• Smart Structures and Systems
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• v.24 no.4
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• pp.475-490
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• 2019

The detection of structural damage without a priori information on the healthy state is challenging. In order to address the issue, the study presents a baseline-free approach to detect damage in beam structures based on an actual influence line. In particular, a multi-segment function-fitting calculation is developed to extract the actual deflection influence line (DIL) of a damaged beam from bridge responses due to a passing vehicle. An intact basis function based on the measurement position is introduced. The damage index is defined as the difference between the actual DIL and a constructed function related to the intact basis, and the damage location is indicated based on the local peak value of the damage index curve. The damage basis function is formulated by using the detected damage location. Based on the intact and damage basis functions, damage severity is quantified by fitting the actual DIL using the least-square calculation. Both numerical and experimental examples are provided to investigate the feasibility of the proposed method. The results indicate that the present baseline-free approach is effective in detecting the damage of beam structures.

• Nuclear Engineering and Technology
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• v.51 no.2
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• pp.444-452
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• 2019

To assess the availability of a nuclear power plant's dynamic systems, it is necessary to consider the impact of dynamic interactions, such as components, software, and operating processes. However, there is currently no simple, easy-to-use tool for assessing the availability of these dynamic systems. The existing method, such as Markov chains, derives an accurate solution but has difficulty in modeling the system. When using conventional fault trees, the reliability of a system with dynamic characteristics cannot be evaluated accurately because the fault trees consider reliability of a specific operating configuration of the system. The dynamic reliability graph with general gates (DRGGG) allows an intuitive modeling similar to the actual system configuration, which can reduce the human errors that can occur during modeling of the target system. However, because the current DRGGG is able to evaluate the dynamic system in terms of only reliability without repair, a new evaluation method that can calculate the availability of the dynamic system with repair is proposed through this study. The proposed method extends the DRGGG by adding the repair condition to the dynamic gates. As a result of comparing the proposed method with Markov chains regarding a simple verification model, it is confirmed that the quantified value converges to the solution.

• Journal of the Korean Society of Safety
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• v.36 no.3
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• pp.66-73
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• 2021

This report documents the results of an at-power internal events Level 1 Probabilistic Safety Assessment (PSA) for a Korea research reactor (KRR). The aim of the study is to determine the accident sequences, construct an internal level 1 PSA model, and estimate the core damage frequency (CDF). The accident quantification is performed using the AIMS-PSA software version 1.2c along with a fault tree reliability evaluation expert (FTREX) quantification engine. The KRR PSA model is quantified using a cut-off value of 1.0E-15/yr to eliminate the non-effective minimal cut sets (MCSs). The final result indicates a point estimate of 4.55E-06/yr for the overall CDF attributable to internal initiating events in the core damage state for the KRR. Loss of Electric Power (LOEP) is the predominant contributor to the total CDF via a single initiating event (3.68E-6/yr), providing 80.9% of the CDF. The second largest contributor is the beam tube loss of coolant accident (LOCA), which accounts for 9.9% (4.49E-07/yr) of the CDF.

• Journal of Korean Dental Science
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• v.14 no.1
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• pp.1-11
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• 2021

Purpose: The alveolar ridge preservation (ARP) is widely conducted for implant placement. However, experimental results using deproteinized porcine bone mineral (DPBM) have been scarce. This retrospective study evaluated factors affecting the primary stability of implants in an area where ARP was performed using DPBM. Materials and Methods: Thirty-eight patients were divided into two groups based on the primary stability, with torque value of 30 Ncm as borderline. To determine the factors that affect the primary stability of implants, we collected data from patients' medical records including age, sex, reentry time, socket location, remaining bone wall at the time of extraction, and type of collagen membrane, as well as from radiographs and histomorphometric analysis. Result: The results showed statistically significant difference for the remaining extraction socket wall (P=0.014), residual graft (P=0.029), and fibrovascular tissue (P=0.02) between the two groups. There was an insignificant tendency toward the time of reentry surgery (P=0.052) and location (P=0.077). All implants placed in sites using DPBM functioned well up to 3 years. Conclusion: Within the limitations of the present study, extraction socket wall, residual graft, and fibrovascular tissue can affect the primary stability at the time of implant placement on grafted sites using DPBM and collagen membranes. In addition, reentry time and locations can be considered. In future studies, comparative experiments in quantified models will be required to supporting the findings.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.10
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• pp.3333-3354
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• 2022

The 5G Core Network (5GC) is an essential part of the mobile communication network, but its security protection strategy based on the boundary construction is difficult to ensure the security inside the network. For example, the Network Function (NF) mutual authentication mechanism that relies on the transport layer security mechanism and OAuth2.0's Client Credentials cannot identify the hijacked NF. To address this problem, this paper proposes a trust model for 5GC based on NF interaction behavior to identify malicious NFs and improve the inherent security of 5GC. First, based on the interaction behavior and context awareness of NF, the trust between NFs is quantified through the frequency ratio of interaction behavior and the success rate of interaction behavior. Second, introduce trust transmit to make NF comprehensively refer to the trust evaluation results of other NFs. Last, classify the possible malicious behavior of NF and define the corresponding punishment mechanism. The experimental results show that the trust value of NFs converges to stable values, and the proposed trust model can effectively evaluate the trustworthiness of NFs and quickly and accurately identify different types of malicious NFs.

• Animal Bioscience
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• v.35 no.5
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• pp.659-669
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• 2022

Objective: Thoroughbred horses have been bred exclusively for racing in England for a long time. Additionally, because horse racing is a global sport, a healthy leisure activity for ordinary citizens, and a high-value business, systematic racehorse breeding at the population level is a requirement for continuous industrial development. Therefore, we established genomic evaluation system (using prize money as horse racing traits) to produce spirited, agile, and strong racing horse population Methods: We used phenotypic data from 25,061 Thoroughbred horses (all registered individuals in Korea) that competed in races between 1994 and 2019 at the Korea Racing Authority and constructed pedigree structures. We quantified the improvement in racehorse breeding output by year in Korea, and this aided in the establishment of a high-level horse-fill industry. Results: We found that pedigree-based best linear unbiased prediction method improved the racing performance of the Thoroughbred population with high accuracy, making it possible to construct an excellent Thoroughbred racehorse population in Korea. Conclusion: This study could be used to develop an efficient breeding program at the population level for Korean Thoroughbred racehorse populations as well as others.

• Journal of Veterinary Science
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• v.21 no.5
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• pp.69.1-69.11
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• 2020

Background: An inappropriate Q angle may affect the biomechanics of the canine patellofemoral joint. Objectives: The purpose of this study was to evaluate the effects of changes in quadriceps angle (Q angle) on patellofemoral joint pressure distribution in dogs. Methods: Eight stifles were positioned at 45, 60, 75, 90, 105, and 120° of flexion in vitro, and 30% body weight was applied through the quadriceps. Patellofemoral contact pressure distribution was mapped and quantified using pressure-sensitive film. For the pressure area, mean pressure, peak pressure, medial peak pressure, and lateral peak pressure, differences between groups according to conditions for changing the Q angle were statistically compared. Results: Increases of 10° of the Q angle result in increases in the pressure area (P = 0.04), mean pressure (P = 0.003), peak pressure, and medial peak pressure (P ≤ 0.01). Increasing the Q angle by 20° increases the pressure area (P = 0.021), mean pressure (P ≤ 0.001), peak pressure (P ≤ 0.01), and medial peak pressure (P ≤ 0.01) significantly, and shows higher mean (P ≤ 0.001) and peak pressures than increasing by 10°. Decreasing the Q angle increases the mean pressure (P = 0.013), peak pressure, and lateral peak pressure (P ≤ 0.001). Conclusions: Both increases and decreases in the Q angle were associated with increased peak patellofemoral pressure, which could contribute to the overloading of the cartilage. Therefore, the abnormal Q angle should be corrected to the physiologically normal value during patellar luxation repair and overcorrection should be avoided.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11b
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• pp.204-209
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• 2000

At harvest, the starch contents of apples, which were related to their maturity, were quantified by using image analysis. The stained area was measured by a computer vision system when an apple slice was stained with KI/I$_2$ solution. The stained area ratio of the stained area of the apple slice to its whole area, or the starch index, was defined as an indicator of starch content. When Tsugaru apples were manually sorted into immature, turning and mature groups, their starch indices were 0.374, 0.312 and 0.129, respectively. Meanwhile, the starch index had correlation to various physicochemical properties of Tsugaru apples. At the statistically significant level of 0.1 %, it was correlated with the pH value, bio-yield force, rupture force and color of intact and skin-removed apples. At the 1 ％ significant level, it had the correlation with the density and moisture content.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.11a
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• pp.133-134
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• 2022

Recently, the criteria for assessing industrial accidents have been replaced by the mortality rate. It was found that the number of deaths from excavation work was the highest among construction machinery. The risk assessment is being conducted, however the industrial accident mortality rate has not decreased. Accordingly, this study aims to provide the basic for the create of a risk assessment model specialized in construction work at excavator. It provides absolute value from the risk model which is capable of delivery the probability of a disaster. In addition, we provide a relative risk model that compares the risk through scores between detailed works. The relative risk model is combined by likelihood and severity; the likelihood indicates the frequency of accidents and the severity indicates seriousness of fatal accidents. A variable that reflects the conditions of the construction site was added to the risk assessment model based on past disaster cases. And using the concepts of probability and average, the risk assessment process was quantified and used as an objective indicator. Therefore, the model is expected to reduce disasters by raising the awareness of disasters.

• Geomechanics and Engineering
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• v.37 no.3
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• pp.253-262
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• 2024

Dynamic properties are pivotal in soil analysis, yet their experimental determination is hampered by complex methodologies and the need for costly equipment. This study aims to predict dynamic soil properties using static properties that are relatively easier to obtain, employing machine learning techniques. The static properties considered include soil cohesion, friction angle, water content, specific gravity, and compressional strength. In contrast, the dynamic properties of interest are the velocities of compressional and shear waves. Data for this study are sourced from 26 boreholes, as detailed in a geotechnical investigation report database, comprising a total of 130 data points. An importance analysis, grounded in the random forest algorithm, is conducted to evaluate the significance of each dynamic property. This analysis informs the prediction of dynamic properties, prioritizing those static properties identified as most influential. The efficacy of these predictions is quantified using the coefficient of determination, which indicated exceptionally high reliability, with values reaching 0.99 in both training and testing phases when all input properties are considered. The conventional method is used for predicting dynamic properties through Standard Penetration Test (SPT) and compared the outcomes with this technique. The error ratio has decreased by approximately 0.95, thereby validating its reliability. This research marks a significant advancement in the indirect estimation of the relationship between static and dynamic soil properties through the application of machine learning techniques.