• Nuclear Engineering and Technology
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• v.51 no.5
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• pp.1417-1427
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• 2019

In this study, we evaluated the performance of a commercial pixelated cadmium zinc telluride (CZT) detector for spectroscopy and identified its feasibility as a Compton camera for radiation monitoring in a nuclear power plant. The detection system consisted of a $20mm{\times}20mm{\times}5mm$ CZT crystal with $8{\times}8$ pixelated anodes and a common cathode, in addition to an application specific integrated circuit. The performance of the various radioisotopes $^{57}Co$, $^{133}Ba$, $^{22}Na$, and $^{137}Cs$ was evaluated. In general, the amplitude of the induced signal in a CZT crystal depends on the interaction position and material non-uniformity. To minimize this dependency, a drift time correction was applied. The depth of each interaction was calculated by the drift time and the positional dependency of the signal amplitude was corrected based on the depth information. After the correction, the Compton regions of each spectrum were reduced, and energy resolutions of 122 keV, 356 keV, 511 keV, and 662 keV peaks were improved from 13.59%, 9.56%, 6.08%, and 5%-4.61%, 2.94%, 2.08%, and 2.2%, respectively. For the Compton imaging, simulations and experiments using one $^{137}Cs$ source with various angular positions and two $^{137}Cs$ sources were performed. Individual and multiple sources of $^{133}Ba$, $^{22}Na$, and $^{137}Cs$ were also measured. The images were successfully reconstructed by weighted list-mode maximum likelihood expectation maximization method. The angular resolutions and intrinsic efficiency of the $^{137}Cs$ experiments were approximately $7^{\circ}-9^{\circ}$ and $5{\times}10^{-4}-7{\times}10^{-4}$, respectively. The distortions of the source distribution were proportional to the offset angle.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.6
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• pp.548-556
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• 2019

The purpose of this study is to analyze the impact of dietary lifestyles and demographic characteristics on the Brand image of restaurants with Nutritional labeling to provide basic marketing data for establishing differentiated Brand image strategies for restaurant businesses. To that end, the SPSS21.0 (ver.) program, frequency analysis, descriptive statistics, factor analysis, reliability analysis, correlation analysis, and multiple linear regression analysis were conducted to verify the hypothesis. As a result, the Brand image of restaurants with Nutritional labeling improved as the metropolitan area sought safety, non-capital area sought taste, males sought health, and females sought safety. In terms of age, it was analyzed that as more people in their 20s sought taste, those their 30s and 40s sought safety, and both married and unmarried people sought safety, the Brand image of restaurants with Nutritional labeling improved. In other words, it could be seen that people with Dietary lifestyles who pursued health and safety had positive images of restaurants with Nutritional labeling regardless of residential area, age, gender, marital status, or whether they had children.

• Korean Journal of Radiology
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• v.19 no.6
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• pp.1077-1088
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• 2018

Objective: To correlate CT parameters on detector-based dual-energy CT enterography (DECTE) with Crohn's disease activity index (CDAI) and externally validate quantitative CT parameters. Materials and Methods: Thirty-nine patients with CD were retrospectively enrolled. Two radiologists reviewed DECTE images by consensus for qualitative and quantitative CT features. CT attenuation and iodine concentration for the diseased bowel were also measured. Univariate statistical tests were used to evaluate whether there was a significant difference in CTE features between remission and active groups, on the basis of the CDAI score. Pearson's correlation test and multiple linear regression analyses were used to assess the correlation between quantitative CT parameters and CDAI. For external validation, an additional 33 consecutive patients were recruited. The correlation and concordance rate were calculated between real and estimated CDAI. Results: There were significant differences between remission and active groups in the bowel enhancement pattern, subjective degree of enhancement, mesenteric fat infiltration, comb sign, and obstruction (p < 0.05). Significant correlations were found between CDAI and quantitative CT parameters, including number of lesions (correlation coefficient, r = 0.573), bowel wall thickness (r = 0.477), iodine concentration (r = 0.744), and relative degree of enhancement (r = 0.541; p < 0.05). Iodine concentration remained the sole independent variable associated with CDAI in multivariate analysis (p = 0.001). The linear regression equation for CDAI (y) and iodine concentration (x) was y = 53.549x + 55.111. For validation patients, a significant correlation (r = 0.925; p < 0.001) and high concordance rate (87.9%, 29/33) were observed between real and estimated CDAIs. Conclusion: Iodine concentration, measured on detector-based DECTE, represents a convenient and reproducible biomarker to monitor disease activity in CD.

• Journal of Broadcast Engineering
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• v.23 no.6
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• pp.939-946
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• 2018

In this paper, we implement a viewer program that can monitor effectively using omni-directional images. The program consists of four modes: Normal mode, ROI(Region of Interest) mode, Tracking mode, and Auto-rotation mode, and the results for each mode is displayed simultaneously. In the normal mode, the wide angle image is rendered as a spherical image to enable pan, tilt, and zoom. In ROI mode, the area is displayed expanded by selecting an area. And, in Auto-rotation mode, it is possible to track the object by mapping the position of the object with the rotation angle of the spherical image to prevent the object from deviating from the spherical image in Tracking mode. Parallel programming for processing of multiple modes is performed to improve the processing speed. This has the advantage that various angles can be seen compared with surveillance system having a limited angle of view.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1445-1456
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• 2018

Environment perception and three-dimensional (3D) reconstruction tasks are used to provide unmanned ground vehicle (UGV) with driving awareness interfaces. The speed of obstacle segmentation and surrounding terrain reconstruction crucially influences decision making in UGVs. To increase the processing speed of environment information analysis, we develop a CPU-GPU hybrid system of automatic environment perception and 3D terrain reconstruction based on the integration of multiple sensors. The system consists of three functional modules, namely, multi-sensor data collection and pre-processing, environment perception, and 3D reconstruction. To integrate individual datasets collected from different sensors, the pre-processing function registers the sensed LiDAR (light detection and ranging) point clouds, video sequences, and motion information into a global terrain model after filtering redundant and noise data according to the redundancy removal principle. In the environment perception module, the registered discrete points are clustered into ground surface and individual objects by using a ground segmentation method and a connected component labeling algorithm. The estimated ground surface and non-ground objects indicate the terrain to be traversed and obstacles in the environment, thus creating driving awareness. The 3D reconstruction module calibrates the projection matrix between the mounted LiDAR and cameras to map the local point clouds onto the captured video images. Texture meshes and color particle models are used to reconstruct the ground surface and objects of the 3D terrain model, respectively. To accelerate the proposed system, we apply the GPU parallel computation method to implement the applied computer graphics and image processing algorithms in parallel.

• Current Optics and Photonics
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• v.3 no.3
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• pp.256-262
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• 2019

Extensive tumor resection accompanied by radiotherapy and chemotherapy is the standard of care for malignant gliomas. However, there is a significant obstacle to the complete resection of the tumor due to the difficulty of distinguishing tumor and normal brain tissue with a conventional surgical microscope. Recently, multiple studies have shown the possibility of fluorescence-guided surgery in malignant gliomas. The most used fluorescence dyes for brain tumor surgery are 5-aminolevulinic acid (5-ALA) and indocyanine green (ICG). In this paper, a new fluorescence guided operation system, which can detect both 5-ALA and ICG fluorescent images simultaneously, is presented. This operation system consists of light emitting diodes (LEDs) which emits 410 nm and 740 nm wavelengths. We have performed experiments on rats in order to verify the operation of the newly developed operation system. Oral administration and imaging were performed to observe the fluorescence of 5-ALA and ICG fluorescence in rats. When LEDs at wavelengths of 410 nm and 740 nm were irradiated on rats, 628 nm wavelength with a violet fluorescence color and 825 nm wavelength with a red fluorescence color were expressed in 5-ALA and ICG fluorescent material, respectively, thus we were able to distinguish the tumor tissues easily. Previously, due to the poor resolution of the conventional surgical microscope and the fact that the color of the vein is similar to that of the tumor, the tumor resection margin was not easy to observe, thus increasing the likelihood for cancer recurrence. However, when the tumor is observed through the fluorescence guided operation system, it is possible to easily distinguish the color with the naked eye and it can be completely removed. Therefore, it is expected that surgical removal of cancerous tumors will be possible and surgical applications and surgical microscopes for cancer tumor removal surgery will be promising in the future.

• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.1-14
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• 2021

Recently, crowdfunding platforms have received attention as one of the content investment platforms for the public. This research attempts to explore the influencing factors on the success of movie euqity crowdfunding project. We use 'number of texts', 'number of images', 'star influence power', 'IP-based movie project', 'movie production stage', 'box office prediction', 'investment capital ratio', 'amount of surplus available investment', 'profit calculation method' and 'minimum investment amount' as independent variables. And we examined how these factors affects the achievement rate of movie crowdfunding. As a result of multiple regression analysis, 'movie production stage', 'investment capital ratio', 'amount of surplus available investment' and 'profit calculation method' have a significant effect on the crowdfunding achievement rate. In addition, the results of this research can be used for reference when planning film crowdfunding projects.

• Journal of Broadcast Engineering
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• v.25 no.6
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• pp.882-897
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• 2020

Recently, the use of immersive media contents representing Panorama and 360° video is increasing. Since the viewing angle is limited to generate the content through a general camera, image stitching is mainly used to combine images taken with multiple cameras into one image having a wide field of view. However, if the parallax between the cameras is large, parallax distortion may occur in the stitched image, which disturbs the user's content immersion, thus an image stitching overcoming parallax distortion is required. The existing Seam Optimization based image stitching method to overcome parallax distortion uses energy function or object segment information to reflect the location information of objects, but the initial seam generation location, background information, performance of the object detector, and placement of objects may limit application. Therefore, in this paper, we propose an image stitching method that can overcome the limitations of the existing method by adding a weight value set differently according to the type of object to the energy value using object detection based on deep learning.

• Journal of Broadcast Engineering
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• v.25 no.6
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• pp.954-964
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• 2020

In immersive media, the most important factor that provides immersion is depth information. Therefore, it is essential to obtain high quality depth information in order to produce high quality immersive media. In this paper we propose an algorithm to improve depth map, considering the segmentation of images and the relationship between multiple views in multi-view systems. The proposed algorithm uses a super-pixel segmentation technique to divide the depth map of the reference view into several segments, and project each segment into adjacent view. Subsequently, the depth map of the adjacent view is improved using plane estimation using the information of the projected segment, and then reversed to the reference view. This process is repeated for several adjacent views to improve the reference depth map by updating the values of the improved adjacent views and the initial depth map of the reference view. Through simulation, the proposed algorithm is shown to surpass the conventional algorithm subjectively and objectively.

• Journal of the Institute of Convergence Signal Processing
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• v.21 no.4
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• pp.183-194
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• 2020

Recently, the number of hip dysplasia (DDH) that occurs during infant and child growth has been increasing. DDH should be detected and treated as early as possible because it hinders infant growth and causes many other side effects In this study, two modelling techniques were used for multiple training techniques. Based on the results after the first transformation, the training was designed to be possible even with a small amount of data. The vertical flip, rotation, width and height shift functions were used to improve the efficiency of the model. Adam optimization was applied for parameter learning with the learning parameter initially set at 2.0 x 10e-4. Training was stopped when the validation loss was at the minimum. respectively A novel image overlay system using 3D laser scanner and a non-rigid registration method is implemented and its accuracy is evaluated. By using the proposed system, we successfully related the preoperative images with an open organ in the operating room