• Atmosphere
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• v.28 no.2
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• pp.163-174
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• 2018

In order to assimilate MHS satellite data into the convective scale model at KMA, ATOVS data are reprocessed to utilize the original high-resolution data. And then to improve the preprocessing experiments for cloud detection were performed and optimized to convective-scale model. The experiment which is land scattering index technique added to Observational Processing System to remove contaminated data showed the best result. The analysis fields with assimilation of MHS are verified against with ECMWF analysis fields and fit to other observations including Sonde, which shows improved results on relative humidity fields at sensitive level (850-300 hPa). As the relative humidity of upper troposphere increases, the bias and RMSE of geopotential height are decreased. This improved initial field has a very positive effect on the forecast performance of the model. According to improvement of model field, the Equitable Threat Score (ETS) of precipitation prediction of $1{\sim}20mm\;hr^{-1}$ was increased and this impact was maintained for 27 hours during experiment periods.

• Nuclear Engineering and Technology
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• v.53 no.12
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• pp.4072-4079
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• 2021

This article presents a study on the state-of-the-art methods for automated radioactive material detection and identification, using gamma-ray spectra and modern machine learning methods. The recent developments inspired this in deep learning algorithms, and the proposed method provided better performance than the current state-of-the-art models. Machine learning models such as: fully connected, recurrent, convolutional, and gradient boosted decision trees, are applied under a wide variety of testing conditions, and their advantage and disadvantage are discussed. Furthermore, a hybrid model is developed by combining the fully-connected and convolutional neural network, which shows the best performance among the different machine learning models. These improvements are represented by the model's test performance metric (i.e., F1 score) of 93.33% with an improvement of 2%-12% than the state-of-the-art model at various conditions. The experimental results show that fusion of classical neural networks and modern deep learning architecture is a suitable choice for interpreting gamma spectra data where real-time and remote detection is necessary.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.181-181
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• 2023

Flood is a major threat to human society, and scientific assessment of flood risk in human living areas is an important task. In this study, two different methods were used to evaluate the flood in Ulsan City, and the results were comprehensively compared and analyzed. Based on the fuzzy mathematics and VIKOR method of the multi-objective decision system, similar evaluation results were obtained in the study area. The results show that due to the large number of rivers in Ulsan City and the relatively high exposure index, the whole city faces a high risk of flooding. However, fuzzy mathematics theory pays more attention to the negative impact of floods on people, and the adaptability in the Nam-gu District is lower. In contrast, the VIKOR method pays more attention to the positive role of the economy and population in flood protection, and thus obtains a higher score. Both approaches demonstrate that the city of Ulsan faces a high risk of flooding and that its citizens and policymakers need to invest in preventing flood damage.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1916-1934
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• 2023

The phishing attack is a malicious emerging threat on the internet where the hackers try to access the user credentials such as login information or Internet banking details through pirated websites. Using that information, they get into the original website and try to modify or steal the information. The problem with traditional defense systems like firewalls is that they can only stop certain types of attacks because they rely on a fixed set of principles to do so. As a result, the model needs a client-side defense mechanism that can learn potential attack vectors to detect and prevent not only the known but also unknown types of assault. Feature selection plays a key role in machine learning by selecting only the required features by eliminating the irrelevant ones from the real-time dataset. The proposed model uses Hyperparameter Optimized Artificial Neural Networks (H-ANN) combined with a Hybrid Firefly and Grey Wolf Optimization algorithm (H-FFGWO) to detect and block phishing websites in Internet of Things(IoT) Applications. In this paper, the H-FFGWO is used for the feature selection from phishing datasets ISCX-URL, Open Phish, UCI machine-learning repository, Mendeley website dataset and Phish tank. The results showed that the proposed model had an accuracy of 98.07%, a recall of 98.04%, a precision of 98.43%, and an F1-Score of 98.24%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.11
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• pp.2966-2986
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• 2023

Climate change is a constant threat to human life, and it is important to understand the public perception of this issue. Previous studies examining climate change have been based on limited survey data. In this study, the authors used big data such as news articles and social media data, within which the authors selected specific keywords related to climate change. Using these natural language data, topic modeling was performed for discourse analysis regarding climate change based on various topics. In addition, before applying topic modeling, sentiment analysis was adjusted to discover the differences between discourses on climate change. Through this approach, discourses of positive and negative tendencies were classified. As a result, it was possible to identify the tendency of each document by extracting key words for the classified discourse. This study aims to prove that topic modeling is a useful methodology for exploring discourse on platforms with big data. Moreover, the reliability of the study was increased by performing topic modeling in consideration of objective indicators (i.e., coherence score, perplexity). Theoretically, based on the social amplification of risk framework (SARF), this study demonstrates that the diffusion of the agenda of climate change in public news media leads to personal anxiety and fear on social media.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.34 no.4
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• pp.57-65
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• 2016

Maeul-soop(Village forest) is a key element of Korean traditional village landscape historically and culturally. However, a number of Maeul-soops have been lost or declined due to various influences since the modern age. For this Maeul-soop that has a variety of conservation values including historical, cultural and ecological ones, attention and efforts for a systematic conservation and restoration of Maeul-soop are needed. The purpose of the present study is to provide information on ecological restoration and sustainable use and management of Maeul-soops based on component plant species, habitat and location characteristics of 499 Maeul-soops spread throughout Korea. Major six categories of threat factors to Maeul-soop ecosystem were identified and the influence of each factor was evaluated. For the evaluation of weight by threat factors for the influence on the vulnerability of Maeul-soop ecosystem, more three-dimensional analysis was conducted using Analytic Hierarchy Process (AHP) analysis method. In the results of evaluation using AHP analysis method, reduction of area, among six categories, was spotted as the biggest threat to existence of Maeul-soops. Next, changes in topography and soil environment were considered as a threat factor of qualitative changes in Maeul-soop ecosystem. Influence of vegetation structure and its qualitative changes on the loss or decline of Masul-soop was evaluated to be lower than that of changes in habitat. Based on weight of each factor, the figures were converted with 100 points being the highest score and the evaluation of vulnerability of Maeul-soop was conducted with the converted figures. In the result of evaluation of vulnerability of Maeul-soops, grade III showed the highest frequency and a normal distribution was formed from low grade to high grade. 38 Maeul-soops were evaluated as grade I which showed high naturality and 10 Maeul-soops were evaluated as grade V as their maintenance was threatened. Also in the results of evaluation of vulnerability of each Maeul-soop, restoration of Maeul-soop's own area was found as top priority to guarantee the sustainability of Maeul-soops. It was confirmed that there was a need to prepare a national level ecological response strategy for each vulnerability factor of Maeul-soop, which was important national ecological resources.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5B
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• pp.485-493
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• 2008

The Artificial Neural Network (ANN) model was suggested for predicting probability of precipitation (PoP) using RDAPS NWP model, observation at AWS and upper-air sounding station. The prediction work was implemented for flood season and the data period is the July, August of 2001 and June of 2002. Neural network input variables (predictors) were composed of geopotential height 500/750/1000 hPa, atmospheric thickness 500-1000 hPa, X & Y-component of wind at 500 hPa, X & Y-component of wind at 750 hPa, wind speed at surface, temperature at 500/750 hPa/surface, mean sea level pressure, 3-hr accumulated precipitation, occurrence of observed precipitation, precipitation accumulated in 6 & 12 hrs previous to RDAPS run, precipitation occurrence in 6 & 12 hrs previous to RDAPS run, relative humidity measured 0 & 12 hrs before RDAPS run, precipitable water measured 0 & 12 hrs before RDAPS run, precipitable water difference in 12 hrs previous to RDAPS run. The suggested ANN has a 3-layer perceptron (multi layer perceptron; MLP) and back-propagation learning algorithm. The result shows that there were 6.8% increase in Hit rate (H), especially 99.2% and 148.1% increase in Threat Score (TS) and Probability of Detection (POD). It illustrates that the suggested ANN model can be a useful tool for predicting rainfall event prediction. The Kuipers Skill Score (KSS) was increased 92.8%, which the ANN model improves the rainfall occurrence prediction over RDAPS.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.2
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• pp.551-558
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• 2016

The recent convergence in ICT industry has created new businesses as well as other opportunities. However, it entails new convergence threat accompanied by security risks. Even though there are security professionals who are dealing with the situation, there is not enough human resource in risk management. Moreover, the amount of research that studies quality of education and training security personnel is not sufficient. This paper explores the curriculum of information security education in the private sector and reasons out fifteen standard curriculums in four professional fields categorized by job classification. In addition, it provides a weighted score table based on the evaluation indicator for the effective security education certificates in the private sector.

• Korean Journal of Health Education and Promotion
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• v.11 no.2
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• pp.33-47
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• 1994

AIDS preventional efforts need to be guided by well trained health care personnel especially by school nurses for the adolescents. This study was designed to get basic data about AIDS educational program development for school nurses. The objectives of this study were to 1) identify AIDS knowledg of school nurses 2) identify AIDS attitudes of school nurses and 3) identify association between AIDS knowledge and sociodemographic characteristics. Data were collected from 173 subjects in Chonbuk province. Self-reporting questionnaire were administered during the period from 1st of June to 30th of June, 1994. AIDS related knowledge was measured by using 44 questions on cause(3 items), testing(3 items), mode of transmission(15 items), clinical manifestations(5 items), treatment(3 items), prevention(5 items), complication(4 items), infection control(3 items) and Using resources(3 items). AIDS related attitudes were measured by five point Likert scales using 13 questions on perceived threats from AIDS crisis (4 items), perceived severity to AIDS(2 items), perceived needs about psychosocial care for HIV infected patients(3 items) and perceived educational needs of AIDS(4 items). The collected data were analyzed by SPSS/PC/sup +/, using percentages, Mean and S.D. descriptive purpose and t-test or F for comparing the variables. The major findings were as follows: 1. Respondents ranged in knowledge of AIDS between 0 and 44 with the 33.79 mean score. Percentage of correctly answered respondents to each categories - mode of transmission : 87.0% - clinical manifestation : 85.0% - cause : 82.5% - prevention : 81.5% - treatment : 76.1% - infection control : 72.8% - testing of HIV infection 71.8% - using community resourses : 50.9% - complication : 45.8% 2. The respondents' attitudes of AIDS The majority(70%) showed higher perceived threat The majority(91.3%) showed higher perceived severity to AIDS crisis As a whole, perceived needs about psychosocial care for HIV infected patients negative The majority (over 96.5%) showed highly perceived educational needs of AIDS. 3. The relationship between AIDS knowledge and each of those general character. AIDS knowledge shows significant difference with age(F=3.50, p<.016), years of professional experience(F=4.14, p<.007) and received lecture about AIDS(F=4.54, p<.000). There was no significant difference between AIDS knowledge and job satisfaction.

• Research in Community and Public Health Nursing
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• v.29 no.3
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• pp.322-334
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• 2018

Purpose: The purpose of this study is to identify factors related to compliance with respiratory infection preventive behaviors including hand washing, cough etiquette, and oral hygiene of older adults. Methods: A cross-sectional study was conducted with a convenience sample of 100 older adults (mean age: $76.11{\pm}6.35$ years, female: 86.0%). Data were collected from a community senior center through face to face interviews by using instruments including measuring knowledge, perceived threat, self-efficacy, compliance with respiratory infection preventive behaviors. Results: The mean score of knowledge was 7.52 out of 13 in total. The compliance with hand washing with soap was 6.0% for 8 or more times per day. Among the participants, 12.0% adhered to the cough etiquette. Sixty-two older adults (62.0%) didn't use interdental brushes or floss at all. The stepwise linear regression indicated that age and self-efficacy for respiratory infection preventive behaviors were significant factors and explained 24.0% of the compliance with hand washing and the cough etiquette. Education level, cancer diagnosis, and self-efficacy for respiratory infection preventive behaviors were significant predictors of oral hygiene. The factor with the greatest effect was self-efficacy in the two models. Conclusion: The findings suggest that it is necessary to improve compliance with respiratory infection preventive behaviors among older adults using senior centers. In order to enhance the compliance, it is necessary to develop nursing programs based on the self-efficacy for respiratory infection preventive behaviors in the senior centers.