• The Journal of the Acoustical Society of Korea
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• v.42 no.4
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• pp.357-363
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• 2023

In underwater signal processing, separating individual signals from mixed signals has long been a challenge due to low signal quality. The common method using Short-time Fourier transform for spectrogram analysis has faced criticism for its complex parameter optimization and loss of phase data. We propose a Triple-path Recurrent Neural Network, based on the Dual-path Recurrent Neural Network's success in long time series signal processing, to handle three-dimensional tensors from multi-channel sensor input signals. By dividing input signals into short chunks and creating a 3D tensor, the method accounts for relationships within and between chunks and channels, enabling local and global feature learning. The proposed technique demonstrates improved Root Mean Square Error and Scale Invariant Signal to Noise Ratio compared to the existing method.

• Imaging Science in Dentistry
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• v.53 no.4
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• pp.345-353
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• 2023

Purpose: The objective of this study was to propose a method for developing a clinical phantom to reproduce various diseases that are clinically prevalent in the field of dentistry. This could facilitate diverse clinical research without unnecessarily exposing patients to radiation. Materials and Methods: This study utilized a single dry skull, which was visually and radiographically examined to evaluate its condition. Existing lesions on the dry skull were preserved, and other relevant lesions were artificially created as necessary. These lesions were then documented using intraoral radiography and cone-beam computed tomography. Once all pre-existing and reproduced lesions were confirmed by the consensus of 2 oral and maxillofacial radiologists, the skull was embedded in a soft tissue substitute. To validate the process, cone-beam computed tomography scans and panoramic radiographs were obtained of the fabricated phantom. All acquired images were subsequently evaluated. Results: Most lesions could be identified on panoramic radiographs, although some sialoliths and cracked teeth were confirmed only through cone-beam computed tomographic images. A small gap was observed between the epoxy resin and the bone structures. However, 2 oral and maxillofacial radiologists agreed that this space did not meaningfully impact the interpretation process. Conclusion: The newly developed phantom has potential for use as a standardized phantom within the dental field. It may be utilized for a variety of imaging studies, not only for optimization purposes, but also for addressing other experimental issues related to both 2- and 3-dimensional diagnostic radiography.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.2
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• pp.311-326
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• 2024

The rapid development of neural network technology promotes the neural network model driven by big data to overcome the texture effect of complex objects. Due to the limitations in complex scenes, it is necessary to establish custom template matching and apply it to the research of many fields of computational vision technology. The dependence on high-quality small label sample database data is not very strong, and the machine learning system of deep feature connection to complete the task of texture effect inference and speculation is relatively poor. The style transfer algorithm based on neural network collects and preserves the data of patterns, extracts and modernizes their features. Through the algorithm model, it is easier to present the texture color of patterns and display them digitally. In this paper, according to the texture effect reasoning of custom template matching, the 3D visualization of the target is transformed into a 3D model. The high similarity between the scene to be inferred and the user-defined template is calculated by the user-defined template of the multi-dimensional external feature label. The convolutional neural network is adopted to optimize the external area of the object to improve the sampling quality and computational performance of the sample pyramid structure. The results indicate that the proposed algorithm can accurately capture the significant target, achieve more ablation noise, and improve the visualization results. The proposed deep convolutional neural network optimization algorithm has good rapidity, data accuracy and robustness. The proposed algorithm can adapt to the calculation of more task scenes, display the redundant vision-related information of image conversion, enhance the powerful computing power, and further improve the computational efficiency and accuracy of convolutional networks, which has a high research significance for the study of image information conversion.

• Advances in nano research
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• v.17 no.4
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• pp.385-399
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• 2024

NEMS (Nano-Electro-Mechanical Systems) devices play a significant role in the advancement of prosthetic hands due to their unique properties at the nanoscale. Their integration enhances the functionality, sensitivity, and performance of prosthetic limbs. Understanding the electro-thermal buckling behavior of such structures is crucial since they may be subjected to extreme heat. So, in this paper, the two-dimensional hyperbolic differential quadrature method (2D-HDQM) integrated with a four-variable refined quasi-3D tangential shear deformation theory (RQ-3DTSDT) in view of the trace of thickness stretching is extended to study electro-thermal buckling response of three-directional poroelastic FG (3D-PFG) circular sector nanoplate patched with piezoelectric layer. Aimed at discovering the real governing equations, coupled equations with the aid of compatibility conditions are employed. Regarding modeling the size-impacts, nonlocal refined logarithmic strain gradient theory (NRLSGT) with two variables called nonlocal and length scale factors is examined. Numerical experimentation and comparison are used to indicate the precision and proficiency related to the created procedure. After obtaining the outputs of the mathematics, an appropriate dataset is used for testing, training and validating of the artificial intelligence. In the results section will be discussed the trace associated with multiple geometrical and physical factors on the electro-thermal buckling performance of the current nanostructure. These findings are essential for the design and optimization of NEMS applications in various fields, including sensing, actuation, and electronics, where thermal stability is paramount. The study's insights contribute to the development of more reliable and efficient NEMS devices, ensuring their robust performance under varying thermal conditions.

• Journal of Web Engineering
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• v.21 no.3
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• pp.729-750
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• 2022

In general, the importance of 6DoF (degree of freedom) 3D (dimension) volumetric contents technology is emerging in 5G (generation) telepresence service, Web-based (WebGL) graphics, computer vision, robotics, and next-generation augmented reality. Since it is possible to acquire RGB images and depth images in real-time through depth sensors that use various depth acquisition methods such as time of flight (ToF) and lidar, many changes have been made in object detection, tracking, and recognition research. In this paper, we propose a method to improve the quality of 3D models for 5G telepresence by processing images acquired through depth and RGB cameras on a multi-view camera system. In this paper, the quality is improved in two major ways. The first concerns the shape of the 3D model. A method of removing noise outside the object by applying a mask obtained from a color image and a combined filtering operation to obtain the difference in depth information between pixels inside the object were proposed. Second, we propose an illumination compensation method for images acquired through a multi-view camera system for photo-realistic 3D model generation. It is assumed that the three-dimensional volumetric shooting is done indoors, and the location and intensity of illumination according to time are constant. Since the multi-view camera uses a total of 8 pairs and converges toward the center of space, the intensity and angle of light incident on each camera are different even if the illumination is constant. Therefore, all cameras take a color correction chart and use a color optimization function to obtain a color conversion matrix that defines the relationship between the eight acquired images. Using this, the image input from all cameras is corrected based on the color correction chart. It was confirmed that the quality of the 3D model could be improved by effectively removing noise due to the proposed method when acquiring images of a 3D volumetric object using eight cameras. It has been experimentally proven that the color difference between images is reduced.

• Journal of the Korean Society of Food Science and Nutrition
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• v.45 no.2
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• pp.261-268
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• 2016

This study was conducted to establish roasting conditions for optimization of Citri Unshii Pericarpium antioxidant activity using response surface methodology (RSM). A central composite design was applied to investigate the effects of two independent variables, namely roasting temperature ($40{\sim}100^{\circ}C$; $X_1$) and roasting time ($5{\sim}15min$; $X_2$), on responses such as electron donating ability ($Y_1$), total phenolic content ($Y_2$), total flavonoid content ($Y_3$), and hydroxyl radical scavenging activity ($Y_4$). The maximum electron donating ability was 72.38% at a roasting temperature of $71.12^{\circ}C$ and roasting time of 9.39 min. The maximum total phenolic content was 10.76 mg tannic acid equivalents/g at a roasting temperature of $69.71^{\circ}C$ and roasting time of 8.39 min. The maximum total flavonoid content was 105.99 mg quercetin equivalents/100 g at $72.54^{\circ}C$ and 8.64 min. The maximum hydroxyl radical scavenging activity was 60.33% at $68.97^{\circ}C$ and 9.84 min. Based on the superimposition of three dimensional RSM with respect to electron donating ability, total phenolic content, total flavonoid content, and hydroxyl radical scavenging activity under various conditions, optimum conditions were established as follows: roasting temperature of $70.90^{\circ}C$ and roasting time of 9.03 min.

• The Journal of Korean Society for Radiation Therapy
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• v.20 no.1
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• pp.11-15
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• 2008

Purpose: The goal of radiation treatment is to deliver a prescribed radiation dose to the target volume accurately while minimizing dose to normal tissues. In this paper, we comparing the dose distribution between three dimensional conformal radiation radiotherapy (3D-CRT) and helical tomotherapy (TOMO) plan for partial breast cancer. Materials and Methods: Twenty patients were included in the study, and plans for two techniques were developed for each patient (left breast:10 patients, right breast:10 patients). For each patient 3D-CRT planning was using pinnacle planning system, inverse plan was made using Tomotherapy Hi-Art system and using the same targets and optimization goals. We comparing the Homogeneity index (HI), Conformity index (CI) and sparing of the organs at risk for dose-volume histogram. Results: Whereas the HI, CI of TOMO was significantly better than the other, 3D-CRT was observed to have significantly poorer HI, CI. The percentage ipsilateral non-PTV breast volume that was delivered 50% of the prescribed dose was 3D-CRT (mean: 40.4%), TOMO (mean: 18.3%). The average ipsilateral lung volume percentage receiving 20% of the PD was 3D-CRT (mean: 4.8%), TOMO (mean: 14.2), concerning the average heart volume receiving 20% and 10% of the PD during treatment of left breast cancer 3D-CRT (mean: 1.6%, 3.0%), TOMO (mean: 9.7%, 26.3%) Conclusion: In summary, 3D-CRT and TOMO techniques were found to have acceptable PTV coverage in our study. However, in TOMO, high conformity to the PTV and effective breast tissue sparing was achieved at the expense of considerable dose exposure to the lung and heart.

• Investigative Magnetic Resonance Imaging
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• v.21 no.2
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• pp.65-70
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• 2017

Purpose: To optimize the saturation time and maximizing the pH-weighted difference between the normal and ischemic brain regions, on 3-tesla amide proton transfer (APT) imaging using an in vivo rat model. Materials and Methods: Three male Wistar rats underwent middle cerebral artery occlusion, and were examined in a 3-tesla magnetic resonance imaging (MRI) scanner. APT imaging acquisition was performed with 3-dimensional turbo spin-echo imaging, using a 32-channel head coil and 2-channel parallel radiofrequency transmission. An off-resonance radiofrequency pulse was applied with a Sinc-Gauss pulse at a $B_{1,rms}$ amplitude of $1.2{\mu}T$ using a 2-channel parallel transmission. Saturation times of 3, 4, or 5 s were tested. The APT effect was quantified using the magnetization-transfer-ratio asymmetry at 3.5 ppm with respect to the water resonance (APT-weighted signal), and compared with the normal and ischemic regions. The result was then applied to an acute stroke patient to evaluate feasibility. Results: Visual detection of ischemic regions was achieved with the 3-, 4-, and 5-s protocols. Among the different saturation times at $1.2{\mu}T$ power, 4 s showed the maximum difference between the ischemic and normal regions (-0.95%, P = 0.029). The APTw signal difference for 3 and 5 s was -0.9% and -0.7%, respectively. The 4-s saturation time protocol also successfully depicted the pH-weighted differences in an acute stroke patient. Conclusion: For 3-tesla turbo spin-echo APT imaging, the maximal pH-weighted difference achieved when using the $1.2{\mu}T$ power, was with the 4 s saturation time. This protocol will be helpful to depict pH-weighted difference in stroke patients in clinical settings.

• Journal of Environmental Impact Assessment
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• v.23 no.6
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• pp.432-444
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• 2014

When the water quality modelling is done with a manual calibration, it is possible that the researcher's opinion may affect the objectivity of the research. Hence, the role of the automatic calibration is highly important. This research applies a technique to automatically calibrate the water quality parameters by implementing an optimization method. This involves estimating the optimum water quality parameters targeting influential parameters towards the lake's BOD, DO, Phosphorus, Nitrogen and Phytoplankton. To accurately calculate the water temperature and hydraulic characteristics of a deep, stratifying lake, EFDC, a 3-dimensional hydraulic model which can be linked to the WASP7 was applied. With EFDC, the segment of the lake is formed and utilized as an input data of the WASP7. For the calibration of the water quality parameters of the WASP7, an influence coefficient algorithm and a genetic algorithm was applied. Of the five water quality variables for calibration, the normalized residuals of the observed and calculated values of DO, TN, CBOD were relatively small and the three water quality variables were calibrated properly. Yet the accuracy of the calibration of TP and Chl-a was relatively low.

• Analytical Science and Technology
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• v.24 no.6
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• pp.510-518
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• 2011

Recent developments and improvements of multiple technological elements including mass spectrometry (MS) instrument, multi-dimensional chromatographic separation, and software tools processing MS data resulted in benefits of large scale proteomics analysis. However, its throughput is limited by the speed and reproducibility of the protein digestion process. In this study, we demonstrated a new method for rapid proteolytic digestion of proteins using acoustic technology. Tryptic digests of BSA prepared at various conditions by super acoustic for optimization time and intensity were analyzed by LC-MS/MS showed higher sequence coverage in compared with traditional 16 hrs digestion method. The method was applied successfully for complex proteins of a breast cancer cells at 30 min of digestion at intensity 2. This new application reduces time-consuming of sample preparation with better efficiency, even with large amount of proteins, and increases high-throughput process in sample preparation state.