• Journal of the Daesoon Academy of Sciences
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• v.49
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• pp.187-227
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• 2024

The purpose of this article is to examine the prospects of the religious cultural experience program of Daesoon Jinrihoe by referring to the current status of Korea's Buddhist temple stays, which began with the 2002 World Cup and have become a regular program for the general public with the establishment of the Cultural Corps of Korean Buddhism in 2004. The motivation for Korean participation is mainly rest, while foreigners tend to be more interested in Korean traditional culture. During the experience, the perceived value felt by the participants led to satisfaction and an intention to revisit. Temple stays have contributed to the globalization of Korean Buddhism. The temple stay of Daesoon Jinrihoe is a religious cultural experience program for the public. If it became a regular program, the target could be expanded to include foreigners who wish to experience Korean culture. The activities such as wearing Hanbok, taking a Dojang Tour, praying, and dialogue over tea can be allocated to the program. As a result, the perceived value by participants could be taken as a cognitive value. For instance, they could learn about Sangje's Reordering of the Universe that transformed the order of Sanggeuk (Mutual Contention) into the order of Sangsaeng (Mutual Beneficence). They way that they live their lives could change as a result of these new understandings. The emotional value of the experience would come from experiencing traditional Korean religious culture. The prospect of implementing such a program is twofold: firstly, there are the tasks of proper preparation, and secondly, there are the positive effects. The tasks would first involve creating a systematic and organized center point. Next there would be the matter of preparing spaces for the temple stay, and lastly, an online platform for advertisement, recruitment, and application would also be greatly beneficial. This is a vision that could contribute to the improving public image of the order, its globalization, and to the overall improvement of the facilities and management that would produce a more socially friendly environment.

• Journal of Internet Computing and Services
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• v.25 no.4
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• pp.65-72
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• 2024

To faithfully represent the intention of the work in the exhibition space, lighting that provides high color reproduction like natural light is required. Thus, many lighting technologies have been introduced to improve CRI, but most of them only evaluated the general color rendering index (CRI Ra), which considers eight pastel colors. Natural light provides excellent color rendering performance for all colors, including red and blue, expressed by color rendering index of R9 and R12, but most artificial lighting has the problem that color rendering performance such as R9 and R12 is significantly lower than that of natural light. Recently, lighting technology that provides CRI at the level of natural light is required to realistically express the colors of works including primary colors but related research is very insufficient. Therefore this paper proposes exhibition hall lighting that fulfills CRI with a focus on CRI Ra, R9, and R12 based on the characteristics of natural light. First reinforcement wavelength bands for improving R9 and R12 are selected through analysis of the actual measurement SPD of natural and artificial lighting. Afterward virtual SPDs with a peak wavelength within the reinforcement wavelength band are created and then SPD combination conditions that satisfy CRI Ra≥95, R9, and R12≥90 are derived through combination simulation with a commercial LED light source. Through this, after specifying two types of light sources with 405,630nm peak wavelength that had the greatest impact on the improvement of R9 and R12, the exhibition hall lighting applied with two W/C White LEDs is designed and a control Index DB of the lighting is constructed. Afterward experiments with the proposed method showed that it was possible to achieve high CRI at the level of natural light with average CRI Ra 96.5, R9 96.2, and R12 94.0 under the conditions of illuminance (300-1,000 Lux) and color temperature (3,000-5,000K).

• Journal of Internet Computing and Services
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• v.25 no.4
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• pp.121-130
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• 2024

As internet and communication technology (ICT) is improved exponentially, types and amount of available data also increase. Even though data analysis including statistics is significant to utilize this large amount of data, there are inevitable limits to process various and complex data in general way. Meanwhile, there are many attempts to apply machine learning (ML) in various fields to solve the problems according to the enhancement in computational performance and increase in demands for autonomous systems. Especially, data processing for the model input and designing the model to solve the objective function are critical to achieve the model performance. Data processing methods according to the type and property have been presented through many studies and the performance of ML highly varies depending on the methods. Nevertheless, there are difficulties in deciding which data processing method for data analysis since the types and characteristics of data have become more diverse. Specifically, multi-variate data processing is essential for solving non-linear problem based on ML. In this paper, we present a multi-variate tabular data processing scheme for ML-aided data analysis by using Titanic dataset from Kaggle including various kinds of data. We present the methods like input variable filtering applying statistical analysis and normalization according to the data property. In addition, we analyze the data structure using visualization. Lastly, we design an ML model and train the model by applying the proposed multi-variate data process. After that, we analyze the passenger's survival prediction performance of the trained model. We expect that the proposed multi-variate data processing and visualization can be extended to various environments for ML based analysis.

• Korean Journal of Plant Resources
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• v.37 no.4
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• pp.386-391
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• 2024

'Jinha' is a new strawberry (Fragaria × ananassa Duch.) cultivar, which was released by the Highland Agriculture Research Institute in 2019. The 'Jinha' cultivar originates from a 2011 cross between 'Albion' and 'Goha,' both of which exhibited excellent ever-bearing characteristics, including continuous flowering and large fruits under long-day and high temperature conditions. This new cultivar was initially named 'Saebong No. 11' after examining its characteristics and productivity during summer cultivation between 2012 and 2016. After regional adaptability tests, 'Jinha' was selected from 'Saebong No. 11' as an elite cultivar. The general characteristics of 'Jinha' include intermediate, elliptic leaves, and medium growth. The fruits are conical and of a red color. The plant height of 'Jinha' is simiar to that of the control variety, 'Flamenco', but it has a lot of number of leaves. The cluster length of 'Jinha' was 35.5 cm, 10.8 cm longer than 24.7 cm of the control variety. The number of flower clusters of 'Jinha' appeared 14.4, which was 4.1 more than that of 'Flamenco'. The average fruit weight of 'Jinha' was 10.1 g, which was 0.8 g heavier than that of 'Flamenco'. The soluble solid content of 'Jinha' was 10.2 °Brix, which was 2.0 °Brix higher than that of 'Flamenco'. The marketable yield of 'Jinha' was 25,931 kg·ha^-1, 440% more than that of 'Flamenco' with 5,900 kg·ha^-1. Therefore, the new cultivar of ever-bearing strawberry 'Jinha' is expected to be very popular in the export or bakery market because it is high soluble solid content and good shape.

• Journal of Korean Dental Hygiene Science
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• v.7 no.1
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• pp.69-81
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• 2024

Background: This study aimed to investigate the association between physical activity and periodontitis based on depression status in a representative sample of Korean adults. Methods: A total of 12,689 subjects who participated in the 7th Korea National Health and Nutrition Examination Survey (2016-2018) were examined. Depression was defined as a PHQ-9 score ≥ 10. Periodontal status was assessed using the community periodontal index, with periodontitis defined as a code ≥ 3. Physical activity categories were divided into a physical activity group and a non-physical activity group, considering the number of days and minutes spent on moderate and vigorous activities. Moderate activity was defined as causing slight breathlessness or a slightly elevated heart rate, while vigorous activity was defined as causing significant breathlessness or a rapid heart rate. Multivariable logistic regression analyses were adjusted for sociodemographic variables (age, sex, education level, and household income), oral and general health behaviors (use of floss and interdental proximal brush, current smoking), and systemic health status (diabetes and hypertension). All analyses utilized a complex sampling design, and subgroup analysis was performed to estimate associations stratified by depression (PHQ-9 ≤ 9 and ≥ 10). Results: Multivariable regression analysis revealed that among participants with depression, those who did not engage in physical activity were 2.65 times more likely to have periodontitis (odds ratio = 2.65, 95% confidence interval = 1.17-6.01). Conclusion: The study findings suggest that individuals who participate in any form of physical activity may be significantly less likely to develop periodontitis, particularly within the group experiencing depression.

• Korean Journal of Environment and Ecology
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• v.38 no.4
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• pp.416-425
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• 2024

This study aims to analyze the changes in land prices and building construction activities before and after exclusion from park district as results of natural park re-planning. Seoraksan National Park, Namhansanseong Provincial Park, and Cheonmasan County Park were selected as study areas, and prices and construction activities were compared between areas remaining in and areas excluded from park districts for ten years after park re-planning. Land prices increased in all three study parks. The largest difference in land prices between remaining and excluded areas occurred in Cheonmasan City Park. Land price increased more in excluded than remaining areas in Seoraksan National Park. Unlike these two parks, the changes in land prices were not much different between remaining and excluded areas in Namhansanseong Provincial Park, which can be attributed to the facts that 1) provincial parks were already developed to certain level even before the exclusion due to its less stringent land use regulation than national parks, and 2) that Namhansanseong Provincial Park was also designated as Restricted Development Zone that has similar land use regulation level to natural parks. Comparison between building density measures before and after exclusion shows that development density generally increased after the exclusion. Building heights mostly increased during 10 years after the exclusion. Building to land ratios and floor area ratios also increased. However, building to land ratios and floor area ratios increased only slightly in Namhansanseong Provincial Park and Cheonmasan City Park, suggesting that in provincial and city parks, land development already occurred as a result of less stringent land use regulation. In conclusion, a national park system significantly restricts property right in natural parks, especially in national parks, which make it difficult to expand existing natural parks and/or establish new natural parks. A remedy for resolving problems related to private lands, such as increasing budget for purchasing private lands and introducing park facilities for local community is urgently required.

• Health Policy and Management
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• v.34 no.3
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• pp.271-281
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• 2024

Background: The unmet healthcare needs (UHNs) of people with disabilities (PWD) are not only detrimental to their quality of life but also can lead to serious health outcomes including death. A variety of factors including socioeconomic, personal, and environmental factors affect UHNs for PWD. Previous studies focused on individual socioeconomic and disability characteristics as influencing factors. Our studies included environmental factors that have a significant impact on the use of healthcare service by PWD. Methods: We analyzed the UHNs status and influencing factors among 4,326 adults with disabilities using the Korea Disability Life Data. Chisquare analysis identified differences in UHNs by general, disability, and environmental characteristics. Logistic regression determined factors affecting UHNs. Results: Those with low educational level (adjusted odds ratio [aOR], 1.229; 95% confidence interval [CI], 1.024-1.475), those with low income level (aOR, 1.416; 95% CI, 1.015-1.976), those who enrolled in private insurance (aOR, 1.234; 95% CI, 1.018-1.496), those who need help with daily living (aOR, 1.298; 95% CI, 1.059-1.592), those who did not go out (OR, 1.566; 95% CI, 1.274-1.924), those who use taxis (aOR, 1.407; 95% CI, 1.047-1.891) or call taxi for people with disabilities when going to the hospital (aOR, 1.370; 95% CI, 1.001-1.875), the communication disabled (aOR, 1.304; 95% CI, 1.029-1.651), those with poor subjective health status (aOR, 1.248; 95% CI, 1.043-1.494), those who felt the explanation of treatment results was insufficient (aOR, 4.035; 95% CI, 1.365-11.927), hose dissatisfied with healthcare services (aOR, 3.515; 95% CI, 2.741-4.508) were more likely to experience UHNs. Conclusion: Effective healthcare service provision for PWD requires not only financial assistance but also social support, along with education for healthcare staff, policies that consider the characteristics of disabilities.

• Health Policy and Management
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• v.34 no.3
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• pp.293-308
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• 2024

Background: Assessing the change in mental health status of quarantined patients in community treatment centers at the time of admission and discharge, and inferring the influencing factors. Methods: The study was conducted on a sample of 1,941 quarantined patients from three community treatment centers. Changes in anxiety, psychological distress, post-traumatic stress, depression, and self-harm ideation between admission and discharge were categorized as either "improved" or "worsened." Inference was performed to determine the probability of worsening in mental health status. Results: The mental health status of quarantined patients, such as anxiety and depression, was relatively higher than that of the general population. Anxiety (84.3% improved) and psychological distress (79.0% improved) were reduced during quarantine treatment. However, some patients continued to experience moderate to severe levels of anxiety (11.2%) and psychological distress (11.0%) at discharge. As for depression, the depression of moderate or higher level was increased at the time of discharge (28.7%→36.7%) compared to admission. The deterioration of anxiety and psychological distress was found to be the most significant factor influencing the worsening of depression at discharge (odds ratio [OR] for anxiety deterioration, 2.04; OR for psychological distress deterioration, 3.56). These effects were also observed similarly in post-traumatic stress and self-injury ideation. Conclusion: Improving anxiety and psychological distress among quarantined patients in community treatment centers can reduce the worsening of post-traumatic stress, depression, and self-injury ideation at the time of discharge. These findings provide evidence for the need for active mental health management from the initial stages of quarantine treatment.

• Journal of the Korean Society of Radiology
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• v.18 no.5
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• pp.523-529
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• 2024

The purpose of this study is to investigate the effect of differences in grid focal distance used in general radiography on the exposure index and image quality, and to provide useful information for the application of grids in clinical radiography. With AEC applied and SID set to 110 cm, 30 images were obtained for each focus distance of the grid at 110 cm, 140 cm, and 180 cm under the same exposure conditions. The dose was measured using the DAP and ESD, while image quality was evaluated using the SNR and CNR. The exposure index (EI) was determined based on the values shown in the image. EI was derived from the values indicated in the images. The mean DAP values at focus distances of 180, 140, and 110 cm were 10.944±0.613, 10.687±0.516, and 9.74±0.588 cGy·cm², respectively. The ESD values were 1041.75±57.92, 1019.99±49.61, and 930.86±55.77 μGy, while the EI values were 205.97±11.77, 210.59±10.37, and 193.8±11.86. The SNR values were 28.48±0.62, 28.41±0.64, and 27.13±0.72 dB, and the CNR values were 0.09859±0.004276, 0.09864±0.004378, and 0.09026±0.004783 dB. The differences in the mean values were statistically significant (p < 0.01). The values were significantly higher at focal distances of 140 cm and 180 cm compared to 110 cm, but there was no significant difference between the focal distances of 140 cm and 180 cm. The correlation analysis results revealed significant negative correlations between FD and DAP (r = -0.642, p < 0.01), ESD (r = -0.629, p < 0.01), EI (r = -0.376, p < 0.01), SNR (r = -0.615, p < 0.01), and CNR (r = -0.575, p < 0.01) for all variables. The results of this study showed a moderate negative correlation between the focus distance of the grid and the SNR, CNR, DAP, and ESD, and a weak negative correlation with the EI. Therefore, radiological technologists should be aware that even when the same exposure conditions are applied using an AEC system, variations in focus distance of the grid can affect the exposure index, dose, and image quality. Careful consideration is needed when setting the target exposure index.

• Journal of the Korean Society of Radiology
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• v.18 no.5
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• pp.531-540
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• 2024

Recently, research and development on automatic diagnosis solutions in the medical imaging field using deep learning are actively underway. In this study, we sought to find a fast and accurate classification deep learning modeling for classification of pneumonia in chest images using Inception V3, a deep learning model based on a convolutional artificial neural network. For this reason, after applying the optimization algorithms AdaGrad, RMS Prop, and Adam to deep learning modeling, deep learning modeling was implemented by selectively applying learning rates of 0.01 and 0.001, and then the performance of chest X-ray image pneumonia classification was compared and evaluated. As a result of the study, in verification modeling that can evaluate the performance of the classification model and the learning state of the artificial neural network, it was found that the performance of deep learning modeling for classification of the presence or absence of pneumonia in chest X-ray images was the best when applying Adam as the optimization algorithm with a learning rate of 0.001. I was able to. And in the case of Adam, which is mainly applied as an optimization algorithm when designing deep learning modeling, it showed excellent performance and excellent metric results when selectively applying learning rates of 0.01 and 0.001. In the metric evaluation of test modeling, AdaGrad, which applied a learning rate of 0.1, showed the best results. Based on these results, when designing deep learning modeling for binary-based medical image classification, in order to expect quick and accurate performance, a learning rate of 0.01 is preferentially applied when applying Adam as an optimization algorithm, and a learning rate of 0.01 is preferentially applied when applying AdaGrad. I recommend doing this. In addition, it is expected that the results of this study will be presented as basic data during similar research in the future, and it is expected to be used as useful data in the health and bio industries for the purpose of automatic diagnosis of medical images using deep learning.