• Computers and Concrete
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• v.20 no.1
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• pp.31-38
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• 2017

In the present study an Artificial Neural Network (ANN) was used to predict the compressive strength of self-compacting concrete. The data developed experimentally for self-compacting concrete and the data sets of a total of 99 concrete samples were used in this work. ANN's are considered as nonlinear statistical data modeling tools where complex relationships between inputs and outputs are modeled or patterns are found. In the present ANN model, eight input parameters are used to predict the compressive strength of self-compacting of concrete. These include varying amounts of cement, coarse aggregate, fine aggregate, fly ash, fiber, water, super plasticizer (SP), viscosity modifying admixture (VMA) while the single output parameter is the compressive strength of concrete. The importance of different input parameters for predicting the strengths at various ages using neural network was discussed in the study. There is a perfect correlation between the experimental and prediction of the compressive strength of SCC based on ANN with very low root mean square errors. Also, the efficiency of ANN model is better compared to the multivariable regression analysis (MRA). Hence it can be concluded that the ANN model has more potential compared to MRA model in developing an optimum mix proportion for predicting the compressive strength of concrete without much loss of material and time.

• Computers and Concrete
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• v.19 no.5
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• pp.457-465
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• 2017

The Taiwanese liquid crystal display (LCD) industry has traditionally produced a huge amount of waste glass that is placed in landfills. Waste glass recycling can reduce the material costs of concrete and promote sustainable environmental protection activities. Concrete is always utilized as structural material; thus, the concrete compressive strength with a variety of mixtures must be studied using predictive models to achieve more precise results. To create an efficient waste LCD glass concrete (WLGC) design proportion, the related studies utilized a multivariable regression analysis to develop a compressive strength waste LCD glass concrete equation. The mix design proportion for waste LCD glass and the compressive strength relationship is complex and nonlinear. This results in a prediction weakness for the multivariable regression model during the initial growing phase of the compressive strength of waste LCD glass concrete. Thus, the R ratio for the predictive multivariable regression model is 0.96. Neural networks (NN) have a superior ability to handle nonlinear relationships between multiple variables by incorporating supervised learning. This study developed a multivariable prediction model for the determination of waste LCD glass concrete compressive strength by analyzing a series of laboratory test results and utilizing a neural network algorithm that was obtained in a related prior study. The current study also trained the prediction model for the compressive strength of waste LCD glass by calculating the effects of several types of factor combinations, such as the different number of input variables and the relevant filter for input variables. These types of factor combinations have been adjusted to enhance the predictive ability based on the training mechanism of the NN and the characteristics of waste LCD glass concrete. The selection priority of the input variable strategy is that evaluating relevance is better than adding dimensions for the NN prediction of the compressive strength of WLGC. The prediction ability of the model is examined using test results from the same data pool. The R ratio was determined to be approximately 0.996. Using the appropriate input variables from neural networks, the model validation results indicated that the model prediction attains greater accuracy than the multivariable regression model during the initial growing phase of compressive strength. Therefore, the neural-based predictive model for compressive strength promotes the application of waste LCD glass concrete.

• Journal of Biomedical Engineering Research
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• v.27 no.6
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• pp.301-309
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• 2006

The main purpose of this study is to derive a regression equation that predicts the individual differences in activity energy expenditure (AEE) using accelerometer during different types of activity. Two subject groups were recruited separately in time: One is a homogeneous group of 94 healthy young adults with age ranged from $20\sim35$ yrs. The other subject group has a broad spectrum of physical characteristics in terms of age and fat ratio. 226 adolescents and adults of age ranged from $12\sim57$ yrs and fat ratio from $4.1\sim39.7%$ were in the second group. The wireless 3-axis accelerometers were developed and carefully fixed at the waist belt level. Simultaneously the total calorie expenditure was measured by gas analyzer. Each subject performed walking and running at speeds of 1.5, 3.0, 4.5, 6.0, 6.5, 7.5, and 8.5 km/hr. A generalized sensor-independent regression equation for AEE was derived. The regression equation was developed fur walking and running. The regression coefficients were predicted as functions of physical factors-age, gender, height, and weight with multivariable regression analysis. The generalized calorie estimation equation predicts AEE with correlation coefficient of 0.96 and the average accuracy of the accumulated calorie was $89.6{\pm}7.9%$.

• Korean Journal of Radiology
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• v.25 no.9
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• pp.788-797
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• 2024

Objective: To investigate the potential association among preoperative breast MRI features, axillary nodal burden (ANB), and disease-free survival (DFS) in patients with early-stage breast cancer. Materials and Methods: We retrospectively reviewed 297 patients with early-stage breast cancer (cT1-2N0M0) who underwent preoperative MRI between December 2016 and December 2018. Based on the number of positive axillary lymph nodes (LNs) determined by postoperative pathology, the patients were divided into high nodal burden (HNB; ≥3 positive LNs) and non-HNB (<3 positive LNs) groups. Univariable and multivariable logistic regression analyses were performed to identify independent risk factors associated with ANB. Predictive efficacy was evaluated using the receiver operating characteristic (ROC) curve and area under the curve (AUC). Univariable and multivariable Cox proportional hazards regression analyses were performed to determine preoperative features associated with DFS. Results: We included 47 and 250 patients in the HNB and non-HNB groups, respectively. Multivariable logistic regression analysis revealed that multifocality/multicentricity (adjusted odds ratio [OR] = 3.905, 95% confidence interval [CI]: 1.685-9.051, P = 0.001) and peritumoral edema (adjusted OR = 3.734, 95% CI: 1.644-8.479, P = 0.002) were independent risk factors for HNB. Combined peritumoral edema and ultifocality/multicentricity achieved an AUC of 0.760 (95% CI: 0.707-0.807) for predicting HNB, with a sensitivity and specificity of 83.0% and 63.2%, respectively. During the median follow-up period of 45 months (range, 5-61 months), 26 cases (8.75%) of breast cancer recurrence were observed. Multivariable Cox proportional hazards regression analysis indicated that younger age (adjusted hazard ratio [HR] = 3.166, 95% CI: 1.200-8.352, P = 0.021), larger tumor size (adjusted HR = 4.370, 95% CI: 1.671-11.428, P = 0.002), and multifocality/multicentricity (adjusted HR = 5.059, 95% CI: 2.166-11.818, P < 0.001) were independently associated with DFS. Conclusion: Preoperative breast MRI features may be associated with ANB and DFS in patients with early-stage breast cancer.

• Journal of Environmental Health Sciences
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• v.47 no.1
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• pp.87-100
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• 2021

Objectives: The purpose of this study was to analyze the factors affecting Bisphenol A (BPA) exposure in children and adolescents using the results of the Korean National Environmental Health Survey (KoNEHS) cycle 3. Methods: A total of 2,380 subjects (n=571, 887, and 922 for 3-5, 6-11, and 12-17 years of age, respectively) were analyzed using an environmental exposure survey and environmental chemical substances concentration levels. Univariable linear regression analysis was performed to determine associated variables such as sex, age, income level, housing type, secondhand smoke time, cup noodles and canned food consumption, seafood consumption, new furniture (within the previous six months), drinking water type, and consumption of herbal medicines. Variables with p-values of less than 0.2 were extracted from the results and a multivariable linear regression analysis was performed using stepwise selection. Results: Univariable linear regression analysis showed positive associations between BPA concentration levels and variables including sex, age, secondhand smoke time, new furniture (within the previous six months), renovated living space (within the previous six months), fish and shellfish consumption, plastic-bottled drink consumption, and herbal medicine. As a result of performing multivariable linear regression analysis, the lower was the age the higher was the concentration of BPA levels. Additionally, women showed higher BPA levels than those of men. The more frequently fish was consumed, the higher was the BPA concentration. Moreover, higher BPA concentrations were observed when taking herbal medicine. Conclusions: The main factors affecting BPA concentration levels were age, gender, and consumption of fish and herbal medicine.

• Journal of Korean society of Dental Hygiene
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• v.21 no.2
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• pp.129-140
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• 2021

Objectives: We sought to evaluate the mitigating effect of using floss and interdental brushes on periodontal health inequality. Methods: This study was based on data acquired from the Seventh Korea National Health and Nutrition Examination Survey (KNHANES VII; 2016-2018). We included 11,359 participants aged ≥19 years in the final analysis. Multivariable logistic regression analysis was performed using socioeconomic characteristics, health behavior, health status, and periodontitis status. We analyzed differences in the prevalence of periodontitis according to household income stratified by the use of floss and interdental brush. Results: In the multivariable logistic regression model, the lowest income group had 1.304 (95% confidence interval [CI] 1.08-1.58) odds ratios for periodontitis than the highest income group. In the interdental brush nonusers or floss nonusers, the lowest income group had significantly higher odds of developing periodontitis. However, we found no significant differences in the periodontitis prevalence between the income groups among the interdental brush users. In the 65-year-old or older group, the same result was observed in the interdental brush and floss users. Conclusions: The results suggest that the use of floss and interdental brushes could alleviate periodontal health inequality.

• Journal of Medicine and Life Science
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• v.19 no.2
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• pp.39-45
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• 2022

This study was undertaken to assess the potential of body mass index (BMI) as a risk factor for massive hemorrhage (MH) after cesarean section (CS) in patients with placenta previa. We retrospectively reviewed the medical records of patients who underwent CS for placenta previa between January 2010 and December 2018. MH was defined as an estimated blood loss ≥2,000 mL during surgery. Clinical characteristics, including BMI, were compared between the groups with and without MH. Subsequently, multivariable logistic regression analysis was conducted to identify the independent risk factors for MH. A total of 189 patients were included in this study. MH was observed in 28 patients (14.8%). According to the multivariable logistic regression analysis results, the risk factors independently associated with MH were BMI at delivery (adjusted odds ratio [aOR], 1.19; 95% confidence interval [CI], 1.04-1.35; P=0.012), placenta accrete (aOR, 24.55; 95% CI, 2.75-219.02; P=0.004), and total previa degree (aOR, 9.86; 95% CI, 2.71-35.96; P=0.001). The study findings showed that maternal obesity, namely a higher BMI at delivery, was an independent risk factor for MH after CS in patients with placenta previa. Close attention should be paid to the potential risk of hemorrhage associated with maternal obesity as well as the well-known risk factors of placenta accreta and total previa degree.

• Journal of Korean Academy of Nursing
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• v.43 no.2
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• pp.154-164
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• 2013

Purpose: The purpose of this article is twofold: 1) introducing logistic regression (LR), a multivariable method for modeling the relationship between multiple independent variables and a categorical dependent variable, and 2) examining use and reporting of LR in the nursing literature. Methods: Text books on LR and research articles employing LR as main statistical analysis were reviewed. Twenty-three articles published between 2010 and 2011 in the Journal of Korean Academy of Nursing were analyzed for proper use and reporting of LR models. Results: Logistic regression from basic concepts such as odds, odds ratio, logit transformation and logistic curve, assumption, fitting, reporting and interpreting to cautions were presented. Substantial shortcomings were found in both use of LR and reporting of results. For many studies, sample size was not sufficiently large to call into question the accuracy of the regression model. Additionally, only one study reported validation analysis. Conclusion: Nursing researchers need to pay greater attention to guidelines concerning the use and reporting of LR models.

• Journal of Korean Neurosurgical Society
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• v.63 no.5
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• pp.640-648
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• 2020

Objective : This study aimed to assess the relationship between increased intracranial pressure (ICP) and mastoid effusions (ME). Methods : Between January 2015 and October 2018, patients who underwent intracranial surgery and had ICP monitoring catheters placed were enrolled. ICP was recorded hourly for at least 3 days. ME was determined by the emergence of opacification in mastoid air cells on follow-up brain imaging. C-reactive protein (CRP) levels, presence of endotracheal tube (ETT) and nasogastric tube (NGT), duration of intensive care unit (ICU) stay, duration of mechanical ventilator application, diagnosis, surgical modalities, and presence of sinusitis were recorded. Each factor's effect on the occurrence of ME was analyzed by binary logistic regression analyses. To analyze the independent effects of ICP as a predictor of ME a multivariable logistic regression analysis was performed. Results : Total of 61 (53%) out of 115 patients had ME. Among the patients who had unilateral brain lesions, 94% of subject (43/50) revealed the ipsilateral development of ME. ME developed at a mean of 11.1±6.2 days. The variables including mean ICP, peak ICP, age, trauma, CRP, ICU stays, application of mechanical ventilators and presence of ETT and NGT showed statistically significant difference between ME groups and non-ME groups in univariate analysis. Sex and the occurrence of sinusitis did not differ between two groups. Adding the ICP variables significantly improved the prediction of ME in multivariable logistic regression analysis. Conclusion : While multiple factors affect ME, this study demonstrates that ICP and ME are probably related. Further studies are needed to determine the mechanistic relationship between ICP and middle ear pressure.

• Acute and Critical Care
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• v.33 no.4
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• pp.230-237
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• 2018

Background: Socioeconomic status (SES) is closely associated with health outcomes, including mortality in critically ill patients admitted to intensive care unit (ICU). However, research regarding this issue is lacking, especially in countries where the National Health Insurance System is mainly responsible for health care. This study aimed to investigate how the SES of ICU patients in South Korea is associated with mortality. Methods: This was a retrospective observational study of adult patients aged ${\geq}20$ years admitted to ICU. Associations between SES-related factors recorded at the time of ICU admission and 30-day and 1-year mortalities were analyzed using univariable and multivariable Cox regression analyses. Results: A total of 6,008 patients were included. Of these, 394 (6.6%) died within 30 days of ICU admission, and 1,125 (18.7%) died within 1 year. Multivariable Cox regression analysis found no significant associations between 30-day mortality after ICU admission and SES factors (P>0.05). However, occupation was significantly associated with 1-year mortality after ICU admission. Conclusions: Our study shows that 30-day mortality after ICU admission is not associated with SES in the National Health Insurance coverage setting. However, occupation was associated with 1-year mortality after ICU admission.