Recently, the recognition is changing about cultural heritage, and the various types of buildings or facilities of modern or contemporary times have been designated as cultural properties after that Registered Cultural Properties System is enforced. The purpose of this study is to survey how the newly born the historic buildings of modern or contemporary times through the remodeling process of the Studio 'Byeol'(the Training Center for Performers of Korean Traditional Music) in the National Theater of Korea so-called a microcosm of performing arts history. In the process, it will examine the merits and demerits of various alternatives and the direction of the remodeling etc., and propose an utilization as a basic data of post evaluation for the remodeling of a historic building. The result are as followings. Firstly, the remodeling that gave a new physical properties to a building can be used a method of conservation and reuse on a historic building. The remodeling of a historic building must be eclectically progress between the owner and the citizen or the economic value and the historicity conservation. And, the remodeling of historic buildings such as the Training Center for Performers of Korean Traditional Music must consider the conservation of the exterior walls in whole or in part at least. Secondly, an architect Lee Hee Tae(李喜泰) who had been to develop his own architectural vocabulary and to test based on the korean traditional architecture and the Training Center for Performers of Korean Traditional Music must be newly evaluated today. Lastly, the remodeling alternatives of the Training Center for Performers of Korean Traditional Music have been analyzed with three types, which is 'repairing only the interior which maintains the size and an appearance of present', 'extending the outer wall to the external column line', 'extending the basement'. And, it was analyzed with the appropriate final decision that it remodels only the interior in the current situation because of a historicity, a budget, a relevant law etc.
To evaluate the effect of interface conditions and retention grooves in the Class V composite resin restoration of the maxillary first premolar, the distribution of the values of stress and displacement was analyzed with the two-dimensional finite element method. The results were obtained as follows : 1. Boundary elements and Stiffness values could be used as the interface parameters in the, finite element method. 2. The amount of restriction of the displacement at the cervical margin by placing a retention groove at the cervical wall was about three times as high as that by placing a retention groove at the occlusal wall. 3. Because of the relative amount of tensile components of the stress values in the bucco-lingual direction, the possibility of dislocation of the restoration was much higher at the cervical margin than at the occlusal margin. 4. It might be recommended that both occlusal and cervical retention grooves be used routinely, but if one, it be placed at the cervical wall.
The parameters of the multiple-vertical-line-element model (MVLEM) of reinforced concrete (RC) shear walls are often empirically determined, which causes large simulation errors. To improve the simulation accuracy of the MVLEM for RC shear walls, this paper proposed a novel method to determine the MVLEM parameters using the artificial neural network (ANN). First, a comprehensive database containing 193 shear wall specimens with complete parameter information was established. And the shear walls were simulated using the classic MVLEM. The average simulation errors of the lateral force and drift of the peak and ultimate points on the skeleton curves were approximately 18%. Second, the MVLEM parameters were manually optimized to minimize the simulation error and the optimal MVLEM parameters were used as the label data of the training of the ANN. Then, the trained ANN was used to generate the MVLEM parameters of the collected shear walls. The results show that the simulation error of the predicted MVLEM was reduced to less than 13% from the original 18%. Particularly, the responses generated by the predicted MVLEM are more identical to the experimental results for the testing set, which contains both flexure-control and shear-control shear wall specimens. It indicates that establishing MVLEM for RC shear walls using ANN is feasible and promising, and that the predicted MVLEM substantially improves the simulation accuracy.
Kim, Hyun-Su;Kim, Yukyung;Lee, So Yeon;Jang, Jun Su
Journal of Korean Association for Spatial Structures
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v.24
no.2
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pp.83-90
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2024
Machine learning is widely applied to various engineering fields. In structural engineering area, machine learning is generally used to predict structural responses of building structures. The aging deterioration of reinforced concrete structure affects its structural behavior. Therefore, the aging deterioration of R.C. structure should be consider to exactly predict seismic responses of the structure. In this study, the machine learning based seismic response prediction model was developed. To this end, four machine learning algorithms were employed and prediction performance of each algorithm was compared. A 3-story coupled shear wall structure was selected as an example structure for numerical simulation. Artificial ground motions were generated based on domestic site characteristics. Elastic modulus, damping ratio and density were changed to considering concrete degradation due to chloride penetration and carbonation, etc. Various intensity measures were used input parameters of the training database. Performance evaluation was performed using metrics like root mean square error, mean square error, mean absolute error, and coefficient of determination. The optimization of hyperparameters was achieved through k-fold cross-validation and grid search techniques. The analysis results show that neural networks and extreme gradient boosting algorithms present good prediction performance.
Park, Se-Ju;Lee, So-In;Park, Sung-Hwan;Cho, Woon-Soo
Journal of the Korea Academia-Industrial cooperation Society
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v.19
no.8
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pp.254-259
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2018
This study was conducted to investigate the effects of therapeutic climbing training on postural alignment and balance of normal adults and to suggest possibilities for clinical intervention. The study investigated 30 normal adults who were randomly assigned to either a training group or a control group (n= 15 each). The training group performed climbing training on the climbing wall three times a week for 6 weeks for a total of 40 minutes, while the control group did not perform any training. Biorecue was used to evaluate balance ability, while formetric was used for evaluation of postural alignment. The results showed that there was a significant difference in body slope between the groups in posture alignment (p<.05), as well as in balance ability (p<.05) and time and group interaction (p<.05). In this study, climbing training affected the posture alignment of normal adults, increased the left and right torso tilt and positively affected balance ability. Therefore, these findings confirm that training using climbing is valuable for rehabilitation and clinical application intervention of the general public and patients.
The purpose of this study was to investigate disinfection state and effective factors of foodservice facilities and utilities of elementary schools in Busan area. Foodservice facilities and utilities investigated in this study were ceiling, wall, floor, trench, greasetrap, hood, pest and dumb waiter. The questionnaire which was administered to 196 dietitians was used as a survey method. The results were as follows. The washing method of foodservice facilities and utilities was mainly used by detergent washing-natural dry. The disinfection method of foodservice facilities and utilities was mainly sanitized by sodium hypochlorite. Dumb waiter and hood were sanitized by 70% ethyl alcohol and iodine. In washing and disinfection frequencies of foodservice facilities and utilities ceiling was twice/year, wall, hood and pest control facilities were once/week, floor, trench, greasetrap and dumb waiter were everyday, respectively. Floor, trench, greasetrap and dumb waiter were disinfected properly, whereas ceiling, wall, hood and pest were not disinfected properly. The washing method was related to dietitian's marital status and education. The disinfection state was related to dietitian's age and career, having of sanitation check list. The disinfection method was also affected dietitian's marital status, number of employee, duration of foodservice, number of total serving and having of sanitation check list. Therefore based on the results of this study, it should be given to the microbiological study on disinfection of facilities and utilities such as ceiling, wall, floor, trench, greasetrap, hood, pest and dumb waiter and the dietitian and employee's sanitation training also should be conducted continuously.
Purpose: Due to the high incidence of shoulder injuries, including shoulder impingement syndrome (SIS), among CrossFit practitioners due to frequent overhead movements, serratus anterior exercises are considered crucial for scapular stabilization in both intervention and prevention. Objective: The objective of this study is to compare the muscle activity and ratios of scapular stabilizing and shoulder girdle muscles between individuals with and without SIS during serratus punch and wall slide exercises, both targeting the serratus anterior muscle, in CrossFit training practitioners. Methods: Surface electromyography was used to compare the muscle activity and activity ratio of scapular stabilizing muscles and shoulder muscles during serratus punch and wall slide exercises in two groups of 20 CrossFit practitioners: ten with SIS and ten without symptoms. Results: The group with SIS showed higher activation of the pectoralis major, upper trapezius, and a higher pectoralis major/serratus anterior and upper trapezius/serratus anterior muscle activation ratio during the serratus punch exercise compared to the group without SIS. Similarly, during the wall slide exercise, the group with SIS exhibited higher activation of the upper trapezius and a higher upper trapezius/serratus anterior muscle activation ratio compared to the group without SIS. However, no significant difference in serratus anterior muscle activation was observed between the two groups. Conclusions: This study highlights the higher activation of the pectoralis major and upper trapezius muscles in CrossFit practitioners with SIS during the serratus anterior exercise, suggesting the importance of minimizing the overactivation of these muscles to prevent impingement syndrome in this population.
To investigate the stability of temporary retaining walls during excavation, it is essential to develop reverse analysis technologies capable of precisely evaluating the properties of the ground and a learning model that can assess stability by analyzing real-time data. In this study, we targeted excavation sites where the C.I.P method was applied. We developed a Deep Neural Network (DNN) model capable of evaluating the stability of the retaining wall, and estimated the physical properties of the ground being excavated using a Differential Evolution Algorithm. We performed reverse analysis on a model composed of a two-layer ground for the applicability analysis of the Differential Evolution Algorithm. The results from this analysis allowed us to predict the properties of the ground, such as the elastic modulus, cohesion, and internal friction angle, with an accuracy of 97%. We analyzed 30,000 cases to construct the training data for the DNN model. We proposed stability evaluation grades for each assessment factor, including anchor axial force, uneven subsidence, wall displacement, and structural stability of the wall, and trained the data based on these factors. The application analysis of the trained DNN model showed that the model could predict the stability of the retaining wall with an average accuracy of over 94%, considering factors such as the axial force of the anchor, uneven subsidence, displacement of the wall, and structural stability of the wall.
Objective : Respiratory muscle weakness and decreased chest mobility has been suggested to result from the deconditioning that accompanied activity level in chronic elderly stokes. The benefits of respiratory exercise programmes on exercise capacity and muscle strength in hemiplegia. This study aimed to determine the effects of selective inspiratory and expiratory muscles training and chest mobility exercise on patients with strokes to establish if an improved exercise capacity can be obtained in patients that are not limited in their daily activities. Methods & Intervention : Twelve patients were assigned to the intensive respiratory exercise group participated in a measures design that evaluated the subjects with pre-treatment and post-treatment. Thirteen subjects who were assigned to a control group received training with breathing exercise and resistance exercise of skeletal muscles. The subjects performed spirometry then undertook a 6-week programme of respiratory muscle and chest mobility training. Training for the two groups was carried out 2 times a week for 6 weeks. Measurements and Results : Spirometry(Forced Vital Capacity: FVC and Closed Circuit Spiromety: CCS) and thoracic mobility were measured before and after the 6 weeks. The experimental group improved significantly compared to control group in FVC, $FEV_1$, MVV, IRV and ERV, and upper chest wall expansion(p<0.05). No significant improvement was seen in thoracic mobility or lung function in control group(p>0.05). Conclusion : The major findings in this study were that a intensive 6week exercise programme of resistive breathing and chest mobility in patients with hemiplegia led to an increase in lung capacity. The resistive breathing exercise programme used here resulted in a significant increase in the chest excursion during breathing.
Mahmoodzadeh, Arsalan;Nejati, Hamid Reza;Mohammadi, Mokhtar;Ibrahim, Hawkar Hashim;Mohammed, Adil Hussein;Rashidi, Shima
Geomechanics and Engineering
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v.31
no.3
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pp.265-279
/
2022
Tunnel convergence prediction is essential for the safe construction and design of tunnels. This study proposes five machine learning models of deep neural network (DNN), K-nearest neighbors (KNN), Gaussian process regression (GPR), support vector regression (SVR), and decision trees (DT) to predict the convergence phenomenon during or shortly after the excavation of tunnels. In this respect, a database including 650 datasets (440 for training, 110 for validation, and 100 for test) was gathered from the previously constructed tunnels. In the database, 12 effective parameters on the tunnel convergence and a target of tunnel wall convergence were considered. Both 5-fold and hold-out cross validation methods were used to analyze the predicted outcomes in the ML models. Finally, the DNN method was proposed as the most robust model. Also, to assess each parameter's contribution to the prediction problem, the backward selection method was used. The results showed that the highest and lowest impact parameters for tunnel convergence are tunnel depth and tunnel width, respectively.
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