• The Transactions of the Korea Information Processing Society
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• v.6 no.7
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• pp.1789-1804
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• 1999

This paper presents a simulation-based system for verification and validation(V&V) of design implication of the Visual Real-time Object Model which is produced by existing object's behavior design method. This system can simulate the dynamic interactions using the executable Ada simulation machine, and can detect various logical and temporal problems in the visual real-time object model prior to the real implementation of the application systems. Also, the system can generate the Ada prototype code from the validated specification. This system is implemented by Visual C++ version 4.2. For simulation, this system is using the Ada language because Ada's real-time expression capabilities such as concurrent processes, rendezvous, temporal behavior expression, and etc, are competent compared to other languages. This work contributes to a tightly coupling of methodology-based visual models and formal-based simulation systems, and also contributes to a realization of automated specification V&V.

• Journal of Korean language education
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• v.29 no.3
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• pp.325-344
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• 2018

The purpose of this study is to summarize PWIM (Picture Words Inductive Model) which is one of learner-centered vocabulary teaching-learning models, and suggest ways to implement them in Korean language education. The pictures that are used in the Korean language education field help visualize the specific shape, color, and texture of the vocabulary that is the learning target; thus, helping beginner learners to recognize the meaning of the sound. Visual material stimulates the intrinsic schema of the learner and not only becomes a 'bridge' connecting the mother tongue and the Korean language, but also reduces difficulty in learning a foreign language because of the ambiguity between meaning and sound in Korean and all languages. PWIM shows commonality with existing learning methods in that it uses visual materials. However, in the past, the teacher-centered learning method has only imitated the teacher because the teacher showed a piece-wise, out-of-life photograph and taught the word. PWIM is a learner-centered learning method that stimulates learners to find vocabulary on their own by presenting visual information reflecting the context. In this paper, PWIM is more suitable for beginner learners who are learning specific concrete vocabulary such as personal identity (mainly objects), residence and environment, daily life, shopping, health, climate, and traffic. The purpose of this study was to develop a method of using PWIM suitable for Korean language learners and teaching procedures. The researchers rearranged the previous research into three steps: brainstorming and word organization, generalization of semantic and morphological rules of extracted words, and application of words. In the case of PWIM, you can go through all three steps at once. Otherwise, it is possible to divide the three steps of PWIM and teach at different times. It is expected that teachers and learners using the PWIM teaching-learning method, which uses realistic visual materials, will enable making an effective class together.

• Korean Journal of Computational Design and Engineering
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• v.13 no.1
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• pp.1-7
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• 2008

Data compression becomes increasingly an important issue for reducing data storage spaces as well as transmis-sion time in network environments. In 3D geometric models, the normal vectors of faces or meshes take a major portion of the data so that the compression of the vectors, which involves the trade off between the distortion of the images and compression ratios, plays a key role in reducing the size of the models. So, raising the compression ratio when the normal vector is compressed and minimizing the visual distortion of shape model's shading after compression are important. According to the recent papers, normal vector compression is useful to heighten com-pression ratio and to improve memory efficiency. But, the study about distortion of shading when the normal vector is compressed is rare relatively. In this paper, new normal vector compression method which is clustering normal vectors and assigning Representative Normal Vector (RNV) to each cluster and using the angular deviation from actual normal vector is proposed. And, using this new method, Visually Undistinguishable Lossy Compression (VULC) algorithm which distortion of shape model's shading by angular deviation of normal vector cannot be identified visually has been developed. And, being applied to the complicated shape models, this algorithm gave a good effectiveness.

• Journal of the Korean Data and Information Science Society
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• v.24 no.3
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• pp.593-601
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• 2013

We often need to include categorial variables as explanatory variables in regression models. The categorial variables in regression models can be quantified through dummy variables. In this study, we provide an education tool using Excel VBA for displaying regression lines along with test results for regression models with a continuous explanatory variable and one or two categorical explanatory variables. The regression lines with test results are provided step by step for the model(s) with interaction(s), the model(s) without interaction(s) but with dummy variables, and the model without dummy variable(s). With this tool, we can easily understand the meaning of dummy variables and interaction effect through graphics and further decide which model is more suited to the data on hand.

• Smart Structures and Systems
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• v.30 no.5
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• pp.501-511
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• 2022

Three-dimensional (3D) models have become crucial for improving civil infrastructure analysis, and they can be used for various purposes such as damage detection, risk estimation, resolving potential safety issues, alarm detection, and structural health monitoring. 3D point cloud data is used not only to make visual models but also to analyze the states of structures and to monitor them using semantic data. This study proposes automating the generation of high-quality 3D point cloud data and removing noise using deep learning algorithms. In this study, large-format aerial images of civilian infrastructure, such as cut slopes and dams, which were captured by drones, were used to develop a workflow for automatically generating a 3D point cloud model. Through image cropping, downscaling/upscaling, semantic segmentation, generation of segmentation masks, and implementation of region extraction algorithms, the generation of the point cloud was automated. Compared with the method wherein the point cloud model is generated from raw images, our method could effectively improve the quality of the model, remove noise, and reduce the processing time. The results showed that the size of the 3D point cloud model created using the proposed method was significantly reduced; the number of points was reduced by 20-50%, and distant points were recognized as noise. This method can be applied to the automatic generation of high-quality 3D point cloud models of civil infrastructures using aerial imagery.

• Journal of the Korean Solar Energy Society
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• v.32 no.spc3
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• pp.199-206
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• 2012

The purpose of this study is to understand the change of impression by comparing the uniformity lighting with the compound lighting. In previous study, we proposed a light controlling method to harmonize daylight from a window and artificial lights from a ceiling and obtained the results to support our method. We referred this method as the Adjusted Compound-Lighting Model (AC Model). The experiment is carried out with the scaled-models and mock-up spaces that were supposed to be an office space. One is lit by the uniform lighting and the other by the compound lighting in each experimental space. In order to present varying illuminance distributions, the two variables were used in this study. Subjects were asked to evaluate the point of difference by semantic differential rating on their overall impression after comparing with two rooms. The results showed that the impressions of compound lighting were more positive score than that of uniformity lighting on the items of 'dim-bright', 'dislike-like', 'artificial-natural' and 'closed-open', and that there was no significant difference in impressions between two spaces on other items.

• Korean Journal of Materials Research
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• v.26 no.8
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• pp.412-416
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• 2016

The electrical properties of Au/n-type Ge Schottky contacts with different contact areas were investigated using current-voltage (I-V) measurements. Analyses of the reverse bias current characteristics showed that the Poole-Frenkel effect became strong with decreasing contact area. The contribution of the perimeter current density to the total current density was found to increase with increasing reverse bias voltage. Fitting of the forward bias I-V characteristics by considering various transport models revealed that the tunneling current is dominant in the low forward bias region. The contributions of both the thermionic emission (TE) and the generation-recombination (GR) currents to the total current were similar regardless of the contact area, indicating that these currents mainly flow through the bulk region. In contrast, the contribution of the tunneling current to the total current increased with decreasing contact area. The largest $E_{00}$ value (related to tunneling probability) for the smallest contact area was associated with higher tunneling effect.

• Journal of the Korea Computer Graphics Society
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• v.20 no.4
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• pp.1-7
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• 2014

The volume rendering has become an important technique in many applications along with hardware development. Understanding and perception of volume visualization benefit from visual cues which are available from shading. Better visual cues can be obtained from global illumination models but it's huge amount of computation and extra GPU memory need cause a lack of interactivity. In this paper, in order to improve visual cues on volume rendering, we propose an image space occlusion shading model which requires no additional resources.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2004.11a
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• pp.39-49
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• 2004

When there is a lack of detailed kinetic information, dFBA(dynamic flux balance analysis) has correctly predicted cellular behavior under given environmental conditions with FBA and different ial equations. However, until now, dFBA has centered on substrate concentration, cell growth, and gene on/off, but a detailed hierarchical structure of a regulatory network has not been taken into account. For this reason, the dFBA has limited the represen tation of interactions between specific regulatory proteins and genes and the whole transcriptional regulation mechanism with environmental change. Moreover, to calculate optimal metabolic flux distribution which maximizes the growth flux and predict the b ehavior of cell system, linear programming package(LINDO) and spreadsheet package(EXCEL) have been used simultaneously. thses two software package have limited in the visual representation of simulation results and it can be difficult for a user to look at the effects of changing inputs to the models. Here, we descirbes the construction of hierarchical regulatory network with defined symbolsand the development of an integrated system that can predict the total control mechanism of regulatory elements (opero ns, genes, effectors, etc.), substrate concentration, growth rate, and optimal flux distribution with time. All programming procedures were accoplished in a visual programming environment (LabVIEW).

• Smart Structures and Systems
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• v.13 no.6
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• pp.901-925
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• 2014

The reliability of a Bridge management System depends on the quality of visual inspection and the reliable estimation of bridge condition rating. However, the current practices of visual inspection have been identified with several limitations, such as: they are time-consuming, provide incomplete information, and their reliance on inspectors' experience. To overcome such limitations, this paper presents an approach of automating the prediction of condition rating for bridges based on digital image analysis. The proposed methodology encompasses image acquisition, development of 3D visualization model, image processing, and condition rating model. Under this method, scaling defect in concrete bridge components is considered as a candidate defect and the guidelines in the Ontario Structure Inspection Manual (OSIM) have been adopted for developing and testing the proposed method. The automated algorithms for scaling depth prediction and mapping of condition ratings are based on training of back propagation neural networks. The result of developed models showed better prediction capability of condition rating over the existing methods such as, Naïve Bayes Classifiers and Bagged Decision Tree.