• Journal of the Korean Geotechnical Society
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• v.38 no.3
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• pp.35-42
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• 2022

The N-value from the Standard Penetration Test (SPT), which is one of the representative in-situ test, is an important index that provides basic geological information and the depth of the bearing layer for the design of geotechnical structures. In the aspect of time and cost-effectiveness, there is a need to carry out a representative sampling test. However, the various variability and uncertainty are existing in the soil layer, so it is difficult to grasp the characteristics of the entire field from the limited test results. Thus the spatial interpolation techniques such as Kriging and IDW (inverse distance weighted) have been used for predicting unknown point from existing data. Recently, in order to increase the accuracy of interpolation results, studies that combine the geotechnics and deep learning method have been conducted. In this study, based on the SPT results of about 22,000 holes of ground survey, a comparative study was conducted to predict the depth of the bearing layer using deep learning methods and IDW. The average error among the prediction results of the bearing layer of each analysis model was 3.01 m for IDW, 3.22 m and 2.46 m for fully connected network and PointNet, respectively. The standard deviation was 3.99 for IDW, 3.95 and 3.54 for fully connected network and PointNet. As a result, the point net deep learing algorithm showed improved results compared to IDW and other deep learning method.

• 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 Cadastre & Land InformatiX
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• v.53 no.1
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• pp.37-46
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• 2023

As real estate values rise, interest in cadastral resurvey is increasing. Accordingly, a cadastral resurvey project is actively underway for drone operation through securing work efficiency and improving accuracy. The need for utilization and management of cadastral resurvey results (drone images) is being raised, and through this study, a 3D spatial information platform was developed to solve the existing drone image management and utilization limitations and to provide drone image-based 3D cadastral information. It is proposed to build and use. The study area was selected as a district that completed the latest cadastral resurvey project in which the study was organized in February 2023. Afterwards, a web-based 3D platform was applied to the study to solve the user's spatial limitations, and the platform was designed and implemented based on drone images, spatial information, and attribute information. Major functions such as visualization of cadastral resurvey results based on 3D information and comparison of performance between previous cadastral maps and final cadastral maps were implemented. Through the open platform established in this study, anyone can easily utilize the cadastral resurvey results, and it is expected to utilize and share systematic cadastral resurvey results based on 3-dimensional information that reflects the actual business district. In addition, a continuous management plan was proposed by integrating the distributed results into one platform. It is expected that the usability of the 3D platform will be further improved if a platform is established for the whole country in the future and a service linked to the cadastral resurvey administrative system is established.

• Journal of The Korean Association For Science Education
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• v.43 no.3
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• pp.237-251
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• 2023

This study explores the possibility of automated scoring for scientific graph answers by designing an automated scoring model using convolutional neural networks and applying it to students' kinematics graph answers. The researchers prepared 2,200 answers, which were divided into 2,000 training data and 200 validation data. Additionally, 202 student answers were divided into 100 training data and 102 test data. First, in the process of designing an automated scoring model and validating its performance, the automated scoring model was optimized for graph image classification using the answer dataset prepared by the researchers. Next, the automated scoring model was trained using various types of training datasets, and it was used to score the student test dataset. The performance of the automated scoring model has been improved as the amount of training data increased in amount and diversity. Finally, compared to human scoring, the accuracy was 97.06%, the kappa coefficient was 0.957, and the weighted kappa coefficient was 0.968. On the other hand, in the case of answer types that were not included in the training data, the s coring was almos t identical among human s corers however, the automated scoring model performed inaccurately.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.3D
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• pp.373-379
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• 2009

Cost estimation in the early phase enables government to plan public budgeting more efficiently by providing information about construction cost. However, cost estimation in the early phase is difficult to predict because only a little information can be utilized. The cost estimation method now being used by the government is calculated by length of the road multiplied by unit cost per length and shows high error rate because it cannot reflect the unique characteristics of each project. As the project is being proceeded, level of available information also changed. So, reflecting available information of a project is important. This paper divided early phase into two parts : planning phase and early design phase, and developed cost estimation model considering level of available information of each phase. Total 143 cases are utilized to find influencing variables and develop cost estimation model and model validation is done by adopting required accuracy level. This cost estimation model reflecting level of available information can be applied to public budgeting, feasibility test, and comparison between routes.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.6D
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• pp.587-597
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• 2010

When a car accident occurs, people who had an accident are not free from civil and criminal issues so that the accident investigator should reenact and analyze the accident situation accurately. In addition, the obtained documents through the analysis of such car accident occurrence and related factors have to be used to carry out the improvement of the areas that has numerous car accidents and complementary actions. The vehicle speed, accelerating force, braking power are currently known as the most affecting factors in accordance with many car accidents, traffic facilities, road design, etc. The vehicle's performance and rode friction coefficient road surface friction coefficient are affecting the most closely in this field. Especially, once the estimate of the speed of the accident moment relating to main eleven articles of Traffic Accident Exemption Law is very important and accuracy is required. However, currently the researches of these matters have not made exclusively yet in Korea. In this study by reflecting this current situation, until the sudden braking history is found from the car's sudden braking, it estimates accurately the transient brake time and rode friction coefficient by measuring a time of transient brake time through the precision speed detector (Vericom VC2000PC). The analysis of the experimental results calculated the transient brake time and friction coefficient to fit into the purpose of this study in the basis of different kind of various special purpose asphalt pavement and slip-prevention pavement and provided the fundamental data.

• The Journal of Korean Academy of Prosthodontics
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• v.61 no.3
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• pp.245-256
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• 2023

When restoring with a dental digital system for implant-supported prosthesis, a double digital scanning technique is required: an intraoral scan of the three-dimensional implant location and intraoral scan after placement of temporary denture or provisional prosthesis. During the intraoral scan, the use of scan body as a stable landmark can improve the accuracy of digital impression and simplify laboratory process. In this case, a full-digital system was used to plan and fabricate a custom abutment, provisional prosthesis, and definitive prosthesis. After implant placement, the scan area of the intraoral scan body connected with implant and the intraoral scan body marked on the inside of temporary denture were superimposed. Out of the superimposed files, a custom abutment and provisional prosthesis were fabricated which match the vertical dimension of temporary denture, and definitive prosthesis was fabricated based on provisional prosthesis. We report this case because result has been functionally and esthetically satisfactory by using vertical dimension and central relation set during the fabrication of temporary denture to the definitive prosthesis.

• Asia Marketing Journal
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• v.15 no.3
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• pp.53-77
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• 2013

As advertising and promotions are categorized as operating expenses, managers tend to reduce marketing budget to improve their short term profitability. Gauging the value and accountability of marketing spending is therefore considered as a major research priority in marketing. To respond this call, recent studies have documented that financial market reacts positively to a firm's marketing activity or marketing related outcomes such as brand equity and customer satisfaction. However, prior studies focus on the relation of marketing variable and financial market variables. This study suggests a channel about how marketing activity increases firm valuation. Specifically, we propose that a firm's marketing activity increases the level of the firm's product market information and thereby the dispersion in financial analysts' earnings forecasts decreases. With less uncertainty about the firm's future prospect, the firm's managers and shareholders have less information asymmetry, which reduces the firm's cost of capital and thereby increases the valuation of the firm. To our knowledge, this is the first paper to examine how informational benefits can mediate the effect of marketing activity on firm value. To test whether marketing activity contributes to increase in firm value by mitigating information asymmetry, this study employs a longitudinal data which contains 12,824 firm-year observations with 2,337 distinct firms from 1981 to 2006. Firm value is measured by Tobin's Q and one-year-ahead buy-and-hold abnormal return (BHAR). Following prior literature, dispersion in analysts' earnings forecasts is used as a proxy for the information gap between management and shareholders. For model specification, to identify mediating effect, the three-step regression approach is adopted. All models are estimated using Markov chain Monte Carlo (MCMC) methods to test the statistical significance of the mediating effect. The analysis shows that marketing intensity has a significant negative relationship with dispersion in analysts' earnings forecasts. After including the mediator variable about analyst dispersion, the effect of marketing intensity on firm value drops from 1.199 (p < .01) to 1.130 (p < .01) in Tobin's Q model and the same effect drops from .192 (p < .01) to .188 (p < .01) in BHAR model. The results suggest that analysts' forecast dispersion partially accounts for the positive effect of marketing on firm valuation. Additionally, the same analysis was conducted with an alternative dependent variable (forecast accuracy) and a marketing metric (advertising intensity). The analysis supports the robustness of the main results. In sum, the results provide empirical evidence that marketing activity can increase shareholder value by mitigating problem of information asymmetry in the capital market. The findings have important implications for managers. First, managers should be cognizant of the role of marketing activity in providing information to the financial market as well as to the consumer market. Thus, managers should take into account investors' reaction when they design marketing communication messages for reducing the cost of capital. Second, this study shows a channel on how marketing creates shareholder value and highlights the accountability of marketing. In addition to the direct impact of marketing on firm value, an indirect channel by reducing information asymmetry should be considered. Potentially, marketing managers can justify their spending from the perspective of increasing long-term shareholder value.

• The Journal of Korean Medicine
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• v.44 no.1
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• pp.128-128
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• 2023

Objectives: This research aimed to develop a guideline for evaluating safety and performance of electronic warm-acupuncture apparatus. With the development of medical devices like electronic warm-acupuncture apparatus with improved performance, convenience and safety measures compared to traditional warm-acupuncture needling, safety and performance guideline is a necessity. Methods: By referring to existing standards and guidelines of other electronic devices for Korean medicine with heating function, guideline for safety and performance assessment of electronic warm-acupuncture apparatus was drafted Results: The guideline, presents explanation for adequate temperature and settings of the apparatus, and safety measurements providing against thermal runaway situations along with guidelines for the manual. Guideline for detailed test method for the performance of the apparatus such as accuracy of temperature increase and the timer, and safety unit was also provided. The test items and suggested test methods for the requirements of biological, electrical and electromagnetic safety were referred to Korean approval documents of ministry of Food and Drug Safety. Conclusion: We proposed the relevant items to verify performance and safety of warm-acupuncture apparatus to assure patient safety and improve the quality of currently developing devices for application in clinical field.

• Journal of Biomedical Engineering Research
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• v.44 no.6
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• pp.450-464
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• 2023

Pulse oximetry, a non-invasive technique for evaluating blood oxygen saturation, conventionally depends on isolated measurements, rendering it vulnerable to factors like illumination profile, spatial blood flow fluctuations, and skin pigmentation. Previous efforts to address these issues through imaging systems often employed red and near-infrared illuminations with distinct profiles, leading to inconsistent ratios of transmitted light and the potential for errors in calculating spatial oxygen saturation distributions. While an integrating sphere was recently utilized as an illumination source to achieve uniform red and near-infrared illumination profiles on the sample surface, its bulkiness presented practical challenges. In this work, we have enhanced the pulse oximetry imaging system by transitioning illumination from an integrating sphere to a multi-wavelength LED configuration. This adjustment ensures simultaneous emission of red and near-infrared light from the same position, creating a homogeneous illumination profile on the sample surface. This approach guarantees consistent patterns of red and near-infrared illuminations that are spatially uniform. The sustained ratio between transmitted red and near-infrared light across space enables precise calculation of the spatial distribution of oxygen saturation, making our pulse oximetry imaging system more compact and portable without compromising accuracy. Our work significantly contributes to obtaining spatial information on blood oxygen saturation, providing valuable insights into tissue oxygenation in peripheral regions.