• Korean Journal of Plant Resources
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• v.14 no.3
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• pp.235-240
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• 2001

Polymerase chain reaction (PCR) is used in a wide array of researches in plant molecular genetics and breeding. However, considerable time and cost are still required for the preparation of DNA suitable for reliable PCR results, especially in plant species containing high amounts of polyphenols. To reduce time and effort for PCR-based analysis, a simplified but reliable method was developed by a combinational employment of a simple and fast DNA extraction procedure and BLOTTO (Bovine Lacto Transfer Technique Optimizer) in reaction mixture. Genomic DNAs prepared by one-step extraction method from recalcitrant plant species such as Rubus coreanus, apple, grape and lettuce were successfully amplified by random primers in the reaction mixture containing 2 to 4% BLOTTO. Successful amplification of ${\gamma}$-TMT transgene in lettuce transformants by the specific primers was also achieved in the same condition, making rapid screening of positive transformants possible. Our results suggest that use of a simple DNA extraction procedure and incorporation of BLOTTO in reaction mixture in combination can reduce time and effort required for the analyses of a large number of germplasms and transformants by PCR-based techniques.

• Smart Media Journal
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• v.10 no.2
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• pp.30-37
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• 2021

Recently, 3D contents used in various fields have been attracting people's attention due to the development of virtual reality and augmented reality technology. In order to produce 3D contents, it is necessary to model the objects as vertices. However, high-quality modeling is time-consuming and costly. In order to convert a 2D character into a 3D model, it is necessary to express it as line drawings through feature line extraction. The extraction of consistent line drawings from 2D cartoon cartoons is difficult because the styles and techniques differ depending on the designer who produces them. Therefore, it is necessary to extract the line drawings that show the geometrical characteristics well in 2D cartoon shapes of various styles. This study proposes a method of automatically extracting line drawings. The 2D Cartoon shading image and line drawings are learned by using adversarial network model, which is artificial intelligence technology and outputs 2D cartoon artwork of various styles. Experimental results show the proposed method in this research can be obtained as a result of the line drawings representing the geometric characteristics when a 2D cartoon painting as input.

• Journal of Periodontal and Implant Science
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• v.50 no.6
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• pp.418-434
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• 2020

Purpose: The purpose of the present study was to evaluate the effect of silica-calcium phosphate composite (SCPC) granules on bone regeneration in extraction sockets. Methods: Ten patients were selected for a split-model study. In each patient, bone healing in SCPC-grafted and control ungrafted sockets was analyzed through clinical, radiographic, histomorphometric, and immunohistochemical assessments 6 months postoperatively. Results: A radiographic assessment using cone-beam computed tomography showed minimal ridge dimension changes in SCPC-grafted sockets, with 0.39 mm and 1.79 mm decreases in height and width, respectively. Core bone biopsy samples were obtained 6 months post-extraction during implant placement and analyzed. The average percent areas occupied by mature bone, woven bone, and remnant particles in the SCPC-grafted sockets were 41.3%±12%, 20.1%±9.5%, and 5.3%±4.4%, respectively. The percent areas of mature bone and woven bone formed in the control ungrafted sockets at the same time point were 31%±14% and 24.1%±9.4%, respectively. Histochemical and immunohistochemical analyses showed dense mineralized bundles of type I collagen with high osteopontin expression intensity in the grafted sockets. The newly formed bone was well vascularized, with numerous active osteoblasts, Haversian systems, and osteocytes indicating maturation. In contrast, the new bone in the control ungrafted sockets was immature, rich in type III collagen, and had a low osteocyte density. Conclusions: The resorption of SCPC granules in 6 months was coordinated with better new bone formation than was observed in untreated sockets. SCPC is a resorbable bone graft material that enhances bone formation and maturation through its stimulatory effect on bone cell function.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.3
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• pp.231-241
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• 2019

Web Usage Mining (WUM) is one part of Web mining and also the application of data mining technique. Web mining technology is used to identify and analyze user's access patterns by using web server log data generated by web users when users access web site. So first of all, it is important that the data should be acquired in a reasonable way before applying data mining techniques to discover user access patterns from web log. The main task of data acquisition is to efficiently obtain users' detailed click behavior in the process of users' visiting Web site. This paper mainly focuses on data acquisition stage before the first stage of web usage mining data process with activities like data acquisition strategy and field extraction algorithm. Field extraction algorithm performs the process of separating fields from the single line of the log files, and they are also well used in practical application for a large amount of user data.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.4
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• pp.211-218
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• 2019

The Ministry of Land, Infrastructure and Transport is planning to launch CAS-500 (Compact Advanced Satellite 500) 1 and 2 in 2019 and 2020. Satellite image information collected through CAS-500 can be used in various fields such as global environmental monitoring, topographic map production, analysis for disaster prevention. In order to utilize in various fields like this, it is important to get the location accuracy of the satellite image. In order to establish the precise geometry of the satellite image, it is necessary to establish a precise sensor model using the GCP (Ground Control Point). In order to utilize various fields, step - by - step automation for orthoimage construction is required. To do this, a database of satellite image GCP chip should be structured systematically. Therefore, in this study, we will analyze various techniques for automatic GCP extraction for precise geometry of satellite images.

• Imaging Science in Dentistry
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• v.51 no.2
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• pp.155-165
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• 2021

Purpose: This study aimed to evaluate changes of the alveolar bone and interdental bone septum of the mandibular incisors through cone-beam computed tomography (CBCT) after orthodontic treatment of mandibular dental crowding without dental extraction. Materials and Methods: The sample consisted of 64 CBCT images(32 pre-treatment and 32 post-treatment) from 32 adult patients with class I malocclusion and an average age of 23.0±3.9 years. The width and height of the alveolar bone and interdental septum, the distance between the cementoenamel junction (CEJ) and the facial and lingual bone crests, and the inclination of the mandibular incisors were measured. Results: The distance between the CEJ and the marginal bone crest on the facial side increased significantly (P<0.05). An increased distance between the CEJ and the bone crest on the facial and lingual sides showed a correlation with the irregularity index (P<0.05); however, no significant association was observed with increasing mandibular incisor inclination (P>0.05). The change in the distance between the CEJ and the marginal bone crest on the facial side was correlated significantly with bone septum height(P<0.05). Conclusion: Bone dehiscence developed during the treatment of crowding without extraction only on the incisors' facial side. Increasing proclination of the mandibular incisor was not correlated with bone dehiscence. The degree of dental crowding assessed through the irregularity index was associated with the risk of developing bone dehiscence. The interdental septum reflected facial marginal bone loss in the mandibular incisors.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.685-694
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• 2022

Building information is essential for various urban spatial analyses. For this reason, continuous building monitoring is required, but it is a subject with many practical difficulties. To this end, research is being conducted to extract buildings from satellite images that can be continuously observed over a wide area. Recently, deep learning-based semantic segmentation techniques have been used. In this study, a part of the structure of the context-based ResU-Net was modified, and training was conducted to automatically extract a building from a 30 cm Worldview-3 RGB image using SpaceNet's building v2 free open data. As a result of the classification accuracy evaluation, the f1-score, which was higher than the classification accuracy of the 2nd SpaceNet competition winners. Therefore, if Worldview-3 satellite imagery can be continuously provided, it will be possible to use the building extraction results of this study to generate an automatic model of building around the world.

• Journal of the Korea Institute of Building Construction
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• v.17 no.6
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• pp.545-557
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• 2017

The study is about the efficient alternative to concrete surface in the field of visual inspection technology for deteriorated infrastructure. By combining industrial drones and deep learning based image analysis techniques with traditional visual inspection and research, we tried to reduce manpowers, time requirements and costs, and to overcome the height and dome structures. On board device mounted on drones is consisting of a high resolution camera for detecting cracks of more than 0.3 mm, a lidar sensor and a embeded image processor module. It was mounted on an industrial drones, took sample images of damage from the site specimen through automatic flight navigation. In addition, the damege parts of the site specimen was used to measure not only the width and length of cracks but white rust also, and tried up compare them with the final image analysis detected results. Using the image analysis techniques, the damages of 54ea sample images were analyzed by the segmentation - feature extraction - decision making process, and extracted the analysis parameters using supervised mode of the deep learning platform. The image analysis of newly added non-supervised 60ea image samples was performed based on the extracted parameters. The result presented in 90.5 % of the damage detection rate.

• Journal of Korea Multimedia Society
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• v.10 no.8
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• pp.1068-1077
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• 2007

This paper proposes a method that extracts characteristics of cracks such as length, thickness and direction from a concrete slab surface image with image processing techniques. These techniques extract the cracks from the concrete surface image in variable conditions including bad image conditions) using the ART2-based RBF network to recognize the dominant directions -45 degree, 45 degree, horizontal and vertical) of the extracted cracks from the automatically calculated specifications like the lengths, directions and widths of the cracks. Our proposed extraction algorithms and analysis of the concrete cracks used a Robert operation to emphasize the cracks, and a Multiple operation to increase the difference in brightness between the cracks and background. After these treatments, the cracks can be extracted from the image by using an iterated binarization technique. Noise reduction techniques are used three separate times on this binarized image, and the specifications of the cracks are extracted form this noiseless image. The dominant directions can be recognized by using the ART2-based RBF network. In this method, the ART2 is used between the input layer and the middle layer to learn, and the Delta learning method is used between the middle layer and the output layer. The experiments using real concrete images showed that the cracks were effectively extracted, and the Proposed ART2-based RBF network effectively recognized the directions of the extracted cracks.

• Journal of Industrial Convergence
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• v.21 no.9
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• pp.41-48
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• 2023

Recently, there has been a sharp increase in the damages caused by ransomware across various sectors of society, including individuals, businesses, and nations. Ransomware is a malicious software that infiltrates user computer systems, encrypts important files, and demands a ransom in exchange for restoring access to the files. Due to its diverse and sophisticated attack techniques, ransomware is more challenging to detect than other types of malware, and its impact is significant. Therefore, there is a critical need for accurate detection and mitigation methods. To achieve precise ransomware detection, an inference engine of a detection system must possess knowledge of ransomware features. In this paper, we propose a model to extract and classify the characteristics of ransomware for accurate detection of ransomware, calculate the similarity of the extracted characteristics, reduce the dimension of the characteristics, group the reduced characteristics, and classify the characteristics of ransomware into attack tools, inflow paths, installation files, command and control, executable files, acquisition rights, circumvention techniques, collected information, leakage techniques, and state changes of the target system. The classified characteristics were applied to the existing ransomware to prove the validity of the classification, and later, if the inference engine learned using this classification technique is installed in the detection system, most of the newly emerging and variant ransomware can be detected.