• International Journal of Computer Science & Network Security
• /
• 제21권5호
• /
• pp.23-30
• /
• 2021

In recent years, hazardous flash flooding has caused deaths and damage to infrastructure in Saudi Arabia. In this paper, our aim is to assess patterns and trends in climate means and extremes affecting flash flood hazards and water resources in Saudi Arabia for the purpose to improve risk assessment for forecast capacity. We would like to examine temperature, precipitation climatology and trend magnitudes at surface stations in Saudi Arabia. Based on the assessment climate patterns maps and trends are accurately used to identify synoptic situations and tele-connections associated with flash flood risk. We also study local and regional changes in hydro-meteorological extremes over recent decades through new applications of statistical methods to weather station data and remote sensing based precipitation products; and develop remote sensing based high-resolution precipitation products that can aid to develop flash flood guidance system for the flood-prone areas. A dataset of extreme events has been developed using the multi-decadal station data, the statistical analysis has been performed to identify tele-connection indices, pressure and sea surface temperature patterns most predictive to heavy rainfall. It has been combined with time trends in extreme value occurrence to improve the potential for predicting and rapidly detecting storms. A methodology and algorithms has been developed for providing a well-calibrated precipitation product that can be used in the early warning systems for elevated risk of floods.

• Journal of Periodontal and Implant Science
• /
• 제51권1호
• /
• pp.30-39
• /
• 2021

Purpose: The present study was undertaken to examine whether periodontal probe visibility (PV) accurately reflects gingival thickness (GT) and to identify factors affecting PV using cluster and multivariate analyses. Methods: The clinical characteristics of the maxillary central incisors (n=90 subjects) were examined. Clinical photographs, sex, PV, probing depth, gingival width, papilla height, GT as measured with an ultrasonic device, and the ratio of crown width to crown length were recorded. Multivariate analysis, using multinomial baseline-category logistic regression, was used to identify factors predictive of PV. Cluster analysis was used to identify gingival biotypes. Results: In the multivariate analysis, sex was the only significant predictor of PV (odds ratio, 6.48). Two clusters of subjects were created based on morphometric parameters. The mean GT among cluster A subjects was significantly lower than that among cluster B subjects (P=0.015). No significant difference was found between cluster A and B subjects in terms of PV score (P=0.583). Conclusions: Periodontal PV was not associated with GT as measured directly using an ultrasonic device. Sex was a highly significant predictor of periodontal PV. GT was found to be correlated with morphological characteristics of the periodontium.

• Journal of Preventive Medicine and Public Health
• /
• 제54권2호
• /
• pp.145-152
• /
• 2021

Objectives: This study aimed to identify regional differences in the high-risk drinking rate among yearly alcohol users in Korea and to identify relevant regional factors for each quintile using quantile regression. Methods: Data from 227 counties surveyed by the 2017 Korean Community Health Survey (KCHS) were analyzed. The analysis dataset included secondary data extracted from the Korean Statistical Information Service and data from the KCHS. To identify regional factors related to the high-risk drinking rate among yearly alcohol users, quantile regression was conducted by dividing the data into 10%, 30%, 50%, 70%, and 90% quantiles, and multiple linear regression was also performed. Results: The current smoking rate, perceived stress rate, crude divorce rate, and financial independence rate, as well as one's social network, were related to the high-risk drinking rate among yearly alcohol users. The quantile regression revealed that the perceived stress rate was related to all quantiles except for the 90% quantile, and the financial independence rate was related to the 50% to 90% quantiles. The crude divorce rate was related to the high-risk drinking rate among yearly alcohol users in all quantiles. Conclusions: The findings of this study suggest that local health programs for high-risk drinking are needed in areas with high local stress and high crude divorce rates.

• 한국보육지원학회지
• /
• 제18권1호
• /
• pp.51-70
• /
• 2022

Objective: In order to promote the rights of childcare teachers, there is a need to identify problems and demands about the rights of childcare teachers. Therefore, this study sought to examine the perception of childcare teachers' rights in order to identify the concepts of teacher rights. Methods: This study used the concept mapping method to identify the concepts of childcare teachers' teacher rights and interpreted these concepts utilizing the multi-dimension analysis method. Results: As a result of interviews from eight childcare teachers, 37 statements were derived. The result of similarities evaluated by 28 childcare teachers showed that 37 statements about teachers' rights consisted of two dimensions and four clusters (direct-indirect and indoor-outdoor of day-care center). Conclusion/Implications: This study suggested that direct and indirect efforts are needed to enhance the rights of childcare teachers and that change is necessary not only within daycare centers such as the principal but that change is also necessary outside daycare centers such as at government agencies in relation to daycare teachers's rights.

• 한국인공지능학회지
• /
• 제10권1호
• /
• pp.21-25
• /
• 2022

Korea has relatively less crime than other countries. However, the crime rate is steadily increasing. Many people think the crime rate is decreasing, but the crime arrest rate has increased. The goal is to check the relationship between CCTV and the crime rate as a way to lower the crime rate, and to identify the correlation between areas without CCTV and areas without CCTV. If you see a crime that can happen at any time, I think you should use a random forest algorithm. We also plan to use machine learning random forest algorithms to reduce the risk of overfitting, reduce the required training time, and verify high-level accuracy. The goal is to identify the relationship between CCTV and crime occurrence by creating a crime prevention algorithm using machine learning random forest techniques. Assuming that no crime occurs without CCTV, it compares the crime rate between the areas where the most crimes occur and the areas where there are no crimes, and predicts areas where there are many crimes. The impact of CCTV on crime prevention and arrest can be interpreted as a comprehensive effect in part, and the purpose isto identify areas and frequency of frequent crimes by comparing the time and time without CCTV.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제16권10호
• /
• pp.3333-3354
• /
• 2022

The 5G Core Network (5GC) is an essential part of the mobile communication network, but its security protection strategy based on the boundary construction is difficult to ensure the security inside the network. For example, the Network Function (NF) mutual authentication mechanism that relies on the transport layer security mechanism and OAuth2.0's Client Credentials cannot identify the hijacked NF. To address this problem, this paper proposes a trust model for 5GC based on NF interaction behavior to identify malicious NFs and improve the inherent security of 5GC. First, based on the interaction behavior and context awareness of NF, the trust between NFs is quantified through the frequency ratio of interaction behavior and the success rate of interaction behavior. Second, introduce trust transmit to make NF comprehensively refer to the trust evaluation results of other NFs. Last, classify the possible malicious behavior of NF and define the corresponding punishment mechanism. The experimental results show that the trust value of NFs converges to stable values, and the proposed trust model can effectively evaluate the trustworthiness of NFs and quickly and accurately identify different types of malicious NFs.

• International Journal of Advanced Culture Technology
• /
• 제10권2호
• /
• pp.1-11
• /
• 2022

Purpose: The purpose of this study was to empirically test a model of associations linking locations and competition among nursing homes (NHs), mediated by facility grade and registered nurse (RN) turnover, on activities of daily living (ADLs) in Korean NHs. Methods: This study used a cross-sectional design to identify causal factors on NH residents' ADLs. Data were collected from June 2017 to August 2017. A disproportionate stratified cluster sampling method of NHs across Korea was used to gain representation. The collected data consisted of location and the Herfindahl-Hirschman Index (HHI), RN turnover rate, facility grade, and NH residents' ADLs. Results: All pathways affecting ADLs were not significant, and the effect on facility grade was significant in RN turnover (β = -.59, p < .001). RN turnover associated negatively with facility grade. In other words, the higher the RN turnover, the worse the facility grade. Conclusion: This study is the first to examine the impact of location and HHIs, mediated by RN turnover rate and facility grade, on NH residents' ADLs. To improve residents' ADLs, subsequent studies are needed to identify the factors affecting ADLs utilizing other variables because this study did not identify factors that affect ADLs.

• International Journal of Computer Science & Network Security
• /
• 제22권12호
• /
• pp.125-131
• /
• 2022

The diversity and complexity of criminal, administrative and civil cases resolved by the courts makes it difficult to develop universal automated tools for the analysis and evaluation of justice. However, big data generated in the scope of justice gives hope that this problem will be resolved as soon as possible. The big data applying makes it possible to identify typical options for resolving cases, form detailed rules for the individualization of a court decision, and correlate these rules with an abstract provisions of law. This approach allows us to somewhat overcome the contradiction between the abstract and the concrete in law, to automate the analysis of justice and to model e-justice for scientific and practical purposes. The article presents the results of using dimension reduction, SHAP value, and p-value to identify, analyze and evaluate the individualization of justice and the differentiation of legal regulation. Processing and analysis of arrays of court decisions by computational methods make it possible to identify the typical views of courts on questions of fact and questions of law. This knowledge, obtained automatically, is promising for the scientific study of justice issues, the improvement of the prescriptions of the law and the probabilistic prediction of a court decision with a known set of facts.

• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 2022년도 학술발표회
• /
• pp.475-475
• /
• 2022

The aim of this study is to identify the significant pollutant sources from the tributaries that are affecting the water quality of the study site, the Geum River and provide a solution to enhance the water quality. Multivariate statistical analysis modles such as cluster analysis, Principal component analysis (PCA) and positive matrix factorization (PMF) were applied to identify and prioritize the major pollutant sources of the two major tributaries, Gab-cheon and Miho-cheon, of the Geum River. PCA identifies three major pollutant sources for Gab-cheon and Miho-cheon, respectively. For Gab-cheon, wastewater treatment plant (WWTP), urban, and agricultural pollutions are identified as major pollutant sources. For Miho-cheon, agricultural, urban, and forest land are identified as major pollutant sources. On the contrary, PMF identifies three pollutant sources in Gab-cheon, same as PCA result and two pollutant sources in Miho-cheon. Water quality control scenarios are formulated and improvement of water quality in the river locations are simulated and analyzed with the Environmental Fluid Dynamic Code (EFDC) model. Scenario results were evaluated using a water quality index developed by Canadian Council of Ministers of the Environment. PCA and PMF appears to be effective to identify water pollution sources for the Geum river and also its tributaries in detail and thus can be used for the development of water quality improvement alternative of the above water bodies.

• Nuclear Engineering and Technology
• /
• 제54권12호
• /
• pp.4684-4692
• /
• 2022

Radionuclide identification is an important part of the nuclear material identification system. The development of artificial intelligence and machine learning has made nuclide identification rapid and automatic. However, many methods directly use existing deep learning models to analyze the gamma-ray spectrum, which lacks interpretability for researchers. This study proposes an explainable radionuclide identification algorithm based on the convolutional neural network and class activation mapping. This method shows the area of interest of the neural network on the gamma-ray spectrum by generating a class activation map. We analyzed the class activation map of the gamma-ray spectrum of different types, different gross counts, and different signal-to-noise ratios. The results show that the convolutional neural network attempted to learn the relationship between the input gamma-ray spectrum and the nuclide type, and could identify the nuclide based on the photoelectric peak and Compton edge. Furthermore, the results explain why the neural network could identify gamma-ray spectra with low counts and low signal-to-noise ratios. Thus, the findings improve researchers' confidence in the ability of neural networks to identify nuclides and promote the application of artificial intelligence methods in the field of nuclide identification.