• Title/Summary/Keyword: Model-based evaluation

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Evaluation of the Relationship between the Exposure Level to Mixed Hazardous Heavy Metals and Health Effects Using Factor Analysis (요인분석을 이용한 유해 중금속 복합 노출수준과 건강영향과의 관련성 평가)

  • Kim, Eunseop;Moon, Sun-In;Yim, Dong-Hyuk;Choi, Byung-Sun;Park, Jung-Duck;Eom, Sang-Yong;Kim, Yong-Dae;Kim, Heon
    • Journal of Environmental Health Sciences
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    • v.48 no.4
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    • pp.236-243
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    • 2022
  • Background: In the case of multiple exposures to different types of heavy metals, such as the conditions faced by residents living near a smelter, it would be preferable to group hazardous substances with similar characteristics rather than individually related substances and evaluate the effects of each group on the human body. Objectives: The purpose of this study is to evaluate the utility of factor analysis in the assessment of health effects caused by exposure to two or more hazardous substances with similar characteristics, such as in the case of residents living near a smelter. Methods: Heavy metal concentration data for 572 people living in the vicinity of the Janghang smelter area were grouped based on several subfactors according to their characteristics using factor analysis. Using these factor scores as an independent variable, multiple regression analysis was performed on health effect markers. Results: Through factor analysis, three subfactors were extracted. Factor 1 contained copper and zinc in serum and revealed a common characteristic of the enzyme co-factor in the human body. Factor 2 involved urinary cadmium and arsenic, which are harmful metals related to kidney damage. Factor 3 encompassed blood mercury and lead, which are classified as related to cardiovascular disease. As a result of multiple linear regression analysis, it was found that using the factor index derived through factor analysis as an independent variable is more advantageous in assessing the relevance to health effects than when analyzing the two heavy metals by including them in a single regression model. Conclusions: The results of this study suggest that regression analysis linked with factor analysis is a good alternative in that it can simultaneously identify the effects of heavy metals with similar properties while overcoming multicollinearity that may occur in environmental epidemiologic studies on exposure to various types of heavy metals.

An Analysis of Road User Acceptance Factors for Fully Autonomous Vehicles : For Drivers and Pedestrians (완전 자율주행자동차에 대한 도로이용자 수용성 요인 분석 : 운전자 및 보행자를 대상으로)

  • Jeong, Mi-Kyeong;Choi, Mee-Sun
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.21 no.5
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    • pp.117-132
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    • 2022
  • The purpose of this study is to analyze factors that affect road users' acceptance of fully autonomous vehicles (level 4 or higher). A survey was done with drivers of general cars and pedestrians who share roads with fully autonomous vehicles. Five acceptability factors were selected: trust towards technology, compatibility, policy, perceived safety, and perceived usefulness. The effect on behavioral intention was analyzed using structural equation modeling (SEM). The perceived safety and trust towards technology were found to be very important in the acceptance of fully autonomous vehicles, regardless of the respondent, and policy was not influential. Compatibility and perceived usefulness were particularly influential factors for drivers. In order to improve the acceptance by road users, securing technical completeness of fully autonomous vehicles is important. Certification and evaluation of the safe driving ability of fully autonomous vehicles should be thoroughly performed, and based on the results, it is necessary to improve the perception by road users. It is necessary to positively recognize fully autonomous vehicles through education and publicity for road users and to support their smooth interaction.

Full-mouth rehabilitation with increasing vertical dimension on the patient with severely worn-out dentition and orthognathic surgery history: A case report (악교정수술 병력을 가진 과도한 치아 마모를 보이는 환자의 수직고경 증가를 동반한 전악 수복 증례)

  • Sang-Myeong Tak;Chang-Mo Jeong;Jung-Bo Huh;So-Hyoun Lee;Mi-Jung Yun
    • The Journal of Korean Academy of Prosthodontics
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    • v.61 no.1
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    • pp.33-43
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    • 2023
  • Pathological wear across the entire dentition causes problems such as collapsed occlusal plane, reduced vertical dimension, anterior premature contact, inadequate anterior guidance, and tooth migration, thereby induce symptoms such as temporomandibular joint disorder, reduced masticatory efficiency, and tooth hypersensitivity. For the treatment of patients with excessive wear, evaluation of vertical dimension should be preceded along with analysis of the cause. The patient in this case was a 45-year-old female with a history of orthognathic surgery. Through clinical examination, radiographic examination, and model analysis, overall tooth wear, interdental spacing in the anterior maxillary region, retruded condylar position, and insufficient interocclusal space for prosthetic restoration were confirmed. Full mouth rehabilitation with increased vertical dimension was planned, the patient's adaptation to the new vertical dimension was evaluated with a removable occlusal splint and temporary prosthesis, and cross-mounting was performed based on the temporary restoration to fabricate the definitive zirconia prosthesis, maintaining the adjusted vertical dimension. It showed satisfactory functional and esthetic results through stable restoration of the occlusal relationship.

Development and Evaluation of Safe Route Service of Electric Personal Assistive Mobility Devices for the Mobility Impaired People (교통약자를 위한 전동 이동 보조기기 안전 경로 서비스의 개발과 평가)

  • Je-Seung WOO;Sun-Gi HONG;Sang-Kyoung YOO;Hoe Kyoung KIM
    • Journal of the Korean Association of Geographic Information Studies
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    • v.26 no.3
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    • pp.85-96
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    • 2023
  • This study developed and evaluated a safe route guidance service for electric personal assistive mobility device used mainly by the mobility impaired people to improve their mobility. Thirteen underlying factors affecting the mobility of electric personal assistive mobility device have been derived through a survey with the mobility impaired people and employees in related organizations in Busan Metropolitan City. After assigning safety scores to individual factors and identifying the relevant factors along routes of interest with an object detection AI model, the safe route for electric personal assistive mobility device was provided through an optimal path-finding algorithm. As a result of comparing the general route of T-map and the recommended route of this study for the identical routes, the latter had relatively fewer obstacles and the gentler slope than the former, implicating that the recommended route is safer than the general one. As future works, it is necessary to enhance the function of a route guidance service based on the real-time location of users and to conduct spot investigations to evaluate and verify its social acceptability.

Soil Depth Estimation and Prediction Model Correction for Mountain Slopes Using a Seismic Survey (탄성파 탐사를 활용한 산지사면 토심 추정 및 예측모델 보정)

  • Taeho Bong;Sangjun Im;Jung Il Seo;Dongyeob Kim;Joon Heo
    • Journal of Korean Society of Forest Science
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    • v.112 no.3
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    • pp.340-351
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    • 2023
  • Landslides are major natural geological hazards that cause enormous property damage and human casualties annually. The vulnerability of mountainous areas to landslides is further exacerbated by the impacts of climate change. Soil depth is a crucial parameter in landslide and debris flow analysis, and plays an important role in the evaluation of watershed hydrological processes that affect slope stability. An accurate method of estimating soil depth is to directly investigate the soil strata in the field. However, this requires significant amounts of time and money; thus, numerous models for predicting soil depth have been proposed. However, they still have limitations in terms of practicality and accuracy. In this study, 71 seismic survey results were collected from domestic mountainous areas to estimate soil depth on hill slopes. Soil depth was estimated on the basis of a shear wave velocity of 700 m/s, and a database was established for slope angle, elevation, and soil depth. Consequently, the statistical characteristics of soil depth were analyzed, and the correlations between slope angle and soil depth, and between elevation and soil depth were investigated. Moreover, various soil depth prediction models based on slope angle were investigated, and corrected linear and exponential soil depth prediction models were proposed.

A Comparative Study on Discrimination Issues in Large Language Models (거대언어모델의 차별문제 비교 연구)

  • Wei Li;Kyunghwa Hwang;Jiae Choi;Ohbyung Kwon
    • Journal of Intelligence and Information Systems
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    • v.29 no.3
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    • pp.125-144
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    • 2023
  • Recently, the use of Large Language Models (LLMs) such as ChatGPT has been increasing in various fields such as interactive commerce and mobile financial services. However, LMMs, which are mainly created by learning existing documents, can also learn various human biases inherent in documents. Nevertheless, there have been few comparative studies on the aspects of bias and discrimination in LLMs. The purpose of this study is to examine the existence and extent of nine types of discrimination (Age, Disability status, Gender identity, Nationality, Physical appearance, Race ethnicity, Religion, Socio-economic status, Sexual orientation) in LLMs and suggest ways to improve them. For this purpose, we utilized BBQ (Bias Benchmark for QA), a tool for identifying discrimination, to compare three large-scale language models including ChatGPT, GPT-3, and Bing Chat. As a result of the evaluation, a large number of discriminatory responses were observed in the mega-language models, and the patterns differed depending on the mega-language model. In particular, problems were exposed in elder discrimination and disability discrimination, which are not traditional AI ethics issues such as sexism, racism, and economic inequality, and a new perspective on AI ethics was found. Based on the results of the comparison, this paper describes how to improve and develop large-scale language models in the future.

An Evaluation of Development Plans for Rolling Stock Maintenance Shop Using Computer Simulation - Emphasizing CDC and Generator Car - (시뮬레이션 기법을 이용한 철도차량 중정비 공장 설계검증 - 디젤동차 및 발전차 중정비 공장을 중심으로 -)

  • Jeon, Byoung-Hack;Jang, Seong-Yong;Lee, Won-Young;Oh, Jeong-Heon
    • Journal of the Korea Society for Simulation
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    • v.18 no.3
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    • pp.23-34
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    • 2009
  • In the railroad rolling stock depot, long-term maintenance tasks is done regularly every two or four year basis to maintain the functionality of equipments and rolling stock body or for the repair operation of the heavily damaged rolling stocks by fatal accidents. This paper addresses the computer simulation model building for the rolling stock maintenance shop for the CDC(Commuter Diesel Car) and Generator Car planned to be constructed at Daejon Rolling Stock Depot, which will be moved from Yongsan Rolling Stock Depot. We evaluated the processing capacity of two layout design alternatives based on the maintenance process chart through the developed simulation models. The performance measures are the number of processed cars per year, the cycle time, shop utilization, work in process and the average number waiting car for input. The simulation result shows that one design alternative outperforms another design alternative in every aspect and superior design alternative can process total 340 number of trains per year 15% more than the proposed target within the current average cycle time.

Analysis of Research Trends in Information Literacy Education Using Keyword Network Analysis and Topic Modeling (키워드 네트워크 분석과 토픽모델링을 활용한 정보활용교육 연구 동향 분석)

  • Jeong-Hoon, Lim
    • Journal of the Korean Society for information Management
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    • v.39 no.4
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    • pp.23-48
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    • 2022
  • The purpose of this study is to investigate the flow of domestic information literacy education research using keyword network analysis and topic modeling and to explore the direction of information literacy education in the future. For this reason, 306 academic papers related to information literacy education published in academic journals of the library and information science field in Korea were chosen. And through the preprocessing process for abstracts of the paper, total keyword appearance frequency, keyword appearance frequency by period, and keyword simultaneous occurrence frequency were analyzed. Subsequently, keyword network analysis analyzed the degree centrality, between centrality, and eigenvector centrality of keywords. Using structural topic modeling analysis, 15 topics -curriculum, information literacy effect, contents of information literacy education, school library education, information media literacy, information literacy ability evaluation index, library anxiety, public library program, health information literacy ability, digital divide, library assisted instruction improvement, research trend, information literacy model, and teacher role-were derived. In addition, the trend of topics by year was analyzed to confirm the change in relative weight by topic. Based on these results, the direction of information literacy education and the suggestions for follow-up research were presented.

Prediction of Safety Grade of Bridges Using the Classification Models of Decision Tree and Random Forest (의사결정나무 및 랜덤포레스트 분류 모델을 이용한 교량 안전등급 예측)

  • Hong, Jisu;Jeon, Se-Jin
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.43 no.3
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    • pp.397-411
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    • 2023
  • The number of deteriorated bridges with a service period of more than 30 years has been rapidly increasing in Korea. Accordingly, the importance of advanced maintenance technologies through the predictions of age-induced deterioration degree, condition, and performance of bridges is more and more noticed. The prediction method of the safety grade of bridges was proposed in this study using the classification models of the Decision Tree and the Random Forest based on machine learning. As a result of analyzing these models for the 8,850 bridges located in national roads with various evaluation indexes such as confusion matrix, balanced accuracy, recall, ROC curve, and AUC, the Random Forest largely showed better predictive performance than that of the Decision Tree. In particular, random under-sampling in the Random Forest showed higher predictive performance than that of other sampling techniques for the C and D grade bridges, with the recall of 83.4%, which need more attention to maintenance because of the significant deterioration degree. The proposed model can be usefully applied to rapidly identify the safety grade and to establish an efficient and economical maintenance plan of bridges that have not recently been inspected.

A Study on Exploring Factors Influencing Military Security Level (Based on the Theory of Planned Behavior, Deterrence and Protection Motivation) (군(軍) 보안수준에 미치는 영향요인 탐색에 관한 연구 (계획 행동이론, 억제이론, 보호 동기 이론을 중심으로))

  • Jong-Hyoun Kim;Sang-Jun Ahn
    • Convergence Security Journal
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    • v.22 no.4
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    • pp.3-9
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    • 2022
  • Recently, as the environment of the 4th industrial revolution has arrived, the opening, sharing and convergence of data are actively being achieved in any organization. However, the opening and sharing of data inevitably leads to security vulnerability and there is ambivalence that is a threat that can affect the existence of an organization operated in the 4th industrial revolution environment. Especially security issues in the organization of the military can be a threat to the state, not the military itself, so it is always necessary to maintain a high level of security discipline. In this paper, 14 variables were selected through structural equation model applying theory of planned behavior, deterrence and protection motivation to find out the security level development measures by extracting factors that can affect security level. As a result, the theory of planned behavior that the security knowledge embodied through the usual security regulation education and evaluation affects the behavior was adopted, and the theory of deterrence and protection motivation showed the significance of the rejection level. In addition, it was confirmed that the variables that have the greatest impact on the military security level through the measured values of the three-year security audit were commanders and mental security. In conclusion, in order to improve the security level, it is suggested that security education, definite reward and punishment, and security system upgrading should be firmly established and mental security posture should be secured.