• Tunnel and Underground Space
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• v.33 no.6
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• pp.534-546
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• 2023

If the disc cutter is excessively worn or damaged, it becomes incapable of rotating and efficiently cutting rockmass. Therefore, it is important to appropriately manage the replacement cycle of the disc cutter based on its degree of wear. In general, the replacement cycle is determined based on the results of manual inspection. However, the manual measurements has issues related to worker safety and may lead to inaccurate measurement results. For these reasons, some foreign countries are developing the real-time measurement system of disc cutter wear by using different sensors. The ultrasonic sensors, eddy current sensors, magnetic sensors, and others are utilized for measuring the wear amount of disc cutters. In this study, the applicability of eddy current sensors for real-time measurement of wear amount in TBM disc cutters was evaluated. The distance measurement accuracy of the eddy current sensor was assessed through laboratory tests. In particular, the accuracy of eddy-current sensor was evaluated in various environmental conditions within the cutterhead chamber. In addition, the measurement accuracy of the eddy current sensor was validated using a 17-inch disc cutter.

• Journal of the Society of Disaster Information
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• v.20 no.2
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• pp.329-338
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• 2024

Purpose: This study verified the safety of the improved box-type girder behavior by comparing and evaluating the bending behavior results of a full-scale specimen based on the analytical behavior of the splice element PSC U-shaped girder with integrated tensioning systems. Method: Based on the results of the service and strength limit state design using the bridge design standard(limit state design method), the applied load of a 40m full-scale specimen was calculated and a static loading experiment using the four-point loading method was performed. Result: When the design load, crack load, and ultimate load were applied, the specimen deflection occurred at 97.1%, 98.5%, and 79.0% of the analytical deflection value. When the design load, crack load, and ultimate load were applied, the crack gauge was measured at 0.009~0.035mm, 0.014~0.050mm, and 6.383~5.522mm at each connection. Conclusion: The specimen behaved linear-elastically until the crack load was applied, and after cracks occurred, it showed strainhardening up to the ultimate load, and it was confirmed that the resistance of bending behavior was clearly displayed against the applied load. The cracks in the dry joints were less than 25% of grade B based on the evaluation of facility condition standard. The final residual deformation after removing the ultimate load was 0.114mm, confirming the stable behavior of the segment connection.

• Journal of the Korean Geotechnical Society
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• v.40 no.2
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• pp.29-40
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• 2024

This study aimed to evaluate the swelling behavior characteristics of KJ-II buffer blocks by performing numerical analysis of swelling pressure measurement experiments using the nonlinear elasticity model of COMSOL Multiphysics. The analysis was conducted under boundary conditions that included isotropic constraints and water injection pressure, mirroring the experimental settings. Validation of the numerical model was achieved by comparing its outputs with experimental results. The validated model was then used to simulate swelling deformations under unconfined conditions and to analyze swelling pressure as influenced by dry density and the geometric shape of the buffer material. The results accurately represented the swelling deformation observed during the saturation process and demonstrated that swelling pressure increases with higher dry density. Moreover, simulations concerning the geometric shape of the buffer material indicated a markedly faster rate of pressure increase in U-shaped samples compared to cylindrical ones. Analysis suggested that stress manifested preemptively near the internal edges of U-shaped samples during saturation. To enhance the simulation's fidelity to actual buffer material behavior, further refinement of the analysis model using a nonlinear elasticity model is recommended.

• Journal of the Korean GEO-environmental Society
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• v.25 no.2
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• pp.5-14
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• 2024

Reinforced concrete bridge decks are the first to be damaged by vehicle loads and rain infiltration. Concrete deterioration primarily occurs owing to the corrosion of rebars and other metal components by chlorides used for snow and ice melting. The structural condition and concrete deterioration of the bridge decks within the pavement were evaluated using ground-penetrating radar (GPR) survey data. To evaluate concrete deterioration in bridges, it is necessary to develop GPR data analysis techniques to accurately identify deteriorated locations and rebar positions. GPR exploration involves the acquisition of reflection and diffraction wave signals due to differences in radar wave propagation velocity in geotechnical media. Therefore, a full-waveform inversion (FWI) method was developed to evaluate the deterioration of reinforced concrete bridge decks by estimating the radar wave propagation velocity in geotechnical media using GPR data. Numerical experiments using a GPR velocity model confirmed the deterioration phenomena of bridge decks, such as concrete delamination and rebar corrosion, verifying the applicability of the developed technology. Moreover, using the synthetic GPR data, FWI facilitates the determination of rebar positions and concrete deterioration locations using inverted velocity images.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.31-38
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• 2024

The digital phase-locked loop(DPLL) is one of the circuits composed of a digital detector, digital loop filter, voltage-controlled oscillator, and divider as a fundamental circuit, widely used in many fields such as electrical and circuit fields. A state estimator using various mathematical algorithms is used to improve the performance of a digital phase-locked loop. Traditional state estimators have utilized Kalman filters of infinite impulse response state estimators, and digital phase-locked loops based on infinite impulse response state estimators can cause rapid performance degradation in unexpected situations such as inaccuracies in initial values, model errors, and various disturbances. In this paper, we propose a two-layer Frobenius norm-based finite impulse state estimator to design a new digital phase-locked loop. The proposed state estimator uses the estimated state of the first layer to estimate the state of the first layer with the accumulated measurement value. To verify the robust performance of the new finite impulse response state estimator-based digital phase locked-loop, simulations were performed by comparing it with the infinite impulse response state estimator in situations where noise covariance information was inaccurate.

• Journal of Service Research and Studies
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• v.14 no.1
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• pp.108-123
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• 2024

In particular, as the current educational institutions are becoming more competitive, universities need to make efforts to survive the fierce competition by improving their service qualities. In this situation, this study was conducted to confirm the effect of international students' evaluation of university service quality on university loyalty through university satisfaction and service engagements, And several implications can be suggested as follows. First, the dimensions of university service quality were identified as important factors that had a great influence on the university satisfaction of international students. Among the service quality dimensions, support services related to international students were found to be the most important variable in university satisfaction. The school's efforts to solve the inconvenience of international students and the grievances of students who feel difficulties that their own students do not feel are considered a very important factor in the satisfaction of international students. Second, it was found that international students' class engagement or friendship engagement can be increased through satisfaction with the school, and eventually, the increased engagements affect university loyalty. In particular, it has been verified that for international students, the loyalty of the school can be increased by establishing friendships with students from various countries and participating in various school programs. Finally, according to the purposes of studying abroad, the difference was confirmed between the groups studying for academic development and better employment and the group employed for overseas experience and immigration.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.3
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• pp.109-121
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• 2024

This paper adopts a resource-based approach to analyze why some universities have a greater number of faculty startups, and how this impacts on performance, in terms of indictors such as the number of employees and revenue sales. More specifically, we propose 9 hypotheses which link institutional resources to faculty startups and their performance, and compare 5 different groups of university resources for cross-college variation, using data from 134 South Korean four-year universities from 2017 to 2020. We find that the institutional factors impacting on performance of faculty startups differ from other categories of startups. The results show that it is important for universities to provide a more favorable environment, incorporating more flexible personnel policies and accompanying startup support infrastructure, for faculty startups, whilest it is more effective to have more financial resources and intellectual property for other categories of startups. Our findings also indicate that university technology-holding company and technology transfer programs are crucial to increase the number of faculty startups and their performance. Our analysis results have implications for both university and government policy-makers, endeavoring to facilitate higher particaption of professors in startup formation and ultimate commercialization of associated teachnologies.

• Journal of the Korean Society of Marine Environment & Safety
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• v.30 no.2
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• pp.147-156
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• 2024

The sustainable management and enhancement of marine resources are becoming increasingly important issues worldwide. This study was conducted in response to these challenges, focusing on the development and performance comparison of fish detection and classification models as part of a deep learning-based technique for assessing the effectiveness of marine resource enhancement projects initiated by the Korea Fisheries Resources Agency. The aim was to select the optimal model by training various sizes of YOLOv8-Seg models on a fish image dataset and comparing each performance metric. The dataset used for model construction consisted of 36,749 images and label files of 12 different species of fish, with data diversity enhanced through the application of augmentation techniques during training. When training and validating five different YOLOv8-Seg models under identical conditions, the medium-sized YOLOv8m-Seg model showed high learning efficiency and excellent detection and classification performance, with the shortest training time of 13 h and 12 min, an of 0.933, and an inference speed of 9.6 ms. Considering the balance between each performance metric, this was deemed the most efficient model for meeting real-time processing requirements. The use of such real-time fish detection and classification models could enable effective surveys of marine resource enhancement projects, suggesting the need for ongoing performance improvements and further research.

• Korean Journal of Environmental Biology
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• v.42 no.2
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• pp.193-206
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• 2024

This study aimed to quantify changes in forest cover and carbon storage of Korean Peninsular during the last two decades by integrating field measurement, satellite remote sensing, and modeling approaches. Our analysis based on 30-m Landsat data revealed that the forested area in Korean Peninsular had diminished significantly by 478,334 ha during the period of 2000-2019, with South Korea and North Korea contributing 51.3% (245,725 ha) and 48.6% (232,610 ha) of the total change, respectively. This comparable pattern of forest loss in both South Korea and North Korea was likely due to reduced forest deforestation and degradation in North Korea and active forest management activity in South Korea. Time series of above ground biomass (AGB) in the Korean Peninsula showed that South and North Korean forests increased their total AGB by 146.4Tg C (AGB at 2020=357.9Tg C) and 140.3Tg C (AGB at 2020=417.4Tg C), respectively, during the last two decades. This could be translated into net AGB increases in South and North Korean forests from 34.8 and 29.4 Mg C ha^-1 C to 58.9(+24.1) and 44.2(+14.8) Mg C ha^-1, respectively. It indicates that South Korean forests are more productive during the study period. Thus, they have sequestered more carbon. Our approaches and results can provide useful information for quantifying national scale forest cover and carbon dynamics. Our results can be utilized for supporting forest restoration planning in North Korea

• Korean Journal of Culture and Social Issue
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• v.30 no.3
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• pp.239-265
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• 2024

The purpose of this study was to compare the predictive accuracy of traditional prediction models (methods) and machine learning algorithms in predicting suicidal behaviors. The research aimed to go beyond a systematic review level and scientifically examine the predictive capabilities of these two techniques through meta-analysis, analyzing variables identified through domestic research, particularly at the regional level. In order to achieve this, a total of 124 studies, including 50 studies utilizing machine learning and 74 studies employing traditional methods, were included in the meta-analysis. The results of the study revealed that the integrated area under the curve (AUC) for studies using traditional methods was .770, which was lower than the integrated AUC value of .853 for studies using machine learning. Particularly, studies conducted in Asia (AUC = .944) demonstrated higher accuracy compared to studies in Western countries (AUC = .820) and Korea (AUC = .864). Additional analysis of the moderating effects in domestic research indicated that a higher proportion of males and the prediction of suicide attempts were associated with higher prediction accuracy. On the other hand, prediction accuracy was lower when the prediction target was suicide deaths and when studies utilized neural network analysis. This study synthesized various research findings on the prediction of suicidal behaviors, verified the effectiveness of prediction using machine learning, and holds significance in exploring variables applicable in the context of South Korea.