• Journal of the Korea Concrete Institute
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• v.24 no.3
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• pp.333-340
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• 2012

The current study prepared 9 laboratorial concrete mixes and 3 ready-mixed concrete batches to examine the size and shape effects in compression failure of lightweight aggregate concrete (LWC). The concrete mixes were classified into three groups: normal-weight, all-lightweight and sand-lightweight concrete groups. For each concrete mix, the aspect ratio of circular or square specimens was 1.0 and 2.0. The lateral dimension of specimens varied between 50 and 150 mm for each laboratorial concrete mix, whereas it ranged from 50 to 400 mm with an incremental variation of 50 mm for each ready-mixed concrete batch. Test observations revealed that the crack propagation and width of the localized failure zone developed in lightweight concrete specimens were considerably different than those of normal-weight concrete (NWC). In LWC specimens, the cracks mainly passed through the coarse aggregate particles and the crack distribution performance was very poor. As a result, a stronger size effect was developed in LWC than in NWC. Especially, this trend was more notable in specimens with aspect ratio of 2.0 than in specimens with that of 1.0. The prediction model derived by Kim et al. overestimated the size effect of LWC when lateral dimension of specimen is above 150 mm. On the other hand, the modification factors specified in ASTM and CEB-FIP provisions, which are used to compensate for the shape effect of specimen on compressive strength, were still conservative in LWC.

• Journal of the Korean Geographical Society
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• v.48 no.2
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• pp.272-287
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• 2013

This paper describes the importance of selecting explanatory variables(e.g. land price determinants) in hedonic pricing models employed in predicting real estate price, and explores dynamics of the land price determinants over time. The City of Junju was chosen as the study area, and repeated measured price data of standard lots over 17 years were analyzed. We applied a three-level modeling approach to this data in consideration of its nested data structure and longitudinal characteristics. Main land price determinants we focused on are primarily based on items included in the standard comparison table of land price, which is an official hedonic pricing model used by Government to estimate land price for tax levy. Our result shows that the land price fluctuation over 17 years was not uniform over the whole study area with each neighborhood revealing different price trend, and as such warrants longitudinal model components. In addition, some of determinants previously recognized as important were proved insignificant. It was also found that significant determinants at a particular time point lost its power gradually over time and vice versa. It is expected that more accurate prediction of price would be possible when taken account for this dynamics of price determinants over time in applying hedonic pricing model method.

• Plant Journal
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• v.10 no.2
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• pp.28-37
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• 2014

Recently, it is considered that environment and energy are critical issues all over the world. In power generation sector in Korea, almost power stations are constructed and operated as cogeneration plants in conformity with this trend. KDHC(Korea District Heating Corporation) goes one step further adopting renewable energy technology like heat pump using wasted heat for energy-saving and environment improvement. This study investigates the performance characteristics by the location of waste heat recovery heat pumps of 5 Gcal/h capacity in 150 MW-class Gwang-gyo cogeneration plant using commercial software 'THERMOFLEX'. Prior to analysis, the simulations are performed with actual operation data, and then the validation of simulations is verified by checking the error within 2%. After verification, the simulations are carried out with 3 locations and the effect on electrical power output and heat output is analyzed. As a result, overall efficiency of cogeneration plant is the highest in the case of heat pump located before DH(District Heating) Heater because of the largest increase of heat output despite of decrease of electrical power output.

• Journal of Korea Water Resources Association
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• v.41 no.10
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• pp.995-1007
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• 2008

Studies on modeling the rainfall-runoff relationship which shows nonlinear trend strongly use artificial neural networks theory not only for the prediction but also for the characteristics analysis of the data used by pattern classification. For the pattern classification, the results from Self-Organizing Map (SOM) mention that the map size and array for the SOM training have significantly influenced on the SOM performance. Since there is no deterministic method or theoretical equation to determine the number of rows and columns for the map size, hexagonal array is generally used for the map array. Therefore, this study present a determination of the optimized map structure for the rainfall-runoff analysis in Naju station considering the map size and array simultaneously which can represent the classified characterization of rainfall-runoff relationship. The result showed that the map size of 20$\times$16 hexagonal array with 8-clustered patterns was selected as an appropriate map structure for rainfall-runoff analysis in Naju station.

• Journal of Preventive Medicine and Public Health
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• v.22 no.3 s.27
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• pp.313-322
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• 1989

The present status of the traffic accident rate in Korea shows that it is the highest in the world with a continuously increasing trend. Human factors account for 90% of the causes of traffic accidents. Therefore, the purpose of this study was to determine some human factors related to traffic accidents by studying the relationship between health status and traffic accidents. To accomplish this purpose, all taxi companies located in the Seoul area were divided in three groups according to the number of taxi possessed, then some companies in each ?roup were randomly selected for study, and a total of 222 drivers in those selected companies were questioned and examined from April 15 to April 22, 1989. Seventy drivers among 222 had experienced a traffic accident. A $x^2$-test was performed on the data, then, factor analysis and discrminant analysis were executed with the following results: 1. The drivers complaining of gastroenteric symptoms numbered 110(49.5%), which was the major symptom among all drivers complaining of poor health. 2. In the primary analysis, variables related to traffic accidents were divided into general, occupational, and health characteristics. Drivers having no traffic accident experience and drivers having that experience were subjected to question about age, educational level, residential status, monthly average income, working hours and days, degree of satisfaction with their profession and homelife, degree of worry about health. degree of fatigue, medication, drunken driving, and illness, but there were no statistical significances. 3. In the factor analysis, the 8 health variables which cause traffic accidents were classified into 3 common factors which were perceived health factor, sleeping and drunken driving, and visual acuity and smoking factor. Perceived health was the factor which contributed most to explaining accidents. 4. In the discriminant analysis, a correct prediction rate of 68.0% was obtained in the factors of all the characteristics. 5. Degree of sttisfaction with their homelife and educational and economic factor in the general characteristics, degree of satisfaction with their profession in the occupational characteristics, and sleeping and drunken driving in the health characteristics were selected as statistically significant factors to discriminant the traffic accident. 6. Among the factors of the general, occupational, and health characteristics, degree of satisfaction with their homelife, driving experience, family factor, perceived factor were selected as the statistically significant factors.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.4
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• pp.284-288
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• 2009

With explosively growing PPI databases, the computational approach for a prediction and configuration of PPI network has been a big stream in the bioinformatics area. Recent researches gradually consider physicochemical properties of proteins and support high resolution results with integration of experimental results. With regard to current research trend, it is very close future to complete a PPI network configuration of each organism. However, direct applying the PPI network to real field is complicated problem because PPI network is only a set of co-expressive proteins or gene products, and its network link means simple physical binding rather than in-depth knowledge of biological process. In this paper, we suggest a protein functional flow model which is a directed network based on a protein functions' relation of signaling transduction pathway. The vertex of the suggested model is a molecular function annotated by gene ontology, and the relations among the vertex are considered as edges. Thus, it is easy to trace a specific function's transition, and it can be a constraint to extract a meaningful sub-path from whole PPI network. To evaluate the model, 11 functional flow models of Homo sapiens were built from KEGG, and Cronbach's alpha values were measured (alpha=0.67). Among 1023 functional flows, 765 functional flows showed 0.6 or higher alpha values.

• Journal of Korean Neurosurgical Society
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• v.30 no.7
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• pp.861-869
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• 2001

Objective : In this study, we investigated the relationship between the histologic grading of meningiomas and proliferative potentials determined by the Ki-67, proliferating cell nuclear antigen(PCNA) and flow cytometry (FCM) with the aim of determining whether these potentials can be used as a parameter to the proliferative activity, in particular of atypical and malignant meningiomas. Methods : This study consisted of 47 meningiomas(6 malignant, 14 atypical, and random sampled 27 benign meningiomas). By immunohistochemical staining of Ki-67 and PCNA on formalin-fixed, paraffin-embedded sections, the anti-human rabbit polyclonal antibody against Ki-67 antigen and anti-PCNA monoclonal antibody(PC10) scores were counted. FCM was also performed on paraffin-embedded tissue using a selective staining technique for DNA. DNA ploidy, S-phase fraction, and proliferative index(PI)) were determined. Results : The results are summarized as follows ; 1) Proliferation rates as assessed by Ki-67 and PCNA closely correlated with the degree of anaplastic histologic features. 2) Proliferative potentials determined by FCM(S-phase fraction and PI) were not able to distinguish between benign and atypical/malignant meningiomas. 3) DNA ploidy was not a useful indicator of histologic grade in these tumors. 4) Proliferative potentials such as Ki-67 staining index(SI) and PCNA SI did not correlate with the ploidy pattern. 5) There was a linear correlation between Ki-67 SI and PCNA SI, but we could not find a correlation between Ki-67 SI and S-phase fraction or PI. Our results also did not show a statistically signficant correlation between PCNA SI and S-phse fraction or PI. Conclusions : We conclude that evaluation of the proliferative potentials with Ki-67 and PCNA is important as an additional factor for the prediction of malignancy in meningiomas. A dual study of Ki-67 and PCNA SIs on the same tissue might improve the accuracy with which the proliferative potential of a tumor can be predicted. We demonstrated that FCM in meningiomas is not valuable in predicting the behavior of these neoplasms, but we did observe a trend toward more malignancy with higher percent S-phase fraction and higher PI. Analysis of the S-phase fraction and PI might therefore be a useful tool to discriminate among histologic grades of meningiomas.

• Journal of the Korean GEO-environmental Society
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• v.22 no.11
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• pp.5-13
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• 2021

The interest of expecting the liquefaction damage is increasing due to the liquefaction in Pohang in 2017. Liquefaction is defined as a phenomenon that the ground can not support the superstructure due to loss of the strength of the ground. As an alternative against this, many studies are being conducted to increase the precision and to compose a liquefaction hazard map for the purpose of identifying the scale of liquefaction damage using the liquefaction potential index (LPI). In this research, in order to analyze the degree of precision with regard to spatial interpolation objects such as LPI value and geotechnical information for LPI determination, liquefaction hazard map were made for the target area. Furthermore, based on the trend of precision, probability value was analyzed using probability maps prepared through qualitative characteristics. Based on the analysis results, the precision of the liquefaction hazard map setting the spatial interpolation object as geotechnical information is higher than that as LPI value. Furthermore, the precision of the liquefaction hazard map does not affect the distribution of the probability value.

• The Journal of Bigdata
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• v.6 no.1
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• pp.91-113
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• 2021

Despite the influence of real estate in the Korean asset market, it is not easy to predict market trends, and among them, apartments are not easy to predict because they are both residential spaces and contain investment properties. Factors affecting apartment prices vary and regional characteristics should also be considered. This study was conducted to compare the factors and characteristics that affect apartment prices in Seoul as a whole, 3 Gangnam districts, Nowon, Dobong, Gangbuk, Geumcheon, Gwanak and Guro districts and to understand the possibility of price prediction based on this. The analysis used machine learning algorithms such as neural networks, CHAID, linear regression, and random forests. The most important factor affecting the average selling price of all apartments in Seoul was the government's policy element, and easing policies such as easing transaction regulations and easing financial regulations were highly influential. In the case of the three Gangnam districts, the policy influence was low, and in the case of Gangnam-gu District, housing supply was the most important factor. On the other hand, 6 mid-lower-level districts saw government policies act as important variables and were commonly influenced by financial regulatory policies.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.8
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• pp.331-343
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• 2019

The purpose of this study is to observe the trends of heart age of Koreans by using the predictor of heart age of the Framingham Heart Study. The subjects were 20,012 adults aged 30~74 years who were enrolled in the Korean National Health and Nutrition Examination Survey from 2005~2013. They filled in the determinants data and they had no history of cardiovascular disease (CVD). The heart age was calculated using a non-laboratory based model of prediction. The difference of heart age and chronological age, and the rate of excessive heart age over 10 years were calculated. The annual trend, the difference according to gender, the age bracket and geographic region, the heart age were all evaluated. Data analysis performed using the SAS program (version 9.3). Complex designed analysis was done. The heart age showed differences according to gender, age bracket and geographic region. The heart age is a useful comprehensive indicator for predicting the CVD events in the near future. So, it could be used for the purposes of exercising caution and guidance on CVD for administering medical care. It is strongly recommended to use heart age as an indicator for customized medical management to focus efforts on relatively vulnerable subjects and their factors for CVD. Further study on Koreans' customized heart age is needed.