• PNF and Movement
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• v.16 no.3
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• pp.355-363
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• 2018

Purpose: The purpose of this study was to obtain detailed and quantified data concerning the effects of plantarflexor muscle fatigue induced in the non-paretic side on the spatial and temporal gait parameters of the bilateral lower extremities during walking in stroke patients. Methods: This study was conducted on 20 patients with chronic stroke. The load contraction fatigue test was applied to induce muscle fatigue in the non-paretic plantarflexor muscle. Step length, stride length, double support, gait velocity and cadence, and functional ambulatory profile (FAP) score in the bilateral lower extremities were measured using a gait analysis system in order to investigate changes in temporal and spatial gait parameters caused by muscle fatigue on the non-paretic side. The statistical significance of the results was evaluated using a paired t-test. Results: A review of the results for gait parameters revealed a significant increase in double support (p<0.05) and a significant decrease in step length, stride length, gait velocity and cadence, and FAP score (p<0.05). Conclusion: These results indicate that the muscle fatigue in the non-paretic side of the stroke patients also affected the paretic side, which led to a decrease in gait functions. This implies a necessity to perform exercise or training programs in a range of clinical aspects not causing muscle fatigue.

• Earthquakes and Structures
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• v.25 no.5
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• pp.385-398
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• 2023

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.

• The Korean Journal of Physiology and Pharmacology
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• v.16 no.3
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• pp.175-180
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• 2012

Yoga has been known to have stimulatory or inhibitory effects on the metabolic parameters and to be uncomplicated therapy for obesity. The purpose of the present study was to test the effect of an 8-week of yoga-asana training on body composition, lipid profile, and insulin resistance (IR) in obese adolescent boys. Twenty volunteers with body mass index (BMI) greater than the 95th percentile were randomly assigned to yoga (age $14.7{\pm}0.5$ years, n=10) and control groups (age $14.6{\pm}1.0$ years, n=10). The yoga group performed exercises three times per week at 40~60% of heart-rate reserve (HRR) for 8 weeks. IR was determined with the homeostasis model assessment of insulin resistance (HOMA-IR). After yoga training, body weight, BMI, fat mass (FM), and body fat % (BF %) were significantly decreased, and fat-free mass and basal metabolic rate were significantly increased than baseline values. FM and BF % were significantly improved in the yoga group compared with the control group (p<0.05). Total cholesterol (TC) was significantly decreased in the yoga group (p<0.01). HDL-cholesterol was decreased in both groups (p<0.05). No significant changes were observed between or within groups for triglycerides, LDL-cholesterol, glucose, insulin, and HOMA-IR. Our findings show that an 8-week of yoga training improves body composition and TC levels in obese adolescent boys, suggesting that yoga training may be effective in controlling some metabolic syndrome factors in obese adolescent boys.

• Journal of Ginseng Research
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• v.19 no.2
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• pp.93-100
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• 1995

This study was undertaken to determine whether administration of a standardized gindeng extract at 300 mg.$d^1$ for 8 weeks could enhance maximum aerobic and anaerobic exercise capabilities and whether any changes of such effects can be occurred when exercise training was added. Forty-one male university students were randomly divided into four groups as ginseng-untrained (GU, n=10), ginseng-trained (GT, n=10), placebo-untrained (PU, n=10), and placebo-trained (PT, n=11). The trained groups underwent 8 weeks of aerobic exercise at 65% of individual's maximum oxygen consumption ($Vo_2$ max) for 30 min.$d^1$, 3d.$wk^1$. Prior to and at the end of experiment, $Vo_2$ max, anaerobic power (AP), anaerobic capacity (AC), and leg muscle strength were determined and some physiological parameters related to $Vo_2$ max were measured. Initially, all subject groups did not differ in average $Vo_2$ max (range 45.9 to 47.9 ml/.kg-1.min-1). After 8 weeks, the $Vo_2$ max increased significantly from the initial level by 12.6% in group GU, 14.5% in group PT, and 24.5% in group GU which was significantly higher than group GU but not group PT. Changes in all measured parameters related to $Vo_2$ max were similar among the subject groups except group PU. Both the AP and the AC were significantly increased in all subject groups (range +3.6 to +13.1% above initial for the AP and +4.4 to) 8.955 above initial for the AC) but the higher changes were found for the AP in groups PT and GU, and for the AC in grouts PT, when compared with group PU. No significant differences in the two anaerobic variables were observed between group GT and the other groups of subjects. Leg strength was also significantly enhanced over group PU in groups PT, GU and GT. There were no significant differences among the latter three subject groups. As a result of these findings, it was concluded that under the conditions of this study ginseng administration at the prescribed dose exhibited the training-like effects on $Vo_2$ max as well as anaerobic power and leg muscle strength but no clear synergistic action on these physical fitness variables occurred when both g inseng administration and exercise training were combined.

• Journal of Korea Entertainment Industry Association
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• v.15 no.8
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• pp.363-377
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• 2021

The present study investigated the effects of dynamic tubing gait training(I and II) on the postural alignment, gait, and quality of life in chronic patients with Parkinson's disease. This study is based on the case study that recruited a total of 3 patients with chronic Parkinson's disease (Hoehn and Yahr Stage of 1 to 3 each one person). Dynamic tubing gait training (I and II) applied to chronic patients with Parkinson's disease for 25 sessions, 30 minutes a day, 5 days a week, over 5 weeks period. To investigate the effects of this study, evaluating using the postural alignment test, muscle activity tests, gait analysis, and quality of life scale for patient with Parkinson's disease. After the intervention of Dynamic tubing gait training (I and II), Trunk flexion was decreased. Also, during walking from initial contact (IC) to mid stance (Mst), muscle activity of Quadriceps, Hamstring, and Tibialis Anterior (TA) was increased and muscle activity of Gastrocnemius was decreased. The muscle activation of Erector Spinae (ES T12, L3) was increased in the H&Y I and III stages and decreased in the H&Y II stage. Length of gait line, single support line, ant/post position and lateral symmetry of center of pressure (COP) parameters improved. The spatio-temporal gait parameters including of step length, stride length, and velocity was increased, and cadence decreased. Further the quality of life of patients with Parkinson's disease was improved. Based on these findings, Dynamic tubing gait training (I and II) could be applied as a new approach to improve posture, gait, quality of life in chronic patients with Parkinson's disease for more than 5 years, whose drug resistance is halved.

• Journal of Industrial Convergence
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• v.22 no.2
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• pp.97-103
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• 2024

The purpose of this study was to examine the impact of balance training on the Inbody and recovery of the balance capability in stroke patient with obesity. The exercise program was to conduct obesity group and normal weight group, 22 subjects were divided equally into experimental(obesity) and controlled group(normal weight), assigned to excercise using the balance training system for 30min a day and 5 days a week. Every pre and post-experimental data of both groups were gathered by Inbody and BSS(Biodex Medical Systems) for 8 weeks. As a result, Comparing the intra-group data measured by Inbody, obesity group showed significant difference in every parameter (p<.05). In the inter-group data, every parameter showed significant difference between both groups (p<.05). Comparing the intra-group data of LOS(Limits Of Stability), obesity group showed significant difference with all parameters, except with 'Backward' and 'Left' (p<.05). In the inter-group data, 'Forward' parameter showed significant difference. Comparing the intra-group data of PS(Postural Stability), obesity group showed significant difference with all parameters (p<.05). The inter-group PS(Postural Stability) results differed significantly only with 'Med/lat'(p=.000). The above results implicate about the following conclusions that the balance training had a big effect on the Inbody and recovery of the balance capability in stroke patient with obesity.

• Computers and Concrete
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• v.22 no.2
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• pp.249-259
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• 2018

This paper presents Artificial Neural Network (ANN) models for evaluating bond strength of deformed, plain and cold formed bars in low strength concrete. The ANN models were implemented using the experimental database developed by conducting experiments in three different universities on total of 138 pullout and 108 splitting specimens under monotonic loading. The key parameters examined in the experiments are low strength concrete, bar development length, concrete cover, rebar type (deformed, cold-formed, plain) and diameter. These deficient parameters are typically found in non-engineered reinforced concrete structures of developing countries. To develop ANN bond model for each bar type, four inputs (the low strength concrete, development length, concrete cover and bar diameter) are used for training the neurons in the network. Multi-Layer-Perceptron was trained according to a back-propagation algorithm. The ANN bond model for deformed bar consists of a single hidden layer and the 9 neurons. For Tor bar and plain bars the ANN models consist of 5 and 6 neurons and a single hidden layer, respectively. The developed ANN models are capable of predicting bond strength for both pull and splitting bond failure modes. The developed ANN models have higher coefficient of determination in training, validation and testing with good prediction and generalization capacity. The comparison of experimental bond strength values with the outcomes of ANN models showed good agreement. Moreover, the ANN model predictions by varying different parameters are also presented for all bar types.

• Quality Improvement in Health Care
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• v.23 no.2
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• pp.11-20
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• 2017

Purpose: The purpose of this study was to determine the effects of rotation direction during curved walking on gait parameters in stroke patients. Methods: A group of thirty subjects with stroke (Berg Balance Scale score${\geq}41$ were fifteen, Berg Balance Scale score${\leq}40$ were fifteen) were enrolled in this study. Testing indications included two directions for rotation in each subject. These indications were for rotation toward the affected and unaffected side in stroke patients. The gait speed, affected side single support duration, affected side double support duration were recorded. The obtained data were analyzed by using paired t-test and Wilcoxon signed rank test in the group that are below and above 40 points of Berg Balance Scale score. Results: There was significant increase affected side single support duration was turned the affected side in stroke patients that presented a Berg Balance Scale score${\geq}41$ (p<.05). There were significant increase gait speed, affected side single support duration, and significant decrease affected side double support duration while subjects were turned the affected side in stroke patients that presented a Berg Balance Scale score${\leq}40$ (p<.05). Conclusion: This result may be effective to rotate in the paralyzed direction to improve the ability of the paralyzed lower limb to gain weight during gait training for stroke patients with a Berg Balance Scale score<40. Therefore, walking training program for hemiplegic patient needs to be suggested in the direction of turning for suitable balance ability.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.7
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• pp.327-332
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• 2016

This study is a leading research project to develop an automatic grade decision making algorithm of a 6-years-old fresh ginseng. For this work, we developed a Ginseng image acquiring instrument which can take 4-direction's images of a Ginseng at the same time and obtained 245 jingen images using the instrument. The 12 parameters were extracted for each image by a manual way. Lastly, 4 parameters were selected depending on a Ginseng grade classification criteria of KGC Ginseng research institute and a survey result which a distribution of averaging 12 parameters. A pattern recognition classifier was used as a support vector machine, designed to "k-class classifier" using the OpenCV library which is a open-source platform. We had been surveyed the algorithm performance(Correct Matching Ratio, False Acceptance Ratio, False Reject Ratio) when the training data number was controlled 10 to 20. The result of the correct matching ratio is 94% of the $1^{st}$ ginseng grade, 98% of the $2^{nd}$ ginseng grade, 90% of the $3^{rd}$ ginseng grade, overall, showed high recognition performance with all grades when the number of training data are 10.

• Journal of ILASS-Korea
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• v.27 no.2
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• pp.57-65
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• 2022

The purpose of this study is to use machine learning to build a model capable of predicting the flash boiling spray characteristics. In this study, the flash boiling spray was visualized using Shadowgraph visualization technology, and then the spray image was processed with MATLAB to obtain quantitative data of spray characteristics. The experimental conditions were used as input, and the spray characteristics were used as output to train the machine learning model. For the machine learning model, the XGB (extreme gradient boosting) algorithm was used. Finally, the performance of machine learning model was evaluated using R² and RMSE (root mean square error). In order to have enough data to train the machine learning model, this study used 12 injectors with different design parameters, and set various fuel temperatures and ambient pressures, resulting in about 12,000 data. By comparing the performance of the model with different amounts of training data, it was found that the number of training data must reach at least 7,000 before the model can show optimal performance. The model showed different prediction performances for different spray characteristics. Compared with the upstream spray angle and the downstream spray angle, the model had the best prediction performance for the spray tip penetration. In addition, the prediction performance of the model showed a relatively poor trend in the initial stage of injection and the final stage of injection. The model performance is expired to be further enhanced by optimizing the hyper-parameters input into the model.