• Journal of the Korean Society of Hazard Mitigation
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• v.11 no.2
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• pp.163-170
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• 2011

Natural stream disasters due to a localized torrential and flash flood has occurring in a small stream especially un-implemented small stream. The survey results during ten years from 2001 to 2010 show that the small stream implementation projects (SSIPs) expenses is increasing with the damages is generally decreasing with variableness in which SSIPs is contributing to disaster prevention in a small stream. This study develop guideline for the selection of SSIPs to support high risk stream at first and save the small streams located on the mountainous area, prevention area and agricultural area which streams have no implementation effects. Developed sub items in guideline are evaluated by stream data collected from 212 small streams where it is proved that sub distance of each item are well arranged by normal distribution. This SSIPs is useful for selecting high risk small stream at first to maximize disaster risk reduction with minimum SSIPs expenses. Also, this SSIPs is used for leading to save small stream on the upstream to minimize flood damages on the down stream with selection a SSIP purchasing agricultural land for preparing flood plane.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.6
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• pp.637-658
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• 2022

TBM tunnel is simple with the iterative process of excavating the ground, building a segment ring-build, and backfilling. Drill & Blast, a conventional tunnel construction method, is more complicated than the TBM tunnel and has some restrictions because it repeats the inspection, drilling, charging, blasting, ventilation, muck treatment, and installation of support materials. However, the preparation work for excavation requires time and cost based on a very detailed plan compared to Drill & Blasting, which reinforces the ground and forms a tunnel after the formation of tunnel portal. This is because the TBM equipment for excavating the target ground determines the success or failure of the construction. If the TBM, an expensive order-made equipment, is incorrectly configured at the assembly stage, it becomes difficult to excavate from the initial stage as well as the main excavation stage. When the assembled shield TBM equipment is dismantled again, and a situation of re-assembly occurs, it is difficult throughout the construction period due to economic loss as well as time. Therefore, in this study, the layout and plan of the site and the assembly process for each major part of the TBM equipment were reviewed for the assembly of slurry shield TBM to construct the largest diameter road tunnel in domestic passing through the Han River and minimized interference with other processes and the efficiency of cutter head assembly and transport were analyzed and improved to suit the site conditions.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.5
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• pp.263-270
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• 2021

In this study, a reliability-based design optimization of a 130-m class fixed-type offshore platform, to be installed in the North Sea, was carried out, while considering environmental, material, and manufacturing uncertainties to enhance its structural safety and economic aspects. For the reliability analysis, and reliability-based design optimization of the structural integrity, unity check values (defined as the ratio between working and allowable stress, for axial, bending, and shear stresses), of the members of the offshore platform were considered as constraints. Weight of the supporting jacket structure was minimized to reduce the manufacturing cost of the offshore platform. Statistical characteristics of uncertainties were defined based on observed and measured data references. Reliability analysis and reliability-based design optimization of a jacket-type offshore structure were computationally burdensome due to the large number of members; therefore, we suggested a method for variable screening, based on the importance of their output responses, to reduce the dimension of the problem. Furthermore, a deterministic design optimization was carried out prior to the reliability-based design optimization, to improve overall computational efficiency. Finally, the optimal design obtained was compared with the conventional rule-based offshore platform design in terms of safety and cost.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.4
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• pp.591-598
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• 2021

The digital phase-locked loops(DPLL) is a circuit used for phase synchronization and has been generally used in various fields such as communication and circuit fields. State estimators are used to design digital phase-locked loops, and infinite impulse response state estimators such as the well-known Kalman filter have been used. In general, the performance of the infinite impulse response state estimator-based digital phase-locked loop is excellent, but a sudden performance degradation may occur in unexpected situations such as inaccuracy of initial value, model error, and disturbance. In this paper, we propose a minimum variance finite impulse response filter with optimal horizon for designing a new digital phase-locked loop. A numerical method is introduced to obtain the measured value interval length, which is an important parameter of the proposed finite impulse response filter, and to obtain a gain, the covariance matrix of the error is set as a cost function, and a linear matrix inequality is used to minimize it. In order to verify the superiority and robustness of the proposed digital phase-locked loop, a simulation was performed for comparison and analysis with the existing method in a situation where noise information was inaccurate.

• Korean Journal of Construction Engineering and Management
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• v.22 no.3
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• pp.79-90
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• 2021

In domestic public construction, disputes are increasing due to differences among stakeholders regarding contract price adjustment. In particular, the actual cost-plus fee for overhead costs due to the schedule extension cannot be agreed upon at the administrative phase, and most of them seek judicial judgment. Thus, this study aims to propose a 'sufficiently satisfactory' alternative to reach an agreement before disputes in order to minimize disputes related to the calculation of additional overhead costs. To this end, this study proposes three alternatives based on the rate method. Firstly, when calculating additional overhead costs, it is not calculated as an actual cost-plus-fee method, but as a rate compared to direct labor costs among net direct costs. Secondly, the calculated indirect labor costs are compensated for up to the legal maximum of legal limit costs such as general management costs, profits and so on. Thirdly, it reflects overhead costs increased or decreased due to change orders. Risks were analyzed by collecting expert opinions on the proposed methods and applying actual cases. Finally, as a result of investigating the level of consensus for each stakeholder, it was confirmed that all stakeholders could agree regardless of the size of the company. The result of this study is expected to as a useful tool among stakeholders in the construction fields that can be able to easily agreed upon.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.59-68
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• 2021

As artificial intelligence(AI) technologies, which have made rapid growth recently, began to be applied to the marine environment such as ships, there have been active researches on the application of CNN-based models specialized for digital videos. In E-Navigation service, which is combined with various technologies to detect floating objects of clash risk to reduce human errors and prevent fires inside ships, real-time processing is of huge importance. More functions added, however, mean a need for high-performance processes, which raises prices and poses a cost burden on shipowners. This study thus set out to propose a method capable of processing information at a high rate while maintaining the accuracy by applying Quantization techniques of a deep learning model. First, videos were pre-processed fit for the detection of floating matters in the sea to ensure the efficient transmission of video data to the deep learning entry. Secondly, the quantization technique, one of lightweight techniques for a deep learning model, was applied to reduce the usage rate of memory and increase the processing speed. Finally, the proposed deep learning model to which video pre-processing and quantization were applied was applied to various embedded boards to measure its accuracy and processing speed and test its performance. The proposed method was able to reduce the usage of memory capacity four times and improve the processing speed about four to five times while maintaining the old accuracy of recognition.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.3
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• pp.119-131
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• 2009

The world's widely used key exchange protocols are open cryptographic communication protocols, such as TLS/SSL, whereas in the financial field in Korea, key exchange protocols developed by industrial classification group have been used that are based on PKI(Public Key Infrastructure) which is suitable for the financial environments of Korea. However, the key exchange protocols are not only vulnerable to client impersonation attacks and known-key attacks, but also do not provide forward secrecy. Especially, an attacker with the private keys of the financial security server can easily get an old session-key that can decrypt the encrypted messages between the clients and the server. The exposure of the server's private keys by internal management problems, etc, results in a huge problem, such as exposure of a lot of private information and financial information of clients. In this paper, we analyze the weaknesses of the cryptographic communication protocols in use in Korea. We then propose two key exchange protocols which reduce the replacement cost of protocols and are also secure against client impersonation attacks and session-key and private key reveal attacks. The forward secrecy of the second protocol is reduced to the HDH(Hash Diffie-Hellman) problem.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.1
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• pp.59-69
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• 2021

Recently, large-scale offshore and coastal structures have been constructed owing to the increasing interest in eco-friendly energy development. To achieve this, precise simulations of waves are necessary to ensure the safe operations of marine structures. Several experiments are required in the field to understand the offshore wave; however, in terms of scale, it is difficult to control variables, and the cost is significant. In this study, numerical waves under various wave conditions are produced using a piston-type wavemaker, and the produced wave profiles are verified by comparing with the results from a numerical wave tank (NWT) modeled using the smoothed particle hydrodynamics (SPH) method and theoretical equations. To minimize the effect by the reflected wave, a mass-weighted damping zone is set at the right end of the NWT, and therefore, stable and uniform waves are simulated. The waves are generated using the linear and Stokes wave theories, and it is observed that the numerical wave profiles calculated by the Stokes wave theory yield high accuracy. When the relative depth is smaller than two, the results show good agreement irrespective of the wave steepness. However, when the relative depth and wave steepness are larger than 2 and 0.04, respectively, the errors are negligible if the measurement position is close to the excitation plate. However, the error is 10% or larger if the measurement position is away from the excitation location. Applicable target wave ranges are confirmed through various case studies.

• Journal of Environmental Impact Assessment
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• v.30 no.1
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• pp.49-60
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• 2021

Environmental impact assessment (EIA) practitioners play a very pivotal role in establishing EIA policies, and when implementing EIA environmental conflicts can be prevented and resolved by sharing information with stakeholders and coordinating opinions. For this reason, grasping the perceptions of stakeholders including practitioners about the overall system, such as EIA policies and implementation, can be helpful in setting improvement directions and policy directions for EIA. However, there is an insufficient information on the perception and understanding of stakeholders about the EIA system and operation currently in effect in Korea. Therefore, this study diagnoses operational and procedural problems for the EIA system, which is a decision-making tool and a precautionary technique that can minimize adverse effects through the environmental information analysis method, and improvement points and systems of the EIA system in the future. We tried to find a complement of an online survey of 37 questions,responses from 95 responses from stakeholders of EIA were summarized. Stakeholders were aware of the problems of the operation of the current system and the preparation of the evaluation form, and this was reflected. Period and cost of preparation of EIS (49%), the introduction of a new method (26%) and the items of collecting opinions and conflict management (41%), which showed high negative response rates (dissatisfied and very dissatisfied), are considered to be areas that we need to supplement further in the future. As society develops rapidly, the system needs to be supplemented accordingly, and policy improvement efforts are needed for items with high negative responses as a result of the survey.

• 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.