• Journal of Internet Computing and Services
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• v.11 no.1
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• pp.85-102
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• 2010

In this paper, we propose a novel method of analyzing video and representing the relationship among characters based on their contexts in the video sequences, namely Character-Net. As a huge amount of video contents is generated even in a single day, the searching and summarizing technologies of the contents have also been issued. Thereby, a number of researches have been proposed related to extracting semantic information of video or scenes. Generally stories of video, such as TV serial or commercial movies, are made progress with characters. Accordingly, the relationship between the characters and their contexts should be identified to summarize video. To deal with these issues, we propose Character-Net supporting the extraction of major characters in video. We first identify characters appeared in a group of video shots and subsequently extract the speaker and listeners in the shots. Finally, the characters are represented by a form of a network with graphs presenting the relationship among them. We present empirical experiments to demonstrate Character-Net and evaluate performance of extracting major characters.

• Journal of Korean Tunnelling and Underground Space Association
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• v.11 no.4
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• pp.419-425
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• 2009

Recently, the number of shallow tunnel construction increases to improve the structural safety and environment-friendliness. In Semi-Cut and Cover Method, ground is excavated to the crown arch level and braced rib arch is set to backfill before the excavation of lower face. Semi-Cut and Cover Method is proposed to solve the problems occurred by the conventional Cut and Cover Method, such as unstability, high-cost and the large cutting slope to be reinforced. In this paper, the behaviors of Braced Rib Arch in shallow tunnel excavated by semi-cut and cover method was studied. Model tests in 1:10 Scale were performed in real construction sequences. The distance between supports of rib arch was 1.8 m and the length of spacer was 1.0 m. the size of test pit was 4.0 m (width)$\times$3.3 m (length) 4.0 m (height) in dimension. Tests results show that backfill load acting on arch was smaller than that in the conventional Open-Cut Method.

• Horticultural Science & Technology
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• v.28 no.6
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• pp.1039-1050
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• 2010

Carrot is one of the useful crops used abundantly in cooking in Western as well as Asia regions such as China and Korea. However, seed coats have hairs which should be removed to increase germination rate. Furthermore, because of seed hairs, farmers face several additional losses, such as time consumption, manpower, capital and so on, for seed handling. To prevent these problems, study of gene related hair formation using short-hair seed lines is required. We analyzed genes related to hair formation from seed through expressed sequenced tag (EST) profiling, based on the fact that the development of carrot seed hair is related to cellulose synthesis pathway in secondary cell wall synthesis stage. To study the gene expression related to hair formation of the carrot seed, a cDNA library was constructed by using the early maturation stage of the short-hair line (659-1) and hairy seed line (677-14). In short-hair (659-1) and hairy seed (677-14) lines, results from of EST profiling through BLASTX search analysis using the NCBI database showed that 172 and 224 unigenes had significant homology with known protein sequences, whereas 233 and 192 unigenes were not, respectively. All ESTs were grouped into 16 categories according to their putative functions. Twenty nine unigenes among all ESTs were considered to be genes regulating seed hair development from cellulose synthesis pathway during secondary cell wall synthesis stage; in results, 14 unigenes related to seed hair development were found only in hairy seed line.

• Korean Journal of Environmental Biology
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• v.38 no.1
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• pp.21-29
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• 2020

Morphology of a strain of unspecified Skeletonema species established from Korean coast was examined by light, fluorescence and scanning electron microscopy, and SSU(small subunit) and LSU(large subunit) rDNA of the strain were also sequenced. The specimen was characterized by solitary or short chains, and each cell contained 1-2 chloroplasts. The valve face was slightly convex, and the terminal fultoportula processes (TFPPs) were open and showed narrow distal ends that could be truncated or spiny with claw-like protrusions. The basal part of the TFPPs was tubular and oblique to the cell axis. The intercalary fultoportula processes (IFPPs) were also narrow, completely open, and joined in a 1 : 1 junction. Occasionally, one IFPP was connected with two opposing IFPPs. The morphological features of the specimen were identical to those of Skeletonema pseudocostatum. Molecular phylogeny based on SSU rDNA revealed that the Korean strain is nested within a clade comprising S. pseudocostatum and S. tropicum. However, based on D1-D2 LSU rDNA sequences, a clade including S. pseudocostatum and a Korean strain was separated from the S. tropicum clade. This indicates that the Korean strain can be identified as S. pseudocostatum. This species represents the first record from Korean coastal waters.

• Composites Research
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• v.32 no.5
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• pp.216-221
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• 2019

Piecewise integrated composite (PIC) beam has different stacking sequences for several regions with respect to their superior load-resisting capabilities. On the interest of current research is to improve bending characteristics of PIC beam, with assigning specific stacking sequence to a specific region with the help of machine learning techniques. 240 elements of from the FE model were chosen to be reference points. Preliminary FE analysis revealed triaxialities at those regularly distributed reference points to obtain learning data creation of machine learning. Triaxiality values catagorise the type of loading i.e. tension, compression or shear. Machine learning model was formulated by learning data as well as hyperparameters and proper load fidelity was suggested by tuned values of hyperparameters, however, comparatively higher nonlinearity intensive region, such as side face of the beam showed poor load fidelity. Therefore, irregular distribution of reference points, i.e., dense reference points were distributed in the severe changes of loading, on the contrary, coarse distribution for rare changes of loading, was prepared for machine learning model. FE model with irregularly distributed reference points showed better load fidelity compared to the results from the model with regular distribution of reference points.

• Composites Research
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• v.35 no.5
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• pp.317-321
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• 2022

In this study, the PIC design method with machine learning that automatically assigning different stacking sequences according to loading types was applied bumper beam. The input value and labels of the training data for applying machine learning were defined as coordinates and loading types of reference elements that are part of the total elements, respectively. In order to compare the 2D and 3D implementation method, which are methods of representing coordinate value, training data were generated, and machine learning models were trained with each method. The 2D implementation method is divided FE model into each face and generating learning data and training machine learning models accordingly. The 3D implementation method is training one machine learning model by generating training data from the entire finite element model. The hyperparameter were tuned to optimal values through the Bayesian algorithm, and the k-NN classification method showed the highest prediction rate and AUC-ROC among the tuned models. The 3D implementation method revealed higher performance than the 2D implementation method. The loading type data predicted through the machine learning model were mapped to the finite element model and comparatively verified through FE analysis. It was found that 3D implementation PIC bumper beam was superior to 2D implementation and uni-stacking sequence composite bumper.