• Biomolecules & Therapeutics
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• v.17 no.2
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• pp.138-143
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• 2009

We have reported previously on a replication incompetent recombinant adenoviral vector, AdLPCD, in which the expression of cytosine deaminase gene (CD) is driven by the tumor-specific L-plastin promoter. AdLPCD vector had been evaluated for its efficacy of chemosensitization of ovarian cancer cells to 5-FC. In spite of the fact that ovarian cancer cells, i.e., OVCAR-3 and SK-OV-3, are capable for adenoviral transduction judged by LacZ reporter gene analysis, two cell lines demonstrated quite different sensitivities toward AdLPCD/5-FC system. In OVCAR-3 cells, infection of AdLPCD followed by exposure to 5-FC resulted in the suppression of cell growth with statistical significance. On the other hand, SK-OV-3 cells were more resistant to the CD/5-FC strategy compared with OVCAR-3 cells under the same condition. The object of study was to investigate factors that would determine the sensitivity to AdLPCD/5-FC. We evaluated conversion rate of 5-FC to 5-FU after infection of AdLPCD by HPLC analysis, $IC_{50}$ of 5-FU, the expression level of integrin receptors i.e., ${\alpha}v{\beta}3$ and ${\alpha}v{\beta}5$, and status of p53 in OVCAR-3 and SK-OV-3 cells. The results indicated that OVCAR-3 cells have few favorable features compared with SK-OV-3 cells to be more effective to the AdLPCD/5-FC strategy; higher level of ${\alpha}v{\beta}5$ integrin, higher rate of conversion of 5-FC into 5-FC, and lower $IC_{50}$ of 5-FU. The results suggest that the replacement of 5-FU with CD/5-FC in combination chemotherapy would be less toxic and much greater cytotoxicity than the conventional combination chemotherapy in some patients.

• Journal of Biomedical Engineering Research
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• v.27 no.5
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• pp.224-228
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• 2006

The object of this study is to investigate the potential of dual-electrospun polymer based structure for vascular tissue engineering, especially for the medium or small sue blood vessels. Polyurethane(PU), which is known to be biocompatible in this area, was electrospun with poly(ethylene oxide) (PEO). Concentration of PU was fixed at 20wt%, while that of PEO was set from 15 to 35wt%. Morphological features were observed by SEM image and measurement of porosity and cellular responses were tested before and after extracting PEO from the hybrid scaffolds by immersing the scaffolds into distilled water. The diameter of PEO fibers were ranged from 200nm to 500nm. The lower concentration of PEO tended to show beads. The porosity of the scaffolds after extracting PEO was highly increased with higher concentration of PEO as expected. Also, higher proliferation rate of smooth muscle cells was observed at higher concentration of PEO than at the lower concentration and without PEO. As conclusions, this dual electrospinning technique combined with PU and PEO is expected to overcome the current barrier of cell penetration by providing more space for cells to proliferation.

• Journal of Korea Multimedia Society
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• v.9 no.5
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• pp.624-634
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• 2006

This paper presents a new watermarking scheme that is robust against geometrical attacks such as translation and rotation. The proposed method is based on the conventional PSADT(Polar Coordinates Shape Adaptive Discrete Transform) method which is an robust watermarking scheme for an arbitrarily-shaped image such as character images. The PSADT method shows perfect robustness against geometrical attack if there is no change in the shape of the image object. However, it cannot be utilized to watermark general rectangular images because of the missing alignment between the watermarked signals in the embedding and extracting side. To overcome this problem we propose a new watermarking scheme that aligns the watermark signal using the image inherent feature, especially corner. Namely the proposed method decides a consistent target region whose shape and position isn't changed by any malicious attack and then embeds the watermark in it using the PSADT method. Experimental results show the robustness of the proposed method against geometrical attacks as well as image compression.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.2
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• pp.352-359
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• 2008

RTLS(Real Time Location Systems) is a technology that identifies a location of a target object and provides peat visibility at a work place. Unlike those of the overseas, domestic ports and shipyards have narrow work places and thus, the efficient utilization of these spaces is one of the most important considerations for improving productivity. Companies considering implementation of RTLS should understand its limitations or applicability. In this paper, problems of RTLS such as fading factors which were caused from the features of RF, and limitations caused from the preconditions of RTLS were explained. To overcome those problems, three types of solutions such as movable RTLS, semi-movable RTLS and combined RTLS with other technologies were suggested.

• Korean Journal of Remote Sensing
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• v.24 no.2
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• pp.117-124
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• 2008

This paper introduces a novel approach for automated mapping of a map feature that is vinyl green house in high spatial resolution imagery Some map features have their unique spatial patterns. These patterns are normally detected in high spatial resolution remotely sensed data by human recognition system. When spatial patterns can be applied to map feature identification, it will improve image classification accuracy and will be contributed a lot to feature identification. In this study, an automated feature identification approach using spatial aucorrelation is developed, specifically for the vinyl green house that has distinctive spatial pattern in its array. The algorithm aimed to develop the method without any human intervention such as digitizing. The method can investigate the characteristics of repeated spatial pattern of vinyl green house. The repeated spatial pattern comes from the orderly array of vinyl green house. For this, object-based approaches are essential because the pattern is recognized when the shapes that are consists of the groups of pixels are involved. The experimental result shows very effective vinyl house extraction. The targeted three vinyl green houses were exactly identified in the IKONOS image for a part of Jeju area.

• Korean Journal of Remote Sensing
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• v.35 no.5_1
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• pp.715-726
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• 2019

With the increasing prevalence of high-resolution satellite images, the need for technology to generate accurate 3D information from the satellite images is emphasized. In order to create a digital terrain model (DTM) that is widely used in applications such as change detection and object extraction, it is necessary to extract trees, buildings, etc. that exist in the digital surface model (DSM) and estimate the height of the ground. This paper presents a method for automatically generating DTM from DSM extracted from KOMPSAT-3A stereo images. The technique was developed to detect the non-ground area and estimate the height value of the ground by using the previously constructed low-resolution topographic data. The average vertical accuracy of DTMs generated in the four experimental sites with various topographical characteristics, such as mountainous terrain, densely built area, flat topography, and complex terrain was about 5.8 meters. The proposed technique would be useful to produce high-quality DTMs that represent precise features of the bare-earth's surface.

• Journal of Fashion Business
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• v.23 no.5
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• pp.31-47
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• 2019

This study focuses on women and fashion in Korea between the 1960s and 1970s, when the government regulated the socio-cultural aspects of individuals while achieving remarkable economic industrialization, particularly through the representative popular weekly magazine 'Sunday-Seoul'. The scope of this study included 168 issues from September 22, 1968 to December 26, 1971. Two research methods were applied, literature research and content analysis research. First, the literature on Korean society, culture, women's fashion, the sociological, feminine and popular cultural studies were reviewed. Thereafter, the contents, cover, articles, pictorials were collected and analyzed for classification and identification of the women's images and women's fashion. In the case of fashion articles, the contents of vocabulary and description texts were highlighted, and in the case of pictorials, the visual elements such as images, silhouettes of clothes, details of features, and patterns of materials were assessed. The images of women in Sunday Seoul's articles and pictorials exhibited extreme opposite, presenting the most important purpose of marriage, 'wise mother and good wife' and 'image of sexual object' for men. The two images of women differed; however, there was one more female image 'industrial laborer' which was placed in the blind spot of interest. The characteristics of fashion which appeared in 'Sunday-Seoul' were 'uniform modern elegance' based on neat mini-style, and 'sexual image of exposure fashion' which endeavored to selectively borrow from overseas pictorials and trend-oriented articles. This could be viewed as a 'transformation of traditional Hanbok', 'avant-garde trend' and 'de-sexualization & indifference of fashion'.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2019.10a
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• pp.87-87
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• 2019

The consumption of herbal medicine and related products (herbal products) have increased in South Korea. At the same time the quality, safety, and efficacy of herbal products is being raised. Currently, the herbal products are standardized and controlled according to the requirements of the Korean Pharmacopoeia, the National Institute of Health and the Ministry of Public Health and Social Affairs. The validation of herbal products and their medicinal component is important, since many of these herbal products are composed of two or more medicinal plants. However, there are no tools to support the validation process. Interest in deep learning has exploded over the past decade, for herbal medicine using algorithms to achieve herb recognition, symptom related target prediction, and drug repositioning have been reported. In this study, individual images of four herbs (Panax ginseng C.A. Meyer, Atractylodes macrocephala Koidz, Poria cocos Wolf, Glycyrrhiza uralensis Fischer), actually sold in the market, were achieved. Certain image preprocessing steps such as noise reduction and resize were formatted. After the features are optimized, we applied GoogLeNet_Inception v4 model for herb image recognition. Experimental results show that our method achieved test accuracy of 95%. However, there are two limitations in the current study. Firstly, due to the relatively small data collection (100 images), the training loss is much lower than validation loss which possess overfitting problem. Secondly, herbal products are mostly in a mixture, the applied method cannot be reliable to detect a single herb from a mixture. Thus, further large data collection and improved object detection is needed for better classification.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.11
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• pp.449-456
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• 2019

This paper is a study on the construction of a wall-climbing mobile robot using vacuum suction and wheel-type movement, and a comparison of the performance of an automatic wall crack detection algorithm based on machine learning that is suitable for such an embedded environment. In the embedded system environment, we compared performance by applying recently developed learning methods such as YOLO for object learning, and compared performance with existing edge detection algorithms. Finally, in this study, we selected the optimal machine learning method suitable for the embedded environment and good for extracting the crack features, and compared performance with the existing methods and presented its superiority. In addition, intelligent problem - solving function that transmits the image and location information of the detected crack to the manager device is constructed.

• Journal of Broadcast Engineering
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• v.26 no.4
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• pp.419-428
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• 2021

Shadow removal plays a key role for the pre-processing of image processing techniques such as object tracking and detection. With the advances of image recognition based on deep convolution neural networks, researches for shadow removal have been actively conducted. In this paper, we propose a novel method for shadow removal, which utilizes self attention distillation to extract semantic features. The proposed method gradually refines results of shadow detection, which are extracted from each layer of the proposed network, via top-down distillation. Specifically, the training procedure can be efficiently performed by learning the contextual information for shadow removal without shadow masks. Experimental results on various datasets show the effectiveness of the proposed method for shadow removal under real world environments.