• Journal of Computing Science and Engineering
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• v.6 no.4
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• pp.243-256
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• 2012

In this paper we present a framework for a novel kind of context-aware preference query composition whereby queries for the Preference SQL system are created. We choose a commercial e-business platform for outdoor activities as a use case and develop a context model for this domain within our framework. The suggested model considers explicit user input, domain-specific knowledge, contextual knowledge and location-based sensor data in a comprehensive approach. Aside from the theoretical background of preferences, the optimization of preference queries and our novel generator based model we give special attention to the aspects of the implementation and the practical experiences. We provide a sketch of the implementation and summarize our user studies which have been done in a joint project with an industrial partner.

• Journal of Fashion Business
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• v.7 no.5
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• pp.1-12
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• 2003

In this study I surveyed the dress and the color symbolism of Scarlett and Melanie in the movie "Gone with the Wind" based on the novel by Margaret Mitchell. In investigating the dress and the color symbolism, I analyzed Scarlett and Melanie's image as described in the novel, and examined how the symbolic imagery is represented through coloration based on the DVD reproduction of the movie "Gone with the Wind" originally produced in 1939. In her novel, the author Margaret Mitchell introduced two women, Scarlett and Melanie, whose respective image sharply contrasts with each other. To express Scarlett's young, vigorous, lusty, and vivacious image, she uses green to depict the character, clothing, and background on the whole. Black, which mainly expresses the death image of the mourning dress. Red symbolizes her fast and lavish image. On the other hand, gray is used to describe Melanie's sedate, shyness, and modest image while alluding to her gloomy atmosphere. Brown symbolizes her sedate and plain image in the novel. In the movie, green symbolizes Scarlett's overwhelming image of youth and liveliness as also depicted in the novel. Melanie, however, seems to appear consistently in gray-blue or purple dresses to reflect her image of modesty, sedation and dignity. Melanie's blue image contrasts with Scarlett's blue image in that the latter is used to hint at the omen to a tragedy to come. Red is used to express Scarlett's passionate and fast image. Black symbolizes death or mourning in the movie.

• Clinical Endoscopy
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• v.57 no.4
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• pp.527-533
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• 2024

Background/Aims: Endoscopic ultrasound (EUS)-guided hepaticogastrostomy (EUS-HGS) performed at the intrahepatic bile duct segment 3 (B3) is widely used for biliary drainage. Although performing post-puncture procedures is easier in the intrahepatic bile duct segment 2 (B2) when using a conventional oblique-viewing (OV) EUS scope, this method may cause transesophageal puncture and severe adverse events. We evaluated the safety and efficacy of B2 puncture using a novel OV-EUS scope. Methods: In this single-center retrospective study, we prospectively enrolled and collected data from 45 patients who consecutively underwent EUS-HGS procedures with a novel OV-EUS scope between September 2021 and December 2022 at our cancer center. Results: The technical success rates of B2-EUS-HGS and EUS-HGS were 93.3% (42/45) and 97.8% (44/45), respectively. The early adverse event rate was 8.9% (4/45) with no cases of scope changes or transesophageal punctures. The median procedure time was 13 minutes (range, 5-30). Conclusions: B2-EUS-HGS can be performed safely with the novel EG-740UT (Fujifilm) OV-scope without transesophageal puncture and with a high success rate. B2-EUS-HGS using this novel OV scope may be the preferred strategy for EUS-HGS.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.34-36
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• 2009

This paper proposes an effective lane detection algorithm using hugh transform and lane model. The proposed lane detection algorithm includes two major components, i.e., lane marks segmentation and an exact lane extraction using a novel postprocessing technique. The first step is to segment lane marks from background images using HSV color model. Then, a novel postprocessing is used to detect an exact lane using Hugh transform and lane models(linear and curved lane models). The postprocessing consists of three parts, i.e, thinning process, Hugh Transform and filtering process. We divide input image into three regions of interests(ROIs). Based on lane curve function(LCF), we can detect an exact lane from various extracted lane lines. The lane models(linear and curved lane mode]) are used in order to judge whether each lane segment is fit or not in each ROIs. Experimental results show that the proposed scheme is very effective in lane detection.

• Journal of Ginseng Research
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• v.48 no.1
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• pp.98-102
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• 2024

Background: Ginseng (Panax ginseng Meyer) is a perennial plant belonging to the Araliaceae family that is known to have various beneficial effects including improving memory loss and spatial cognitive ability, and anti-cancer and anti-diabetes activity. Its functional benefits also include improving liver function, regulating blood pressure, stress, and providing antioxidant activity. Usually, various agrochemicals are used in cultivating ginseng preventing from many diseases. Methods: FCGP (field cultivated ginseng in pot) was implemented by imitating MCWG (mountain cultivated wild ginseng). Pesticide analysis of pot cultivation was carried out and the contents of bioactive components such as ginsenoside were also analyzed. Results: FCGP ginsenoside content was higher than that of FCG (field cultivated ginseng) and MCWG. FCGP has been shown to have a relatively high antioxidant effect compared with cultivated ginseng. Conclusion: It was confirmed that ginseng can be grown for 6 years without resorting to use of pesticides. In addition, it was confirmed that effective accumulation of physiologically active ingredients such as ginsenoside is possible. Our result represents FCGP is a novel method of pesticide-free ginseng cultivation

• Journal of Information Processing Systems
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• v.10 no.1
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• pp.55-68
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• 2014

Automatic segmentation of foreground text from the background in degraded document images is very much essential for the smooth reading of the document content and recognition tasks by machine. In this paper, we present a novel approach to the binarization of degraded document images. The proposed method uses a new local contrast feature extracted based on the stroke width of text. First, a pre-processing method is carried out for noise removal. Text boundary detection is then performed on the image constructed from the contrast feature. Then local estimation follows to extract text from the background. Finally, a refinement procedure is applied to the binarized image as a post-processing step to improve the quality of the final results. Experiments and comparisons of extracting text from degraded handwriting and machine-printed document image against some well-known binarization algorithms demonstrate the effectiveness of the proposed method.

• Journal of Microbiology and Biotechnology
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• v.16 no.5
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• pp.771-777
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• 2006

A novel gene (agiA) required for adventurous gliding motility in Myxococcus xanthus has been identified. Null mutations in this gene caused defects in the gliding movement of isolated cells, suggesting that it belongs to one of the A-motility genes. The isolated agiA mutant cells neither glided nor produced slime trails on agar surface. However, agiA was different from other known A-motility genes in that the agiA mutant created in the $S^-$ mutant background glided in the swarm of cells, since other known A-motility mutants created in the $S^-$ mutant background do not move in the swarm of cells. The agiA mutant was also defective in fruiting body development. Sequence analysis predicted that agiA encodes a 787-amino-acid protein with eight tripeptide repeat motifs.

• Journal of Electrical Engineering and Technology
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• v.11 no.1
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• pp.234-240
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• 2016

We propose a novel framework for markerless camera-based games. By using a visual camera, our method may yield robust human body segmentation with high performance comparable to the segmentation using depth cameras. The edges of human bodies are detected by subtracting gradient backgrounds, and human body regions are segmented by the operations based on mathematical morphology. Collisions between detected regions and virtual objects are determined by finding the colliding time using intra-frame positions of virtual objects. Experimental results show that the proposed method may produce robust segmentation of human bodies, thereby and the collision responses are more accurate than previous methods. Therefore, the proposed framework can be widely used in camera-based games requiring high performance.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.408-410
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• 2009

We present an efficient and robust measurement model for visual tracking. This approach builds on and extends work on subspace representations of measurement model. Subspace-based tracking algorithms have been introduced to visual tracking literature for a decade and show considerable tracking performance due to its robustness in matching. However the measures used in their measurement models are often restricted to few approaches. We propose a novel measure of object matching using Angle In Feature Space, which aims to improve the discriminability of matching in subspace. Therefore, our tracking algorithm can distinguish target from similar background clutters which often cause erroneous drift by conventional Distance From Feature Space measure. Experiments demonstrate the effectiveness of the proposed tracking algorithm under severe cluttered background.

• Journal of Korea Multimedia Society
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• v.17 no.4
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• pp.420-432
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• 2014

In detection of moving objects from video sequences, an essential process for intelligent visual surveillance, the cast shadows accompanying moving objects are different from background so that they may be easily extracted as foreground object blobs, which causes errors in localization, segmentation, tracking and classification of objects. Most of the previous research results about moving cast shadow detection and removal usually utilize color information about objects and scenes. In this paper, we proposes a novel cast shadow removal method of moving objects in gray level video data for visual surveillance application. The proposed method utilizes observations about edge patterns in the shadow region in the current frame and the corresponding region in the background scene, and applies Laplacian edge detector to the blob regions in the current frame and the corresponding regions in the background scene. Then, the product of the outcomes of application determines moving object blob pixels from the blob pixels in the foreground mask. The minimal rectangle regions containing all blob pixles classified as moving object pixels are extracted. The proposed method is simple but turns out practically very effective for Adative Gaussian Mixture Model-based object detection of intelligent visual surveillance applications, which is verified through experiments.