• Journal of Digital Convergence
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• v.10 no.10
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• pp.333-338
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• 2012

Human resource management is bringing the various changes with the IT technology. In particular, if HRM is non-scientific method such as group management, physical plant, working hours constraints, personal contacts, etc, the current enterprise human resources management(e-HRM) appeared in the individual dimension management, virtual workspace (for example: smart work center, home work, etc.), working time flexibility and elasticity, computer-based statistical data and the scientific method of analysis and management has been a big difference in the sense. Therefore, depending on changes in the environment, companies have introduced a variety of techniques as RFID card, fingerprint time & attendance systems in order to build more efficient and strategic human resource management system. In this paper, time and attendance, access control management system was developed using multi camera for 2D and 3D face recognition technology-based for efficient enterprise human resource management. We had an issue with existing 2D-style face-recognition technology for lighting and the attitude, and got more than 90% recognition rate against the poor readability. In addition, 3D face recognition has computational complexities, so we could improve hybrid video recognition and the speed using 3D and 2D in parallel.

• The International Journal of Costume Culture
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• v.13 no.2
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• pp.141-153
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• 2010

Fashion needs to be understood as practicality and creative behavior and various movements of paintings act as inspirations of original design for fashion designers. This study seeks to find sources of fashion designs in the works of Mark Rothko who is in the center of color-field abstract. Color-field of Rothko provides infinite inspirations as colors are identically treated as shapes and lighting and textures are all included on top of it. In this study, the purpose is to create color focused artistic fashion design by exploring the possibility of expression with the colors of Rothko as the main motive. The study method is as follows. First, the concept and significance of color-field abstract are researched through documented data. Works of Rothko is divided into three periods according to their characteristics. The background of the formation of color-field abstract of Rothko is understood by analyzing the trends of the works in each period. Second, twenty representative works from 1949 to 1969 are selected and analyzed in formative components of color, shape and textures in order to more accurately understand shape of colors, brilliance, simplicity that appear in the mature color-field abstract of Rothko. Third, preexisting methods of color-field of paintings developed into motives of clothing are studied focusing on the collections from 1997 to 2006. Examples of applications of color-field images in modern fashion designs are analyzed. Fourth, motives are selected based on general characteristics of color-field abstract of Rothko and the results of the formative analysis. Clothing is produced that expresses the colors of the paintings of Rothko more effectively. As the results of the study, restrained shapes and textures and various forms of color combinations shown in color-field abstract of Rothko provided deep inspirations on material composition and color planning for fashion design focused on colors. Additionally, needle-punching technique using wool for the production technique enabled relief texture expressions of materials by colors and effective applications of soft and warm atmosphere of color-field abstract of Rothko on clothing. Especially, the ideology of color-field abstract of Rothko of shaping of colors could be expressed and the direction of the development of motives could be presented at the same time by specifically applying color combination method using horizontal division of atypical color-field from the formative characteristics of color-field abstract of Rothko.

• Korean Journal of Optics and Photonics
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• v.17 no.1
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• pp.47-53
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• 2006

The Integrated Ballistics Identification Systems (IBIS) is widely used for bullet and casing signature identification. The IBIS obtains a pair of ballistic signatures from two bullets (or casings) using optical microscopy, and estimates a correlation score which can represent the degree of signature match. However, this method largely depends on lighting and surface conditions because optical image contrast is primarily a function of test surface's slope, shadowing, multiple reflections, optical properties, and illumination direction. Moreover, it can be affected with surface height variation. To overcome these problems and improve the identification system, we used well known surface topographic techniques, such as confocal microscopy and white-light scanning interferometry. The measuring instruments were calibrated by a NIST step height standard and verified by a NIST sinusoidal profile roughness standard and a commercial roughness standard. We also suggest a new analysis method for the ballistic identification. In this method, the maximum cross-correlation function CCFmax is used to quantify the degree of signature match. If the compared signatures were exactly the same, CCFmax would be $100\%$.

• Design & Manufacturing
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• v.14 no.1
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• pp.8-14
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• 2020

In general, auto parts production assembly line is assembled and produced by automatic mounting by an automated robot. In such a production site, quality problems such as misalignment of parts (doors, trunks, roofs, etc.) to be assembled with the vehicle body or collision between assembly robots and components are often caused. In order to solve such a problem, the quality of parts is manually inspected by using mechanical jig devices outside the automated production line. Automotive inspection technology is the most commonly used field of vision, which includes surface inspection such as mounting hole spacing and defect detection, body panel dents and bends. It is used for guiding, providing location information to the robot controller to adjust the robot's path to improve process productivity and manufacturing flexibility. The most difficult weighing and measuring technology is to calibrate the surface analysis and position and characteristics between parts by storing images of the part to be measured that enters the camera's field of view mounted on the side or top of the part. The problem of the machine vision device applied to the automobile production line is that the lighting conditions inside the factory are severely changed due to various weather changes such as morning-evening, rainy days and sunny days through the exterior window of the assembly production plant. In addition, since the material of the vehicle body parts is a steel sheet, the reflection of light is very severe, which causes a problem in that the quality of the captured image is greatly changed even with a small light change. In this study, the distance between the car body and the door part and the door are acquired by the measuring device combining the laser slit light source and the LED pattern light source. The result is transferred to the joint robot for assembling parts at the optimum position between parts, and the assembly is done at the optimal position by changing the angle and step.

• Journal of Distribution Science
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• v.13 no.5
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• pp.103-111
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• 2015

Purpose - When it comes to first impressions of family restaurants, people basically think of the following factors: cozy, a refreshing space, indoor lighting, atmospheric music, the best-quality service through mutual interactions with employees, birthday events, follow-up customer management, brand image, and many others. Focusing on such family restaurants characteristics, with consumption experience and customer satisfaction determined as mediator variables, this study looks into the selection factors that affect customer loyalty when choosing a family restaurant. Subsequently, the study conducts an empirical analysis of these selection factors with the greatest influence. Research design, data, and methodology - This study analyzed 200 total surveys of family restaurant customers including college students, workers, housewives, and others. The survey was conducted over two weeks in May 2014. For statistical processing, SPSS 21 was used for factor analysis and reliability analysis as well as AMOS for structural equation analysis. In terms of a variable that would influence either consumption experience or customer satisfaction at the restaurants, the study introduced the concept of customer equity. The study designed a model based on a hypothesis developed using the following factors: customer encounter service value, customer convenience value, brand equity, relationship equity, and other factors defined as components of customer equity by Rust et al. (2000) determined as independent variables as well as with customer experience and customer satisfaction set as mediator variables. The hypothesis, after all, assumed that customer loyalty would be positively (+) influenced. Results - The analysis results from the study reported that brand value, customer encounter service value, and relationship value have positive (+) effects on consumption experience and customer satisfaction. However, as for customer convenience value, this turned out not to have a statistically significant influence on consumption experience and customer satisfaction. In regard to a relation between consumption experience and customer satisfaction, the results showed that the former affects the latter, and in terms of intervening variables, both of these appeared to have a positive (+) effect on customer loyalty. Conclusions - This study suggests that family restaurants should look for strategies that focus on how to promote customer relationships. For example, restaurants could try birthday events or discount events to achieve this goal. Since the study ended up realizing relatively low levels of suitability and statistical significance, the path of the study changed. After all, in order to increase suitability and statistical significance, the study had to eliminate factors such as service quality and others and for this reason the study was unable to conduct the analysis as initially planned. In addition, the data samples of the research were mainly gathered from students, which made it hard to say that the analysis was carried out on samples from every different group. Future research should analyze the characteristics of each group of customers for factors affecting customer satisfaction and customer loyalty in the family restaurant chain.

• The Journal of the Korea Contents Association
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• v.17 no.1
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• pp.634-661
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• 2017

This study examines the procedure of successful novel adaptation. It is well known from precedent studies that narrative structure of novels should change forms to suit the media characteristics of films. But, the changing forms of narrative structure is not a sufficient condition of successful novel adaptation, but a necessary condition. A successful adaptation could be completed with filmic expressions on the presented narrative structure. The core of filmic expression is cinematic language which means the composition and array of image and sound. The novel, Kirishma Thing deals with everyday life of high school students and it consists of six stories which are narrated by one student each in first person point of view. The film, Kirishma Thing implemented a different strategy. It reveals the same events several times to show many characters over in each person's point of view in the first half. In the second half, all the characters gathers at the rooftop of the school to have an unilinear narrative structure over one event. This film utilize all kinds of cinematic language to achieve these structures including the widescreen aspect ratio which exposes as many characters as possible in one shot, picture composition which shows the same event in a different point of view, contrast in lighting and music which differentiates and empowers the last sequence of the film.

• Journal of the Korea Society of Computer and Information
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• v.18 no.8
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• pp.65-75
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• 2013

This paper proposes a method of tracking the hand region and detecting the fingertip using only depth images. In order to eliminate the influence of lighting conditions and obtain information quickly and stably, this paper proposes a tracking method that relies only on depth information, as well as a method of using region growing to identify errors that can occur during the tracking process and a method of detecting the fingertip that can be applied for the recognition of various gestures. First, the closest point of approach is identified through the process of transferring the center point in order to locate the tracking point, and the region is grown from that point to detect the hand region and boundary line. Next, the ratio of the invalid boundary, obtained by means of region growing, is used to calculate the validity of the tracking region and thereby judge whether the tracking is normal. If tracking is normal, the contour line is extracted from the detected hand region and the curvature and RANSAC and Convex-Hull are used to detect the fingertip. Lastly, quantitative and qualitative analyses are performed to verify the performance in various situations and prove the efficiency of the proposed algorithm for tracking and detecting the fingertip.

• Journal of the Korea Convergence Society
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• v.10 no.6
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• pp.7-14
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• 2019

In this paper, we propose a Cascade Classifier face detection method using the Haar-like feature, which is complemented by the Flood Fill algorithm for lossy areas due to illumination and shadow in YCbCr color space extraction. The Cascade Classifier using Haar-like features can generate noise and loss regions due to lighting, shadow, etc. because skin color extraction using existing YCbCr color space in image only uses threshold value. In order to solve this problem, noise is removed by erosion and expansion calculation, and the loss region is estimated by using the Flood Fill algorithm to estimate the loss region. A threshold value of the YCbCr color space was further allowed for the estimated area. For the remaining loss area, the color was filled in as the average value of the additional allowed areas among the areas estimated above. We extracted faces using Haar-like Cascade Classifier. The accuracy of the proposed method is improved by about 4% and the detection rate of the proposed method is improved by about 2% than that of the Haar-like Cascade Classifier by using only the YCbCr color space.

• Journal of Platform Technology
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• v.10 no.3
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• pp.60-68
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• 2022

As AI-technology develops, interest in the safety of autonomous driving is increasing. Recently, autonomous vehicles have been increasing, but efforts to solve side effects have been sluggish. In particular, night autonomous vehicles have more problems. This is because the probability of accidents is higher in the night driving environment than in the day environment. There are more factors to consider for self-driving at night. Among these factors, reflection of light or reflected light of lighting may be a fundamental cause of night accidents. Therefore, this study proposes method to reduce accidents and improve safety by reducing reflected light generated by the headlights of opposite vehicles or various surrounding light that appear as an important problem in night autonomous vehicles. Therefore, first, in an image obtained by a sensor of a night autonomous vehicle, illumination reflected light is extracted using reflected light characteristic information, and a color of each pixel using a reflection coefficient is found to reduce a special area generated by geometric characteristics. In addition, we find a new area using only the brightness component of the specular area, define it as Illuminated Reflection Light (IRL), and finally present a method to reduce it. Although the illumination reflection light could not be completely reduce, generally satisfactory results could be obtained. Therefore, it is believed that the proposed study can reduce casualties by solving the problems of night autonomous driving and improving safety.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.3
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• pp.226-235
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• 2023

This study aimed to supplement the shortcomings of the Multiple-sensor-based Frost Observation System (MFOS). The developed frost observation system is an improvement of the existing system. Based on the leaf wetness sensor (LWS), it not only detects frost but also functions to predict surface temperature, which is a major factor in frost occurrence. With the existing observation system, 1) it is difficult to observe ice (frost) formation on the surface when capturing an image of the LWS with an RGB camera because the surface of the sensor reflects most visible light, 2) images captured using the RGB camera before and after sunrise are dark, and 3) the thermal infrared camera only shows the relative high and low temperature. To identify the ice (frost) generated on the surface of the LWS, a LWS that was painted black and three sheets of glass at the same height to be used as an auxiliary tool to check the occurrence of ice (frost) were installed. For RGB camera shooting before and after sunrise, synchronous LED lighting was installed so the power turns on/off according to the camera shooting time. The existing thermal infrared camera, which could only assess the relative temperature (high or low), was improved to extract the temperature value per pixel, and a comparison with the surface temperature sensor installed by the National Institute of Meteorological Sciences (NIMS) was performed to verify its accuracy. As a result of installing and operating the MFOS v2, which reflects these improvements, the accuracy and efficiency of automatic frost observation were demonstrated to be improved, and the usefulness of the data as input data for the frost prediction model was enhanced.