• Journal of Korean Society for Quality Management
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• v.50 no.4
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• pp.843-861
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• 2022

Purpose: This study explores the impact of digital transformation (DT) strategies on gaining a competitive advantage in interactive educational services. Methods: We develop a service value proposition model by analyzing educational service elements to confirm the impact of DT in the classroom through case studies. This study focuses on educational services that DT has a positive impact on organizational competitiveness by providing opportunities for customers to engage in operational processes. This case study summarizes competitiveness using SWOT (strengths, weaknesses, opportunities, and threats) analysis. Results: The findings of the case study indicate that DT-enabled competitive factors contribute to an organization's competitive advantage. The study results present key resource as social cloud services, data combination, content sharing, and products/services. The online application that collects user data about education and shares class and evaluation information creates a new class operational process in the field of educational service for a value proposition of collection-merging-sharing with social cloud function. Conclusion: The results of this study can be used as a good guideline for educational service providers interested in applying DT for improved customer satisfaction and educational organizations' competitiveness. In addition, the study findings provide theoretical and practical implications on SWOT approaches to changing the educational service provision ways through digital transformation.

• Journal of the Korean Society of Visualization
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• v.21 no.1
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• pp.57-66
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• 2023

In this study, we investigate the effects of a single roughness element on Venturi cavitation. The single roughness element of hemispherical shape is installed at the throat inlet of a Venturi tube. Since the wake behind the roughness element induces an additional pressure drop, cavitation inception occurs at a higher Cavitation number for the Venturi model with the single roughness element than for the Venturi model with no roughness. Cavitation bubbles form along the wake of the roughness element and lengthen in the streamwise direction as the Cavitation number decreases, forming a longitudinal cavitation. With a further decrease in the Cavitation number, the longitudinal cavitation bubble merges with the sheet cavitation initiated from the exit edge of the Venturi tube throat, followed by the shedding of cloud cavitation. The merging of the longitudinal cavitation and sheet cavitation is accompanied by a sudden decrease in the discharge coefficient and an increase in the pressure loss coefficient as it chokes the flow inside the Venturi tube.

• Journal of Information Processing Systems
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• v.19 no.4
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• pp.417-426
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• 2023

To improve the effect of image restoration and solve the image detail loss, an image dehazing enhancement algorithm based on mean guided filtering is proposed. The superpixel calculation method is used to pre-segment the original foggy image to obtain different sub-regions. The Ncut algorithm is used to segment the original image, and it outputs the segmented image until there is no more region merging in the image. By means of the mean-guided filtering method, the minimum value is selected as the value of the current pixel point in the local small block of the dark image, and the dark primary color image is obtained, and its transmittance is calculated to obtain the image edge detection result. According to the prior law of dark channel, a classic image dehazing enhancement model is established, and the model is combined with a median filter with low computational complexity to denoise the image in real time and maintain the jump of the mutation area to achieve image dehazing enhancement. The experimental results show that the image dehazing and enhancement effect of the proposed algorithm has obvious advantages, can retain a large amount of image detail information, and the values of information entropy, peak signal-to-noise ratio, and structural similarity are high. The research innovatively combines a variety of methods to achieve image dehazing and improve the quality effect. Through segmentation, filtering, denoising and other operations, the image quality is effectively improved, which provides an important reference for the improvement of image processing technology.

• Geomechanics and Engineering
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• v.15 no.5
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• pp.1101-1111
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• 2018

This study aims to present accurate soil modeling and validation of a single roadside guardrail post as well as a single concrete pile installed near cut slopes or compacted sloping embankment. The conventional Winkler's elastic spring model and p-y curve approach for horizontal ground cannot directly be applied to sloping ground where ultimate soil resistance is significantly dependent on ground inclination. In this study, both grid-based 3-D FE model and particle-based SPH (smoothed particle hydrodynamics) model available in LS-DYNA have been adopted to predict the static behavior of a laterally loaded guardrail post. The SPH model has potential to eliminate any artificial soil stiffness due to the deterioration of the node-connected Lagrangian soil mesh. For this purpose, this study comprises two parts. Firstly, only 3-D FE modeling has been tested to show the numerical validity for a single concrete pile in sloping ground using Mohr-Coulomb material. However, this material option cannot be implemented for SPH elements. Nevertheless, Mohr-Coulomb model has been used since this material model requires six input soil data that can be obtained from the comparative papers in literatures. Secondly, this work is extended to compute the lateral resistance of a guardrail post located near the slope using the hybrid approach that combines Lagrange FE elements and SPH elements by the suitable node-merging option provided by LS-DYNA. For this analysis, the FHWA soil material developed for application to road-base soils has been used and also allows the application of SPH element.

• Journal of The Korean Digital Architecture Interior Association
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• v.5 no.1
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• pp.9-16
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• 2005

In Interior design, light is the most important factor in deciding color, texture and illumination level which are the basic factors of spatial design. To apply rendering technologies on prediction of illuminating effect, it is important to understand and analyse the basic properties of the illumination models that are local illumination model and global illumination model. The illumination models in computer graphics express the factors which determine the surface color, texture and light distribution through the reflection. The purpose of this study is to propose the best way of shading algorithm in interior space provided by the computer, based on the experimental analysis that 5 shading methods are applied to the interior space. The results of this study were as followed. 1) Local illumination models that are Lambert shading, Ground shading and Phong shading are not suitable to the prediction of interior illumination effect. 2) Ray tracing that is global illumination model could be adopted to interior illumination effects. Ray tracing is a very versatile algorithm because of the large range of lighting effects it can model. 3) Neither radiality nor ray tracing offers a complete solution for simulating all interior illumination effects. 4) Radiosity excels at rendering diffuse-to-diffuse inter-reflections and ray tracing excels at rendering specular reflections. By merging both shading techniques, that offers the best of both. Using computer technologies to simulate lighting in preliminary design stage which will provide information for designers and occupants to determine the effect of using artificial light sources at each stage of their design process. Further study in illumination analysis, prediction of illumination effect, and lighting calculation is required as computer media expands.

• Journal of Korean Society for Geospatial Information Science
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• v.15 no.2 s.40
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• pp.3-14
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• 2007

This study proposes an automatic method to generate 3D building models using a draft map, which is an intermediate product generated during the map generation process based on aerial photos. The proposed method is to generate a terrain model, roof models, and wall models sequentially from the limited 3D information extracted from an existing draft map. Based on the planar fitting error of the roof corner points, the roof model is generated as a single planar facet or a multiple planar structure. The first type is derived using a robust estimation method while the second type is constructed through segmentation and merging based on a triangular irregular network. Each edge of this roof model is then projected to the terrain model to create a wall facet. The experimental results from its application to real data indicates that the building models of various shapes in wide areas are successfully generated. The proposed method is evaluated to be an cost and time effective method since it utilizes the existing data.

• Journal of the Korea Society of Computer and Information
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• v.14 no.8
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• pp.25-31
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• 2009

Widely used color information recognition methods based on the RGB color model with static fuzzy inference rules have limitations due to the model itself-the detachment of human vision and applicability of limited environment. In this paper, we propose a method that is based on HSI model with new inference process that resembles human vision recognition process. Also, a user can add, delete, update the inference rules in this system. In our method, we design membership intervals with sine, cosine function in H channel and with functions in trigonometric style in S and I channel. The membership degree is computed via interval merging process. Then, the inference rules are applied to the result in order to infer the color information. Our method is proven to be more intuitive and efficient compared with RGB model in experiment.

• The Korean Journal of Applied Statistics
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• v.28 no.6
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• pp.1275-1288
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• 2015

A microscale weather analysis module (about 1km or less) is a microscale numerical weather prediction model designed for operational forecasting and atmospheric research needs such as radiant energy, thermal energy, and humidity. The accuracy of the module is directly related to the usefulness and quality of real-time microscale weather information service in the metropolitan area. This paper suggests an object based verification method useful for spatio-temporal evaluation of the accuracy of the microscale weather analysis module. The method is a graphical method comprised of three steps that constructs a lattice field of evaluation statistics, merges and identifies objects, and evaluates the accuracy of the module. We develop lattice fields using various evaluation spatio-temporal statistics as well as an efficient object identification algorithm that conducts convolution, masking, and merging operations to the lattice fields. A real data application demonstrates the utility of the verification method.

• Tunnel and Underground Space
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• v.28 no.1
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• pp.111-124
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• 2018

The purpose of this study is to analyze ventilation design factor for network-type double-deck road tunnel that have been developed actively around the world. A numerical analysis was carried out through computational fluid dynamics (CFD) to derive shock loss coefficient that occurs due to the change in cross sectional area at both merging section and diverging section. The model used for the numerical analysis is real-scale model and the reliability of the result is secured by comparing with the coefficient of the previous studies. As a result of this study, shock loss coefficient was calculated depending on the change in cross-sectional area ratio and was higher than the result of previous studies in case of both merging section and diverging section. It is considered that the characteristics of the geometrical structure of network-type double-deck road tunnel have a great impact on shock loss coefficient. Therefore, the result of this study is expected to be helpful for more accurate ventilation design of network-type double-deck road tunnel.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.105-111
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• 2009

Widely used color information recognition methods based on the RGB color model with static fuzzy inference rules have limitations due to the model itself - the detachment of human vision and applicability of limited environment. In this paper, we propose a method that is based on HSI model with new inference process that resembles human vision recognition process. Also, a user can add, delete, update the inference rules in this system. In our method, we design membership intervals with sine, cosine function in H channel and with functions in trigonometric style in S and I channel. The membership degree is computed via interval merging process. Then, the inference rules are applied to the result in order to infer the color information. Our method is proven to be more intuitive and efficient compared with RGB model in experiment.