• Journal of the Korean institute of surface engineering
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• v.54 no.5
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• pp.230-237
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• 2021

In this study, the influence of silicon contents on the microstructure, mechanical and tribological properties of Ti-Al-Si-N coatings were systematically investigated for application of cutting tools. The composition of the Ti-Al-Si-N coatings were controlled by different combinations of TiAl₂ and Ti₄Si composite target powers using an arc ion plating technique in a reactive gas mixture of high purity Ar and N₂ during depositions. Ti-Al-Si-N films were nanocomposite consisting of nanosized (Ti,Al,Si)N crystallites embedded in an amorphous Si₃N₄/SiO₂ matrix. The instrumental analyses revealed that the synthesized Ti-Al-Si-N film with Si content of 5.63 at.% was a nanocomposites consisting of nano-sized crystallites (5-7 nm in dia.) and a three dimensional thin layer of amorphous Si₃N₄ phase. The hardness of the Ti-Al-Si-N coatings also exhibited the maximum hardness value of about 47 GPa at a silicon content of ~5.63 at.% due to the microstructural change to a nanocomposite as well as the solid-solution hardening. The coating has a low friction coefficient of 0.55 at room temperature against an Inconel alloy ball. These excellent mechanical and tribological properties of the Ti-Al-Si-N coatings could help to improve the performance of machining and cutting tool applications.

• Korean Journal of Environmental Agriculture
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• v.40 no.2
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• pp.99-107
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• 2021

BACKGROUND: Pesticide uptake by a rotational crop after being used for the primary crop is a potential cause of violation against the pesticide law if the pesticide is not registered in the secondary crop. This study was conducted to investigate the plant back interval (PBI) of fluopyram for the rotational cultivation of radish. METHODS AND RESULTS: Two experimental approaches were performed the evaluation of residues in radish cultivated successively in soil 16 days after treated with fluopyram onto pepper plant (T1) and in radish cultivated in bare soil treated with fluopyram at PBI 30 and PBI 60 days (T2). A modified QuEChERS method coupled with LC/MS/MS analysis showed good linearity of matrix-matched standard calibration of fluopyram with the coefficient values of determination greater than 0.995. Recovery values at levels of 0.01, 0.05, 0.1 and 0.25 mg/kg ranged from average 84.9 to 117.6% with RSD less than 10%. Fluopyram residues in radish harvested from T1 and T2 were found as levels less than maximum residue limit. CONCLUSION: This study suggests 20~30 days as the PBI of fluopyram for the rotational cultivation of radish in the greenhouse soil treated with fluopyram used for pepper as the primary crop.

• Journal of Korean Academy of Nursing
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• v.49 no.1
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• pp.59-68
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• 2019

Purpose: This study evaluated the psychometric properties of the Korean version of Yale Food Addiction Scale for Children (YFAS-C). Methods: Participants were 419 young adolescent students (11~15 years old). The content validity of the expert group was calculated as the content validity index (CVI) after the translation and reverse translation process of the 25 items of the YFAS-C. The multitrait-multimethod matrix (MTMM) method was used to verify the construct validity; the generalized linear model (GLM) was used to evaluate the concurrent and incremental validity. Reliability was calculated as Kuder-Richardson-20 (KR-20) and Spearman-Brown coefficients. Results: The CVI of the 25 items was greater than the item-level CVI .80 and the scale-level CVI .90. The Korean version of YFAS-C had verified convergent validity in emotional eating and external eating and discriminant validity in restrained eating. In addition, it had verified concurrent validity in emotional eating and external eating. Finally the incremental validity of the Korean version of YFAS-C was statistically significant on BMI. Reliability was KR-20 ${\alpha}=.69$ and the Spearman-Brown coefficient was .64. Conclusion: The Korean version of YFAS-C is a valid and reliable scale for measuring the severity of food addiction; it can be a useful scale for preventing obesity by predicting food addiction early.

• Tribology and Lubricants
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• v.35 no.2
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• pp.87-93
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• 2019

This work aims to develop a dry lubricant for oilless bush, especially a solid lubricant, thereby creating a coating method with improved properties of anti-friction and load-carrying capacity without oil lubrication. In this work, spherical-shaped powders of thermosetting resin such as polyimide (PI) are mixed with a binder matrix obtained by mixing a fluorocarbon compound resin such as Polytetrafluoroethylene (PTFE) or Ethylene tetra fluoro ethylene (ETFE) with itself or with a non-fluorocarbon thermoplastic resin such as Polyether ether ketone (PEEK). And these dry lubricant mixtures are thickly coated (200-300 mm in the thickness) on the inner surface of the bush by using a wet-typed air-spray deposition method. It was found that the load-carrying capacity of the solid lubricant for excavator bush (60 mm in diameter) that operates under a high load condition (at 40 MPa) is greatly improved owing to the spherical-shaped powders of thermosetting resin. In addition, the coefficient of friction at the sliding surface is also reduced less than 0.1. Thick coating also lowers the contact stress at the edge of a bush that results in better tribological performances. The result suggests that the lubrication performance and durability life of the bush can be remarkably improved even without lubrication (oil or grease).

• Korean Journal of Environmental Agriculture
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• v.38 no.1
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• pp.1-9
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• 2019

BACKGROUND: Accurate and simple analytical method determining Fluxametamid residue was necessary in various food matrices. Additionally, fulfilment of the international guideline of Codex (Codex Alimentarius Commission CAC/GL 40) was required for the analytical method. In this study, we developed Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS) method to determine the Fluxametamid residue in foods. METHODS AND RESULTS: Fluxametamid was extracted with acetonitrile, partitioned and concentrated with dichloromethane. To remove the interferences, silica SPE cartridge was used before LC-MS/MS (Liquid Chromatography-Tandem Mass Spectrometry) analysis with $C_{18}$ column. Five agricultural commodities (mandarin, potato, soybean, hulled rice, and red pepper) were used as a group representative to verify the method. The liner matrix-matched calibration curves were confirmed with coefficient of determination ($r^2$) greater than 0.99 at calibration range of 0.001-0.25 mg/kg. The limits of detection and quantification were 0.001 and 0.005 mg/kg, respectively. Mean average accuracies were shown to be 82.24-115.27%. The precision was also shown to be less than 10% for all five samples. CONCLUSION: The method investigated in this study was suitable to the Codex guideline for the residue analysis. Thus, this method can be useful for determining the residue in various food matrices as routine analysis.

• Nuclear Engineering and Technology
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• v.53 no.3
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• pp.949-959
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• 2021

The current study aims to explore the shielding properties of multi-component borate-based glass series. Seven glass-samples with composition of (80-y)H₃BO₃-10ZnO-10Na₂O-yBaO where (y = 0, 5, 10, 15, 20, 25 and 30 mol.%) were synthesized by melt-quench method. Various shielding features for photons, neutrons, and protons were determined for all prepared samples. XCOM, Phy-X program, and SRIM code were performed to determine and explain several shielding properties such as equivalent atomic number, exposure build-up factor, specific gamma-ray constants, effective removal cross-section (Σ_R), neutron scattering and absorption, Mass Stopping Power (MSP) and projected range. The energy ranges for photons and protons were 0.015-15 MeV and 0.01-10 MeV, respectively. The mass attenuation coefficient (μ/ρ) was also determined experimentally by utilizing two radioactive sources (¹⁶⁶Ho and ¹³⁷Cs). Consistent results were obtained between experimental and XCOM values in determining μ/ρ of the new glasses. The addition of BaO to the glass matrix led to enhance the μ/ρ and specific gamma-ray constants of glasses. Whereas the remarkable reductions in Σ_R, MSP, and projected range values were reported with increasing BaO concentrations. The acquired results nominate the use of these glasses in different radiation shielding purposes.

• Korean Journal of Agricultural Science
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• v.47 no.4
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• pp.1109-1122
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• 2020

The aim of this study was to develop a marbling classification and prediction model using small parts of sirloin images based on a deep learning algorithm, namely, a convolutional neural network (CNN). Samples were purchased from a commercial slaughterhouse in Korea, images for each grade were acquired, and the total images (n = 500) were assigned according to their grade number: 1++, 1+, 1, and both 2 & 3. The image acquisition system consists of a DSLR camera with a polarization filter to remove diffusive reflectance and two light sources (55 W). To correct the distorted original images, a radial correction algorithm was implemented. Color images of sirloins of Hanwoo (mixed with feeder cattle, steer, and calf) were divided and sub-images with image sizes of 161 × 161 were made to train the marbling prediction model. In this study, the convolutional neural network (CNN) has four convolution layers and yields prediction results in accordance with marbling grades (1++, 1+, 1, and 2&3). Every single layer uses a rectified linear unit (ReLU) function as an activation function and max-pooling is used for extracting the edge between fat and muscle and reducing the variance of the data. Prediction accuracy was measured using an accuracy and kappa coefficient from a confusion matrix. We summed the prediction of sub-images and determined the total average prediction accuracy. Training accuracy was 100% and the test accuracy was 86%, indicating comparably good performance using the CNN. This study provides classification potential for predicting the marbling grade using color images and a convolutional neural network algorithm.

• Investigative Magnetic Resonance Imaging
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• v.25 no.2
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• pp.93-100
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• 2021

Purpose: (1) To evaluate the trabecular pattern at the femoral attachment of the posterior cruciate ligament (PCL) in patients with a PCL injury; (2) to analyze bone microarchitecture by applying gray level co-occurrence matrix (GLCM)-based texture analysis; and (3) to determine if there is a significant relationship between bone microarchitecture and posterior instability. Materials and Methods: The study included 96 patients with PCL tears. Trabecular patterns were evaluated on T2-weighted MRI qualitatively, and were evaluated by GLCM texture analysis quantitatively. The grades of posterior drawer test (PDT) and the degrees of posterior displacement on stress radiographs were recorded. The 96 patients were classified into two groups: acute and chronic injury. And 27 patients with no PCL injury were enrolled for control. Pearson's correlation coefficient and one-way ANOVA with Bonferroni test were conducted for statistical analyses. This protocol was approved by the Institutional Review Board. Results: A thick and anisotropic trabecular bone pattern was apparent in normal or acute injury (n = 57/61;93.4%), but was not prominent in chronic injury and posterior instability (n = 31/35;88.6%). Grades of PDT and degrees of posterior displacement on stress radiograph were not correlated with texture parameters. However, the texture analysis parameters of chronic injury were significantly different from those of acute injury and control groups (P < 0.05). Conclusion: The trabecular pattern and texture analysis parameters are useful in predicting posterior instability in patients with PCL injury. Evaluation of the bone microarchitecture resulting from altered biomechanics could advance the understanding of PCL function and improve the detection of PCL injury.

• Advances in aircraft and spacecraft science
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• v.8 no.4
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• pp.345-372
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• 2021

The analysis of nonlinear vibrations, buckling, post-buckling, flutter boundary determination and post-flutter behavior of a homogeneous curved plate assuming cylindrical bending is conducted in this article. Other assumptions include simply-supported boundary conditions, supersonic aerodynamic flow at the top of the plate, constant pressure conditions below the plate, non-viscous flow model (using first- and third-order piston theory), nonlinear structural model with large deformations, and application of mechanical and thermal loads on the curved plate. The analysis is performed with constant environmental indicators (flow density, heat, Reynolds number and Mach number). The material properties (i.e., coefficient of thermal expansion and modulus of elasticity) are temperature-dependent. The equations are derived using the principle of virtual displacement. Furthermore, based on the definitions of virtual work, the potential and kinetic energy of the final relations in the integral form, and the governing nonlinear differential equations are obtained after fractional integration. This problem is solved using two approaches. The frequency analysis and flutter are studied in the first approach by transferring the handle of ordinary differential equations to the state space, calculating the system Jacobin matrix and analyzing the eigenvalue to determine the instability conditions. The second approach discusses the nonlinear frequency analysis and nonlinear flutter using the semi-analytical solution of governing differential equations based on the weighted residual method. The partial differential equations are converted to ordinary differential equations, after which they are solved based on the Runge-Kutta fourth- and fifth-order methods. The comparison between the results of frequency and flutter analysis of curved plate is linearly and nonlinearly performed for the first time. The results show that the plate curvature has a profound impact on the instability boundary of the plate under supersonic aerodynamic loading. The flutter boundary decreases with growing thermal load and increases with growing curvature.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.131-138
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• 2022

Novel Coronavirus (COVID-19) is viewed as one of the main general wellbeing theaters on the worldwide level all over the planet. Because of the abrupt idea of the flare-up and the irresistible force of the infection, it causes individuals tension, melancholy, and other pressure responses. The avoidance and control of the novel Covid pneumonia have moved into an imperative stage. It is fundamental to early foresee and figure of infection episode during this troublesome opportunity to control of its grimness and mortality. The entire world is investing unimaginable amounts of energy to fight against the spread of this lethal infection. In this paper, we utilized machine learning and deep learning techniques for analyzing what is going on utilizing countries shared information and for detecting the climate factors that effect on spreading Covid-19, such as humidity, sunny hours, temperature and wind speed for understanding its regular dramatic way of behaving alongside the forecast of future reachability of the COVID-2019 around the world. We utilized data collected and produced by Kaggle and the Johns Hopkins Center for Systems Science. The dataset has 25 attributes and 9566 objects. Our Experiment consists of two phases. In phase one, we preprocessed dataset for DL model and features were decreased to four features humidity, sunny hours, temperature and wind speed by utilized the Pearson Correlation Coefficient technique (correlation attributes feature selection). In phase two, we utilized the traditional famous six machine learning techniques for numerical datasets, and Dense Net deep learning model to predict and detect the climatic factor that aide to disease outbreak. We validated the model by using confusion matrix (CM) and measured the performance by four different metrics: accuracy, f-measure, recall, and precision.