• Journal of Broadcast Engineering
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• v.26 no.5
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• pp.500-507
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• 2021

The virtual reality industry has an opportunity to take another leap forward with the surge in demand for non-face-to-face content and interest in the metaverse after Covid-19. Therefore, in order to popularize virtual reality content along with this trend, high-quality content production and storytelling research suitable for the characteristics of virtual reality should be continuously conducted. In order for content to which virtual reality characteristics are applied to be effectively produced through user feedback, a quantitative index that can evaluate the content is needed. In this study, the process of viewing virtual reality contents was analyzed and head movement was set as a quantitative indicator. Afterwards, the experimenter watched five animations and analyzed the correlation between recorded head movement information and immersion. As a result of the analysis, high immersion was shown when the head movement speed was relatively slow, and it was found that the head movement speed can be used significantly as an index indicating the degree of content immersion. The result derived in this way can be used as a quantitative indicator that can verify the validity of the storytelling method applied after the prototype is produced when the creator creates virtual reality content. This method can improve the quality of content by quickly identifying the problems of the proposed storytelling method and suggesting a better method. This study aims to contribute to the production of high-quality virtual reality content and the popularization of virtual reality content as a basic research to analyze immersion based on the quantitative indicator of head movement speed.

• The Southeast Asian review
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• v.21 no.2
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• pp.43-75
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• 2011

The article focuses on the impact and Acceptance of Hindu culture in Modern Southeast Asian Buddhism. The purpose of this study is to examine critically the influential epic Ramayana on Siam culture, Thai Ramayana version 'Ramakien', reveal instances of Buddhist Modification. The Ramayana by the great sage Valmiki is considered by Indians to be the first great literary work to be produced in India. The influence of this work is to be seen not only through centuries but even in other countries, such as Thailand where there are modified modern versions. In this paper, I have three objectives : (1) I may discuss the epic Ramayana of India gave birth to the Ramakien of Thailand. In modern times Valmiki's epic was made to fit the spiritual trends current in the new Chakri dynasty, which were themselves based on Brahmanic tradition and Theravada buddhism. With regarding to the structure of the Traibhumi cosmography, and the relationship between merit and power implied by this cosmography ranks all beings from demons to deities in a hierarchy of merit which accrues according to karma the actions of past lives. (2) I analyze how to have attempted to dissect the Hindi and Thai version of the Ramayana. The Hindu concept of kingship is also depicted in the life of Rama. The Hindus see in Rama the norm of a true Hindu life characterized by the Caste and Dharma. In Thai transformed version, it does not preach Hindu values of personal or social life. The Ramakien emphasized that the Buddhism were higher than all other laws, and that the King is regarded as the incarnation of Phra Ram, and thus is also the narration of the righteous buddhist ruler. (3) I discuss how cultural or social contexts can influence the structure of the royal Wat. The whole epic was painted by the order of Rama I in the galleries of the Wat Phra Keo. In other words, it is the very centre of the dynastic cult enshrining the Emerald Buddha, the most iconic expression of the Ramakien tradition were officially amalgamated. Rama I was continued the process of elaborating and stabilizing the complex religious pattern, with Buddhism at the pinnacle. My finding will support the idea that the Ramakien is particularly appealing to the Thai people because it presents the image of an ideal king, Rama, who symbolizes the force of virtue or dharma while Thotsakan represents the force of evil. Eventually the force of good prevails. Being Buddhists, the Thai poets bring into the story the Buddhist philosophy(especially, the law of cause and effect, karma). This paper examines the role of the Hindu epic Ramayana in the historical and cultural contact between Hindu India and Buddhist Southeast Asia. It should now be possible to evaluate what elements of Hindu culture were transmitted into Thai through the Rama story.

• Journal of Korean Academy of Oral Health
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• v.41 no.4
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• pp.290-295
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• 2017

Objectives: Dental plaque emits red fluorescence under a visible blue light near the ultra-violet end of the light spectrum. The fluorescence characteristics of each microorganism have been reported in several studies. The aim of this study was to evaluate changes in red fluorescence of oral microorganisms that is affected by blood in the culture media. Methods: The gram-positive Actinomyces naeslundii (AN, KCTC 5525) and Lactobacillus casei (LC, KCTC 3109) and gram negative Prevotella intermedia (PI, KCTC 3692) that are known to emit red fluorescence were used in this study. Each bacterium was activated in broth and cultivated in different agar media at $37^{\circ}C$ for 7 days. Tryptic soy agar with hemin and vitamin $K_3$ (TSA), TSA with sheep blood (TSAB), basal medium mucin (BMM) medium, and BMM with sheep blood (BMMB) were used in this study. Fluorescence due to bacterial growth was observed under 405-nm wavelength blue light using the quantitative light-induced fluorescence-digital (QLF-D) device. The red, green, and blue fluorescence values of colonies were obtained using image-analysis software and the red to green ratio (R/G value) and red to total RGB ratio (R/RGB value) were calculated for quantitative comparison. Results: The QLF-D images of the AN, LC, and PI colonies showed red fluorescence in all media, but the fluorescence of all bacteria was reduced in TSA and BMM media, compared with in TSAB and BMMB media. Both the R/G and the R/RGB values of all bacteria were significantly reduced in growth media without blood (P<0.001). Conclusions: Based on this in vitro study, it can be concluded that red fluorescence of oral bacteria can be affected by growth components, especially blood. Blood-containing medium could be a significant factor influencing red fluorescence of oral bacteria. It can be further hypothesized that bleeding in the oral cavity can increase the red fluorescence of dental plaque.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.3
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• pp.133-139
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• 2021

Currently, the process of constructing a high-definition road map has a high proportion of manual labor, so there are limitations in construction time and cost. Research to automate map production with high-definition road maps using artificial intelligence is being actively conducted, but since the construction of training data for the map construction is also done manually, there is a need to automatically build training data. Therefore, in this study, after converting to images using point clouds acquired by a mobile mapping system, the road marking areas were extracted through image reclassification and overlap analysis using thresholds. Then, a methodology was proposed to automatically construct training data for deep learning data for the high-definition road map through the classification of the polygon types in the extracted regions. As a result of training 2,764 lane data constructed through the proposed methodology on a deep learning-based PointNet model, the training accuracy was 99.977%, and as a result of predicting the lanes of three color types using the trained model, the accuracy was 99.566%. Therefore, it was found that the methodology proposed in this study can efficiently produce training data for high-definition road maps, and it is believed that the map production process of road markings can also be automated.

• Journal of Korea Water Resources Association
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• v.54 no.3
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• pp.167-179
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• 2021

In order to characterize the mixing process of confluence for understanding the impacts of a river on the other river, it has been crucial to analyze the spatial mixing patterns for main streams depending on various inflow conditions of tributaries. However, most conventional studies have mostly relied upon hydraulic or water quality numerical models for understanding mixing pattern analysis of confluences, due to the difficulties to acquire a wide spatial range of in-situ data for characterizing mixing process. In this study, backscatters (or SNR) measured from ADCPs were particularly used to track sediment mixing assuming that it could be a surrogate to estimate the suspended sediment concentration. Raw backscatter data were corrected by considering the beam spreading and absorption by water. Also, an optical Laser diffraction instrument (LISST) was used to verify the method of acoustic backscatter and to collect the particle size distribution of main stream and tributary. In addition, image-based spatial distributions of sediment mixture in the confluence were monitored in various flow conditions by using an unmanned aerial vehicle (UAV), which were compared with the spatial distribution of acoustic backscatter. As results, we found that when acoustic backscatter by ADCPs were well processed, they could be proper indicators to identify the spatial patterns of the three-dimensional mixing process between two rivers. For this study, flow and sediment mixing characteristics were investigated in the confluence between Nakdong and Nam river.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.47 no.2
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• pp.163-170
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• 2021

This study was conducted to create a technology to remove acne bacteria with human-friendly materials. First, the Cutibacterium acnes (C. acnes) were adsorbed to the mica disc to grow, and then the biofilm was checked through an atomic microscope to see if the biofilm had grown. Based on the topographic image, the shape changed round, the size was 17% longer on average, and the phase value of the resonance frequency separating materials was observed as a single value, the biofilm grown by covering the extracellular polymeric substrate (EPS). As a result of processing 50 mM of amino acids in the matured biofilm, the concentration of C. acnes decreased when valine, serine, arginine and leucine were treated. Scanning with nanoindentation and AFM contact modes confirmed that the hardness of biofilms treated with Valine (Val) increased. This indicates that an AFM tip measured cell which may have more solidity than that of EPS. The experiment of fluorescent tagged to EPS displays an existence of EPS at the condition of 10 mM Val, but an inhibition of growth of EPS at the 50 mM Val. Number of C. acnes was also reduced above 10 mM of Val. Weak adhesion of biofilm generated from an inhibition of EPS formation seems to induce decrease of C. acnes. Accordingly, we elucidated that Val has an efficiency which eliminates C. acnes by approach of an inhibition of EPS.

• Journal of Broadcast Engineering
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• v.27 no.3
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• pp.318-331
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• 2022

With the recent development of hardware computing devices and software based frameworks, machine tasks using deep learning networks are expected to be utilized in various industrial fields and personal IoT devices. However, in order to overcome the limitations of high cost device for utilizing the deep learning network and that the user may not receive the results requested when only the machine task results are transmitted from the server, Collaborative Intelligence (CI) proposed the transmission of feature maps as a solution. In this paper, an efficient compression method for feature maps with vast data sizes to support the CI paradigm was analyzed and presented through experiments. This method increases redundancy by applying feature map reordering to improve compression efficiency in traditional video codecs, and proposes a feature map method that improves compression efficiency and maintains the performance of machine tasks by simultaneously utilizing image compression format and video compression format. As a result of the experiment, the proposed method shows 14.29% gain in BD-rate of BPP and mAP compared to the feature compression anchor of MPEG-VCM.

• Korean Chemical Engineering Research
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• v.60 no.2
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• pp.300-307
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• 2022

Time-resolved serial femtosecond crystallography (TR-SFX) is a powerful technique for determining temporal variations in the structural properties of biomacromolecules on ultra-short time scales without causing structure damage by employing femtosecond X-ray laser pulses generated by an X-ray free electron laser (XFEL). The mixing rate of reactants and biomolecule samples, as well as the hit rate between crystal samples and x-ray pulses, are critical factors determining TR-SFX performance, such as accurate image acquisition and efficient sample consumption. We here develop two distinct sample delivery systems that enable ultra-fast mixing and on-demand droplet injecting via pneumatic application with a square pulse signal. The first strategy relies on inertial mixing, which is caused by the high-speed collision and subsequent coalescence of droplets ejected through a double nozzle, while the second relies on on-demand pneumatic jetting embedded with a 3D-printed micromixer. First, the colliding behaviors of the droplets ejected through the double nozzle, as well as the inertial mixing within the coalesced droplets, are investigated experimentally and numerically. The mixing performance of the pneumatic jetting system with an integrated micromixer is then evaluated by using similar approaches. The sample delivery system devised in this work is very valuable for three-dimensional biomolecular structure analysis, which is critical for elucidating the mechanisms by which certain proteins cause disease, as well as searching for antibody drugs and new drug candidates.

• Journal of the Korean Society of Radiology
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• v.16 no.5
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• pp.661-672
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• 2022

After the outbreak of the SARS-CoV2 virus that causes COVID-19, it spreads around the world with the number of infections and deaths rising rapidly caused a shortage of medical resources. As a way to solve this problem, chest X-ray diagnosis using Artificial Intelligence(AI) received attention as a primary diagnostic method. The purpose of this study is to comprehensively analyze the detection of COVID-19 via AI. To achieve this purpose, 292 studies were collected through a series of Classification methods. Based on these data, performance measurement information including Accuracy, Precision, Area Under Cover(AUC), Sensitivity, Specificity, F1-score, Recall, K-fold, Architecture and Class were analyzed. As a result, the average Accuracy, Precision, AUC, Sensitivity and Specificity were achieved as 95.2%, 94.81%, 94.01%, 93.5%, and 93.92%, respectively. Although the performance measurement information on a year-on-year basis gradually increased, furthermore, we conducted a study on the rate of change according to the number of Class and image data, the ratio of use of Architecture and about the K-fold. Currently, diagnosis of COVID-19 using AI has several problems to be used independently, however, it is expected that it will be sufficient to be used as a doctor's assistant.

• Journal of Convergence for Information Technology
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• v.11 no.5
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• pp.30-37
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• 2021

Various devices are connected to the Internet, and attacks using the Internet are occurring. Among such attacks, there are attacks that use malicious URLs to make users access to wrong phishing sites or distribute malicious viruses. Therefore, how to detect such malicious URL attacks is one of the important security issues. Among recent deep learning technologies, neural networks are showing good performance in image recognition, speech recognition, and pattern recognition. This neural network can be applied to research that analyzes and detects patterns of malicious URL characteristics. In this paper, performance analysis according to various parameters was performed on a method of detecting malicious URLs using neural networks. In this paper, malicious URL detection performance was analyzed while changing the activation function, learning rate, and neural network structure. The experimental data was crawled by Alexa top 1 million and Whois to build the data, and the machine learning library used TensorFlow. As a result of the experiment, when the number of layers is 4, the learning rate is 0.005, and the number of nodes in each layer is 100, the accuracy of 97.8% and the f1 score of 92.94% are obtained.