• Journal of Korean Neurosurgical Society
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• v.62 no.6
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• pp.643-648
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• 2019

Objective : Shunt-dependent hydrocephalus (SdHCP) is a well-known complication of aneurysmal subarachnoid hemorrhage (SAH). The risk factors for SdHCP have been widely investigated, but few risk scoring systems have been established to predict SdHCP. This study was performed to investigate the risk factors for SdHCP and devise a risk scoring system for use before aneurysm obliteration. Methods : We reviewed the data of 301 consecutive patients who underwent aneurysm obliteration following SAH from September 2007 to December 2016. The exclusion criteria for this study were previous aneurysm obliteration, previous major cerebral infarction, the presence of a cavum septum pellucidum, a midline shift of >10 mm on initial computed tomography (CT), and in-hospital mortality. We finally recruited 254 patients and analyzed the following data according to the presence or absence of SdHCP : age, sex, history of hypertension and diabetes mellitus, Hunt-Hess grade, Fisher grade, aneurysm size and location, type of treatment, bicaudate index on initial CT, intraventricular hemorrhage, cerebrospinal fluid drainage, vasospasm, and modified Rankin scale score at discharge. Results : In the multivariate analysis, acute HCP (bicaudate index of ${\geq}0.2$) (odds ratio [OR], 6.749; 95% confidence interval [CI], 2.843-16.021; p=0.000), Fisher grade of 4 (OR, 4.108; 95% CI, 1.044-16.169; p=0.043), and an age of ${\geq}50years$ (OR, 3.938; 95% CI, 1.375-11.275; p=0.011) were significantly associated with the occurrence of SdHCP. The risk scoring system using above parameters of acute HCP, Fisher grade, and age (AFA score) assigned 1 point to each (total score of 0-3 points). SdHCP occurred in 4.3% of patients with a score of 0, 8.5% with a score of 1, 25.5% with a score of 2, and 61.7% with a score of 3 (p=0.000). In the receiver operating characteristic curve analysis, the area under the curve (AUC) for the risk scoring system was 0.820 (p=0.080; 95% CI, 0.750-0.890). In the internal validation of the risk scoring system, the score reliably predicted SdHCP (AUC, 0.895; p=0.000; 95% CI, 0.847-0.943). Conclusion : Our results suggest that the herein-described AFA score is a useful tool for predicting SdHCP before aneurysm obliteration. Prospective validation is needed.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.1
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• pp.1-10
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• 2022

Deep neural networks are widely used to solve various problems. In a fully connected neural network, the nonlinear activation function is a function that nonlinearly transforms the input value and outputs it. The nonlinear activation function plays an important role in solving the nonlinear problem, and various nonlinear activation functions have been studied. In this study, we propose a combined parametric activation function that can improve the performance of a fully connected neural network. Combined parametric activation functions can be created by simply adding parametric activation functions. The parametric activation function is a function that can be optimized in the direction of minimizing the loss function by applying a parameter that converts the scale and location of the activation function according to the input data. By combining the parametric activation functions, more diverse nonlinear intervals can be created, and the parameters of the parametric activation functions can be optimized in the direction of minimizing the loss function. The performance of the combined parametric activation function was tested through the MNIST classification problem and the Fashion MNIST classification problem, and as a result, it was confirmed that it has better performance than the existing nonlinear activation function and parametric activation function.

• Journal of the Korea institute for structural maintenance and inspection
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• v.20 no.4
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• pp.35-43
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• 2016

Recently, the pipeline system for waste transportation has been increasingly constructed as new solution for the waste collection and disposal system by constantly increasing domestic waste which issued as social problem. The pipeline system is constructed through long distance, so proper long-term monitoring system is necessary which available to detect the damage location for the effective maintenance. In this paper, the experimental study is carried out to evaluate the applicability of optical strain gauge sensor based on FBG for the long-term monitoring system. Three test parameters such as pressure leaking, blockage and deformation are considered as typical damages for real-scale pipeline test specimen. In order to measure flexural and volumetric strain and temperature, three FBG sensors are installed at each monitoring sections. From the test results, this study suggested effective methods of sensor installation and arrangement. Also the sensor spacing for the design of monitoring system using FBG sensor is derived by the correlation of distances from deformation between sensor responses.