• Journal of Korean Society of Transportation
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• v.21 no.2
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• pp.63-70
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• 2003

Real-time information on vehicle queue at intersections is essential for optimal traffic signal control, which is substantial part of Intelligent Transport Systems (ITS). Computer vision is also potentially an important element in the foundation of integrated traffic surveillance and control systems. The objective of this research is to propose a method for detecting an exact queue lengths at signalized intersections using image processing techniques and a neural network model Fuzzy ARTMAP, which is a supervised and self-organizing system and claimed to be more powerful than many expert systems, genetic algorithms. and other neural network models like Backpropagation, is used for recognizing different patterns that come from complicated real scenes of a car park. The experiments have been done with the traffic scene images at intersections and the results show that the method proposed in the paper could be efficient for the noise, shadow, partial occlusion and perspective problems which are inevitable in the real world images.

• Journal of the Korean Society of Food Culture
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• v.23 no.1
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• pp.130-137
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• 2008

If we may practice the nutrition education planned on the basis which carefully grasped the inappropriate behavioral determinants of middle-school students, it might be an effective method achieving the change in perception and behavior improving the distorted perception about the ideal body shape, so we are to suggest the 8 week program of body shape perception improvement for successful nutrition education as follows. The body shape perception improvement program is a step-by-step group consulting program. At the introduction stage, we let them understand the meaning of true beauty and body change of teenage period and forming of sexual identity. At the stage of perception conversion, we let them have the opportunity to observe the status of body perception of the teenager and self-observation. At the stage of correction, we let them criticize the distorted body image in the society with mass media at the same time with the self-reflection. At the stage of maintenance and evaluation, we suggested the behavior guidance while preparing it. Setting this as the basis, we applied the contents such as the evaluations through cultural sharing events making somethings while directly participating. As the target groups to practice education were middle school students, we considered the learning level and behavioral features of the middle school students, and composed the programs including the methods such as role play, watching real things, media production, discussions and experiences. If the program of body shape perception improvement developed at this study could be utilized at the field of schools, the teenagers can change their ways of thought naturally avoiding the view about unified appearance rightly perceiving negative self-image that the teenagers can have and if the group consulting can be practiced regularly at each school, many students may experience the change in perception, so it might solicit the improvement of health of the families and local societies as well as that of the individual student.

• Journal of the Korea Society of Computer and Information
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• v.27 no.11
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• pp.181-190
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• 2022

In this paper, we use a LiDAR sensor and an image camera to detect a left-turning waiting vehicle in two ways, unlike the existing image-type or loop-type left-turn detection system, and a left-turn traffic signal corresponding to the waiting length of the left-turning lane. A system that can efficiently assign a system is introduced. For the LiDAR signal transmitted and received by the LiDAR sensor, the left-turn waiting vehicle is detected in real time, and the image by the video camera is analyzed in real time or at regular intervals, thereby reducing unnecessary computational processing and enabling real-time sensitive processing. As a result of performing a performance test for 5 hours every day for one week with an intersection simulation using an actual signal processor, a detection rate of 99.9%, which was improved by 3% to 5% compared to the existing method, was recorded. The advantage is that 99.9% of vehicles waiting to turn left are detected by the LiDAR sensor, and even if an intentional omission of detection occurs, an immediate response is possible through self-correction using the video, so the excessive waiting time of vehicles waiting to turn left is controlled by all lanes in the intersection. was able to guide the flow of traffic smoothly. In addition, when applied to an intersection in the outskirts of which left-turning vehicles are rare, service reliability and efficiency can be improved by reducing unnecessary signal costs.

• Journal of the East Asian Society of Dietary Life
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• v.20 no.5
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• pp.639-654
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• 2010

This study attempted to research the local food of various regions at a personal level by discovering how food has developed das part of a region's culture base. Discovery of the characteristic story behind the making of a region's characteristic food as local delicacies can inspire self-esteem in the culture, and enhance the real-life image as appropriate to a region, and thereby be made a part of local tourism and thus contributing to the local economy. For this reason, the native foods of the region of Chungcheongnam-do were researched in terms of the cultural sensibilities that inform the unique history of that region. The study was designed so as to aid in understanding food's characteristic value in Chungcheongnam-do and to give a historical representation of Chungcheongnam-do's image by means of storytelling techniques; thus, the local food's character can be presented alongside a story that appeals to the five senses. For this purpose, Chungcheongnam-do's representative native rice table was cast as the 'Hyunchoong rice meal table' - after the figure of admiral Yi Sun Shin of Asan area region, a representative image of Chungcheongnam-do - and 'Choosa rice meal table', after the figure of 'Choosa' Kim Jeong Hee of Yesan region, of which various literary works form a representative image of Chungcheongnam-do. 'Hyunchoong rice meal table' was composed of a health food centered menu which could supply sufficient nutrition as a food ration in times of war or winter shortage, thus providing an image of nutrition and power as appropriate to these situations. Also, to assess the health effectiveness of each rice table, the functionality of the ingredients were investigated as reported in 'Sik-ryo-chan-yo : a dietary treatment' which was published by Soon-Ui Cheon in the Chosun era and by which the foods of the early Chosun era won recognition as being both healthy profitable.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.8
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• pp.1553-1559
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• 2017

This paper proposes a lane departure detection algorithm using a single camera equipped in front of a vehicle. The proposed algorithm generates a partial top-view image for a small ROI (region of interest) designated on the top-view space form the image acquired by the camera, detects lanes on the small partial top-view image, and makes a decision on the lane departure by checking overlap between the pre-assigned virtual vehicle and the detected lanes. The proposed algorithm also includes the removal of lines occurred by road symbols (noises) disturbing the lane departure detection between lanes and the prediction of lost lanes using lane information of previous fames. In lane departure detection test using real road videos, the proposed algorithm makes the right decision of 99.0% in lane keeping conditions and 94.7% in lane departure conditions.

• Journal of Advanced Research in Ocean Engineering
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• v.3 no.3
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• pp.136-148
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• 2017

The paper presents dual arm ROV manipulation using deep reinforcement learning. The purpose of this underwater manipulator is to investigate and excavate natural resources in ocean, finding lost aircraft blackboxes and for performing other extremely dangerous tasks without endangering humans. This research work emphasizes on a self-learning approach using Deep Reinforcement Learning (DRL). DRL technique allows ROV to learn the policy of performing manipulation task directly, from raw image data. Our proposed architecture maps the visual inputs (images) to control actions (output) and get reward after each action, which allows an agent to learn manipulation skill through trial and error method. We have trained our network in simulation. The raw images and rewards are directly provided by our simple Lua simulator. Our simulator achieve accuracy by considering underwater dynamic environmental conditions. Major goal of this research is to provide a smart self-learning way to achieve manipulation in highly dynamic underwater environment. The results showed that a dual robotic arm trained for a 3DOF movement successfully achieved target reaching task in a 2D space by considering real environmental factor.

• Journal of Korea Multimedia Society
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• v.18 no.3
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• pp.312-322
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• 2015

In this paper a new defect detection method for flat panel display that does not require any separately prepared reference images and shows robustness against problems with regard to pixel tolerance and nonuniform illumination condition is proposed. In order to perform defect detection under any magnification value of camera, the proposed method automatically obtains the value of pattern interval through an image analysis. Using the information for pattern interval, an advanced PCSR-G method presented in this paper utilizes neighboring patterns as its reference images instead of utilizing any separately prepared reference images. Also this paper proposes a scheme to improve the performance of the conventional PCSR-G method by extracting and applying additional information for pixel tolerance and intensity distribution considering the value of pattern interval. Simulation results show that the performance of the proposed method utilizing pixel tolerance and intensity distribution is superior to that of the conventional method. Also, it is proved that the proposed method that is implemented using parallel technique based on GPGPU can be applied to real system.

• Fashion & Textile Research Journal
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• v.16 no.5
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• pp.689-697
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• 2014

This study aims to analyze the representation forms of bloggers' personal style on the fashion blogs and enlighten their values which can be actively applied to design and marketing in fashion industry. Image representation of fashion bloggers is reflected by the characteristics in the digital environment, which are the creative manipulation of expression and the production of virtual and fantastic images by taking advantage of the composite medium such as images, music, videos, articles, etc. Also real time updates in blog indicate the latest trends in terms of the representation of image as the actual currency. The study conducted case studies of 5 women's personal fashion blogs through the verification of a variety of global fashion media and blog ranking sites: Style Bubble, Style Rookie, The Cherry Blossom Girl, The Blond Salad, and Fashion Toast. Research findings are as follows. First, the application of creative design elements is indicated as symbolic items, self-made designs, DIY, and various mix and match emphasizing design elements such as color, patterns, proportion, etc. Second, the virtual representation is very highlighted on the story telling applied by film like production or digital effect. Third, the commercial application with mainly sponsored wardrobe and designer collaboration indicates promoting a updated trend as well as a specific brand or designer to make their business profits.

• Journal of the Korean Electrochemical Society
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• v.3 no.2
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• pp.104-108
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• 2000

It is very important to know the real roughness of electrode surface in electrochemistry. But it is impossible to know absolute roughness of electrode surface for various reasons. In this work, we compared the roughnesses of polycrystalline gold electrode often used in electrochemistry calculated from the images of scanning tunneling microscopy (STM) and cyclic voltammetry with those of Au (111) and HOPG. The roughness of polycrystalline gold calculated from STM image was $1.1(\pm0.1)$, that from adsorption-desorption of oxygen was $2.4(\pm0.7)$ and that from adsorption of N-docosyl-N'-methyl viologen was $1.6(\pm0.1)$.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.2
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• pp.101-106
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• 2010

We propose an approach to estimate the real-time moving trajectory of an object in this paper. The object's position is obtained from the image data of a CCD camera, while a state estimator predicts the linear and angular velocities of the moving object. To overcome the uncertainties and noises residing in the input data, a Extended Kalman Filter(EKF) and neural networks are utilized cooperatively. Since the EKF needs to approximate a nonlinear system into a linear model in order to estimate the states, there still exist errors as well as uncertainties. To resolve this problem, in this approach the Kohonen networks, which have a high adaptability to the memory of the inputoutput relationship, are utilized for the nonlinear region. In addition to this, the Kohonen network, as a sort of neural network, can effectively adapt to the dynamic variations and become robust against noises. This approach is derived from the observation that the Kohonen network is a type of self-organized map and is spatially oriented, which makes it suitable for determining the trajectories of moving objects. The superiority of the proposed algorithm compared with the EKF is demonstrated through real experiments.