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3rd International Symposium on Advanced Material Research, ISAMR 2019

作者： Xie, Chao-Fan Huang, Rey-Chue Xu, Lin Zhang, Fuquan Xu, Lu-Xiong I-Shou University Department of Electrical Engineering Kaohsiung Taiwan Fuqing Branch of Fujian Normal University Electronic information and Engineering Institute FuQing FuZhouFuJian China Key Laboratory of Nondestructive Testing Fuqing Branch of Fujian Normal University FuQing FuZhouFuJian China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350121 China School of Software Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9783035714647

Chromatographic separation is an indispensable and important technology in the manufacturing process of chemical products and biomedicine. It uses the distribution differences of a compound in the stationary phase and mobile phase to achieve the separation of the mixture. It is of great value to study the separation process of substances by simulated moving bed chromatography. By digitally simulating the process of moving bed, we can observe the influence of parameter changes on substance analysis by chromatography, and then find out the law of substance separation, which can provide theoretical basis for scientific research of biopharmaceuticals. © 2020 Trans Tech Publications Ltd, Switzerland.

关键词： Separation

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Reproducibility Assessment of Magnetic Resonance Spectroscopy of Pregenual Anterior Cingulate Cortex across Sessions and Vendors via the Cloud Computing Platform CloudBrain-MRS

arXiv

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arXiv 2025年

作者： Chen, Runhan Lin, Meijin Chen, Jianshu Lin, Liangjie Wang, Jiazheng Li, Xiaoqing Wang, Jianhua Huang, Xu Qian, Ling Liu, Shaoxing Long, Yuan Guo, Di Qu, Xiaobo Han, Haiwei National Institute for Data Science in Health and Medicine Xiamen University Xiamen361102 China College of Ocean & Earth Sciences Xiamen University Xiamen361102 China Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance Xiamen University Xiamen361102 China Department of Electronic Science Xiamen University Xiamen361102 China Clinical and Technical Support Philips Healthcare Beijing100016 China School of Economics and Management Xiamen University of Technology Xiamen361024 China Department of Radiology The First Hospital Affiliated to Xiamen University Xiamen361003 China Software Technology Company Limited Suzhou215163 China School of Computer and Information Engineering Xiamen University of Technology Xiamen361024 China

Given the need to elucidate the mechanisms underlying illnesses and their treatment, as well as the lack of harmonization of acquisition and post-processing protocols among different magnetic resonance system vendors, this work is to determine if metabolite concentrations obtained from different sessions, machine models and even different vendors of 3 T scanners can be highly reproducible and be pooled for diagnostic analysis, which is very valuable for the research of rare diseases. Participants underwent magnetic resonance imaging (MRI) scanning once on two separate days within one week (one session per day, each session including two proton magnetic resonance spectroscopy (1H-MRS) scans with no more than a 5-minute interval between scans (no off-bed activity)) on each machine. were analyzed for reliability of within- and between sessions using the coefficient of variation (CV) and intraclass correlation coefficient (ICC), and for reproducibility of across the machines using correlation coefficient. As for within- and between- session, all CV values for a group of all the first or second scans of a session, or for a session were almost below 20%, and most of the ICCs for metabolites range from moderate (0.4≤ICC © 2025, CC BY.

关键词： Magnetic resonance imaging

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Paralle acceleration of multi-mode SAR imaging on GPU 5

Paralle acceleration of multi-mode SAR imaging on GPU

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IET International Radar Conference 2020, IET IRC 2020

作者： Bai, Lan Guo, Zhengwei Wang, Kuan Fu, Zewen College of Computer and Information Engineering Henan University Kaifeng475004 China Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng475004 China Henan Engineering Research Center of Intelligent Technology and Application Henan University Kaifeng475004 China

ISBN: (纸本)9781839535635

With the continuous expansion of the application field of multi-mode synthetic aperture radar (SAR) system, which can satisfy different imaging demands. In order to get SAR image, it is necessary to image the echo received by multi-mode SAR system. However, the huge computation of the imaging algorithm affects the processing efficiency of SAR system. The power of Graphics processing Unit (GPU) can suffice the increasing demands in processing, which has been used in many common areas. The acceleration effect of GPU is very obvious compared with Central processing Unit (CPU) platform. This paper proposed a Chirp Scaling acceleration algorithm based on GPU for multi-mode SAR, and comparison of computational time over traditional CPU and GPU platform. The experimental results shows that the GPU accelerated SAR imaging algorithm can achieve a good acceleration effect. © 2020 Institution of Engineering and technology. All rights reserved.

关键词： Program processors

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Adaptive Variational Mode Time-frequency Analysis of Ship Radiated Noise

Adaptive Variational Mode Time-frequency Analysis of Ship Ra...

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International Conference on information Science and Control Engineering (ICISCE)

作者： Haoyi Zhang Naveed Ur Rehman Junejo Weitao Sun Hailan Chen Jiaquan Yan Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou China Ilma University Karachi Pakistan School of Marine Science and Technology Northwestern Polytechnical University Xi’an China School of Science Jimei University Xiamen China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou China

In this paper, we have proposed a novel time-frequency analysis method implementing adaptive variational mode decomposition (AVMD) and Wigner-Ville Distribution (WVD) to visualize the local features of ship radiated noise. Unlike the traditional methods are invalid under low signal to noise ratio (SNR), the proposed method is suitable for constructing time-frequency (TF) image with the capability of mining the local feature information accurately. Firstly, we employ complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) on the raw signal to determine the numbers of variational modes which is equal to intrinsic mode functions (IMFs) numbers. Secondly, we perform VMD algorithm to extract the local features absolutely by decomposing the raw signal into IMFs, where we set the IMFs gained by CEEMDAN as the input parameter of VMD. Finally, we adopt Wigner-Ville distribution (WVD) to draw TF signatures of all the IMFs, then superpose them to reconstruct the objected signal that can solve the cross-item problem. We have conducted the comparative experiments by the real oceanic data. Under the different SNRs, we have verified the effectiveness and robustness of the proposed method, also obtained better performance in terms of resolution than compared algorithm.

关键词： Time-frequency analysis Image resolution Sea measurements Feature extraction Robustness Time measurement Noise robustness

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A novel ship detection method based on Gabor feature 5

A novel ship detection method based on Gabor feature

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IET International Radar Conference 2020, IET IRC 2020

作者： Chang, Jiahui Fu, Zewen Li, Ning Chang, Jike College of Computer and Information Engineering Henan University Kaifeng475004 China Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng475004 China Henan Engineering Research Center of Intelligent Technology and Application Henan University Kaifeng475004 China

ISBN: (纸本)9781839535635

Synthetic Aperture Radar (SAR) Systems can be used for discovery and surveillance. According to the current requirements, accurate ship detection is becoming more and more important. However, the accuracy of traditional ship detection algorithm is not satisfying in complex scene. As a consequence, this paper proposes a novel method for detecting ships within SAR imagery using Gabor feature and Two Parameter Constant False Alarm Rate (2P-CFAR) detection technique. First, feature extraction was performed by using Gabor filter. Then, combined with the extracted orientation feature, the ship recognition of SAR image is obtained by 2P-CFAR detector. Finally, false alarms among the candidate targets were removed by geometric features of the ships. To prove the rationality of this method, experiments were carried with two high-resolution Gaofen-3 satellite SAR images in open sea background. The experimental results show that the presented method has preferable performance in the accuracy of ship identification. © 2020 Institution of Engineering and technology. All rights reserved.

关键词： Synthetic aperture radar

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A Framework of Darknet Forensics

A Framework of Darknet Forensics

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作者： Leng Tao Yu Aimin Chinese Academy of Sciences Institute of Information Engineering University of Chinese Academy of Sciences School of Cyber Security Sichuan Police College Department of Computer Science and Technology Sichuan Police College Criminal Inspection Sichuan Provincial University Key Laboratory

The dark web market is full of illegal and criminal activities such as the sale of sensitive personal information, guns, drugs, and terrorist videos. Cybercriminals use The Onion Router(TOR) browser to enter the dark web for information publishing and trading. Because the onion router browser provides privacy protection and anonymity, it is widely used. This privacy protection mode has brought great challenges to network investigators. This article aims to detect the use of the latest Tor browser, compare and analyze the evidence information contained in the registry, memory images,hard disk files, and network data packets through forensic experiments. At the same time, it compares and analyzes the different access modes of the Tor browser, and collects and uses Tor browsing. Evidence of cybercrime committed by a device is helpful to the development of electronic data forensics analysis.

关键词： tor browser memory forensic network forensic artifacts

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Under-determined audio source separation using the convolutive narrowband approximation and flexible ℓ p regularizer

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Applied Acoustics 2025年 240卷

作者： Junjie Yang Liu Yang Yi Guo Yuan Xie Shengli Xie School of Automation Guangdong University of Technology Guangdong Key Laboratory of IoT Information Technology (GDUT) and Key Laboratory of Intelligent Information Processing and System Integration of IoT (GDUT) Ministry of Education Guangzhou 510006 China School of Computer Science and Cyber Engineering Guangzhou University Guangzhou 510006 China School of Computer Data and Mathematical Sciences Western Sydney University Parramatta 2150 NSW Australia Mechanical and Electrical Engineering Guangzhou University and Key Laboratory of Intelligent Detection and The Internet of Things in Manufacturing (GDUT) Ministry of Education Guangzhou 510006 China

Convolutive narrowband approximation (CNA) model is widely utilized in audio source separation, particularly in strongly reverberant scenarios. However, in under-determined audio source separation, the CNA model often faces a serious ill-conditioned inverse filtering problem due to its mixing matrices containing columns that approach zero. To mitigate this issue, a ℓ p regularizer-based approach is proposed in this paper, assuming mixing filters of CNA model are known or pre-estimated. First, the STFT mixture components of all frames at each frequency bin are concatenated into a long vector, and the CNA system is accordingly expanded to a block-circulant structured linear mixing model. Next, a maximum likelihood estimation, constrained by the proposed mixing model, is introduced to exploit the sparsity of STFT source components with the ℓ p regularizer, where these components are assumed to independently follow super-Gaussian distributions. Finally, an augmented Lagrange multiplier with efficient iterative strategy is developed to search for the suitable sparse solution. The proposed strategy with regularizer p can be flexibly selected in a range of ( 0 , 1 ] to achieve robustness and accuracy in performance. Experimental results in various under-determined cases demonstrate the superior performance of the proposed algorithm over state-of-the-art approaches.

关键词： Maximum likelihood estimation

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Image super-resolution quality assessment: Structural fidelity versus statistical naturalness

arXiv

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arXiv 2021年

作者： Zhou, Wei Wang, Zhou Chen, Zhibo Dept. of Electrical and Computer Engineering University of Waterloo WaterlooONN2L3G1 Canada CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei230027 China

Single image super-resolution (SISR) algorithms reconstruct high-resolution (HR) images with their low-resolution (LR) counterparts. It is desirable to develop image quality assessment (IQA) methods that can not only evaluate and compare SISR algorithms, but also guide their future development. In this paper, we assess the quality of SISR generated images in a two-dimensional (2D) space of structural fidelity versus statistical naturalness. This allows us to observe the behaviors of different SISR algorithms as a tradeoff in the 2D space. Specifically, SISR methods are traditionally designed to achieve high structural fidelity but often sacrifice statistical naturalness, while recent generative adversarial network (GAN) based algorithms tend to create more natural-looking results but lose significantly on structural fidelity. Furthermore, such a 2D evaluation can be easily fused to a scalar quality prediction. Interestingly, we find that a simple linear combination of a straightforward local structural fidelity and a global statistical naturalness measures produce surprisingly accurate predictions of SISR image quality when tested using public subject-rated SISR image datasets. Code of the proposed SFSN model is publicly available at https://***/weizhou-geek/SFSN. Copyright © 2021, The Authors. All rights reserved.

关键词： Generative adversarial networks

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Color space volume and superpixel based leukocyte image segmentation 10

Color space volume and superpixel based leukocyte image segm...

引用

10th International Conference on information technology in Medicine and Education, ITME 2019

作者： Zhou, Xiaogen Li, Zuoyong Wang, Chuansheng Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou China College of Mathematics and Computer Science Fuzhou University Fuzhou China School of Computer Science and Technology Harbin University of Science and Technology Harbin China

ISBN: (纸本)9781728139173

In this paper, we propose a novel method based on color space volume and multimodal histogram thresholding (MHT) for leukocyte segmentation in human blood smear images under the rapid staining condition. The proposed method first defines a new color space volume to highlight the leukocyte's nucleus region, and it then uses the MHT method to extract the nucleus. Then, the proposed method takes the central region in the superpixel segmentation result as an initial leukocyte region, and it then uses the MHT method to extract the leukocyte region. Finally, the cytoplasm is obtained by subtracting the nucleus region from the leukocyte region. Experimental results on a dataset containing 300 leukocyte images under rapid staining condition show that the proposed method provides a higher segmentation accuracy than the counterparts. © 2019 IEEE.

关键词： Superpixels

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Explainable medical visual question answering via chain of evidence

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Knowledge-Based Systems 2025年 324卷

作者： Chen Qiu Ke Huang Zhiqiang Xie Maofu Liu Jinguang Gu Xiaofen Zong School of Computer Science and Technology Wuhan University of Science and Technology Wuhan 430081 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan 430081 China Department of Psychiatry Renmin Hospital of Wuhan University Wuhan 430060 China

Medical Visual Question Answering (MedVQA) has delivered success in healthcare, aiming to answer questions about clinical findings from medical images. However, developing models that are evidence-based and can precisely interpret decision-making with medical knowledge remains a crucial objective. To address these challenges, we reframe the MedVQA problem as a task of generating evidence, which is intrinsically consistent with the medical diagnostic interaction process. We introduce Med-CoE, a framework that leverages the chain-of-thought capacity of LLMs along with medical knowledge sources to address the explanation gap in MedVQA tasks. Med-CoE establishes an evidence verification and interpretation mechanism under a three-stage training process with medical knowledge grounding. We pre-train our model on the PMC-OA corpus and generate auto-labeling Chain of Evidences via LLMs prompt and then fine-tune Med-CoE on two benchmarks. Experimental findings show that Med-CoE outperforms state-of-the-art methods by a large margin, e.g., 10.7% on direct-answer task of PMC-VQA and 4.0% on SLAKE.

关键词： Chain of evidence Large language model Medical visual question answering

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