• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.spc
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• pp.1-8
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• 2023

To investigate the national science and technology policy direction in the field of construction machinery, an analysis was conducted on projects selected as national research and development (R&D) initiatives by the government. Assuming that the project titles contain key keywords, text mining was employed to substantiate this assumption. Project information data spanning nine years from 2014 to 2022 was collected through the National Science & Technology Information Service (NTIS). To observe changes over time, the years were divided into three-year sections. To analyze research trends efficiently, keywords were categorized into groups: 'equipment,' 'smart,' and 'eco-friendly.' Based on the collected data, keyword frequency analysis, N-gram analysis, and topic modeling were performed. The research findings indicate that domestic government R&D in the construction machinery field primarily focuses on smart-related research and development. Specifically, investments in monitoring systems and autonomous operation technologies are increasing. This study holds significance in analyzing objective research trends through the utilization of big data analysis techniques and is expected to contribute to future research and development planning, strategic formulation, and project management.

• Electronics and Telecommunications Trends
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• v.39 no.4
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• pp.73-81
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• 2024

As the demand for a healthy life increases and the use of information technology expands, interest in digital healthcare has increased. Among the digital healthcare technologies, digital therapeutics (DTx), which are capable of disease prevention, management, and treatment rather than simple healthcare, are expected to play a key role in future healthcare services. As interest in untact remote treatment that can minimize the risk of viral infection has rapidly increased since the spread of COVID-19, the application of DTx has received much attention because it can partially replace face-to-face treatment for mental illnesses, chronic diseases, and other diseases, reducing concerns about infection. In addition, because of the nature of software, DTx have lower toxicity and fewer side effects than existing treatments and do not require manufacturing, transportation, and storage like general medicines. Hence, they can be supplied in large quantities at low cost and have the advantage of lowering medical costs. However, despite these advantages, it has been pointed out that there are difficulties in investment and universal use because of the complexity of pricing and malpractice compensation. In other words, if it is difficult to prove and measure the improvements in disease management and treatment using DTx and it takes a considerable amount of time and money to do so, it will be difficult to attract investment from stakeholders such as medical providers and pharmaceutical companies. In this paper, we examine the domestic and global application status and development trends of DTx and determine the relevant implications.

• Journal of The Korean Association of Information Education
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• v.25 no.5
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• pp.813-824
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• 2021

To improve educational performance by analyzing the learning trends of adult learners of Open High Schools, various algorithm models using artificial intelligence were designed and performance was evaluated by applying them to real data. We analyzed Log data of 115 adult learners in the cyber education system of Open High Schools. Most adult learners of Open High Schools learned more than recommended learning time, but at the end of the semester, the actual learning time was significantly reduced compared to the recommended learning time. In the second half of learning, the participation rate of VODs, formation assessments, and learning activities also decreased. Therefore, in order to improve educational performance, learning time should be supported to continue in the second half. In the latter half, we developed an artificial intelligence algorithm models using Tensorflow to predict learning time by data they started taking the course. As a result, when using CNN(Convolutional Neural Network) model to predict single or multiple outputs, the mean-absolute-error is lowest compared to other models.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.9 s.186
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• pp.23-30
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• 2006

• Clinical and Experimental Pediatrics
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• v.49 no.12
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• pp.1267-1274
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• 2006

This is to determine current status and historical trends of the health of Korean adolescents. Adolescence is not only a time of health and well-being, but also a time of experimentation and of being at risk of significant threats by health-damaging behaviors. A comprehensive overview through a review of major national demographic data on health-related issues would give health professionals chances to deal with Korean adolescents' unique needs to improve their health.

• Communications for Statistical Applications and Methods
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• v.12 no.1
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• pp.199-205
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• 2005

In general, simple correspondence analysis has handled mainly correspondence relations between the row and column categories but can not display the trends of their change over the time. For solving this problem, we will propose DSCA(Dynamic Simple Correspondence Analysis) of transition matrix data using supplementary categories in this study, Moreover, DSCA provides its trend of the change for the future by predicting and displaying trend toward the change from a standard point of time to the next.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2014.05a
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• pp.14-15
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• 2014

The modular construction is as yet early stage of market in Korea. So It is have difficulty of market demand forecast of the modular building. Therefore, this study was done analysis for market trends of the modular building using ARIMA(Auto Regressive Integrated Moving Average) model by time series data.

• Journal of Preventive Medicine and Public Health
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• v.45 no.5
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• pp.323-328
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• 2012

Objectives: Economic growth and development of medical technology help to improve the average life expectancy, but the western diet and rapid conversions to poor lifestyles lead an increasing risk of major chronic diseases. Coronary heart disease mortality in Korea has been on the increase, while showing a steady decline in the other industrialized countries. An age-period-cohort analysis can help understand the trends in mortality and predict the near future. Methods: We analyzed the time trends of ischemic heart disease mortality, which is on the increase, from 1985 to 2009 using an age-period-cohort model to characterize the effects of ischemic heart disease on changes in the mortality rate over time. Results: All three effects on total ischemic heart disease mortality were statistically significant. Regarding the period effect, the mortality rate was decreased slightly in 2000 to 2004, after it had continuously increased since the late 1980s that trend was similar in both sexes. The expected age effect was noticeable, starting from the mid-60's. In addition, the age effect in women was more remarkable than that in men. Women born from the early 1900s to 1925 observed an increase in ischemic heart mortality. That cohort effect showed significance only in women. Conclusions: The future cohort effect might have a lasting impact on the risk of ischemic heart disease in women with the increasing elderly population, and a national prevention policy is need to establish management of high risk by considering the age-period-cohort effect.

• Journal of Preventive Medicine and Public Health
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• v.36 no.4
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• pp.325-331
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• 2003

Objectives : To analyze medical service utilization and trends among the elderly in the last year of life. Method : The subjects of this study were People that had died at the age sixty-five and above between January $1^{st}$ and June $30^{th}$ 2000 The names of the deceased and their dates of death were collected from the data of the funeral-expenses-receivers of the National Health Insurance Corporation (NHIC). This data was merged with that of the individual medical expenses of the NHIC. Results : In the first half of 2000, 84.2% of the funeral-expenses-receivers (53,063) utilized medical services during the year prior to their death; 51.0% (27,042) were female and 49.0% (26,021) male. In the last twelve months of life, the medical fees, the number of days receiving medical services and the number of days receiving medicine were 3,107,935 Won, 47.88 and 153.21, respectively, for each person. As the age of the groups increased, the level of medical service utilization decreased; the change was more obvious in female group. The level of medical service utilization during the twelve months prior to death drastically increased around the time of death. Conclusions : This study, from an analysis of the level of medical service utilization prior to death, shows a concentrated volume of medical services during a certain time period prior to death.

• Korean Journal of Construction Engineering and Management
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• v.16 no.4
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• pp.80-88
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• 2015

In the case of those types of work that are performed outdoor construction work, many non-working days occur due to climatic elements such as low temperature, rainfall, and high wind velocity. In particular, damage incurred construction delays hardly decreases because weather forecasting has become difficult due to global warming. In the present study, time points of drastic changes in annual average temperatures, annual average maximum temperatures, and annual average minimum temperatures were identified through BCP analysis and increasing/decreasing trends of non-working days in summer and winter were compared and analyzed on the basis of the change points. According to the results of the study, annual average temperatures drastically changed in 1988 and 1998. After the two time points, non-working days in summer and winter clearly showed increasing trends and decreasing trends respectively.