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Dual-stream coupling network with wavelet transform for cross-resolution person re-identification

Journal of Systems Engineering and Electronics 2023年第3期34卷 682-695页

作者： SUN Rui YANG Zi ZHAO Zhenghui ZHANG Xudong Key Laboratory of Knowledge Engineering with Big Data(Ministry of Education) Hefei University of TechnologyHefei 230601China School of Computer and Information Hefei University of TechnologyHefei 230601China

Person re-identification is a prevalent technology deployed on intelligent *** have been remarkable achievements in person re-identification methods based on the assumption that all person images have a sufficiently high resolution,yet such models are not applicable to the open *** real world,the changing distance between pedestrians and the camera renders the resolution of pedestrians captured by the camera *** low-resolution(LR)images in the query set are matched with high-resolution(HR)images in the gallery set,it degrades the performance of the pedestrian matching task due to the absent pedestrian critical information in LR *** address the above issues,we present a dualstream coupling network with wavelet transform(DSCWT)for the cross-resolution person re-identification ***,we use the multi-resolution analysis principle of wavelet transform to separately process the low-frequency and high-frequency regions of LR images,which is applied to restore the lost detail information of LR ***,we devise a residual knowledge constrained loss function that transfers knowledge between the two streams of LR images and HR images for accessing pedestrian invariant features at various *** qualitative and quantitative experiments across four benchmark datasets verify the superiority of the proposed approach.

关键词： cross-resolution feature invariant learning person re-identification residual knowledge transfer wavelet transform

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MeDict-GP: An Accurate Entity Recognition Model Combining Medical Domain Knowledge and Globalization Ideas 23

MeDict-GP: An Accurate Entity Recognition Model Combining Me...

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9th International Conference on Computing and Artificial Intelligence, ICCAI 2023

作者： Zhang, Yixuan Liu, Junzhen Lu, Wei Faculty of Data Science City University of Macau Macau China School of Aliyun Big Data Applications Zhuhai College of Science and Technology Zhuhai China

ISBN: (纸本)9781450399029

In order to extract medical terms from the vast amount of medical literature, such as diseases, treatment modalities, and drug names, clinical named entity recognition (CNER), a crucial step and foundation in medical natural language processing, aims to increase the effectiveness and caliber of clinical research. Medical named entity identification has given rise to a number of recognition models, however these algorithms struggle to recognize nested connections in medical texts and multilingual annotations in Mandarin and English. For this reason, we provide the sensible and precise MeDict-GP model, which fuses the lexicon with the globalization framework GlobalPointer to predict the labels and output the prediction sequences. It solely employs the medical domain as input to the lexicon embedding model. We discovered that the MeDict-GP model attained an F1-Score value of 68.171 percent in the assessment tests on the CMeEE medical dataset, an improvement of 1.17 percent compared to the manual annotation findings. We discovered through a series of comparative ablation experiments that adding domain lexicons and adversarial training can boost entity recognition accuracy. Our next step will be to investigate models that are more particular and have better capacity to demarcate entity borders because we also discovered that the models frequently failed to recognize certain medical entities. © 2023 Copyright held by the owner/author(s).

关键词： Clinical research

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AI-Enhanced Secure data Aggregation for Smart Grids with Privacy Preservation

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Computers, Materials & Continua 2025年第1期82卷 799-816页

作者： Congcong Wang Chen Wang Wenying Zheng Wei Gu School of Software Nanjing University of Information Science and TechnologyNanjing210044China School of Information Science and Engineering Zhejiang Sci-Tech UniversityHangzhou310018China State Key Laboratory of Public Big Data Guizhou UniversityGuiyang550025China School of Computer Science and Technology(School of Artificial Intelligence) Zhejiang Sci-Tech UniversityHangzhou310018China School of Computer Science(School of Cyber Science and Engineering) Nanjing University of Information Science and TechnologyNanjing210044China

As smart grid technology rapidly advances,the vast amount of user data collected by smart meter presents significant challenges in data security and privacy *** research emphasizes data security and user privacy concerns within smart ***,existing methods struggle with efficiency and security when processing large-scale *** efficient data processing with stringent privacy protection during data aggregation in smart grids remains an urgent *** paper proposes an AI-based multi-type data aggregation method designed to enhance aggregation efficiency and security by standardizing and normalizing various data *** approach optimizes data preprocessing,integrates Long Short-Term Memory(LSTM)networks for handling time-series data,and employs homomorphic encryption to safeguard user *** also explores the application of Boneh Lynn Shacham(BLS)signatures for user *** proposed scheme’s efficiency,security,and privacy protection capabilities are validated through rigorous security proofs and experimental analysis.

关键词： Smart grid data security privacy protection artificial intelligence data aggregation

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Formal Specification and Verification of API Security Based on Design by Contract 6

Formal Specification and Verification of API Security Based ...

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6th IEEE International Conference on Power, Intelligent Computing and Systems, ICPICS 2024

作者： Tang, Qing Zhou, Zetong Bu, Zhaoxiong Ma, Li Zhong, Yong Guangdong Chankong Big Data Technology Co. Ltd. Foshan China School of Management Guangdong University of Technology Foshan China School of Electronic and Information Engineering Foshan University Foshan China School of Electronic and Information Engineering Foshan University Zhixin Urban Big Data Technology Research Institute Foshan China School of Electronic and Information Engineering Foshan University Zhixin Urban Big Data Technology Research Institute Foshan Data Science Association Foshan China

ISBN: (纸本)9798350374315

The exploitation and hijacking of API vulnerabilities are becoming increasingly prominent issues in software supply chain security. This paper proposes an Object-Z based formal verification method for APIs in the supply chain, aiming to address the security risks associated with API applications. By incorporating the concept of design by contract and using Object-Z for formal modeling, a dynamic defense against API threats is implemented. Finally, based on a classification analysis of API threats in the supply chain, this paper presents a ase study through modeling and application analysis. © 2024 IEEE.

关键词： Formal specification

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An Improved Hard Thresholding Pursuit Algorithm for Compressive Sensing 3

An Improved Hard Thresholding Pursuit Algorithm for Compress...

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3rd International Conference on Consumer Electronics and Computer Engineering, ICCECE 2023

作者： Li, Qingliu Ren, Dandan Luo, Yuan School of Mathematics and Big Data Anhui University of Science and Technology Anhui Province Huainan China

ISBN: (纸本)9798350331578

The tail-?1 minimization model greatly improves the sparse signal recovery ability compared with ?1 minimization model. However, solving the tail-?1 minimization problem requires high computational cost and a lot of time. The hard thresholding pursuit (HTP) technology is attractive due to its computational efficiency in practice. Inspired by the HTP technology, the HTP technology is considered to be an efficient technique to solve the tail-?1 minimization problem. This paper introduces an improved HTP technology, namely tail-HTP. The tail-HTP technology retains the computational simplicity of the HTP technology and greatly improves the efficiency of solving the tail-?1 minimization problem. In addition, the tail-HTP technology also improves the sparse signal recovery ability of the HTP technology. The experimental results verify the high efficiency and superior sparse signal recovery ability of the tail-HTP technology. © 2023 IEEE.

关键词： Computational efficiency

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Integral experiment on slab^(nat)Pb using D-T and D-D neutron sources to validate evaluated nuclear data

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Nuclear science and Techniques 2025年第3期36卷 119-133页

作者： Kuo-Zhi Xu Yang-Bo Nie Chang-Lin Lan Yan-Yan Ding Shi-Yu Zhang Qi Zhao Xin-Yi Pan Jie Ren Xi-Chao Ruan Key Laboratory of Nuclear Data China Institute of Atomic EnergyBeijing 102413China School of Nuclear Science and Technology Lanzhou UniversityLanzhou 730000China

Lead(Pb)plays a significant role in the nuclear industry and is extensively used in radiation shielding,radiation protection,neutron moderation,radiation measurements,and various other critical ***,the measurement and evaluation of Pb nuclear data are highly regarded in nuclear scientific research,emphasizing its crucial role in the *** the time-of-flight(ToF)method,the neutron leakage spectra from three^(nat)Pb samples were measured at 60°and 120°based on the neutronics integral experimental facility at the China Institute of Atomic Energy(CIAE).The^(nat)Pb sample sizes were30 cm×30 cm×5 cm,30 cm×30 cm×10 cm,and 30 cm×30 cm×15 *** sources were generated by the Cockcroft-Walton accelerator,producing approximately 14.5 MeV and 3.5 MeV neutrons through the T(d,n)^(4)He and D(d,n)^(3)He reactions,*** neutron spectra were also calculated by employing the Monte Carlo code of MCNP-4C,and the nuclear data of Pb isotopes from four libraries:CENDL-3.2,JEFF-3.3,JENDL-5,and ENDF/B-Ⅷ.0 were used *** comparing the simulation and experimental results,improvements and deficiencies in the evaluated nuclear data of the Pb isotopes were *** of the calculated results were consistent with the experimental results;however,a few areas did not fit *** the(n,el)energy range,the simulated results from CENDL-3.2 were significantly overestimated;in the(n,inl)D and the(n,inl)C energy regions,the results from CENDL-3.2 and ENDF/B-Ⅷ.0 were significantly overestimated at 120°,and the results from JENDL-5 and JEFF-3.3 are underestimated at 60°in the(n,inl)D energy *** calculated spectra were analyzed by comparing them with the experimental spectra in terms of the neutron spectrum shape and C/E *** results indicate that the theoretical simulations,using different data libraries,overestimated or underestimated the measured values in certain energy *** neutron energies and angular distributions in

关键词： Integral experiment Neutron leakage spectra ^(nat)Pb D-T and D-D neutron sources Evaluated nuclear data

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Part-Whole Relational Few-Shot 3D Point Cloud Semantic Segmentation

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Computers, Materials & Continua 2024年第3期78卷 3021-3039页

作者： Shoukun Xu Lujun Zhang Guangqi Jiang Yining Hua Yi Liu School of Computer Science and Artificial Intelligence Aliyun School of Big Data and School of SoftwareChangzhou UniversityChangzhou213164China Department of Computer Science University of AberdeenKing’s CollegeAberdeenAB243FXUK

This paper focuses on the task of few-shot 3D point cloud semantic *** some progress,this task still encounters many issues due to the insufficient samples given,e.g.,incomplete object segmentation and inaccurate semantic *** tackle these issues,we first leverage part-whole relationships into the task of 3D point cloud semantic segmentation to capture semantic integrity,which is empowered by the dynamic capsule routing with the module of 3D Capsule Networks(CapsNets)in the embedding ***,the dynamic routing amalgamates geometric information of the 3D point cloud data to construct higher-level feature representations,which capture the relationships between object parts and their ***,we designed a multi-prototype enhancement module to enhance the prototype ***,the single-prototype enhancement mechanism is expanded to the multi-prototype enhancement version for capturing rich ***,the shot-correlation within the category is calculated via the interaction of different samples to enhance the intra-category *** studies prove that the involved part-whole relations and proposed multi-prototype enhancement module help to achieve complete object segmentation and improve semantic ***,under the integration of these two modules,quantitative and qualitative experiments on two public benchmarks,including S3DIS and ScanNet,indicate the superior performance of the proposed framework on the task of 3D point cloud semantic segmentation,compared to some state-of-the-art methods.

关键词： Few-shot point cloud semantic segmentation CapsNets

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Multi-media cleaning system based on tip-electrode optimisation and its application in energy efficient purification 4

Multi-media cleaning system based on tip-electrode optimisat...

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4th International Conference on New Energy and Power Engineering, ICNEPE 2024

作者： Liang, Tianyou Huang, Tingkun Liang, Baoer Zhu, Guanyu Liang, Yanchun Zhu, Tianyuan Zhuhai College of Science and Technology School of Computer Science Zhuhai China Zhuhai College of Science and Technology School of Life Science Zhuhai China Zhuhai College of Science and Technology School of Big Data Science Zhuhai China

ISBN: (纸本)9798331516086

In this paper, a multi-media cleaning system based on the optimisation of the tip electrode structure is developed, which significantly improves the electrochemical reaction efficiency and realises the efficient purification of air, water and industrial waste gas by adopting the carbon nanotube material and the design of awn-shaped tip electrode. The experimental results show that the system has low energy consumption, long service life and excellent purification performance, and is suitable for a variety of environmental treatment scenarios with broad application prospects. © 2024 IEEE.

关键词： Air cleaners

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Towards trustworthy blockchain systems in the era of “Internet of value”: development, challenges, and future trends

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science China(Information sciences) 2022年第5期65卷 250-260页

作者： Hai JIN Jiang XIAO National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and TechnologyHuazhong University of Science and Technology

Since the advent of cryptocurrencies such as Bitcoin, blockchain, as their underlying technologies,has drawn a massive amount of attention from both academia and the industry. This ever-evolving technology inherits the “genes” of distributed systems, offering significant advantages of immutability, transparency,auditability, and tamper-resistance. These benefits help blockchain re-establish public confidence, and hold the significant promise of reliable information sharing and value transfer. Therefore, blockchain has become the foundation of crucial strategic deployments in countries across the world, and the fundamental basis for building the next generation Web 3.0 — “Internet of value”. In this article, we will start with unraveling the essential ingredients of blockchain technology, and showing the characteristics of each of these ingredients in the context of distributed systems. We will then present the core technical challenges that need to be addressed prior to unleashing its full potential, including its performance, scalability, and cross-chain interoperability. Finally, we will introduce the recent developments of blockchain systems, and discuss the future trends of the blockchain ecosystem.

关键词： blockchain distributed systems internet of value challenges development

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FHO-based Hybrid Neural Networks for Short-Term Load Forecasting in Economic Dispatch of Power Systems

Journal of Network Intelligence

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Journal of Network Intelligence 2025年第1期10卷 262-284页

作者： Wei, Yi Wang, Chia-Hung Suo, Yi-Fan Zhao, Qi-Gen Yuan, Jin-Chen Chen, Shu-Meng College of Computer Science and Mathematics Fujian University of Technology Fuzhou350118 China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou350118 China

With the development of the smart grid era, the data volume of the power system on the user side is growing rapidly, and the dependence of citizens on electricity is increasing significantly. In this paper, we aim to maximize the benefits of both supply and demand in the power system, from two aspects: improving the accuracy of short-term load forecasting and optimizing the economic dispatch of the power system. Firstly, based on the analysis of electricity consumption data, an improved load forecasting method via hybrid neural network is proposed. After determining the prediction results of the proposed model, we solved a short-term economic dispatch problem with the objective function of minimizing the generation cost of the power system and constraints such as unit start-up and shutdown, to achieve optimization of economic dispatch. In this work, an improved hybrid neural network with Firehawk Optimization (FHO) algorithm is developed to improve the accuracy of the prediction model by optimizing hyperparameters such as input data, number of hidden layer neurons, and batch size. In a series of numerical experiments, the proposed method is compared with other well-known optimization algorithms, such as Particle Swarm Optimization (PSO), Grey Wolf Optimiser (GWO) and Wild Horse Optimisation (WHO). From the comparison results, it shows that our method acheives better performance evaluation, and also improves the prediction accuracy of neural network models. Based on the load forecasting results, we determine the optimal scheduling scheme for the combination of power supply units, which minimizes the load and achieves higher applicability. © 2025, Taiwan Ubiquitous Information CO LTD. All rights reserved.

关键词： economic dispatch problem electric load forecasting electric power system firehawk optimization algorithm smart power grids supply and demand sides

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