• Journal of the Korean Institute of Navigation
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• v.25 no.1
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• pp.45-52
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• 2001

The purpose of this study is the optimum modification of dynamic characteristics of stiffened plate structure. In the method of the optimization, finite element method(FEM), sensitivity analysis and optimum structural modification method are used. To begin with, using FEM, the dynamic characteristics of stiffened plate structure is analyzed. Next, rate of change of dynamic characteristics by the change of design variable is calculated using the sensitivity analysis. Then, amount of change of design variable is calculated using this sensitivity value and optimum structural modification method. The change of natural frequency is made to be an objective function. Thickness of plate and cross section moment become a design variable. It is shown that the results are effective in the optimum modification for dynamic characteristics of the stiffened plate structure.

• Journal of Soil and Groundwater Environment
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• v.10 no.4
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• pp.13-17
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• 2005

For the SAT modeling system considering the reaction module which consists of nitrification, denitrification and organic oxidation, an imaginary cross-sectional 2-dimensional model simulation was carried out to analyze the sensitivity of the model. Four parameters, such as hydraulic conductivity, source water loading rate, ground surface pavement and operation schedule, were considered for the sensitivity analysis. Most factors considered in model development step were well reflected in the simulation results.

• Proceedings of the Korean Nuclear Society Conference
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• 1997.05b
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• pp.445-450
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• 1997

Self-Powered Neutron Detectors(SPNDs) are currently used to estimate the power generation distribution and fuel burn-up in several nuclear power reactors in Korea. In this paper, Monte Carlo simulation is accomplished to calculate the escape probability of beta particle as a function of their birth position fur the typical geometry of rhodium-based SPNDs. Also, a simple numerical method calculates the initial generation rate of beta particles and the change of generation rate due to rhodium burn-up. Using the simulation and the numerical method, the burn-up profile of rhodium density and the neutron sensitivity are calculated as a function of burn-up time in the reactor. The sensitivity of the SPNDs decreases non-linearly due to the high absorption cross-section and the non-uniform burn-up of rhodium in the emitter rod. In addition, for improvement of some properties of rhodium-based SPNDs which are currently used, this paper presents a new material. The method used here can be applied to the analysis of other types of SPNDs and will be useful in the optimum design of new SPNDs for long term usage.

• Clinical and Experimental Pediatrics
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• v.62 no.6
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• pp.217-223
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• 2019

Purpose: To determine the diagnostic value of eosinopenia and the neutrophil-to-lymphocyte ratio (NLR) in the diagnosis of early onset neonatal sepsis (EONS). Methods: This cross-sectional study was conducted in the Neonatology Ward of R.D. Kandou General Hospital Manado between July and October 2017. Samples were obtained from all neonates meeting the inclusion criteria for EONS. Data were encoded using logistic regression analysis, the point-biserial correlation coefficient, chi-square test, and receiver operating characteristic curve analysis, with a P value <0.05 considered significant. Results: Of 120 neonates who met the inclusion criteria, 73 (60.8%) were males and 47 (39.2%) were females. Ninety (75%) were included in the sepsis group and 30 (25%) in the nonsepsis group. The mean eosinophil count in EONS and non-EONS groups was $169.8{\pm}197.1cells/mm^3$ and $405.7{\pm}288.9cells/mm^3$, respectively, with statistically significant difference (P<0.001). The diagnostic value of eosinopenia in the EONS group (cutoff point: $140cells/mm^3$) showed 60.0% sensitivity and 90.0% specificity. The mean NLR in EONS and non-EONS groups was $2.82{\pm}2.29$ and $0.82{\pm}0.32$, respectively, with statistically significant difference (P<0.001). The diagnostic value of NLR in the EONS group (cutoff point, 1.24) showed 83.3% sensitivity and 93.3% specificity. Conclusion: Eosinopenia has high specificity as a diagnostic marker for EONS and an increased NLR has high sensitivity and specificity as a diagnostic marker for EONS.

• Journal of Korea Multimedia Society
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• v.22 no.3
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• pp.349-356
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• 2019

When a prescription change occurs in the hospital depending on a patient's improvement status, pharmacists directly classify manually returned pills which are not taken by a patient. There are hundreds of kinds of pills to classify. Because it is manual, mistakes can occur and which can lead to medical accidents. In this study, we have compared YOLO, Faster R-CNN and RetinaNet to classify and detect pills. The data consisted of 10 classes and used 100 images per class. To evaluate the performance of each model, we used cross-validation. As a result, the YOLO Model had sensitivity of 91.05%, FPs/image of 0.0507. The Faster R-CNN's sensitivity was 99.6% and FPs/image was 0.0089. The RetinaNet showed sensitivity of 98.31% and FPs/image of 0.0119. Faster RCNN showed the best performance among these three models tested. Thus, the most appropriate model for classifying pills among the three models is the Faster R-CNN with the most accurate detection and classification results and a low FP/image.

• Imaging Science in Dentistry
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• v.52 no.2
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• pp.187-195
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• 2022

Purpose: This study developed a convolutional neural network (CNN) model to diagnose maxillary sinusitis on panoramic radiographs(PRs) and cone-beam computed tomographic (CBCT) images and evaluated its performance. Materials and Methods: A CNN model, which is an artificial intelligence method, was utilized. The model was trained and tested by applying 5-fold cross-validation to a dataset of 148 healthy and 148 inflamed sinus images. The CNN model was implemented using the PyTorch library of the Python programming language. A receiver operating characteristic curve was plotted, and the area under the curve, accuracy, sensitivity, specificity, positive predictive value, and negative predictive values for both imaging techniques were calculated to evaluate the model. Results: The average accuracy, sensitivity, and specificity of the model in diagnosing sinusitis from PRs were 75.7%, 75.7%, and 75.7%, respectively. The accuracy, sensitivity, and specificity of the deep-learning system in diagnosing sinusitis from CBCT images were 99.7%, 100%, and 99.3%, respectively. Conclusion: The diagnostic performance of the CNN for maxillary sinusitis from PRs was moderately high, whereas it was clearly higher with CBCT images. Three-dimensional images are accepted as the "gold standard" for diagnosis; therefore, this was not an unexpected result. Based on these results, deep-learning systems could be used as an effective guide in assisting with diagnoses, especially for less experienced practitioners.

• Structural Monitoring and Maintenance
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• v.9 no.1
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• pp.59-80
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• 2022

In the present study, the objective is to detect the structural damages using the responses obtained from the sensors at the optimal location under uncertainty conditions. Reducing the error rate in damage detection process due to responses' noise is an important goal in this study. In the proposed algorithm for optimal sensor placement, the noise of responses recorded from the sensors is initially reduced using the principal component analysis. Afterward, the optimal sensor placement is obtained by the damage detection equation based sensitivity analysis. The sensors are placed on degrees of freedom corresponding to the minimum error rate in structural damage detection through this procedure. The efficiency of the proposed method is studied on a truss bridge, a space dome, a double-layer grid as well as a three-story experimental frame structure and the results are compared. Moreover, the performance of the suggested method is compared with three other algorithms of Average Driving Point Residue (ADPR), Effective Independence (EI) method, and a mass weighting version of EI. In the examples, young's modulus, density, and cross-sectional areas of the elements are considered as uncertainty parameters. Ultimately, the results have demonstrated that the presented algorithm under uncertainty conditions represents a high accuracy to obtain the optimal sensor placement in the structures.

• Advances in materials Research
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• v.11 no.3
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• pp.191-209
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• 2022

Very slow degradation of synthetic based polymers has created a severe environmental issue that increased awareness towards research in polymers of biodegradable property. Soy protein isolate (SPI) is a natural biopolymer used as matrix in green composites but it has limitations of low mechanical properties and high water sensitivity. To enhance mechanical properties and reduce water sensitivity of Jute-SPI composites, SPI was modified with pine rosin which is also a natural cross-linking agent. 30% glycerol on the weight basis of a matrix was used as a plasticizer. The fibre volume fraction was kept constant at 0.2 whereas the pine rosin in SPI ranged from 5% to 30% of the matrix. The effects of pine rosin on mechanical, thermal, water sensitivity and surface morphology have been characterized using various techniques. The mechanical properties and water absorbency were found to be optimum for 15% pine rosin in Jute-SPI composite. Therefore, Jute-SPI composite without pine rosin and with 15% pine rosin were chosen for investigation through characterization by Fourier transforms infrared spectroscopy (FTIR), Thermo-gravimetric analysis (TGA), X-Ray diffraction (XRD) and Scanning electron microscope (SEM). The surface morphology of the composite was influenced by pine rosin which is shown in the SEM image. TGA measurement showed that the thermal properties improved due to the addition of pine rosin. Antimicrobial test showed antimicrobial property in the composite occurring 15% pine rosin. The research paper concludes that the modification of SPI resin with an optimum percentage of pine rosin enhanced mechanical, thermal as well as water-resistant properties of jute fibre reinforced composites.

• Journal of Digital Convergence
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• v.12 no.7
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• pp.305-314
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• 2014

This study was conducted to investigate the cultural sensitivity and stereotype about immigrant women among nursing students. The participants in this study were 144 nursing students Data were collected from May to June 2013. The mean age of subjects was 21.8 years old. 68.1% of subjects had have experiences to travel abroad. Many subjects(90.3%) reported that multi-cultural education was needed. 66.0% of subjects met foreigners at clinical place among practice period. The cultural sensitivity and stereotype were middle range. It suggested that to prepare for the coming era of globalization, and to increase the nursing students' cultural sensitivity, a transcultural nursing curriculum needs to develop for appropriate and effective services in cross-cultural situations of the multicultural families in Korea.

• Journal of Sensor Science and Technology
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• v.23 no.2
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• pp.114-121
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• 2014

We report a polysilicon active area membrane field effect transistor (PSAFET) pressure sensor for low stress deflection of membrane. The PSAFET was produced in conventional FET semiconductor fabrication and backside wet etching. The PSAFET located at the front side measured pressure change using 300 nm thin-nitride membrane when a membrane was slightly strained by the small deflection of membrane shape from backside with any physical force. The PSAFET showed high sensitivity around threshold voltage, because threshold voltage variation was composed of fractional function form in sensitivity equation of current variation. When gate voltage was biased close to threshold voltage, a fractional function form had infinite value at $V_{tn}$, which increased the current variation of sensitivity. Threshold voltage effect was dominant right after the PSAFET was turned on. Narrow transistor channel established by small current flow was choked because electron could barely cross drain-source electrodes. When gate voltage was far from threshold voltage, threshold voltage effect converged to zero in fractional form of threshold voltage variations and drain current change was mostly determined by mobility changes. As the PSAFET fabrication was compatible with a polysilicon FET in CMOS fabrication, it could be adapted in low pressure sensor and bio molecular sensor.