The Experts below are selected from a list of 27240 Experts worldwide ranked by ideXlab platform
Hogyu Yoon - One of the best experts on this subject based on the ideXlab platform.
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minimizing Residual Images of amorphous indium gallium zinc oxide thin film transistor based flexible organic light emitting diode displays by controlling oxygen partial pressure
Journal of Nanoscience and Nanotechnology, 2020Co-Authors: Do Young Won, Hyunmin Kim, Manhcuong Nguyen, Rino Choi, Jae Min Myoung, Hogyu YoonAbstract:Plastic organic light emitting diode displays suffer from Residual Image, which is closely connected with the hysteresis of the driving thin-film transistor in the pixels. Therefore, in researching paper, we manufactured an OLED display comprise a polyimide substrate and an amorphous indium gallium zinc oxide thin film transistor active layer. Paper proposed a solution for reducing hysteresis through oxygen partial pressure control and evaluated it using hysteresis analysis. The results showed that hysteresis is strongly dependent on the threshold voltage is settled by the oxygen partial pressure while active layer deposition of the TFT. Moreover, hysteresis decreases with increasing temperature.
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Residual Image suppression through annealing process of amorphous indium gallium zinc oxide thin film transistor for plastic organic light emitting diode display
Journal of Nanoscience and Nanotechnology, 2020Co-Authors: Do Young Won, Hyunmin Kim, Manhcuong Nguyen, Rino Choi, Jae Min Myoung, Hogyu YoonAbstract:For the evaluation of the Residual Image suppression, the amorphous indium-gallium-zinc-oxide thin film transistor was manufactured with electric field shield metal on silicon oxide multi-buffer layer, without the need for a silicon crystallization process through the excimer laser process, and is advantageous for the manufacture of large-scale plastic organic light-emitting display. We conducted a study on the propensity to suppress a Residual Image according to the temperature of the annealing process in amorphous indium gallium zinc oxide. The evaluation divided by the ambient process temperature conditions to measure the change and restoration tendency of the gray current by the black/white current of thin film transistors, and for precise measurement of the current change intervals, the current was analyzed in 0.004 seconds per point. Through the study, Residual Image of amorphous Indium Gallium Zinc Oxide transistor was found to be suppressed as the temperature of the annealing crystallization increased from 250°C to 325°C, and there was no improvement effect on the 325°C or higher. The trend of threshold voltage shift of thin film transistors according to the two process temperature conditions, 250°C and 325°C, was analyzed by Two sample T analysis method, and the analysis confirmed that the trend of current deterioration is different through p-value 0.007.
Lei Xing - One of the best experts on this subject based on the ideXlab platform.
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a model based scatter artifacts correction for cone beam ct
Medical Physics, 2016Co-Authors: Wei Zhao, Don Vernekohl, Jun Zhu, Luyao Wang, Lei XingAbstract:Purpose: Due to the increased axial coverage of multislice computed tomography (CT) and the introduction of flat detectors, the size of x-ray illumination fields has grown dramatically, causing an increase in scatter radiation. For CT imaging, scatter is a significant issue that introduces shading artifact, streaks, as well as reduced contrast and Hounsfield Units (HU) accuracy. The purpose of this work is to provide a fast and accurate scatter artifacts correction algorithm for cone beam CT (CBCT) imaging. Methods: The method starts with an estimation of coarse scatter profiles for a set of CBCT data in either Image domain or projection domain. A denoising algorithm designed specifically for Poisson signals is then applied to derive the final scatter distribution. Qualitative and quantitative evaluations using thorax and abdomen phantoms with Monte Carlo (MC) simulations, experimental Catphan phantom data, and in vivo human data acquired for a clinical Image guided radiation therapy were performed. Scatter correction in both projection domain and Image domain was conducted and the influences of segmentation method, mismatched attenuation coefficients, and spectrum model as well as parameter selection were also investigated. Results: Results show that the proposed algorithm can significantly reduce scatter artifacts and recover the correct HU in either projection domain or Image domain. For the MC thorax phantom study, four-components segmentation yields the best results, while the results of three-components segmentation are still acceptable. The parameters (iteration number K and weight β) affect the accuracy of the scatter correction and the results get improved as K and β increase. It was found that variations in attenuation coefficient accuracies only slightly impact the performance of the proposed processing. For the Catphan phantom data, the mean value over all pixels in the Residual Image is reduced from −21.8 to −0.2 HU and 0.7 HU for projection domain and Image domain, respectively. The contrast of the in vivo human Images is greatly improved after correction. Conclusions: The software-based technique has a number of advantages, such as high computational efficiency and accuracy, and the capability of performing scatter correction without modifying the clinical workflow (i.e., no extra scan/measurement data are needed) or modifying the imaging hardware. When implemented practically, this should improve the accuracy of CBCT Image quantitation and significantly impact CBCT-based interventional procedures and adaptive radiation therapy.
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a model based scatter artifacts correction for cone beam ct
arXiv: Medical Physics, 2016Co-Authors: Wei Zhao, Don Vernekohl, Jun Zhu, Luyao Wang, Lei XingAbstract:The purpose of this work is to provide a fast and accurate scatter artifacts correction algorithm for cone beam CT (CBCT) imaging. The method starts with an estimation of coarse scatter profiles for a set of CBCT data in either Image domain or projection domain. A denoising algorithm designed specifically for Poisson signals is then applied to derive the final scatter distribution. Qualitative and quantitative evaluations using thorax and abdomen phantoms with Monte Carlo (MC) simulations, experimental Catphan phantom data, and in vivo human data acquired for a clinical Image guided radiation therapy were performed. Results show that the proposed algorithm can significantly reduce scatter artifacts and recover the correct HU in either projection domain or Image domain. For the MC thorax phantom study, four components segmentation yield the best results, while the results of three components segmentation are still acceptable. For the Catphan phantom data, the mean value over all pixels in the Residual Image is reduced from -21.8 HU to -0.2 HU and 0.7 HU for projection domain and Image domain, respectively. The contrast of the in vivo human Images are greatly improved after correction. The software-based technique has a number of advantages, such as high computational efficiency and accuracy, and the capability of performing scatter correction without modifying the clinical workflow or modifying the imaging hardware. When implemented practically, this should improve the accuracy of CBCT Image quantitation and significantly impact CBCT-based interventional procedures and adaptive radiation therapy.
F Ricci - One of the best experts on this subject based on the ideXlab platform.
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stormy weather in 3c 196 1 nuclear outbursts and merger events shape the environment of the hybrid radio galaxy 3c 196 1
The Astrophysical Journal, 2018Co-Authors: F Ricci, Lorenzo Lovisari, R P Kraft, F Massaro, A Paggi, E Liuzzo, G R Tremblay, W FormanAbstract:We present a multi-wavelength analysis based on archival radio, optical and X-ray data of the complex radio source 3C 196.1, whose host is the brightest cluster galaxy of a $z=0.198$ cluster. HST data show H$\alpha$+[N II] emission aligned with the jet 8.4 GHz radio emission. An H$\alpha$+[N II] filament coincides with the brightest X-ray emission, the northern hotspot. Analysis of the X-ray and radio Images reveals cavities located at galactic- and cluster- scales. The galactic-scale cavity is almost devoid of 8.4 GHz radio emission and the south-western H$\alpha$+[N II] emission is bounded (in projection) by this cavity. The outer cavity is co-spatial with the peak of 147 MHz radio emission, and hence we interpret this depression in X-ray surface brightness as being caused by a buoyantly rising bubble originating from an AGN outburst $\sim$280 Myrs ago. A \textit{Chandra} snapshot observation allowed us to constrain the physical parameters of the cluster, which has a cool core with a low central temperature $\sim$2.8 keV, low central entropy index $\sim$13 keV cm$^2$ and a short cooling time of $\sim$500 Myr, which is $<0.05$ of the age of the Universe at this redshift. By fitting jumps in the X-ray density we found Mach numbers between 1.4 and 1.6, consistent with a shock origin. We also found compelling evidence of a past merger, indicated by a morphology reminiscent of gas sloshing in the X-ray Residual Image. Finally, we computed the pressures, enthalpies $E_{cav}$ and jet powers $P_{jet}$ associated with the cavities: $E_{cav}\sim7\times10^{58}$ erg, $P_{jet}\sim1.9\times10^{44}$ erg s$^{-1}$ for the inner cavity and $E_{cav}\sim3\times10^{60}$ erg, $P_{jet}\sim3.4\times10^{44}$ erg s$^{-1}$ for the outer cavity.
Do Young Won - One of the best experts on this subject based on the ideXlab platform.
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minimizing Residual Images of amorphous indium gallium zinc oxide thin film transistor based flexible organic light emitting diode displays by controlling oxygen partial pressure
Journal of Nanoscience and Nanotechnology, 2020Co-Authors: Do Young Won, Hyunmin Kim, Manhcuong Nguyen, Rino Choi, Jae Min Myoung, Hogyu YoonAbstract:Plastic organic light emitting diode displays suffer from Residual Image, which is closely connected with the hysteresis of the driving thin-film transistor in the pixels. Therefore, in researching paper, we manufactured an OLED display comprise a polyimide substrate and an amorphous indium gallium zinc oxide thin film transistor active layer. Paper proposed a solution for reducing hysteresis through oxygen partial pressure control and evaluated it using hysteresis analysis. The results showed that hysteresis is strongly dependent on the threshold voltage is settled by the oxygen partial pressure while active layer deposition of the TFT. Moreover, hysteresis decreases with increasing temperature.
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Residual Image suppression through annealing process of amorphous indium gallium zinc oxide thin film transistor for plastic organic light emitting diode display
Journal of Nanoscience and Nanotechnology, 2020Co-Authors: Do Young Won, Hyunmin Kim, Manhcuong Nguyen, Rino Choi, Jae Min Myoung, Hogyu YoonAbstract:For the evaluation of the Residual Image suppression, the amorphous indium-gallium-zinc-oxide thin film transistor was manufactured with electric field shield metal on silicon oxide multi-buffer layer, without the need for a silicon crystallization process through the excimer laser process, and is advantageous for the manufacture of large-scale plastic organic light-emitting display. We conducted a study on the propensity to suppress a Residual Image according to the temperature of the annealing process in amorphous indium gallium zinc oxide. The evaluation divided by the ambient process temperature conditions to measure the change and restoration tendency of the gray current by the black/white current of thin film transistors, and for precise measurement of the current change intervals, the current was analyzed in 0.004 seconds per point. Through the study, Residual Image of amorphous Indium Gallium Zinc Oxide transistor was found to be suppressed as the temperature of the annealing crystallization increased from 250°C to 325°C, and there was no improvement effect on the 325°C or higher. The trend of threshold voltage shift of thin film transistors according to the two process temperature conditions, 250°C and 325°C, was analyzed by Two sample T analysis method, and the analysis confirmed that the trend of current deterioration is different through p-value 0.007.
Hui Huang - One of the best experts on this subject based on the ideXlab platform.
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etnet error transition network for arbitrary style transfer
arXiv: Computer Vision and Pattern Recognition, 2019Co-Authors: Chunjin Song, Yang Zhou, Minglun Gong, Hui HuangAbstract:Numerous valuable efforts have been devoted to achieving arbitrary style transfer since the seminal work of Gatys et al. However, existing state-of-the-art approaches often generate insufficiently stylized results under challenging cases. We believe a fundamental reason is that these approaches try to generate the stylized result in a single shot and hence fail to fully satisfy the constraints on semantic structures in the content Images and style patterns in the style Images. Inspired by the works on error-correction, instead, we propose a self-correcting model to predict what is wrong with the current stylization and refine it accordingly in an iterative manner. For each refinement, we transit the error features across both the spatial and scale domain and invert the processed features into a Residual Image, with a network we call Error Transition Network (ETNet). The proposed model improves over the state-of-the-art methods with better semantic structures and more adaptive style pattern details. Various qualitative and quantitative experiments show that the key concept of both progressive strategy and error-correction leads to better results. Code and models are available at this https URL.
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etnet error transition network for arbitrary style transfer
Neural Information Processing Systems, 2019Co-Authors: Chunjin Song, Yang Zhou, Minglun Gong, Hui HuangAbstract:Numerous valuable efforts have been devoted to achieving arbitrary style transfer since the seminal work of Gatys et al. However, existing state-of-the-art approaches often generate insufficiently stylized results under challenging cases. We believe a fundamental reason is that these approaches try to generate the stylized result in a single shot and hence fail to fully satisfy the constraints on semantic structures in the content Images and style patterns in the style Images. Inspired by the works on error-correction, instead, we propose a self-correcting model to predict what is wrong with the current stylization and refine it accordingly in an iterative manner. For each refinement, we transit the error features across both the spatial and scale domain and invert the processed features into a Residual Image, with a network we call Error Transition Network (ETNet). The proposed model improves over the state-of-the-art methods with better semantic structures and more adaptive style pattern details. Various qualitative and quantitative experiments show that the key concept of both progressive strategy and error-correction leads to better results. Code and models are available at https://github.com/zhijieW94/ETNet.
