• Physical Therapy Korea
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• v.26 no.3
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• pp.1-10
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• 2019

Background: Winged scapular (WS) causes muscle imbalance with abnormal patterns when moving the arm. In particular, the over-activation of the upper trapezius (UT) and decrease in activity of the lower trapezius (LT) and serratus anterior (SA) produce abnormal scapulohumeral rhythm. Therefore, the SA requires special attention in all shoulder rehabilitation programs. In fact, many previous studies have been devoted to the SA muscle strength training needed for WS correction. Objects: The purpose of this study was to investigate the effect of shoulder girdle muscle and ratio according to the angle of shoulder abduction and external weight in supine position. Methods: Twenty three WS patients participated in this experiment. They performed scapular protraction exercise in supine position with the weights of 0 kg, 1 kg, 1.5 kg, and 2 kg at shoulder abduction angles of $0^{\circ}$, $30^{\circ}$, $60^{\circ}$, and $90^{\circ}$. The angle and weight applications were randomized. Surface electromyography (EMG) was used to collect the EMG data of the SA, pectoralis major (PM), and UT during the exercise. The ratio of PM/SA and UT/SA was confirmed. Two-way repeated analyses of variance were used to determine the statistical significance of SA, PM, and UT and the ratios of PM/SA and UT/SA. Results: There was a significant difference in SA according to angle (p<.05). Significant differences were also identified depending on the angle and weight (p<.05). The angle of abduction at $0^{\circ}$, $30^{\circ}$ and weight of 2 kg showed the highest SA activity. However, there was no significant difference between PM and UT (p>.05). There was a significant difference between PM/SA and UT/SA in ratio of muscle activity according to angle (p<.05). Significant differences were found at PM/SA angles of $30^{\circ}$, $60^{\circ}$ and $90^{\circ}$ (p<.05). For UT/SA, significant difference was only observed at $90^{\circ}$ (p<.05). Conclusion: Based on the results of this study, in order to strengthen the SA, it was found to be most effective to use 1 and 1.5 kg weights with abduction angles of $0^{\circ}$ and $30^{\circ}$ at shoulder protraction in supine position.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.163-179
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• 2020

With the expansion of platform-based taxi service, mobility and convenience of users are getting better. However, due to profitability problem, marginalized areas in the supply of the service are expected to appear. As such, this study analyzed spatial marginalization of taxi service caused by imbalance in supply and demand during the night-time when public transportation service is suspended. According to hot-spot analysis of taxi, outskirt of a city and residential areas showed high vacancy and greater number of drop-offs compared to the number of pick-ups. On the contrary, they were confirmed low in the center and sub-centers of a city. Centrality analysis also showed a similar pattern with hot-spot analysis. Due to this, drivers may refuse to pick up a customer bound for an area with lower out-degree centrality compared to in-degree centrality as it might be difficult for the drivers to pick up another customer after dropping off the current customer. Thus, customers may need to wait for a taxi for a longer time. For this reason, improvement in spatial marginalization caused by mismatch of supply and demand is required. Also, the outcome of this study is expected to be utilized as a basic data.

• Korean Journal of Construction Engineering and Management
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• v.23 no.1
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• pp.98-105
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• 2022

It is essential for vertical smart farms that artificially grow crops in an enclosed space to properly utilize air environment facilities to create an appropriate growth environment. However, domestic vertical smart farm companies are creating a growing environment by relying on empirical data rather than systematic methods. Using IoT to create a growing environment based on systematic and precise monitoring can increase crop production yield and maximize profitability. This study aims to construct a monitoring system using IoT and to analyze the cause by demonstrating the imbalance of temperature environment, which is a significant factor in crop cultivation. 1) The horizontal temperature distribution of the multi-layer shelf was measured with different operating methods of LED and air conditioner. As a result, there was a temperature difference of "up to 1.7℃" between the sensors. 2) As a result of measuring the vertical temperature distribution, the temperature difference was "up to 6.3℃". In order to reduce this temperature gap, a strategy for proper arrangement and operation of air conditioning equipment is required.

• Journal of the Korean Society for Library and Information Science
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• v.57 no.3
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• pp.97-117
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• 2023

The purpose of this study is to suggest a mid- to long-term expansion plan to resolve the blind spot and alleviate the imbalance of public library services in Daegu City. The research methods for this purpose included literature review, related laws and statistical data analysis, case study, and opinion survey. As a result, the first service area was set as a total of 14 areas based on administrative districts(Jung-gu, Seo-gu, Nam-gu, and Dalseong-gun each have one, Dong-gu and Buk-gu each have two, and Suseong-gu and Dalseo-gu have three each). Second, the expansion scenario for public libraries in Daegu City was proposed to add 26 libraries by the final target year (2032) based on the trend of national library growth over the past 13 years (2008-2020) and the forecast for the next 10 years (2023-2032). Third, the construction scenarios for each basic local government, excluding the Daegu representative library, are as follows: One library each in Jung-gu, Seo-gu, and Nam-gu; two libraries in Suseong-gu; three libraries in Dalseong-gun; four libraries in Dong-gu; and seven libraries each in Buk-gu and Dalseo-gu. In terms of floor area, it is proposed to add a total of 17 branch libraries with a minimum legal standard of 330-2,499㎡, four central libraries with 2,500-4,999㎡ each, and four central libraries with 5,000-9,999㎡ each. On the premise of these conditions, Daegu City and public libraries should focus on creating an inclusive and open community space, creating a digital platform, strengthening the library operation and cooperation system centered on Daegu representative library, developing collections and specializing services for local hub libraries, enhancing various knowledge information and program services, managing key library indicators and improving social contribution.

• Journal of the Korean Society of Food Culture
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• v.23 no.1
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• pp.1-9
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• 2008

This study aimed to offer some basic data for nutrition education to housewives by comparing behaviors of eating out targeted on housewives who live in Daejon surveyed by classification of regions and by family forms. As for their ages, 79 housewives (16.0%) are less than 30, 179 housewives (36.8%) are between 30 and 39, 156 housewives (35.9%) are between 40 and 49 and 74 housewives (15.2%) are more than 50, and as for their final academic careers, 204 housewives (41.9%) graduated from universities, which was the most and as for religions, 172 housewives (35.3%) had no religion, which was the most, and in the case that they had religions, 137 housewives (27.5%) believed in Christianity. And as for occupations, 327 housewives (69.0%) had no job, and in case they had jobs, 123 housewives (25.3%) that occupied the most were professional. As for husbands’ occupations, profession was the most for 143 housewives (29.4%) and as for monthly income, $2\; million\;won{\sim}3\;million$ won was most as 40.0%. As for times of eating out, ‘4 times a year’ was said by 131 housewives (26.9%), which was the most, and as for the times of food home service, ‘seldom’ was said by 221 housewives (45.4%), and as to the expense for eating out a month, ‘less than 100,000 won’ was said by 219 housewives (45.0%), which was the most, and as for the reasons of their eating out, ‘for harmony in a family’ was said by 119 housewives (24.4%). As for times of eating out by general items of housewives, it was appeared that the younger, the higher in education, less in religion, more in occupation, the more professional in their husbands’ jobs, the more nuclear in family forms, fewer in number of family members and the more average family income per a month, they had more times of eating out. Regarding the factors influencing on eating out, ‘high price’, ‘nutritive imbalance’ and ‘use of MSG’ were pointed by 204 housewives (41.9%), 83 housewives (17.0%) and 63 housewives (12.9%) respectively as the problems of food service shops. And as for the question why their went to their regular restaurants, 185 housewives (38.0%) said ‘taste of food’, and the most considerable thing when they selected menu at a restaurant was ‘taste of food’ for 167 housewives (34.3%). The survey showed that a lot of housewives thought the prices at restaurants were high, and they valued taste of food most, therefore food service shops should improve the taste and nutrition of food.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.2
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• pp.181-196
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• 2024

This study examines the impact of university graduate Startup rates on economic growth in the regions where universities are located, using panel data from 35 universities in 17 regions in Korea and 21 universities in 13 cities in China over a six-year period from 2016 to 2021. In Korea, a total of 35 universities were selected as part of the Ministry of Education's "University-initiated Startup" policy, including Startup-oriented universities, leading universities in Startup education innovation, Startup education bases, and excellent universities in Startup education, while in China, 21 universities were selected as part of the pilot bases established as part of the "Mass Entrepreneurship, Mass Innovation" policy. To analyze the economic impact of the universities on the regions where they are located, we aimed to conduct an empirical analysis of the economic impact using economic indicators of the economic growth rate of the regions where they are located. The results of the empirical analysis show that the Startup rate of university graduates in Korea and China both have a positive impact on the regional economic growth rate, but the Startup rate of local university graduates in Korea has a greater impact on the regional economy than in China. Based on the findings that the number of entrepreneurs produced by universities has a positive impact on the economic growth of their regions, this study draws implications for the role of universities and regions in revitalizing local economies and the establishment of systems to resolve the imbalance between metropolitan and non-metropolitan areas.

• Journal of dental hygiene science
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• v.24 no.2
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• pp.115-123
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• 2024

Background: The population of Gangneung City in South Korea has shown a gradual increase in the proportion of individuals aged 65 years and older, and the most frequently reported diseases for several years have consistently been periodontal diseases, including gingivitis and periodontitis. The regional imbalance in the distribution of dental personnel and resources has emerged as a problem of inequality in the use of dental care. It has been advocated to identify areas with disadvantages in dental care and develop public dental policies based on that. This study aimed to develop a customized oral healthcare program for local seniors based on a Public-Private-Academic Partnership, and to evaluate the oral health status of older adults in Gangneung City. Methods: The participants were residents aged 60 years and above in Gangneung City. A questionnaire including general information, systemic health status, and oral health status was administered to the participants. In addition, oral healthcare and education tailored to each individual's health status were provided once or twice based on their oral health status. The collected data were analyzed using IBM SPSS Statistics 25 for descriptive statistical analysis. Results: Among the older adults in Gangneung City, 75% had at least one prosthesis and exhibited symptoms of gingivitis or periodontitis. Additionally, the modified sulcus bleeding index decreased among participants who underwent the program twice. Over 90% of the participants expressed satisfaction with the program. Conclusion: The program appeared to contribute positively to the oral health promotion among local seniors. Further oral healthcare programs should focus on seniors in rural and old urban areas to reduce disparities in oral health across regions.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.11
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• pp.471-480
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• 2023

The Korean construction order volume in South Korea grew significantly from 91.3 trillion won in public orders in 2013 to a total of 212 trillion won in 2021, particularly in the private sector. As the size of the domestic and overseas markets grew, the scale and complexity of EPC (Engineering, Procurement, Construction) projects increased, and risk management of project management and ITB (Invitation to Bid) documents became a critical issue. The time granted to actual construction companies in the bidding process following the EPC project award is not only limited, but also extremely challenging to review all the risk terms in the ITB document due to manpower and cost issues. Previous research attempted to categorize the risk terms in EPC contract documents and detect them based on AI, but there were limitations to practical use due to problems related to data, such as the limit of labeled data utilization and class imbalance. Therefore, this study aims to develop an AI model that can categorize the contract terms based on the FIDIC Yellow 2017(Federation Internationale Des Ingenieurs-Conseils Contract terms) standard in detail, rather than defining and classifying risk terms like previous research. A multi-text classification function is necessary because the contract terms that need to be reviewed in detail may vary depending on the scale and type of the project. To enhance the performance of the multi-text classification model, we developed the ELECTRA PLM (Pre-trained Language Model) capable of efficiently learning the context of text data from the pre-training stage, and conducted a four-step experiment to validate the performance of the model. As a result, the ensemble version of the self-developed ITB-ELECTRA model and Legal-BERT achieved the best performance with a weighted average F1-Score of 76% in the classification of 57 contract terms.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.105-129
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• 2020

This study uses corporate data from 2012 to 2018 when K-IFRS was applied in earnest to predict default risks. The data used in the analysis totaled 10,545 rows, consisting of 160 columns including 38 in the statement of financial position, 26 in the statement of comprehensive income, 11 in the statement of cash flows, and 76 in the index of financial ratios. Unlike most previous prior studies used the default event as the basis for learning about default risk, this study calculated default risk using the market capitalization and stock price volatility of each company based on the Merton model. Through this, it was able to solve the problem of data imbalance due to the scarcity of default events, which had been pointed out as the limitation of the existing methodology, and the problem of reflecting the difference in default risk that exists within ordinary companies. Because learning was conducted only by using corporate information available to unlisted companies, default risks of unlisted companies without stock price information can be appropriately derived. Through this, it can provide stable default risk assessment services to unlisted companies that are difficult to determine proper default risk with traditional credit rating models such as small and medium-sized companies and startups. Although there has been an active study of predicting corporate default risks using machine learning recently, model bias issues exist because most studies are making predictions based on a single model. Stable and reliable valuation methodology is required for the calculation of default risk, given that the entity's default risk information is very widely utilized in the market and the sensitivity to the difference in default risk is high. Also, Strict standards are also required for methods of calculation. The credit rating method stipulated by the Financial Services Commission in the Financial Investment Regulations calls for the preparation of evaluation methods, including verification of the adequacy of evaluation methods, in consideration of past statistical data and experiences on credit ratings and changes in future market conditions. This study allowed the reduction of individual models' bias by utilizing stacking ensemble techniques that synthesize various machine learning models. This allows us to capture complex nonlinear relationships between default risk and various corporate information and maximize the advantages of machine learning-based default risk prediction models that take less time to calculate. To calculate forecasts by sub model to be used as input data for the Stacking Ensemble model, training data were divided into seven pieces, and sub-models were trained in a divided set to produce forecasts. To compare the predictive power of the Stacking Ensemble model, Random Forest, MLP, and CNN models were trained with full training data, then the predictive power of each model was verified on the test set. The analysis showed that the Stacking Ensemble model exceeded the predictive power of the Random Forest model, which had the best performance on a single model. Next, to check for statistically significant differences between the Stacking Ensemble model and the forecasts for each individual model, the Pair between the Stacking Ensemble model and each individual model was constructed. Because the results of the Shapiro-wilk normality test also showed that all Pair did not follow normality, Using the nonparametric method wilcoxon rank sum test, we checked whether the two model forecasts that make up the Pair showed statistically significant differences. The analysis showed that the forecasts of the Staging Ensemble model showed statistically significant differences from those of the MLP model and CNN model. In addition, this study can provide a methodology that allows existing credit rating agencies to apply machine learning-based bankruptcy risk prediction methodologies, given that traditional credit rating models can also be reflected as sub-models to calculate the final default probability. Also, the Stacking Ensemble techniques proposed in this study can help design to meet the requirements of the Financial Investment Business Regulations through the combination of various sub-models. We hope that this research will be used as a resource to increase practical use by overcoming and improving the limitations of existing machine learning-based models.

• Journal of agricultural medicine and community health
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• v.35 no.3
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• pp.260-273
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• 2010

Objectives: The purpose of this study was to investigate the perceptions of married Korean women regarding marriage and childbirth, and their awareness of childbirth-related issues such as low birth rates, sex preferences and sex imbalances in Korea. Methods: A total of 453 married women aged 20 or older were randomly selected from four urban districts and five rural districts out of 25 districts in Gyeongju, a consolidated city located in Gyeongsangbuk-do Province, South Korea. The survey was conducted from December 2005 to February 2006. A total of 392 out of 453 questionnaires(86.5% response rate) were collected, and 44 incomplete questionnaires were excluded, leaving 348 completed questionnaires to be used for data analysis. Age was divided into three groups as below 49, 50-69, 70 or older. Results: Women's perceptions of marriage were associated with age(p<0.01). Perceptions about childbirth were also significantly related to age(p<0.01), type of residential area (p<0.01) and education level(p<0.05). Sex preferences were significantly related to age(p<0.05) and occupation(p<0.01). Of the respondents aged 49 or younger, 34.8% indicated that the ideal number of children is two, while 25.5% of respondents aged 50 to 69 and 15.3% of respondents aged 70 and 33.7% of respondents aged 70 or older considered four children to be the ideal number. Perceptions of sex imbalance were significantly related to socioeconomic status(p<0.01) and occupation(p<0.01). The largest number of respondents cited "economic burden" as the main reason for low birth rates. Multiple logistic regressions were performed for all three age groups using male sex preference as the dependent variable under the assumption that respondents can have only a single child. Socioeconomic status (p<0.01) and residential area (p<0.05) were significant variables for those aged 49 or below. Education level(p<0.05) and residential area (p<0.01) were statistically significant variables on preferring son in case of having only one child for respondents aged 50 to 69. We did not detect any significant independent variables in respondents who were 70 or older. Conclusions: Our results highlight the necessity of developing policies and public education programs to explain the consequences of low birth rates and sex imbalances in Korea. As increasing numbers of women work outside the home, it is important for the government and employers to provide social and working environments where women do not consider marriage and childbirth to be obstacles to social and business activities.