• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.8
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• pp.189-199
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• 2017

The purpose of this study is to compare the grid usage that is common to Leonardo da Vinci and J.N.L. Durand in the process of designing the architectural plan. In the days when there was no proper measurement tool, auxiliary lines relied entirely on the architect's personal mindset and design convenience. Therefore, it is considered that studying the auxiliary lines drawn by the architects will be useful for studying the human perception system. Among auxiliary lines, the grid has been used by many architects. Leonardo da Vinci and J.N.L. Durand are famous. However, these two show a significant different grid usage. As auxiliary grid and space ares added the center of the Leonardo da Vinci grid continues to move, and the grid in his sketch is becoming a building space itself. So I call it 'conceptual grid'. In the case of J.N.L. Durand, the one center of the grid is always at the center of the drawing. That is, all the positions of the grid can be determined in phase around a common point, and all of the same specifications are assumed. The grid is a kind of filter. That's why his grid is a visual abstraction of the process of thinking. In this paper, I will call the grid of J.N.L. Durand as 'abstract grid'.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.241-265
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• 2023

A corporate insolvency prediction model serves as a vital tool for objectively monitoring the financial condition of companies. It enables timely warnings, facilitates responsive actions, and supports the formulation of effective management strategies to mitigate bankruptcy risks and enhance performance. Investors and financial institutions utilize default prediction models to minimize financial losses. As the interest in utilizing artificial intelligence (AI) technology for corporate insolvency prediction grows, extensive research has been conducted in this domain. However, there is an increasing demand for explainable AI models in corporate insolvency prediction, emphasizing interpretability and reliability. The SHAP (SHapley Additive exPlanations) technique has gained significant popularity and has demonstrated strong performance in various applications. Nonetheless, it has limitations such as computational cost, processing time, and scalability concerns based on the number of variables. This study introduces a novel approach to variable selection that reduces the number of variables by averaging SHAP values from bootstrapped data subsets instead of using the entire dataset. This technique aims to improve computational efficiency while maintaining excellent predictive performance. To obtain classification results, we aim to train random forest, XGBoost, and C5.0 models using carefully selected variables with high interpretability. The classification accuracy of the ensemble model, generated through soft voting as the goal of high-performance model design, is compared with the individual models. The study leverages data from 1,698 Korean light industrial companies and employs bootstrapping to create distinct data groups. Logistic Regression is employed to calculate SHAP values for each data group, and their averages are computed to derive the final SHAP values. The proposed model enhances interpretability and aims to achieve superior predictive performance.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.6B
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• pp.503-512
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• 2009

Watershed models, which are a tool for water cycle mechanism, are classified as the distributed model and the lumped model. Currently, the distributed models have been more widely used than lumped model for many researches and applications. The lumped model estimates the parameters in the conceptual and empirical sense, on the other hand, in the case of distributed model the first-guess value is estimated from the grid-based watershed characteristics and rainfall data. Therefore, the distributed model needs more detailed parameter adjustment in its calibration and also one should precisely understand the model parameters' characteristics and sensitivity. This study uses Jungnang basin as a study area and $Vflo^{TM}$ model, which is a physics-based distributed hydrologic model, is used to analyze its parameters' sensitivity. To begin with, 100 years frequency-design rainfall is derived from Huff's method for rainfall duration of 6 hours, then the discharge is simulated using the calibrated parameters of $Vflo^{TM}$ model. As a result, hydraulic conductivity and overland's roughness have an effect on runoff depth and peak discharge, respectively, while channel's roughness have influence on travel time and peak discharge.

• The Korean Journal of Franchise Management
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• v.7 no.2
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• pp.15-25
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• 2016

Purpose - This study examined the effect of perceived corporate social responsibility (CSR) on cognitive trust, emotional trust, and loyalty among using Korean food buffet franchises. The result of this study is expected to provide practical implication to industry practitioners in expanding their understanding of the CSR effect in the marketing perspective. Research design, data, and methodology - The data was collected from a panel of online research companies who are over 20 years old and dined in at Korean style buffet franchise outlets more than five times. A total of 370 samples were used after eliminating outliers and missing data. the data were analyzed SEM with SPSS and AMOS. Result - The result of this study showed that: 1) social CSR activities have an effect only on emotional trust; 2) food-related CSR activities influence both cognitive trust and emotional trust; and 3) both cognitive trust and emotional trust have a significant impact on customer loyalty in Korean style buffet franchises. However, it is important to note that this study found no significant causal impact from environmental CSR activities. Furthermore, this study found that food-related CSR activities have the greater influence on the cognitive trust, and cognitive trust is more influential on the customer loyalty than the emotional trust. Conclusions - Based on the findings, this study provides practical implications to industry practitioners. First, that CSR has a significant impact on customer trust suggests that Korean style buffet franchises should focus on CSR activities to improve customer trust. Second, that food-related CSR activities have the greater influence on the cognitive trust implies that industry practitioners should reinforce food-related CSR activities as a marketing tool to enhance emotional trust and the overall credibility of their franchise. Third, we need to find CSR measures at the social level that can secure emotional trust so that customer loyalty can be formed. Fourth, Korean food buffet franchise food service companies should concentrate their efforts on CSR activities at food and social level among the three dimensions suggested by researchers in order to form customer loyalty. For next study, perceived concept of CSR on individual customer should be examined.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6A
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• pp.977-988
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• 2006

The goal of this study is to develop a realistic methodology for determination of the Life-Cycle Cost (LCC)-effective optimal seismic retrofit and maintenance strategy of deteriorating bridges. The proposed methodology is based on the concept of minimum LCC which is expressed as the sum of present value of seismic retrofit costs, expected maintenance costs, and expected economic losses with the constraints such as design requirements and acceptable risk of death. The proposed methodology is applied to the LCC-effective optimal seismic retrofit and maintenance strategy of a steel bridge considered as a example bridge in the accompanying study, and various conditions such as corrosion environments and Average Daily Traffic Volumes (ADTVs) are considered to investigate the effects on total expected LCC. In addition, to verify the validity of the developed methodology, the results are compared with the existing methodology. From the numerical investigation, it may be positively expected that the proposed methodology can be effectively utilized as a practical tool for the decision-making of LCC-effective optimal seismic retrofit and maintenance strategy of deteriorating bridges.

• Asia Marketing Journal
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• v.15 no.2
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• pp.75-97
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• 2013

While good return policies are suggested as one of the critical services for e-commerce, ambivalence between the burden of the cost and shoppers' satisfaction may prevent e-tailers from increasing their level of leniency. Based on the S-O-R model, this study has attempted to develop a grounded theory to explain how lenient return policies shape online shoppers' perceptions and responses, with a focus on cultural influences in the relationship. In order to check the cultural effects of the lenient return policy, thirty two female and eleven male undergraduate students in South Korean shoppers, who are accustomed to strict return policies, participated in the semi-structured interview. A series of open-ended questions were designed to explore consumers' reactions toward four different levels of the lenient return policy: from the strict type in South Korea to the lenient type in the U.S. Using qualitative research methods, this research has defined three types of dimensions of lenient return policy: return possible period, complexity of progress, and other restrictions. While previous researchers did not pay much attention, the last dimension, other restrictions, is shown to be the most significant in influencing online shoppers' perceptions, especially in South Korea. Also, the impacts on online shoppers' perceptions from the three types of sub-dimensions of return policy were somewhat different. Whereas a longer return possible period was considered more favorable, a medium level of complexity and restrictions were considered more desirable. In summary, this result showed that shoppers in Eastern cultures, i.e. South Korean online shoppers, seem favorable to a medium level of lenient return policies, while allowing for taking precautions against possible fraudulent behaviors and setting other restrictions. Therefore, most of retailers in South Korea recommended that e-tailers who adopt the most lenient return policies raise the bar to guard ethical shoppers from fraudulent users. Next, lenient return policies can enhance ease of use, usefulness, affect, and trust while relieving perceived risk, which is connected to intention to purchase, satisfaction, and loyalty. Interestingly, lenient return policies are more likely to change the behavioral responses of online shoppers, such as return and purchase, rather than change their attitudes or beliefs such as image, satisfaction, and loyalty. This tendency can be seen more clearly in the direct influences of return policy on responses. The reaction to lenient return policy is mostly the intention to return or to purchase. This suggests that return policy serves the e-tailers as a powerful tool in increasing online shoppers' purchase intention at the moment of purchase. Therefore, e-tailers who plan to expand their market to eastern countries, including South Korea, have to build a shield of restrictions around their lenient return policy, rather than immediately applying their original liberalized return policy. Also, e-tailers in South Korea need to review their strict and undifferentiated return policies to deal with the unsatisfied reactions of online shoppers toward their normal return policies. Although the present study was confined to the return policies currently being practiced by popular e-tailers, it would be worthwhile to develop effective return policies separately for each country, especially South Korea, keeping the culture of the relevant country in mind.

• Journal of Internet of Things and Convergence
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• v.10 no.1
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• pp.29-37
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• 2024

The purpose of this study is to investigate the impact of education applying the Havruta learning method in fundamentals nursing classes for nursing students on problem-solving ability, self-directed learning ability, critical thinking disposition, and learning commitment. One-group pretest-posttest design was used. Nursing students received training applying the Havruta learning method for 6 weeks (12 hours) in fundamentals nursing classes. The study was conducted from September 18 to November 6, 2023. Data were analyzed using SPSS/WIN 28.0 with mean, standard deviation, and paired samples t-test. problem-solving ability (t=4.52, p<.001), self-directed learning ability(t=-4.61, p<.001), critical thinking disposition(t=-4.10, p<.001) significantly increased before and after the 6-week Havruta learning method training for nursing students. However, there was no statistically significant difference in learning commitment (t=-0.28, p=.782). The Havruta learning method is an effective nursing education tool for improving problem-solving ability, self-directed learning ability, and critical thinking disposition. The results of this study can serve as basic data for nursing professors when planning teaching and learning strategies using Havruta. Research will be needed to utilize the Havruta learning method in various classes and evaluate its effectiveness.

• Journal of Drive and Control
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• v.20 no.4
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• pp.115-122
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• 2023

This study utilized a discrete element method (DEM) simulation, as one of the virtual field trials, to predict the impact of tillage depth on the rotary blade shaft during rotavator tilling. The virtual field for the simulation was generated according to soil properties observed in an actual field. Following the generation of particles for the virtual field, a sequence of calibration steps followed to align the mechanical properties more closely with those of real soil. Calibration was conducted with a focus on bulk density and shear torque, resulting in calibration errors of just 0.02% for bulk density and 0.52% for shear torque. The prediction of the load on a rotary tiller's blade shaft involved a three-pronged approach, considering shaft torque, draft force, and vertical force. In terms of shaft torque, the values exhibited significant increases of 42.34% and 36.91% for every 5-centimeter increment in tillage depth. Similarly, the vertical force saw substantial growth by 40.41% and 36.08% for every 5-centimeter increment. In contrast, the variation in draft force based on tillage depth was comparatively lower at 18.49% and 0.96%, indicating that the effect of tillage depth on draft force was less pronounced than its impact on shaft torque and vertical force. From a perspective of agricultural machinery research, this study provides valuable insights into the DEM soil modeling process, accounting for changes in soil properties with varying tillage depths. These findings are expected to be instrumental in future agricultural machinery design studies.

• Korean Journal of Radiology
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• v.22 no.8
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• pp.1240-1252
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• 2021

Objective: To compare the accuracy for detecting breast cancer in the diagnostic setting between the use of digital breast tomosynthesis (DBT), defined as DBT alone or combined DBT and digital mammography (DM), and the use of DM alone through a systematic review and meta-analysis. Materials and Methods: Ovid-MEDLINE, Ovid-Embase, Cochrane Library and five Korean local databases were searched for articles published until March 25, 2020. We selected studies that reported diagnostic accuracy in women who were recalled after screening or symptomatic. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. A bivariate random effects model was used to estimate pooled sensitivity and specificity. We compared the diagnostic accuracy between DBT and DM alone using meta-regression and subgroup analyses by modality of intervention, country, existence of calcifications, breast density, Breast Imaging Reporting and Data System category threshold, study design, protocol for participant sampling, sample size, reason for diagnostic examination, and number of readers who interpreted the studies. Results: Twenty studies (n = 44513) that compared DBT and DM alone were included. The pooled sensitivity and specificity were 0.90 (95% confidence interval [CI] 0.86-0.93) and 0.90 (95% CI 0.84-0.94), respectively, for DBT, which were higher than 0.76 (95% CI 0.68-0.83) and 0.83 (95% CI 0.73-0.89), respectively, for DM alone (p < 0.001). The area under the summary receiver operating characteristics curve was 0.95 (95% CI 0.93-0.97) for DBT and 0.86 (95% CI 0.82-0.88) for DM alone. The higher sensitivity and specificity of DBT than DM alone were consistently noted in most subgroup and meta-regression analyses. Conclusion: Use of DBT was more accurate than DM alone for the diagnosis of breast cancer. Women with clinical symptoms or abnormal screening findings could be more effectively evaluated for breast cancer using DBT, which has a superior diagnostic performance compared to DM alone.

• Nuclear Engineering and Technology
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• v.55 no.12
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• pp.4447-4464
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• 2023

This paper focuses on the development of a new computational model of the CNESTEN's TRIGA Mark II research reactor using the 3D continuous energy Monte-Carlo code TRIPOLI-4 (T4). This new model was developed to assess neutronic simulations and determine quantities of interest such as kinetic parameters of the reactor, control rods worth, power peaking factors and neutron flux distributions. This model is also a key tool used to accurately design new experiments in the TRIGA reactor, to analyze these experiments and to carry out sensitivity and uncertainty studies. The geometry and materials data, as part of the MCNP reference model, were used to build the T4 model. In this regard, the differences between the two models are mainly due to mathematical approaches of both codes. Indeed, the study presented in this article is divided into two parts: the first part deals with the development and the validation of the T4 model. The results obtained with the T4 model were compared to the existing MCNP reference model and to the experimental results from the Final Safety Analysis Report (FSAR). Different core configurations were investigated via simulations to test the computational model reliability in predicting the physical parameters of the reactor. As a fairly good agreement among the results was deduced, it seems reasonable to assume that the T4 model can accurately reproduce the MCNP calculated values. The second part of this study is devoted to the sensitivity and uncertainty (S/U) studies that were carried out to quantify the nuclear data uncertainty in the multiplication factor k_eff. For that purpose, the T4 model was used to calculate the sensitivity profiles of the k_eff to the nuclear data. The integrated-sensitivities were compared to the results obtained from the previous works that were carried out with MCNP and SCALE-6.2 simulation tools and differences of less than 5% were obtained for most of these quantities except for the C-graphite sensitivities. Moreover, the nuclear data uncertainties in the k_eff were derived using the COMAC-V2.1 covariance matrices library and the calculated sensitivities. The results have shown that the total nuclear data uncertainty in the k_eff is around 585 pcm using the COMAC-V2.1. This study also demonstrates that the contribution of zirconium isotopes to the nuclear data uncertainty in the k_eff is not negligible and should be taken into account when performing S/U analysis.