• Journal of Digital Convergence
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• v.13 no.11
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• pp.331-336
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• 2015

The texture mapping used for the low-polygon models is one of the important workflows in the graphical representation of the 3D game. Only one hand painted texture is mapped on the surface of the 3D model and represents the color of the material and visual sense of touching by itself in that process. In the 3D game graphics, it is very important to visualize the textile sensation such as protruding and denting. It can be interpreted by the Gestalt Law to recognize a plane as a 3D sense of volume. Moreover, the concept of Affordance is necessary to recognize and perceive the textile sensation. It means visual recognizing of that relationship in the learning process. In this paper, The questionnaire survey targeting 3D game graphic designers is carried out. By analyzing the survey results, we suggest the important characteristic in the process of making hand painted texture.

• Archives of Plastic Surgery
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• v.44 no.3
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• pp.223-227
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• 2017

Background Carpal tunnel release is one of the most common surgical procedures performed by hand surgeons. The authors created a surgical simulation of open carpal tunnel release utilizing a mobile and rehearsal platform app. This study was performed in order to validate the simulator as an effective training platform for carpal tunnel release. Methods The simulator was evaluated using a number of metrics: construct validity (the ability to identify variability in skill levels), face validity (the perceived ability of the simulator to teach the intended material), content validity (that the simulator was an accurate representation of the intended operation), and acceptability validity (willingness of the desired user group to adopt this method of training). Novices and experts were recruited. Each group was tested, and all participants were assigned an objective score, which served as construct validation. A Likert-scale questionnaire was administered to gauge face, content, and acceptability validity. Results Twenty novices and 10 experts were recruited for this study. The objective performance scores from the expert group were significantly higher than those of the novice group, with surgeons scoring a median of 74% and medical students scoring a median of 45%. The questionnaire responses indicated face, content, and acceptability validation. Conclusions This mobile-based surgical simulation platform provides step-by-step instruction for a variety of surgical procedures. The findings of this study help to demonstrate its utility as a learning tool, as we confirmed construct, face, content, and acceptability validity for carpal tunnel release. This easy-to-use educational tool may help bring surgical education to a new- and highly mobile-level.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.27 no.3
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• pp.5-23
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• 2016

The aim of this study is to analyze the effect and limitation of teacher librarians' self-reported appraisals and suggest it's activation plans about school library based instruction (SLBI). According to results of analyses, the SLBI begin with subject teachers' demand for learning materials and teacher librarians play their educational role in Information search & access and representation & synthesis of information during the instruction. Compared with previous studies, the limitations of SLBI we can see in this study are restricted role of teacher librarians, exclusive attitude and antipathy to classroom opening of subject teachers under the SLBI. The bars of promoting the SLBI are also the difficulty of collaborative working with several same subject teachers and subject classroom system. The ways of activating the SLBI suggested in their self-reported appraisals are building intimacy with subject teachers and participating actively curriculum council, peer-supervision and demonstration classes.

• Journal of The Korean Association For Science Education
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• v.17 no.3
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• pp.313-321
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• 1997

The purpose of this study was to investigate the instructional effect of a four-stage problem solving approach visually emphasizing the molecular level of matter upon students' conceptions and problem solving ability. On the basis of the research results regarding molecular representation in learning chemistry, problem-solving instruction, and the effect of visual materials, the instructional strategy was developed while considering Korean educational situations. The treatment and control groups (2 classes) were selected from a girls' high school in Seoul and taught about stoichiometry, gas, liquid, solid, and solution for 13 weeks. For the treatment group, 52 charts were supplied in order to emphasize the molecular level of matter and/or 4 stage problem solving strategy-understanding, planning, solving, and reviewing. For the control group, traditional instruction was used. Before the instructions, the Group Assessment of Logical Thinking and the Spatial Ability Test were administered, and their scores were used as covariate and blocking variable, respectively. After the instructions, students' conceptions and problem solving ability were measured by the Chemistry Conceptions Test (CCT) and the Chemistry Problem Solving Ability Test (CPSAT), respectively. The results indicated that the CCT scores of the treatment group were significantly higher than those of the control group. The students in the treatment group also exhibited less misconceptions than those in the control group. However, there was not significant difference for the CPSAT scores. No interaction with students' spatial ability was found for both students' conceptions and problem solving ability. Educational implications are discussed.

• Health Policy and Management
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• v.27 no.4
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• pp.336-346
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• 2017

Background: Due to the asymmetry of information and knowledge and the power of bureaucrats and medical professionals, it is not easy for citizens to participate in health care policy making. This study analyzes the case of the insured organization participating in the Health Insurance Policy Committee (HIPC) and provides a basis for discussing methods and conditions for better public participation. Methods: Qualitative analysis was conducted using the in-depth interviews with the participants and document data such as materials for HIPC meetings. Semi-structured interviews were conducted with purposively sampled six participants from organizations representing the insured in HIPC. The meanings related to the factors affecting participation were found and categorized into major categories. Results: The main factors affecting participating in the decision making process were trust and cooperation among the participants, structure and procedure of governance, representation and expertise of participants, and contents of issues. Due to limited cooperation, participants lacked influence in important decisions. There was an imbalance in power due to unreasonable procedures and criteria for governance. As the materials for meetings were provided inappropriate manner, it was difficult for participants to understand the contents and comments on the meeting. Due to weak accountability structure, opinions from external stakeholders have not been well received. The participation was made depending on the expertise of individual members. The degree of influence was different depending on the contents of the issues. Conclusion: In order to meet the values of democracy and realize the participation that the insured can demonstrate influence, it is necessary to have a fair and reasonable procedure and a sufficient learning environment. More deliberative structure which reflects citizen's public perspective is required, rather than current negotiating structure of HIPC.

• Journal of Internet Computing and Services
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• v.21 no.3
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• pp.103-111
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• 2020

Liver cancer is the most fatal cancer that occurs worldwide. In order to diagnose liver cancer, the patient's physical condition was checked by using a CT technique using radiation. Segmentation was needed to diagnose the liver on the patient's abdominal CT scan, which the radiologists had to do manually, which caused tremendous time and human mistakes. In order to automate, researchers attempted segmentation using image segmentation algorithms in computer vision field, but it was still time-consuming because of the interactive based and the setting value. To reduce time and to get more accurate segmentation, researchers have begun to attempt to segment the liver in CT images using CNNs, which show significant performance in various computer vision fields. The pixel value, or numerical value, of the CT image is called the Hounsfield Unit (HU) value, which is a relative representation of the transmittance of radiation, and usually ranges from about -2000 to 2000. In general, deep learning researchers reduce or limit this range and use it for training to remove noise and focus on the target organ. Here, we observed that the range of HU values was limited in many studies but different in various liver segmentation studies, and assumed that performance could vary depending on the HU range. In this paper, we propose the possibility of considering HU value range as a hyper parameter. U-Net and ResUNet were used to compare and experiment with different HU range limit preprocessing of CHAOS dataset under limited conditions. As a result, it was confirmed that the results are different depending on the HU range. This proves that the range limiting the HU value itself can be a hyper parameter, which means that there are HU ranges that can provide optimal performance for various models.

• Journal of Educational Research in Mathematics
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• v.13 no.4
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• pp.463-483
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• 2003

In the learning of mathematics, students experience the semiotic activities of representing and interpreting mathematical signs. We called these activities as the representing and interpreting of mathematical signs. On the foundation of Peirce's three elements of the sign, we analysed that students constructed the representamen to interpret the concept of correlation as for the object, "as one is taller, one's size of foot is larger" 4 middle school students who participated the gifted center in Seoul, arranged the statistical data, constructed their own representamen, and then learned the conventional signs as a result of the whole class discussion. In the process, students performed the detailed representing and interpreting of signs, depended on the templates of the known signs, and interpreted the process voluntarily. As the semiotic activities were taken place in this way, it was needed that mathematics teacher guided the representing and interpreting of mathematical signs so that the representation and the meaning of the sign were constructed each other, and that students endeavored to get the negotiation of the interpretants and the representamens, and to reach the conventional representing.

• Journal of KIISE
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• v.44 no.1
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• pp.51-56
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• 2017

The research area for solving question answering (QA) problems using artificial intelligence models is in a methodological transition period, and one such architecture, the dynamic memory network (DMN), is drawing attention for two key attributes: its attention mechanism defined by neural network operations and its modular architecture imitating cognition processes during QA of human. In this paper, we increased accuracy of the inferred answers, by adapting an automatic data augmentation method for lacking amount of training data, and by improving the ability of time perception. The experimental results showed that in the 1K-bAbI tasks, the modified DMN achieves 89.21% accuracy and passes twelve tasks which is 13.58% higher with passing four more tasks, as compared with one implementation of DMN. Additionally, DMN's word embedding vectors form strong clusters after training. Moreover, the number of episodic passes and that of supporting facts shows direct correlation, which affects the performance significantly.

• Journal of the Korean Society for information Management
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• v.22 no.3 s.57
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• pp.261-287
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• 2005

The purpose of this paper is to explore the ways to improve the performance of SVM (Support Vector Machines) text classifier using inter-document similarities. SVMs are powerful machine learning systems, which are considered as the state-of-the-art technique for automatic document classification. In this paper text categorization via SVMs approach based on feature representation with document vectors is suggested. In this approach, document vectors instead of index terms are used as features, and vector similarities instead of term weights are used as feature values. Experiments show that SVM classifier with document vector features can improve the document classification performance. For the sake of run-time efficiency, two methods are developed: One is to select document vector features, and the other is to use category centroid vector features instead. Experiments on these two methods show that we can get improved performance with small vector feature set than the performance of conventional methods with index term features.

• The Journal of the Korea Contents Association
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• v.9 no.8
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• pp.57-63
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• 2009

Object recognition technologies using PCA(principal component analysis) recognize objects by deciding representative features of objects in the model image, extracting feature vectors from objects in a image and measuring the distance between them and object representation. Given frequent recognition problems associated with the use of point-to-point distance approach, this study adopted the k-nearest neighbor technique(class-to-class) in which a group of object models of the same class is used as recognition unit for the images in-putted on a continual input image. However, the robustness of recognition strategies using PCA depends on several factors, including illumination. When scene constancy is not secured due to varying illumination conditions, the learning performance the feature detector can be compromised, undermining the recognition quality. This paper proposes a new PCA recognition in which database of objects can be detected under different illuminations between input images and the model images.