• Steel and Composite Structures
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• v.19 no.5
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• pp.1077-1094
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• 2015

This paper presents an experimental study on the effectiveness of simultaneous application of carbon fiber-reinforced polymer (CFRP) and steel jacket in strengthening slender reinforced concrete (RC) column. The columns were 200 mm square cross section with lengths ranging from 1600 to 3000 mm. Ten columns were tested under axial load. The effects of the strengthening technique, slenderness ratio, cross-section area of steel angle and CFRP layer number were examined in terms of axial load-axial strain curve, CFRP strain, steel strip strain and steel angle strain. The experiments indicate that strengthening RC columns with combined CFRP and steel jacket is effective in enhancing the load capacity, ductility and energy dissipation capacity of RC column. Based on the existing models for RC columns strengthened with CFRP and with steel jacket, a design formula considering a slenderness reduction factor is proposed to predict the load capacity of the RC columns strengthened with combined CFRP and steel jacket. The predictions agree well with the experimental results.

• Geomechanics and Engineering
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• v.28 no.5
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• pp.505-520
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• 2022

In recent years, geotextile-encased gravel columns (usually called stone columns) have become a popular method to increasing soil shear strength, decreasing the settlement, acceleration of the rate of consolidation, reducing the liquefaction potential and increasing the bearing capacity of foundations. The behavior of improved loose base-soil with gravel columns under shear loading and the shear stress-horizontal displacement curves got from large scale direct shear test are of great importance in understanding the performance of this method. In the present study, by performing 36 large-scale direct shear tests on sandy base-soil with different fine-content of zero to 30% in both not improved and improved with gravel columns, the effect of the presence of gravel columns in the loose soils were investigated. The results were used to predict the shear stress-horizontal displacement curve of these samples using support vector machines (SVM). Variables such as the non-plastic fine content of base-soil (FC), the area replacement ratio of the gravel column (Arr), the geotextile encasement and the normal stress on the sample were effective factors in the shear stress-horizontal displacement curve of the samples. The training and testing data of the model showed higher power of SVM compared to multilayer perceptron (MLP) neural network in predicting shear stress-horizontal displacement curve. After ensuring the accuracy of the model evaluation, by introducing different samples to the model, the effect of different variables on the maximum shear stress of the samples was investigated. The results showed that by adding a gravel column and increasing the Arr, the friction angle (ϕ) and cohesion (c) of the samples increase. This increase is less in base-soil with more FC, and in a proportion of the same Arr, with increasing FC, internal friction angle and cohesion decreases.

• Clinical and Experimental Reproductive Medicine
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• v.36 no.4
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• pp.255-263
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• 2009

Objective: The objective of the study was to determine the diagnostic performance of transabdominal ultrasound by receiver operating characteristic (ROC) curve analysis, in order to evaluate the usefulness in establishing the diagnosis of polycystic ovary syndrome (PCOS). Methods: Questionnaires were given to 8,793 reproductive women reviewed at Ewha Womans University Mokdong hospital. Ultrasound examinations were performed in 701 women with a transabdominal transducer. Transabdominal ultrasounds were performed in 185 normal control women (normal menstruation without hyperandrogenism or PCO morphology) and 248 PCOS patients according to National Institutes of Health (NIH) PCOS diagnosis criteria. ROC curves were calculated for ovarian volume and follicle number. Results: In normal control group, the mean age were $23.64{\pm}4.26$ years old and the mean ovarian volume and follicle number were $6.03{\pm}1.89\;cm^3$ and $6.49{\pm}1.93$, respectively. The ovarian volume showed an area under the ROC curve (AURC) of 0.761. A ovarian volume decision threshold >$9\;cm^3$ had a sensitivity of 51.0% and a specificity of 91.4% for the diagnosis of PCOS. The follicle number showed an AURC of 0.733. A follicle number decision threshold ${\geq}9$ had a sensitivity of 54.9% and a specificity of 87.0% for the diagnosis of PCOS. A follicle number decision threshold ${\geq}10$ had a sensitivity of 53.2% and a specificity of 90.4%. A follicle number and a ovarian volume did not have a high diagnostic power for screening for PCOS. Conclusion: Our results suggest that transabdominal ultrasound assessment is not effective for the detection of PCOS in young women of reproductive age.

• Korean Journal of Clinical Pharmacy
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• v.10 no.3
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• pp.125-129
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• 2000

The effect of circadian rhythm on gentamicin pharmacokinetics was studied in rabbits who took a single intravenous 2 mg/kg dose of gentamicin at 09:00 in the morning (a.m.) and 22:00 in the evening (p.m.). A significant circadian rhythm of pharmacokinetic parameters as a function of time of day was noted in rabbits, showing lower total body clearance $CL_t$ and higher serum area under the curve (AUC) when given in the evening. The half-life $t_{1/2}$ was shorter in the morning $(3.88\pm0.62h)$ when compared to the evening $(4.76\pm0.75\;h)$. The AUC was greater in the evening $(25.92\pm3.49\;{\mu}g/ml{\cdot}hr)$ than that in the morning $(22.42\pm3.42\;{\mu}g/ml{\cdot}hr)$, most likely because the CLt was significantly higher when gentamicin was given in the morning $(0.18\pm0.28\;ml/hr)$ versus in the evening $(0.15\pm0.26\;ml/hr)$. The $t_{1/2}$ of gentamicin in the evening was increased significantly(p<0.05) compared to those of gentamicin in the morning. It is reasonable to consider individual circadian rhythm for effective dosage regimen of gentamicin in clinical chronotherapeutics.

• Childhood Kidney Diseases
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• v.26 no.1
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• pp.46-51
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• 2022

Purpose: Delta neutrophil index (DNI) indicates immature granulocytes in peripheral blood and has been confirmed to be effective as a prognostic factor for neonatal sepsis. Also, it has been reported to have diagnostic value in acute pyelonephritis and in predicting vesicoureteral reflux (VUR) in the infant. We conducted the study to verify whether DNI is also helpful in the entire pediatric age group with febrile urinary tract infection (UTI). Methods: Medical records of children hospitalized for febrile UTIs were analyzed retrospectively. All subjects underwent kidney ultrasound and voiding cystourethrography. In the group with and without VUR, we compared sex and age, and the following laboratory values: the white blood cell count, neutrophil, polymorphonuclear leucocyte, eosinophil, hemoglobin, platelet count, C-reactive protein, DNI value, and the finding of ultrasound. Results: A total of 315 patients (163 males and 152 females; range, 0-127 months) were eligible, and 41 patients (13%) had VUR. As a result of univariate analysis, the white blood cell count, neutrophil, DNI, and ultrasonic abnormalities were high in the reflux group, and the hemoglobin and lymphocyte fraction values were low. The value of DNI and the abnormal ultrasound were significantly higher in the reflux group on the multivariate analysis. The area under the curve value of the receiver operating curve was higher in DNI (0.640; 95% confidence interval, 0.536-0.744; P=0.004), and the DNI cutoff value for VUR prediction was 1.85%. Conclusions: We identified that ultrasound findings and DNI values were helpful predictors of VUR in pediatric febrile UTIs.

• Journal of Korean Academy of Nursing
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• v.54 no.2
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• pp.193-210
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• 2024

Purpose: The objective of this study was to develop a predictive model for the sexual experiences of adolescents using the random forest method and to identify the "variable importance." Methods: The study utilized data from the 2019 to 2021 Korea Youth Risk Behavior Web-based Survey, which included 86,595 man and 80,504 woman participants. The number of independent variables stood at 44. SPSS was used to conduct Rao-Scott χ² tests and complex sample t-tests. Modeling was performed using the random forest algorithm in Python. Performance evaluation of each model included assessments of precision, recall, F1-score, receiver operating characteristics curve, and area under the curve calculations derived from the confusion matrix. Results: The prevalence of sexual experiences initially decreased during the COVID-19 pandemic, but later increased. "Variable importance" for predicting sexual experiences, ranked in the top six, included week and weekday sedentary time and internet usage time, followed by ease of cigarette purchase, age at first alcohol consumption, smoking initiation, breakfast consumption, and difficulty purchasing alcohol. Conclusion: Education and support programs for promoting adolescent sexual health, based on the top-ranking important variables, should be integrated with health behavior intervention programs addressing internet usage, smoking, and alcohol consumption. We recommend active utilization of the random forest analysis method to develop high-performance predictive models for effective disease prevention, treatment, and nursing care.

• Journal of Pharmaceutical Investigation
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• v.35 no.2
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• pp.101-106
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• 2005

The pharmacokinetics of oral nifedipine (5 mg/kg) was studied in rabbits given after or simultaneously with naringin (1.5, 7.5 and 15 mg/kg, respectively). The area under the plasma concentration-time curve (AUC) and the peak concentration $(C_{max})$ of nifedipine coadministered or pretreated with naringin were significantly increased (p < 0.05, coad.; p < 0.01, pret.) compared with the control group. The absolute bioavailability (AB%) of nifedipine was significantly (p < 0.05, coad.; p < 0.01, pret.) higher by 22.3 - 28.1 % compared to the control (17.9%). The relative bioavailability (RB%) of nifedipine was higher by 1.24 - 1.43 times (coad.) and 1.32 -1.57 times (pret.) than those of the control, showing that preatreatrnent of naringin was more effective than that of the coadministration of naringin. Naringin did not show significant effect on the Tmax and $t_{1/2}$ of nifedipine. It is suggested that naringin may alter pharmacokinetic paramiters of nifedipine by inhibition of P-glycoprotein efflux pump and its first-pass metabolism. The dosage of nifedipine should be adjusted when it is administered with naringin in a clinical situation.

• Journal of Periodontal and Implant Science
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• v.48 no.2
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• pp.114-123
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• 2018

Purpose: The aim of the current study was to develop a computer-assisted detection system based on a deep convolutional neural network (CNN) algorithm and to evaluate the potential usefulness and accuracy of this system for the diagnosis and prediction of periodontally compromised teeth (PCT). Methods: Combining pretrained deep CNN architecture and a self-trained network, periapical radiographic images were used to determine the optimal CNN algorithm and weights. The diagnostic and predictive accuracy, sensitivity, specificity, positive predictive value, negative predictive value, receiver operating characteristic (ROC) curve, area under the ROC curve, confusion matrix, and 95% confidence intervals (CIs) were calculated using our deep CNN algorithm, based on a Keras framework in Python. Results: The periapical radiographic dataset was split into training (n=1,044), validation (n=348), and test (n=348) datasets. With the deep learning algorithm, the diagnostic accuracy for PCT was 81.0% for premolars and 76.7% for molars. Using 64 premolars and 64 molars that were clinically diagnosed as severe PCT, the accuracy of predicting extraction was 82.8% (95% CI, 70.1%-91.2%) for premolars and 73.4% (95% CI, 59.9%-84.0%) for molars. Conclusions: We demonstrated that the deep CNN algorithm was useful for assessing the diagnosis and predictability of PCT. Therefore, with further optimization of the PCT dataset and improvements in the algorithm, a computer-aided detection system can be expected to become an effective and efficient method of diagnosing and predicting PCT.

• The Journal of the Acoustical Society of Korea
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• v.42 no.3
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• pp.262-269
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• 2023

In this paper, we propose a Linear Prediction (LP) analysis-based feature for detecting Snapping Shrimp (SS) Noise (SSN) in underwater acoustic data. SS is a species that creates high amplitude signals in shallow, warm waters, and its frequent and loud sound is a major source of noise. The proposed feature takes advantage of the characteristic of SSN, which is sudden and rapidly disappearing, by using LP analysis to detect the exact noise interval and reduce the effects of SSN. The error between the predicted and measured value is large and results in effective SSN detection. To further improve performance, a constant false alarm rate detector is incorporated into the proposed feature. Our evaluation shows that the proposed methods outperform the state-of-the-art MultiLayer-Wavelet Packet Decomposition (ML-WPD) in terms of receiver operating characteristic curve and Area Under the Curve (AUC), with the LP analysis-based feature achieving a higher AUC by 0.12 on average and lower computational complexity.

• Preventive Nutrition and Food Science
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• v.17 no.4
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• pp.239-244
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• 2012

This study investigated the hypoglycemic effect of the Padina arborescens extract in STZ-induced diabetic mice. Freeze-dried Padina arborescens were extracted with 80% methanol and concentrated for use in this study. The hypoglycemic effect was determined by inhibitory activities against ${\alpha}$-glucosidase and ${\alpha}$-amylase as well as the alleviation of postprandial blood glucose level. Padina arborescens extracts showed higher inhibitory activities than acarbose, a positive control against ${\alpha}$-glucosidase and ${\alpha}$-amylase. The $IC_{50}$ values of Padina arborescens extracts against ${\alpha}$-glucosidase and ${\alpha}$-amylase were 0.26 and 0.23 mg/mL, respectively, which evidenced as more effective than observed with acarbose. The increase of postprandial blood glucose levels were significantly suppressed in the Padina arborescens extract administered group than the control group in the streptozotocin induced diabetic mice. Furthermore, the area under the curve (AUC) was significantly lowered via Padina arborescens extract administration in diabetic mice (p 0.05). These results indicated that the Padina arborescens extract might be used as an inhibitor of ${\alpha}$-glucosidase and ${\alpha}$-amylase and delay absorption of dietary carbohydrates.