• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.10
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• pp.1845-1852
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• 2008

The key elements of inter prediction are motion estimation(ME) and motion compensation(MC). Motion estimation is to find the optimum motion vectors, not only by using a distance criteria like the SAD, but also by taking into account the resulting number of 비트s in the 비트 stream. Motion compensation is compensate for movement of blocks of current frame. Inter-prediction Encoding is always the main bottleneck in high-quality streaming applications. Therefore, in real-time streaming applications, dedicated hardware for executing Inter-prediction is required. In this paper, we studied a motion estimator(ME) for H.264/AVC. The designed motion estimator is based on 2-D systolic array and it connects processing elements for fast SAD(Sum of Absolute Difference) calculation in parallel. By providing different path for the upper and lower lesion of each reference data and adjusting the input sequence, consecutive calculation for motion estimation is executed without pipeline stall. With data reuse technique, it reduces memory access, and there is no extra delay for finding optimal partitions and motion vectors. The motion estimator supports variable-block size and takes 328 cycles for macro-block calculation. The proposed architecture is local memory-free different from paper [6] using local memory. This motion estimation encoder can be applicable to real-time video processing.

• Smart Media Journal
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• v.12 no.1
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• pp.9-16
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• 2023

Recently, a convolutional neural network (CNN) based system is being developed to overcome the limitations of human resources in the apple quality classification of farmhouse. However, since convolutional neural networks receive only images of the same size, preprocessing such as sampling may be required, and in the case of oversampling, information loss of the original image such as image quality degradation and blurring occurs. In this paper, in order to minimize the above problem, to generate a image patch based graph of an original image and propose a random walk-based positional encoding method to apply the graph transformer model. The above method continuously learns the position embedding information of patches which don't have a positional information based on the random walk algorithm, and finds the optimal graph structure by aggregating useful node information through the self-attention technique of graph transformer model. Therefore, it is robust and shows good performance even in a new graph structure of random node order and an arbitrary graph structure according to the location of an object in an image. As a result, when experimented with 5 apple quality datasets, the learning accuracy was higher than other GNN models by a minimum of 1.3% to a maximum of 4.7%, and the number of parameters was 3.59M, which was about 15% less than the 23.52M of the ResNet18 model. Therefore, it shows fast reasoning speed according to the reduction of the amount of computation and proves the effect.

• Progress in Medical Physics
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• v.17 no.3
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• pp.173-178
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• 2006

The purpose of this study was to evaluate the radiation dose for clinical PET/CT protocols in clinical environments using Alderson phantom and TLDs. Radiation doses were evaluated for both Philips GEMINI 16 slice PET/CT system and GE DSTe 16 slice PET/CT system. Specific organ doses with $^{137}Cs$ transmission scan, high quality CT scan and topogram in philips GEMINI PET/CT system were measured. Specific organ doses with CT scan for attenuation map, CT scan for diagnosis and topogram in GE DSTe PET/CT system were also measured. The organs were selected based on ICRP60 recommendation. The TLDs used for measurements were selected for within an accuracy of ${\pm}5%$ and calibrated in 10 MV X-ray radiation field. The effective doses for $^{137}Cs$ transmission scan, high qualify scan, and topogram in Philips GEMINI PET/CT system were $0.14{\pm}0.950,\;29.49{\pm}1.508\;and\;0.72{\pm}0.032mSv$ respectively. The effective doses for CT scan to make attenuation map, CT scan to diagnose and topogram in GE DSTe PET/CT system were $20.06{\pm}1.003,\;24.83{\pm}0.805\;and\;0.27{\pm}0.008mSv$ respectively. We evaluated the total effective dose by adding effective dose for PET Image. The total PET/CT doses for Philips GEMINI PET/CT (Topogram+$^{137}Cs$ transmission scan+PET, Topogram+high qualify CT+PET) and GE DSTe PET/CT (Topogram +CT for attenuation map+ PET, Topogram+diagnostic CT+ PET) are $7.65{\pm}0.951,\;37.00{\pm}1.508,\;27.12{\pm}1.003\;and\;31.89{\pm}0.805mSv$ respectively. Further study may be needed to be peformed to find optimal PET/CT acquisition protocols for reducing the patient exposure with good image qualify.

• Journal of Korean Society for Geospatial Information Science
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• v.8 no.1 s.15
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• pp.51-63
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• 2000

Dynamic traffic assignment(DTA) has been a topic of substantial research during the past decade. While DTA is gradually maturing, many aspects of DTA still need improvement, especially regarding its formulation and solution algerian Recently, with its promise for In(Intelligent Transportation System) and GIS(Geographic Information System) applications, DTA have received increasing attention. This potential also implies higher requirement for DTA modeling, especially regarding its solution efficiency for real-time implementation. But DTA have many mathematical difficulties in searching process due to the complexity of spatial and temporal variables. Although many solution algorithms have been studied, conventional methods cannot iud the solution in case that objective function or constraints is not convex. In this paper, the genetic algorithm to find the solution of DTA is applied and the Merchant-Nemhauser model is used as DTA model because it has a nonconvex constraint set. To handle the nonconvex constraint set the GENOCOP III system which is a kind of the genetic algorithm is used in this study. Results for the sample network have been compared with the results of conventional method.

• Journal of the Korean Society of Radiology
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• v.17 no.3
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• pp.305-314
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• 2023

With the development of medical technology and radiation treatment equipment, the frequency of high-precision radiation therapy such as intensity modulation radiation therapy has increased. Image-guided radiation therapy has become essential for radiation therapy in precise and complex treatment plans. In particular, with the introduction of imaging equipment for diagnosis in a linear accelerator, CBCT scanning became possible, which made it possible to calibrate and correct the patient's posture through 3D images. Although more precise reproduction of the patient's posture has become possible, the exposure dose delivered to the patient during the image acquisition process cannot be ignored. Radiation optimization is necessary in the field of radiation therapy, and efforts to reduce exposure are necessary. However, when acquiring 3D CBCT images by changing the imaging conditions to reduce exposure, there should be no image quality or artefacts that would make it impossible to align the patient's position. In this study, Rando phantom was used to scan and evaluate images for each shooting condition. The highest SNR was obtained at 100 kV 80 mA 25 ms F1 filter 180°. As the tube voltage and tube current increased, the noise decreased, and the bowtie filter showed the optimal effect at high tube current. Based on the actual scanned images, it was confirmed that patient alignment was possible under all imaging conditions, and that image-guided radiation therapy for patient alignment was possible under the condition of 70 kV 10 mA 20 ms F0 filter 180°, which showed the lowest SNR. In this study, image evaluation was conducted according to the imaging conditions, and low tube voltage, tube current, and small rotation angle scan are expected to be effective in reducing radiation exposure. Based on this, the patient's exposure dose should be kept as low as possible during CBCT imaging.