• Journal of Wetlands Research
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• v.25 no.2
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• pp.159-165
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• 2023

This study measured the ecological niche overlap between two deciduous oak species(Quercus acutissmia and Q. dentata) according to the change in growth responses after treating with the moisture and nutrient contents of the soil at four gradients, and interpreted the degree of competition between the two oak species by ordination method. In the moisture environment gradient, the ecological niche overlap of the two species was high in the photosynthesis-related leaf organs and low in plant architecture such as shoot length. In addition, in case of competition between two oaks, Q. dentata was remarkably dominant in soil moisture gradient, but Q. acutissimia slightly was slightly advantageous over Q. dentata in the soil nutrient gradient. These results show that even in a similar taxonomical group growing in a similar habitat, the response to the organ system of the plant varies depending on the type of environment factor, resulting in different competitive differences among plants.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.419-437
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• 2023

As the number of thin filers in Korea surpasses 12 million, there is a growing interest in enhancing the accuracy of assessing their credit default risk to generate additional revenue. Specifically, researchers are actively pursuing the development of default prediction models using machine learning and deep learning algorithms, in contrast to traditional statistical default prediction methods, which struggle to capture nonlinearity. Among these efforts, Graph Neural Network (GNN) architecture is noteworthy for predicting default in situations with limited data on thin filers. This is due to their ability to incorporate network information between borrowers alongside conventional credit-related data. However, prior research employing graph neural networks has faced limitations in effectively handling diverse categorical variables present in credit information. In this study, we introduce the Transformer embedded Graph Convolutional Network (TeGCN), which aims to address these limitations and enable effective default prediction for thin filers. TeGCN combines the TabTransformer, capable of extracting contextual information from categorical variables, with the Graph Convolutional Network, which captures network information between borrowers. Our TeGCN model surpasses the baseline model's performance across both the general borrower dataset and the thin filer dataset. Specially, our model performs outstanding results in thin filer default prediction. This study achieves high default prediction accuracy by a model structure tailored to characteristics of credit information containing numerous categorical variables, especially in the context of thin filers with limited data. Our study can contribute to resolving the financial exclusion issues faced by thin filers and facilitate additional revenue within the financial industry.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.6
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• pp.199-206
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• 2017

The experience sampling method (ESM) is an innovative research method to study the immediate real emotional experience experienced in real life through the immediate reaction of research participants. ESM, which has received significant attention in recent, is considered as the research method particularly for child care teachers' emotions and happiness. This method has been shown to be able to overcome the limitations in current research methods, based on teachers' recall or surveys, in assessing child care teachers' emotional states or stress levels. Despite the expectation that the need for further research on the increased stress and negative emotional experiences of child care teachers and its appropriateness as the alternative research method to study child care teachers' immediate emotional experience, ESM has deficiencies in that research participants need to have their pencil-and-paper survey packages on hand whenever their electronic beepers randomly beep. Furthermore, ESM demands much more researcher energy and efforts to handle the voluminous data collected from each participant in effectively creating a database. In this paper, in order to apply ESM successfully to the study of child care teachers' emotional experience, we aim to develop a software program that uses mobile communication technology. Given that traditional types of data collection methods in social science research can prove too burdensome to encourage participation in surveys in the first place or ensure the return of completed surveys, the present study adopts a convergent research approach to develop a software program that is able to obtain ESM participants' answers immediately on their personal smart phones. This study deals with system construction and prototyping for software development as a basic research and evaluates the research results through indepth interview with experts.

• International Journal of Computer Science & Network Security
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• v.22 no.1
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• pp.340-346
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• 2022

The article examines the formation of the scientific paradigm of transformation of the potential-forming space of the regional economy under the influence of intellectual and innovative determinants. Based on the study of different scientific views on the nature and properties of potential-forming space through the study of approaches to understanding the concept of "space" clarified the complexity and multifaceted nature of the phenomenon and found that its characteristics are relevant to the industrial development model. It is revealed that the leading modern trends related to the spread of globalization and regionalization, rapid development of information and communication technologies, diffusion of innovations accompany the transition from industrial to post-industrial development and its development, which leads to new development: changes production, nature and relations between business entities, etc. It is proved that under such conditions, the region as a key element of the economic system, acquires a leading role in achieving sustainable and balanced development. These processes significantly affect the potential-forming space of the regional economy under the influence of intellectual and innovative determinants, leading to the need for its transformation and change in accordance with modern realities, which is reflected in thorough research on the formation of scientific paradigm based on the formation of its theoretical foundations and methodological basis. This study reveals the essence, role, functions, structure, process of formation of the scientific paradigm of transformation of the potential-forming space of the regional economy under the influence of intellectual and innovative determinants. It is proved that the formation of the modern scientific paradigm of transformation of the potential-forming space of the regional economy under the influence of intellectual and innovative determinants occurs in the context of building a post-industrial model of development, accompanied by consideration of the region as a spatial object territories from the physical plane to the spatial environment in which the development of human capital, innovation and self-development of the region. Taking into account the above, the article outlines the prerequisites and factors of formation of the scientific paradigm of transformation of the potential-forming space of the regional economy under the influence of intellectual and innovative determinants.

• Korean Journal of Construction Engineering and Management
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• v.24 no.6
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• pp.66-73
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• 2023

The construction industry suffers losses due to failures in demand forecasting due to price fluctuations in construction raw materials, increased user costs due to project cost changes, and lack of forecasting system. Accordingly, it is necessary to improve the accuracy of construction raw material price forecasting. This study aims to predict the price of construction raw materials and verify applicability through the improvement of the Data Refactor technique. In order to improve the accuracy of price prediction of construction raw materials, the existing data refactor classification of low and high frequency and ARIMAX utilization method was improved to frequency-oriented and ARIMA method utilization, so that short-term (3 months in the future) six items such as construction raw materials lumber and cement were improved. ), mid-term (6 months in the future), and long-term (12 months in the future) price forecasts. As a result of the analysis, the predicted value based on the improved Data Refactor technique reduced the error and expanded the variability. Therefore, it is expected that the budget can be managed effectively by predicting the price of construction raw materials more accurately through the Data Refactor technique proposed in this study.

• Korean Journal of Plant Resources
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• v.37 no.1
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• pp.79-86
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• 2024

This study was conducted to determine the conditions for breaking dormancy in the seeds of the North Korean plant resource, Trollius macropetalus, and to investigate its germination characteristics. The morphological characteristics and viability of T. macropetalus seeds were examined. Germination characteristics were investigated based on temperature conditions (15/6℃ & 25/15℃), cold stratification treatment, and GA₃ treatment. The results showed that cold stratification treatment had no effect on breaking the dormancy of T. macropetalus. GA₃ treatment significantly increased the germination rate of T. macropetalus and also improved the mean germination days and germination speed. However, compared to the 15/6℃ condition, the effectiveness of GA₃ treatment for T. macropetalus decreased under the 25/15℃ condition. It was determined that T. macropetalus have a nondeep-type morpho-physiological dormancy. The most effective conditions for breaking dormancy were found to be the 15/6℃ temperature condition and GA₃ treatment at 500 mg·L^-1. The findings of this study are expected to provide valuable information for the mass propagation of T. macropetalus, which has potential applications in landscaping and pharmaceutical materials.

• Journal of Korean Society of Rural Planning
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• v.30 no.2
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• pp.13-24
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• 2024

This study conducts an analysis of social media big data pertaining to island tourism resources, aiming to discern the diverse forms and categories of island tourism favored by consumers, ascertain predominant resources, and facilitate objective decision-making grounded in scientific methodologies. To achieve this objective, an examination of blog posts published on Naver from 2022 to 2023 was undertaken, utilizing keywords such as 'Island tourism', 'Island travel', and 'Island backpacking' as focal points for analysis. Text mining techniques were applied to sift through the data. Among the resources identified, the port emerged as a significant asset, serving as a pivotal conduit linking the island and mainland and holding substantial importance as a focal point and resource for tourist access to the island. Furthermore, an analysis of the disparity between existing island tourism resources and those acknowledged by tourists who actively engage with and appreciate island destinations led to the identification of 186 newly emerging resources. These nascent resources predominantly clustered within five regions: Incheon Metropolitan City, Tongyeong/Geoje City, Jeju Island, Ulleung-gun, and Shinan-gun. A scrutiny of these resources, categorized according to the tourism resource classification system, revealed a notable presence of new resources, chiefly in the domains of 'rural landscape', 'tourist resort/training facility', 'transportation facility', and 'natural resource'. Notably, many of these emerging resources were previously overlooked in official management targets or resource inventories pertaining to existing island tourism resources. Noteworthy examples include ports, beaches, and mountains, which, despite constituting a substantial proportion of the newly identified tourist resources, were not accorded prominence in spatial information datasets. This study holds significance in its ability to unearth novel tourism resources recognized by island tourism consumers through a gap analysis approach that juxtaposes the existing status of island tourism resource data with techniques utilizing social media big data. Furthermore, the methodology delineated in this research offers a valuable framework for domestic local governments to gauge local tourism demand and embark on initiatives for tourism development or regional revitalization.

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.4
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• pp.303-314
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• 2024

Recently, the consecutive shield tunnel boring machine (TBM) has gained attention for its potential to enhance TBM penetration rates. However, its development requires a thorough risk assessment due to the unconventional nature of its equipment and hydraulic systems, coupled with the absence of design or construction precedents. This study investigated the causal relationships between four accidents and eight relevant sources associated with the consecutive shield TBM. Subsequently, risk levels were determined based on expert surveys and a risk matrix technique. The findings highlighted significant impacts associated with collapses or surface settlements and the likelihood of causal combinations leading to misalignment. Specifically, this study emphasized the importance of proactive mitigation measures to address collapses or surface settlements caused by inadequate continuous tail void backfill or damaged thrust jacks. Furthermore, it is recommended to develop advanced non-destructive testing technology capable of comprehensive range detection across helical segments, to design a sequential thrust jack propulsion system, and to determine an optimal pedestal angle.

• Journal of Navigation and Port Research
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• v.48 no.4
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• pp.249-260
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• 2024

This paper aimed to summarize research on technologies that could efficiently reduce wave-making resistance of container ships. Tto develop wave resistance reduction technology that could be applied to container ships and use it in real ship design, hull-form optimal design was performed by applying optimization algorithms, hull-form change algorithms, ship performance prediction algorithms, automation algorithms, and iterative optimal design techniques. A computer program was also developed. To properly set design variables known to be important elements in hull-form optimal design and to efficiently set lower and upper limits of design variables, a sensitivity analysis algorithm was developed and applied to hull-form optimal design. To predict the reliability and applicability of the developed computer program for real ships, hull-form optimal design was performed for a KRISO Container Ship (KCS), a container ship with various studies conducted worldwide. Hull-form optimal design was performed at Fn=0.26, the design speed of the KCS ship. Numerical analysis was performed on the hull-form of the target ship, the KCS ship, and the hull-form of the ship derived as a result of the hull-form optimal design to determine wave resistance, wave system, and wave height. The optimal ship's wave resistance was found to be reduced by 80.60% compared to the target ship. The displacement and wetted surface area were also found to be reduced by 1.54% and 1.21%, respectively.

• Computers and Concrete
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• v.34 no.3
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• pp.329-346
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• 2024

In this study, it is aimed to investigate the vertical seismic performance of reinforced concrete (R/C) frame buildings in two different building stocks, one of which consists of those designed as per the previous Turkish Seismic Code (TSC-2007) that does not consider the vertical earthquake load, and the other of which consists of those designed as per the new Turkish Seismic Code (TSCB-2018) that considers the vertical earthquake load. For this aim, three R/C buildings with heights of 15 m, 24 m and 33 m are designed separately as per TSC-2007 and TSCB-2018 based on some limitations in terms of seismic zone, soil class and structural behavior factor (Rx/Ry) etc. The vertical earthquake motion effects are identified according to the linear time-history analyses (LTHA) that are performed separately for only horizontal (H) and combined horizontal+vertical (H+V) earthquake motions. LTHA is performed to predict how vertical earthquake motion affects the response of the designed buildings by comparing the linear response parameters of the base shear force, the base overturning, the base axial force, top-story vertical displacement. Nonlinear time-history analysis (NLTHA) is generally required for energy dissipative buildings, not required for design of buildings. In this study, the earthquake records are scaled to force the buildings in the linear range. Since nonlinear behavior is not expected from the buildings herein, the nonlinear time-history analysis (NLTHA) is not considered. Eleven earthquake acceleration records are considered by scaling them to the design spectrum given in TSCB-2018. The base shear force is obtained not to be affected from the combined H+V earthquake load for the buildings. The base overturning moment outcomes underline that the rigidity of the frame system in terms of the dimensions of the columns can be a critical parameter for the influence of the vertical earthquake motion on the buildings. In addition, the building stock from TSC-2007 is estimated to show better vertical earthquake performance than that of TSCB-2018. The vertical earthquake motion is found out to be highly effective on the base axial force of 33 m building rather than 15 m and 24 m buildings. Thus, the building height is a particularly important parameter for the base axial force. The percentage changes in the top-story vertical displacement of the buildings designed for both codes show an increase parallel to that in the base axial force results. To extrapolate more general results, it is clear to state that many buildings should be analyzed.