• Explosives and Blasting
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• v.38 no.4
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• pp.16-25
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• 2020

Multi-setting smart-investigation of the ground and large uncharged hole boring (MSP) method to reduce the blast-induced vibration in a tunnel excavation is carried out over 50m of long-distance boring in a horizontal direction and thus has been accompanied by deviations in boring alignment because of the heavy and one-directional rotation of the rod. Therefore, the deviation has been adjusted through the boring machine's variable setting rely on the previous construction records and expert's experience. However, the geological characteristics, machine conditions, and inexperienced workers have caused significant deviation from the target alignment. The excessive deviation from the boring target may cause a delay in the construction schedule and economic losses. A deep learning-based prediction model has been developed to discover an ideal initial setting of the MSP machine. Dropout, early stopping, pre-training techniques have been employed to prevent overfitting in the training phase and, significantly improved the prediction results. These results showed the high possibility of developing the model to suggest the boring machine's optimum initial setting. We expect that optimized setting guidelines can be further developed through the continuous addition of the data and the additional consideration of the other factors.

• Tunnel and Underground Space
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• v.33 no.6
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• pp.547-560
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• 2023

Recently, research on predicting ground classification using machine learning techniques, TBM excavation data, and ground data is increasing. In this study, a multi-classification prediction study for uniaxial compressive strength (UCS) was conducted by applying random forest model based on a decision tree among machine learning techniques widely used in various fields to machine data and ground data acquired at three slurry shield TBM sites. For the classification prediction, the training and test data were divided into 7:3, and a grid search including 5-fold cross-validation was used to select the optimal parameter. As a result of classification learning for UCS using a random forest, the accuracy of the multi-classification prediction model was found to be high at both 0.983 and 0.982 in the training set and the test set, respectively. However, due to the imbalance in data distribution between classes, the recall was evaluated low in class 4. It is judged that additional research is needed to increase the amount of measured data of UCS acquired in various sites.

• Korean Journal of Remote Sensing
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• v.30 no.5
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• pp.665-675
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• 2014

In this paper spectral characteristics and spectral patterns of pine wilt disease at different development stage were analyzed in Geoje-do where the disease has already spread. Ground-based hyperspectral imaging containing hundreds of wavelength band is feasible with continuous screening and monitoring of disease symptoms during pathogenesis. The research is based on an hyperspectral imaging of trees from infection phase to witherer phase using a ground based hyperspectral camera within the area of pine wilt disease outbreaks in Geojedo for the analysis of pine wilt disease. Hyperspectral imaging through hundreds of wavelength band is feasible with a ground based hyperspectral camera. In this research, we carried out wavelength band change analysis on trees from infection phase to witherer phase using ground based hyperspectral camera and comparative analysis with major vegetation indices such as Normalized Difference Vegetation Index (NDVI), Red Edge Normalized Difference Vegetation Index (reNDVI), Photochemical Reflectance Index (PRI) and Anthocyanin Reflectance Index 2 (ARI2). As a result, NDVI and reNDVI were analyzed to be effective for infection tree detection. The 688 nm section, in which withered trees and healthy trees reflected the most distinctions, was applied to reNDVI to judge the applicability of the section. According to the analysis result, the vegetation index applied including 688 nm showed the biggest change range by infection progress.

• Journal of the Korean Academy of Clinical Electrophysiology
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• v.1 no.2
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• pp.49-60
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• 2003

The purpose of this study was to evaluate the effect of Halliwick 10 point program on the balance control. Fourteen undergraduate students participated in the experiment, and classified 7 experiment and 7 control group, randomly. Halliwick 10 point program was applied in the experiment group for 4 weeks. Balance index was measured using KAT 2000. Balance index were measured before, during(2 weeks), and after(4 weeks) the training for 4 weeks. 2-way repeated measures ANOVA was used to further distinguish between the groups. The following results were obtained; 1. The total balance index scores from a KAT were significantly decreased after 4 weeks compared with before the training passing of time. However there was no significant difference between experiment and control group. 2. The left and anterior shifting balance index scores from a KAT were significantly decreased after 4 weeks compared with before the training passing of time. However there was no significant difference between experiment and control group. These results lead us to the conclusion that the balance ability of women twenties increase as the water is higher than that of the ground applied Halliwick 10 point program of the water specific therapy province. Therefore, A further direction of this study will be to provide more evidence for Halliwick 10 point program in the water specific therapy.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.52 no.1
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• pp.56-64
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• 2016

This study analyzed characteristics of officers' watch-keeping during fishing operation at the fisheries training ship KAYA (GT: 1,737 tons, Pukyong National University). It observed fishing works of three officers in wheel house of KAYA. The observations were carried out at the fishing ground 45 miles away from east of Jeju from 7 to 8 January 2010. The works and movements of the officers were recorded with three common video cameras and a 4-channel MPEG-4 Triplex DVR. Recorded data of the working circulation was analyzed by using the post-processing method. As a result of the traffic lines, the average (${\pm}S.D$) of working hour (min) and moving frequency (times), distance (m) and speed (m/min) during setting the net was 11.8 (0.9), 43.7 (8.1), 133.9 (35.8) and 10.5 (0.6), respectively. During trawling the net, it was 100, 241 (39.8), 615.7 (194.6) and 5.2 (1.6), respectively. During hauling the net, it was 17.6 (1.4), 41.0 (7.2), 196.9 (37.6) and 10.7 (0.8), respectively. In addition, it has a different tendency of the instrument usage frequency by the fishing works. During setting, the usage priority was CCTV, ECDIS, RPM and pitch controller, net monitor, GPS plotter, chart room, X-band radar, fish finder and public addressor. During trawling, it was CCTV, ECDIS, fish finder, X-band radar, net monitor, chart room, GPS plotter, RPM and pitch controller, auto pilot and steering, interphone, wind speed and direction indicator, No.1. VHF, navigation light control panel and public addressor. During hauling, it was CCTV, RPM and pitch controller, GPS plotter, public addressor, chart room, net monitor, X-band radar, auto pilot and steering and fish finder.

• Nuclear Engineering and Technology
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• v.51 no.3
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• pp.807-817
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• 2019

Airborne Gamma Ray Spectrometry (AGRS) with its important applications such as gathering radiation information of ground surface, geochemistry measuring of the abundance of Potassium, Thorium and Uranium in outer earth layer, environmental and nuclear site surveillance has a key role in the field of nuclear science and human life. The Broyden-Fletcher-Goldfarb-Shanno (BFGS), with its advanced numerical unconstrained nonlinear optimization in collaboration with Artificial Neural Networks (ANNs) provides a noteworthy opportunity for modern AGRS. In this study a new AGRS system empowered by ANN-BFGS has been proposed and evaluated on available empirical AGRS data. To that effect different architectures of adaptive ANN-BFGS were implemented for a sort of published experimental AGRS outputs. The selected approach among of various training methods, with its low iteration cost and nondiagonal scaling allocation is a new powerful algorithm for AGRS data due to its inherent stochastic properties. Experiments were performed by different architectures and trainings, the selected scheme achieved the smallest number of epochs, the minimum Mean Square Error (MSE) and the maximum performance in compare with different types of optimization strategies and algorithms. The proposed method is capable to be implemented on a cost effective and minimum electronic equipment to present its real-time process, which will let it to be used on board a light Unmanned Aerial Vehicle (UAV). The advanced adaptation properties and models of neural network, the training of stochastic process and its implementation on DSP outstands an affordable, reliable and low cost AGRS design. The main outcome of the study shows this method increases the quality of curvature information of AGRS data while cost of the algorithm is reduced in each iteration so the proposed ANN-BFGS is a trustworthy appropriate model for Gamma-ray data reconstruction and analysis based on advanced novel artificial intelligence systems.

• Safety and Health at Work
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• v.14 no.3
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• pp.303-308
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• 2023

Background: Occupational workers at altitudes are more prone to falls, leading to catastrophic outcomes. Acrophobia, height-related anxiety, and affected executive functions lead to postural instabilities, causing falls. This study investigated the effects of repeated virtual height exposure and training on cognitive processing and height-related anxiety. Methods: Twenty-eight healthy volunteers (age 20.48 ± 1.26 years; mass 69.52 ± 13.78 kg) were recruited and tested in seven virtual environments (VE) [ground (G), 2-story altitude (A1), 2-story edge (E1), 4-story altitude (A2), 4-story edge (E2), 6-story altitude (A3), and 6-story edge (E3)] over three days. At each VE, participants identified occupational hazards present in the VE and completed an Attitude Towards Heights Questionnaire (ATHQ) and a modified State-Trait Anxiety Inventory Questionnaire (mSTAIQ). The number of hazards identified and the ATHQ and mSTAIQ scores were analyzed using a 7 (VE; G, A1, A2, A3, E1, E2, E3) x 3 (DAY; DAY 1, DAY 2, DAY 3) factorial repeated measures analysis of variance. Results: The participants identified the lowest number of hazards at A3 and E3 VEs and on DAY 1 compared to other VEs and DAYs. ATHQ scores were lowest at G, A1, and E1 VEs. Conclusion: Cognitive processing is negatively affected by virtual altitudes, while it improves with short-term training. The features of virtual reality, such as higher involvement, engagement, and reliability, make it a better training tool to be considered in ergonomic settings. The findings of this study will provide insights into cognitive dual-tasking at altitude and its challenges, which will aid in minimizing occupational falls.

• Journal of Aerospace System Engineering
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• v.18 no.3
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• pp.76-85
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• 2024

Recently, from a global perspective, the use of small unmanned aerial vehicles in terrorism and warfare is increasing, and the need for anti-drone shooting training targeting small UAVs is increasing. However, in reality, there are many cases in Korea where anti-drone shooting training is restricted, due to complaints such as noise. In this paper, we describe the development and testing of an electric-powered direct strike type high-speed, low-noise small aerial target drone. To achieve the flight speed and endurance required for shooting training, target drone sizing was performed, and aerodynamic performance analysis was conducted using a CFD program. Based on the performance analysis, the motor propulsion system was selected and a variable pitch propeller system was designed, and performance tests were performed on a ground test rig. Finally, the target flight speed, flight time, and flight noise level were confirmed through flight tests.

• Korean Journal of Applied Biomechanics
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• v.26 no.2
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• pp.143-151
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• 2016

Objective: The purpose of this study was to investigate the effect of fatigue induction on ground reaction force (GRF) components, postural stability, and vertical jump performance in Taekwondo athletes. Method: Ten Taekwondo athletes (5 men, 5 women; mean age, $22.30{\pm}2.62years$; mean height, $174.21{\pm}9.20cm$; mean body weight, $67.28{\pm}12.56kg$) participated in this study. Fatigue was induced by a short period of strenuous exercise performed on a motorized treadmill. The analyzed variables included vertical jump performance, static stability (mediolateral [ML], center of pressure [COP], anteroposterior [AP] COP, ${\Delta}COPx$, ${\Delta}COPy$, and COP area), postural stability index values (ML stability index [MLSI], AP stability index [APSI], vertical stability index [VSI], dynamic postural stability index [DPSI]), and GRF components (ML force, AP force, peak vertical force [PVF], and loading rate). To analyze the variables measured in this study, PASW version 22.0 was used to calculate the mean and standard deviation, while a paired t-test was used to evaluate the pre- versus post-fatigue results. Pearson's correlation coefficients among variables were also analyzed. The statistical significance level was set at ${\alpha}$ = .05. Results: Vertical jump performance decreased significantly after the induction of fatigue, while AP COP, ${\Delta}COPx$, COP area, APSI, VSI, and DPSI increased significantly. PVF and loading rate increased significantly after the induction of fatigue, while the postural stability variables (AP COP, ${\Delta}COPy$, COP area, APSI, VSI, DPSI) were similarly correlated with GRF components (PVF, loading rate) after fatigue was achieved (r = .600, $R^2$ = 37%). Conclusion: These results suggest that the induction of fatigue can decrease postural stability and exercise performance of Taekwondo athletes during training and competition sessions.

• Korean Journal of Applied Biomechanics
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• v.18 no.1
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• pp.31-38
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• 2008

The purpose of this study was to investigate the effects of anterior cruciate ligament (ACL) injury prevention program on the ground reaction force during the rebound in female highschool basketball players. Sixteen highschool female basketball players (ages 16 to 18 years) were participated in this study. Eight of these players participated in a 8-week ACL injury prevention program. Before and After ACL injury prevention program, initial peak value(%BW), maximum peak value(%BW), impulse(%BW sec), and loading rate(N/sec) were measured in the players. The experiment group after ACL injury prevention program showed significant decreased initial peak value, impulse, and loading rate.