• 대한물리치료과학회지
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• 제24권2호
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• pp.9-16
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• 2017

Purpose: This study was conducted in order to examine the changes of muscle activitis of erector spine muscles and Gluteus maximus during the bridge exercise with adductor muscles. Method: After attaching the EMG device to the Gluteus maximus and erector spine muscles of the 100 healthy adult males in their 20s, applying the stabilizer pressure biofeedback device between the knees, the bridge movement was carried out 10 seconds. Result: During the exercise of the bridge movement, the muscular activities in erector spine and gluteus maximus were significantly different in ralation to the simultaneous contractive adductor muscles of the bridge(p<.05). Conclusion: Thus, the bridge exercise is carried out in conjunction with the simultaneous contraction of adductor muscles that suggests that the training are more effective in erector spine and gluteus maximus activities.

• Structural Engineering and Mechanics
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• 제71권2호
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• pp.175-183
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• 2019

This paper deals with damage detection in a girder bridge using transmissibility functions as input data to Artificial Neural Networks (ANNs). The original contribution in this work is that these two novel methods are combined to detect damage in a bridge. The damage was simulated in a real bridge in Vietnam, i.e. Ca-Non Bridge. Finite Element Method (FEM) of this bridge was used to show the reliability of the proposed technique. The vibration responses at some points of the bridge under a moving truck are simulated and used to calculate the transmissibility functions. These functions are then used as input data to train the ANNs, in which the target is the location and the severity of the damage in the bridge. After training successfully, the network can be used to assess the damage. Although simulated responses data are used in this paper, the practical application of the technique to real bridge data is potentially high.

• 한국전산구조공학회논문집
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• 제16권3호
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• pp.229-236
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• 2003

손상평가를 위해 많은 연구자들에 의해 인공신경망이 이용되어 왔다. 그러나, 인공신경망을 이용한 손상평가에 있어 정확성과 능률성을 제고하기 위해서는 몇가지 문제점이 있다. 기존의 인공신경망 특히 역전파신경망(BPNN)의 경우 신경망 학습을 위해 많은 수의 학습패턴을 필요로 하며, 또한 신경망의 구조와 해의 수렴간에 어떤 확정적인 관계가 존재하지 않는다. 따라서 신경망의 은닉층의 수와 한 은닉층에서의 노드수는 시행착오적으로 결정되게 된다. 이러한 많은 훈련패턴의 준비와 최적의 신경망 구조 결정을 위해서는 많은 시간이 필요하다. 본 논문에서는 이러한 단점들을 극복하기 위해 확률신경망을 패턴분류기로 사용하였다. 이를 판형철도교의 손상평가에 수치해석적으로 검증하였다. 또한 확률신경망을 이용한 철도판형교 손상평가시 적절한 훈련패턴 선택을 위해 모드형상과 고유진동수를 사용한 경우의 적용성에 대해 검토하였다.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2002년도 가을 학술발표회 논문집
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• pp.227-236
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• 2002

The purpose of this study makes a retrofit and rehabilitation practice trough the analysis and the improvement for the underlying problem of current retrofit and rehabilitation methods. Therefore, the deterioration process, the damage cause, the condition classification, the fatigue mechanism and the applied quantity of strengthening methods for RC deck slabs were analyzed. Artificial neural networks are efficient computing techniques that are widely used to solve complex problems in many fields. In this study, a back-propagation neural network model for estimating a management on existing reinforced concrete bridge decks from damage cause, damage type, and integrity assessment at the initial stage is need. The training and testing of the network were based on a database of 36. Four different network models were used to study the ability of the neural network to predict the desirable output of increasing degree of accuracy. The neural networks is trained by modifying the weights of the neurons in response to the errors between the actual output values and the target output value. Training was done iteratively until the average sum squared errors over all the training patterns were minimized. This generally occurred after about 5,000 cycles of training.

• Structural Engineering and Mechanics
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• 제85권4호
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• pp.469-484
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• 2023

A deep recursive bidirectional Cuda Deep Neural Network Long Short Term Memory (Bi-CuDNNLSTM) layer is recruited in this paper to predict the entire force time histories, and the corresponding hysteresis and backbone curves of reinforced concrete (RC) bridge piers using experimental fast and slow cyclic tests. The proposed stacked Bi-CuDNNLSTM layers involve multiple uncertain input variables, including horizontal actuator displacements, vertical actuators axial loads, the effective height of the bridge pier, the moment of inertia, and mass. The functional application programming interface in the Keras Python library is utilized to develop a deep learning model considering all the above various input attributes. To have a robust and reliable prediction, the dataset for both the fast and slow cyclic tests is split into three mutually exclusive subsets of training, validation, and testing (unseen). The whole datasets include 17 RC bridge piers tested experimentally ten for fast and seven for slow cyclic tests. The results bring to light that the mean absolute error, as a loss function, is monotonically decreased to zero for both the training and validation datasets after 5000 epochs, and a high level of correlation is observed between the predicted and the experimentally measured values of the force time histories for all the datasets, more than 90%. It can be concluded that the maximum mean of the normalized error, obtained through Box-Whisker plot and Gaussian distribution of normalized error, associated with unseen data is about 10% and 3% for the fast and slow cyclic tests, respectively. In recapitulation, it brings to an end that the stacked Bi-CuDNNLSTM layer implemented in this study has a myriad of benefits in reducing the time and experimental costs for conducting new fast and slow cyclic tests in the future and results in a fast and accurate insight into hysteretic behavior of bridge piers.

• 실천공학교육논문지
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• 제15권2호
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• pp.259-271
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• 2023

본 연구의 목적은 산업체 수요에 부합하고 외부 환경변화와 트렌드에 기민하게 대응하는 기업 맞춤형 자격 제도를 통해 직업훈련 활성화 방안을 마련하는 것이다. 이를 위해 직업능력개발사업의 현황 및 한계, 국내 자격제도 현황 및 한계, 직업능력개발 관련 정부 정책, 기업 인사담당자 FGI, 중소기업 인사담당자 설문, 전문가 자문 등을 통해 교육훈련 결과 인증 기반의 자격 체계 수립, 수요자인 기업 중심으로 자격체계를 전략으로 설정하여 지역 기업 기반의 맞춤형 자격운영 체계로 BRIDGE 3.0 모델을 제시하였다.

• Computers and Concrete
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• 제3권1호
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• pp.29-42
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• 2006

In this study, a novel education system for inspection of concrete bridges is presented. The new education approach uses virtual reality (VR) and three-dimensional computer graphics (3DCG) in training engineers to become bridge inspection specialists. The slow time-dependent deterioration of concrete bridges can be reproduced on the computer screen in any chosen time frame, thus providing the trainees with illustrative and educative insight into the deterioration problem. In the proposed VR/3DCG approach a three-dimensional model of concrete bridge, including surfaces, viewpoints and walkthrough paths is created. With the help of this virtual bridge model, an experienced bridge inspection specialist teaches the different deterioration phenomena of concrete bridges to the trainees. The new system was tested, and the inspection results from the case bridge showed that in comparison with the traditional Japanese bridge inspection education system, the new system gives better results. In addition to the improvement of quality of bridge inspections, the new VR/3DCG system-based education brings along some other, more intangible benefits.

• 해양환경안전학회지
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• 제8권1호
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• pp.53-59
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• 2002

A correctly designed bridge offers improved operational safety in terms of increased vigilance, flexibility of operation, precision of control and operator＇s situational awareness. According1y to design human centered bridge, the consideration shall be given to the man-machine interface, location and interrelation of workstation, configuration of console, windows. field of vision and bridge working environment. The state-of-the-art suits for one-man operation by integration of conning information and central information presentation. Further, it is desirable to enable two man ship operation for emergency operations, training purposes and redundancy. In this point of view, this thesis would like to design a conceptual bridge.

• 웰빙융합연구
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• 제5권1호
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• pp.31-35
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• 2022

Purpose: This study was conducted to investigate the effects of change in the unstable support surface location during bridge exercise on the muscle activity of erector spinae and gluteus maximus. Research design, data and methodology: 12 healthy participants aged 23.32 ±1.02 were measured muscle activities of erector spinae and gluteus maximus during bridge exercise and compared between the exercise conditions; unstable support surface located on upper back and feet during bridge exercise. Paired t-test was performed to identify whether there was a significant difference in the muscle activities between the exercise conditions. Results: As a result, even though higher levels of the averaged muscle activities of both erector spinae and gluteus maximus during exercise in unstable support surface located on feet than upper back were observed, no significant differences were found. Conclusions: The change of unstable support surface location during bridge exercise for low back pain rehabilitation would be more appropriate to be used to increase levels of tension of muscle activities and train fine motor control rather than to strengthening muscle strength.

• 한국전문물리치료학회지
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• 제27권4호
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• pp.250-256
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• 2020

Background: Unstable surface-based core training can significantly enhance core strength, but no studies have compared the effects of balance pad- and sling-assisted exercises. Objects: To study the effects of unstable surface-based balance pad- and sling-assisted core strength exercises on muscle activity. Methods: Twenty male students aged 20-25 years participated in this study. The effects of three types of core strength exercises, performed with a sling or balance pad, on the activities of three muscles, i.e., the right musculus obliquus externus abdominis (EO), right erector spinae (ES), and right gluteus maximus (GM), were examined. Results: 1) In the glute bridge exercise, the percentage of maximum voluntary contraction of the EO, ES, and GM were significantly different between the balance pad- and sling-assisted exercises. The relative contribution of the ES and GM activities to all muscle activity were not significantly different between the two training types, whereas that for EO showed a significant difference. 2) There was no significant difference in the percentage value of maximum voluntary contraction (%MVC) among the EO, ES, and GM during the "leg-lifting with flat support" exercise, and there were no significant difference in the relative contributions between the two training types. 3) In the "side bridge leg separation exercise", the %MVC of the ES, EO, and GM were significantly different between the two training types. Conclusion: Sling training for core muscles was generally better than balance pad assist training. The majority of physiotherapy patients require core training. Our results could guide physiotherapists in the choice of targeted exercises for these patients.