• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.6
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• pp.853-860
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• 2022

The purpose of this study is to suggest an improvement plan for the calculation method of the engineer standard wage rate (ESWR) and to compute a reasonable ESWR. To this end, an adequacy review of theESWR calculation criteria was conducted along with an extensive engineering industry survey. The survey results were analyzed using an effective response sample of 748 companies out of 1,000 survey samples extracted by stratifying the 5,879 survey population. The main results were as follows. ①When calculating the engineering service fee, the prime contractor's engineer wage is suitable for the ESWR. The ESWR can be estimated by the formula 'average wage÷[1-proportion of subcontract orders×(1-subcontract rate)].' ② The field survey showed that the number of monthly working days was 20.35-20.54 days at 99 % confidence interval, which was significantly different from the current standard (22 days). In addition, as a result of a legal review of the ESWR criteria, it was found that the number of working days should be calculated in accordance with the Labor Standards Act after 2022. ③ Applying government guidelines, the time difference between the wage survey and the ESWR application can be corrected by the past ESWR increase rate for a specific period. ④ Using modeling based on the analysis above, the current ESWR was 13.5-14.5 % lower than the appropriate level. A lower ESWR was driven by the non-reflection of subcontract structure (4.1 %), overestimation of monthly work days (6.8-7.8 %), and application of past wage (2.6 %). The proposed model is expected to be widely used in policy making, as it can provide a useful framework for calculating the standard wage rate in similar industries as well as calculating appropriate engineering fees.

• Journal of Korea Water Resources Association
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• v.55 no.6
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• pp.393-404
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• 2022

Reliable terrestrial rainfall observations from satellites at finer spatial resolution are essential for urban hydrological and microscale agricultural demands. Although various traditional "top-down" approach-based satellite rainfall products were widely used, they are limited in spatial resolution. This study aims to assess the potential of a novel "bottom-up" approach for rainfall estimation, the parameterized SM2RAIN model, applied to the C-band SAR Sentinel-1 satellite data (SM2RAIN-S1), to generate high-spatial-resolution terrestrial rainfall estimates (0.01° grid/6-day) over Central South Korea. Its performance was evaluated for both spatial and temporal variability using the respective rainfall data from a conventional reanalysis product and rain gauge network for a 1-year period over two different sub-regions in Central South Korea-the mixed forest-dominated, middle sub-region and cropland-dominated, west coast sub-region. Evaluation results indicated that the SM2RAIN-S1 product can capture general rainfall patterns in Central South Korea, and hold potential for high-spatial-resolution rainfall measurement over the local scale with different land covers, while less biased rainfall estimates against rain gauge observations were provided. Moreover, the SM2RAIN-S1 rainfall product was better in mixed forests considering the Pearson's correlation coefficient (R = 0.69), implying the suitability of 6-day SM2RAIN-S1 data in capturing the temporal dynamics of soil moisture and rainfall in mixed forests. However, in terms of RMSE and Bias, better performance was obtained with the SM2RAIN-S1 rainfall product over croplands rather than mixed forests, indicating that larger errors induced by high evapotranspiration losses (especially in mixed forests) need to be included in further improvement of the SM2RAIN.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.271-278
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• 2022

This study attempted to prepare basic data for international students with Vietnamese nationality in Korea to identify positive psychological capital, social support, social presence, and quality of life and to prepare support measures to improve their quality of life. Data collection is from May 1, 2021 to June 30, 2021, and was conducted through an online survey for anonymity and convenience. For data analysis, the IBM SPSS/25 statistical program was used, and the significance level for the results was measured as .05, and the reliability of each measurement tool was calculated. The results of this study are summarized as follows. First, the age of the subjects was '24 years old-27 years old', and women accounted for the majority. In the fourth grade, the fourth grade was the most, with "outgoing" personality, "sometimes" experiences of interpersonal conflict, "more than four years and less than five years" in the period of residence in Korea, and the level of Korean proficiency was "grade three." Second, the average quality of life of Vietnamese international students was 3.52 points (out of 5 points), positive psychological capital was 3.98 points (out of 6 points), social support was 2.96 points (out of 4 points), and social presence was 3.59 points (out of 5 points). Third, in the case of the quality of life of Vietnamese international students, there was a significant difference according to their personality, and as a result of post-verification, the quality of life of the 'extroverted' group was higher than the 'mixed' group. There was a significant difference according to interpersonal conflict), and as a result of post-examination, the "no conflict" group had a higher quality of life than the "conflict frequent" group. Fourth, the factors that most affected the subject's quality of life were social support, positive psychological capital, and personality (extroverted). The explanatory power of the model was 33.2%.

• Journal of Korean Society of Forest Science
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• v.112 no.4
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• pp.561-573
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• 2023

National forests have an advantage over private forests in terms of higher investment in capital, technology, and labor, allowing for more intensive management. As such, national forests are expected to serve not only as a strategic reserve of forest resources to address the long-term demand for timber but also to stably perform various essential forest functions demanded by society. However, most forest stands in the current national forests belong to the fourth age class or above, indicating an imminent timber harvesting period amid an imbalanced age class structure. Therefore, if timber harvesting is not conducted based on systematic management planning, it will become difficult to ensure the continuity of the national forests' diverse functions. This study was conducted to determine the optimal volume of timber production in the national forests to improve the age-class structure while sustainably maintaining their economic and public functions. To achieve this, the study first identified areas within the national forests suitable for timber production. Subsequently, a forest management planning model was developed using multi-objective linear programming, taking into account both the national forests' economic role and their public benefits. The findings suggest that approximately 488,000 hectares within the national forests are suitable for timber production. By focusing on management of these areas, it is possible to not only improve the age-class distribution but also to sustainably uphold the forests' public benefits. Furthermore, the potential volume of timber production from the national forests for the next 100 years would be around 2 million m³ per year, constituting about 44% of the annual domestic timber supply.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.1
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• pp.125-140
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• 2023

Careful preparation for a start-up can lower the risk of failure and create a successful business model. However, there are still challenges for middle-aged entrepreneurs, as start-up services and policies are often not readily accessible or fully utilized. Despite active research on middle-aged start-ups, previous studies have not delved deeply into the demographics of start-up preparation and various preparation behaviors. In response to this, a study was conducted to identify which start-up support services middle-aged entrepreneurs use, and how start-up preparation can be classified based on this. Data from 324 middle-aged tech start-up owners, based in Seoul and who started their businesses within the past 7 years, was collected and analyzed. The results showed that middle-aged entrepreneurs had moderate start-up preparation, with the greatest focus on the preparation period and the least focus on start-up education. Latent Profile Analysis revealed three groups of start-up preparation types among middle-aged entrepreneurs: "Overall Tribal Type," "Lack of Start-up Education Type," and "Comprehensive Preparation Type." BCH was performed on start-up satisfaction, start-up competence, fear of failure, access to start-up services, and support needs for middle-aged entrepreneurs based on the preparation type. The results showed that "Overall Tribal Type" had statistically lower start-up satisfaction, competence, and service accessibility compared to the other groups. Meanwhile, "Comprehensive Preparation Type" had a statistically lower fear of failure than the other types. "Overall Tribal Type" also had lower accessibility to middle-aged start-up services. All types had a high recognition of the need for support for specialized middle-aged start-ups. The findings highlight the need for more comprehensive support for middle-aged entrepreneurs. This could include expanding support projects to enhance their level of preparation, providing customized support based on their level of preparation, and improving the visibility and accessibility of start-up support services for middle-aged individuals. Additionally, specialized education that addresses the characteristics of middle-aged individuals should be provided.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.4
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• pp.21-35
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• 2023

Expectations surrounding generative AI technology and its profound ramifications are sweeping across various industrial domains. Given the anticipated pivotal role of the startup ecosystem in the utilization and advancement of generative AI technology, it is imperative to cultivate a deeper comprehension of the present state and distinctive attributes characterizing venture capital (VC) investments within this domain. The current investigation delves into South Korea's landscape of VC investment deals and prognosticates the projected VC investments by juxtaposing these against the United States, the frontrunner in the generative AI industry and its associated ecosystem. For analytical purposes, a compilation of 286 investment deals originating from 117 U.S. generative AI startups spanning the period from 2008 to 2023, as well as 144 investment deals from 42 South Korean generative AI startups covering the years 2011 to 2023, was amassed to construct new datasets. The outcomes of this endeavor reveal an upward trajectory in the count of VC investment deals within both the U.S. and South Korea during recent years. Predominantly, these deals have been concentrated within the early-stage investment realm. Noteworthy disparities between the two nations have also come to light. Specifically, in the U.S., in contrast to South Korea, the quantum of recent VC deals has escalated, marking an augmentation ranging from 285% to 488% in the corresponding developmental stage. While the interval between disparate investment stages demonstrated a slight elongation in South Korea relative to the U.S., this discrepancy did not achieve statistical significance. Furthermore, the proportion of VC investments channeled into generative AI enterprises, relative to the aggregate number of deals, exhibited a higher quotient in South Korea compared to the U.S. Upon a comprehensive sectoral breakdown of generative AI, it was discerned that within the U.S., 59.2% of total deals were concentrated in the text and model sectors, whereas in South Korea, 61.9% of deals centered around the video, image, and chat sectors. Through forecasting, the anticipated VC investments in South Korea from 2023 to 2029 were derived via four distinct models, culminating in an estimated average requirement of 3.4 trillion Korean won (ranging from at least 2.408 trillion won to a maximum of 5.919 trillion won). This research bears pragmatic significance as it methodically dissects VC investments within the generative AI domain across both the U.S. and South Korea, culminating in the presentation of an estimated VC investment projection for the latter. Furthermore, its academic significance lies in laying the groundwork for prospective scholarly inquiries by dissecting the current landscape of generative AI VC investments, a sphere that has hitherto remained void of rigorous academic investigation supported by empirical data. Additionally, the study introduces two innovative methodologies for the prediction of VC investment sums. Upon broader integration, application, and refinement of these methodologies within diverse academic explorations, they stand poised to enhance the prognosticative capacity pertaining to VC investment costs.

• Health Policy and Management
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• v.34 no.1
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• pp.48-58
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• 2024

Background: The purpose of this study was to investigate the association between external medical service use and the characteristics of Chungcheongnam-do patients. We aimed to provide evidence of external medical service use enhance the healthcare delivery system in Chungcheongnam-do. Methods: We used the Health Insurance Cohort DB 2.0 of 2016-2019, and 2,570,439 patients were included in the study. Multivariate logistic regression and multinomial logistic regression were used to identify the association between external medical service use and each patient characteristic. Generalized linear model was used to identify the association between medical costs and external medical service use area. Results: During the study period, 32.2% of inpatients and 12.5% of outpatients had external medical service use in Chungcheongnam-do. In comparison to patients living in Cheonan and Asan, the odds ratio (OR) for external medical services use was higher across all regions. Specifically, hospitalized patients from Gyeryong, Nonsan, and Geumsan (OR, 116.817) and Gongju, Buyeo, and Cheongyang (OR, 72.931) demonstrated extremely high likelihood of external medical service use in the Daejeon area. Furthermore, compared to medical expenses incurred within Chungcheongnam-do, patients with external medical service use in the capitol area (outpatient=17.01%, inpatients=22.11%) and Daejeon area (outpatient=16.63%, inpatients=15.41%) spent more on healthcare services. Conclusion: This study found the evidence of external medical service use among Chungcheongnam-do patients. Further study should be conducted taking into account variables including satisfaction of local medical services, different types of patient diseases, and others. The study's findings may serve as a foundation for policy proposals aimed at ensuring the financial stability of our health insurance system, ensuring the efficient delivery of medical care, and localization of medical care.

• Economic and Environmental Geology
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• v.57 no.1
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• pp.1-15
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• 2024

The Melanesian region in the western Pacific is dominated by complex plate tectonics, with the largest oceanic plateau, the OntongJava plateau, and a hotspot, the Caroline Islands. To better understand the complex geodynamics of the region, we estimate P- and S-velocity models and 𝛿 (V_P/V_S) model by using relative teleseismic travel times measured at seismometers on land and the seafloor. Our results show high-velocity anomalies in the subduction zones of the Melanesian region to a depth of about 400 km, which is thought to be subducting Solomon Sea, Bismarck, and Australian plates along plate boundaries. Along subduction zones, positive 𝛿 (V_P/V_S) anomalies are found, which may be caused by partial melting due to dehydration. A broad high-velocity anomaly is observed at 600 km depth below the Ontong-Java plateau, with a negative 𝛿 (V_P/V_S) anomaly. This is thought to be a viscous and dry remnant of the Pacific plate that subducted at 45-25 Ma, with a low volume of fluids due to dehydration for a long period in the mantle transition zone. Beneath the Caroline Islands, a strong low-velocity anomaly is obseved to a depth of 800 km and appears to be connected to the underside of the remnant Pacific plate in the mantle transition zone. This suggests that the mantle plume originating in the lower mantle has been redirected due to the interaction with the remnant Pacific plate and has reached its current location. The mantle plume also has a positive 𝛿 (V_P/V_S) anomaly, which is thought to be due to the influence of embedded fluids or partial melting. A high-velocity anomaly, interpreted as an effect of the thick lithosphere beneath the Ontong-Java plateau, is observed down to 300 km depth with a negative 𝛿 (V_P/V_S) anomaly, which likely indicate that little fluid remains in the melt residue accumulated in the lithosphere.

• The Korean Society of Law and Medicine
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• v.24 no.4
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• pp.67-101
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• 2023

The utilization of generative AI in the medical field is also being rapidly researched. Access to vast data sets reduces the time and energy spent in selecting information. However, as the effort put into content creation decreases, there is a greater likelihood of associated issues arising. For example, with generative AI, users must discern the accuracy of results themselves, as these AIs learn from data within a set period and generate outcomes. While the answers may appear plausible, their sources are often unclear, making it challenging to determine their veracity. Additionally, the possibility of presenting results from a biased or distorted perspective cannot be discounted at present on ethical grounds. Despite these concerns, the field of generative AI is continually advancing, with an increasing number of users leveraging it in various sectors, including biomedical and life sciences. This raises important legal considerations regarding who bears responsibility and to what extent for any damages caused by these high-performance AI algorithms. A general overview of issues with generative AI includes those discussed above, but another perspective arises from its fundamental nature as a large-scale language model ('LLM') AI. There is a civil law concern regarding "the memorization of training data within artificial neural networks and its subsequent reproduction". Medical data, by nature, often reflects personal characteristics of patients, potentially leading to issues such as the regeneration of personal information. The extensive application of generative AI in scenarios beyond traditional AI brings forth the possibility of legal challenges that cannot be ignored. Upon examining the technical characteristics of generative AI and focusing on legal issues, especially concerning the protection of personal information, it's evident that current laws regarding personal information protection, particularly in the context of health and medical data utilization, are inadequate. These laws provide processes for anonymizing and de-identification, specific personal information but fall short when generative AI is applied as software in medical devices. To address the functionalities of generative AI in clinical software, a reevaluation and adjustment of existing laws for the protection of personal information are imperative.

• Journal of the Korea Organic Resources Recycling Association
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• v.31 no.4
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• pp.29-39
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• 2023

In this study, an analysis of medical waste generation characteristics was conducted, differentiating between ordinary situation and the outbreaks of massive infectious diseases. During ordinary situation, prediction models for medical waste quantities by type, general medical waste(G-MW), hazardous medical waste(H-MW), infectious medical waste(I-MW), were established through regression analysis, with all significance values (p) being <0.0001, indicating statistical significance. The determination coefficient(R2) values for prediction models of each category were analyzed as follows : I-MW(R2=0.9943) > G-MW(R2=0.9817) > H-MW(R2=0.9310). Additionally, factors such as GDP(G-MW), the number of medical institutions (H-MW), and the elderly population ratio(I-MW), utilized as influencing factors and consistent with previous literature, showed high correlations. The total MW generation, evaluated by combining each model, had an MAE of 2,615 and RMSE of 3,353. This indicated accuracy levels similar to the medical waste models of H-MW(2,491, 2,890) and I-MW(2,291, 3,267). Due to limitations in accurately estimating the quantity of medical waste during the rapid and outbreaks of massive infectious diseases, the generation unit of I-MW was derived to analyze its characteristics. During the early unstable stage of infectious disease outbreaks, the generation unit was 8.74 kg/capita·day, 2.69 kg/capita·day during the stable stage, and an average of 0.08 kg/capita·day during the reduction stage. Correlation analysis between generation unit of I-MW and lethality rates showed +0.99 in the unstable stage, +0.52 in the stable stage, and +0.96 in the reduction period, demonstrating a very high positive correlation of +0.95 or higher throughout the entire outbreaks of massive infectious diseases. The results derived from this study are expected to play a useful role in establishing an effective medical waste management system in the field of health care.