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10th IEEE Conference on Big Data Security on Cloud, BigDataSecurity 2024

作者： Liu, Jingnian Liang, Wei Chen, Yuxiang Jin, Kai Hunan University of Science and Technology Hunan Key Laboratory for Service Computing and Novel Software Technology School of Computer Science and Engineering Xiangtang China

ISBN: (纸本)9798350389524

Medical image anomaly detection refers to machine learning techniques to analyze and identify lesions and abnormalities in them. However, in medical images, anomaly samples are usually sparse, which can lead to supervised learning not being able to obtain sufficient training. While existing unsupervised learning is mainly based on reconstruction and generation as well as feature embedding, these methods do not take into account the problem of data type bias during domain migration and often face the problem of loose judgment boundaries. To this end, this paper proposes a novel unsupervised learning method, SyNet, based on noisy anomaly synthesis. First, the problem at domain migration is well solved by aggregating the range of features within the feature map, fusing the multiscale features at the intermediate level, and adding feature adapters. Then, anomaly samples are synthesized by adding noise in the feature space, which is more efficient and stable than generating samples in the image space. Finally, normal and abnormal data are distinguished by training the discriminator. In this paper, experiments are conducted on ISIC and brain MRI datasets, and SyNet achieves nearly 20% improvement in AUC, ACC and other metrics compared with the current mainstream methods, and also has good inference efficiency. © 2024 IEEE.

关键词： Anomaly detection

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In situ preparation of Ag@AgCl/Bio-veins composites and their photocatalytic activity and recyclability

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Frontiers of Chemical science and engineering 2023年第7期17卷 906-917页

作者： Min Zou Chao Tan Zhengqiu Yuan Ming Wu Jian Jian Lei Zhang Yan Zhang Zhou Ma Hu Zhou School of Resource&Environment and Safety Engineering Hunan University of Science and TechnologyXiangtan 411201China Key Laboratory of Theoretical Organic Chemistry and Functional Molecules Ministry of EducationFunctional Film Materials Engineering Research Center of Hunan ProvinceHunan Provincial Key Laboratory of Advanced Materials for New Energy Storage and ConversionSchool of Chemistry and Chemical EngineeringHunan University of Science and TechnologyXiangtan 411201China School of Information and Electrical Engineering Hunan University of Science and TechnologyXiangtan 411201China

The industrial application of nano-photocatalysts in wastewater treatment has been severely restricted for a long time due to their difficult separation,poor reusability,and low *** this work,a facile strategy was proposed to enhance the photocatalytic activity and recovery performance of Ag@AgCl *** veins(Bio-veins)with a unique 3D porous construction were used as carriers for the in-situ growth of Ag@AgCl *** electron microscopy results showed that the Ag@AgCl nanoparticles were uniformly loaded on the surface and interior of the Bio-veins,and the size of the Ag@AgCl nanoparticles immobilized on the Bio-veins(50–300 nm)was significantly smaller than Ag@AgCl obtained by the co-precipitation method(1–3μm).The Bio-veins played a vital role in the photocatalysis reaction *** degradation efficiency of the Ag@AgCl/Bio-veins(CI4)was up to 3.50 times as high as pure Ag@***,the composites also exhibited excellent recyclability and stability under both visible and solar *** work provided a suitable strategy for nano-photocatalysts for practical application and may also offer new possibilities for the high-value utilization of biomass materials.

关键词： Ag@AgCl biological veins photocatalytic activity recyclability

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Bi-directional Projection Framework for Fast Single Image Super Resolution

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Recent Patents on engineering 2024年第9期18卷 152-167页

作者： Zhou, Ying Zheng, Zhichao Sun, Quansen School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China School of Computer and Electronic Information/School of Artificial Intelligence Nanjing Normal University Nanjing China

Background: Collaborative Representation (CR) has been widely used in Single Image Super Resolution (SISR) with the assumption that Low-resolution (LR) and high-resolution (HR) features can be linearly represented by neighborhoods and share consistent CR coefficients. Numerous patents and journal papers have been published. However, this CR consistency does not hold in the reconstruction phase, which leads to degraded performance. Methods: To fulfill this gap, we propose a novel bi-directional projection model (BDPM) to establish a bi-directional mapping between LR and HR features without any consistency constraint. The multiple projection matrices are offline computed to reduce reconstruction time greatly. We further develop several strategies to extract features and group neighborhoods such that local structures can be preserved better. Results: Compared to the learning-based methods, BDPM is about 2 to 10 times faster and compared to the reconstruction-based methods, it is about 500 to 2,000 times faster. Conclusion: The empirical studies verify the effectiveness of BDPM and extensive experimental results demonstrate that BDPM achieves better SISR performance than many state-of-the-arts. © 2024 Bentham science Publishers.

关键词： Mapping

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Data-driven output regulation control for constrained linear systems

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science China(Information sciences) 2025年第3期68卷 338-353页

作者： Chaoyu XIA Yi DONG Chaoli WANG Shengyuan XU Shanghai Research Institute for Intelligent Autonomous Systems Tongji University College of Electronic and Information Engineering Shanghai Research Institute for Intelligent Autonomous SystemsTongji University Department of Control Science and Engineering School of Optical-Electrical and Computer EngineeringUniversity of Shanghai for Science and Technology Department of Automation Nanjing University of Science and Technology

This study introduces a data-driven approach for state and output feedback control addressing the constrained output regulation problem in unknown linear discrete-time systems. Our method ensures effective tracking performance while satisfying the state and input constraints, even when system matrices are not available. We first establish a sufficient condition necessary for the existence of a solution pair to the regulator equation and propose a data-based approach to obtain the feedforward and feedback control gains for state feedback control using linear programming. Furthermore, we design a refined Luenberger observer to accurately estimate the system state, while keeping the estimation error within a predefined set. By combining output regulation theory, we develop an output feedback control strategy. The stability of the closed-loop system is rigorously proved to be asymptotically stable by further leveraging the concept of λ-contractive sets.

关键词： output regulation constrained system data-driven.

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A hybrid memory architecture supporting fine-grained data migration

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Frontiers of computer science 2024年第2期18卷 31-41页

作者： Ye CHI Jianhui YUE Xiaofei LIAO Haikun LIU Hai JIN National Engineering Research Center for Big Data Technology and System Services Computing Technology and System LabCluster and Grid Computing LabSchool of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China Department of Computer Science Michigan Technological UniversityMichigan 49931USA

Hybrid memory systems composed of dynamic random access memory(DRAM)and Non-volatile memory(NVM)often exploit page migration technologies to fully take the advantages of different memory *** previous proposals usually migrate data at a granularity of 4 KB pages,and thus waste memory bandwidth and DRAM *** this paper,we propose Mocha,a non-hierarchical architecture that organizes DRAM and NVM in a flat address space physically,but manages them in a cache/memory *** the commercial NVM device-Intel Optane DC Persistent Memory Modules(DCPMM)actually access the physical media at a granularity of 256 bytes(an Optane block),we manage the DRAM cache at the 256-byte size to adapt to this feature of *** design not only enables fine-grained data migration and management for the DRAM cache,but also avoids write amplification for Intel Optane *** also create an Indirect Address Cache(IAC)in Hybrid Memory Controller(HMC)and propose a reverse address mapping table in the DRAM to speed up address translation and cache ***,we exploit a utility-based caching mechanism to filter cold blocks in the NVM,and further improve the efficiency of the DRAM *** implement Mocha in an architectural *** results show that Mocha can improve application performance by 8.2%on average(up to 24.6%),reduce 6.9%energy consumption and 25.9%data migration traffic on average,compared with a typical hybrid memory architecture-HSCC.

关键词： non-volatile memory hybrid memory system data migration fine-grained caching

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Effects of CeO_(2)Content on the Microstructure and Mechanical Properties of ZK60 Mg Alloy

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Acta Metallurgica Sinica(English Letters) 2025年第2期38卷 287-298页

作者： Wei Qiu Shuang-Long Li Zhao-Yuan Lu Sen-Mao Zhang Jian Chen Wei Chen Lang Gan Wei Li Yan-Jie Ren Jun Luo Mao-Hai Yao Wen Xie School of Energy and Power Engineering Changsha University of Science and TechnologyChangsha 410114China Key Laboratory of Energy Efficiency and Clean Utilization The Education Department of Hunan ProvinceChangsha University of Science and TechnologyChangsha 410114China School of Mechanical&Energy Engineering Zhejiang University of Science and TechnologyHangzhou 310023China Hunan Provincial Key Laboratory of Vehicle Power and Transmission System Hunan Institute of EngineeringXiangtan 411104China Hunan Rare Earth Metal Material Research Institute Institute of Rare Earth Light AlloysChangsha 410126China

This study primarily investigates the effect of CeO_(2)content on the microstructure and mechanical properties of ZK60 Mg *** results indicate that CeO_(2)can be reduced by Mg to elemental Ce,predominantly in the form of the Mg-Zn-Ce *** addition of CeO_(2)notably refines the grain size of as-cast ZK60 Mg alloy,with the Mg-Zn-Ce phase primarily distributed along grain *** extrusion,grain size increases and then decreases with increasing CeO_(2)content,while the dynamic recrystallization(DRX)fraction gradually *** behavior is chiefly attributed to the hindrance of the DRX process by a high density of second phases and the restriction of recrystallized grains growth by fine *** basal texture intensity increases progressively with the addition of CeO_(2).As the CeO_(2)content rises,the yield strength(YS)and elongation(EL)of the alloys show significant *** increase in YS is mainly due to the combined effects of grain refinement strengthening and dispersion *** contrast,the enhanced EL is closely related to the heterogeneous structure of the ***,the ZK60-1.2CeO_(2)alloy exhibits the ultimate tensile strength,YS and EL of 274 MPa,160 MPa and 17.3%,respectively.

关键词： Magnesium alloy Rare earth oxides Microstructure Mechanical property

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A hybrid blockchain and machine learning approach for intrusion detection system in Industrial Internet of Things

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Alexandria engineering Journal 2025年 127卷 619-627页

作者： Song, Wu Zhu, Xiangyuan Ren, Sheng Tan, Wenxue Peng, Yibo School of Computer and Electrical Engineering Hunan University of Arts and Science Hunan Changde415000 China Hunan Provincial Key Laboratory of Network Investigational Technology Hunan Police Academy Hunan Changsha410138 China

The Industrial Internet of Things (IIoT) is a key component of Industry 4.0, which enables manufacturing to be automated and data collected in real-time. Edge IoT devices are subject to cybersecurity threats and unauthorised access. Decentralisation and resource limitations of IIoT often prevent traditional security mechanisms from addressing these threats. Intrusion detection systems (IDSs), which are used to detect intrusions in IIoT environments, are presented in this paper as hybrid machine learning-blockchain approaches. Blockchain technology ensures data integrity, secures communication, and prevents unauthorised modifications through the proposed system. To reduce false positives and improve threat detection accuracy, XGBoost is able to reduce the number of false positives. Using the BOT-IoT dataset, the model is demonstrated to be superior to conventional intrusion detection systems. This approach ensures enhanced security and trustworthiness of IIoT networks by offering a scalable, efficient, and secure solution. © 2025

关键词： Industrial internet of things (IIoT)

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Prompt Learning for Few-Shot Question Answering via Self-Context Data Augmentation

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2025年第3期6卷 589-603页

作者： Qiu, Jian-Qiang Zhang, Chun-Yang Chen, C. L. Philip Fuzhou University College of Computer and Data Science Fuzhou350108 China South China University of Technology School of Computer Science and Engineering Guangzhou510006 China

Pretrained language models (PLMs) have shown remarkable performance on question answering (QA) tasks, but they usually require fine-tuning (FT) that depends on a substantial quantity of QA pairs. Therefore, improving the performance of PLMs in scenarios with only a small number of training examples, also known as a few-shot setting, is of great practical significance. Current mitigation strategies for the few-shot QA task largely rely on pretraining a QA task-specific language model from scratch, overlooking the potential of foundational PLMs to generate QA pairs, particularly in the few-shot setting. To address this issue, we propose a prompt-based QA data augmentation method aimed at automating the creation of high-quality QA pairs. It employs the PFT method, adapting the question generation process of PLMs to the few-shot setting. Additionally, we introduce a dynamic text filling training strategy. This strategy simulates the progressive human learning process, thereby alleviating overfitting of PLMs in the few-shot setting and enhancing their reasoning capability to tackle complex questions. Extensive experiments demonstrate that the proposed method outperforms existing approaches across various few-shot configurations. 2691-4581 © 2024 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See https://***/publications/rights/*** for more information.

关键词： Zero-shot learning

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Deep Learning Based Signal Detection for Quadrature Spatial Modulation System

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China Communications 2024年第10期21卷 78-85页

作者： Shu Dingyun Peng Yuyang Yue Ming Fawaz AL-Hazemi Mohammad Meraj Mirza School of Computer Science and Engineering Macao University of Science and TechnologyMacaoChina Department of Computer and Network Engineering University of JeddahSaudi Arabia Department of Computer Science College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif 21944Saudi Arabia

With the development of communication systems, modulation methods are becoming more and more diverse. Among them, quadrature spatial modulation(QSM) is considered as one method with less capacity and high efficiency. In QSM, the traditional signal detection methods sometimes are unable to meet the actual requirement of low complexity of the system. Therefore, this paper proposes a signal detection scheme for QSM systems using deep learning to solve the complexity problem. Results from the simulations show that the bit error rate performance of the proposed deep learning-based detector is better than that of the zero-forcing(ZF) and minimum mean square error(MMSE) detectors, and similar to the maximum likelihood(ML) detector. Moreover, the proposed method requires less processing time than ZF, MMSE,and ML.

关键词： bit error rate complexity deep learning quadrature spatial modulation

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Catalytic asymmetric(3+3)cycloaddition between different 2-indolylmethanols

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science China Chemistry 2024年第8期67卷 2629-2636页

作者： Tianzhen Li Sijia Liu Shufang Wu Qi Cheng Qun Chen Yinchun Jiao Yuchen Zhang Feng Shi School of Petrochemical Engineering School of Materials ScienceEngineeringChangzhou UniversityChangzhou 213164China Research Center of Chiral Functional Heterocycles School of Chemistry and Materials ScienceJiangsu Normal UniversityXuzhou 221116China School of Chemistry and Chemical Engineering Hunan University of Science and TechnologyXiangtan 411201China School of Chemistry and Chemical Engineering Henan Normal UniversityXinxiang 453007China

The catalytic asymmetric(3+3)cycloaddition between different 2-indolylmethanols has been established,in which a series of chiral indole-fused six-membered heterocycles were constructed in high yields with excellent *** work not only has established the first catalytic asymmetric cycloaddition between different 2-indolylmethanols but also provided a powerful strategy for constructing enantioenriched indole-fused six-membered ***,biological evaluation discovered some products with promising antitumor ***,theoretical calculations performed on the reaction pathway and activation mode provide an in-depth understanding of this catalytic asymmetric(3+3)cycloaddition among different 2-indolylmethanols,which will advance the understanding of the chemistry of indolylmethanols.

关键词： asymmetric organocatalysis chiral phosphoric acid cycloaddition enantioselectivity 2-indolylmethanol

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