• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1283-1297
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• 2023

Mid-wave infrared (MWIR) imagery, due to its ability to capture the temperature of land cover and objects, serves as a crucial data source in various fields including environmental monitoring and defense. The KOMPSAT-3A satellite acquires MWIR imagery with high spatial resolution compared to other satellites. However, the limited spatial resolution of MWIR imagery, in comparison to electro-optical (EO) imagery, constrains the optimal utilization of the KOMPSAT-3A data. This study aims to create a highly visible MWIR fusion image by leveraging the edge information from the KOMPSAT-3A panchromatic (PAN) image. Preprocessing is implemented to mitigate the relative geometric errors between the PAN and MWIR images. Subsequently, we employ a pre-trained pixel difference network (PiDiNet), a deep learning-based edge information extraction technique, to extract the boundaries of objects from the preprocessed PAN images. The MWIR fusion imagery is then generated by emphasizing the brightness value corresponding to the edge information of the PAN image. To evaluate the proposed method, the MWIR fusion images were generated in three different sites. As a result, the boundaries of terrain and objects in the MWIR fusion images were emphasized to provide detailed thermal information of the interest area. Especially, the MWIR fusion image provided the thermal information of objects such as airplanes and ships which are hard to detect in the original MWIR images. This study demonstrated that the proposed method could generate a single image that combines visible details from an EO image and thermal information from an MWIR image, which contributes to increasing the usage of MWIR imagery.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1413-1425
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• 2023

The increasing frequency of wildfires due to climate change is causing extreme loss of life and property. They cause loss of vegetation and affect ecosystem changes depending on their intensity and occurrence. Ecosystem changes, in turn, affect wildfire occurrence, causing secondary damage. Thus, accurate estimation of the areas affected by wildfires is fundamental. Satellite remote sensing is used for forest fire detection because it can rapidly acquire topographic and meteorological information about the affected area after forest fires. In addition, deep learning algorithms such as convolutional neural networks (CNN) and transformer models show high performance for more accurate monitoring of fire-burnt regions. To date, the application of deep learning models has been limited, and there is a scarcity of reports providing quantitative performance evaluations for practical field utilization. Hence, this study emphasizes a comparative analysis, exploring performance enhancements achieved through both model selection and data design. This study examined deep learning models for detecting wildfire-damaged areas using Landsat 8 satellite images in California. Also, we conducted a comprehensive comparison and analysis of the detection performance of multiple models, such as U-Net and High-Resolution Network-Object Contextual Representation (HRNet-OCR). Wildfire-related spectral indices such as normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as input channels for the deep learning models to reflect the degree of vegetation cover and surface moisture content. As a result, the mean intersection over union (mIoU) was 0.831 for U-Net and 0.848 for HRNet-OCR, showing high segmentation performance. The inclusion of spectral indices alongside the base wavelength bands resulted in increased metric values for all combinations, affirming that the augmentation of input data with spectral indices contributes to the refinement of pixels. This study can be applied to other satellite images to build a recovery strategy for fire-burnt areas.

• Journal of Venture Innovation
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• v.3 no.2
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• pp.95-109
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• 2020

The source of value-added creation in modern times has been transformed from material to man's value-added generating power, and ownership of the means of production has been converted from a particular landlord, capitalist to a person with value-added capacity, and a system of capital participation is needed beyond the profit-sharing system or performance incentive system in which workers of an enterprise participate in simple profits if they significantly increase the added value of the company. It is also necessary to introduce our private stock system as a means of addressing the problem of capital bias and for the stable development of capitalism. The purpose of Employee Stock Ownership Plans is to improve the economic and social status of workers and promote labor-management cooperation by allowing workers to acquire and hold shares of the stock company in which the employee ownership association is established through the employee ownership association, but the reality is that our stock ownership system has failed to achieve its purpose due to insufficient protection against the employee. In terms of welfare, the acquisition of our company shares should include active government support for the welfare of workers' ownership on a social welfare level rather than on the logic of the capital market, and in terms of investment, it would not be appropriate to apply the regulation for investor protection to see workers' acquisition of our company shares as 'investment' in the view of workers' willingness to own shares on the stock market. Therefore, as a way to support and deregulate employee's stock acquisition, 1. Expanding direct support, such as tax support, 2. As employee's stock ownership association is being discussed as a division's nature, it is less effective in terms of various management, not investment, and 3. Those who own stocks with 1% of the company's shares and 300 million won in face value will be classified as major shareholders. As a way to reduce the risk of management of our company owners and cooperative funds, As a measure to reduce the risk of management of our company owners and cooperative funds, only our employee shareholders' association shall manage the fund in a long-term deposit, and even though our employee's stock is managed by the association or company after the end of the deposit period, the management of each employee shall be allowed and In terms of improving the utilization of our company's stock and fund, 1. Employee's stockholders are prohibited from lending during the deposit period, but it is necessary to improve profitability by allowing them to borrow under strict restrictions, 2. It is necessary to make the use of the employee's welfare funds available for the preservation of losses, and to stipulate the redemption obligations of unlisted companies in order to improve the redemption system of our company.

• Korean Journal of Remote Sensing
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• v.39 no.5_2
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• pp.811-825
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• 2023

In accordance with the government's stance of actively promoting intelligent administrative service policies through data utilization, in the disaster and safety management field, it also is proceeding with disaster and safety management policies utilizing data and constructing systems for responding efficiently to new and complex disasters and establishing scientific and systematic safety policies. However, it is difficult to quickly and accurately grasp the on-site situation in the event of a disaster, and there are still limitations in providing information necessary for situation judgment and response only by displaying vast data. This paper focuses on deriving specific needs to make disaster situation management work more intelligent and efficient by utilizing intelligent information technology. Through individual interviews with workers at the Central Disaster and Safety Status Control Center, we investigated the scope of disaster situation management work and the main functions and usability of the geographic information system (GIS)-based integrated situation management system by practitioners in this process. In addition, the data built in the system was reclassified according to purpose and characteristics to check the status of data in the GIS-based integrated situation management system. To derive needed to make disaster situation management more intelligent and efficient by utilizing intelligent information technology, 3 strategies were established to quickly and accurately identify on-site situations, make data-based situation judgments, and support efficient situation management tasks, and implementation tasks were defined and task priorities were determined based on the importance of implementation tasks through analytic hierarchy process (AHP) analysis. As a result, 24 implementation tasks were derived, and to make situation management efficient, it is analyzed that the use of intelligent information technology is necessary for collecting, analyzing, and managing video and sensor data and tasks that can take a lot of time of be prone to errors when performed by humans, that is, collecting situation-related data and reporting tasks. We have a conclusion that among situation management intelligence strategies, we can perform to develop technologies for strategies being high important score, that is, quickly and accurately identifying on-site situations and efficient situation management work support.

• Korean Journal of Environmental Biology
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• v.41 no.3
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• pp.179-192
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• 2023

In this study, changes in the microbial ecosystem of the Yeongheungdo island coastal waters were investigated for five years to collect basic data. To evaluate the influence of distance from the coast on the microbial ecosystem, four sites, coastal Site (S1) and 0.75, 1.5, and 3 km away from the coast, were set up and the changes in physicochemical and biological factors were monitored. The results showed seasonal changes in water temperature, dissolved oxygen, salinity, and pH but with no significant differences between sites. For nutrients, the concentration of dissolved inorganic nitrogen increased from 6.4 μM in April-June to 16.4 μM in July-November, while that of phosphorus and silicon phosphate increased from 0.4 μM and 2.5 μM in April-June to 1.1 μM and 12.0 μM in July-November, respectively. Notably, phosphorus phosphate concentrations were lower in 2014-2015 (up to 0.2 μM) compared to 2016-2018 (up to 2.2 μM), indicating phosphorus limitation during this period. However, there were no differences in nutrients with distance from the coast, indicating that there was no effect of distance on nutrients. Phytoplankton (average 511 cells mL^-1) showed relatively high biomass (up to 3,370 cells mL^-1) in 2014-2015 when phosphorus phosphate was limited. Notably, at that time, the concentration of dissolved organic carbon was not high, with concentrations ranging from 1.1-2.3 mg L^-1. However, no significant differences in biological factors were observed between the sites. Although this study revealed that there was no disturbance of the ecosystem, further research and more basic data on the microecosystem are necessary to understand the ecosystem of the Incheon.

• 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.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.4
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• pp.65-76
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• 2023

In the field of technology entrepreneurship and startups, the development of Artificial Intelligence(AI) has emerged as a key topic for business model innovation. As a result, venture firms are making various efforts centered on AI to secure competitiveness(Kim & Geum, 2023). The purpose of this study is to analyze the relationship between the development of GenAI technology and the startup ecosystem by analyzing domestic news articles to identify trends in the technology startup field. Using BIG Kinds, this study examined the changes in GenAI-related news articles, major issues, and trends in Korean news articles from 1990 to August 10, 2023, focusing on the emergence of ChatGPT before and after, and visualized the relevance through network analysis and keyword visualization. The results of the study showed that the mention of GenAI gradually increased in the articles from 2017 to 2023. In particular, OpenAI's ChatGPT service based on GPT-3.5 was highlighted as a major issue, indicating the popularization of language model-based GenAI technologies such as OpenAI's DALL-E, Google's MusicLM, and VoyagerX's Vrew. This proves the usefulness of GenAI in various fields, and since the launch of ChatGPT, Korean companies have been actively developing Korean language models. Startups such as Ritten Technologies are also utilizing GenAI to expand their scope in the technology startup field. This study confirms the connection between GenAI technology and startup entrepreneurship activities, which suggests that it can support the construction of innovative business strategies, and is expected to continue to shape the development of GenAI technology and the growth of the startup ecosystem. Further research is needed to explore international trends, the utilization of various analysis methods, and the possibility of applying GenAI in the real world. These efforts are expected to contribute to the development of GenAI technology and the growth of the startup ecosystem.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.5
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• pp.77-90
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• 2023

This study aims to investigate the potential of alternative credit assessment through Social Networking Sites (SNS) as a complementary tool to conventional loan review processes. It seeks to discern the impact of SNS usage characteristics and loan product attributes on credit loan repayment. To achieve this objective, we conducted a binomial logistic regression analysis examining the influence of SNS usage patterns, loan characteristics, and personal attributes on credit loan conditions, utilizing data from Company A's credit loan program, which integrates SNS data into its actual loan review processes. Our findings reveal several noteworthy insights. Firstly, with respect to profile photos that reflect users' personalities and individual characteristics, individuals who choose to upload photos directly connected to their personal lives, such as images of themselves, their private circles (e.g., family and friends), and photos depicting social activities like hobbies, which tend to be favored by individuals with extroverted tendencies, as well as character and humor-themed photos, which are typically favored by individuals with conscientious traits, demonstrate a higher propensity for diligently repaying credit loans. Conversely, the utilization of photos like landscapes or images concealing one's identity did not exhibit a statistically significant causal relationship with loan repayment. Furthermore, a positive correlation was observed between the extent of SNS usage and the likelihood of loan repayment. However, the level of SNS interaction did not exert a significant effect on the probability of loan repayment. This observation may be attributed to the passive nature of the interaction variable, which primarily involves expressing sympathy for other users' comments rather than generating original content. The study also unveiled the statistical significance of loan duration and the number of loans, representing key characteristics of loan portfolios, in influencing credit loan repayment. This underscores the importance of considering loan duration and the quantity of loans as crucial determinants in the design of microcredit products. Among the personal characteristic variables examined, only gender emerged as a significant factor. This implies that the loan program scrutinized in this analysis does not exhibit substantial discrimination based on age and credit scores, as its customer base predominantly consists of individuals in their twenties and thirties with low credit scores, who encounter challenges in securing loans from traditional financial institutions. This research stands out from prior studies by empirically exploring the relationship between SNS usage and credit loan repayment while incorporating variables not typically addressed in existing credit rating research, such as profile pictures. It underscores the significance of harnessing subjective, unstructured information from SNS for loan screening, offering the potential to mitigate the financial disadvantages faced by borrowers with low credit scores or those ensnared in short-term liquidity constraints due to limited credit history a group often referred to as "thin filers." By utilizing such information, these individuals can potentially reduce their credit costs, whereas they are supposed to accrue a more substantial financial history through credit transactions under conventional credit assessment system.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.5
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• pp.169-185
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• 2022

This study analyzed the effect of entrepreneurial competency on entrepreneurial intentions by using the entrepreneurial opportunity recognition as a mediator for middle and middle-aged office workers. The sub-variables of entrepreneurial competency are classified into management competency, technology competency, business competency and funding competency. 222 copies of questionnaires collected from middle-aged and elderly office workers residing across the country centered on the metropolitan area were used for empirical analysis. Based on a simple mediating model with singular mediator using SPSS v22.0 and PROCESS macro v4.0. was analyzed. As a result of the analysis, first, among entrepreneurial competencies, business competency and funding capacity were found to have a positive (+) significant effect on the entrepreneurial intentions, but management and technical competency did not have a significant effect. The higher the business competency and funding competency. Second, it was found that all of the sub-variables of entrepreneurial competency had a significant effect in the positive (+) direction on the recognition of entrepreneurial opportunities. It was confirmed that management competency has the greatest influence on the entrepreneurial opportunity recognition and technology competence has the smallest effect. Third, it was found that the entrepreneurial opportunity recognition had a significant effect on entrepreneurial intentions. The discovery of an opportunity recognizing opportunities for start-up is a prerequisite for entrepreneur. Fourth, it was found that the entrepreneurial opportunity recognition mediates between the management competency, technological competency, business competency, funding competency, and entrepreneurial intention. It suggests that opportunity discovery by recognizing opportunities for entrepreneurship is a prerequisite for start-up. As implications of this study, it suggests that in order to inspire middle-aged and elderly office workers to start their own business, it is necessary to have indirect experience with education and to establish and promote a government support system for financing.. Second, It suggests that education on leadership and organizational management is particularly necessary to strengthen the opportunity recognition. Third, it suggests that the discovery of opportunities to recognize opportunities for start-up is a prerequisite for entrepreneur. Therefore, it is necessary to prepare a manual and conduct training on opportunity search, recognition, evaluation, and utilization according to the stage of opportunity development. Fourth, it suggests that in order to strengthen the intention to start a business, ALso, it is necessary to manage both the entrepreneurial competency and entrepreneurial opportunities recognition at the same time. By presenting the practical directions that can be given differentially, we intend to contribute to the provision of practical directions and policy establishment for the promotion of entrepreneurial activities of office workers who can give vitality to the ecosystem.

• 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.