• Journal of Biomedical Engineering Research
• /
• v.44 no.2
• /
• pp.139-146
• /
• 2023

Osteoporosis is a disease in which the risk of bone fractures increases due to a decrease in bone density caused by aging. Osteoporosis is diagnosed by measuring bone density in the total hip, femoral neck, and lumbar spine. To accurately measure bone density in the lumbar spine, the vertebral region must be segmented from the lumbar X-ray image. Deep learning-based automatic spinal segmentation methods can provide fast and precise information about the vertebral region. In this study, we used 695 lumbar spine images as training and test datasets for a deep learning segmentation model. We proposed a lumbar automatic segmentation model, CM-Net, which combines the center point of the spine and the modified U-Net network. As a result, the average Dice Similarity Coefficient(DSC) was 0.974, precision was 0.916, recall was 0.906, accuracy was 0.998, and Area under the Precision-Recall Curve (AUPRC) was 0.912. This study demonstrates a high-performance automatic segmentation model for lumbar X-ray images, which overcomes noise such as spinal fractures and implants. Furthermore, we can perform accurate measurement of bone density on lumbar X-ray images using an automatic segmentation methodology for the spine, which can prevent the risk of compression fractures at an early stage and improve the accuracy and efficiency of osteoporosis diagnosis.

• Journal of Korean Society on Water Environment
• /
• v.39 no.4
• /
• pp.316-328
• /
• 2023

In this study, the characteristics of nonpoint pollutant outflow and contribution rate of pollution in Songya-stream mainstream and tributaries were analyzed. Further, water pollution management and improvement measures for pollution-oriented rivers were proposed. An on-site investigation was conducted to determine the inflow of major pollutants into the basin, and it was found that pollutants generated from agricultural land and livestock facilities flowed into the river, resulting in a high concentration of turbid water. Based on the analysis results of the pollution load data calculated through actual measurement monitoring (flow and water quality) and the occurrence and emission load data calculated using the national pollution source survey data, the S3 and S6 were selected as the concerned pollution tributaries in the Songya-stream basin. Results of cluster analysis using Pearson correlation coefficient evaluation and Density based spatial clustering of applications with noise (DBSCAN) technique showed that the S3 and S6 were most consistent with the C2 cluster (a cluster of Songya-stream mainstream owned area) corresponding to the mainstream of Songya-stream. The analysis results of the major pollutants in the concerned pollution tributaries showed that livestock and land pollutants were the major pollutants. Consequently, optimal management techniques such as fertilizer management, water gate management in paddy, vegetated filter strip and livestock manure public treatment were proposed to reduce livestock and land pollutants.

• Journal of the Korean Geotechnical Society
• /
• v.25 no.11
• /
• pp.53-60
• /
• 2009

Construction of a tunnel induces rock masses damage around the tunnel. The degree of damage produced on rock masses will affect on the mechanical and hydraulic behaviors of the rock masses. In this paper, P wave velocity measured by cross-hole test was used to assess rock masses damage around the test tunnel. Initiation of source signal was carried out using mechanical impact at the source installed borehole. In consequence, the generated P wave signal was low noise and apparent wave form, which allows accurate pick-up of first arrival time. From the test, the region where rock damage is expected shows relatively low P wave velocity. In addition, with multiple points of P wave velocity measurement along each cross-hole, two dimensional P wave tomography was obtained. The tomography provides apparent view of the rock damage behind the tunnel. The measured P wave velocity was correlated with features of rock masses, porosity and Q value.

• Ocean Systems Engineering
• /
• v.13 no.2
• /
• pp.173-193
• /
• 2023

Reliable prediction of the motion of FOWT (floating offshore wind turbine) and associated mooring line tension is important in both design and operation/monitoring processes. In the present study, a 5MW OC4 semisubmersible wind turbine is numerically modeled, simulated, and analyzed by the open-source numerical tool, OpenFAST and in-house numerical tool, Charm3D-FAST. Another commercial-level program FASTv8-OrcaFlex is also introduced for comparison for selected cases. The three simulation programs solve the same turbine-floater-mooring coupled dynamics in time domain while there exist minor differences in the details of the program. Both the motions and mooring-line tensions are calculated and compared with the DeepCWind 1/50 scale model-testing results. The system identification between the numerical and physical models is checked through the static-offset test and free-decay test. Then the system motions and mooring tensions are systematically compared among the simulated results and measured values. Reasonably good agreements between the simulation and measurement are demonstrated for (i) white-noise random waves, (ii) typical random waves, and (iii) typical random waves with steady wind. Based on the comparison between numerical results and experimental data, the relative importance and role of the differences in the numerical methodologies of those three programs can be observed and interpreted. These comparative-study results may provide a certain confidence level and some insight of potential variability in motion and tension predictions for future FOWT designs and applications.

• Smart Structures and Systems
• /
• v.31 no.1
• /
• pp.57-68
• /
• 2023

Bridge hangers, such as those in suspension and cable-stayed bridges, suffer from cumulative fatigue damage caused by dynamic loads (e.g., cyclic traffic and wind loads) in their service condition. Thus, the identification of damage to hangers is important in preserving the service life of the bridge structure. This study develops a new method for condition assessment of bridge hangers. The tension force of the bridge and the damages in the element level can be identified using the Bayesian optimization method. To improve the number of observed data, the additional mass method is combined the Bayesian optimization method. Numerical studies are presented to verify the accuracy and efficiency of the proposed method. The influence of different acquisition functions, which include expected improvement (EI), probability-of-improvement (PI), lower confidence bound (LCB), and expected improvement per second (EIPC), on the identification of damage to the bridge hanger is studied. Results show that the errors identified by the EI acquisition function are smaller than those identified by the other acquisition functions. The identification of the damage to the bridge hanger with various types of boundary conditions and different levels of measurement noise are also studied. Results show that both the severity of the damage and the tension force can be identified via the proposed method, thereby verifying the robustness of the proposed method. Compared to the genetic algorithm (GA), particle swarm optimization (PSO), and nonlinear least-square method (NLS), the Bayesian optimization (BO) performs best in identifying the structural damage and tension force.

• Journal of Korean Clinical Health Science
• /
• v.11 no.1
• /
• pp.1639-1643
• /
• 2023

Purpose. We wanted to find out how the changes in brain function affected by the beats per minute (BPM) of music affected visual function. Methods. The subjects were 40 people in their 20s (30 men, 10 women) with no eye disease, strabismus, amblyopia and a corrected visual acuity of 1.0 or higher. Wearing headphones while excluding surrounding noise as much as possible, we played music while adjusting the beat rate at 40 BPM intervals from 80 to 200 BPM. Then, pupil size measurement, lag of accommodation test, and minus lens addition method maximum accommodation test were performed and analyzed. Results. As a result of analyzing changes in visual function according to beats per minute [BPM], it was found that although sound can be consciously affected, it does not directly affect visual function significantly in terms of accommodative lag and changes in pupil size. It was confirmed that the effect was limited to the maximum accommodation. Conclusions. In clinical practice, it is necessary to conduct a refraction test while keeping in mind that there are changes in visual function depending on the BPM of surrounding sounds.

• The Journal of the Acoustical Society of Korea
• /
• v.43 no.2
• /
• pp.178-183
• /
• 2024

This study introduces an enhanced sound source localization technique, bolstered by a data-driven deep learning approach, to improve the precision and accuracy of direction of arrival estimation. Focused on refining Time Difference Of Arrival (TDOA) based sound source localization, the research hinges on accurately estimating TDOA from cross-correlation functions. Accurately estimating the TDOA still remains a limitation in this research field because the measured value from actual microphones are mixed with a lot of noise. Additionally, the digitization process of acoustic signals introduces quantization errors, associated with the sampling frequency of the measurement system, that limit the precision of TDOA estimation. A deep learning-based approach is designed to overcome these limitations in TDOA accuracy and precision. To validate the method, we conduct comprehensive evaluations using both two and three-microphone array configurations. Moreover, the feasibility and real-world applicability of the suggested method are further substantiated through experiments conducted in an anechoic chamber.

• Structural Engineering and Mechanics
• /
• v.90 no.1
• /
• pp.19-26
• /
• 2024

In recent years, an increasing number of experimental studies have shown that the practical application of mature active control systems requires consideration of robustness criteria in the design process, including the reduction of tracking errors, operational resistance to external disturbances, and measurement noise, as well as robustness and stability. Good uncertainty prediction is thus proposed to solve problems caused by poor parameter selection and to remove the effects of dynamic coupling between degrees of freedom (DOF) in nonlinear systems. To overcome the stability problem, this study develops an advanced adaptive predictive fuzzy controller, which not only solves the programming problem of determining system stability but also uses the law of linear matrix inequality (LMI) to modify the fuzzy problem. The following parameters are used to manipulate the fuzzy controller of the robotic system to improve its control performance. The simulations for system uncertainty in the controller design emphasized the use of acceleration feedback for practical reasons. The simulation results also show that the proposed H∞ controller has excellent performance and reliability, and the effectiveness of the LMI-based method is also recognized. Therefore, this dynamic control method is suitable for seismic protection of civil buildings. The objectives of this document are access to adequate, safe, and affordable housing and basic services, promotion of inclusive and sustainable urbanization, implementation of sustainable disaster-resilient construction, sustainable planning, and sustainable management of human settlements. Simulation results of linear and non-linear structures demonstrate the ability of this method to identify structures and their changes due to damage. Therefore, with the continuous development of artificial intelligence and fuzzy theory, it seems that this goal will be achieved in the near future.

• Journal of Environmental Science International
• /
• v.33 no.3
• /
• pp.217-226
• /
• 2024

Manufacturing workers face increased fatigue and stress due to environmental factors in workplace such as noise and vibration. Addressing this issue requires creating conducive rest spaces; however, the existing conditions of rest spaces in manufacturing workplace are subpar and lack sufficient scholarly evidence. This study investigated the effect of nature-based rest spaces on the physical and emotional recovery from fatigue on manufacturing workers. Three manufacturing complexes with nature-friendly rest spaces were selected, and 63 manufacturing workers participated in the study. The measurement tools included the Multidimensional Fatigue Scale (MFS) for fatigue levels, physiological indicators (blood pressure and heart rate), and emotional indicators (Zuckerman Inventory of Personal Reaction Scale; ZIPERS, Perceived Restorativeness Scale; PRS, Profile of Mood States; POMS and State-Trait Anxiety Inventory; STAI). The study compared recovery levels during a 7-minute rest between a space without plants and a space with natural elements. The results indicated a significant reduction in systolic and diastolic blood pressure of participants in green rest spaces compared with those in conventional rest spaces. Regarding fatigue levels, green rest spaces showed a decrease in systolic blood pressure in the middle-fatigue and high-fatigue groups. Positive feelings increased in green spaces, whereas negative emotions decreased, suggesting that short breaks in nature-friendly environments effectively promote workers' physical and emotional recovery. Furthermore, this study emphasizes the importance of green space in various work environments to promote well-being in workers.

• Journal of Advanced Navigation Technology
• /
• v.28 no.2
• /
• pp.193-200
• /
• 2024

This paper describes the design and development of a transmit receiver module(TRM) for mounting on X-band SAR of the NEXTSat-2. The TRM generates the chirp signal with required bandwidth through the DDS in X-band and performs frequency conversion, combination for the signal to transmit and be received and frequency synthesis. Tx path of the TRM produces signals of total 28 bandwidths up to 96.8 MHz and has output signal level of more than + 9.37 dBm. Rx path of the TRM has minimum noise figure of 15.7 dB. The measurement results show that required requirements are satisfied. The TRM is installed on the NEXTSat-2 flight model(FM), launched by KSLV-II(Nuri) on May 23, 2023 and currently operational.