• Journal of the Korean Applied Science and Technology
• /
• v.37 no.3
• /
• pp.496-508
• /
• 2020

This study reviews studies on the core stabilization of respiratory muscle training for the elderly health. Previous research data and presenting basic literature data suggest that respiratory activation is an important mechanism for core strengthening via exercise interventions for the elderly. The review found that first, the mechanism of improving the respiratory muscles weakened by aging to address the loss of core function due to old age sarcopenia among the elderly results entails promoting the autonomic nervous system by focusing on the respiratory muscle activation pattern, the core muscle sensation mobilized for body centering. Second, nerve roots, intraperitoneal pressure, and deep muscles in the trunk of the body can be promoted while controlling respiratory stimulation with cognitive feedback. Effortful inspiration increases the activation of respiratory assistive muscles and effortless exhalation can improve the core muscle mobilization by involving abdominal muscles. Third, through respiratory muscle training, the elderly can increase their awareness of spinal centering and improve the ability to control the deep core muscles that must be mobilized for core stabilization. In conclusion, respiratory muscle training to increase the utilization of the trunk muscles seems to be a useful core stabilization exercise for the elderly with chronic tension and joint degeneration.

• International Journal of Advanced Culture Technology
• /
• v.7 no.4
• /
• pp.23-31
• /
• 2019

This study was a quasi-experimental study with a single group pre-posttest design for evaluating the effects and meanings of a global health training program for nursing students. A mixed data collection method utilizing both qualitative and quantitative methods was applied. The qualitative method consisted of reflection journal entry analysis, while the quantitative study evaluated data collected from a self-reported questionnaire. After attending the program, cultural competencies of participants significantly increased than pre-test while global citizenship was not. Through an analysis of reflection journals written during the overseas training period, the meanings of experiences derived after the program were classified into five themes and 12 sub themes, which were, 'improvement of global health leadership', 'experience of barriers in reality', 'improvement of nursing professional value', 'inspiration of a perspective on health equity', and 'internal growth'. The results indicate that global health training program evaluated in this study was meaningful; it provided students with opportunities to experience the nurse's role in diverse global environments and attempted to measure the effects.

• International Journal of Industrial Entomology and Biomaterials
• /
• v.7 no.2
• /
• pp.117-125
• /
• 2003

To know the impact of female pupal weight corresponding to the male cocoon shell weight upon fecundity, hatchability and percentage of non-viable eggs, the experimental multivoltine breeds namely BL67 and 96A were categorised into low, medium and high batches according to the weight of female pupae and male cocoon shells and moths emerged from low, medium and high female pupae were allowed to mate withmoths emerged from low, medium and high male cocoon shells. Both the experimental breeds of BL67 and 96A revealed a fairl trend in fecundity for high batch ＞ medium batch ＞ low batch. When data were statistically analysed, a significant (p ＜ 0.05) and a highly significant (p ＜ 0.01) increase in fecundity was observed in the medium and high batches of BL67 during November - December, 2002 whereas highly significant (p ＜ 0.01) increase was observed in the high batches of 96A during November - December, 2002. Data revealed a highly significant (p ＜ 0.01) increase in fecundity in medium and high batches of both the breeds during January - February, 2003. More interestingly, a significant (p ＜ 0.05) reduction was noted in percentage of non-viable eggs in high batches of 96A during January - February, 2003. But no significant variation in hatchability was noticed due to the effect of differential female pupal weight and male cocoon shell weight.

• The Korean Journal of Emergency Medical Services
• /
• v.20 no.2
• /
• pp.21-35
• /
• 2016

Purpose: This study aims to investigate awareness and performance of infection control during ambulance attendant training, and to provide basic data for infection control. Methods: The subjects were 235 paramedic students who completed ambulance attendant training. There were 51 questions. The infection control dimension was divided into hand washing, personal protective equipment use, and environmental management, for each sub-dimension, awareness and performance were measured by a 4-point scale. The collected data were analyzed using SPSS statistics ver. 22.0. Results: A total of 95.3%, of the subjects completed an orientation for ambulance attendant training and 71.7% received education on infection. In all three sub-dimensions, hand- washing (p<.001), personal protective equipment use (p<.001), and environmental management (p<.001), awareness scored higher than performance. The awareness of infection control showed a significantly positive correlation (r=.394) with performance. Conclusion: In order to improve performance of infection control, education to improve awareness should be provided, and paramedics with higher performance levels in hand washing, and use of gloves and masks wearing should be assigned as training advisors.

• International Journal of Internet, Broadcasting and Communication
• /
• v.11 no.4
• /
• pp.31-36
• /
• 2019

Unsupervised neural networks have not caught enough attention until Generative Adversarial Network (GAN) was proposed. By using both the generator and discriminator networks, GAN can extract the main characteristic of the original dataset and produce new data with similarlatent statistics. However, researchers understand fully that training GAN is not easy because of its unstable condition. The discriminator usually performs too good when helping the generator to learn statistics of the training datasets. Thus, the generated data is not compelling. Various research have focused on how to improve the stability and classification accuracy of GAN. However, few studies delve into how to improve the training efficiency and to save training time. In this paper, we propose a novel optimizer, named FAST-ADAM, which integrates the Lookahead to ADAM optimizer to train the generator of a semi-supervised generative adversarial network (SSGAN). We experiment to assess the feasibility and performance of our optimizer using Canadian Institute For Advanced Research - 10 (CIFAR-10) benchmark dataset. From the experiment results, we show that FAST-ADAM can help the generator to reach convergence faster than the original ADAM while maintaining comparable training accuracy results.

• Journal of Engineering Education Research
• /
• v.21 no.5
• /
• pp.40-53
• /
• 2018

The purpose of this study was to investigate the factors affecting the satisfaction of the program for the quality improvement of the long-term on-site training operated by the university. The survey questionnaire data of 393 students who participated in the IPP program of K university were used to analyze the data and the results were as follows: First, factors affecting the satisfaction of long-term on-site training were corporation factors and university factors. Specifically, job contents, coaching, job scope, center support were found to have a significant effect in that order. Second, the factors affecting the satisfaction of long-term on-site training were different according to group characteristics(IPP participation types, major types, corporation types). It is necessary to intensively manage the common and important corporation factors, and it is necessary to closely examine each factor derived from group characteristics, and to support and strive at university level according to group characteristics in student counseling and matching.

• Journal of Labour Economics
• /
• v.43 no.4
• /
• pp.179-203
• /
• 2020

This study aims to compare and analyze the impact of labor unions on job training programs using two different longitudinal data, Workplace Panel Survey (WPS) and Korean Labor and Inocme Panel Study (KLIPS). By applying the Correlated Random Effect (CRE) model to both individual-level and establishment-level data, we observe that labor unions increase the likelihood that establishments provide employees with job training programs and workers participate in the trainings. Our results shed light on the role of labor unions to increase the opportunities of job training programs for workers.

• Tribology and Lubricants
• /
• v.38 no.4
• /
• pp.152-161
• /
• 2022

Chemical mechanical planarization (CMP) is a technology that planarizes the surfaces of semiconductor devices using chemical reaction and mechanical material removal, and it is an essential process in manufacturing highly integrated semiconductors. In the CMP process, a conditioning process using a diamond conditioner is applied to remove by-products generated during processing and ensure the surface roughness of the CMP pad. In previous studies, prediction of pad wear by CMP conditioning has depended on numerical analysis studies based on mathematical simulation. In this study, using an artificial neural network, the ratio of conditioner coverage to the distance between centers in the conditioning system is input, and the average conditioning density, standard deviation, nonuniformity (NU), and conditioning density distribution are trained as targets. The result of training seems to predict the target data well, although the average conditioning density, standard deviation, and NU in the contact area of wafer and pad and all areas of the pad have some errors. In addition, in the case of NU, the prediction calculated from the training results of the average conditioning density and standard deviation can reduce the error of training compared with the results predicted through training. The results of training on the conditioning density profile generally follow the target data well, confirming that the shape of the conditioning density profile can be predicted.

• The Journal of Asian Finance, Economics and Business
• /
• v.9 no.5
• /
• pp.11-18
• /
• 2022

Current research intended to measure the spillovers of education and on-the-job training to enhance sustainable economic development. Consideration of research and development expenditures for on-the-job training expands the impact of education and, thus, may provide spillovers for Pakistan's economic growth. The primary focus of this research is to look at the combined impact of education and research and development spending as value-added variables for sustainable growth. The econometric study uses data from a variety of sources, including the Pakistan Bureau of Statistics, the Pakistan Economic Survey, and world development indices. The secondary annual time series data from 1976 to 2019 are analyzed. To adequately estimate the empirical model, ARDL has been used while the presence of the unit root has been tested using the ADF test. The findings show that education, research, and development all contribute to all-inclusive, sustainable economic growth. Labor and capital, among other traditional components, continue to be the backbone of the development process. Still, the spillover effect is much enhanced with the expansion in education and the on-job training in the form of research and development expenditures. Consequently, the introduction of research and development in education will lead to a sustainable and inclusive economy.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2009.05a
• /
• pp.1207-1210
• /
• 2009

The goal of this research is to apply the neural networks models for the disaggregation of the pan evaporation (PE) data, Republic of Korea. The neural networks models consist of generalized regression neural networks model (GRNNM) and multilayer perceptron neural networks model (MLP-NNM), respectively. The disaggregation means that the yearly PE data divides into the monthly PE data. And, for the performances of the neural networks models, they are composed of training and test performances, respectively. The training and test performances consist of the only historic data, respectively. From this research, we evaluate the impact of GRNNM and MLP-NNM for the disaggregation of the nonlinear time series data. We should, furthermore, construct the credible data of the monthly PE data from the disaggregation of the yearly PE data, and can suggest the methodology for the irrigation and drainage networks system.