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.
Exploratory data analysis is the process of observing and understanding data collected from various sources to identify their distributions and correlations through their structures and characterization. This process can be used to identify correlations among conditioning factors and select the most effective factors for analysis. This can help the assessment of landslide susceptibility, because landslides are usually triggered by multiple factors, and the impacts of these factors vary by region. This study compared two stages of exploratory data analysis to examine the impact of the data exploration procedure on the landslide prediction model's performance with respect to factor selection. Deep-learning-based landslide susceptibility analysis used either a combinations of selected factors or all 23 factors. During the data exploration phase, we used a Pearson correlation coefficient heat map and a histogram of random forest feature importance. We then assessed the accuracy of our deep-learning-based analysis of landslide susceptibility using a confusion matrix. Finally, a landslide susceptibility map was generated using the landslide susceptibility index derived from the proposed analysis. The analysis revealed that using all 23 factors resulted in low accuracy (55.90%), but using the 13 factors selected in one step of exploration improved the accuracy to 81.25%. This was further improved to 92.80% using only the nine conditioning factors selected during both steps of the data exploration. Therefore, exploratory data analysis selected the conditioning factors most suitable for landslide susceptibility analysis and thereby improving the performance of the analysis.
Hyun-Jin Jung;Hyojoon An;Jaehwan Kim;Kitae Park;Jong-Han Lee
Journal of the Korea institute for structural maintenance and inspection
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v.27
no.6
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pp.102-110
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2023
PSC-I girder bridges constitute the largest proportion among highway bridges in Korea. According to the precision safety diagnosis data for the past 10 years, approximately 41.3% of the PSC-I bridges have been graded as C. Furthermore, with the increase in the aging of bridges, preemptive management is becoming more important. Damage and deterioration to the deck and girder with a long replacement cylce can have considerable impacts on the service and deterioration of a bridge. In addition, the high rate of device damages, including expansion joints and bearings, necessitates an investigation into the influence of the device damage in the structural members of the bridge. Therefore, this study defined representative PSC-I girder bridges with single and multiple spans to evaluate heterogeneous damages that incorporate the damage of the bridge member and device with the deterioration of the deck. The heterogeneous damages increased a crack area ratio compared to the individual single damage. For the single-span bridge, the occurrence of bearing damage leads to the spread of crack distribution in the girder, and in the case of multi-span bridges, expansion joint damage leads to the spread of crack distribution in the deck. The research underscores that bridge devices, when damaged, can cause subsequent secondary damage due to improper repair and replacement, which emphasizes the need for continuous observation and responsive action to the damages of the main devices.
The concept of Mydata emerged with the expansion of the data economy. MyData aims to empower individuals by enhancing their right to self-determination over their personal data. The use of MyData is expected to enable the provision of innovative service in various fields. Since 2022, MyData has been introduced and actively used in the financial sector. In the future, not only financial institutions but also Bigtech and Fintech companies are expected to actively join and demonstrate rapid expansion. To ensure steady growth for MyData in the financial sector, it is necessary to assess acceptance behaviors from multiple perspectives. However, the majority of existing research solely focuses on positive acceptance. This study analyzed the impact of users' personal characteristics and innovation characteristics on both innovation resistance and acceptance resistance. The analysis revealed that personal and innovation characteristics contribute to an increase in distrust and innovation resistance in the MyData service. In addition, it has been confirmed that it can lead to actions such as delayed acceptance and refusal to accept. The results of this study offer both theoretical and practical insights into user behavior within the MyData service market.
Journal of the Korean Applied Science and Technology
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v.40
no.5
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pp.1092-1103
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2023
This study is a study to investigate how the achievement goal orientation of domestic winter sports participants has an effect on fun factors and participation satisfaction. A total of 326 questionnaires were used in this study, SPSS(Version 27.0) was used as a data processing method, and frequency analysis, reliability analysis, exploratory factor analysis, correlation analysis, and multiple regression analysis were used as statistical methods. The results of verifying the statistical effects of achievement goal tendency, fun factors, and participation satisfaction are as follows. First, as a result of verifying the effect of achievement goal orientation on fun factors, self-goal orientation and task goal propensity, which are sub-factors of achievement goal orientation, had significant effects on exercise ability, exercise utility, promotion of friendship, and self-satisfaction factors. Second, self-goal and task goal propensity, which are sub-factors of achievement goal orientation, had significant effects on facilities, costs, classes, interpersonal relationships, and health factors. Third, the sub-factors of fun factors such as exercise ability, exercise utility, promotion of friendship, and self-satisfaction had significant impacts on facilities, costs, lessons, interpersonal relationships and health factors.
Yoon-Soo Jang;Jae-Han Lee;Na-Rae Lee;Dong-Woo Kim;June-Hee Lee;Kyung-Jae Lee
Annals of Occupational and Environmental Medicine
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v.35
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pp.50.1-50.11
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2023
Background: The rise in telecommuting or non-face-to-face work owing to the coronavirus disease 2019 pandemic has fueled conversations regarding the "right to disconnect." Although evidence suggests that receiving work-related communications through telecommunication devices outside of work hours may lead to various symptoms and illnesses, limited research has been undertaken on these symptoms. This study therefore aims to investigate the correlation between receiving work communications through telecommunication devices after work hours and the occurrence of work-related headaches and eyestrain in full-time, non-shift white-collar workers. Methods: This study used data from the 6th Korean Working Conditions Survey. The frequency of using telecommunication devices for work purposes outside of working hours was divided into five categories: "Every day," "Several times a week," "Several times a month," "Rarely," and "Never." Work-related headaches and eyestrain were categorized based on a "yes" or "no" response to the survey questions. Descriptive statistics, χ2 tests, and multiple logistic regression analyses were performed using SPSS 27.0. Results: After adjusting for sex, age, income level, education, occupation, workplace size, work hours, and sleep disorders, the odds ratio (OR) of work-related headaches and eyestrain based on frequency of telecommunication device usage were as follows: "rarely" (OR: 1.292; 95% confidence interval [CI]: 1.111-1.503), "several times a month" (OR: 1.551; 95% CI: 1.249-1.926), "several times a week" (OR: 1.474; 95% CI: 1.217-1.784), and "every day" (OR: 1.548; 95% CI: 1.321-1.813). Conclusions: Employees who use telecommunication devices for work after regular hours are more susceptible to experiencing work-related headaches and eyestrain compared to those who do not. However, there is a dearth of research examining the physical and mental health impacts of using telecommunication devices for after-hours work. Furthermore, the existing preventative measures in Korea are insufficient. Consequently, it is imperative to develop effective measures and conduct additional research to address this issue.
The climate change impacts on hydrological components and water balance in Jeju Island were evaluated using multiple climate models and watershed model, SWAT-K. To take into account the uncertainty of the future forecast data according to climate models, climate data of 9 GCMs were utilized as weather data of SWAT-K for future period (2010-2099). Using the modeling results of the past (1992-2013) and the future period, the hydrological changes of each year were analyzed and the precipitation, runoff, evapotranspiration and recharge were increasing. Compared with the past, the change in the runoff was the largest (up to 50% increase) and the evapotranspiration was relatively small (up to 11% increase). Monthly results show that the amount of evapotranspiration and the amount of recharge are greatly increased as the amount of precipitation increases in August and September, while the amount of evapotranspiration decreases in the same period. January and December showed the opposite tendency. As a result of analyzing future water balance changes, the ratio of runoff, evapotranspiration, and recharge to rainfall did not change much, but compared to the past, the runoff rate increased up to 4.3% in the RCP 8.5 scenario, while the evapotranspiration rate decreased by up to 3.5%. Based on the results of other researchers and this study, it is expected that rainfall and runoff will increase gradually in the future under the assumption of present climate change scenarios. Especially summer precipitation and runoff are expected to increase. As a result, the amount of groundwater recharge in Jeju Island will increase.
This study built a model to predict the daily number of visitors to 18 trails in the Taebaeksan National Park using the auto-counter system data to analyze the factors affecting the daily number of visitors to each trail and classified the trails by visitors' behaviors. Results of the multiple regression models with the daily number of visitors of the 18 trails indicated that the events, such as the National Foundation Day celebration of Snow Festival, affected the number of visitors of all of the 18 trails and were the most critical factor that determined the daily number of visitors to the Taebaeksan National Park. The long-holidays of three days or longer and other national holidays also affected the daily number of visitors to the trails. Precipitation had a negative impact on the number of visitors of trails where the intention of most visitors was for sightseeing or camping instead of hiking, whereas had no significant impacts on the number of visitors of trails where many visitors intended for hiking. It indicated that visitors who intended for hiking went ahead hiking even if the weather was poor. The effects of temperature had a positive effect on the number of visitors who intended for hiking but a negative effect on the number of visitor to the trails near Danggol Plaza where the Snow Festival was held in each winter, suggesting that the impact of the Snow Festival was the deterministic factor for trail management. Results of K-mean clustering showed that the 18 trails of the Taekbaeksan National Park could be classified into three types: those affected by the Snow Festival (type 1), those that have sightseeing points and so were visited mostly by non-hikers (type 2), and those visited mostly by hikers (type 3). Since visitor behaviors and illegal actions differ according to the trail type, this study's results can be used to prepare a trail management plan based on the trail characteristics.
The aim of this study was to investigate the impact of depression, somatization, and jaw disability on graded chronic pain of TMD using Research Diagnostic Criteria for Temporomandibular Disorders (RDC/TMD). Ninety-three patients (17 men and 76 women, mean$\pm$SD age of 30.1$\pm$12.5 years) diagnosed with TMD based on RDC/TMD axis I criteria were administered RDC/TMD axis II history questionnaire. The relationships between depression, somatization, jaw disability, and each parameters of graded chronic pain (e.g. pain intensity, pain days, disability score, disability days, graded chronic pain scale) were analyzed by multiple regression analysis. The obtained results were as follows: 1. Among 93 TMD patients, the prevalence of low disability group of graded chronic pain scale was 42.0% and high disability group of graded chronic pain scale was 51.5%. 2. Depression did not show any significant influences on pain intensity, pain days, disability score, disability days, and graded chronic pain scale. 3. Somatization showed a significant effect on pain intensity (p<0.01), disability days (p<0.01), and graded chronic pain scale (p<0.01) except for both pain days and disability score. 4. Jaw disability also showed a significant effect on pain intensity (P<0.001), disability days (p<0.01), and graded chronic pain scale (P<0.001) except for both pain days and disability score. Somatization and jaw disability may closely relate to the pain intensity and degree of disability that TMD patients perceive. Therefore, comprehensive understanding of psychological profile and improvement of functional limitation of jaw movements in the patient should be considered to obtain an excellent outcome of chronic TMD management.
The aim of this research was to develop a climate change vulnerability index at the district level (Si, Gun, Gu) with respect to the health care sector in Korea. The climate change vulnerability index was esimated based on the four major causes of climate-related illnesses : vector, flood, heat waves, and air pollution/allergies. The vulnerability assessment framework consists of six layers, all of which are based on the IPCC vulnerability concepts (exposure, sensitivity, and adaptive capacity) and the pathway of direct and indirect impacts of climate change modulators on health. We collected proxy variables based on the conceptual framework of climate change vulnerability. Data were standardized using the min-max normalization method. We applied the analytic hierarchy process (AHP) weight and aggregated the variables using the non-compensatory multi-criteria approach. To verify the index, sensitivity analysis was conducted by using another aggregation method (geometric transformation method, which was applied to the index of multiple deprivation in the UK) and weight, calculated by the Budget Allocation method. The results showed that it would be possible to identify the vulnerable areas by applying the developed climate change vulnerability assessment index. The climate change vulnerability index could then be used as a valuable tool in setting climate change adaptation policies in the health care sector.
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