• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.979-986
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• 2022

In this study, the virtual exhibition using 3D architectural space was analyzed in terms of the viewer's experience. For this purpose, the analysis items of the virtual architectural space include whether the actual architectural space is reproduced, the introduction of surreal elements, the degree of freedom of movement and circulation, the level of photorealism of spatial expression, the level of reproduction of the exhibits and information provision method, and the interaction with other participants. Six virtual exhibition projects designed by a well-known architect were selected and analyzed. Three directions were found through the analysis. First, even when designing a virtual exhibition space with a high degree of freedom, there is a tendency to present a familiar architectural environment. Second, the current method of creating a virtual architectural space is that the method using a 360-degree rendering image and the method using a game engine coexist with pros and cons. Third, the interaction between participants in the virtual exhibition is implemented only by using a game engine. It is expected that the virtual space production environment using the game engine to be developed will become more advantageous in the future.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.2
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• pp.48-55
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• 2022

The color image of the brand comes first and is an important visual element that leads consumers to the consumption of the product. To express more effectively what the brand wants to convey through design, the printing market is striving to print accurate colors that match the intention. In 'offset printing' mainly used in printing, colors are often printed in CMYK (Cyan, Magenta, Yellow, Key) colors. However, it is possible to print more accurate colors by making ink of the desired color instead of dotting CMYK colors. The resulting ink is called 'spot color' ink. Spot color ink is manufactured by repeating the process of mixing the existing inks. In this repetition of trial and error, the manufacturing cost of ink increases, resulting in economic loss, and environmental pollution is caused by wasted inks. In this study, a deep learning algorithm to predict printed spot colors was designed to solve this problem. The algorithm uses a single DNN (Deep Neural Network) model to predict printed spot colors based on the information of the paper and the proportions of inks to mix. More than 8,000 spot color ink data were used for learning, and all color was quantified by dividing the visible light wavelength range into 31 sections and the reflectance for each section. The proposed algorithm predicted more than 80% of spot color inks as very similar colors. The average value of the calculated difference between the actual color and the predicted color through 'Delta E' provided by CIE is 5.29. It is known that when Delta E is less than 10, it is difficult to distinguish the difference in printed color with the naked eye. The algorithm of this study has a more accurate prediction ability than previous studies, and it can be added flexibly even when new inks are added. This can be usefully used in real industrial sites, and it will reduce the attempts of the operator by checking the color of ink in a virtual environment. This will reduce the manufacturing cost of spot color inks and lead to improved working conditions for workers. In addition, it is expected to contribute to solving the environmental pollution problem by reducing unnecessarily wasted ink.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.spc
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• pp.1-10
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• 2022

As the volume of marine hazardous and noxious substances (HNSs) transported in domestic and overseas seas increases, the risk of HNS spill accidents is gradually increasing. HNS leaked into the sea causes destruction of marine ecosystems, pollution of the marine environment, and human casualties. Secondary accidents accompanied by fire and explosion are possible. Therefore, various types of HNSs must be rapidly detected, and a control strategy suitable for the characteristics of each substance must be established. In this study, the ground HNS spill experiment process and application result of detection algorithms were presented based on hyperspectral remote sensing. For this, styrene was spilled in an outdoor pool in Brest, France, and simultaneous observation was performed through a hyperspectral sensor. Pure styrene and seawater spectra were extracted by applying principal component analysis (PCA) and the N-Findr method. In addition, pixels in hyperspectral image were classified with styrene and seawater by applying spectral matching techniques such as spectral distance similarity (SDS), spectral correlation similarity (SCS), spectral similarity value (SSV), and spectral angle mapper (SAM). As a result, the SDS and SSV techniques showed good styrene detection results, and the total extent of styrene was estimated to be approximately 1.03 m². The study is expected to play a major role in marine HNS monitoring.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.2
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• pp.249-256
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• 2022

Various studies are being actively conducted to show that the real-time visualization technology that combines BIM (Building Information Modeling) and AR (Augmented Reality) helps to increase construction management decision-making and processing efficiency. However, when large-capacity BIM data is projected into AR, there are various limitations such as data transmission and connection problems and the image cut-off issue. To improve the high efficiency of visualizing, a mesh optimization algorithm based on the k-nearest neighbors (KNN) classification framework to reconstruct BIM data is proposed in place of existing mesh optimization methods that are complicated and cannot adequately handle meshes with numerous boundaries of the 3D models. In the proposed algorithm, our target BIM model is optimized with the Unity C# code based on triangle centroid concepts and classified using the KNN. As a result, the algorithm can check the number of mesh vertices and triangles before and after optimization of the entire model and each structure. In addition, it is able to optimize the mesh vertices of the original model by approximately 56 % and the triangles by about 42 %. Moreover, compared to the original model, the optimized model shows no visual differences in the model elements and information, meaning that high-performance visualization can be expected when using AR devices.

• Journal of the Korean Society of Floral Art and Design
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• no.41
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• pp.93-114
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• 2019

The purpose of this study is to analyze the characteristics and problems of the content of flower design education videos on YouTube and to search for improvement direction. The subjects of analysis were 129 pieces of videos uploaded in the last one year including 'craftman floral design' as a search term. The result shows that contents covered were practical lectures, theory lectures, test related tips, job and character introduction, test work, educational guidance and publicity. The production format could be divided into studio lecture, classroom lecture, video feature, interview, Vlog, and television program. The hub-type programming strategy that periodically uploads the videos satisfying the target audiences' interests is mostly applied. The type of lecture covered 'practical skill test' got a good response from the users. Overall, content diversity, interaction between creators and users, and harmonious programming strategies are lacking. In order to improve this, it is necessary for emotional and expressive creators to pioneer differentiated fields and practice based on actual field. The introduction of interactive elements such as games and quizzes and the application of new media technologies such as VR and AR are worth trying. Three strategic types of 'hero', 'hub', and 'how to' should be applied complementary. As the demand for education content related to flower design is expected to expand in the future, it is required to develop content that can be used in various platforms, foster professional creators, and develop associated business models.

• Science of Emotion and Sensibility
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• v.25 no.4
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• pp.129-138
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• 2022

In the context of the increasing applications of voice assistants in vehicles, we focused on the association between the visual appeal of the cars and the acoustic characteristics of the voice assistants. This study aimed to investigate the relationship between the visual appeal of the vehicle and the voice assistant based on their emotional characteristics. A total of 15 adjectives were used to assess the emotional characteristics of 12 types of cars and six types of voices. An online interview was carried out, instructing participants to match three adjectives with the presented car images or voices. This was followed with a brief interview to allow the participants to reflect on the adjective matches. Based on the assessments, we performed principal component analysis (PCA) to determine factors. We aimed to deploy the cars and voices and analyze the patterns of clustering. The PCA analysis revealed two factors profiled as "Light-Heavy" and "Comfortable-Radical." Both car and voice stimuli were deployed in a two-dimensional space showing the internal relationship within and between the two substances. Based on the coordination data, a hierarchical cluster grouped the 18 stimuli into four groups labeled as challenge, elegance, majesty, and vigor. This study identified two latent factors describing the emotional characteristics of both car images and voice types clustered into four groups based on their emotional characteristics. The coherent matches between car style and voice type are expected to address the design concept more successfully.

• Journal of the Korean Recycled Construction Resources Institute
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• v.11 no.2
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• pp.130-137
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• 2023

This study analyzed the effect of mixing order on the flowability, compressive strength, and flexural strength of cement composites reinforced with polyvinyl alcohol(PVA) fibers and multi-walled carbon nanotubes(MWCNTs). The experimental results showed that the addition of CNTs significantly reduced the flowability, and the flowability was considerably affected by the mixing order when CNTs were added. The compressive strength was most effectively improved when water and CNTs solution were mixed first before adding PVA fibers, and the flexural strength was highest when water and CNTs solution were mixed with PVA fibers after dry mixing. However, there was no clear correlation between the flexural toughness and the mixing order. In addition, scanning electron microscopy(SEM) image analysis was conducted to analyze the microstructure. The SEM images showed that CNTs were randomly dispersed through the specimens and contributed to the strength improvement, but the effect of the mixing order was not clearly observed. The main results of this study are expected to be useful for evaluations of workability and material performance of PVA fiber-reinforced cement composites with CNTs.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.5D
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• pp.611-617
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• 2009

With advanced technologies applied to transportation, realtime traffic information has been necessary for not only drivers but also agencies. In normal, traffic conditions have been represented to three levels according to congestion: "free", "slow", and "jammed". Those categories and criteria are set up for traffic management even though traffic information is provided for drivers. This study examines how drivers feel current congestion levels and delves into traffic categories and criteria which they recognize. To collect data for drivers' recognition, a survey of freeway travellers is conducted answering the question about traffic flow speed from video image on a freeway section. In the result of the survey, the surveyee preferred a 4-level traffic condition including "delayed" to 3-level traffic condition. As its criteria, 20 km/h, 50 km/h, and 75 km/h were obtained. These results are expected to contribute to building more appropriate traffic information for drivers and providing an operational guideline for Traffic Monitering Centers.

• Journal of Service Research and Studies
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• v.11 no.2
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• pp.21-36
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• 2021

This study investigated the means-end chain theory more concretely through the APT hard laddering technique. This is carrying out a questionnaire survey targeting users by hair salon type, and the items drawn from the qualitative laddering technique are applied. The technique is a comparative analysis of each attribute, consequences, and value item by analyzing each step's questions. The results are as follows. First, hairdresser's ability, acceptance of individual-customized opinions, and cheap price were the most mentioned items in the selection attributes. As for the consequences items, image transformation, neatness, novelty, and psychological stability were drawn in order. The items indicated as important among the value items were satisfaction, followed by happiness, confidence, beauty, and bond. Second, the remarkable selection attributes, irrelevant of hair salon type, was revealed as hairdresser's ability and the key values pursued when using a hair salon were drawn as satisfaction, confidence, and beauty. From this result, it was found that meeting the desire of consumers using hair salons can be linked with ultimately pursued values. It was also verified that partial differences were shown by hair salon type and this meant that consumers' desire and expected benefits were different by hair salon type. Although this study drew value perception through comparison with hair salon types based on the means-end chain theory, it was confirmed that the most important selection attribute was hairdresser's ability and they select and use hair salons to gain satisfaction and confidence.

• Journal of The Geomorphological Association of Korea
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• v.27 no.1
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• pp.1-19
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• 2020

A river bed which is submerged in water at high flow and becomes part of the river at low flow, serves as a bridge between the river and the land. The channel bar creates a unique ecosystem with vegetation adapted to the particular environment and the water pool forms a wetland that plays a very important role in the environment. To evaluate anthropogenic impacts on the river bed in the Middle Yeongsangang River, the fluvial landforms in the stream channel were analyzed using multi-temporal remotely-sensed images. In the aerial photograph of 2005 taken before the construction of the large weirs, oxbow lakes, mid-channel bars, point bars, and natural wetlands between the artificial levees were identified. Multiple bars divided the flow of stream water to cause the braided pattern in a particular section. After the construction of the Seungchon weir, aerial photographs of 2013 and 2015 revealed that most of the fluvial landforms disappeared due to the dredging of its riverbed and water level control(maintenance at 7.5El.m). Sentinel-2 images were analyzed to identify differences between before and after the opening of weir gate. Change detection was performed with the near infrared and shortwave infrared spectral bands to effectively distinguish water surfaces from land. As a result, water surface area of the main stream of the Yeongsangang River decreased by 40% from 1.144km² to 0.692km². A large mid-channel bar that has been deposited upstream of the weir was exposed during low water levels, which shows the obvious influence of weir on the river bed. Newly formed unvegetated point bars that were deposited on the inside of a meander bend were identified from the remotely sensed images. As the maintenance period of the weir gate opening was extended, various habitats were created by creating pools and riffles around the channel bars. Considering the ecological and hydrological functions of the river bed, it is expected that the increase in bar areas through weir gate opening will reduce the artificial interference effect of the weir.