• Journal of Korean Dental Hygiene Science
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• v.5 no.2
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• pp.1-11
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• 2022

Background: This study was aimed at investigating the type of work of dental hygienists and identifying factors affecting the subjective health status according to hazardous risk factors in the working environment. Methods: From May 15 to 31, 2019, we surveyed 411 dental hygienists working at dental hospitals in the metropolitan area. SPSS 25.0 was used to perform the frequency analysis, t-test, one-way analysis of variance, Pearson's correlation analysis, and multiple regression analysis. Results: Regarding factors related to the degree of exposure to hazardous risk factors in the work environment and subjective health status, the more exposed the ergonomic (p<0.05) and psychological (p< 0.001)factors, the worse is the subjective health status. Conclusion: The results of this study suggest that the working environment should be improved for dental hygienists such that they can perform their duties in a safe environment.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.494-496
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• 2013

Cost-Benefit Analysis (CBA) is a systematic optimization process that allows users to compare different alternatives and to determine if a project is a solid investment. Many state DOTs have included CBA in their pavement management systems (PMSs) to help allocate state funds for maintenance, rehabilitation, resurfacing, and reconstruction of pavements. In a typical CBA, each pavement type has an assigned weight factor which represents the level of importance of this pavement type. To conduct an accurate CBA, it is essential to select appropriate weight factors. Arbitrarily assigning weights factors to pavements can lead to biased and inaccurate funding allocation decisions. The purpose for this paper is to outline a method to develop an ideal set of weight factors that can be utilized to conduct more accurate CBA. To this end, a matrix of all possible weight factors sets was developed. CBA was conducted for each set of weight factors to obtain a population of possible optimization solutions. Then a regression analysis was performed to establish the relationship between benefit and weight factors. Finally, a multi-objective genetic algorithm was applied to select the optimal set of weight factors. The findings from this study can be used by state DOTs to strategically manage their roadway systems in a cost effective manner.

• Journal of the korean academy of Pediatric Dentistry
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• v.51 no.1
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• pp.40-54
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• 2024

This study aims to identify the regional distribution in the prevalence of dental caries and related multidimensional factors among 12-year-old children in Korea. Data from the 2018 Child Oral Health Survey were used to calculate the average DMFT index of 12-year-old children in metropolitan cities, and a multi-level regression model was applied to explain the regional distribution of dental caries prevalence and related factors. Factors were divided into two levels by administrative structure. This study finds a significant regional difference in the prevalence of dental caries in 12-year-old Korean children across metropolitan cities. Multilevel analysis showed that district-level factors (average number of pit and fissure-sealed permanent teeth, dental treatment demand rate, preventive treatment rate, sex ratio, and number of dentists per 100,000 people) and metropolitan-level factors (intakes of cariogenic beverages and number of pediatric dental hospitals and clinics per 100,000 people) had a significant effect on dental caries prevalence (p < 0.05). Individual characteristics and local socio-environmental factors influence the prevalence of dental caries. Especially considering the strong dependence on preventive treatment and accessibility to dental care services, it is necessary to provide adequate preventive treatment and expand health care resources in high-risk areas of dental caries.

• Korea Journal of Hospital Management
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• v.29 no.3
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• pp.11-25
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• 2024

Purpose: This study investigates the factors influencing medical school faculty's entrepreneurial decisions and prioritizes these factors. Methodology: The study examines the determinants of entrepreneurial decisions among medical school faculty by reviewing prior studies. These determinants were categorized into four perspectives: resource-based, industrial organization, entrepreneur characteristics, and other. Using the Analytic Hierarchy Process(AHP), the study analyzed the relative priorities of 27 specific indicators. Surveys were conducted with medical school faculty with startup experience, professors with relevant expertise, and organizational leaders involved in entrepreneurship. A total of 33 responses were validated for consistency, and an empirical analysis identified the priority of factors influencing medical school faculty startups. Findings: The findings reveal that 'entrepreneur characteristics' and 'institutional and organizational support' are the highest priority factors for medical school faculty. Key resource-based factors include the 'leave of absence' or 'concurrent employment policy,' availability of 'professional human resources,' and 'organizational support' specializing in startups. An integrated analysis shows that while intellectual resources such as research publications, patents, and physical space are necessary, the highest priority is given to leave policies, professional human resources, and organizational support. Practical Implication: Medical school faculty are recognized as key innovation agents in the bio-health industry. The results provide crucial insights for policymakers and stakeholders at governmental, institutional, and organizational levels. Strengthening self-competence, increasing entrepreneurship opportunities, and establishing professional human resources and organizational support within medical universities or hospitals are critical for facilitating medical school faculty startups.

• The Journal of the Korea Contents Association
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• v.12 no.10
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• pp.178-194
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• 2012

Regional medical center, this country's public health researchers to activate discussion about public health nature of publicness and Regional medical center to identify actual conditions of the present analysis of previous studies based on the experience of researchers and policy factors, environmental factors, financial factors, and self-sustaining factors affecting the activation of the public health by assuming that the four provinces, Chungnam Regional Medical Center conducted the survey to target four factors through empirical analysis and 40 kinds of relationships with sub-variables hypothesis. To empirical analysis as a background element present hypotheses and research model setting, study population and method of analysis of the set, factor analysis and reliability, validity analysis conducted, and Windows 7 operating system SPSS 19.0 analysis tool for Regional Medical Center enable the public health was to investigate the relationship between factors and variables, PLS 2.0 as an analytical tool to test the hypothesis through the analysis of the model was used.

• The Journal of the Korea Contents Association
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• v.9 no.12
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• pp.814-825
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• 2009

This paper is to analyze the relative weight and the priority order of the selection factors for IPTV. To obtain the goal this paper, firstly, the selecting factors for IPTV were identified and conceptualized on reviewing previous literatures. And this paper proposed the hierarchy model using the factor analysis on IPTV users. and utilized AHP in analysis method. Secondly, AHP model constructed 4 higher factors, and 15 lower factors. The higher factors were 'Quality Acceptance', 'Social Effect', 'Using Motive' and 'Individual Psychology'. Results of this study show that relative weights among factors IPTV selection were founded as 'Quality Acceptance(33.0%)', 'Utilization Motive(31.8%)', 'Individual Psychology(21.3%)' and 'Social Influence(13.9%)'. Economic efficiency takes the top rank in sub-criteria included 15 factors and than convenience, amount of information, discrimination, self-efficacy, innovation, relative advantage in order listed. For the generalization of the research results, further researchs are needed to investigate intended use of IPTV on other method of analysis.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.774-777
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• 2005

Dengue Fever(DF) and Dengue haemorrhagic fever(DHF) has become a major international public health concern. Dengue Fever(DF) and Dengue haemorrhagic Fever (DHF) is also still the major health problem of Thailand, although many campaigns against it have been conducted throughout the country. GIS and Remotely Sensed data are used to evaluate the relationships between socio-spatial, environmental factors/indicators and the incidences of viral diseases. The aim of the study is to identify the spatial risk factors in Dengue and Dengue Haemorrhagic Fever in Sukhothai province, Thailand using statistical, spatial and GIS Modelling. Preliminary results demonstrated that physical factors derived from remotely sensed data could indicate variation in physical risk factors affecting DF and DHF. The present study emphasizes the potential of remotely sensed data and GIS in spatial factors affecting Dengue Risk Zone analysis. The relationship between land cover and the cases of incidence of DF and DHF by information value method revaluated that highest information value is obtained for Built-up area. A negative relationship was observed for the forest area. The relations between climate data and cases of incidence have shown high correlation with rainfall factors in rainy season but poor correlation with temperature and relative humidity. The present study explores the potential of remotely sensed data and GIS in spatial analysis of factors affecting Dengue epidemic, strong spatial analysis tools of GIS. The capabilities of GIS for analyst spatial factors influencing risk zone has made it possible to apply spatial statistical analysis in Disease risk zone.

• Journal of Family Resource Management and Policy Review
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• v.13 no.4
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• pp.115-139
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• 2009

This study focused on the development of a scale measuring the effect of consumer education. The purposes of this study were to develop a tool which could measure consumer knowledge, consumer attitudes and consumer behavior. Data were collected from 266 college students. Analysis was done using frequency, cross tabulation analysis, reliability test, principle components factor analysis, confirmatory factor analysis (Amos 5.0), and multiple regression analysis. The results from this study were as follows: 1) Nine consumer knowledge factors (23-items) were identified: consciousness of consumer education and evaluation, consumer rights and allowance management, methods of consumer education and consumer institutions, green energy and environmental consumption, essence and content of consumer education, consumer rights and consumer duty, critical consideration and consumer's damage salvation, buying minds and decision-making, independent consumers. Total variance was 58.4%. Cronbach's alpha for the nine factors ranged from .68-.79. 2) Five consumer attitude factors (26-items) were identified: green environmental consumption, consumer's role and rights, resources saving and consumer's damage salvation, consciousness of consumers, and right consumption. Total variance was 59.2%. Cronbach's alpha for the five factors ranged from .89-.94. 3) Seven consumer behavior factors (27-items) were identified: social role and rights of consumer and consumer movement, right buying and segregated garbage collection, green environmental consumption and resources saving, altruism and decision-making, allowance management and impulse buying, consumer's damage salvation, and consciousness of consumer. The total variance was 59.1%. Cronbach's alpha for the seven factors ranged from .77-.88. Finally, a scale measuring the effect of consumer education consisting of 76 items (consumer knowledge: 23 items (9 factors), consumer attitude: 26 items (5 factors), consumer behavior: 27 items (7 factors)) was constructed.

• Journal of Korea Port Economic Association
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• v.34 no.3
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• pp.113-132
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• 2018

Mokpo port marked the $131^{st}$ anniversary of its opening in 2018. while the Mokpo has taken the new port development initiatives, it is limited by inefficient port functioning due to the lack of maritime port policy and government investment. Hence, port logistics has not been activated. Additionally, studies on Mokpo port have not been conducted, and knowledge available on the port is declarative in nature. On the other hand, research on port competitiveness focuses on how to analyze the factors that determine port competitiveness. Therefore, this study was intended to expand the existing research on Mokpo port and conduct an analysis of non-competitiveness factors and suggested improvements by considering the operational aspect of Mokpo port. In this regard the importance of non-competitiveness factors was assessed through an analytic hierarchy process(AHP) analysis and the influence of the non-competitiveness factors was analyzed through an fuzzy structural modeling(FSM) analysis. The result of the AHP analysis show ed the important non-competitiveness factors included the deactivation of industrial complexes around Mokpo port, the number of liner route, the cost of the pilot and tug. Accor ding to the FSM analysis, the top level included the non-competitive factors at Mokpo port; the intermediate level included the number of liner routes, cost of pilot and tug, enrance and clearance fee, costs of inland transportation, fee for port facilities, and loading and unloading costs; and the bottom level comprised the most non-competitive factors including the deactivation of industrial complexes around Mokpo port, hinterland connectivity, access to international port, incentives, and cost of transportation and storage. Based on the results of analysis, improvements were suggested for non-competitive factors of Mokpo.

• Education of Primary School Mathematics
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• v.26 no.4
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• pp.333-348
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• 2023

Clear analysis and diagnosis of various characteristic factors of individual students is the most important in order to realize individual customized teaching and learning, which is considered the most essential function of math artificial intelligence-based digital textbooks. In this study, analysis factors and tools for individual customized learning diagnosis and construction models for data collection and analysis were derived from mathematical AI digital textbooks. To this end, according to the Ministry of Education's recent plan to apply AI digital textbooks, the demand for AI digital textbooks in mathematics, personalized learning and prior research on data for it, and factors for learner analysis in mathematics digital platforms were reviewed. As a result of the study, the researcher summarized the factors for learning analysis as factors for learning readiness, process and performance, achievement, weakness, and propensity analysis as factors for learning duration, problem solving time, concentration, math learning habits, and emotional analysis as factors for confidence, interest, anxiety, learning motivation, value perception, and attitude analysis as factors for learning analysis. In addition, the researcher proposed noon data on the problem, learning progress rate, screen recording data on student activities, event data, eye tracking device, and self-response questionnaires as data collection tools for these factors. Finally, a data collection model was proposed that time-series these factors before, during, and after learning.