• Structural Engineering and Mechanics
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• v.78 no.2
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• pp.117-124
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• 2021

This work focused on the novel numerical tool for the bending responses of carbon nanotube reinforced composites (CNTRC) beams. The higher order shear deformation beam theory (HSDT) is used to determine strain-displacement relationships. A new exponential function was introduced into the carbon nanotube (CNT) volume fraction equation to show the effect of the CNT distribution on the CNTRC beams through displacements and stresses. To determine the mechanical properties of CNTRCs, the rule of the mixture was employed by assuming that the single-walled carbon nanotubes (SWCNTs)are aligned and distributed in the matrix. The governing equations were derived by Hamilton's principle, and the mathematical models presented in this work are numerically provided to verify the accuracy of the present theory. The effects of aspect ratio (l/d), CNT volume fraction (Vcnt), and the order of exponent (n) on the displacement and stresses are presented and discussed in detail. Based on the analytical results. It turns out that the increase of the exponent degree (n) makes the X-beam stiffer and the exponential CNTs distribution plays an indispensable role to improve the mechanical properties of the CNTRC beams.

• Korean Journal of Remote Sensing
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• v.37 no.1
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• pp.169-176
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• 2021

The Global Space-based Inter-Calibration System (GSICS) is an international partnership sponsored by World Meteorological Organization (WMO) to continue and improve climate monitoring and to ensure consistent accuracy between observation data from meteorological satellites operating around the world. The objective for GSICS is to inter-calibration from pairs of satellites observations, which includes direct comparison of collocated Geostationary Earth Orbit (GEO)-Low Earth Orbit (LEO) observations. One of the GSICS inter-calibration methods, the Ray-matching technique, is a surrogate approach that uses matched, co-angled and co-located pixels to transfer the calibration from a well calibrated satellite sensor to another sensor. In Korea, the first GEO satellite, Communication Ocean and Meteorological Satellite (COMS), is used to participate in the GSICS program. The National Meteorological Satellite Center (NMSC), which operated COMS/MI, calculated the Radiative Transfer Model (RTM)-based GSICS coefficient coefficients. The L1P reproduced through GSICS correction coefficient showed lower RMSE and Bias than L1B without GSICS correction coefficient applied. The calculation cycles of the GSICS correction coefficients for COMS/MI visible channel are provided annual and diurnal (2, 5, 10, 14-day), but long-term evaluation according to these cycles was not performed. The purpose of this paper is to perform evaluation depending on the annual/diurnal cycles of COMS/MI GSICS correction coefficients based on the ray-matching technique using Suomi-NPP/Visible Infrared Imaging Radiometer Suite (VIIRS) data as reference data. As a result of evaluation, the diurnal cycle had a higher coincidence rate with the reference data than the annual cycle, and the 14-day diurnal cycle was the most suitable for use as the GSICS correction coefficient.

• Advances in nano research
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• v.12 no.1
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• pp.73-79
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• 2022

Due to the extensive use of concrete structures in various applications, the improvement of their strength and quality has become of great importance. A new way of achieving this purpose is to add different types of nanoparticles to concrete admixtures. In this work, a mathematical model has been employed to analyze the vibration of concrete beams reinforced by graphene oxide (GO) nanoparticles. To verify the accuracy of the presented model, an experimental study has been conducted to compare the compressive strengths of these beams. Since GO nanoparticles are not readily dissolved in water, before producing the concrete samples, the GO nanoparticles are dispersed in the mixture by using a shaker, magnetic striker, ultrasonic devices, and finally, by means of a mechanical mixer. The sinusoidal shear deformation beam theory (SSDBT) is employed to model the concrete beams. The Mori-Tanaka model is used to determine the effective properties of the structure, including the agglomeration influences. The motion equations are calculated by applying the energy method and Hamilton's principle. The vibration frequencies of the concrete beam samples are obtained by an analytical method. Three samples containing 0.02% GO nanoparticles are made and their compressive strengths are measured and compared. There is a good agreement between our results and those of the mathematical model and other papers, with a maximum difference of 1.29% between them. The aim of this work is to investigate the effects of nanoparticle volume fraction and agglomeration and the influences of beam length and thickness on the vibration frequency of concrete structures. The results show that by adding the GO nanoparticles, the vibration frequency of the beams is increased.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.175-182
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• 2022

In our daily life, we come across different types of information, for example in the format of multimedia and text. We all need different types of information for our common routines as watching/reading the news, listening to the radio, and watching different types of videos. However, sometimes we could run into problems when a certain type of information is required. For example, someone is listening to the radio and wants to listen to jazz, and unfortunately, all the radio channels play pop music mixed with advertisements. The listener gets stuck with pop music and gives up searching for jazz. So, the above example can be solved with an automatic audio classification system. Deep Learning (DL) models could make human life easy by using audio classifications, but it is expensive and difficult to deploy such models at edge devices like nano BLE sense raspberry pi, because these models require huge computational power like graphics processing unit (G.P.U), to solve the problem, we proposed DL model. In our proposed work, we had gone for a low complexity model for Audio Event Detection (AED), we extracted Mel-spectrograms of dimension 128×431×1 from audio signals and applied normalization. A total of 3 data augmentation methods were applied as follows: frequency masking, time masking, and mixup. In addition, we designed Convolutional Neural Network (CNN) with spatial dropout, batch normalization, and separable 2D inspired by VGGnet [1]. In addition, we reduced the model size by using model quantization of float16 to the trained model. Experiments were conducted on the updated dataset provided by the Detection and Classification of Acoustic Events and Scenes (DCASE) 2020 challenge. We confirm that our model achieved a val_loss of 0.33 and an accuracy of 90.34% within the 132.50KB model size.

• Advances in nano research
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• v.15 no.1
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• pp.59-65
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• 2023

In this present article, the mechanical behavior of single-walled black phosphorene nanotubes (SW-αPNTs) is simulated using molecular dynamics (MD). The proposed model is subjected to the axial loading and the effects of morphological parameters, such as the mono-vacancy defect and strain rate on the tensile behavior of the zigzag and armchair SW-αPNTs are studied as a pioneering work. In order to assess the accuracy of the MD simulations, the stress-strain response of the current MD model is successfully verified with the efficient quantum mechanical approach of the density functional theory (DFT). Along with reproducing the DFT results, the accurate MD simulations successfully anticipate a significant variation in the stress-strain curve of the zigzag SW-αPNTs, namely the knick point. Predicting such mechanical behavior of SW-αPNTs may be an important design factor for lithium-ion batteries, supercapacitors, and energy storage devices. The simulations show that the ultimate stress is increased by increasing the diameter of the pristine SW-αPNTs. The trend is identical for the ultimate strain and stress-strain slope as the diameter of the pristine zigzag SW-αPNTs enlarges. The obtained results denote that by increasing the strain rate, the ultimate stress/ultimate strain are respectively increased/declined. The stress-strain slope keeps increasing as the strain rate grows. It is worth noting that the existence of mono-atomic vacancy defects in the (12,0) zigzag and (0,10) armchair SW-αPNT structures leads to a drop in the tensile strength by amounts of 11.1% and 12.5%, respectively. Also, the ultimate strain is considerably altered by mono-atomic vacancy defects.

• Advances in nano research
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• v.15 no.5
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• pp.451-466
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• 2023

Gastrointestinal cancer (GC) is a prevalent malignant tumor of the digestive system that poses a severe health risk to humans. Due to the specific organ structure of the gastrointestinal system, both endoscopic and MRI diagnoses of GIC have limited sensitivity. The primary factors influencing curative efficacy in GIC patients are drug inefficacy and high recurrence rates in surgical and pharmacological therapy. Due to its unique optical features, good biocompatibility, surface effects, and small size effects, nanotechnology is a developing and advanced area of study for the detection and treatment of cancer. Because of its deep location and complex surgery, diagnosing and treating gastrointestinal cancer is very difficult. The early diagnosis and urgent treatment of gastrointestinal illness are enabled by nanotechnology. As diagnostic and therapeutic tools, nanoparticles directly target tumor cells, allowing their detection and removal. XGBoost was used as a classification method known for achieving numerous winning solutions in data analysis competitions, to capture nonlinear relations among many input variables and outcomes using the boosting approach to machine learning. The research sample included 300 GC patients, comprising 190 males (72.2% of the sample) and 110 women (27.8%). Using convolutional neural networks (CNN) and artificial neural networks (ANN)-EXtreme Gradient Boosting (XGBoost), the patients mean± SD age was 50.42 ± 13.06. High-risk behaviors (P = 0.070), age at diagnosis (P = 0.037), distant metastasis (P = 0.004), and tumor stage (P = 0.015) were shown to have a statistically significant link with GC patient survival. AUC was 0.92, sensitivity was 81.5%, specificity was 90.5%, and accuracy was 84.7 when analyzing stomach picture.

• Advances in nano research
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• v.15 no.4
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• pp.315-328
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• 2023

The main goal of the present study was to assess the effects of eggshell powder (ESP) and halloysite nanotubes (HNTs) on the mechanical properties of abaca fiber (AF)-reinforced natural composites. For this purpose, a limited number of indentation tests were first performed on the AF/polypropylene (PP) composites for different HNT and ESP loadings (0 wt.% ~ 6 wt.%), load amplitudes (150, 200, and 250 N), and two types of indenters (Vickers or conical). The Young's modulus, hardness and plasticity index of each specimen were calculated using the indentation test results and Oliver-Pharr method. The accuracy of the experimental results was confirmed by comparing the values of the Young's modulus obtained from the indentation test with the results of the conventional tensile test. Then, a feed-forward shallow artificial neural network (ANN) with high efficiency was trained based on the obtained experimental data. The trained ANN could properly predict the variations of the mentioned mechanical properties of AF/PP composites incorporated with different HNT and ESP loadings. Furthermore, the trained ANN demonstrated that HNTs increase the elastic modulus and hardness of the composite, while the incorporation of ESP reduces these properties. For instance, the Young's modulus of composites incorporated with 3 wt.% of ESP decreased by 30.7% compared with the pure composite, while increasing the weight fraction of ESP up to 6% decreased the Young's modulus by 34.8%. Moreover, the trained ANN indicated that HNTs have a more significant effect on reducing the plasticity index than ESP.

• Journal of Digital Policy
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• v.2 no.4
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• pp.33-39
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• 2023

With a continuous occurrence of right-turn traffic accidents at intersections, there is an increasing demand for measures to address these incidents. In response, a technology has been developed to detect the presence of pedestrians through object detection in CCTV footage at right-turn areas and display warning messages on the screen to alert drivers. The YOLO (You Only Look Once) model, a type of object detection model, was employed to assess the performance of object detection. An algorithm was also devised to address misidentification issues and generate warning messages when pedestrians are detected. The accuracy of recognizing pedestrians or objects and outputting warning messages was measured at approximately 82%, suggesting a potential contribution to preventing right-turn accidents

• Advances in nano research
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• v.16 no.4
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• pp.413-426
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• 2024

This paper investigates the dynamic behavior of a simply supported viscoelastic plate made of functionally graded carbon nanotube reinforced composite under dynamic loading. Carbon nanotubes are distributed in 5 different shapes: U, V, A, O and X, depending on the shape they form through the thickness of the plate. The displacement fields are derived in the Laplace domain using a higher-order shear deformation theory. Equations of motion are obtained through the application of the energy method and Hamilton's principle. The resulting equations of motion are solved using Navier's method. Transforming the Laplace domain displacements into the time domain involves Durbin's modified inverse Laplace transform. To validate the accuracy of the developed algorithm, a free vibration analysis is conducted for simply supported plate made of functionally graded carbon nanotube reinforced composite and compared against existing literature. Subsequently, a parametric forced vibration analysis considers the influence of various parameters: volume fractions of carbon nanotubes, their distributions, and ratios of instantaneous value to retardation time in the relaxation function, using a linear standard viscoelastic model. In the forced vibration analysis, the dynamic distributed load applied to functionally graded carbon nanotube reinforced composite viscoelastic plate is obtained in terms of double trigonometric series. The study culminates in an examination of maximum displacement, exploring the effects of different carbon nanotube distributions, volume fractions, and ratios of instantaneous value to retardation times in the relaxation function on the amplitudes of maximum displacements.

• Proceedings of the Korean Vacuum Society Conference
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• 2016.02a
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• pp.93-93
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• 2016

Large scale integrated circuits (LSIs) has been improved by the shrinkage of the circuit dimensions. The smaller chip sizes and increase in circuit density require the miniaturization of the line-width and space between metal interconnections. Therefore, an extreme precise control of the critical dimension and pattern profile is necessary to fabricate next generation nano-electronics devices. The pattern profile control of plasma etching with an accuracy of sub-nanometer must be achieved. To realize the etching process which achieves the problem, understanding of the etching mechanism and precise control of the process based on the real-time monitoring of internal plasma parameters such as etching species density, surface temperature of substrate, etc. are very important. For instance, it is known that the etched profiles of organic low dielectric (low-k) films are sensitive to the substrate temperature and density ratio of H and N atoms in the H2/N2 plasma [1]. In this study, we introduced a feedback control of actual substrate temperature and radical density ratio monitored in real time. And then the dependence of etch rates and profiles of organic films have been evaluated based on the substrate temperatures. In this study, organic low-k films were etched by a dual frequency capacitively coupled plasma employing the mixture of H2/N2 gases. A 100-MHz power was supplied to an upper electrode for plasma generation. The Si substrate was electrostatically chucked to a lower electrode biased by supplying a 2-MHz power. To investigate the effects of H and N radical on the etching profile of organic low-k films, absolute H and N atom densities were measured by vacuum ultraviolet absorption spectroscopy [2]. Moreover, using the optical fiber-type low-coherence interferometer [3], substrate temperature has been measured in real time during etching process. From the measurement results, the temperature raised rapidly just after plasma ignition and was gradually saturated. The temporal change of substrate temperature is a crucial issue to control of surface reactions of reactive species. Therefore, by the intervals of on-off of the plasma discharge, the substrate temperature was maintained within ${\pm}1.5^{\circ}C$ from the set value. As a result, the temperatures were kept within $3^{\circ}C$ during the etching process. Then, we etched organic films with line-and-space pattern using this system. The cross-sections of the organic films etched for 50 s with the substrate temperatures at $20^{\circ}C$ and $100^{\circ}C$ were observed by SEM. From the results, they were different in the sidewall profile. It suggests that the reactions on the sidewalls changed according to the substrate temperature. The precise substrate temperature control method with real-time temperature monitoring and intermittent plasma generation was suggested to contribute on realization of fine pattern etching.