• Journal of the Korean Geotechnical Society
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• v.22 no.10
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• pp.77-91
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• 2006

Domestic practices in shotcrete use have developed in many respects even now, but it still has issues about material, construction, quality standard and so on. In overseas, the construction using high strength shotcrete with $39.2{\sim}58.8 MPa$ of compressive strength is becoming common based on the shotcrete technology of high strength and durability. However, domestic shotcrete design strength is low at around 20.6 MPa of compressive strength and a long term durability is also insufficient. In this paper, field tests using high-quality additives and accelerators were performed to obtain the improvement of shotcrete strength and EFNARC standard was used to evaluate the field test results. In addition, deterioration test combined with the freezing-thawing and carbonation was also performed in order to investigate a long-term durability of high-strength shotcrete. As a result of the field test, the promotion ratio of early strength was $90{\sim}97%$ in case of using alkali-free accelerators. And the compressive strength of the shotcrete using Micro-silica fume was $45.2{\sim}55.8MPa$ and flexible strength was $5.01{\sim}6.66MPa$, so the promotion ratio of strength was $37{\sim}79%$ and $17{\sim}61%$ respectively. The promotion effect of strength by silica fine additives ratio of $7.5{\sim}10%$ for cement mass was much superior to the other cases. It was especially examined that using Micro-silica fume reduced deterioration due to mixed steel fiber and improved a long-term durability of shotcrete.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.7
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• pp.267-278
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• 2017

The aim of this paper was to develop a scale for measuring gender identity among sports participants (114 male, 193 female). Gender similarities and latent mean analysis was used to validate the gender identity measurement method. Data processing was carried out by way of frequency analysis, exploratory and confirmatory factor analysis, reliability, correlation, normal distribution of questions, and latent mean analysis using SPSS 18.0 and AMOS 18.0. The results of this study were as follows: First, the equivalence had revealed the configurable, metric, and scalar invariance of the scale that can be used in multi-groups in the same way. Second, women had a more open inclination than men when it came to participating in sports activities (p<.001). Third, women participating in sports activities tended to be more conservative than men (p<.001). Fourth, women who participated in sports activities showed a higher subjective tendency than men (p<.001). Fifth, there was no statistical difference in the outward tendency when participating in sports activities (p<.05). The results of this study suggest that gender identity among sports participants is not influenced by the changing times and the advancement of women in society.

• 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.

• The Korean Journal of Franchise Management
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• v.9 no.1
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• pp.41-51
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• 2018

Purpose - In franchise system, how to build the relationship between the franchisor and franchisee through influence strategy is very important, because it affects on the long-term orientation like recontract intentions. Thus, this study examines the effect of mandatory influence strategy on relationship satisfaction, relationship trust, and recontract intentions in the context of food-service franchise industry. This study suggests the guidelines on how franchisor uses their influence strategy on franchisee to maintain and increase the recontract intentions. Research design, data, and methodology - This study examines the structural relationship between mandatory influence strategy, relationship satisfaction, relationship trust, and recontract intentions from the franchisee's perspective. Mandatory influence strategy divide into three sub-dimensions such as request, legalistic plea, threat. In order to test the purposes of this study, research model and hypotheses were developed. Every constructs were measured by multiple items tested and developed in the previous research. Also, the constructs utilized in this research are measured using 7-point scales anchored by "1=strongly disagree" and 7=strongly agree". The data were collected from 496 owner and owner manager franchisees and were analyzed using SPSS 21.0 and Smart PLS 3.0. program. Analysis of frequency was conducted to identify the demographics and general characteristics of the survey subjects. In order to measure the reliability and validity of the measurement tools, confirmatory factor analysis and correlation analysis were conducted and structural model analysis was conducted to verify the proposed research model. Result - The results of this study are as follows. First, this research found that mandatory influence strategy is positively related to relationship satisfaction and relationship trust, but not to recontract intention directly. Second, this research also found that the full mediating role of relationship satisfaction and relationship trust between the mandatory influence strategy and recontract intention. Conclusions - The findings of this research indicate that franchisor should use properly mandatory influence strategy to improve recontract intentions through relationship satisfaction and relationship trust. Due to the nature of food-service franchise industry, which needs high relationship quality, franchisor must manage their franchisee using influence strategy in order to improve satisfaction and trust. If franchisee perceives higher relationship quality, they will show higher intention to recontract. At the end of this paper, limitations and future research directions were suggested.

• 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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.6A
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• pp.535-542
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• 2010

Precise estimation of a structure's dynamic characteristics is indispensable for ensuring stable dynamic responses during lifetime especially for the structures which can experience resonance such as railway bridges. In this paper, the results of forced vibration tests of different excitation methods (vibration exciter and impact hammer) are compared to examine the differences and the cause of differences of extracted natural frequencies. Consequently a natural frequency modification method is suggested to eliminate effects of non-structural disturbance factors. Also, sequential forced vibration tests are performed before and after track construction according to the construction stage of a railway bridge, and the variation of natural frequencies are examined. Effect of added mass of vibration exciter and variation of support condition due to the level of excitation force are concluded as the major cause of natural frequency differences. Thus eliminating these effects can enhance the reliability of the extracted natural frequencies. Construction of track affects not only the mass of structure but also the stiffness of the structure. Also, the amount of increase in stiffness varies according to the level of structural deflection. Therefore, reasonable estimation of the level of structural response during operation is important for precise natural frequency calculation at design phase.

• The Journal of the Acoustical Society of Korea
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• v.42 no.6
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• pp.519-528
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• 2023

The aim of this study was to enhance the flow rate and noise performance of a centrifugal pump in dishwashers by designing an optimized impeller shape through numerical and experimental investigations. To evaluate the performance of the target centrifugal pump, experiment was conducted using a pump performance tester and noise experiment was carried out in a semi-anechoic chamber with microphones and a reflecting wall behind the dishwasher. Through the use of advanced computational fluid dynamics techniques, numerical simulations were performed to analyze the flow and aeroacoustics performance of our target centrifugal pump impeller. To achieve this, numerical simulations were carried out using the Reynolds-Average Navier-Stokes equations and Ffowcs-Willliams and Hawkings equations as governing equations. In order to ensure the validity of numerical methods, a thorough comparison of numerical results with experimental results. After having confirmed the reliability of the current numerical method of this study, the optimization of the target centrifugal pump impeller was conducted. An improvement in flow rate was confirmed numerically, and a manufactured proto-type of the optimized model was used for experimental investigation. Furthermore, it was observed that by applying the fan law, we could effectively reduce noise levels without reducing the flow rate.

• Journal of the Korean Society of Radiology
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• v.17 no.6
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• pp.1009-1015
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• 2023

This study was a one-group pretest-posttest design experimental study that attempted to verify the effects of applying the Havruta learning method on the academic self-efficacy, academic achievement, and communication skills of radiology college students. This study was conducted from May 1 to June 23, 2023, and applied the Havruta learning method for 6 weeks to 38 second-year radiologists taking a radiology technology course at a university in Jeollanam-do. SPSS/WIN 21.0 was used for data analysis, the reliability of the scale was verified, the subject's general characteristics, pre-test values and post-test values for measurement variables were verified with descriptive statistics, and the difference between before and after the Havruta learning method was verified with paired t-test. Research results show that the Havruta learning method improves academic self-efficacy (t=-2.70, p<.001), academic achievement (t=-2.87, p=.006), and communication skills (t=-2.76, p=.008). showed a statistically significant difference. As a result, Havruta learning method was confirmed as an effective learning method that improves academic self-efficacy, academic achievement, and communication skills of radiology college students. In the future, expanded application of the Havruta learning method will be necessary.

• Journal of Biomedical Engineering Research
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• v.44 no.6
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• pp.363-376
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• 2023

According to the COVID-19, development of various medical software based on IoT(Internet of Things) was accelerated. Especially, interest in a central software system that can remotely monitor and control ventilators is increasing to solve problems related to the continuous increase in severe COVID-19 patients. Since medical device software is closely related to human life, this study aims to develop central monitoring system that can remotely monitor and control multiple ventilators in compliance with medical device software development standards and to verify performance of system. In addition, to ensure the safety and reliability of this central monitoring system, this study also specifies risk management requirements that can identify hazardous situations and evaluate potential hazards and confirms the implementation of cybersecurity to protect against potential cyber threats, which can have serious consequences for patient safety. As a result, we obtained medical device software manufacturing certificates from MFDS(Ministry of Food and Drug Safety) through technical documents about performance verification, risk management and cybersecurity application.The purpose of this study is to conduct a usability assessment to ensure that ergonomic design has been applied so that the ventilator central monitoring system can improve user satisfaction, efficiency, and safety. The rapid spread of COVID-19, which began in 2019, caused significant damage global medical system. In this situation, the need for a system to monitor multiple patients with ventilators was highlighted as a solution for various problems. Since medical device software is closely related to human life, ensuring their safety and satisfaction is important before their actual deployment in the field. In this study, a total of 21 participants consisting of respiratory staffs conducted usability test according to the use scenarios in the simulated use environment. Nine use scenarios were conducted to derive an average task success rate and opinions on user interface were collected through five-point Likert scale satisfaction evaluation and questionnaire. Participants conducted a total of nine use scenario tasks with an average success rate of 93% and five-point Likert scale satisfaction survey showed a high satisfaction result of 4.7 points on average. Users evaluated that the device would be useful for effectively managing multiple patients with ventilators. However, improvements are required for interfaces associated with task that do not exceed the threshold for task success rate. In addition, even medical devices with sufficient safety and efficiency cannot guarantee absolute safety, so it is suggested to continuously evaluate user feedback even after introducing them to the actual site.

• Journal of the Korea Society for Simulation
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• v.33 no.2
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• pp.1-11
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• 2024

A cyber-physical system is a technology that connects the physical systems of a manufacturing environment with a cyber space to enable simulation. One of the major challenges in this technology is the seamless communication between these two environments. In complex manufacturing processes, it is crucial to adapt to various protocols of manufacturing equipment and ensure the transmission and reception of a large volume of data without delays or errors. In this study, we propose a method for constructing agent models for real-time simulation-capable cyberphysical systems. To achieve this, we design data collection units as independent agent models and effectively integrate them with existing simulation tools to develop the overall system architecture. To validate the proposed structure and ensure reliability, we conducted empirical testing by integrating various equipment from a real-world smart microfactory system to assess the data collection capabilities. The experiments involved testing data delay and data gaps related to data collection cycles. As a result, the proposed approach demonstrates flexibility by enabling the application of various internal data collection methods and accommodating different data formats and communication protocols for various equipment with relatively low communication delays. Consequently, it is expected that this approach will promote innovation in the manufacturing industry, enhance production line efficiency, and contribute to cost savings in maintenance.