• Journal of the Korean Geotechnical Society
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• v.26 no.3
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• pp.59-68
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• 2010

Systematic risk management is necessary in grand scaled urban construction because of the existence of complicated and various risk factors. Problems of obstructions, adjacent structures, safety, environment, traffic and geotechnical properties need to be solved because urban construction is progressed in limited space not as general earthwork. Therefore the establishment of special risk management system is necessary to manage not only geotechnical properties but also social and cultural uncertainties. This research presents the technique analysis by the current state of risk management technique. Risk factors were noticed and the importance of each factor was estimated through survey. The systemically categorized database was established. Risk extraction module, matrix and score module were developed based on the database. Expected construction budget and time distribution can be computed by Monte Carlo analysis of probabilities and influences. Construction budgets and time distributions of before and after response can be compared and analyzed 80 the risks are manageable for entire whole construction time. This system will be the foundation of standardization and integration. Procurement, efficiency improvement, effective time and resource management are available through integrated management technique development and application. Conclusively decrease in cost and time is expected by systemization of project management.

• Knowledge Management Research
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• v.23 no.4
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• pp.275-294
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• 2022

In recent years, with the continuous integrative development of e-commerce and social media, social commerce, as a trust-centered social transaction mode, has become an important performance form of e-commerce. The good experience of online community and abundant user-generated content (UGC) attract more and more users and businesses to participate in the community contribution. In this context, the cost of accessing information is continuously decreasing, which not only makes the purchase process more concise and efficient, but also greatly increases the possibility of consumers' impulsive consumption. However, there are very few empirical studies on the internal influencing mechanism of consumers' impulsive consumption based on the characteristics of UGC for social commerce. In view of this, based on S-O-R model, this study constructs a model of consumers' impulsive consumption in the context of social commerce from the characteristics of UGC, with perceived risk as the mediating variable and tie strength as the moderating variable. The results show that content authenticity, content usefulness, and content valence of UGC have significant negative impacts on consumers' risk perception in the process of purchase decision-making, and consumers' perceived risk has a significant negative impact on consumers' impulsive consumption. Meanwhile, the tie strength between UGC producer and UGC receiver plays a moderating role between content usefulness and perceived risk, as well as between perceived risk and impulsive consumption. Finally, combined with the above findings, this study provides effective suggestions for relevant participants in social commerce in terms of business management.

• Journal of Aerospace System Engineering
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• v.16 no.1
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• pp.49-55
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• 2022

The role of drones has been expanded to various fields such as agriculture, construction, and logistics. In particular, agriculture drones are emerging as an effective alternative to solve the problem of labor shortage and reduce the input cost. In this study therefore, we proposed the fruit recognition algorithm and harvesting mechanism for fruit harvesting drone system that can safely harvest fruits at high positions. In the fruit recognition algorithm, we employ "You-Only-Look-Once" which is a deep learning-based object detection algorithm and verify its feasibility by establishing a virtual simulation environment. In addition, we propose the fruit harvesting mechanism which can be operated by a single driving motor. The rotational motion of the motor is converted into a linear motion by the scotch yoke, and the opened gripper moves forward, grips a fruit and rotates it for harvesting. The feasibility of the proposed mechanism is verified by performing Multi-body dynamics analysis.

• 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.

• Journal of the Korean Society of Radiology
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• v.17 no.3
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• pp.367-373
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• 2023

Aircrews and passengers are exposed to radiation from cosmic rays and secondary scattered rays generated by reactions with air or aircraft. For aircrews, radiation safety management is based on the exposure dose calculated using a space-weather environment simulation. However, the exposure dose varies depending on solar activity, altitude, flight path, etc., so measuring by route is more suggestive than the calculation. In this study, we developed an instrument to measure the cosmic radiation dose using a general-purpose Si sensor and a multichannel analyzer. The dose calculation applied the algorithm of CRaTER (Cosmic Ray Telescope for the Effects of Radiation), a space radiation measuring device of NASA. Energy and dose calibration was performed with Cs-137 662 keV gamma rays at a standard calibration facility, and good dose rate dependence was confirmed in the experimental range. Using the instrument, the dose was directly measured on the international line between Dubai and Incheon in May 2023, and it was similar to the result calculated by KREAM (Korean Radiation Exposure Assessment Model for Aviation Route Dose) within 12%. It was confirmed that the dose increased as the altitude and latitude increased, consistent with the calculation results by KREAM. Some limitations require more verification experiments. However, we confirmed it has sufficient utilization potential as a cost-effective measuring instrument for monitoring exposure dose inside or on personal aircraft.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5B
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• pp.575-589
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• 2008

In the present work, we investigate the hydrodynamic behavior of a turbulent bore, such as tsunami bore and tidal bore, generated by the removal of a gate with water impounded on one side. The bore generation system is similar to that used in a general dam-break problem. In order to the numerical simulation of the formation and propagation of a bore, we consider the incompressible flows of two immiscible fluids, liquid and gas, governed by the Navier-Stokes equations. The interface tracking between two fluids is achieved by the volume-of-fluid (VOF) technique and the M-type cubic interpolated propagation (MCIP) scheme is used to solve the Navier-Stokes equations. The MCIP method is a low diffusive and stable scheme and is generally extended the original one-dimensional CIP to higher dimensions, using a fractional step technique. Further, large eddy simulation (LES) closure scheme, a cost-effective approach to turbulence simulation, is used to predict the evolution of quantities associated with turbulence. In order to verify the applicability of the developed numerical model to the bore simulation, laboratory experiments are performed in a wave tank. Comparisons are made between the numerical results by the present model and the experimental data and good agreement is achieved.

• The Plant Pathology Journal
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• v.39 no.1
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• pp.108-122
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• 2023

Fusarium oxysporum f. sp. lycopersici (Fol) and Fusarium oxysporum f. sp. cubense (Foc), are the causal agent of Fusarium wilt disease of tomato and banana, respectively, and cause significant yield losses worldwide. A cost-effective measure, such as biological control agents, was used as an alternative method to control these pathogens. Therefore, in this study, six isolates of the Streptomyces-like colony were isolated from soils and their antagonistic activity against phytopathogenic fungi and plant growth-promoting (PGP) activity were assessed. The results showed that these isolates could inhibit the mycelial growth of Fol and Foc. Among them, isolate STRM304 showed the highest percentage of mycelial growth reduction and broad-spectrum antagonistic activity against all tested fungi. In the pot experiment study, the culture filtrate of isolates STRM103 and STRM104 significantly decreased disease severity and symptoms in Fol inoculated plants. Similarly, the culture filtrate of the STRM304 isolate significantly reduced the severity of the disease and symptoms of the disease in Foc inoculated plants. The PGP activity test presents PGP activities, such as indole acetic acid production, phosphate solubilization, starch hydrolysis, lignin hydrolysis, and cellulase activity. Interestingly, the application of the culture filtrate from all isolates increased the percentage of tomato seed germination and stimulated the growth of tomato plants and banana seedlings, increasing the elongation of the shoot and the root and shoot and root weight compared to the control treatment. Therefore, the isolate STRM103 and STRM104, and STRM304 could be used as biocontrol and PGP agents for tomato and banana, respectively, in sustainable agriculture.

• Analytical Science and Technology
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• v.21 no.4
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• pp.284-295
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• 2008

For plastics samples, a method using combustion ion chromatography was selected as a method for rapid low-cost analysis to test whether hazardous substances are contained or not. Using combustion ion chromatography, a verification test for F, Cl and Br compounds generated a linear calibration curve with a correlation coefficient of $r^2$ = 0.999~1.000 in the calibration range from 0.5 to 4.0 mg/kg. The detection limits were found to be 0.005~0.024 mg/kg and quantitative limits were found to be 0.014~0.073 mg/kg. The recoveries of combustion ion chromatography using certified reference material (CRM) were found to be 95.5~104.9%. Based on these results, a proficiency test was conducted together with several laboratories in and out of the country, to make comparative analysis of the results from each laboratory. As a result, the data supported the use of combustion ion chromatography as an effective analysis method to deal with regulations for halogen-free electronic products and for other hazardous substances in the electronic products.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.2
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• pp.25-32
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• 2023

In this study, a double wall system is introduced, which was invented to simplify the complicated manufacturing process of the existing precast concrete (PC) double wall systems and to remove defects such as laitance that may occur during the production of concrete panels. An experimental study was conducted to investigate the tensile resisting capacity of the steel tube which is embedded in the precast concrete panel to keep the spacing between PC panels and to prevent damage of the PC panels during transportation and casting concrete onsite. The experiment was planned to determine the detail of effective steel tube connection considering the steel plate treatment method according to the formation of the opening, the presence of embedded concrete, and the reinforcement welding for additional dowel action as key variables. As a result, the ultimate tensile strength increased by 20-30% compared to the control specimen (ST) except for the steel tube specimen (ST_CP) which has steel plates bent inward at the end part of the steel tube. Since the specimen (ST_CON) filled with concrete inside the control specimen has no additional process and cost for the steel tube connections compared to the control specimen during the production of the developed double wall system, it is determined to be the appropriate detail of steel tube connection.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.7
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• pp.295-302
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• 2023

Software requirements written in natural language may have different meanings from the stakeholders' viewpoint. When designing an architecture based on quality attributes, it is necessary to accurately classify quality attribute requirements because the efficient design is possible only when appropriate architectural tactics for each quality attribute are selected. As a result, although many natural language processing models have been studied for the classification of requirements, which is a high-cost task, few topics improve classification performance with the imbalanced quality attribute datasets. In this study, we first show that the classification model can automatically classify the Korean requirement dataset through experiments. Based on these results, we explain that data augmentation through EDA(Easy Data Augmentation) techniques and undersampling strategies can improve the imbalance of quality attribute datasets, and show that they are effective in classifying requirements. The results improved by 5.24%p on F1-score, indicating that handling imbalanced data helps classify Korean requirements of classification models. Furthermore, detailed experiments of EDA illustrate operations that help improve classification performance.