• 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.

• Imaging Science in Dentistry
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• v.47 no.3
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• pp.165-174
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• 2017

Purpose: This study was performed to investigate the influence of object shape and distance from the center of the image on the volumetric accuracy of cone-beam computed tomography (CBCT) scans, according to different parameters of tube voltage and current. Materials and Methods: Four geometric objects(cylinder, cube, pyramid, and hexagon) with predefined dimensions were fabricated. The objects consisted of Teflon-perfluoroalkoxy embedded in a hydrocolloid matrix (Dupli-Coe-Loid TM; GC America Inc., Alsip, IL, USA), encased in an acrylic resin cylinder assembly. An Alphard Vega Dental CT system (Asahi Roentgen Ind. Co., Ltd, Kyoto, Japan) was used to acquire CBCT images. OnDemand 3D (CyberMed Inc., Seoul, Korea) software was used for object segmentation and image analysis. The accuracy was expressed by the volume error (VE). The VE was calculated under 3 different exposure settings. The measured volumes of the objects were compared to the true volumes for statistical analysis. Results: The mean VE ranged from -4.47% to 2.35%. There was no significant relationship between an object's shape and the VE. A significant correlation was found between the distance of the object to the center of the image and the VE. Tube voltage affected the volume measurements and the VE, but tube current did not. Conclusion: The evaluated CBCT device provided satisfactory volume measurements. To assess volume measurements, it might be sufficient to use serial scans with a high resolution, but a low dose. This information may provide useful guidance for assessing volume measurements.

• Journal of the Korean Society for Nondestructive Testing
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• v.14 no.3
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• pp.151-156
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• 1994

Exertion has been made to develop high-temperature (about $250{\sim}650^{\circ}C$) immersion ultrasonic sensor for the visualization of objects, temperature measurement, dimensional check, or nondestructive testing of welds under liquid sodium. In this study, the feasibility of the ultrasonic sensor taking advantage of a strip waveguide was confirmed by water-experiment. The lowest order of antisymmetric Lamb wave was used in the frequency range with negligible dispersion. This plate wave was excited in the stainless steel strip waveguide of 1.0mm thickness and 13mm width by the comb-structure transducer of 2.3MHz frequency. Its attenuation coefficient was 1.2dB/m in air and 380dB/m in water. The signal to noise ratio of 25dB was obtained from a planar reflector 270mm away from the beam aperture of $13mm{\times}39mm$ size.

• Journal of Electrical Engineering and Technology
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• v.10 no.5
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• pp.2070-2076
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• 2015

Nano composite materials were multi-constituent combinations of nano dimensional phases with distinct differences in structure, chemistry and properties. Nano particles were less likely to create large stress concentrations and thereby can avoid the compromise of the material ductility while improve other mechanical properties. Corona discharge was an electrical discharge. The ionization of a fluid surrounding a conductor was electrically energized. This discharge would occur when the strength of the electric field around the conductor was high enough to form a conductive region, but not high enough to cause electrical breakdown or arcing to nearby objects. This paper shows all the studies done on the preparation of nano fillers. Special attention has given to the ACSR transmission line conductor, TiO₂ nano fillers and also to the evaluation of corona resistance on dielectric materials discussed in detail. The measurement of the dielectric properties of the nano fillers and the parameters influencing them were also discussed in the paper. Corona discharge test reveals that in 0%N ACSR sample corona loss was directly proportional to the applied line voltage. No significant change in corona loss between 0%N and 1%N. When TiO₂ nano filler concentration was increased up to 10%N fine decrement in corona loss was found when compared to base ACSR conductor, corona loss was decreased by 40.67% in 10%N ACSR sample. It was also found from the surface conditions test that inorganic TiO₂ nano filler increases the key parameters like tensile strength and erosion depth.

• The Bulletin of The Korean Astronomical Society
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• v.35 no.2
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• pp.84.1-84.1
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• 2010

Globular clusters (GCs) are known to be one of the oldest objects in the Milky Way. Therefore the dynamical informations of GCs are very important to understand the formation and evolution of our Galaxy. Motion of GCs in the halo of Galaxy can be traced by radial velocities of individual stars and proper motions of GCs. Measuring the radial velocities of stars in GCs has been challenging for decades because the brightness of stars (even for the brightest stars) in GCs are too faint (V>14) to measure the radial velocities. The available large telescopes (D>4m) enable us to observe the spectra of stars in the red giant branch of GCs, and it is now more plausible to measure the radial velocities of stars in GCs. On the contrary it is still very difficult to measure the sky-projected two-dimensional motion of GCs in Galaxy even with the large telescopes because the distance to GCs is quite large (~10kpc) compared to the spatial resolution of present-day large ground-based telescopes. Instruments on-board Hubble Space Telescope are ideal to study the proper motion of GCs thanks to their extremely high spatial resolution (~0.05arcsec). We report a study of proper motion of NGC 104, one of the most metal-rich Milky Way GCs, based-on archival images of NGC 104 observed using HST/ACS. Using the stars in Small Magellanic Cloud as reference coordinate, we are able to measure the proper motions of individual stars in NGC 104 with a high precision. We discuss the internal dynamics of stars in NGC 104 by comparing proper motion results based-on shorter (<1yr) and longer (~7yrs) time durations.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.10-16
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• 2022

As an important part of virtual production, In-camera VFX is the process of shooting actual objects and virtual three-dimensional backgrounds in real-time through computer graphics technology and display technology, and obtaining the final film. In the In-camera VFX process, there are currently only two types of medium used to undertake background imaging, LED wall and chroma key screen. Among them, the In-camera VFX based on LED wall realizes background imaging through LED display technology. Although the imaging quality is guaranteed, the high cost of LED wall increases the cost of virtual production. The In-camera VFX based on chroma key screen, the background imaging is realized by real-time keying technology. Although the price is low, due to the limitation of real-time keying technology and lighting conditions, the usability of the final picture is not high. The short-throw projection technology can compress the projection distance to within 1 meter and get a relatively large picture, which solves the problem of traditional projection technology that must leaving a certain space between screen and the projector, and its price is relatively cheap compared to the LED wall. Therefore, in the In-camera VFX process, short-throw projection technology can be tried to project backgrounds. This paper will analyze the principle of short-throw projection technology and the existing In-camera VFX solutions, and through the comparison experiments, propose a low-cost solution that uses short-throw projectors to project virtual backgrounds and realize the In-camera VFX process.

• Physical Therapy Korea
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• v.30 no.3
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• pp.174-183
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• 2023

Background: Office workers experience neck or back pain due to poor posture, such as flexed head and forward head posture, during long-term sedentary work. Posture correction is used to reduce pain caused by poor posture and ensures proper alignment of the body. Several assistive devices have been developed to assist in maintaining an ideal posture; however, there are limitations in practical use due to vast size, unproven long-term effects or inconsistency of maintaining posture alignment. We developed a headphone and necklace posture correction system (HANPCS) for posture correction using an inertial measurement unit (IMU) sensor that provides visual or auditory feedback. Objects: To demonstrate the test-retest reliability and concurrent validity of neck and upper trunk flexion measurements using a HANPCS, compared with a three-dimensional motion analysis system (3DMAS). Methods: Twenty-nine participants were included in this study. The HANPCS was applied to each participant. The angle for each action was measured simultaneously using the HANPCS and 3DMAS. The data were analyzed using the intraclass correlation coefficient (ICC) = [3,3] with 95% confidence intervals (CIs). Results: The angular measurements of the HANPCS for neck and upper trunk flexions showed high intra- (ICC = 0.954-0.971) and inter-day (ICC = 0.865-0.937) values, standard error of measurement (SEM) values (1.05°-2.04°), and minimal detectable change (MDC) values (2.92°-5.65°). Also, the angular measurements between the HANPCS and 3DMAS had excellent ICC values (> 0.90) for all sessions, which indicates high concurrent validity. Conclusion: Our study demonstrates that the HANPCS is as accurate in measuring angle as the gold standard, 3DMAS. Therefore, the HANPCS is reliable and valid because of its angular measurement reliability and validity.

• Journal of Broadcast Engineering
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• v.14 no.3
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• pp.322-331
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• 2009

This paper proposes an efficient data representation of stereo images using edge-based mesh optimization. Mash-based two dimensional warping for stereo images mainly depends on the performance of a node selection and a disparity estimation of selected nodes. Therefore, the proposed method first of all constructs the feature map which consists of both strong edges and boundary lines of objects for node selection and then generates a grid-based mesh structure using initial nodes. The displacement of each nodal position is iteratively estimated by minimizing the predicted errors between target image and predicted image after two dimensional warping for local area. Generally, iterative two dimensional warping for optimized nodal position required a high time complexity. To overcome this problem, we assume that input stereo images are only horizontal disparity and that optimal nodal position is located on the edge include object boundary lines. Therefore, proposed iterative warping method performs searching process to find optimal nodal position only on edge lines along the horizontal lines. In the experiments, we compare our proposed method with the other mesh-based methods with respect to the quality by using Peak Signal to Noise Ratio (PSNR) according to the number of nodes. Furthermore, computational complexity for an optimal mesh generation is also estimated. Therefore, we have the results that our proposed method provides an efficient stereo image representation not only fast optimal mesh generation but also decreasing of quality deterioration in spite of a small number of nodes through our experiments.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.12
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• pp.519-524
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• 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 Broadcast Engineering
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• v.26 no.6
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• pp.680-691
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• 2021

Due to the recent developments of attaining 3D contents by using devices such as 3D scanners, the diversity of the contents being used in AR(Augmented Reality)/VR(Virutal Reality) fields is significantly increasing. There are several ways to represent 3D data, and using point clouds is one of them. A point cloud is a cluster of points, having the advantage of being able to attain actual 3D data with high precision. However, in order to express 3D contents, much more data is required compared to that of 2D images. The size of data needed to represent dynamic 3D point cloud objects that consists of multiple frames is especially big, and that is why an efficient compression technology for this kind of data must be developed. In this paper, a motion estimation and compensation method for dynamic point cloud objects using 3D DCT is proposed. This will lead to switching the 3D video frames into I frames and P frames, which ensures higher compression ratio. Then, we confirm the compression efficiency of the proposed technology by comparing it with the anchor technology, an Intra-frame based compression method, and 2D-DCT based V-PCC.