• Journal of the Korean Society of Radiology
• /
• v.17 no.6
• /
• pp.835-841
• /
• 2023

The aim of this study is to evaluate the diagnostic ability of dual-energy computed tomography (DECT) for Composition determination of urinary stones in phantom model. Seventeen cases with urinary stones who underwent DECT were enrolled in the study. The composition of the urinary stones was extracted from the seventeen patients were analyzed with DECT in phantom model with fresh pork. The volume scan method using Dual-energy software was used and the scanned image sets were assessed. All 17 urinary stones of the phantom model were analyzed according to the stone composition using DE stone Analysis were divided into uric acid stones (n=6, 35.29%) and non-uric acid stones (n=11, 64.71%). These urinary stones were pathologically confirmed. The mean attenuation values of uric acid stones at 135 kV, 100 kV and 80 kV was 348.87 ± 166.37 HU, 345.33 ± 151.18 HU and 337.94 ± 172.77 HU, respectively. The mean attenuation values of non-uric acid stones at 135 kV, 100 kV and 80 kV was 551.93 ± 297.09 HU, 747.04 ± 351.31 HU and 958.19 ± 424.72 HU, respectively. At 80 kV, uric acid stones and non-uric acid stones showed significant difference in the attenuation values(P<0.05). The attenuation values of DECT could differentiate the compositions of urinary stones between uric acid and non-uric acid stones at 80 kV in phantom model.

• Journal of Venture Innovation
• /
• v.4 no.1
• /
• pp.67-86
• /
• 2021

The purpose of this study was to examine the effects of office workers' covert narcissism on organizational silence and identify the (Duel)mediation effects on fear of negative evaluation and the avoidance motivation. This study used a survey of 393 office workers to measure the covert narcissism, the organizational silence, the fear of negative evaluation and the avoidance motivation. The collected data were analyzed by IBM SPSS 23 and SPSS PROCESS macro in a Bootstrapping method. The result shows that the covert narcissism, the organizational silence, the fear of negative evaluation and the avoidance motivation have positive correlations. In addition, a simple regression analysis was used according to the research model and all of them showed adequate coefficient of determination between each variables. Next, the mediating model was verified by mediation of the fear of negative evaluation and the avoidance motivation. In the relationship between the covert narcissism and the organizational silence, the mediating effect of the fear of negative evaluation was not verified and the avoidance motive showed a partial mediating effect. Finally, in the relationship between the covert narcissism and the organizational silence, the fear of negative evaluation and the avoidance motivation were gradually mediated through the (Duel)mediation effects model, and the model was statistically significant. Through this study, The implications of this study were discussed, not only the limitations of the study but also the necessity of further research were discussed.

• KIPS Transactions on Software and Data Engineering
• /
• v.12 no.12
• /
• pp.519-524
• /
• 2023

In hashing-based image retrieval, the hash code of a manipulated image is different from the original image, making it difficult to search for the same image. This paper proposes and evaluates a self-supervised deephashing model that generates perceptual hash codes from feature information such as texture, shape, and color of images. The comparison models are autoencoder-based variational inference models, but the encoder is designed with a fully connected layer, convolutional neural network, and transformer modules. The proposed model is a variational inference model that includes a SimAM module of extracting geometric patterns and positional relationships within images. The SimAM module can learn latent vectors highlighting objects or local regions through an energy function using the activation values of neurons and surrounding neurons. The proposed method is a representation learning model that can generate low-dimensional latent vectors from high-dimensional input images, and the latent vectors are binarized into distinguishable hash code. From the experimental results on public datasets such as CIFAR-10, ImageNet, and NUS-WIDE, the proposed model is superior to the comparative model and analyzed to have equivalent performance to the supervised learning-based deephashing model. The proposed model can be used in application systems that require low-dimensional representation of images, such as image search or copyright image determination.

• Journal of the Korean Geotechnical Society
• /
• v.39 no.12
• /
• pp.37-46
• /
• 2023

Dynamic soil properties are essential factors for predicting the detailed behavior of the ground. However, there are limitations to gathering soil samples and performing additional experiments. In this study, we used an artificial neural network (ANN) to predict dynamic soil properties based on static soil properties. The selected static soil properties were soil cohesion, internal friction angle, porosity, specific gravity, and uniaxial compressive strength, whereas the compressional and shear wave velocities were determined for the dynamic soil properties. The Levenberg-Marquardt and Bayesian regularization methods were used to enhance the reliability of the ANN results, and the reliability associated with each optimization method was compared. The accuracy of the ANN model was represented by the coefficient of determination, which was greater than 0.9 in the training and testing phases, indicating that the proposed ANN model exhibits high reliability. Further, the reliability of the output values was verified with new input data, and the results showed high accuracy.

• The Journal of the Acoustical Society of Korea
• /
• v.28 no.7
• /
• pp.661-667
• /
• 2009

Trabecular-bone-mimicking phantoms consisting of parallel-nylon-wire arrays were used to investigate correlations of phase velocity and attenuation coefficient with structural properties in trabecular bone. Trabecular separation (Tb.Sp) of the 7 trabecular-bone-mimicking phantoms ranged from 300 to $900\;{\mu}m$ and volume fraction (VF) from 1.6% to 8.7%. Phase velocity and attenuation coefficient of the phantoms were measured by using a through-transmission method in water, with a matched pair of broadband unfocused transducers with a diameter of 12.7 mm and a center frequency of 1 MHz. Phase velocity and attenuation coefficient at 1 MHz decreased almost linearly with increasing Tb. Sp and increased almost linearly with increasing VF. The simple and multiple linear regression models with phase velocity and attenuation coefficient as independent vanables and Tb.Sp and VF as dependent variables demonstrated that the coefficients of determination for the prediction of VF were higher than those for the prediction of Tb.Sp. The results obtained in the trabecular-bone-mimicking phantoms consisting of parallel-nylon-wire arrays were consistent with those in human trabecular bone suggesting that the structural properties can be estimated from the measurements of phase velocity and attenuation coefficient in trabecular bone.

• The Journal of the Acoustical Society of Korea
• /
• v.28 no.4
• /
• pp.392-400
• /
• 2009

In this paper, we propose an effective speech reinforcement technique base on ITU-T G.729A CS-ACELP codec under the near-end background noise environments. In general, since the intelligibility of the far-end speech for the near-end listener is significantly reduced under near-end noise environments, we require a far-end speech reinforcement approach to avoid this phenomena. In contrast to the conventional speech reinforcement algorithm, we reinforce the excitation signal of the codec's parameters received from the far-end speech signal based on the G.729A speech codec under various background noise environments. Specifically, we first estimate the excitation signal of ambient noise at the near-end through the encoder of the G.729A speech codec, reinforcing the excitation signal of the far-end speech transmitted from the far-end. we specially propose a novel approach to directly reinforce the excitation signal of far-end speech signal based on the decoder of the G.729A. The performance of the proposed algorithm is evaluated by the CCR (Comparison Category Rating) test of the method for subjective determination of transmission quality in ITU-T P.800 under various noise environments and shows better performances compared with conventional SNR Recovery methods.

• Journal of the Korean GEO-environmental Society
• /
• v.25 no.2
• /
• pp.5-14
• /
• 2024

Reinforced concrete bridge decks are the first to be damaged by vehicle loads and rain infiltration. Concrete deterioration primarily occurs owing to the corrosion of rebars and other metal components by chlorides used for snow and ice melting. The structural condition and concrete deterioration of the bridge decks within the pavement were evaluated using ground-penetrating radar (GPR) survey data. To evaluate concrete deterioration in bridges, it is necessary to develop GPR data analysis techniques to accurately identify deteriorated locations and rebar positions. GPR exploration involves the acquisition of reflection and diffraction wave signals due to differences in radar wave propagation velocity in geotechnical media. Therefore, a full-waveform inversion (FWI) method was developed to evaluate the deterioration of reinforced concrete bridge decks by estimating the radar wave propagation velocity in geotechnical media using GPR data. Numerical experiments using a GPR velocity model confirmed the deterioration phenomena of bridge decks, such as concrete delamination and rebar corrosion, verifying the applicability of the developed technology. Moreover, using the synthetic GPR data, FWI facilitates the determination of rebar positions and concrete deterioration locations using inverted velocity images.

• Steel and Composite Structures
• /
• v.50 no.6
• /
• pp.705-720
• /
• 2024

Analyzing the collapse behavior of thin-walled steel structures holds significant importance in ensuring their safety and longevity. Geometric imperfections present on the surface of metal materials can diminish both the durability and mechanical integrity of steel shells. These imperfections, encompassing local geometric irregularities and deformations such as holes, cavities, notches, and cracks localized in specific regions of the shell surface, play a pivotal role in the assessment. They can induce stress concentration within the structure, thereby influencing its susceptibility to buckling. The intricate relationship between the buckling behavior of these structures and such imperfections is multifaceted, contingent upon a variety of factors. The buckling analysis of thin-walled steel shell structures, similar to other steel structures, commonly involves the determination of crucial material properties, including elastic modulus, shear modulus, tensile strength, and fracture toughness. An established method involves the emulation of distributed geometric imperfections, utilizing real test specimen data as a basis. This approach allows for the accurate representation and assessment of the diversity and distribution of imperfections encountered in real-world scenarios. Utilizing defect data obtained from actual test samples enhances the model's realism and applicability. The sizes and configurations of these defects are employed as inputs in the modeling process, aiding in the prediction of structural behavior. It's worth noting that there is a dearth of experimental studies addressing the influence of geometric defects on the buckling behavior of cylindrical steel shells. In this particular study, samples featuring geometric imperfections were subjected to experimental buckling tests. These same samples were also modeled using Finite Element Analysis (FEM), with results corroborating the experimental findings. Furthermore, the initial geometrical imperfections were measured using digital image correlation (DIC) techniques. In this way, the response of the test specimens can be estimated accurately by applying the initial imperfections to FE models. After validation of the test results with FEA, a numerical parametric study was conducted to develop more generalized design recommendations for the stainless-steel shell structures with the initial geometric imperfection. While the load-carrying capacity of samples with perfect surfaces was up to 140 kN, the load-carrying capacity of samples with 4 mm defects was around 130 kN. Likewise, while the load carrying capacity of samples with 10 mm defects was around 125 kN, the load carrying capacity of samples with 14 mm defects was measured around 120 kN.

• Korean Journal of Environmental Agriculture
• /
• v.36 no.3
• /
• pp.201-210
• /
• 2017

BACKGROUND: The current study was to monitor of 9 veterinary antibiotics (ceftiofur, clopidol, florfenicol, sulfamethazine, sulfamethoxazole, sulfathiazole, tetracycline, tiamulin, and tylosin) in manure using liquid chromatography-tandem mass spectrometry (LC-MS/MS) in positive and negative electrospray ionization mode. METHODS AND RESULTS: Sample preparation was carried out using Mcllvaine buffer and citrate salts to adjust the pH of the sample followed by purification with dispersive solid phase extraction (d-SPE). Separation of analytes during LC-MS/MS analysis was conducted using an Eclipse Plus $C_{18}$ column and the mobile phase was in gradient mode with, 0.1% formic acid and 5 mM ammonium formate in methanol (A) and 0.1% formic acid and 5 mM ammonium formate in distilled water (B). The linearity of the matrix-matched calibrations of all tested antibiotics was good, with $R^2$ determination coefficients ${\geq}0.9920$. The limit of detection (LOD) and quantifications (LOQ) were $0.1-67.0{\mu}g/kg$ and $0.4-200.0{\mu}g/kg$, respectively. Analysis of 13 solid and liquid manure samples taken from the Republic of Korea revealed concentrations less than $0.7{\mu}g/kg$ for tiamulin, $1497.6{\mu}g/kg$ for sulfamethazine. CONCLUSION: To monitor 9 veterinary antibiotics from manure samples in 13 provincial areas throughout the Republic of Korea, an analytical method was developed. The developed method was fully validated and successfully applied for monitoring various veterinary antibiotics in manure samples.

• Nuclear Medicine and Molecular Imaging
• /
• v.40 no.1
• /
• pp.33-39
• /
• 2006

Purpose: To determine appropriate sampling frequency and time of multiple blood sampling dual exponential method with $^{99m}Tc$-DTPA for calculating glomerular filtration rate (GFR). Materials & Methods: Thirty four patients were included in this study. Three mCi of $^{99m}Tc$-DTPA was intravenously injected and blood sampling at 9 different times, 5ml each, were done. Using the radioactivity of serum, measured by gamma counter, the GFR was calculated using dual exponential method and corrected with the body surface area. Using spontaneously chosen 2 data points of serum radioactivity, 15 collections of 2-sample GFR were calculated. And 10 collections of 3-sample GFR and 12 collections of 4-sample GFR were also calculated. Using the 9-sample GFR as a reference value, degree of agreement was analyzed with Kendall's $\tau$ correlation coefficients, mean difference and standard deviation. Results: Although some of the 2-sample GFR showed high correlation coefficient, over or underestimation had evolved as the renal function change. The 10-120-240 min 3-sample GFR showed a high correlation coefficient (${\tau}=0.93$), minimal difference ($Mean{\pm}SD=-1.784{\pm}3.972$), and no over or underestimation as the renal function changed. The 4-sample GFR showed no better accuracy than the 3-sample GFR. Conclusions: In the wide spectrum of renal function, the 10-120-240 min 3-sample GFC could be the best choice for estimating the patients' renal function.