penalty technique gives highly accurate solution without shear locking in dealing with Mindlin-Reissner plates.

• Journal of Korean Society for Atmospheric Environment
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• v.16 no.4
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• pp.415-420
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• 2000

The daily mean concentrations of PM2.5 mass ionic species carbonaceous species and HNO3, HCl, and NH3 were analyzed at three background sites in Korea : Kangwha, Kosan, and Dongbaik during two intensive field studies between December 1996 and January 1997, Four-day backward trajectory analysis was also carried out. The mean concentrations of anthropogenic species were higher at Kangwha and Dongbaik than Kosan. At these two sites themean concentrations of nitrate and ammonium/ammonia were higher than those of Kosan. It was suggested that these two sites be considered as the background sites of the Seoul Metropolitan Area and Pusan respectively. Major chemical components in fine particles were sulfate organic carbon nitrate and ammonium for all the sites. More than 90% of sulfate were non-sea-salt(nss) sulfates and most of the nss sulfate in PM2.5 might be present as ammonium sulfates at all sites. Most of air parcels arriving a Kangwha and Dongbaik were from the northern China. At Kosan during the measurement period half of air parcels were from the northern China and the other half from the southern China. At Kosan the concentrations of anthropogenic air pollutants originated from the southern China were higher than those typically observed from the northern China.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.1
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• pp.47-58
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• 2019

The purpose of this paper is to examine the relationship between the nature of controlling shareholders and corporate anti-corruption practice disclosure (ACPD) as well as the mediating role of political background of the chairman or CEO of the firm on the relationship between the two. The content analysis was conducted to extract ACPD from standalone corporate social responsibility reports (CSRR) of 703 China's A-share listed companies. A dummy variable was constructed according to whether a firm disclosed ACPD or not. Logistic regression analysis was used then. Results show that the nature of controlling shareholders has a significant impact on corporate ACPD, with central enterprises disclosing the most frequently, local state-owned enterprises the second and private enterprises the least. Political background of the chairman or CEO has a negative impact on corporate ACPD of state-owned enterprises. These findings have some useful insights in understanding the rent-seeking behavior and information disclosure behavior of corporates in emerging markets. In order to curb the serious corruption problem which is commonplace in developing countries like China, the government should exert certain pressure to strengthen the supervision of information disclosure of listed firms and improve information transparency.