• Journal of the Korean Institute of Landscape Architecture
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• v.52 no.2
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• pp.39-50
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• 2024

Color is an essential visual element that has a significant impact on the formation of a city's image and people's perceptions. Quantitative analysis of color in urban environments is a complex process that has been difficult to implement in the past. However, with recent rapid advances in Machine Learning, it has become possible to analyze city colors using photos shared by tourists. This study selected Dali City, a popular tourist destination in China, as a case study. Photos of Dali City shared by tourists were collected, and a method to measure large-scale city colors was explored by combining machine learning techniques. Specifically, the DeepLabv3+ model was first applied to perform a semantic segmentation of tourist sharing photos based on the ADE20k dataset, thereby separating artificial elements in the photos. Next, the K-means clustering algorithm was used to extract colors from the artificial elements in Dali City, and an adjacency matrix was constructed to analyze the correlations between the dominant colors. The research results indicate that the main color of the artificial elements in Dali City has the highest percentage of orange-grey. Furthermore, gray tones are often used in combination with other colors. The results indicated that local ethnic and Buddhist cultures influence the color characteristics of artificial elements in Dali City. This research provides a new method of color analysis, and the results not only help Dali City to shape an urban color image that meets the expectations of tourists but also provide reference materials for future urban color planning in Dali City.

• Korean Journal of Radiology
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• v.21 no.10
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• pp.1165-1177
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• 2020

Objective: To assess the feasibility of applying a deep learning-based denoising technique to coronary CT angiography (CCTA) along with iterative reconstruction for additional noise reduction. Materials and Methods: We retrospectively enrolled 82 consecutive patients (male:female = 60:22; mean age, 67.0 ± 10.8 years) who had undergone both CCTA and invasive coronary artery angiography from March 2017 to June 2018. All included patients underwent CCTA with iterative reconstruction (ADMIRE level 3, Siemens Healthineers). We developed a deep learning based denoising technique (ClariCT.AI, ClariPI), which was based on a modified U-net type convolutional neural net model designed to predict the possible occurrence of low-dose noise in the originals. Denoised images were obtained by subtracting the predicted noise from the originals. Image noise, CT attenuation, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were objectively calculated. The edge rise distance (ERD) was measured as an indicator of image sharpness. Two blinded readers subjectively graded the image quality using a 5-point scale. Diagnostic performance of the CCTA was evaluated based on the presence or absence of significant stenosis (≥ 50% lumen reduction). Results: Objective image qualities (original vs. denoised: image noise, 67.22 ± 25.74 vs. 52.64 ± 27.40; SNR [left main], 21.91 ± 6.38 vs. 30.35 ± 10.46; CNR [left main], 23.24 ± 6.52 vs. 31.93 ± 10.72; all p < 0.001) and subjective image quality (2.45 ± 0.62 vs. 3.65 ± 0.60, p < 0.001) improved significantly in the denoised images. The average ERDs of the denoised images were significantly smaller than those of originals (0.98 ± 0.08 vs. 0.09 ± 0.08, p < 0.001). With regard to diagnostic accuracy, no significant differences were observed among paired comparisons. Conclusion: Application of the deep learning technique along with iterative reconstruction can enhance the noise reduction performance with a significant improvement in objective and subjective image qualities of CCTA images.

• Journal of Preventive Medicine and Public Health
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• v.57 no.1
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• pp.37-46
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• 2024

Objectives: The objective of this study was to characterize mental health issues among Vietnamese healthcare workers (HCWs) and to identify related factors. Methods: A cross-sectional study was conducted with 990 HCWs in 2021. Their mental health status was measured using the Depression, Anxiety, and Stress Scale. Results: In total, 49.9%, 52.3%, and 29.8% of respondents were found to have depression, anxiety, and stress, respectively. The multivariable linear regression model revealed that factors associated with increased anxiety scores included depression scores (β, 0.45; 95% confidence interval [CI], 0.39 to 0.51) and stress scores (β, 0.46; 95% CI, 0.41 to 0.52). Factors associated with increased depression scores included being frontline HCWs (β, 0.57; 95% CI, 0.10 to 1.10), stress scores (β, 0.50; 95% CI, 0.45 to 0.56), and anxiety scores (β, 0.41; 95% CI, 0.36 to 0.47), while working experience was associated with reduced depression scores (β, -0.08; 95% CI, -0.16 to -0.01). Factors associated with increased stress scores included working experience (β, 0.08; 95% CI, 0.00 to 0.16), personal protective equipment interference with daily activities (β, 0.55; 95% CI, 0.07 to 1.00), depression scores (β, 0.54; 95% CI, 0.48 to 0.59), and anxiety scores (β, 0.45; 95% CI, 0.39 to 0.50), while age was associated with reduced stress scores (β, -0.12; 95% CI, -0.20 to -0.05). Conclusions: Specific interventions are necessary to enhance and promote the mental health of HCWs so they can successfully cope with the circumstances of the pandemic.

• Journal of the Korean earth science society
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• v.45 no.1
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• pp.48-71
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• 2024

Typhoons are representative oceanic and atmospheric phenomena that cause interactions within the Earth's system with diverse influences. In recent decades, the typhoons have tended to strengthen due to rapidly changing climate. The 2022 revised science curriculum emphasizes the importance of teaching-learning activities using advanced science and technology to cultivate digital literacy as a citizen of the future society. Therefore, it is necessary to solve the temporal and spatial limitations of textbook illustrations and to develop effective instructional materials using global-scale big data covered in the field of earth science. In this study, according to the procedure of the PDIE (Preparation, Development, Implementation, Evaluation) model, the inquiry activity data was developed to visualize the track of the typhoon using the image data of GK-2A. In the preparatory stage, the 2015 and 2022 revised curriculum and the contents of the inquiry activities of the current textbooks were analyzed. In the development stage, inquiry activities were organized into a series of processes that can collect, process, visualize, and analyze observational data, and a GUI (Graphic User Interface)-based visualization program that can derive results with a simple operation was created. In the implementation and evaluation stage, classes were conducted with students, and classes using code and GUI programs were conducted respectively to compare the characteristics of each activity and confirm its applicability in the school field. The class materials presented in this study enable exploratory activities using actual observation data without professional programming knowledge which is expected to contribute to students' understanding and digital literacy in the field of earth science.

• Journal of Korean Neurosurgical Society
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• v.67 no.3
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• pp.345-353
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• 2024

Objective : Blood-blister aneurysms (BBAs) of the internal carotid artery (ICA) are challenging lesions with high morbidity and mortality rates. Although research on BBAs is well documented in different populations, the study of BBAs in the Tibetan population is extremely rare. This study aimed to evaluate the characteristics of BBAs and analyze the treatment modalities and long-term outcomes in the Tibetan population in comparison with the Han population. Methods : The characteristics of patients with BBAs of the ICA from January 2009 to January 2021 at our institution were reviewed. The features of aneurysms, treatment modalities, complications, and follow-up outcomes were retrospectively analyzed. Results : A total of 130 patients (41 Tibetan and 89 Han patients) with BBAs of the ICA who underwent treatment were enrolled. Compared with the Han group, the Tibetan group significantly demonstrated a high ratio of BBAs among ICAs (8.6%, 41/477 vs. 1.6%, 89/5563; p<0.05), a high ratio of vasospasm (34.1%, 14/41 vs. 6.7%, 6/89; p=0.001), a high risk of ischemic events (43.9%, 18/41 vs. 22.5%, 20/89; p<0.05), and a low ratio of good outcomes (modified Rankin scale, 0-2) at the 1-year follow-up (51.2%, 21/41 vs. 74.2%, 66/89; p<0.05). The multivariate regression model showed that ischemic events significantly contributed to the prediction of outcomes at 1 year. Further analysis revealed that microsurgery and vasospasm were associated with ischemic events. Conclusion : In comparison with Han patients, the Tibetan population had a high ratio of BBA occurrence, a high incidence of ischemic events, and a high ratio of poor outcomes. The endovascular approach showed more benefits in BBA patients.

• Particle and aerosol research
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• v.19 no.4
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• pp.111-128
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• 2023

Chungcheongnam-do has various emission sources, including large-scale facilities such as power plants, steel and petrochemical industry complexes, which can lead to the severe PM pollution. Here, we measured concentrations of PM₁₀, PM_2.5, and its metallic elements at a suburban site in Taean, Chungcheongnam-do from September 2017 to June 2022. During the measurement period, the average concentrations of PM₁₀ and PM_2.5 were 58.6 ㎍/m³ (9.6~379.0 ㎍/m³) and 35.0 ㎍/m³ (6.1~132.2 ㎍/m³), respectively. The concentration of PM₁₀ and PM_2.5 showed typical seasonal variation, with higher concentration in winter and lower concentration in summer. When high concentrations of PM_2.5 occurred, particulary in winter, the fraction of Zn and Pb components considerably increased, indicating a significant contribution of Zn and Pb to high-PM_2.5 concentration. In addition, Zn and Pb exhibited the highest correlation coefficient among all other metallic elements of PM_2.5. A backward trajectory cluster analysis and CPF model were performed to examine the origin of PM_2.5. The high concentration of PM_2.5 was primarily influenced by emissions from industrial complexes located in the northeast and northwest areas.

• Journal of Korean Society for Quality Management
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• v.51 no.4
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• pp.531-550
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• 2023

Purpose: The unique nature of life-and-death healthcare services sets them apart from other service industries. While many studies exist on the relationship between healthcare services and customer satisfaction, most of them focus on mildly ill patients, ignoring the differences between critically ill and non-seriously ill patients. This study discusses the actual quality of healthcare services for patients who are facing life-threatening illnesses and are on life support, as well as their right to protection and dignity. Methods: The survey conducted to 149 patients with the four major illnesses: cancer, heart disease, brain disease and rare and incurable disease, those who have experiences with senior general hospitals. Results: The basic statistics of this study are adequate to represent the four major critical illnesses, and the reliability and validity of this study's hypotheses, which were measured by multiple items, were analyzed, and the internal consistency was judged to be high. In addition, it was found that the convergent validity was good and the discriminant validity was also secured. When examining the goodness of fit of the hypotheses, the SRMR, which is the standardized root mean square of residuals that measures the difference between the covariance matrix of the data variables and the theoretical covariance matrix structure of the model, met the optimal criteria. Conclusion: The academic implications of this study are differentiated from other studies by moving away from evaluating the quality of healthcare services for mildly ill patients and focusing on the rights and dignity of patients with life-threatening illnesses in four senior general hospitals. In terms of academic implications, this study enriches the depth of related studies by demonstrating the right to protection and dignity as a factor of patient-centeredness based on physical environment quality, interaction quality, and outcome quality, which are presented as sub-factors of healthcare quality. We found that the three quality factors classified by Brady and Cronin (2001) are optimized for healthcare quality assessment and management, and that the results of patients' interaction quality assessment can be used to provide a comprehensive quality rating for hospitals. Health and human rights are inextricably linked, so assessing the degree to which rights and dignity are protected can be a superior and more comprehensive measurement tool than traditional health level measures for healthcare organizations. Practical implications: Improving the quality of the physical environment and the quality of outcomes is an important challenge for hospital managers who attract patients with life and death conditions, but given the scale and economics of time, money, and human inputs, improving the quality of interactions and defining them as performance indicators in hospital quality management is an efficient way to create maximum value in the short term.

• Journal of the Korean Society for information Management
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• v.41 no.1
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• pp.509-536
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• 2024

The purpose of this study is to develop a metadata AP for managing the person and organization name authority data in the National Debt Redemption Movement Digital Archive, a small-scale digital archive. The design principles and core metadata elements were derived by analyzing person/organization(group or corporateBody) metadata standards, implementation practices, and guidelines of libraries and archives, and mapped to the National Debt Redemption Movement person/organization name thesaurus data and the Wikidata Linked Metadata Model, resulting in 10 elements in the identification area, 14 elements in the content area, 8 elements in the relationship area, and 4 elements in the control area. A simple structure schema was applied so that it can be applied even in small organizations, and for interoperability, the schema was proposed with reference to DublinCore and SKOS schemes, and the applicability was confirmed based on actual data. The results of this study can be utilized as a basis for institutions that recognize the importance of data management but have difficulty in applying it in practice, when they want to prepare a system for managing their own authority data.

• Korean Journal of Environmental Biology
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• v.42 no.2
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• pp.193-206
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• 2024

This study aimed to quantify changes in forest cover and carbon storage of Korean Peninsular during the last two decades by integrating field measurement, satellite remote sensing, and modeling approaches. Our analysis based on 30-m Landsat data revealed that the forested area in Korean Peninsular had diminished significantly by 478,334 ha during the period of 2000-2019, with South Korea and North Korea contributing 51.3% (245,725 ha) and 48.6% (232,610 ha) of the total change, respectively. This comparable pattern of forest loss in both South Korea and North Korea was likely due to reduced forest deforestation and degradation in North Korea and active forest management activity in South Korea. Time series of above ground biomass (AGB) in the Korean Peninsula showed that South and North Korean forests increased their total AGB by 146.4Tg C (AGB at 2020=357.9Tg C) and 140.3Tg C (AGB at 2020=417.4Tg C), respectively, during the last two decades. This could be translated into net AGB increases in South and North Korean forests from 34.8 and 29.4 Mg C ha^-1 C to 58.9(+24.1) and 44.2(+14.8) Mg C ha^-1, respectively. It indicates that South Korean forests are more productive during the study period. Thus, they have sequestered more carbon. Our approaches and results can provide useful information for quantifying national scale forest cover and carbon dynamics. Our results can be utilized for supporting forest restoration planning in North Korea

• Industry Promotion Research
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• v.9 no.3
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• pp.295-309
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• 2024

With the implementation of the Northeast Revitalization Strategy, the tourism industry in Heilongjiang Province had an increasingly greater impact on regional economic development. Based on the tourism panel data of Heilongjiang Province from 2005 to 2021, this paper used DEA-BCC and Malmquist Index to analyze the static and dynamic changes of the tourism industry.The results of the study were as follows: (1) Static: The OE value reached strong DEA effectiveness in 2010, 2013, and 2019, indicated that tourism resources had been fully utilized. The SE value changed dramatically between 0.354 and 1, and the PTE value approached 1. OE was mainly affected by SE changes. (2) Dynamic: The total factor productivity (TFP) was overall greater than 1 and grew at an average annual rate of 13.8%. The variation in TFP was primarily influenced by the index of technological progress, indicated that the tourism industry in Heilongjiang Province made full use of technology for resource development, with a relatively high level of development efficiency. Therefore, the future focus of Heilongjiang Province's tourism industry will be on adjustments in industrial scale, technological innovation, and policy optimization.