• Journal of The Korean Society of Integrative Medicine
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• v.8 no.4
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• pp.125-131
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• 2020

Purpose : Lower extremity orthoses have been used as conservative methods to recover gait of the stroke patients. The purpose of this study is to examine how newly designed pelvic belt orthosis can improve gait ability and dynamic balance of adults with Hemiparesis after stroke. Methods : 22 patients who had hemiparesis after stroke participated in this study. Two groups were randomly created by assigning 10 subjects to the experimental group and the rest of the 12 subjects to the control group. The control group was treated by conventional physical therapy and occupational therapy. Identical therapy protocols were used to treat the experimental group who were assigned to wear the pelvic belt orthosis during post measurement. This study has a group of independent variables including group, gender, age, height, MAS, lesion side, cause and a group of dependent variables including gait speed, cadence, step length, stride length, and dynamic balance. The GAITRite system was used to measure spatial-temporal gain parameters and the balance system SD to measure dynamic balance. The data was analyzed using R version 3.3.1. Random forest, boosting algorithm, and MANOVA test were conducted to determine the effects of independent variables on dependent variables. Results : This study has a group of independent variables including group, gender, age, height, MAS, lesion side, cause and a group of dependent variables including gait speed, cadence, step length, stride length, and dynamic balance. The independent variable "group" has the most important value, which is approximately 25.42 (%IncMSE) representing a value three times greater than the second important predictor "height." Conclusion : As a result of this research, the hypothesis is validated with conclusion that Pelvic Belt orthosis could be effectively used for improving gait ability and balance of the patients with post-stroke hemiparesis.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.123-130
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• 2022

During the past decades, detection of gear defects remains as a major problem, especially when the gears are subject to non-stationary phenomena. The idea of this paper is to mixture a multilevel wavelet transform with a fast EMD decomposition in order to early detect gear defects. The sensitivity of a kurtosis is used as an indicator of gears defect burn. When the gear is damaged, the appearance of a crack on the gear tooth disrupts the signal. This is due to the presence of periodic pulses. Nevertheless, the existence of background noise induced by the random excitation can have an impact on the values of these temporal indicators. The denoising of these signals by multilevel wavelet transform improves the sensitivity of these indicators and increases the reliability of the investigation. Finally, a defect diagnosis result can be obtained after the fast transformation of the EMD. The proposed approach consists in applying a multi-resolution wavelet analysis with variable decomposition levels related to the severity of gear faults, then a fast EMD is used to early detect faults. The proposed mixed methods are evaluated on vibratory signals from the test bench, CETIM. The obtained results have shown the occurrence of a teeth defect on gear on the 5th and 8th day. This result agrees with the report of the appraisal made on this gear system.

• Korean Journal of Applied Biomechanics
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• v.32 no.1
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• pp.1-8
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• 2022

Objective: This study proposes a methodology to analyze important variables that have a significant impact on the putting direction prediction using a machine learning-based putting direction prediction model trained with IMU sensor data. Method: Putting data were collected using an IMU sensor measuring 12 variables from 6 adult males in their 20s at K University who had no golf experience. The data was preprocessed so that it could be applied to machine learning, and a model was built using five machine learning algorithms. Finally, by comparing the performance of the built models, the model with the highest performance was selected as the proposed model, and then 12 variables of the IMU sensor were applied one by one to analyze important variables affecting the learning performance. Results: As a result of comparing the performance of five machine learning algorithms (K-NN, Naive Bayes, Decision Tree, Random Forest, and Light GBM), the prediction accuracy of the Light GBM-based prediction model was higher than that of other algorithms. Using the Light GBM algorithm, which had excellent performance, an experiment was performed to rank the importance of variables that affect the direction prediction of the model. Conclusion: Among the five machine learning algorithms, the algorithm that best predicts the putting direction was the Light GBM algorithm. When the model predicted the putting direction, the variable that had the greatest influence was the left-right inclination (Roll).

• Journal of Korea Trade
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• v.24 no.8
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• pp.133-152
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• 2020

Purpose - The purpose of this study is to analyze the determinants of commodity trade in Korea and China and to examine the implications of China's GVC shift from export to domestic market on its impact on Korea's trade. Design/methodology - This study selected 30 major trading partner countries. The dependent variable is the trade volume, and the independent variables are general economic factors such as gross domestic product (GDP), GDP per capita, distance, and FTA. Findings - The trade pattern of Korea's commodities shows that GDP has a positive relationship with trade, import, and export. Distance has a significant negative relationship with total trade, import, and export. FTA is significant for import but it is not significant for total trade and export. The trade pattern of China's commodities shows that GDP has a significant positive relationship with total trade, import, and export. Distance has a negative relationship with trade, import, and export. GDP per capita is not significant for total trade and import, but it is significant for export. FTA is significant for total trade and export, but it is not significant for import. Originality/value - Existing papers were studied mainly in certain industrial sectors such as agriculture, manufacturing, automobile industry and steel industry. This paper attempts to collects vast amounts of data about the 30 countries of Korea and China respectively and analyzes by Random Effect Model dividing the goods (0 to 9) in units of STIC (Rev. 4). The major contribution is that the decision factors affecting commodity trade can be analyzed in SITC units (0-9) to obtain analysis results that are subdivided by product group and organized by product.

• Animal Bioscience
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• v.36 no.1
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• pp.98-107
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• 2023

Objective: Current quail production is configured as an economic activity in scale. Advancements in quail nutrition have been limited to areas such as breeding and, automation of facilities and ambience. The objective of this study was to evaluate the performance responses, liver and oviduct morphometry, and liver histology of Japanese laying quails subjected to different levels of nitrogen-corrected apparent metabolizable energy (MEn). Methods: A completely random design was used that consisted of nine levels of MEn, six replicates, and five hens per cage with a total of 270 quails. The experimental period lasted for 10 weeks. The variables of performance were subjected to analysis of variance and then regression analysis using the broken-line model. The morphometric and histological variables were subjected to multivariate exploratory techniques. Results: The MEn levels influenced the responses to zootechnical performance. The broken-line model estimated the maximum responses for feed intake, egg production, egg weight, and egg mass as 3,040, 2,820, 1,802, and 2,960 kcal of MEn per kg of diet, respectively. Multivariate analysis revealed that the occurrence of hepatic steatosis and increased levels of Kupffer cells were not related to MEn levels. Conclusion: The level of 2,960 kcal/kg of MEn meets performance variable requirements without compromising hepatic physiology.

• Journal of the Korean Society of Safety
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• v.37 no.3
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• pp.52-59
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• 2022

Conventionally, all the unsafe acts by human beings in relation to industrial accidents have been regarded as unintentional human errors. Exceptionally, however, in the cases with fatalities, seriously injured workers, and/or losses that evoked social issues, attention was paid to violating related laws and regulations for finding out some people to be prosecuted and given judicial punishments. As Heinrich stated, injury or loss in an accident is quite a random variable, so it can be unfair to utilize it as a criterion for prosecution or punishment. The present study was conducted to comprehend how categorizing intentional violations in unsafe acts might disrupt conventional conclusions about the industrial accident process. It was also intended to seek out the right direction for countermeasures by examining unsafe acts comprehensively rather than limiting the analysis to human errors only. In an analysis of 150 industrial accident cases that caused fatalities and featured relatively clear accident scenarios, the results showed that only 36.0% (54 cases) of the workers recognized the situation they confronted as risky, out of which 29.6% (16 cases) thought of the risk as trivial. In addition, even when the risks were recognized, most workers attempted to solve the hazardous situations in ways that violated rules or regulations. If analyzed with a focus on human errors, accidents can be attributed to personal deviations. However, if considered with an emphasis on safety rules or regulations, the focus will naturally move to the question of whether the workers intentionally violated them or not. As a consequence, failure of managerial efforts may be highlighted. Therefore, it was concluded that management should consider unsafe acts comprehensively, with violations included in principle, during accident investigations and the development of countermeasures to prevent future accidents.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.143-149
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• 2022

Since patent documents contain detailed results of research and development technologies, many studies on various patent analysis methods for effective technology analysis have been conducted. In particular, research on quantitative patent analysis by statistics and machine learning algorithms has been actively conducted recently. The most used patent data in quantitative patent analysis is technology keywords. Most of the existing methods for analyzing the keyword data were models based on the Gaussian probability distribution with random variable on real space from negative infinity to positive infinity. In this paper, we propose a model using gamma probability distribution to analyze the frequency data of patent keywords that can theoretically have values from zero to positive infinity. In addition, in order to determine the regression equation of the gamma-based regression model, two-mode network is constructed to visualize the technological association between keywords. Practical patent data is collected and analyzed for performance evaluation between the proposed method and the existing Gaussian-based analysis models.

• Safety and Health at Work
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• v.14 no.1
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• pp.66-70
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• 2023

Background: Online teaching and learning extend the duration of using gadgets such as mobile phones and tablets. A prolonged usage of these gadgets in a static position can lead to musculoskeletal disorders (MSD). Therefore, this study aims to identify the risk factors related to musculoskeletal symptoms while using gadgets during work from home due to the COVID-19 pandemic. Method: A cross-sectional survey with online-based questionnaires was collected from the University of Indonesia, consisting of lecturers, students, and managerial staff. The minimum number of respondents was 1,080 and was defined by stratified random sampling. Furthermore, the dependent variable was musculoskeletal symptoms, while the independent were age, gender, job position, duration, activity when using gadgets, and how to hold them. Result: Most of the respondents had mobile phones but only 16% had tablets. Furthermore, about 56.7% have used a mobile phone for more than 10 years, while about 89.7% have used a tablet for less than 10 years. A multivariate analysis found factors that were significantly associated with MSD symptoms while using a mobile phone, such as age, gender, web browsing activity, work, or college activities. These activities include doing assignments and holding the phone with two hands with two thumbs actively operating. The factors that were significantly associated with MSD symptoms when using tablets were gender, academic position, social media activity, and placing the tablet on a table with two actively working index fingers. Conclusion: Therefore, from the results of this study it is necessary to have WFH and e-learning policies to reduce MSD symptoms and enhance productivity at work.

• Composites Research
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• v.21 no.6
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• pp.23-30
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• 2008

In this paper, the effect of the natural aging on the strength distribution and structural service life of a Filament Wound (FW) composite pressure vessel was studied. The fiber failure strain, which is varied significantly, was considered as the design random variable and the strength analysis was carried out by probabilistic numerical approach. The progressive failure analysis technique and the First Order Reliability Method (FORM) were embedded in this numerical model. As the calculation results, the probability of failure was obtained for each aging time steps and it is found that the strength degradation in FW composite pressure vessel, due to the natural aging, appears within 10 year-aging-time. As an example of the life prediction under natural aging using arbitrary laminated model, the service lifetime of 13 years was predicted based on the probability of failure of 2.5% and the design pressure of 3,250 psi.

• Asia-Pacific Journal of Business
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• v.14 no.1
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• pp.131-148
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• 2023

Purpose - Since the 2020s, the management philosophy of Chinese firms' ESG has been rapidly established under the leadership of the Chinese government. We empirically analyze the ESG characteristics and effects on corporate value of Chinese firms. Design/methodology/approach - Using OLS and random effect panel regression analysis, we identify ESG determinants. In analyzing the impact on corporate value, likewise a large number of literatures, we adopt a 2SLS methodology using instrumental variables in the reason of endogeneity between ESG and firm value. We analyze using the G2SLS methodology, which is improving the efficiency of the estimation coefficients along with 2SLS. Findings - We find that ESG ratings are high in state-owned and foreign capital invested companies, ESG ratings are low in companies with a high proportion of non-floating stocks which implies information asymmetry. However, there are no significance in the institutional investor's, the major 10 largest shareholders' and manager's ownership. Furthermore, we can support most of the hypotheses that ESG ratings will be high in companies with high management performance. ESG ratings are significantly higher in companies with high ROA, rich in cash asset, low debt ratio, and large size. we strongly support the hypothesis that the higher the ESG rating, the higher the firm value, and ESG has a moderating effect on state-owned companies, non-floating shares, the ownership of institutional investors, manager, and the 10 major shareholder. In particular, state-owned companies, the proportion of non-floating shares, and the ownership of the 10 major shareholders have a negative impact on firm value, however, ESG attenuates this negative effect. Research implications or Originality - This study looks forward to enhancing our understanding of ESG characteristics in East Asia.