Xi'an Jiaotong University

About: Xi'an Jiaotong University is a education organization based out in Xi'an, China. It is known for research contribution in the topics: Heat transfer & Dielectric. The organization has 85440 authors who have published 99682 publications receiving 1579683 citations. The organization is also known as: '''Xi'an Jiaotong University''' & Xi'an Jiao Tong University.

Constant Time Weighted Median Filtering for Stereo Matching and Beyond

Abstract: Despite the continuous advances in local stereo matching for years, most efforts are on developing robust cost computation and aggregation methods. Little attention has been seriously paid to the disparity refinement. In this work, we study weighted median filtering for disparity refinement. We discover that with this refinement, even the simple box filter aggregation achieves comparable accuracy with various sophisticated aggregation methods (with the same refinement). This is due to the nice weighted median filtering properties of removing outlier error while respecting edges/structures. This reveals that the previously overlooked refinement can be at least as crucial as aggregation. We also develop the first constant time algorithm for the previously time-consuming weighted median filter. This makes the simple combination ``box aggregation + weighted median'' an attractive solution in practice for both speed and accuracy. As a byproduct, the fast weighted median filtering unleashes its potential in other applications that were hampered by high complexities. We show its superiority in various applications such as depth up sampling, clip-art JPEG artifact removal, and image stylization.

A review of bio-oil production from hydrothermal liquefaction of algae

Abstract: Algae is generally regarded as the only source of renewable biodiesel that is capable of meeting the global demand for transport fuels. Hydrothermal liquefaction is the method of dissolving organic compounds in subcritical water at high ion product, which can accelerate the acid-catalyzed and hydrolytic decomposition of algal macromolecules. This promising process converts different algal strains with high moisture content to high bio-oil yields with lower coke and lower energy consumption in comparison to other methods. The properties of the resulting bio-oil are clearly affected by parameters such as temperature, reaction time, algae species, algae concentration, reaction atmosphere, and catalysts, in subcritical water reaction conditions. This paper will provide an extensive review of the updated results on the hydrothermal liquefaction of microalgae. Including summary on the conversion of major compounds in microalgae and products related to the process and the influences of reaction conditions, catalysts and hydrotreating with comparing the variation tendencies and main results reported.

Review of hydrogen production using chemical-looping technology

Abstract: Hydrogen is an attractive energy carrier due to its potentially high energy efficiency and low generation of pollutants, which can be used for transportation and stationary power generation. However, hydrogen is not readily available in sufficient quantities and the production cost is still high. Steam methane reforming (SMR) process is now the most widely used technology for H 2 production, but this process is complex and cannot get thorough carbon capture. Hydrogen production using chemical looping technology has received a great deal of attention in recent years because it can produce hydrogen with higher process efficiency and can capture carbon dioxide. Many researchers have carried out intensive research work on the hydrogen production processes using chemical looping technology. Based on the previous studies stated in the literature, the authors try to give an overview on the recent advances of two categories, chemical looping reforming (CLR) and chemical looping hydrogen production (CLH) processes. Besides, the characteristics of the processes are pointed out based on the comparison with the conventional SMR process. The existing technical problems and the aspects of future research of each approach are also summarized.

Deep learning Radiomics of shear wave elastography significantly improved diagnostic performance for assessing liver fibrosis in chronic hepatitis B: a prospective multicentre study

Abstract: Objective We aimed to evaluate the performance of the newly developed deep learning Radiomics of elastography (DLRE) for assessing liver fibrosis stages. DLRE adopts the radiomic strategy for quantitative analysis of the heterogeneity in two-dimensional shear wave elastography (2D-SWE) images. Design A prospective multicentre study was conducted to assess its accuracy in patients with chronic hepatitis B, in comparison with 2D-SWE, aspartate transaminase-to-platelet ratio index and fibrosis index based on four factors, by using liver biopsy as the reference standard. Its accuracy and robustness were also investigated by applying different number of acquisitions and different training cohorts, respectively. Data of 654 potentially eligible patients were prospectively enrolled from 12 hospitals, and finally 398 patients with 1990 images were included. Analysis of receiver operating characteristic (ROC) curves was performed to calculate the optimal area under the ROC curve (AUC) for cirrhosis (F4), advanced fibrosis (≥F3) and significance fibrosis (≥F2). Results AUCs of DLRE were 0.97 for F4 (95% CI 0.94 to 0.99), 0.98 for ≥F3 (95% CI 0.96 to 1.00) and 0.85 (95% CI 0.81 to 0.89) for ≥F2, which were significantly better than other methods except 2D-SWE in ≥F2. Its diagnostic accuracy improved as more images (especially ≥3 images) were acquired from each individual. No significant variation of the performance was found if different training cohorts were applied. Conclusion DLRE shows the best overall performance in predicting liver fibrosis stages compared with 2D-SWE and biomarkers. It is valuable and practical for the non-invasive accurate diagnosis of liver fibrosis stages in HBV-infected patients. Trial registration number NCT02313649; Post-results.

Cryptanalysis of a chaotic image encryption method

Abstract: The security of digital images attracts much attention recently, and many image encryption methods have been proposed. In IS-CAS2000, a new chaotic key-based algorithm (CKBA) for image encryption was proposed. This paper points out CKBA is very weak to the chosen/known-plaintext attack with only one plain-image, and its security to brute-force ciphertext-only attack is overestimated by the authors. That is to say, CKBA is not secure at all from cryptographic viewpoint. Some experiments are made to show the feasibility of the chosen/known-plaintext attack. We also discuss some remedies to the original scheme and their performance, and we find none of them can essentially improve the security of CKBA.