• Textile Coloration and Finishing
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• 제32권4호
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• pp.217-225
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• 2020

In this study, the dyeing characteristics of nylon fabric which is dyed with supercritical fluid were investigated. There were two dyes used in the dyeing experiment: C.I. Disperse Red 167 and C.I. Disperse Violet 93. Dyeing temperature, pressure, and leveling time were fixed at 110℃, 250bar, 60minutes, and the experiment was conducted with dyeing concentration of 0.1, 0.3, 0.5, and 0.85% o.w.f. The analysis of the experimental results was found out through the measurement of washing fastness and color coordinate. In addition, the calibration curve of each dye was drawn up and the amount of remaining dye was checked by measuring the absorbance of the residual dye. As a result of color difference measurement, as the concentration increased, the L⁎ value decreased and the K/S value increased. However, the increase in K/S value compared to the amount of input decreased as the concentration increased. The comparative experiment on the amount of residual dye(C.I. Disperse Red 167) in the pot showed that 99.14% of the amount was dyed at the concentration of 0.1% o.w.f, while it rapidly decreased to 77% at 0.85% o.w.f. C.I. Disperse Violet 93 dye also decreased from 0.5% o.w.f to 93.91%. In the washing fastness experiment of both dyes, the level of washing fastness began to decrease from samples dyed at 0.5% o.w.f. It may be because the simply absorbed dye was produced instead of completely being fixed in the amorphous region of the nylon fiber.

• Steel and Composite Structures
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• 제41권6호
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• pp.831-850
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• 2021

Surface subsidence caused by mining subsidence has an impact on neighboring structures and utilities. In other words, subsurface voids created by mining or tunneling activities induce soil movement, exposing buildings to physical and/or functional destruction. Soil-structure is evaluated employing probability distribution laws to account for their uncertainty and complexity to estimate structural vulnerability. In this study, to investigate the displacement field and surface settlement profile caused by mining subsidence, on the basis of a Winklersoil model, analytical equations for the moment-rotation response ofsoil during mining induced ground movements are developed. To define the full static moment-rotation response, an equation for the uplift-yield state is constructed and integrated with equations for the uplift- and yield-only conditions. The constructed model's findings reveal that the inverse of the factor of safety (x) has a considerable influence on the moment-rotation curve. The maximal moment-rotation response of the footing is defined by X = 0:6. Despite the use of Winkler model, the computed moment-rotation response results derived from the literature were analyzed through the ELM-SVM hybrid of Extreme Learning Machine (ELM) and Support Vector Machine (SVM). Also, Monte Carlo simulations are used to apply continuous random parameters to assess the transmission of ground motions to structures. Following the findings of RMSE and R2, the results show that the choice of probabilistic laws of input parameters has a substantial impact on the outcome of analysis performed.

• Journal of the Korea Institute of Information Security & Cryptology
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• 제33권4호
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• pp.687-697
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• 2023

Botnets, whose attack patterns are becoming more sophisticated and diverse, are recognized as one of the most serious cybersecurity threats today. This paper revisits the experimental results of botnet detection using autoencoder, a semi-supervised deep learning model, for UGR and CTU-13 data sets. To prepare the input vectors of autoencoder, we create data points by grouping the NetFlow records into sliding windows based on source IP address and aggregating them to form features. In particular, we discover a simple power-law; that is the number of data points that have some flow-degree is proportional to the number of NetFlow records aggregated in them. Moreover, we show that our power-law fits the real data very well resulting in correlation coefficients of 97% or higher. We also show that this power-law has an impact on the learning of autoencoder and, as a result, influences the performance of botnet detection. Furthermore, we evaluate the performance of autoencoder using the area under the Receiver Operating Characteristic (ROC) curve.

• Nuclear Engineering and Technology
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• 제54권11호
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• pp.4244-4252
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• 2022

The accuracy of Monte Carlo (MC) simulations in estimating the computed tomography radiation dose is highly dependent on the accuracy of CT scanner model. A system was developed to observe the 3D model intuitively and to calculate the X-ray energy spectrum and the bowtie (BT) filter model more accurately in Monte Carlo N-particle (MCNP). Labview's built-in Open Graphics Library (OpenGL) was used to display basic surfaces, and constructive solid geometry (CSG) method was used to realize Boolean operations. The energy spectrum was calculated by simulating the process of electronic shooting and the BT filter model was accurately modeled based on the calculated shape curve. Physical data from a study was used as an example to illustrate the accuracy of the constructed model. RMSE between the simulation and the measurement results were 0.97% and 0.74% for two filters of different shapes. It can be seen from the comparison results that to obtain an accurate CT scanner model, physical measurements should be taken as the standard. The energy spectrum library should be established based on Monte Carlo simulations with modifiable input files. It is necessary to use the three-segment splicing modeling method to construct the bowtie filter model.

• Journal of the Korean Geotechnical Society
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• 제24권4호
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• pp.67-78
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• 2008

In this study, artificial cemented sand made of a few portland cement and Nak-Dong river sand was researched closely to investigate cementing effect quantitatively through unconfined tests and triaxial tests. The peak strength and elastic modulus increased and dilation of cemented sand was restricted by the cementation, but after breakage of the cementation, dilation and negative excess pore water pressure increased. In stress-strain curve, strain-softening behavior appeared in drained condition but strain-hardening behavior was appeared in undrained condition as a result of the increase of effective stress. The test was quantitatively analyzed by multiple regression models, correlating each response variable with input variable. The equations are valid only over the range investigated. Its adjusted coefficient of determination was $0.81{\sim}0.91$, and dry density is important factor for estimating strength of cemented sand.

• Convergence Security Journal
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• 제22권1호
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• pp.81-92
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• 2022

The rapidly growing IoT market is expanding not only in general households but also in smart homes and smart cities. Among the major protocols used in IoT, ZigBee accounts for more than 90% of the smart home's door lock market and is mainly used in miniaturized sensor devices, so the safety of the protocol is very important. However, the device using Zig Bee is not satisfied with the omnidirectional safety because it uses a fixed key during the authentication process that connects to the network, and it has not been resolved in the recently developed ZigBee 3.0. This paper proposes a design method that provides omnidirectional safety to the ZigBee authentication protocol and can be quickly applied to existing protocols. The proposed improved ZigBee authentication protocol analyzed and applied the recently developed OWE protocol to apply ECDH, which has low computational volume and provides omnidirectional safety in IoT. Based on this, it provides the safety of the ZigBee authentication protocol, and it is expected that it will be able to provide user convenience as it does not require a separate certificate or password input.

• Atmosphere
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• 제33권5호
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• pp.531-548
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• 2023

We developed the Aviation Convective Index (ACI) for predicting deep convective area using the operational global Numerical Weather Prediction model of the Korea Meteorological Administration. Seasonally optimized ACI (ACI_SnOpt) was developed to consider seasonal variabilities on deep convections in Korea. Yearly optimized ACI (ACI_YrOpt) in Part 1 showed that seasonally averaged values of Area Under the ROC Curve (AUC) and True Skill Statistics (TSS) were decreased by 0.420% and 5.797%, respectively, due to the significant degradation in winter season. In Part 2, we developed new membership function (MF) and weight combination of input variables in the ACI algorithm, which were optimized in each season. Finally, the seasonally optimized ACI (ACI_SnOpt) showed better performance skills with the significant improvements in AUC and TSS by 0.983% and 25.641% respectively, compared with those from the ACI_YrOpt. To confirm the improvements in new algorithm, we also conducted two case studies in winter and spring with observed Convectively-Induced Turbulence (CIT) events from the aircraft data. In these cases, the ACI_SnOpt predicted a better spatial distribution and intensity of deep convection. Enhancements in the forecast fields from the ACI_YrOpt to ACI_SnOpt in the selected cases explained well the changes in overall performance skills of the probability of detection for both "yes" and "no" occurrences of deep convection during 1-yr period of the data. These results imply that the ACI forecast should be optimized seasonally to take into account the variabilities in the background conditions for deep convections in Korea.

• Annals of Hepato-Biliary-Pancreatic Surgery
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• 제27권2호
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• pp.195-200
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• 2023

Backgrounds/Aims: We aimed to build a machine learning tool to help predict low-grade intraductal papillary mucinous neoplasms (IPMNs) in order to avoid unnecessary surgical resection. IPMNs are precursors to pancreatic cancer. Surgical resection remains the only recognized treatment for IPMNs yet carries some risks of morbidity and potential mortality. Existing clinical guidelines are imperfect in distinguishing low-risk cysts from high-risk cysts that warrant resection. Methods: We built a linear support vector machine (SVM) learning model using a prospectively maintained surgical database of patients with resected IPMNs. Input variables included 18 demographic, clinical, and imaging characteristics. The outcome variable was the presence of low-grade or high-grade IPMN based on post-operative pathology results. Data were divided into a training/validation set and a testing set at a ratio of 4:1. Receiver operating characteristics analysis was used to assess classification performance. Results: A total of 575 patients with resected IPMNs were identified. Of them, 53.4% had low-grade disease on final pathology. After classifier training and testing, a linear SVM-based model (IPMN-LEARN) was applied on the validation set. It achieved an accuracy of 77.4%, with a positive predictive value of 83%, a specificity of 72%, and a sensitivity of 83% in predicting low-grade disease in patients with IPMN. The model predicted low-grade lesions with an area under the curve of 0.82. Conclusions: A linear SVM learning model can identify low-grade IPMNs with good sensitivity and specificity. It may be used as a complement to existing guidelines to identify patients who could avoid unnecessary surgical resection.

• Korean Journal of Optics and Photonics
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• 제20권5호
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• pp.266-271
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• 2009

We designed a thermo-optic switch based on a directional coupler with not only a high extinction ratio but also significantly low power consumption. The switch operates by using the thermo-optic effect of the polymer which the refractive index changes by heating the electrode. If the electrode is not powered (OFF), the input light will be coupled completely to the other waveguide. When the electrode is powered at a certain level (ON), input light launched into the input waveguide will remain in that waveguide due to the lower index adjusted in the other waveguide. The switch based on the directional coupler was designed using the generalized extinction ratio curve and the lateral shift of the input waveguide. The coupling length is 1,610 ${\mu}m$ and the extinction ratios are -28 and -30 dB for ON and OFF states, respectively. The electrode structures were optimized by thermal analysis. The transported heat into the waveguide is increased, as the electrode width (w) is increased and the center distance between the electrode and the waveguide (d) is decreased. Also, because the heat generated in the electrode affects the other waveguide, the temperature difference between two waveguides is varied as the given w and d. There are specific conditions which have the maximum of the temperature difference. That of the temperature difference is increased as the width and the temperature of the electrode are increased. Especially, when the switch is designed using the condition with the maximum of the temperature difference for switching, the temperature of the electrode can be decreased. We expect this condition will be the novel method for the reduction of the power consumption in a thermo-optic switch.

• Progress in Medical Physics
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• 제15권4호
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• pp.202-209
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• 2004

Flat panel based digital radiography (DR) systems have recently become useful and important in the field of diagnostic radiology. For DRs with amorphous silicon photosensors, CsI(TI) is normally used as the scintillator, which produces visible light corresponding to the absorbed radiation energy. The visible light photons are converted into electric signal in the amorphous silicon photodiodes which constitute a two dimensional array. In order to produce good quality images, detailed behaviors of DR detectors to radiation must be studied. The relationship between air exposure and the DR outputs has been investigated in many studies. But this relationship was investigated under the condition of the fixed tube voltage. In this study, we investigated the relationship between the DR outputs and X-ray in terms of the absorbed energy in the detector rather than the air exposure using SPEC-l8, an X-ray energy spectrum model. Measured exposure was compared with calculated exposure for obtaining the inherent filtration that is a important input variable of SPEC-l8. The absorbed energy in the detector was calculated using algorithm of calculating the absorbed energy in the material and pixel values of real images under various conditions was obtained. The characteristic curve was obtained using the relationship of two parameter and the results were verified using phantoms made of water and aluminum. The pixel values of the phantom image were estimated and compared with the characteristic curve under various conditions. It was found that the relationship between the DR outputs and the absorbed energy in the detector was almost linear. In a experiment using the phantoms, the estimated pixel values agreed with the characteristic curve, although the effect of scattered photons introduced some errors. However, effect of a scattered X-ray must be studied because it was not included in the calculation algorithm. The result of this study can provide useful information about a pre-processing of digital radiography.