• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6A
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• pp.965-976
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• 2006

A realistic lifetime seismic-reliability based approach is unavoidable to perform Life-Cycle Cost (LCC)-effective optimum design, maintenance, and retrofitting of structures against seismic risk. So far, though a number of researchers have proposed the LCC-based seismic design and retrofitting methodologies, most researchers have only focused on the methodological point. Accordingly, in most works, they have not been quantitatively considered critical factors such as the effects of seismic retrofit, maintenance, and environmental stressors on lifetime seismic reliability assessment of deteriorating structures. Thus, in this study, a systemic lifetime seismic reliability analysis methodology is proposed and a program HPYER-DRAIN2DX-DS is developed to perform the desired lifetime seismic reliability analysis. To demonstrate the applicability of the program, it is applied to an example bridge with or without seismic retrofit and maintenance strategies. From the numerical investigation, it may be positively stated that HYPER-DRAIN2DX-DS can be utilized as a useful numerical tool for LCC-effective optimum seismic design, maintenance, and retrofitting of bridges.

• The Journal of the Korea Contents Association
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• v.22 no.8
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• pp.671-680
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• 2022

This study evaluated the consistency between the web-based and paper-based mibyeong and cold-heat pattern questionnaire, the Korean medicine-based tool for diagnosing and classifying health status. First, a web-based survey was conducted on 72 ordinary people; subsequently, a paper-based survey was conducted after a certain time interval. The equivalence between the web-based and paper-based surveys was evaluated on the basis of the consistency between scores using the Intraclass Correlation Coefficient (ICC) and Bland-Altman methodology. The mibyeong questionnaire showed high reliability for the web-based and paper-based surveys (ICC=0.95, 95% CI 0.92 - 0.97), and the cold-heat pattern questionnaire showed high reliability for both cold syndrome (ICC=0.98, 95% CI 0.96 - 0.99) and heat syndrome (ICC=0.9, 95% CI 0.83 - 0.93). The difference in average scores between the two survey methods was -0.25 for the mibyeong survey, -0.17 for the cold syndrome, and 0.11 for the heat syndrome, showing a similar pattern. Among the respondents, 84% showed positive satisfaction with the web-based survey, and 80% preferred the web-based survey. Overall, this study confirmed the reliability and feasibility of the web-based survey methods for the mibyeong and cold-heat pattern questionnaire. This could be a useful tool for the follow-up of subjects in long-term cohort studies.

• Journal of the Korean Society of Radiology
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• v.83 no.2
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• pp.265-283
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• 2022

To develop Korean coronavirus disease (COVID-19) chest imaging justification guidelines, eight key questions were selected and the following recommendations were made with the evidence-based clinical imaging guideline adaptation methodology. It is appropriate not to use chest imaging tests (chest radiograph or CT) for the diagnosis of COVID-19 in asymptomatic patients. If reverse transcription-polymerase chain reaction testing is not available or if results are delayed or are initially negative in the presence of symptoms suggestive of COVID-19, chest imaging tests may be considered. In addition to clinical evaluations and laboratory tests, chest imaging may be contemplated to determine hospital admission for asymptomatic or mildly symptomatic un-hospitalized patients with confirmed COVID-19. In hospitalized patients with confirmed COVID-19, chest imaging may be advised to determine or modify treatment alternatives. CT angiography may be considered if hemoptysis or pulmonary embolism is clinically suspected in a patient with confirmed COVID-19. For COVID-19 patients with improved symptoms, chest imaging is not recommended to make decisions regarding hospital discharge. For patients with functional impairment after recovery from COVID-19, chest imaging may be considered to distinguish a potentially treatable disease.

• Journal of Radiation Industry
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• v.17 no.4
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• pp.471-479
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• 2023

In In-situ radioactivity measurement techniques, efficiency calibration models use predefined models to simulate a sample's geometry and radioactivity distribution. However, simplified efficiency calibration models lead to uncertainties in the efficiency curves, which in turn affect the radioactivity concentration results. This study aims to develop an efficiency calibration optimization methodology to improve the accuracy of in-situ gamma radiation measurements for byproducts from industrial facilities. To accomplish the objective, a drive mechanism for rotational measurement of an byproduct simulator and a sample was constructed. Using ISOCS, an efficiency calibration model of the designed object was generated. Then, the sensitivity analysis of the efficiency calibration model was performed, and the efficiency curve of the efficiency calibration model was optimized using the sensitivity analysis results. Finally, the radiation concentration of the simulated subject was estimated, compared, and evaluated with the designed certification value. For the sensitivity assessment of the influencing factors of the efficiency calibration model, the ISOCS Uncertainty Estimator was used for the horizontal and vertical size and density of the measured object. The standard deviation of the measurement efficiency as a function of the longitudinal size and density of the efficiency calibration model decreased with increasing energy region. When using the optimized efficiency calibration model, the measurement efficiency using IUE was improved compared to the measurement efficiency using ISOCS at the energy of ²²⁸Ac (911 keV) for the nuclide under analysis. Using the ISOCS efficiency calibration method, the difference between the measured radiation concentration and the design value for each simulated subject measurement direction was 4.1% (1% to 10%) on average. The difference between the estimated radioactivity concentration and the design value was 3.6% (1~8%) on average when using the ISOCS IUE efficiency calibration method, which was closer to the design value than the efficiency calibration method using ISOCS. In other words, the estimated radioactivity concentration using the optimized efficiency curve was similar to the designed radioactivity concentration. The results of this study can be utilized as the main basis for the development of regulatory technologies for the treatment and disposal of waste generated during the operation, maintenance, and facility replacement of domestic byproduct generation facilities.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.105-129
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• 2020

This study uses corporate data from 2012 to 2018 when K-IFRS was applied in earnest to predict default risks. The data used in the analysis totaled 10,545 rows, consisting of 160 columns including 38 in the statement of financial position, 26 in the statement of comprehensive income, 11 in the statement of cash flows, and 76 in the index of financial ratios. Unlike most previous prior studies used the default event as the basis for learning about default risk, this study calculated default risk using the market capitalization and stock price volatility of each company based on the Merton model. Through this, it was able to solve the problem of data imbalance due to the scarcity of default events, which had been pointed out as the limitation of the existing methodology, and the problem of reflecting the difference in default risk that exists within ordinary companies. Because learning was conducted only by using corporate information available to unlisted companies, default risks of unlisted companies without stock price information can be appropriately derived. Through this, it can provide stable default risk assessment services to unlisted companies that are difficult to determine proper default risk with traditional credit rating models such as small and medium-sized companies and startups. Although there has been an active study of predicting corporate default risks using machine learning recently, model bias issues exist because most studies are making predictions based on a single model. Stable and reliable valuation methodology is required for the calculation of default risk, given that the entity's default risk information is very widely utilized in the market and the sensitivity to the difference in default risk is high. Also, Strict standards are also required for methods of calculation. The credit rating method stipulated by the Financial Services Commission in the Financial Investment Regulations calls for the preparation of evaluation methods, including verification of the adequacy of evaluation methods, in consideration of past statistical data and experiences on credit ratings and changes in future market conditions. This study allowed the reduction of individual models' bias by utilizing stacking ensemble techniques that synthesize various machine learning models. This allows us to capture complex nonlinear relationships between default risk and various corporate information and maximize the advantages of machine learning-based default risk prediction models that take less time to calculate. To calculate forecasts by sub model to be used as input data for the Stacking Ensemble model, training data were divided into seven pieces, and sub-models were trained in a divided set to produce forecasts. To compare the predictive power of the Stacking Ensemble model, Random Forest, MLP, and CNN models were trained with full training data, then the predictive power of each model was verified on the test set. The analysis showed that the Stacking Ensemble model exceeded the predictive power of the Random Forest model, which had the best performance on a single model. Next, to check for statistically significant differences between the Stacking Ensemble model and the forecasts for each individual model, the Pair between the Stacking Ensemble model and each individual model was constructed. Because the results of the Shapiro-wilk normality test also showed that all Pair did not follow normality, Using the nonparametric method wilcoxon rank sum test, we checked whether the two model forecasts that make up the Pair showed statistically significant differences. The analysis showed that the forecasts of the Staging Ensemble model showed statistically significant differences from those of the MLP model and CNN model. In addition, this study can provide a methodology that allows existing credit rating agencies to apply machine learning-based bankruptcy risk prediction methodologies, given that traditional credit rating models can also be reflected as sub-models to calculate the final default probability. Also, the Stacking Ensemble techniques proposed in this study can help design to meet the requirements of the Financial Investment Business Regulations through the combination of various sub-models. We hope that this research will be used as a resource to increase practical use by overcoming and improving the limitations of existing machine learning-based models.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.63-82
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• 2016

Individuals gather information online to resolve problems in their daily lives and make various decisions about the purchase of products or services. With the revolutionary development of information technology, Web 2.0 has allowed more people to easily generate and use online reviews such that the volume of information is rapidly increasing, and the usefulness and significance of analyzing the unstructured data have also increased. This paper presents an analysis on the lexical features of expert product reviews to determine their influence on consumers' purchasing decisions. The focus was on how unstructured data can be organized and used in diverse contexts through text mining. In addition, diverse lexical features of expert reviews of contents provided by a third-party review site were extracted and defined. Expert reviews are defined as evaluations by people who have expert knowledge about specific products or services in newspapers or magazines; this type of review is also called a critic review. Consumers who purchased products before the widespread use of the Internet were able to access expert reviews through newspapers or magazines; thus, they were not able to access many of them. Recently, however, major media also now provide online services so that people can more easily and affordably access expert reviews compared to the past. The reason why diverse reviews from experts in several fields are important is that there is an information asymmetry where some information is not shared among consumers and sellers. The information asymmetry can be resolved with information provided by third parties with expertise to consumers. Then, consumers can read expert reviews and make purchasing decisions by considering the abundant information on products or services. Therefore, expert reviews play an important role in consumers' purchasing decisions and the performance of companies across diverse industries. If the influence of qualitative data such as reviews or assessment after the purchase of products can be separately identified from the quantitative data resources, such as the actual quality of products or price, it is possible to identify which aspects of product reviews hamper or promote product sales. Previous studies have focused on the characteristics of the experts themselves, such as the expertise and credibility of sources regarding expert reviews; however, these studies did not suggest the influence of the linguistic features of experts' product reviews on consumers' overall evaluation. However, this study focused on experts' recommendations and evaluations to reveal the lexical features of expert reviews and whether such features influence consumers' overall evaluations and purchasing decisions. Real expert product reviews were analyzed based on the suggested methodology, and five lexical features of expert reviews were ultimately determined. Specifically, the "review depth" (i.e., degree of detail of the expert's product analysis), and "lack of assurance" (i.e., degree of confidence that the expert has in the evaluation) have statistically significant effects on consumers' product evaluations. In contrast, the "positive polarity" (i.e., the degree of positivity of an expert's evaluations) has an insignificant effect, while the "negative polarity" (i.e., the degree of negativity of an expert's evaluations) has a significant negative effect on consumers' product evaluations. Finally, the "social orientation" (i.e., the degree of how many social expressions experts include in their reviews) does not have a significant effect on consumers' product evaluations. In summary, the lexical properties of the product reviews were defined according to each relevant factor. Then, the influence of each linguistic factor of expert reviews on the consumers' final evaluations was tested. In addition, a test was performed on whether each linguistic factor influencing consumers' product evaluations differs depending on the lexical features. The results of these analyses should provide guidelines on how individuals process massive volumes of unstructured data depending on lexical features in various contexts and how companies can use this mechanism from their perspective. This paper provides several theoretical and practical contributions, such as the proposal of a new methodology and its application to real data.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.4
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• pp.21-30
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• 2014

Lately, new influentials have secured a large number of volunteers on social networks due to vitalization of various social media. There has been considerable research on these influential people in social networks but the research has limitations on location information of Location Based Social Network Service(LBSNS). Therefore, the purpose of this study is to propose a spatial detection methodology and application plan for influentials who make comments about diverse social and cultural issues in LBSNS using spatial statistical analysis methods. Twitter was used to collect analysis object data and 168,040 Twitter messages were collected in Seoul over a month-long period. In addition, 'politics,' 'economy,' and 'IT' were set as categories and hot issue keywords as given categories. Therefore, it was possible to come up with an exposure index for searching influentials in respect to hot issue keywords, and exposure index by administrative units of Seoul was calculated through a spatial joint operation. Moreover, an influential index that considers the spatial dependence of the exposure index was drawn to extract information on the influential areas at the top 5% of the influential index and analyze the spatial distribution characteristics and spatial correlation. The experimental results demonstrated that spatial correlation coefficient was relatively high at more than 0.3 in same categories, and correlation coefficient between politics category and economy category was also more than 0.3. On the other hand, correlation coefficient between politics category and IT category was very low at 0.18, and between economy category and IT category was also very weak at 0.15. This study has a significance for materialization of influentials from spatial information perspective, and can be usefully utilized in the field of gCRM in the future.

• Child Health Nursing Research
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• v.5 no.3
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• pp.292-304
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• 1999

The lengthened average span of human life by virtue of recent developments in medicine has caused the Population of elders to increase. The development of modern industrial society has transformed family structure from the large family system to that of a nuclear family. Due to the shift in family structure, the problem of support for the aged has surfaced as a nursing problem as well as a social problem. With regard to this problem, this study aims to investigate the adolescent's understanding of elders and aging. By identifying their understanding and classifying their attitude patterns, this study will help the nursing assessment of the support of elders in the family. This study employed Q-methodology and the research was conducted from December 1998 to May 1999. One method of the research included deep interviews with elders, those who are in their 50's. 40's or 30's. and the adolescent. 183 Q-Populations taken from literary works such as poems or novels were also formed as another method. Finally. 36 Q-cards were made after consultation with Professors of the nursing department. The subjects of the P- sample were 30 high sohoolboys/girls - who were in first, second, and third years. The result showed that 3 factors provided an explanation for 59.14% of the whole variables: the first factor, 41.37%; the second factor. 11.49%, and the third factor. 6.28%. These three factors were analyzed and categorized as three types. Twenty subjects out of the 30 were included in Type 1: Respecting Elders. The statements which showed the most positive consent were as follows: 'The declining age is a perfect time to prosper completing a worthy life' ; 'Getting old. one needs financial stability' and 'Elders wish the best for their children' The statements showing the most negative response were as follows: 'It is better to die than to live as an older person' ; 'Elders are insignificant' ; and 'Getting old is the worst unhappiness that tortures human.' Four subjects were included in Type 2. Resenting Elders. The statements which showed the most positive consent were as follows: 'Aging is a process of dying that nobody can escape from'. 'Elders should be concerned about his health and try to maintain their health' ; and 'When you set older. you regret about the life in the Past.' The statements showing the most negative response were as follows: 'When You get older. You should stand aloof greed and worldly things' 'When You got older, You become generous and gentle' ; and 'When You set he gets old. You change to become a comfortable and warm person.' Six out of 30 subject were included in Type 3 Caring Elders. The statements which showed the most positive consent were as follows: 'Elders should be concerned about his health and try to maintain their health' ; 'Elders wish the best for their children' ; and 'Elders deserve to be treated with filial respects.' The statements showing the most negative response were as follows 'Elders are insignificant' ; 'Elders have freedom and plenty of free time.' and 'Elders are alienated form and drove out of the society.' The above-mentioned results show that most adolescents in Korea recognize aging as the time of fruition and development: it is a time of benefiting and giving back to society. Aging can also be seen as a time of generosity and magnanimity and the time of respect and favorable treatment from society. despite the change of modern society and the ostensible transformation of a family system. Their recognition seems deeply rooted in the traditional confucian values and the dual family system which is Peculiar especially to the Korea - one which maintains both the superficial form of nuclear family and the substantial mode of the enlarged family system. In sum, many Korean adolescents attribute the meaning of the elderly and aging to the type of the respect with the elderly and the type of the elderly's caretaking.

• Journal of the Korean Institute of Landscape Architecture
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• v.46 no.3
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• pp.1-13
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• 2018

Landscape Architecture is a minority manpower field that requires wide knowledge and experience. Therefore, the service market is narrower than other fields, and education service for practitioners is lacking. The purpose of this study is to propose e-learning content development methodology that can provide customized landscaping practical education according to the level of education and increase the economic efficiency of the development process. First, in theoretical review, the ADDIE model was modified to select the curriculum development model that pursues efficiency and introduced the concept of reusing learning objects in the SCORM-based model. In particular, to overcome the problems presented in the precious studies, the analysis and design stages have been strengthened and faculty designers with integrated knowledge of Landscape Architecture and ICT have led the overall phase. The actual development process is based on a step by step procedure--analysis of landscaping practitioners needs and environments, etc., teaching and learning procedures and the design of activities considering contents reuse, the first development such as actual shooting and editing, and the second development reusing the first development content--and was done in the order of evaluation and revision of professionalism and satisfaction. As a result of the study, the space-based courses composed of modular learning objects were first developed as 216 courses in 8 subjects, as 208 courses in 3 subjects in total, in which the modularized learning object are crossed and combined in units and difficulty-based courses were second developed in 216 courses with 3 subjects in total. As a result of the evaluation the satisfaction assessment of the overall satisfaction was 4.20 and the average value of the eight measures was 3.97, both being close to 4.0. For the professional assessment, the scores of 8 subjects were very high at 84.8 to 96.4 points. in context, the scores of 5 subjects were equal to from 89.9 to 96.4 points. In conclusion, as the study was conducted based on a clear understanding of the digital characteristics of e-learning contents and general characteristic of the landscaping industry, it was possible to develop a curriculum by developing a course composed of modular learning objects and reusing learning objects by unit. In particular, it has been proven to be effective in conveying professional knowledge and experiences via general procedures and provided an opportunity to overcome some analog problems that may occur in offline education. In the future, further studies need to be done by expanding the content and by focusing on segmented subjects.

• Journal of Korean Society of Environmental Engineers
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• v.38 no.11
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• pp.611-617
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• 2016

Remanufacturing that is the rebuilding of a product to specifications of the original manufactured product by collecting used-product, completely disassembling, cleaning and repairing or replacing with a new part and reassembling has been received attention in aspects of resource, recycling because it is a great environmental improvement. Remanufacturing is the rebuilding of a product to specifications of the original manufactured product by collecting used-product, completely disassembling, cleaning and repairing or replacing with a new part and reassembling. With a great environmental improvement and resource recycling and conservation, many studies were conducted. Up to date, remanufacturing activities are mainly applied to automobile parts and printer toner cartridge in South Korea. However, remanufacturing of rental product is not well conducted although rental products are collected in good condition and could be remanufactured in the same condition as a new product. Therefore, in this study, we conducted life cycle assessment (LCA) to an air cleaner product that is one of rental products. This study attempts to identify the processes in new products and remanufacturing life cycles that contribute the most environmental impacts. The results show that air cleaner remanufacturing could reduce about 20% of environmental impacts compared to new product. The greatest benefit related to environmental impact is with regard to ozone layer depletion potential (ODP), which is reduced by 94%. In the life cycle of air cleaner, raw material extraction stage had the most environmental impacts, especially with regard to abiotic depletion potential (ADP) and global warming potential (GWP). In the environmental impacts in each part, the ABS power had the highest environmental impacts.