• Computers and Concrete
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• v.33 no.1
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• pp.55-75
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• 2024

The present study introduces an optimum performance soft computing model for predicting the compressive strength of high-performance concrete (HPC) by comparing models based on conventional (kernel-based, covariance function-based, and tree-based), advanced machine (least square support vector machine-LSSVM and minimax probability machine regressor-MPMR), and deep (artificial neural network-ANN) learning approaches using a common database for the first time. A compressive strength database, having results of 1030 concrete samples, has been compiled from the literature and preprocessed. For the purpose of training, testing, and validation of soft computing models, 803, 101, and 101 data points have been selected arbitrarily from preprocessed data points, i.e., 1005. Thirteen performance metrics, including three new metrics, i.e., a20-index, index of agreement, and index of scatter, have been implemented for each model. The performance comparison reveals that the SVM (kernel-based), ET (tree-based), MPMR (advanced), and ANN (deep) models have achieved higher performance in predicting the compressive strength of HPC. From the overall analysis of performance, accuracy, Taylor plot, accuracy metric, regression error characteristics curve, Anderson-Darling, Wilcoxon, Uncertainty, and reliability, it has been observed that model CS4 based on the ensemble tree has been recognized as an optimum performance model with higher performance, i.e., a correlation coefficient of 0.9352, root mean square error of 5.76 MPa, and mean absolute error of 4.1069 MPa. The present study also reveals that multicollinearity affects the prediction accuracy of Gaussian process regression, decision tree, multilinear regression, and adaptive boosting regressor models, novel research in compressive strength prediction of HPC. The cosine sensitivity analysis reveals that the prediction of compressive strength of HPC is highly affected by cement content, fine aggregate, coarse aggregate, and water content.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.1
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• pp.49-63
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• 2016

In this study, we analyzed the effects of regional hydrologic variability during warm season (June-September) in South Korea due to ENSO (El $Ni{\tilde{n}}o$-Southern Oscillation) pattern changes over the Tropical Pacific Ocean (TPO). We performed composite analysis (CA) and statistical significance test by Student's t-test using observed hydrologic data (such as, precipitation and streamflow) in the 113 sub-watershed areas over the 5-Major River basin, in South Korea. As a result of this study, during the warm-pool (WP) El $Ni{\tilde{n}}o$ year shows a significant increasing tendency than normal years. Particularly, during the cold-tongue (CT) El $Ni{\tilde{n}}o$ decaying years clearly decreasing tendency compared to the normal years was appeared. In addition, the La $Ni{\tilde{n}}a$ years tended to show a slightly increasing tendency and maintain the average year state. In addition, from the result of scatter plot of the percentage anomaly of hydrologic variables during warm season, it is possible to identify the linear increasing tendency. Also the center of the scatter plot shows during the WP El $Ni{\tilde{n}}o$ year (+17.93%, +26.99%), the CT El $Ni{\tilde{n}}a$ year (-8.20%, -15.73%), and the La $Ni{\tilde{n}}a$ year (+8.89%, +15.85%), respectively. This result shows a methodology of the tele-connection based long-range water resources prediction for reducing climate forecasting uncertainty, when occurs the abnormal SSTA (such as, El $Ni{\tilde{n}}o$ and La $Ni{\tilde{n}}a$) phenomenon in the TPO region. Furthermore, it can be a useful data for water managers and end-users to support long-range water-related policy making.

• The Journal of Korean Society for Radiation Therapy
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• v.23 no.2
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• pp.91-96
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• 2011

Purpose: The aim of study is to expose a more uniform dose depending on the relationship between a body mass index in patients who underwent radiation therapy and an acquired dosimetric information by using a thermoluminescent dosimeter. Materials and Methods: Since 2006 to August 2011 we investigated 28 people who underwent radiation therapy were enrolled in AMC. Each patient was measured on the head, neck, chest, abdomen, pelvis, thigh, knee joint, and ankle joint using the thermoluminescent dosimeter. The measurement value of each points compared with the prescribed center point, abdominal point, and dose measurements of points on which to base the abdomen and the patient's body mass index (BMI) were compared with reference point, abdomen dose. Results: 28 patients on prescribed dose in the abdomen by which the center point, an average dose was $100.6{\pm}5.5%$, and the other seven measuring points with the average maximum difference among the head, neck, chest, pelvic, thigh, knee, and ankle were $92.8{\pm}4.2%$, $97.6{\pm}6.2%$, $96.4{\pm}5.5%$, $102.6{\pm}5.3%$, $103.4{\pm}7.9%$, $95.8{\pm}5.9%$, $96.1{\pm}5.5%$. The relationship of abdominal point dose and the patient's body mass index (BMI) was analyzed a scatter plot, and the result of linear relationship analysis by regression method, the regression of the dose (y) was -1.009 BMI (x) plus 123.3 and coefficient of determination ($R^2$) was represented 0.697. Conclusion: The total body irradiation treatment process was evaluated the dose deviation and then the prescribed dose by which the average abdominal dose was satisfied with $100.6{\pm}5.5%$. Results of the relationship analysis between BMI and dose, if we apply the correction value for each patients, it can be achieved more uniform dose delivery.

• Journal of The Korean Society of Grassland and Forage Science
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• v.38 no.1
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• pp.53-60
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• 2018

Yield prediction model for mixed pasture was developed with a shortage that the relationship between dry matter yield (DMY) and days of summer depression (DSD) was not properly reflected in the model in the previous research. Therefore, this study was designed to eliminate the data of the regions with distinctly different climatic conditions and then investigate their relationships DMY and DSD using the data in each region separately of regions with distinct climatic characteristics and classify the data based on regions for further analysis based on the previous mixed pasture prediction model. The data set used in the research kept 582 data points from 11 regions and 41 mixed pasture types. The relationship between DMY and DSD in each region were analyzed through scatter plot, correlation analysis and multiple regression analysis in each region separately. In the statistical analysis, DMY was taken as the response variable and 5 climatic variables including DSD were taken as explanatory variables. The results of scatter plot showed that negative correlations between DMY and DSD were observed in 7 out of 9 regions. Therefore, it was confirmed that analyzing the relationship between DMY and DSD based on each region is necessary and 5 regions were selected (Hwaseong, Suwon, Daejeon, Siheung and Gwangju) since the data size in these regions is large enough to perform the further statistical analysis based on large sample approximation theory. Correlation analysis showed that negative correlations were found between DMY and DSD in 3 (Hwaseong, Suwon and Siheung) out of the 5 regions, meanwhile the negative relationship in Hwaseong was confirmed through multiple regression analysis. Therefore, it was concluded that the interpretability of the yield prediction model for mixed pasture could be improved based on constructing the models using the data from each region separately instead of using the pooled data from different regions.

• Journal of the Korean Society of Radiology
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• v.15 no.5
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• pp.591-602
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• 2021

Acute ischemic stroke(AIS) should be diagnosed within a few hours of onset of cerebral infarction symptoms using diagnostic radiology. In this study, we evaluated the clinical usefulness of SVD and the Bayesian algorithm to measure the volume of cerebral infarction using computed tomography perfusion(CTP) imaging and magnetic resonance diffusion-weighted imaging(MR DWI). We retrospectively included 50 patients (male : female = 33 : 17) who visited the emergency department with symptoms of AIS from September 2017 to September 2020. The cerebral infarct volume measured by SVD and the Bayesian algorithm was analyzed using the Wilcoxon signed rank test and expressed as a median value and an interquartile range of 25 - 75 %. The core volume measured by SVD and the Bayesian algorithm using was CTP imaging was 18.07 (7.76 - 33.98) cc and 47.3 (23.76 - 79.11) cc, respectively, while the penumbra volume was 140.24 (117.8 - 176.89) cc and 105.05 (72.52 - 141.98) cc, respectively. The mismatch ratio was 7.56 % (4.36 - 15.26 %) and 2.08 % (1.68 - 2.77 %) for SVD and the Bayesian algorithm, respectively, and all the measured values had statistically significant differences (p < 0.05). Spearman's correlation analysis showed that the correlation coefficient of the cerebral infarct volume measured by the Bayesian algorithm using CTP imaging and MR DWI was higher than that of the cerebral infarct volume measured by SVD using CTP imaging and MR DWI (r = 0.915 vs. r = 0.763 ; p < 0.01). Furthermore, the results of the Bland Altman plot analysis demonstrated that the slope of the scatter plot of the cerebral infarct volume measured by the Bayesian algorithm using CTP imaging and MR DWI was more steady than that of the cerebral infarct volume measured by SVD using CTP imaging and MR DWI (y = -0.065 vs. y = -0.749), indicating that the Bayesian algorithm was more reliable than SVD. In conclusion, the Bayesian algorithm is more accurate than SVD in measuring cerebral infarct volume. Therefore, it can be useful in clinical utility.

• Analytical Science and Technology
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• v.27 no.1
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• pp.66-77
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• 2014

This study was carried out to examine the authenticity discrimination of circulated vegetable oils by using carbon isotope ratio (${\delta}^{13}C$) and fatty acid composition. This analysis was applied to vegetable oils which we can buy in Korean markets, and the analytical instrument was measured by using EA-IR/MS for ${\delta}^{13}C$ and GC/FID for fatty acid composition. ${\delta}^{13}C$ was separated into 3 groups as $C_3$ plant including sesame oil, $C_4$ plant including maize oil, and rice bran oil. Fatty acid composition was significantly different among vegetable oils. In addition, the interval of low and high price vegetable oils was classified through the scatter plot analysis showing the correlation of the ${\delta}^{13}C$ and fatty acid composition. Therefore, through a simultaneous determination of the ${\delta}^{13}C$ and fatty acid composition, we are able to determine the majority of vegetable oils. It help to ensure food safety in Korean market by exclusion of economically modified adulteration in food.

• The Journal of the Korea Contents Association
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• v.20 no.4
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• pp.273-283
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• 2020

The purpose of this study is to evaluate the user's evaluation of the street environment for the Urban Regeneration New Deal project, which maintains its original urban context and improves the urban environment, as opposed to the full-demolition projects such as urban redevelopment or reconstruction. A questionary survey was conducted on residents for the general neighborhood type of Urban Regeneration New Deal projects in Daegu. An IPA(Importance-Performance Analysis) was conducted to compare the user's satisfaction with the street environments. The main results are as follows. First, the importance and satisfaction of street environments were different for each project. Second, the cleanliness of sidewalks showed high importance and satisfaction at all projects. Third, residents' satisfaction with signs and buildings was high, but their importance was low. Last, residents' satisfaction with parking and the segregation of pedestrian and vehicle was low, but their importance was high. It is necessary to build differentiated plans and programs to meet the needs of residents in the Urban Regeneration New Deal projects.

• Korean Journal of Ecology and Environment
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• v.45 no.3
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• pp.302-313
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• 2012

Long-term trends (e.g. 1997~2010) of chlorophyll a and water quality properties of the Yeongsan River were analyzed by using water quality monitoring data collected by the water information system, ministry of environment. Nine monitoring stations were selected along the main channel of the river, and parameters of BOD, COD, TN, TP, conductivity, TSS and chlorophyll a were collected for surface water monthly through the monitoring system. Trends of water quality and chlorophyll a were analyzed by the Seasonal Mann-Kendall Test and LOWESS (Locally Weighted Scatter-plot Smoother). The results showed that the water quality parameters, including chlorophyll a, were improved in all stations except Station WC in the most-upper region, where water quality data for the determined parameters were increased, indicating a reduction in water quality. Based on the results from LOWESS analysis, chlorophyll a (algal blooms), BOD and COD recently began to increase after 2007 suggesting that an additional study on the cause of these increases in organic pollution, as well as a better management system for the region are required.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.3
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• pp.162-175
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• 2018

The purpose of this study was to analyze the surface temperature of surface fabrics using UAV TIR images, to mitigate problems in the thermal environment of urban areas. Surface temperature values derived from UAV images were compared with those measured in-situ during the similar period as when the images were taken. The difference in the in-situ measured and UAV image derived surface temperatures is the highest for gray colored concrete roof fabrics, at $17^{\circ}C$, and urethane fabrics show the lowest difference, at $0.3^{\circ}C$. The experiment power of the scatter plot of in-situ measured and UAV image derived surface temperatures was 63.75%, indicating that the correlation between the two is high. The surface fabrics with high temperature are metal roofs($48.9^{\circ}C$), urethane($43.4^{\circ}C$), and gray colored concrete roofs($42.9^{\circ}C$), and those with low temperature are barren land($30.2^{\circ}C$), area with trees and lawns($30.2^{\circ}C$), and white colored concrete roofs($34.9^{\circ}C$). These results show that accurate analysis of the thermal characteristics of surface fabrics is possible using UAV images. In future, it will be necessary to increase the usability of UAV images via comparison with in-situ data and linkage to satellite imagery.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.8
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• pp.4583-4589
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• 2013

Objective: This study aimed to investigate the effect of multimodality treatment of advanced paediatric hepatoblastoma (HB) and the factors affecting prognosis. Methods: A total of 35 children underwent multimodality treatments consisting of chemotherapy, surgery, interventional therapy, and autologous peripheral blood stem cell transplantation. The patients were followed up every month. Results: Serum AFP levels in 33 out of 35 patients in this study were significantly increased (P = 0.0002). According to the statistical scatter plot, the values of serum AFP on the 25th, 50th, and 75th percentages were 1,210, 1,210 and 28,318 ng/dl, respectively. Of the 35 cases, 21 were stage IV. 18 cases were treated with systemic chemotherapy before surgery, and 3 cases with locally interventional chemotherapy before surgery. Statistical analysis showed that the preferred interventional treatment affected prognosis, and that there was a statistically significant difference (P = 0.024). Some 33 patients completed the follow-up, of which 17 were in complete remission (CR), 5 were in partial remission (PR), 1 became disease progressive (DP), and 10 died. The remission and overall survival rates were 66.7% (22/33) and 69.7% (23/33), respectively. Patients with the mixed HB phenotypes had worse prognoses than the epithelial phenotype (P < 0.001), and patients in stage IV had a lower survival rate than those in stage III (P < 0.001). Conclusion: Multimodality treatment can effectively improve remission rate and prolong the survival of children with advanced HB. In addition, alpha-fetoprotein (AFP), a tumor marker of liver malignant tumors, HB pathological classification, and staging are highly useful in predicting prognosis.