• 대한간호학회지
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• 제35권4호
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• pp.680-685
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• 2005

Purpose. The purpose of the study was to categorize nursing students' subjectivity in their attitude toward their jobs, and thereby understand the differences among these attitude types. Methods. The study used a Q-method to measure nursing students' attitude toward jobs identity types. In-depth and objective interviews and literature review formed Q sample. The P sample consisted of 25 nursing students. Results. The results of the study show that nursing students can be categorized into three types, depending on their attitudes toward their jobs. The firs type, 'interest-oriented' students, strongly disagree to the follow-ing: giving priority to job over marriage, standing unfair treatment in the workplace, the importance of pro-motion opportunity, irresponsibility, and uncertainty. The 'reward-oriented' students, on the other hand, strongly disagree to the following: indifference to career prospects, employment-related relocation of residence, irresponsibility, standing difficulties, and compromises with others. The third type of nursing students is the possession-oriented students, who strongly disapprove of irresponsibility, refusal to compromise with reality, standing unfair job allocation or promotion and career uncertainty. Conclusions. The study on nursing college students' attitude toward their jobs is meaningful in the following aspects: First, the study clarifies nursing college students' attitudes toward their job by categorizing it. Second, the study confirms the changing attitudes of nursing students toward jobs with the change of times and calls for proper educational programs to foster healthy career attitudes. Third, proper decision-making as regards jobs and job allocation for nurses, or their career attitudes, is beneficial to individuals, the medical industry, and society.

• Membrane and Water Treatment
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• 제14권2호
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• pp.65-76
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• 2023

Given the limited water resources and the presence of multiple decision makers with different and usually conflicting objectives in the exploitation of water resources systems, especially dam's reservoirs; therefore, the decision to determine the optimal allocation of reservoir water among decision-makers and stakeholders is a difficult task. In this study, by combining a fuzzy VIKOR technique or fuzzy multi-criteria decision making (FMCDM) and the Young's bilateral bargaining model, a new method was developed to determine the optimal quantitative and qualitative water allocation of dam's reservoir water with the aim of increasing the utility of decision makers and stakeholders and reducing the conflicts among them. In this study, by identifying the stakeholders involved in the exploitation of the dam reservoir and determining their utility, the optimal points on trade-off curve with quantitative and qualitative objectives presented by Mojarabi et al. (2019) were ranked based on the quantitative and qualitative criteria, and economic, social and environmental factors using the fuzzy VIKOR technique. In the proposed method, the weights of the criteria were determined by each decision maker using the entropy method. The results of a fuzzy decision-making method demonstrated that the Young's bilateral bargaining model was developed to determine the point agreed between the decisions makers on the trade-off curve. In the proposed method, (a) the opinions of decision makers and stakeholders were considered according to different criteria in the exploitation of the dam reservoir, (b) because the decision makers considered the different factors in addition to quantitative and qualitative criteria, they were willing to participate in bargaining and reconsider their ideals, (c) due to the use of a fuzzy-logic based decision-making approach and considering different criteria, the utility of all decision makers was close to each other and the scope of bargaining became smaller, leading to an increase in the possibility of reaching an agreement in a shorter time period using game theory and (d) all qualitative judgments without considering explicitness of the decision makers were applied to the model using the fuzzy logic. The results of using the proposed method for the optimal exploitation of Iran's 15-Khordad dam reservoir over a 30-year period (1968-1997) showed the possibility of the agreement on the water allocation of the monthly total dissolved solids (TDS)=1,490 mg/L considering the different factors based on the opinions of decision makers and reducing conflicts among them.

• Journal of Information Processing Systems
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• 제16권1호
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• pp.61-82
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• 2020

The security risk management used by some service providers is not appropriate for effective security enhancement. The reason is that the security risk management methods did not take into account the opinions of security experts, types of service, and security vulnerability-based risk assessment. Moreover, the security risk assessment method, which has a great influence on the risk treatment method in an information security risk assessment model, should be security risk assessment for fine-grained risk assessment, considering security vulnerability rather than security threat. Therefore, we proposed an improved information security risk management model and methods that consider vulnerability-based risk assessment and mitigation to enhance security controls considering limited security budget. Moreover, we can evaluate the security cost allocation strategies based on security vulnerability measurement that consider the security weight.

• 대한치과의사협회지
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• 제58권3호
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• pp.152-168
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• 2020

The propensity score matching method is a statistical method used to reduce selection bias in observational studies and to show effects similar to random allocation. There are many observational studies in dentistry research, and differences in baseline covariates between the control and case groups affect the outcome. In order to reduce the bias due to confounding variables, the propensity scores are used by equating groups based on the baseline covariates. This method is effective, especially when there are many covariates or the sample size is small. In this paper, the propensity score matching method was explained in a simple way with a dental example by using R software. This simulated data were obtained from one of retrospective study. The control group and the case group were matched according to the propensity score and compared before and after treatment. The propensity score matching method could be an alternative to compensate for the disadvantage of the observation study by reducing the bias based on the covariates with the propensity score.

• 실내환경 및 냄새 학회지
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• 제17권4호
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• pp.322-329
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• 2018

The objective of this study is to identify the research trend in the field of indoor environment in Korea. We collected 419 papers published in the Journal of the Korean Society for indoor environment between 2004 and 2018, and attempted to produce datasets using a topic modeling technique, Latent Dirichlet Allocation(LDA). The result of topic modeling showed that 8 topics ("VOCs investigation", "Subway environment", "Building thermal environment", "School health", "Building particulate matter", "Asbestos risk", "Radon risk", "Air cleaner and treatment") could be extracted using Gibbs sampling method. In terms of topic trends, investigation of volatile organic compounds, subway environment, school health, and building particulate matter showed a decreasing tendency, while the building thermal environment, asbestos risk, radon risk, air cleaners, and air treatment showed an increasing tendency. The results of this topic modeling could help us to understand current trends related indoor environment, and provide valuable information in developing future research and policy frameworks.

• 대한한의학회지
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• 제43권1호
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• pp.73-86
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• 2022

Objectives: In the health care industry, the influence of online reviews is growing. As medical services are provided mainly by providers, those services have been managed by hospitals and clinics. However, direct promotions of medical services by providers are legally forbidden. Due to this reason, consumers, like patients and clients, search a lot of reviews on the Internet to get any information about hospitals, treatments, prices, etc. It can be determined that online reviews indicate the quality of hospitals, and that analysis should be done for sustainable hospital marketing. Method: Using a Python-based crawler, we collected reviews, written by real patients, who had experienced Korean medicine, about more than 14,000 reviews. To extract the most representative words, reviews were divided by positive and negative; after that reviews were pre-processed to get only nouns and adjectives to get TF(Term Frequency), DF(Document Frequency), and TF-IDF(Term Frequency - Inverse Document Frequency). Finally, to get some topics about reviews, aggregations of extracted words were analyzed by using LDA(Latent Dirichlet Allocation) methods. To avoid overlap, the number of topics is set by Davis visualization. Results and Conclusions: 6 and 3 topics extracted in each positive/negative review, analyzed by LDA Topic Model. The main factors, consisting of topics were 1) Response to patients and customers. 2) Customized treatment (consultation) and management. 3) Hospital/Clinic's environments.

• Asian Pacific Journal of Cancer Prevention
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• 제14권3호
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• pp.2097-2100
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• 2013

Background: To estimate the numbers and trends in cervix cancer cases visiting the Radiotherapy Department at Manipal Teaching Hospital, Pokhara, Nepal, statistical modelling from retrospective data was applied. Materials and Methods: A retrospective study was carried out on data for a total of 159 patients treated for cervix cancer at Manipal Teaching Hospital, Pokhara, Nepal, between $28^{th}$ September 2000 and $31^{st}$ December 2008. Theoretical statistics were used for statistical modelling and forecasting. Results: Using curve fitting method, Linear, Logarithmic, Inverse, Quadratic, Cubic, Compound, Power and Exponential growth models were validated. Including the constant term, none of the models fit the data well. Excluding the constant term, the cubic model demonstrated the best fit, with $R^2$=0.871 (p=0.004). In 2008, the observed and estimated numbers of cases were same (12). According to our model, 273 patients with cervical cancer are expected to visit the hospital in 2015. Conclusions: Our data predict a significant increase in cervical cancer cases in this region in the near future. This observation suggests the need for more focus and resource allocation on cervical cancer screening and treatment.

• 한국실내디자인학회논문집
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• 제17권6호
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• pp.161-169
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• 2008

Recently, appearance is recognized as competitiveness as well as self expressing means, so understanding of general people have been rapidly changed. Also, since modem people have interest in an operation as well as various cosmetic treatment fields, a plastic surgery clinic is expanding its region to laser treatment and skin care for modem people. However, the plastic surgery clinic is not located in a building for only hospitals, but located in general neighborhood living facilities or an office building, so medical treatment is performed at the place. It is often found that a building plan can not conform to conditions that the hospital requires. This study is to understand a plane deciding factor of the plastic surgery clinic by analyzing it in a limit of building space and functional aspects of the plastic surgery clinic. A study method is first to investigate space composition according to the function, area allocation according to the function and a space privacy region after classifying study objects into large, middle, small scales so as to understand a functional role of the plastic surgery clinic, and secondly to analyze on the base of length of long and short edges of space and a moving line system after classifying common space types of the plastic surgery clinic through plane analysis of the study objects. As a result of the study, functional space difference according to the scale was shown, and the common space types were affected by length of the long and short edges, and it can influence space composition.

• 한국치위생학회지
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• 제22권6호
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• pp.563-572
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• 2022

Objectives: The purpose of this study is to provide basic data for elucidating the clinical experiences of nursing assistants working at dental clinics and for establishing the bases necessary for building a safe working environment for the staff at dental clinics. Methods: From March 28 to August 20, 2022, the study conducted in-depth interviews with nursing assistants working with dental hygienists in dental clinics. The collected data were analyzed using the phenomenological method. Results: The study analyzed the meanings associated with the dental clinical assistance work experiences of nursing assistants in dental clinics. A total of 98 semantic words and 9 sub-categories were extracted, which were ultimately categorized into 4 central meanings: 'imperfect reality', 'work without boundaries', 'putting oneself in someone else's shoes', and 'symbiosis'. Conclusions: The nursing assistants were exposed to an environment where they needed to perform delegated treatment procedures even when they lacked dental work competency. They recognized their gaps in learning and the necessity for designated roles as clinical assistants. Thus, it is necessary to review the allocation and expansion of the work roles of dental practitioners based on the practical and rational realities in dental practice.

• Asian Pacific Journal of Cancer Prevention
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• 제15권14호
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• pp.5571-5575
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• 2014

Background: The ability to predict the survival time of breast cancer patients is important because of the potential high morbidity and mortality associated with the disease. To develop a predictive inference for determining the survival of breast cancer patients, we applied a novel Bayesian method. In this paper, we propose the development of a databased statistical probability model and application of the Bayesian method to predict future survival times for White Hispanic female breast cancer patients, diagnosed in the US during 1973-2009. Materials and Methods: A stratified random sample of White Hispanic female patient survival data was selected from the Surveillance Epidemiology and End Results (SEER) database to derive statistical probability models. Four were considered to identify the best-fit model. We used three standard model-building criteria, which included Akaike Information Criteria (AIC), Bayesian Information Criteria (BIC), and Deviance Information Criteria (DIC) to measure the goodness of fit. Furthermore, the Bayesian method was used to derive future survival inferences for survival times. Results: The highest number of White Hispanic female breast cancer patients in this sample was from New Mexico and the lowest from Hawaii. The mean (SD) age at diagnosis (years) was 58.2 (14.2). The mean (SD) of survival time (months) for White Hispanic females was 72.7 (32.2). We found that the exponentiated Weibull model best fit the survival times compared to other widely known statistical probability models. The predictive inference for future survival times is presented using the Bayesian method. Conclusions: The findings are significant for treatment planning and health-care cost allocation. They should also contribute to further research on breast cancer survival issues.