• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.979-995
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• 2023

As wildfires are difficult to predict, real-time monitoring is crucial for a timely response. Geostationary satellite images are very useful for active fire detection because they can monitor a vast area with high temporal resolution (e.g., 2 min). Existing satellite-based active fire detection algorithms detect thermal outliers using threshold values based on the statistical analysis of brightness temperature. However, the difficulty in establishing suitable thresholds for such threshold-based methods hinders their ability to detect fires with low intensity and achieve generalized performance. In light of these challenges, machine learning has emerged as a potential-solution. Until now, relatively simple techniques such as random forest, Vanilla convolutional neural network (CNN), and U-net have been applied for active fire detection. Therefore, this study proposed an active fire detection algorithm using state-of-the-art (SOTA) deep learning techniques using data from the Advanced Himawari Imager and evaluated it over East Asia and Australia. The SOTA model was developed by applying EfficientNet and lion optimizer, and the results were compared with the model using the Vanilla CNN structure. EfficientNet outperformed CNN with F1-scores of 0.88 and 0.83 in East Asia and Australia, respectively. The performance was better after using weighted loss, equal sampling, and image augmentation techniques to fix data imbalance issues compared to before the techniques were used, resulting in F1-scores of 0.92 in East Asia and 0.84 in Australia. It is anticipated that timely responses facilitated by the SOTA deep learning-based approach for active fire detection will effectively mitigate the damage caused by wildfires.

• Korea Trade Review
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• v.48 no.4
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• pp.303-320
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• 2023

Recently, import and export companies have been using T/T remittance and Surrender B/L more frequently than L/C when selecting the process and method of trade payment settlement. The new trade and logistics environment is thriving in the era of the Fourth Industrial Revolution (4IR). Document-based trade transactions are undergoing a digitalization as bills of lading or smart contracts are being developed. The purpose of this study is to verify whether exporters choose export payment types based on negotiating factors. In addition, we would like to discuss the application of the characteristics of the new trade and logistics environment. Data for analysis was collected through surveys. The collection method consisted of direct visits to the company, e-mail, fax, and online surveys. The survey distribution period is from February 1, 2023, to April 30, 2023. The questionnaire was distributed in 2,000 copies, and 447 copies were collected. The final 336 copies were used for analysis, excluding 111 copies that were deemed inappropriate for the purpose of this study. The results of the study are shown below. First, among the negotiating factors, the product differentiation of exporters did not significantly affect the selection of export payment types. Second, among the negotiating factors, the greater the purchasing advantage recognized by exporters, the higher the possibility of using the post-transfer method. In addition to analyzing the results, this study suggests that exporters should consider adopting new payment methods, such as blockchain technology-based bills of lading and trade finance platforms, to adapt to the characteristics of the evolving trade and logistics environment. Therefore, exporters should continue to show interest in initiatives aimed at digitizing trade documents as a response to the challenges posed by bills of lading. In future studies, it is necessary to address the lack of social awareness in Korea by conducting advanced research abroad.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.229-256
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• 2023

The increase in telecommuting and household electricity demand due to the pandemic has led to significant changes in electricity demand patterns. This has led to difficulties in identifying KEPCO's PPA (power purchase agreements) and residential solar power generation and has added to the challenges of electricity demand forecasting and grid operation for power exchanges. Unlike other energy resources, electricity is difficult to store, so it is essential to maintain a balance between energy production and consumption. A shortage or overproduction of electricity can cause significant instability in the energy system, so it is necessary to manage the supply and demand of electricity effectively. Especially in the Fourth Industrial Revolution, the importance of data has increased, and problems such as large-scale fires and power outages can have a severe impact. Therefore, in the field of electricity, it is crucial to accurately predict the amount of power generation, such as renewable energy, along with the exact demand for electricity, for proper power generation management, which helps to reduce unnecessary power production and efficiently utilize energy resources. In this study, we reviewed the renewable energy generation forecasting system, its objectives, and practical applications to construct optimal aggregated power resources using data from 169 power plants provided by the Ministry of Trade, Industry, and Energy, developed an aggregation algorithm considering the settlement of the forecasting system, and applied it to the analytical logic to synthesize and interpret the results. This study developed an optimal aggregation algorithm and derived an aggregation configuration (Result_Number 546) that reached 80.66% of the maximum settlement amount and identified plants that increase the settlement amount (B1783, B1729, N6002, S5044, B1782, N6006) and plants that decrease the settlement amount (S5034, S5023, S5031) when aggregating plants. This study is significant as the first study to develop an optimal aggregation algorithm using aggregated power resources as a research unit, and we expect that the results of this study can be used to improve the stability of the power system and efficiently utilize energy resources.

• 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.5
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• pp.17-32
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• 2023

The entrepreneurial activities of college students play a significant role in modern economic and social development, particularly as a solution to the changing economic landscape and youth unemployment issues. Introducing innovative ideas and technologies into the market through entrepreneurship can contribute to sustainable economic growth and social value. Additionally, the entrepreneurial intentions of college students are shaped by various factors, making it crucial to deeply understand and appropriately support these elements. To this end, this study systematically explores the importance and impact of role models through a multiple serial mediation analysis. Through a survey of 300 college students, the study analyzed how two psychological variables, growth mindset and entrepreneurial self-efficacy, mediate the influence of role models on entrepreneurial intentions. The presence and success stories of role models were found to enhance the growth mindset of college students, which in turn boosts their entrepreneurial self-efficacy and ultimately strengthens their entrepreneurial intentions. The analysis revealed that exposure to role models significantly influences the formation of a growth mindset among college students. This mindset fosters a positive attitude towards viewing challenges and failures in entrepreneurship as learning opportunities. Such a mindset further enhances entrepreneurial self-efficacy, thereby strengthening the intention to engage in entrepreneurial activities. This research offers insights by integrating various theories, such as mindset theory and social learning theory, to deeply understand the complex process of forming entrepreneurial intentions. Practically, this study provides important guidelines for the design and implementation of college entrepreneurship education. Utilizing role models can significantly enhance students' entrepreneurial intentions, and educational programs can strengthen students' growth mindset and entrepreneurial self-efficacy by sharing entrepreneurial experiences and knowledge through role models. In conclusion, this study provides a systematic and empirical analysis of the various factors and their complex interactions that impact the entrepreneurial intentions of college students. It confirms that psychological factors like growth mindset and entrepreneurial self-efficacy play a significant role in shaping entrepreneurial intentions, beyond mere information or technical education. This research emphasizes that these psychological factors should be comprehensively considered when developing and implementing policies and programs related to college entrepreneurship education.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.5
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• pp.63-75
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• 2023

This study conducted empirical analysis on the factors affecting the investment performance of 205 domestic venture funds (with a total liquidation amount of 7.25 trillion KRW) newly formed from 2007 to 2017 and completely liquidated as of the end of 2022. Due to the nature of private equity funds, obtaining empirical data is extremely challenging, especially for data post-COVID-19 era liquidations. Nevertheless, despite these challenges, it is meaningful to analyze the impact on the investment returns of domestic venture funds using the most recent data available from the past 10 years. This study categorized the factors influencing venture fund performance into external environmental factors and internal factors. External environmental factors included "economic cycles," "stock markets," "venture markets," and "exit markets," while internal factors included the fund management company's capabilities in terms of "experience," "professional personnel," and "assets under management (AUM)." The fund structure was also categorized into "fund size" and "fund length" for comparative analysis. In summary, the analysis yielded the following results: First, the 3-year government bond yield, which represents economic cycles well, was found to have a significant impact on fund performance. Second, the average 3-month KOSDAQ index return after fund formation had a statistically significant positive effect on fund performance. Third, the number of IPOs, indicating the competition intensity at the time of venture fund liquidation, was shown to have a negative effect on fund performance. Fourth, it was observed that the larger the AUM of the fund management company, the better the fund's returns. Finally, venture fund returns showed variations depending on the year of formation (Vintage). Therefore, when individuals consider investing in venture funds, it is considered a highly effective investment strategy to construct an investment portfolio taking into account not only external environmental factors and internal fund factors but also the vintage year.

• 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.1
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• pp.89-106
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• 2022

Recently, in Korea, the number of unemployed people who have lost their jobs involuntarily due to closure of workplaces, layoffs, and poor management stood at 788,000 in October 21, an increase of 44,000 from last August (Statistics Office, 2021). The average retiring age of workers is 49.7, so regardless of their intention, they often end up retiring early unavoidably. Meanwhile, it has been found that eight out of ten workers have startup intention; therefore, now their startup is regarded to be essential, not selective. The purpose of this study is to investigate if workers' entrepreneurial orientation, continuous learning, satisfaction with remuneration, and employment prospect are correlated with entrepreneurial intention and examine if innovative behavior mediates the relations. To sum up the results, first, innovativeness and risk sensitivity in entrepreneurship are found to have positive effects on workers' entrepreneurial intention. Restless challenges and innovative thinking at work are crucial variables to enhance entrepreneurial intention. Second, satisfaction with remuneration influences entrepreneurial intention positive effects, and continuous learning and employment prospect, too, have positive effects on entrepreneurial intention. As employment instability is increasing at work due to the rapidly changing corporate environment, Considering whether the current organization will strive for survival or prepare to start a business for sustainable economic activity, it is judged that there is a willingness to start a business for better compensation even if the satisfaction of compensation is high. In addition, it was confirmed that the possibility of employability with the career desired by the organization as well as the securing of practical competency and expertise through continuous learning are important variables in increasing the will to start a business. Third, relations between entrepreneurial orientation, satisfaction with remuneration, continuous learning, employment prospect, and entrepreneurial intention are found to be mediated by innovative behavior; however, its mediative effect in relations between innovativeness, risk sensitivity, and entrepreneurial intention in entrepreneurship is dismissed. Innovative behavior at work are found to be major variables to elevate entrepreneurial intention in relations between continuous learning, employment prospect, and satisfaction with remuneration.

• Economic and Environmental Geology
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• v.57 no.2
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• pp.161-175
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• 2024

Aggregate typically refers to sand and gravel formed by the transportation of rocks in rivers or artificially crushed, constituting a core resource in the construction industry. Gyeongsangbuk-do, the largest administrative area in South Korea, produces various sources of gravel, including forest, land (excluding other sources), river, and crushed stone. As of 2022, it has extracted approximately 6.96 million cubic meters of aggregate, with permitted production totaling around 4.07 million cubic meters and reported production of about 2.88 million cubic meters. The aggregate demand in Gyeongsangbuk-do is estimated to be 12.39 million cubic meters according to the estimation method in Ready-Mix Concrete. From the supply perspective, about 120 extraction sites are operational, with most municipalities maintaining an appropriate balance between aggregate demand and supply. However, in some areas, there is inbound and outbound transportation of aggregate to neighboring regions. Regions with significant inbound and outbound aggregate transportation in Gyeongsangbuk-do are areas connected to Daegu Metropolitan City and Pohang City along the Gyeongbu rail line, showing a high correlation with population distribution. Gyeongsangbuk-do faces challenges such as population decline, aging rural areas, and insufficient balanced regional development. Analysis using GIS reveals these trends in gravel demand and supply. Currently in this study, Gyeongsangbuk-do meets its demand for aggregate through the supply of various aggregate sources, maintaining stable aggregate procurement. River and terrestrial aggregates may be sustained as short-term supply strategies due to the difficulty of longterm development. Considering the reliance on raw material supply for selective crushing, it suggests the need for raw material management to maintain stability. Gyeongsangbuk-do highlights quarries in the forest as an important resource for sustainable aggregate supply, advocating for the development of large-scale aggregate quarries as a long-term alternative. These research findings are expected to provide valuable insights for formulating strategies for sustainable management and stable utilization of aggregate resources.

• Journal of the Korean Institute of Landscape Architecture
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• v.52 no.2
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• pp.51-63
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• 2024

While the government policy to fully adopt BIM in the construction sector is being implemented, the construction and utilization of landscape BIM models are facing challenges due to problems such as limitations in BIM authoring tools, difficulties in modeling natural materials, and a shortage in BIM content including libraries. In particular, plants, fundamental design elements in the field of landscape architecture, must be included in BIM models, yet they are often omitted during the modeling process, or necessary information is not included, which further compromises the quality of the BIM data. This study aimed to contribute to the construction and utilization of landscape BIM models by developing a plant library that complies with BIM standards and is applicable to the landscape industry. The plant library of trees and shrubs was developed in Revit by modeling 3D shapes and collecting attribute items. The geometric information is simplified to express the unique characteristics of each plant species at LOD200, LOD300, and LOD350 levels. The attribute information includes properties on plant species identification, such as species name, specifications, and quantity estimation, as well as ecological attributes and environmental performance information, totaling 24 items. The names of the files were given so that the hierarchy of an object in the landscape field could be revealed and the object name could classify the plant itself. Its usability was examined by building a landscape BIM model of an apartment complex. The result showed that the plant library facilitated the construction process of the landscape BIM model. It was also confirmed that the library was properly operated in the basic utilization of the BIM model, such as 2D documentation, quantity takeoff, and design review. However, the library lacked ground cover, and had limitations in those variables such as the environmental performance of plants because various databases for some materials have not yet been established. Further efforts are needed to develop BIM modeling tools, techniques, and various databases for natural materials. Moreover, entities and systems responsible for creating, managing, distributing, and disseminating BIM libraries must be established.