• Journal of Korean Society of Forest Science
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• v.112 no.4
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• pp.426-441
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• 2023

This study investigated the predictive accuracy of a model of landslide displacement in Jecheon-si, where a great number of landslides were triggered by heavy rain on both natural (non-clear-cut) and clear-cut slopes during August 2020. This was accomplished by applying three flow direction methods (single flow direction, SFD; multiple flow direction, MFD; infinite flow direction, IFD) and the degree of root cohesion to an infinite slope stability equation. The application assumed that the soil saturation and any changes in root cohesion occurred following the timber harvest (clear-cutting). In the study area, 830 landslide locations were identified via landslide inventory mapping from satellite images and 25 cm resolution aerial photographs. The results of the landslide modeling comparison showed the accuracy of the models that considered changes in the root cohesion following clear-cutting to be improved by 1.3% to 2.6% when compared with those not considered in the area under the receiver operating characteristics (AUROC) analysis. Furthermore, the accuracy of the models that used the MFD algorithm improved by up to 1.3% when compared with the models that used the other algorithms in the AUROC analysis. These results suggest that the discriminatory application of the root cohesion, which considers changes in the vegetation condition, and the selection of the flow direction method may influence the accuracy of landslide predictive modeling. In the future, the results of this study should be verified by examining the root cohesion and its dynamic changes according to the tree species using the field hydrological monitoring technique.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.933-948
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• 2023

Atmospheric aerosols not only have adverse effects on human health but also exert direct and indirect impacts on the climate system. Consequently, it is imperative to comprehend the characteristics and spatiotemporal distribution of aerosols. Numerous research endeavors have been undertaken to monitor aerosols, predominantly through the retrieval of aerosol optical depth (AOD) via satellite-based observations. Nonetheless, this approach primarily relies on a look-up table-based inversion algorithm, characterized by computationally intensive operations and associated uncertainties. In this study, a novel high-resolution AOD direct retrieval algorithm, leveraging machine learning, was developed using top-of-atmosphere reflectance data derived from the Geostationary Ocean Color Imager-II (GOCI-II), in conjunction with their differences from the past 30-day minimum reflectance, and meteorological variables from numerical models. The Light Gradient Boosting Machine (LGBM) technique was harnessed, and the resultant estimates underwent rigorous validation encompassing random, temporal, and spatial N-fold cross-validation (CV) using ground-based observation data from Aerosol Robotic Network (AERONET) AOD. The three CV results consistently demonstrated robust performance, yielding R²=0.70-0.80, RMSE=0.08-0.09, and within the expected error (EE) of 75.2-85.1%. The Shapley Additive exPlanations(SHAP) analysis confirmed the substantial influence of reflectance-related variables on AOD estimation. A comprehensive examination of the spatiotemporal distribution of AOD in Seoul and Ulsan revealed that the developed LGBM model yielded results that are in close concordance with AERONET AOD over time, thereby confirming its suitability for AOD retrieval at high spatiotemporal resolution (i.e., hourly, 250 m). Furthermore, upon comparing data coverage, it was ascertained that the LGBM model enhanced data retrieval frequency by approximately 8.8% in comparison to the GOCI-II L2 AOD products, ameliorating issues associated with excessive masking over very illuminated surfaces that are often encountered in physics-based AOD retrieval processes.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1009-1029
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• 2023

Urban trees play a vital role in urban ecosystems,significantly reducing impervious surfaces and impacting carbon cycling within the city. Although previous research has demonstrated the efficacy of employing artificial intelligence in conjunction with airborne light detection and ranging (LiDAR) data to generate urban tree information, the availability and cost constraints associated with LiDAR data pose limitations. Consequently, this study employed freely accessible, high-resolution multispectral satellite imagery (i.e., Sentinel-2 data) to estimate fractional tree canopy cover (FTC) within the urban confines of Suwon, South Korea, employing machine learning techniques. This study leveraged a median composite image derived from a time series of Sentinel-2 images. In order to account for the diverse land cover found in urban areas, the model incorporated three types of input variables: average (mean) and standard deviation (std) values within a 30-meter grid from 10 m resolution of optical indices from Sentinel-2, and fractional coverage for distinct land cover classes within 30 m grids from the existing level 3 land cover map. Four schemes with different combinations of input variables were compared. Notably, when all three factors (i.e., mean, std, and fractional cover) were used to consider the variation of landcover in urban areas(Scheme 4, S4), the machine learning model exhibited improved performance compared to using only the mean of optical indices (Scheme 1). Of the various models proposed, the random forest (RF) model with S4 demonstrated the most remarkable performance, achieving R² of 0.8196, and mean absolute error (MAE) of 0.0749, and a root mean squared error (RMSE) of 0.1022. The std variable exhibited the highest impact on model outputs within the heterogeneous land covers based on the variable importance analysis. This trained RF model with S4 was then applied to the entire Suwon region, consistently delivering robust results with an R² of 0.8702, MAE of 0.0873, and RMSE of 0.1335. The FTC estimation method developed in this study is expected to offer advantages for application in various regions, providing fundamental data for a better understanding of carbon dynamics in urban ecosystems in the future.

• Journal of Life Science
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• v.33 no.12
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• pp.995-1001
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• 2023

This study investigated the effects of three music genres (classical, new age, and rock) on the stress levels of six Jeju crossbred horses (Jeju horse × Thoroughbred) in a horse stable. The horses were exposed to the three genres for seven days, and their stress levels were measured by analyzing physiological markers, including neurotransmitter (cortisol, β-endorphin, dopamine, serotonin, and oxytocin) plasma levels and creatine phosphokinase (CPK) and aldolase serum levels. The neurotransmitter analysis showed significant differences in cortisol levels between classical and new age music exposure. Dopamine levels decreased significantly only with new age exposure. Although there were no significant differences in β-endorphin levels between the three genres, β-endorphin levels decreased with increasing classical and new age music playback times and increased with increasing rock music playback times. There were no significant differences in serotonin levels between the three genres. Oxytocin levels decreased significantly with exposure to classical and rock music. The CPK and aldolase analyses showed that CPK levels decreased significantly only with exposure to new age music and increased after playback ended, while aldolase levels decreased significantly with classical and new age music exposure and increased after playback ended. These findings suggest that classical music and new age are the optimal music genres for the psychological stability of Jeju crossbred horses. Playing back an appropriate music genre could be used to improve breeding and promote the welfare of Jeju crossbred horses.

• Korean Journal of Culture and Social Issue
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• v.29 no.4
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• pp.537-567
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• 2023

This study compared the nature of disgust caused by the crime scene with that by the stereotype of the sexual-minority defendant, and compared the effect of each type of disgust on evidence evaluation and legal judgment. A total of 600 participants (300 men, average age of 44.40) were randomly assigned to sources of disgust (crime scene, sexual minorities defendant, control condition), the existence of additional evidence of innocence (o/x), and the existence of judicial directives (o/x). As a result of the study, disgust under the condition of a cruel crime scene with strong physical disgust was significantly higher than that of the sexual minority defendant, interpreted the evidence in a more guilty direction, and was more prone to_evaluate that the defendant was guilty. It is noteworthy that evidence evaluation was a significant moderating variable between disgust and probability of guilt under conditions where the source of disgust was a sexual minority, but not under control conditions and crime scene condition. It means that the effect of disgust on legal judgment may not be direct when the defendant is a sexual minority. In addition, the existence of the judicial instruction had a significant inverse effect on the sentence. And simple effect analysis found that presenting judicial instruction lowered probability of guilt only under the control condition. This makes it reasonable to infer that disgust derived from the characteristics of the crime scene and the defendant can be recognized as integral emotions that are difficult to correct with instructions. Finally, pity for the defendant was significantly higher under the conditions of sexual minority which shows that an emotional response of sympathy may occur in addition to disgust for sexual minorities. After examining the nature of disgust (physical & moral), legal judgment according to the source and degree of disgust was reviewed. In addition, the meaning of disgust and sympathy for the sexual minority defendant was discussed.

• Korean Journal of Environmental Biology
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• v.41 no.3
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• pp.325-334
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• 2023

The invasive red swamp crayfish, Procambarus clarkii, is native to south-central United States and northeastern Mexico. Recently, it has been being spreading in the wild in South Korea. However, its primary sources, introduction routes, establishment, and expansion in South Korea remain unclear. Here, we analyzed genetic diversity and population genetic structures of its domestic natural populations during early invasion, commercial stock from local aquaria (a suspected introduction source), and original United States population using mitochondrial COI gene sequences for 267 individuals and eight microsatellite markers for 158 individuals. Natural and commercial populations of P. clarkii showed reduced genetic diversity (e.g., haplotype diversity and allelic richness). The highest genetic diversity was observed in one original source population based on both genetic markers. Despite a large number of individuals in commercial aquaria, we detected remarkably low genetic diversity and only three haplotypes among 226 individuals, suggesting an inbred population likely originating from a small founder group. Additionally, the low genetic diversity in the natural population indicates a small effective population size during early establishment of P. clarkii in South Korea. Interestingly, genetic differentiation between natural populations and the United States population was lower than that between natural populations and aquarium populations. This suggests that various genetic types from the United States likely have entered different domestic aquariums, leading to distinct natural populations through separate pathways. Results of our study will provide an insight on the level of genetic divergence and population differentiation during the initial stage of invasion of non-indigenous species into new environments.

• Journal of Mushroom
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• v.21 no.4
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• pp.254-260
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• 2023

The characteristics and spore production of Gonji7ho, Bunhong, and Sunjung fruiting bodies were assessed at different growth stages. The shape of the Pleurotus species fruiting body starts out short and small, then takes on a typical mushroom shape as it grows. Gonji7ho has a long stalk, Bunhong has a short stalk and a wide cap, and Sunjung's cap and stalk dimensions are intermediate. Each variety displayed deep color at the beginning of growth but became steadily lighter with continued growth. The shape of the linkage between the mushroom stalk and cap changed from an initial central position to a lateral position after the growing stage. Gonji7ho cap diameter increased 7-fold from 15.5 mm (5 days of growth) to 37.9 mm (9 days of growth). Growth rates for each growth day measured using the growth percentage of the previous day were 285.5% (5 → 6th day), 182.2% (6 → 7th day), 129.4% (7 → 8th day), and 103.8% (8 → 9th day). This trend was also observed in Bunhong and Sunjung, but Bunhong's growth rate was more rapid (4.9 fold on day 6, 2.7 fold on day 7) and continued to increase through day 9. Harvest yield, which is of greatest interest to farmers, displayed a similar trend spanning the growth period, as did cap diameter. Gonji7ho harvest yield increased rapidly until day 7 of growth (more than 177%), then growth slowed down beginning around day 8, and further decreased on day 9 (98%). Similar trends were observed in Bunhong and Sunjung. Bunhong showed characteristic rapid growth in harvest yield (4.9 fold compared to the previous day on day 6 and 2.7 fold on day 7), and the increase continued through day 9. A decrease in mushroom harvest yield commonly seen in the late growth stage is thought to be due to the death of some mushrooms and decomposition of cap tissue. Basidiospore content increased with number of growth days but decreased after day 8. Gonji7ho yielded the highest production on day 7 of growth, coinciding with harvest time, with 209,000,000 spores. This trend was also observed in Bunhong and Sunjung. These results will provide researchers with basal data and guide farmers in selecting the optimal harvest day.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.1
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• pp.203-223
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• 2023

Recently, the platform industry is rapidly growing in the global market, and competition is intensifying at the same time. Therefore, in order for domestic platform companies to have global competitiveness in the platform market, it is necessary to study the platform business ecosystem and success factors. However, most of the recent platform-related studies have been theoretical studies on the characteristics of platform business status analysis, platform economy, and indirect network externalities of platforms. Therefore, this study comprehensively analyzed the success factors of Silicon Valley's business ecosystem proposed in previous studies, and at the same time analyzed the success factors extracted from stakeholders in the actual Silicon Valley platform business ecosystem. And based on these factors, an IPA analysis was conducted as a way to propose a success plan to stakeholders in the platform business ecosystem. As a result of the analysis, among the success factors collected through previous studies, manpower, capital, and challenge culture were identified as factors that are relatively well maintained in both importance and satisfaction in Silicon Valley. In the end, it can be seen that the creation of an environment and culture in which Silicon Valley can use it to challenge itself based on excellent human resources and abundant capital contributes the most to the success of Silicon Valley's platform business. On the other hand, although it is of high importance to Silicon Valley's platform corporate ecosystem, the factors that show relatively low satisfaction among stakeholders are 'learning and benchmarking among active companies' and 'strong ties and cooperation between members', and it is analyzed that interest and effort are needed to strengthen these factors in the future. Finally, the systems and policies necessary for market autonomous competition, 'business support service industry', 'name value', and 'spin-off start-up' were important factors in literature research, but the importance and satisfaction of these factors were lowered due to changes in the times and environment. This study has academic implications in that it comprehensively analyzes the success factors of Silicon Valley's business ecosystem proposed in previous studies, and at the same time analyzes the success factors extracted from stakeholders in the actual Silicon Valley platform business ecosystem. In addition, there is another academic implications that importance and satisfaction were simultaneously examined through IPA analysis based on these various extracted factors. As for academic implications, it is meaningful in that it contributed to the formation of the domestic platform ecosystem by providing the government and companies with concrete information on the success factors of the platform business ecosystem and the theoretical grounds for the growth of domestic platform businesses.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.6
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• pp.195-208
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• 2022

The role of venture CEO and their intrinsic capabilities on organizational performance can be determined by the level of resource synchronization initiated by the focal managers. Despite the important role of venture CEOs, a systematic lack of in-depth theoretical and empirical studies on ruminating the relationship between the effects of a CEO's capabilities and organizational performance depending on the level of resource synchronization exist for the rationale of investigation. To supplement the limitations of previous studies, this research empirically analyzes the role of managers specifically synchronizing organizational resources that affect organizational performance in the professional sports industry. Based on the entrepreneurship theory and resource-based view (RBV), this research conceptualizes the roles of venture CEO and basketball head coach in the professional sports industry as very similar in terms of organizational structure and performance mechanism embedding entrepreneurial characteristics necessary for managing organizational resources. In this research, we hypothesized (1) organizational resource synchronization will mediate the positive relationship between the ability of professional basketball head coach and organizational performance and (2) the indirect effect of the professional basketball head coach's capabilities on organizational performance mediated by resource synchronization will be moderated by the capabilities of players. To test these hypotheses, we utilized the PROCESS macro model 58 with the empirical data of 9 seasons (2013~2014-2021~2022) of 30 National Basketball Association (NBA) and 10 Korean Basketball League (KBL) teams. The statistical results showed that (1) resource synchronization mediates the positive relationship between professional basketball head coach capabilities and organizational performance and (2) the capabilities of players moderated the indirect effects of the abilities of head coaches on team performance via resource synchronization. This paper contributes to both academic and practical domains of entrepreneurship by empirically testing the research model through objective professional sports data.