• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.35 no.3
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• pp.25-35
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• 2022

Objectives : This study is designed to analyze outpatients who received medical treatments in ophthalmology, otolaryngology & dermatology clinic in Cheonan for 3 years. Based on the results, we intend to identify the trends of outpatients and provide the base data that can be used for future researches on patient characteristics, and Korean medicine treatments on field, statistical surveys, policy setting related to medical services. Methods : We retrospectively analyzed outpatients according to gender, year, age, season, main diagnosis, number of visits. The statistical analysis performed using IBM SPSS 25.0 for Windows. Results : The results of analyzing the electronic medical records of 1,260 patients are as follows. 1. Patients increased in 2019 compared to 2018, but decreased due to the influence of COVID-19 in 2020, and women visited more than men. The most visited age group was 40s and 50s, and summer was the highest in season. 2. By analyzing the number of visits per patient, men visited more than women, under the age of 20 was highest in age group and spring was highest in season. 3. Every year, sudden hearing loss, a frequent disease in otology, increased, and rhinitis, a frequent disease in ophthalmology, decreased. And the proportion of patients in dermatology was about 30% of the total 100 diseases. Conclusions : In order to increase the supply and use of Korean medicine in the Cheonan area in the future, it is essential to provide support at the association level and systematic supplement at the government level in consideration of the characteristics of the patient group and the trend of frequency diseases.

• Journal of the Korean Society of Physical Medicine
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• v.18 no.1
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• pp.67-76
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• 2023

PURPOSE: The study compared the satisfaction of the exercise program in a face-to-face and non-face-to-face manner with the same exercise program. METHODS: This study was conducted through convenience sampling for 57 seniors over 65 years of age. After conducting 30 minutes of the same exercise program face-to-face on the first visit and non-face-to-face on the second visit, a satisfaction survey was conducted. The survey data were processed statistically using SPSS 26.0 (SPSS Inc, IBM, USA). An independent t-test was used to compare the type of exercise program. The Spearman's Rank Correlation was conducted to correlate the satisfaction between cognitive function and education level. RESULTS: The overall satisfaction with the face-to-face program was higher than the non-face-to-face exercise programs. All three satisfaction items in face-to-face exercise programs were higher than in non-face-to-face exercise programs (p < .05). The main source of dissatisfaction in the case of face-to-face exercise programs was having a good relationship with people for face-to-face and a 'lack of communication' in the case of non-face-to-face. CONCLUSION: The elderly showed higher satisfaction in face-to-face exercise than in non-face-to-face exercise. This study is significant in that accurate satisfaction comparison was possible by conducting the same exercise program on the same subject for a relatively short time, and through this, the development of an exercise program was suggested.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.2
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• pp.59-76
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• 2023

Since the COVID-19 era, the rise in apartment prices has been unconventional. In this uncertain real estate market, price prediction research is very important. In this paper, a model is created to predict the actual transaction price of future apartments after building a vast data set of 870,000 from 2015 to 2020 through data collection and crawling on various real estate sites and collecting as many variables as possible. This study first solved the multicollinearity problem by removing and combining variables. After that, a total of five variable selection algorithms were used to extract meaningful independent variables, such as Forward Selection, Backward Elimination, Stepwise Selection, L1 Regulation, and Principal Component Analysis(PCA). In addition, a total of four machine learning and deep learning algorithms were used for deep neural network(DNN), XGBoost, CatBoost, and Linear Regression to learn the model after hyperparameter optimization and compare predictive power between models. In the additional experiment, the experiment was conducted while changing the number of nodes and layers of the DNN to find the most appropriate number of nodes and layers. In conclusion, as a model with the best performance, the actual transaction price of apartments in 2021 was predicted and compared with the actual data in 2021. Through this, I am confident that machine learning and deep learning will help investors make the right decisions when purchasing homes in various economic situations.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.27-40
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• 2023

With the increase in the spread of smart devices and the impact of COVID-19, the consumption of media contents through smart devices has significantly increased. Along with this trend, the amount of media contents viewed through OTT platforms is increasing, that makes contents recommendations on these platforms more important. Previous contents-based recommendation researches have mostly utilized metadata that describes the characteristics of the contents, with a shortage of researches that utilize the contents' own descriptive metadata. In this paper, various text data including titles and synopses that describe the contents were used to recommend similar contents. KLUE-RoBERTa-large, a Korean language model with excellent performance, was used to train the model on the text data. A dataset of over 20,000 contents metadata including titles, synopses, composite genres, directors, actors, and hash tags information was used as training data. To enter the various text features into the language model, the features were concatenated using special tokens that indicate each feature. The test set was designed to promote the relative and objective nature of the model's similarity classification ability by using the three contents comparison method and applying multiple inspections to label the test set. Genres classification and hash tag classification prediction tasks were used to fine-tune the embeddings for the contents meta text data. As a result, the hash tag classification model showed an accuracy of over 90% based on the similarity test set, which was more than 9% better than the baseline language model. Through hash tag classification training, it was found that the language model's ability to classify similar contents was improved, which demonstrated the value of using a language model for the contents-based filtering.

• Journal of Korean Society on Water Environment
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• v.39 no.3
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• pp.231-239
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• 2023

Public sewage treatment facilities are a necessary infrastructure for public health that treat sewage generated in cities and basin living areas and discharge it into rivers or seas. Recently, the role of public sewage treatment is receiving attention as a place of use of wastewater-based epidemiology (WBE), which analyzes human specific metabolic emissions or biomarkers present in sewage to investigate the environment to which the population is exposed in the water drain. WBE is mainly applied to investigate legal and water-law drug use or to predict and analyze the lifestyle of local residents. WBE has also been applied to predict and analyze the degree of infectious diseases that are prevalent worldwide, such as COVID-19. Since sewage flowing into public sewage treatment facilities includes living information of the population living in the drainage area, it is easy to collect basic data to predict the confirmation and spread of infectious diseases. Therefore, it is necessary to establish a new role of public sewage treatment facilities as an infrastructure necessary for WBE that can obtain information on the confirmation and spread of infectious diseases other than the traditional role of public sewage treatment. In South Korea, the sewerage supply rate is about 95.5% and the number of public sewage treatment facility is 4,209. This means that the infrastructure of sewerage is fully established. However, to successfully drive for WBE , research on monitoring and big-data analysis is needed.

• Journal of the Korean Applied Science and Technology
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• v.40 no.1
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• pp.113-122
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• 2023

This study attempted to investigate the effects of experience of non-contact lectures on learning flow against college students majoring in cosmetology and provide basic data to beauty education industry in the with-COVID-19 era. For this, a self-administered questionnaire survey was performed against 300 college students majoring in cosmetology from June 7 to 21, 2022. A total of 286 copies were collected and used for final analysis. The collected data were analyzed by frequency analysis, factor analysis, exploratory factor analysis, descriptive statistics, correlation analysis and multiple regression analysis, using SPSS 21.0, and the results found the followings: According to analysis of non-contact lecture experience factors, two course satisfaction factors were obtained. In learning flow, learning pleasure and learning flow were found. Specifically, class activities had a positive influence on 'learning pleasure (𝛽=.279, p<.007)' and 'learning flow (𝛽=.221, p<.031)' with statistical significance (p<.05). In addition, course satisfaction revealed a positive effect on 'learning flow (𝛽=.223, p<.041)' with statistical significance (p<.05). The above results confirm that experience of non-contact lectures affects learning flow. Therefore, it is anticipated that there would be more efforts to seek an efficient non-contact learning plan in this new era.

• Journal of the Korean Society for Library and Information Science
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• v.57 no.3
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• pp.191-210
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• 2023

The purpose of this study is to draw implications through domestic and international best case studies of library programs, and to suggest ways to improve a public library reading programs through analysis based on the 3rd Reading Culture Promotion Basic Plan in line with the changing role of future libraries. there is To this end, first, prior studies were analyzed from various angles to derive clustering standards for library programs. Based on this, programs of various domestic and foreign libraries were analyzed based on clustering criteria. And based on the clustering criteria of library programs and the 13 key tasks under the 4 strategies of the 3rd Reading Culture Promotion Basic Plan, the status of a specific public library reading programs was analyzed. Through this, in consideration of the demand of users in the era of the 4th Industrial Revolution, participatory reading promotion programs are expanded, and in response to the post-COVID-19 era, beyond face-to-face library services, non-face-to-face and non-contact library services are also considered. A development plan was presented. It is expected that this analysis and application attempt will ultimately go beyond the unit library and contribute to improving the public library service in Korea into a library program closely related to the lives of users.

• Journal of the Korea Society for Simulation
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• v.32 no.3
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• pp.75-91
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• 2023

As the business-to-customer (B2C) online market expands after the COVID-19 pandemic, the logistics industry has been constructing automated warehouses to handle multi-product, low-volume logistics. When constructing a logistics automation warehouse, it is crucial to validate that the facility's performance and operational logic are designed to meet the required throughput of the automated warehouse from the system design phase. This study proposes simulation-based validation and optimal alternatives for an H logistics automation warehouse in Iksan, Jeollabuk-do. Firstly, we focused on the box supply and packing processes, which are related to the release process, among the entire logistic processes. Then, we analyzed the potential bottlenecks in the target process and designed and implemented a discrete-event simulation model based on the analysis results. The simulation experiments showed that the facility parameters and operational logic identified in the system design phase did not satisfy the performance requirements of the entire automated warehouse. Additional experiments were conducted to suggest alternatives to meet the system performance requirements by changing the facility parameters and operational logic. We expect that the proposed study will be utilized in the future, not only in the system design phase but also in the system construction phase, for verification purposes to ensure that the construction proceeds according to the design.

• Korean Chemical Engineering Research
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• v.61 no.1
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• pp.62-67
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• 2023

Due to the prolonged impact of COVID-19, the demand for Information Technology (IT) products is increasing, and their production facilities are expanded. Consequently, the use of harmful and dangerous chemicals are increased, the risk of fire(s) and explosion(s) is also elevated. In order to mitigate these risks, the government sets standards, such as KS C IEC 60079-10-1, and manages explosion-prone hazardous facilities where flammable substances are manufactured, used, and handled. However, using the standards of KS, it is difficult to predict the actual possibility of an explosion in a facility, because ventilation (an important factor) is not considered when setting up a hazardous work environment. In this study, the SEMI S6, Tracer Gas Test was applied to the chemical vapor deposition (CVD) facility, a major part of the display industry, to evaluate ventilation performance and to confirm the possibility of creating a less explosive environment. Based on the results, it was confirmed that the ventilation performance in the assumed scenarios met the standards stipulated in SEMI S6, along with supporting the possibility of creating a less explosive working condition. Therefore, it is recommended to use the prediction tool using engineering techniques, as well as KS standards, in such hazardous environments to prevent accidents and/or reduce economic burden following accidents.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.3
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• pp.115-122
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• 2022

With the outbreak of COVID-19 a few years ago, video conferencing and electronic document work have increased, and for this reason, the proportion of computer work among modern people's daily routines is increasing. However, as more and more people work on computers in the wrong posture for a long time, the number of patients with poor eyesight and text neck is increasing. Until recently, many studies have been published to correct posture, but most of them have limitations that users may experience discomfort because they have to correct posture by wearing equipment. A posture correction sensor algorithm is proposed to prevent access to the minimum distance between a computer monitor and a person using an ultrasonic sensor device. At this time, an algorithm for minimizing false alarms among warning alarms that sound at the minimum distance is also proposed. Because the ultrasonic sensor device is used, posture correction can be performed without attaching a device to the body, and the user can relieve discomfort. In addition, experimental results showed that accuracy can be improved by reducing false alarms by removing more than half of the noise generated during distance measurement.