• KNOM Review
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• v.23 no.2
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• pp.18-28
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• 2020

With the development of the virtual community, the benefits that IT technology provides to people in fields such as healthcare, industry, communication, and culture are increasing, and the quality of life is also improving. Accordingly, there are various malicious attacks targeting the developed network environment. Firewalls and intrusion detection systems exist to detect these attacks in advance, but there is a limit to detecting malicious attacks that are evolving day by day. In order to solve this problem, intrusion detection research using machine learning is being actively conducted, but false positives and false negatives are occurring due to imbalance of the learning dataset. In this paper, a Random Oversampling method is used to solve the unbalance problem of the UNSW-NB15 dataset used for network intrusion detection. And through experiments, we compared and analyzed the accuracy, precision, recall, F1-score, training and prediction time, and hardware resource consumption of the models. Based on this study using the Random Oversampling method, we develop a more efficient network intrusion detection model study using other methods and high-performance models that can solve the unbalanced data problem.

• Geophysics and Geophysical Exploration
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• v.26 no.4
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• pp.211-228
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• 2023

Ground-penetrating radar (GPR) surveys are commonly used to monitor embankments, which is a nondestructive geophysical method. The results of GPR surveys can be complex, depending on the situation, and data processing and interpretation are subject to expert experiences, potentially resulting in false detection. Additionally, this process is time-intensive. Consequently, various studies have been undertaken to detect cavities in GPR survey data using deep learning methods. Deep-learning-based approaches require abundant data for training, but GPR field survey data are often scarce due to cost and other factors constaining field studies. Therefore, in this study, a deep- learning-based model was developed for embankment GPR survey cavity detection using data augmentation strategies. A dataset was constructed by collecting survey data over several years from the same embankment. A you look only once (YOLO) model, commonly used in computer vision for object detection, was employed for this purpose. By comparing and analyzing various strategies, the optimal data augmentation approach was determined. After initial model development, a stepwise process was employed, including box clustering, transfer learning, self-ensemble, and model ensemble techniques, to enhance the final model performance. The model performance was evaluated, with the results demonstrating its effectiveness in detecting cavities in embankment GPR survey data.

• Korean Journal of Environment and Ecology
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• v.37 no.5
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• pp.327-336
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• 2023

This study aimed to propose an effective method for surveying wild birds by comparing the results of bioacoustic detection with those obtained through a field survey. The study sites were located at Dongbaek-dongsan and a 1100-altitude wetland in Jeju-do, South Korea. The bioacoustic detection was conducted over the course of 12 months in 2020. For the bioacoustic detection, a Song-meter SM4 device was installed at each study site, recording bird songs in 1-min per hour, .wav, and 44,100 Hz format. The findings of the field survey were taken from the 「Long-term trends of Bird Community at Dongbaekdongsan and 1100-Highland Wetland of Jeju Island, South Korea.」 by Banjade et al. (2019). The results of this study are as follows. First, the avifauna identified using bioacoustic detection comprised 29 families and 46 species in Dongbaek-dongsan, and 16 families and 25 species in the 1100-altitude wetland. Second, based on the song frequency, the dominant species in Dongbaek-dongsan were Hypsipetes amaurotis (Brown-eared Bulbul, 33.62%), Horornis diphone (Japanese Bush Warbler, 12.13%), and Zosterops japonicus (Warbling White-eye, 9.77%). In the 1100-altitude wetland the dominant species were Corvus macrorhynchos (Large-billed Crow, 27.34%), H. diphone (19.43%), and H. amaurotis (16.56%). Third, in the field survey conducted at Dongbaek-dongsan, the number of detected bird species was 39 in 2009, 51 in 2012, 35 in 2015, and 45 in 2018, while the bioacoustic detection identified 46 species. In the field survey conducted in the 1100-altitude wetland, the number of detected bird species was 37 in 2009, 42 in 2012, 34 in 2015, and 38 in 2018, while the bioacoustics detection identified 25 species. Overall, 43.6% of the 78 species detected in the field survey in Dongbaek-dongsan (34 species) were identified using bioacoustic detection, and 38.3% of the 47 species detected in the field survey in the 1100-altitude wetland (18 species) were identified using bioacoustic detection. Fourth, the bioacoustic detection identified 9 families and 12 species of birds in Dongbaek-dongsan, and 3 families and 7 species of birds in the 1100-altitude wetland. No results from field survey were available for these species. The identified birds were predominantly nocturnal, including Otus sunia (Oriental Scops Owl) and Ninox japonica (Northern Boobook), passage migrants, including Larvivora cyane (Siberian Blue Robin), L. sibilans (Rufous-tailed Robin), and winter visitors with a relatively small number of visiting individuals, such as Bombycilla garrulus (Bohemian Waxwing) and Loxia curvirostra (Red Crossbill). Fifth, the birds detected in the field survey but not through bioacoustic detection included 18 families and 48 species in Dongbaek-dongsan and 14 families and 27 species in the 1100-altitude wetland; the most representative families were Ardeidae, Accipitridae, and Muscicapidae. This study is significant as it provides essential data supporting the possibility of an effective survey combining bioacoustic detection with field studies, given the increasing use of bioacoustic devices in ornithological studies in South Korea.

• International Journal of Naval Architecture and Ocean Engineering
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• v.6 no.2
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• pp.484-495
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• 2014

This paper introduces the use of network theory to model and analyze disparate ship design information. This work will focus on a ship's distributed systems and their intra- and intersystem structures and interactions. The three system to be analyzed are: a passageway system, an electrical system, and a fire fighting system. These systems will be analyzed individually using common network metrics to glean information regarding their structures and attributes. The systems will also be subjected to community detection algorithms both separately and as a multiplex network to compare their similarities, differences, and interactions. Network theory will be shown to be useful in the early design stage due to its simplicity and ability to model any shipboard system.

• Journal of Korean Public Health Nursing
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• v.22 no.2
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• pp.165-176
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• 2008

Purpose: This study was conducted in order to analyze the factors that influence alcohol use disorder in elders in KyongBuk province. The results of the study will provide basic information for the development of nursing interventions to promote proper alcohol use in elders. Methods: The subjects were 626 elderly individuals. Alcohol use disorder was defined as a score of more than 15 point on the AUDIT-K(Korean version of Alcohol Use Identification Test). Descriptive statistics, chi-square test, ANOVA and logistic regression were utilized to analyze the data. Results: Overall incidence of alcohol use disorder level; normal 73.2%, problem drinking 7.5% and alcohol use disorder 19.3%. Significant factors affecting alcohol use disorder were sex (OR=6.897), religious belief (OR=1.836), smoking (OR=2.948), liver disease (OR=4.753) and depression (OR=1.779). Conclusion: Community health care nurses perform a crucial function in the screening of elderly alcoholics. Early detection and treatment of depression in elders may help to prevent alcoholism.

• Structural Monitoring and Maintenance
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• v.7 no.1
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• pp.43-58
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• 2020

Pile foundations of existing bridges lie in soil and water environment for long term and endure relatively heavy vertical loads, thus prone to damages, especially after stricken by external forces, such as earthquake, collision, soil heap load and etc., and the piles may be injured to certain degrees as well. There is a relatively complete technical system for quality inspection of new bridge pile foundations without structures on the top. However, there is no mature technical standard in the engineering community for the non-destructive testing technology specific to the existing bridge pile foundations. The quality of bridge pile foundations has always been a major problem that plagues bridge maintenance. On the basis of many years' experiences in test engineering and theoretical studies, this study developed a new type of detection technology and equipment for the existing bridge piles.

• Health Policy and Management
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• v.6 no.1
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• pp.85-109
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• 1996

Telemedicine can increase accessibility to advance medical technology at the university hospital for community residents living in a remote area. This paper focused on the economic evaluation of telemedicine to identify important factors influencing costs and benefits and to understand how these factors can be changed to improve economic performance of the telemedicine. When the telemedicine project currently operating in Korea was evaluated based on the traditional cost-benefit analysis, the results showed a heavy net loss wiht a B/C ration of 0.56. As several values were added to the analysis based on the Information Economics approach, B/C ratios steadly increased. When the saving of medical expenses from the early detection of diseases was taken into a consideration, the ration exceeded the break-even point. >From the sensitivity analysis, a number of patients and the cost for equipment and communication were found to be the key factors for influencing economic performance of telemedicine.

• Journal of Microbiology and Biotechnology
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• v.18 no.5
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• pp.815-820
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• 2008

Two culture-independent methods, namely ribosomal DNA libraries and denaturing gradient gel electrophoresis (DGGE), were adopted to examine the microbial community of a Malaysian light crude oil. In this study, both 16S and 18S rDNAs were PCR-amplified from bulk DNA of crude oil samples, cloned, and sequenced. Analyses of restriction fragment length polymorphism (RFLP) and phylogenetics clustered the 16S and 18S rDNA sequences into seven and six groups, respectively. The ribosomal DNA sequences obtained showed sequence similarity between 90 to 100% to those available in the GenBank database. The closest relatives documented for the 16S rDNAs include member species of Thermoincola and Rhodopseudomonas, whereas the closest fungal relatives include Acremonium, Ceriporiopsis, Xeromyces, Lecythophora, and Candida. Others were affiliated to uncultured bacteria and uncultured ascomycete. The 16S rDNA library demonstrated predomination by a single uncultured bacterial type by >80% relative abundance. The predomination was confirmed by DGGE analysis.

• Journal of Information Processing Systems
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• v.15 no.3
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• pp.616-631
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• 2019

With the rapid increase of information on the World Wide Web, finding useful information on the internet has become a major problem. The recommendation system helps users make decisions in complex data areas where the amount of data available is large. There are many methods that have been proposed in the recommender system. Collaborative filtering is a popular method widely used in the recommendation system. However, collaborative filtering methods still have some problems, namely cold-start problem. In this paper, we propose a movie recommendation system by using social network analysis and collaborative filtering to solve this problem associated with collaborative filtering methods. We applied personal propensity of users such as age, gender, and occupation to make relationship matrix between users, and the relationship matrix is applied to cluster user by using community detection based on edge betweenness centrality. Then the recommended system will suggest movies which were previously interested by users in the group to new users. We show shown that the proposed method is a very efficient method using mean absolute error.

• Publications of The Korean Astronomical Society
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• v.38 no.2
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• pp.13-24
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• 2023

More than 5,000 exoplanets have been detected nowadays. One of the key motivations of exoplanet detection is to understand what physical/chemical conditions of exoplanets are suitable for harboring extraterrestrial life. Such conditions are called "habitability," and most modern studies assume the existence of liquid water as its key factor. In this paper, we review the current status of exoplanet and habitability studies, as well as some future (habitable) exoplanet survey plans, mostly from National Academies of Sciences, Engineering, and Medicine (2018, 2021). Also, we suggest several research items that the Korean astronomy and space science community could contribute to habitability.