• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.4
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• pp.40-55
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• 2023

Arbor Day is a day that encourages people to plant trees and symbolizes the timing of planting. Arbor Day has been honored on April 5th in Korea, but it often does not agree to actual planting time due to global warming. This study confirmed the discrepancy between Arbor Day and regional soil-thawing times and reviewed alternative dates for tree planting using satellite-based soil-thaw data (FT-ESDR) from 1991 to 2020. Study results showed that the start time of planting on the Korean Peninsula, which was indicated by soil-thaw dates, was March 24 during 1991-2000, and it progressively changed to March 17 during 2011-2020. Should Arbor Day be changed based on soil-thaw periods, mid-March would be the most comprehensive, suitable alternative period considering the number of governmental administration units (cities and counties) and the land area of soil-thaw. Tree-Planting Day (March 14) and International Day of Forests (March 21) were found suitable for alternative dates to Arbor Day because they were close to the average soil-thaw time of Korean Peninsula (March 19) and land area whose soil-thaw time was within 10 days from those two dates ranged from 52.5% to 58.8% centered geographically on the mid-section of the peninsula. Since the periods of soil-thaw will continue to change due to climate change, it is necessary to reflect the trend of advancing planting periods in the future if Arbor Day is changed to an earlier date.

• Journal of Industrial Convergence
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• v.21 no.12
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• pp.11-23
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• 2023

This study aims to investigate the relationship between service recovery justice, residual emotions, and customer behavior. It empirically verifies that low justice in service recovery affects residual emotions and, in turn, has an impact on customers' negative behaviors. Furthermore, this research distinguishes customer-brand relationship quality into emotional relationship quality and cognitive relationship quality and seeks to validate that the type of relationship quality may influence the extent to which the justice of recovery processes affects residual emotions. Data was collected through surveys, and hypotheses were tested using structural equation modeling. The research findings indicate that among the dimensions of service recovery justice, procedural justice and interactional justice significantly influence residual emotions. Moreover, residual emotions have a significant impact on both the intention to revisit and the intention to engage in negative word-of-mouth. In addition, the impact of distributive justice and procedural justice on residual emotions was found to be higher for cognitive relationship quality than emotional relationship quality, and the impact of interactional justice on residual emotions was found to be higher for emotional relationship quality than cognitive relationship quality.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.489-498
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• 2023

Advancements in hardware performance and computing technology have facilitated the progress of climate prediction models to address climate change. The Korea Meteorological Administration employs the GloSea6 model with supercomputer technology for operational use. Various universities and research institutions utilize the Low-GloSea6 model, a low-resolution coupled model, on small to medium-scale servers for weather research. This paper presents an analysis using Intel VTune Profiler on Low-GloSea6 to facilitate smooth weather research on small to medium-scale servers. The tri_sor_dp_dp function of the atmospheric model, taking 1125.987 seconds of CPU time, is identified as a hotspot. Nonlinear regression models, a machine learning technique, are applied and compared to existing functions conducting numerical operations. The K-Nearest Neighbors regression model exhibits superior performance with MAE of 1.3637e-08 and SMAPE of 123.2707%. Additionally, the Light Gradient Boosting Machine regression model demonstrates the best performance with an RMSE of 2.8453e-08. Therefore, it is confirmed that applying a nonlinear regression model to the tri_sor_dp_dp function during the execution of Low-GloSea6 could be a viable alternative.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.1
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• pp.213-227
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• 2022

Recently, research on social entrepreneurship, which simultaneously pursues social value creation and economic sustainability has increased rapidly. Researchers conducted several empirical studies, noting that social entrepreneurship is a major factor in improving the performance of social enterprises. However, most previous studies usually have limitations in measuring the performance of social enterprises based on the subjective perception of entrepreneurs, which implies the limitations of the common method bias. In addition, there is a lack of empirical evidence that can explain the specific process in which the personal characteristic of an entrepreneur, social entrepreneurship, affects the achievement of dual goals. Therefore, this study empirically investigates the effect of social entrepreneurship on performance increasing the objectivity of performance measurement and including blended value orientation(BVO), a characteristic of viewing social and economic performance as a single thing. The purpose of the study is to verify the effect of social entrepreneurship and BVO on the social and economic performance of social enterprises. We conducted regression analysis using the results of the perception survey of social enterprises in South Korea and objective performance data. As a result, risk-taking, a sub-factor of social entrepreneurship, had a positive effect on economic and social performance at a significant level. In addition, it was confirmed that social entrepreneurship improves BVO, and it affects social performance. Therefore, this study found that social entrepreneurship and BVO have a discriminatory effect on economic and social performance, respectively. This study is meaningful in that it attempted to overcome the common method bias as measuring subjectivity performance.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.2
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• pp.179-193
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• 2022

This study aims to identify the relationship marketing factors and examine the mediating factors of perceived customer value on the relationship between relationship marketing factors and loyal on rural tourism. We collected and analyzed the survey data from the customers who had experienced rural tourism before. The results from the empirical analysis are as follows. First, through the exploratory factor analysis, four factors such as customer orientation, responsive attraction, professionalism, and ties were derived. Second, it was found all four factors have significant positive effects on loyalty. Third, both responsive attraction and professionalism have significant positive effects on perceived customer value. However, customer orientation and ties do not have significant effects. Fourth, the perceived customer value showed a full mediating effect between responsive attraction and loyalty, whereas it showed a partial mediating effect between professionalism and loyalty. Additionally, it was found that gender did not affect loyalty but significantly affected perceived customer value. This means that women had lower perceived value for rural tourism than men. To improve the loyalty of rural tourism, it is necessary to improve customer orientation, professionalism, ties, and perceived customer value.

• Information Systems Review
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• v.22 no.4
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• pp.21-39
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• 2020

Recently, deep learning has shown high performance in various applications such as pattern analysis and image classification. Especially known as a difficult task in the field of machine learning research, stock market forecasting is an area where the effectiveness of deep learning techniques is being verified by many researchers. This study proposed a deep learning Convolutional Neural Network (CNN) model to predict the direction of stock prices. We then used the feature selection method to improve the performance of the model. We compared the performance of machine learning classifiers against CNN. The classifiers used in this study are as follows: Logistic Regression, Decision Tree, Neural Network, Support Vector Machine, Adaboost, Bagging, and Random Forest. The results of this study confirmed that the CNN showed higher performancecompared with other classifiers in the case of feature selection. The results show that the CNN model effectively predicted the stock price direction by analyzing the embedded values of the financial data

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.6
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• pp.27-40
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• 2023

This study analyzes the factors affecting the survival of young start-up companies. A youth start-up company was defined as a company with a founder's age under 39. The study was based on evaluation data from 3,540 companies evaluated by the Technology Guarantee Fund to support youth start-up guarantees during the period from 2012 to 2015. In this study, independent variables were defined as founder characteristics, start-up environment, and start-up strategy, and entrepreneurship, knowledge level, and development capabilities were set as variables for start-up characteristics, competition conditions and comparative advantage with alternatives in the start-up environment, and item novelty, commercialization plan and financing plan were set as variables. For variable measurement, the evaluation index of the youth start-up evaluation model of the Technology Guarantee Fund was used. Management performance was defined as the survival of a company, and the survival of 12, 36, 60, and 84 months was measured based on the occurrence of insolvency registered by the Korea Technology Guarantee Fund. The Cox proportional risk model was used for hypothesis testing. As a result of the analysis, knowledge level and development capability were statistically significant in the characteristics of the founder, and the financing plan in the start-up strategy was statistically significant regardless of the survival period. Among the start-up strategies, the novelty of the item had a positive effect on survival after 36 months. Entrepreneurship was significant only in 12-month survival. The most important order for survival was identified in the order of financing plan, knowledge level, item novelty and development capability, of which the founder's knowledge level in the beginning and the funding plan in the second half had the greatest impact.

• Korean Journal of Plant Resources
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• v.37 no.1
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• pp.62-70
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• 2024

Fruit thinning rate and characteristics were investigated for three years on seven promising pear (Pyrus pyrifolia Nakai) cultivars, which were treated by lime-sulfur as an eco-chemical thinning substance. Lime-sulfur was treated twice at the second and third days after full bloom by cultivar. Most of pear cultivars were significantly thinned by lime-sulfur compounds. Especially 'Whangkeumbae', 'Supergold' and 'Hanareum' exhibited high flower thinning rates, 41.5%, 40.1% and 39.9%, respectively. As weather conditions at the lime-sulfur treatment, insolation and cloud amount were correlated with flower thinning rate but not significant (r = 0.49 and r = -0.45, respectively). These results suggest that lime-sulfur is suitable for reducing labor force for flower thinning of Korean pears but flower thinning effects of lime-sulfur can vary depending on other factors such as environmental conditions. This information will provide useful data for low labor force cultivation of Korean pear cultivars.

• Journal of Dental Anesthesia and Pain Medicine
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• v.24 no.3
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• pp.187-193
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• 2024

Background: Patients with autism spectrum disorder (ASD) present challenges in dental treatment cooperation owing to deficits in communication skills and social interaction. Behavioral guidance, sedation, and general anesthesia may be employed to ensure the quality of dental care for individuals with ASD. This study aimed to examine the trends in dental treatment for patients with ASD who visited the Department of Pediatric Dentistry at Dankook University Jukjeon Dental Hospital, an oral health center for the disabled in the Gyeonggi region, over the past 10 years. Methods: This study utilized the order communication system to gather data on sex, age, cooperation level, number of quadrants treated, and administration of sedation or general anesthesia for patients with ASD who visited the Department of Pediatric Dentistry at Dankook University Jukjeon Dental Hospital between January 2013 and December 2022. Results: The total number of patients with ASD increased annually, possibly due to an increase in ASD prevalence and the hospital's designation as a center for disabled oral health. General anesthesia was predominant before 2017, with a shift towards N₂O-O₂ sedation. The most common age group for sedation or general anesthesia was 6-9 years, with a higher prevalence in males than in females. Notably, N₂O-O₂ and midazolam sedation resulted in better cooperation and fewer treated teeth than general anesthesia. Conclusion: This study highlights the evolving trends in dental treatment for individuals with ASD, indicating a shift towards outpatient methods, particularly N₂O-O₂ sedation. The sex distribution aligns with national statistics, emphasizing a higher prevalence of ASD in males than in females. These findings underscore the need for further research to establish evidence-based guidelines for optimal dental care strategies tailored to the unique needs of individuals with ASD.

• Journal of Industrial Convergence
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• v.22 no.5
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• pp.23-37
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• 2024

The purpose of this study is to investigate various factors affecting the relationship between digital leadership and digital transformation in companies. In particular, focusing on the mediating effect of dynamic digital capabilities that quickly sensing and seizing advanced and convergent digital technologies and apply them to the organization, this study also intends to examine the moderating effect of the organization's acceptance intention. The hypotheses were verified with a sample of 258 copies of data collected by conducting a survey on companies participating in mini-clusters in industrial complexes nationwide. As a result of the study, dynamic digital capabilities showed a significant mediating effect in the relationship between digital leadership and digital transformation, and the effect of dynamic digital capabilities on the level of digital transformation differed according to the organization's digital acceptance intention. This study presented a new concept and measurement items of digital dynamic capabilities, and how to consider digital leadership, dynamic digital capabilities and acceptance level of organization when promoting digital transformation in companies.