• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.3
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• pp.156-162
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• 2021

The number of smart farms has increased to save labor in agricultural production as the subsidy become available from central and local governments. The number of illegal greenhouses has also increased, which causes serious issues for the local governments. In the present study, we developed Mask-RCNN model to detect greenhouses based on satellite images. Greenhouses in the satellite images were labeled for training and validation of the model. The Mask-RC NN model had the average precision (AP) of 75.6%. The average precision values for 50% and 75% of overlapping area were 91.1% and 81.8%, respectively. This results indicated that the Mask-RC NN model would be useful to detect the greenhouses recently built without proper permission using a periodical screening procedure based on satellite images. Furthermore, the model can be connected with GIS to establish unified management system for greenhouses. It can also be applied to the statistical analysis of the number and total area of greenhouses.

• Journal of Korean Library and Information Science Society
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• v.51 no.4
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• pp.313-332
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• 2020

The purpose of this study is to compare motivations for self-archiving across disciplines on an academic social networking site. We carried out an online survey with ResearchGate(RG) users, testing 18 motivational factors that we developed from a previous study (enjoyment, personal/professional gain, reputation, learning, self-efficacy, altruism, reciprocity, trust, community interest, social engagement, publicity, accessibility, self-archiving culture, influence of external actors, credibility, system stability, copyright concerns, additional time, and effort). We adapted Biglan's classification system of academic disciplines and compared motivations across different categories of discipline. First, we compared motivations across the four combined categories by the two dimensions - hard-pure, hard-applied, soft-pure, and soft-applied. We also performed a motivation comparison across each dimension between soft and hard disciplines and between pure and applied disciplines. We examined investigated statistical differences in motivations by demographic characteristics and RG usage of participants across categories as well. Findings showed that there were differences of motivations, such as enjoyment, accessibility, influence of external actors and additional time and effort, and personal/professional gains, for self-archiving across disciplines. For example, RG users in the hard-applied were more highly motivated by enjoyment than others; RG users in the soft-pure were more highly motivated by personal/professional gains than others. It is expected that findings could be used to develop strategies encouraging researchers in various disciplines contributing to share their data and publications in ASNSs.

• (The)Korea Educational Review
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• v.24 no.1
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• pp.199-225
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• 2018

Using the 3rd to the 6th wave data from the Korean Children and Youth Panel Survey(KCYPS), we examined the effects of academic characteristics and social relations on the trajectories of the life satisfaction among adolescents. OLS results showed that male students were more satisfied with their lives than female students in the 3rd grade of middle school. As academic characteristics, academic achievement and the level of class adjustment improved life satisfaction but the amount of learning time spent had a negative effect on life satisfaction. However, the effect of academic achievement lost its statistical significance after including variables of social relations. Relationships with parents, teachers, and friends had positive effects on life satisfaction. The longitudinal analysis using the fixed effect estimation also showed a similar result of the associations among the variables to that in the OLS analysis. The life satisfaction gap between male and female students narrowed over time from the 3rd grade of middle school to the 2nd grade of high school. The effects of relationships with parents and friends showed significant effects on both female and male students, but the relationship with their teachers was significant only for female students. Based on the results, we discussed the issues of Korean education related to the life satisfaction among adolescents.

• The Korean Journal of Applied Statistics
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• v.34 no.3
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• pp.449-460
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• 2021

ASVspoof 2017 deals with detection of replay attacks and aims to classify real human voices and fake voices. The spoofed voice refers to the voice that reproduces the original voice by different types of microphones and speakers. data augmentation research on image data has been actively conducted, and several studies have been conducted to attempt data augmentation on voice. However, there are not many attempts to augment data for voice replay attacks, so this paper explores how audio modification through data augmentation techniques affects the detection of replay attacks. A total of 7 data augmentation techniques were applied, and among them, dynamic value change (DVC) and pitch techniques helped improve performance. DVC and pitch showed an improvement of about 8% of the base model EER, and DVC in particular showed noticeable improvement in accuracy in some environments among 57 replay configurations. The greatest increase was achieved in RC53, and DVC led to an approximately 45% improvement in base model accuracy. The high-end recording and playback devices that were previously difficult to detect were well identified. Based on this study, we found that the DVC and pitch data augmentation techniques are helpful in improving performance in the voice spoofing detection problem.

• Journal of Digital Convergence
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• v.19 no.3
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• pp.55-64
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• 2021

Public libraries are a space where residents learn a wide range of knowledge and ideologies, and as they are directly connected to life, various related studies have been conducted. In most previous studies, variables such as population, traffic accessibility, and environment were found to be highly relevant to library use. In this study, it can be said that the difference from previous studies is that the book borrow demand and relevance were analyzed by reflecting the variables of cultural characteristics based on the book borrow history (1,820,407 cases) and member information (297,222 persons). As a result of the analysis, it was analyzed that as the increase in borrows for social science and literature books compared to technical science books, the demand for book borrows increased. In addition, various descriptive statistical analyzes were used to analyze the characteristics of library book borrow demand, and policy implications and limitations of the study were also presented based on the analysis results. and considering that cultural characteristics change depending on the location and time of day, it is believed that related research should be continued in the future.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.333-337
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• 2021

Companion animals are physically, mentally, and socially beneficial to humans, giving us great comfort in living in the Corona19 (COVID-19) era. It is also an era of the Fourth Industrial Revolution, featuring the convergence of information and communication technology. Korea, which is facing a super-aged society, has the highest suicide rate among OECD countries, and companion animals that are effective in emotional stability can be the answer. This study is about companion animals that are effective in stabilizing the emotions of the elderly, one of the major problems in the Republic of Korea, which is about to solve in a super-aged society with more than 20 percent of the elderly aged 65 or older, needs to solve. The impact of knowledge of raising companion animals on the satisfaction level of the elderly was investigated through the management and awareness of infectious diseases. Although the level of care of companion animals had a very significant (p<0.001) effect on the satisfaction of the companion animals, the recognition of infectious diseases has no statistical significance (p>0.05). Raising companion animals with knowledge of rearing increases the satisfaction level and can lead to a happier life. While personal learning is important, it is also believed that supporting education will be necessary as a policy consideration.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.1
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• pp.25-33
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• 2021

With the development of machine learning techniques, various types of data such as vibration, temperature, and flow rate can be used to detect and diagnose abnormalities in machine conditions. In particular, in the field of the state monitoring of rotating machines, the fault diagnosis of machines using vibration data has long been carried out, and the methods are also very diverse. In this study, an experiment was conducted to collect vibration data from normal and abnormal compressors by installing accelerometers directly on rotary compressors used in household air conditioners. Data segmentation was performed to solve the data shortage problem, and the main features for the fault classification model were extracted through the chi-square test after statistical and physical features were extracted from the vibration data in the time domain. The support vector machine (SVM) model was developed to classify the normal or abnormal conditions of compressors and improve the classification accuracy through the hyperparameter optimization of the SVM.

• Journal of Korean Library and Information Science Society
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• v.52 no.2
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• pp.379-400
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• 2021

This study aims to analyze the trend of library use according to the expansion of public library infrastructure in Korea, and to search for new roles and services of libraries based on the results of the study. Using the statistical analysis, literature review and partially interview method, the number of borrowers and loans from 2009 to 2019 were analyzed. The result of the survey reveals that the number of public libraries increased by 61.3% during the survey period, while the number of borrowers decreased by 57.5%, and the number of book loans increased only by 18.2%. The result of the analysis claims that the causes of the decrease in the number of materials borrowers were an error in the process of inputting statistics and manipulating the number of book loans by the local library. The population of children and young adults decreased during the survey period, which led to a decrease in the number of children and young adult borrowers. The result of the study reveals that the increase in the use of public libraries in Korea, like other advanced countries, is stagnant. The following new roles and services are suggested for the development of public libraries: Libraries expand non-face-to-face services and electronic resources, and promote their use. Libraries expand cultural and lifelong learning programs further.

• The Korean Journal of Applied Statistics
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• v.35 no.4
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• pp.553-568
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• 2022

The Household Income and Expenditure Survey is a representative survey of Statistics Korea, which aims to measure and analyze national income and consumption levels and their changes by understanding the current state of household balances. Recently, the disconnection problem in these time series caused by the large-scale reorganization of the survey methods in 2017 and 2019 has become an issue. In this study, we model the characteristics of the time series in the Household Income and Expenditure Survey up to 2016, and use the modeling to compute forecasts for linking the expenditures in 2017 and 2018. In order to evenly reflect the characteristics across all expenditure item series and to reduce the impact of a specific forecast model, we synthesize a total of 8 models such as regression models, time series models, and machine learning techniques. In particular, the noteworthy aspect of this study is that it improves the forecast by using the optimal combination technique that can exactly reflect the hierarchical structure of the Household Income and Expenditure Survey without loss of information as in the top-down or bottom-up methods. As a result of applying the proposed method to forecast expenditure series from 2017 to 2019, it contributed to the recovery of time series linkage and improved the forecast. In addition, it was confirmed that the hierarchical time series forecasts by the optimal combination method make linkage results closer to the actual survey series.

• The Korean Journal of Applied Statistics
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• v.35 no.4
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• pp.457-468
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• 2022

In aged society, it is important to prevent older people from being disability needing long-term care. The purpose of this study is to develop a prediction model to discover high-risk groups who are likely to be beneficiaries of Long-Term Care Insurance. This study is a retrospective study using database of National Health Insurance Service (NHIS) collected in the past of the study subjects. The study subjects are 7,724,101, the population over 65 years of age registered for medical insurance. To develop the prediction model, we used logistic regression, decision tree, random forest, and multi-layer perceptron neural network. Finally, random forest was selected as the prediction model based on the performances of models obtained through internal and external validation. Random forest could predict about 90% of the older people in need of long-term care using DB without any information from the assessment of eligibility for long-term care. The findings might be useful in evidencebased health management for prevention services and can contribute to preemptively discovering those who need preventive services in older people.