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EDT-MTOS: An Edge Digital Twin Enabled VEC Multi-hop Collaborative Task Offloading Scheme

IEEE Internet of Things Journal 2025年

作者： Zhao, Xiaoyan Zhang, Jiale Wang, Chenyang Yuan, Peiyan Zhang, Junna Li, Xiangyang Henan Normal University School of Computer and Information Engineering Xinxiang453007 China Shenzhen University Guangdong Laboratory of Artificial Intelligence and Digital Economy College of Computer Science and Software Engineering Shenzhen518000 China University of Science and Technology of China School of Computer Science and Technology Hefei230026 China

Vehicle Edge Computing (VEC) can effectively improve the efficiency of vehicle task calculation and offloading by integrating edge computing and the Internet of Vehicles. However, current research in VEC mostly focuses on device collaboration within single-hop or two-hop ranges, limiting the additional performance gain and load balancing provided by multi-hop device collaboration. In this study, an Edge Digital Twin assisted Multi-hop Task Offloading Scheme (EDT_MTOS) is proposed to enhance the execution efficiency of vehicle tasks by establishing an edge digital twin layer for virtual mapping of vehicles and edge servers. Firstly, the multi-hop task offloading problem is transformed into a cost optimization problem related to delay and energy consumption under the constraint of load balancing. Secondly, a dynamic collaboration knowledge graph based on digital twin knowledge mapping is introduced to select collaborative device sets for the upload and return links within the multi-hop range. Then, a value iteration algorithm based on the maximum link quality is proposed to realize the dynamic collaboration knowledge graph. Furthermore, a task offloading solution algorithm is proposed based on Dynamic collaboration Knowledge Graph and Double Deep Q-Network (DKG_DDQN). Finally, the simulation results demonstrate that the proposed offloading algorithm can reduce vehicle task processing costs by 33.77% and 26.53% in an idle scenario, and by 27.60% and 26.21% in a busy scenario, compared to state-of-the-art collaborative algorithms such as COOR and DRL-COMV, respectively. © 2014 IEEE.

关键词： Edge computing

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Research on Ultrasound Image Based Prostate Cancer Auxiliary Diagnosis System

Research on Ultrasound Image Based Prostate Cancer Auxiliary...

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Image Processing, Electronics and computers (IPEC), Asia-Pacific Conference on

作者： Xueri Li Zhiyong Liu Lei Yang College of Computer Science Guangdong University of Science and Technology Dongguan China School of computer science Guangdong Polytechnic Normal University Guangzhou China

ISBN: (数字)9798350374407

ISBN: (纸本)9798350374414

Image processing technology has made remarkable breakthroughs in recent years, driven by both algorithms and computing power. Not only has the image quality achieved a qualitative leap, but also its application in the fields of medical image diagnosis, security monitoring and analysis has become more and more extensive, providing a strong support for the scientific and technological progress of the society and the convenience of daily life. Currently, Prostate cancer ranks as one of the most frequently occurring malignant tumours, and the study of prostate cancer ultrasound image-assisted diagnosis artificial intelligence system helps accurate diagnosis and timely treatment. The improved Mask R-CNN is used to accurately segment the prostate region from the background in ultrasound images of the prostate; then the background information is masked and multiple prostate ultrasound image datasets are constructed for use in the Inception-V3 network for image classification and detection. Compared with other detection methods, this method has higher accuracy. This study will effectively improve the efficiency of prostate cancer diagnosis work.

关键词： Image quality Image segmentation Ultrasonic imaging Accuracy Security Prostate cancer Monitoring Medical diagnostic imaging Tumors Image classification

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Image Enhancement and Deep Learning in Predicting the Gleason Score of Transcrectal Ultrasound Images of Prostate Cancer

Image Enhancement and Deep Learning in Predicting the Gleaso...

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Image Processing, Electronics and computers (IPEC), Asia-Pacific Conference on

作者： Xueri Li Zhiyong Liu Lei Yang Department of Computer Science Guangdong University of Science and Technology Dongguan China School of computer science Guangdong Polytechnic Normal University Guangzhou China

ISBN: (数字)9798350374407

ISBN: (纸本)9798350374414

The Gleason grading system for prostate cancer offers a crucial point of reference for clinical evaluation of available treatment alternatives. However, there are few studies on pathological grading of prostate cancer ultrasound images, and how to accurately describe its aggressiveness is a hot issue. Therefore, this paper proposes a deep learning-based network model for Gleason grading of prostate cancer. The model consists of three modules: lesion region labelling, image enhancement, and pathological grading. Specifically, the model firstly uses the improved S-Mask R-CNN network model to label the prostate cancer lesion region, then performs image enhancement by morphological image processing and PCNN algorithm, and finally performs pathological grading of prostate ultrasound images using Xception. The experimental results on the prostate ultrasound image dataset collected in the hospital show that the prediction accuracy of the Gleason grading model in this paper is higher than that of other classical grading models and manual diagnosis by doctors.

关键词： Deep learning Pathology Ultrasonic imaging Accuracy Hospitals Predictive models Lesions Prostate cancer Image enhancement Medical diagnostic imaging

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Impact frequency variation of self-excited oscillation pulsed supercritical carbon dioxide jets

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Petroleum Exploration and Development 2023年第5期50卷 1261-1268页

作者： SHEN Helian LIU Yong WEI Jianping QIU Liming LI Haichao DENG Yujie State Key Laboratory Cultivation Base for Gas Geology and Gas Control Henan Polytechnic UniversityJiaozuo 454000China State Collaborative Innovation Center of Coal Work Safety and Clean-Efficiency Utilization Jiaozuo 454000China School of Civil and Resource Engineering University of Science and Technology BeijingBeijing 100083China

In order to obtain the impact frequency of resonant coal breaking by self-excited oscillation pulsed supercritical carbon dioxide(SC-CO_(2))jet,large eddy simulation was used to analyze the formation and development process of self-excited oscillation pulsed SC-CO_(2)jet,the variation of jet impact frequency in the nozzle and the free flow field,and the variation of jet impact frequency at different positions in the jet axis and under different cavity *** test device of jet impact frequency was developed,and experiments were performed to verify the conclusions of the numerical *** results show that the frequency of the self-excited oscillation pulsed SC-CO_(2)jet is different in the nozzle and the free flow *** the nozzle,the frequency generated by the fluid disturbance is the same,and the jet frequency at the exit of the nozzle is consistent with that inside the *** the free flow field,due to the compressibility of CO_(2),the pressure,velocity and other parameters of SC-CO_(2)jets have obvious fluctuation *** feature causes the impact frequency of the self-excited oscillation pulsed SC-CO_(2)jet to decrease gradually in the *** the cavity length allows the adjustment of the jet impact frequency in the free flow field by affecting the disturbance frequency of the self-excited oscillation pulsed SC-CO_(2)jet inside the nozzle.

关键词： self-excited oscillation plused SC-CO_(2)jet resonant coal-breaking jet impact frequency cavity length

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The Conversion of Biowaste and Residue to Biofuel:From History,Physics Principles,to the Current Status of technology,Mitigation of Environmental Impact and Economic Challenges

The Conversion of Biowaste and Residue to Biofuel:From Histo...

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作者： Kewei Chen Ziyu Rui Chenyang Xu Zeqi Huang The Hong Kong Polytechnic University Hangzhou High School Henan University of Science and Technology

As the most commonly-used renewable energy in the world energy consumption,the potential and popularity of biomass energy is significantly *** the United States in 2018,renewable energy accounted for 11% of the national energy consumption,with 44.5%contributed by biomass *** article will focus on one feedstock,bio-waste and residue,in biomass ***,this journal will include an overview of the history of the technique,explanation of the fundamental physical principles,along with the discussions regarding major technology implementation of the conversion technique,and finally end with an evaluation of the environmental impacts and economic opportunities and *** the end of the journal,we will show that the development of bio-waste and residue conversion techniques will naturally benefit from biomass' carbon cycle and the variety of techniques ***,it has a large potential no matter environmentally or economically,along with technological advancement and the development of government regulations to minimize its harm.

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Joint Coarse to Fine-Grained Spatio-Temporal Modeling for Video Action Recognition

IEEE Transactions on Biometrics, Behavior, and Identity Scie...

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IEEE Transactions on Biometrics, Behavior, and Identity science 2025年第3期7卷 444-457页

作者： Li, Chunlei Cheng, Can Yu, Miao Liu, Zhoufeng Huang, Di Zhongyuan University of Technology School of Electrical Information and Engineering Henan Zhengzhou451191 China Beihang University School of Computer Science and Engineering Beijing100191 China

The action recognition task involves analyzing video content and temporal relationships between frames to identify actions. Crucial to this process are action representations that effectively capture varying temporal scales and spatial motion variations. To address these challenges, we propose the Joint Coarse to Fine-Grained Spatio-Temporal Modeling (JCFG-STM) approach, which is designed to capture robust spatio-temporal representations through three key components: the Temporal-enhanced Spatio-Temporal Perception (TSTP) module, the Positional-enhanced Spatio-Temporal Perception (PSTP) module, and the Fine-grained Spatio-Temporal Perception (FSTP) module. Specifically, TSTP is designed to fuse temporal information across both local and global spatial scales, while PSTP emphasizes the integration of spatial coordinate directions, both horizontal and vertical, with temporal dynamics. Meanwhile, FSTP focuses on combining spatial coordinate information with short-term temporal data by differentiating neighboring frames, enabling fine-grained spatio-temporal modeling. JCFG-STM effectively focuses on multi-granularity and complementary motion patterns associated with actions. Extensive experiments conducted on large-scale action recognition datasets, including Kinetics-400, Something-Something V2, Jester, and EgoGesture, demonstrate the effectiveness of our approach and its superiority over state-of-the-art methods. © 2019 IEEE.

关键词： Video analysis

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Conv-TasNet Adaptive Noise Cancellation Model Enhanced by WaveNet

Conv-TasNet Adaptive Noise Cancellation Model Enhanced by Wa...

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Intelligent Systems and Computational Networks (ICISCN), International Conference on

作者： Kun Zhao Yaojie Hou College of Computer Science and Technology (College of Big Data) Taiyuan University of Technology Jinzhong China College of Electrical and Automation Henan Polytechnic University Jiaozuo China

ISBN: (数字)9798331529246

ISBN: (纸本)9798331529253

Traditional speech denoising methods often struggle with low signal-to-noise ratios (SNR) and poor clarity in complex noise environments. To address these limitations, this study introduces an adaptive denoising model that integrates Conv-TasNet with WaveNet enhancements. The proposed model incorporates causal convolution within the Conv-TasNet separator to better capture long-term dependencies and employs WaveNet's gating activation mechanism to effectively handle nonlinear speech features. Additionally, a mask weighting strategy is implemented to emphasize target speech signals while suppressing background noise. Experimental results demonstrate that the enhanced model significantly outperforms the original Conv-TasNet, achieving an SNR improvement from –5 dB to 33.74 dB and reducing mean squared error (MSE) to nearly zero. These findings confirm the model's superior performance and robustness in complex noisy environments, highlighting its potential for advanced speech enhancement applications.

关键词： Adaptation models Convolution Computational modeling Particle separators Noise reduction Speech enhancement Feature extraction Computational efficiency Noise measurement Signal to noise ratio

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Fuzzy PID Parameter Optimization of Hydraulic Turbine Based on Adaptive Hybrid Evolutionary Algorithm

Fuzzy PID Parameter Optimization of Hydraulic Turbine Based ...

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New Power System and Power Electronics (NPSPE), International Conference on

作者： Xueri Li Zhensheng Huang Zhiyong Liu Lei Yang Department of Computer Science Guangdong University of Science and Technology Dongguan China School of Computer Science Guangdong Polytechnic Normal University Guangzhou China

ISBN: (数字)9798350389869

ISBN: (纸本)9798350389876

Aiming at the optimization of PID parameters of hydropower units, based on the fuzzy PID controller, the characteristics of water turbine governing system and PID optimization index, the PID of hydro turbine governor is established Parameter optimization model: the self-adaptive hybrid evolution optimization algorithm framework (SAHEL) and fuzzy PID simulation test for 4% and 100% no-load frequency interference and 10% and 50% load frequency interference simulation test are adopted. Compared with traditional differential evolution, fuzzy differential evolution, particle swarm optimization and improved genetic algorithm, the fuzzy PID parameters obtained by the algorithm are compared under different working conditions (frequency disturbance or load disturbance), the number optimal solution not only has a small overshoot, but also has a short transition process time. ITAE index is also good, which is more conducive to the smooth, fast and stable system, and is more conducive to the theory and practice of parameter optimization of steam turbine governing system.

关键词： Water Hydraulic turbines Adaptation models Interference Regulation Indexes Particle swarm optimization Optimization Frequency control Genetic algorithms

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Provably Secure Symmetric-Key Privacy-Preserving authenticated key agreement protocol 23

Provably Secure Symmetric-Key Privacy-Preserving authenticat...

引用

Proceedings of the 2023 13th International Conference on Communication and Network Security

作者： Liang Ni Hengsheng Zhou Yawei Zhang Xiaoyan Liu Bingke Gu School of Computer Scienc Zhongyuan University of Technology China and Henan Development and Innovation Laboratory of Industrial Internet Security Big Data Zhongyuan University of Technology China School of Computer Science Zhongyuan University of Technology China School of Computer Science Zhongyuan University of Technology China and School of Computer Science Fujian Normal University China

ISBN: (纸本)9798400707964

In recent years, the rapid development of Quantum Computing technology has had a huge impact on the security of traditional Public Key Cryptography. However, the security of Hash functions and Symmetric Cryptographic algorithms is relatively less impacted by this security threaten and commonly have higher execution efficiency. This two primitives can offset the security impact by appropriately increasing the output scale of a Hash function and symmetric key respectively. Therefore, the Symmetric Key Authenticated Key Agreement(SAKA) protocol which constructed mainly by Hash functions and symmetric cryptographic algorithms has gradually attracted more attention. In this paper we proposed a provably secure SAKA scheme. We extend the security model used by Ferreira et al to formally prove the security of our protocol by introducing a criterion for indistinguishability of identities and Synchronization Robustness property. Our protocol not only captures basic security properties such as Perfect Forward Secrecy, Entity Authentication and Key Indistinguishability but also achieved Privacy Preservation and Full Synchronization Robustness. Furthermore, its implementation does not need to rely on a huge and complex Public key Infrastructure(PKI), so we can easily deploy it in a coucurrent environment. Comparison results indicate that the proposal consumes the least computation resource and reasonable communication cost among nine SAKA protocols while equiping 10 security properties.

关键词： perfect forward secrecy privacy preservation puncturable key encapsulation mechanism resistance to quantum computing symmetric key

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Real-time Performance Study of Information Transmission in EPA Industrial Ethernet

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Chinese Journal of Electronics 2023年第1期21卷 125-130页

作者： Ning Liu Chongquan Zhong Yuqin Bai School of Mechanical and Power Engineering Henan Polytechnic University Jiaozuo China School of Control Science and Engineering Dalian University of Technology Dalian China

In order to propose the method of evaluating and improving the real-time performance of EPA (Ethernet for plant automation) industrial Ethernet, the real-time performance of EPA information transmission was studied from theoretical and experimental perspectives. By analyzing information transmission regularity and EPA deterministic scheduling mechanism, several indicators including delivery time, time synchronization accuracy, utilization percentage of configured timeslice, datasending time offset accuracy and throughput RTE that can be used to specify the real-time performance of EPA information transmission were presented and investigated. On this basis, the test principles and test methods of the indicators were studied. Furthermore, an experiment platform was developed to test the real-time indicators of EPA information transmission. According to the analysis and the experiment, some methods to improve the real-time performance of EPA information transmission were proposed.

关键词： Performance evaluation Job shop scheduling Software algorithms Information processing Ethernet Throughput Real-time systems

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