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2023 International Conference on Telecommunications, Electronics and Informatics, ICTEI 2023

作者： Ni, Shuiping Wang, Shijie Li, Huifang Li, Pengkun Henan Polytechnic University College of Computer Science and Technology Jiaozuo China

ISBN: (纸本)9798350342963

Single image super-resolution (SISR) reconstruction algorithms mostly use a single scale convolution kernel to extract the features of low-resolution images, which will easily cause a large number of details loss. Usually, the depth of the model network is increased to achieve better image reconstruction effect. With the increase of the depth of the network, the model gradient disappears, and increase network parameters, making the training difficult. A multi-scale residual attention model is proposed to achieve single image super-resolution reconstruction. The model consists of shallow feature extraction, multi-scale residual attention network and reconstruction. The convolution kernels of different scales are used for feature extraction of low-resolution image convolution. Residual attention network can eliminate gradient disappearance and network degradation. Adding attention mechanism in residual network can make the high-frequency region characteristics of network channel get more attention, and enhance the texture and detail information of reconstructed image. © 2023 IEEE.

关键词： Feature extraction

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Source localization in signed networks with effective distance

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Chinese Physics B 2024年第2期33卷 577-585页

作者：马志伟孙蕾丁智国黄宜真胡兆龙 Zhejiang Normal University School of Computer Science and TechnologyJinhua 321004China Shanghai Business School School of Business and EconomicsShanghai 200235China Jinhua Polytechnic School of Information EngineeringJinhua 321016China

While progress has been made in information source localization,it has overlooked the prevalent friend and adversarial relationships in social *** paper addresses this gap by focusing on source localization in signed network *** the topological characteristics of signed networks and transforming the propagation probability into effective distance,we propose an optimization method for observer ***,by using the reverse propagation algorithm we present a method for information source localization in signed *** experimental results demonstrate that a higher proportion of positive edges within signed networks contributes to more favorable source localization,and the higher the ratio of propagation rates between positive and negative edges,the more accurate the source localization ***,this aligns with our observation that,in reality,the number of friends tends to be greater than the number of adversaries,and the likelihood of information propagation among friends is often higher than among *** addition,the source located at the periphery of the network is not easy to ***,our proposed observer selection method based on effective distance achieves higher operational efficiency and exhibits higher accuracy in information source localization,compared with three strategies for observer selection based on the classical full-order neighbor coverage.

关键词： complex networks signed networks source localization effective distance

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Research on the closed-loop supply chain of intelligent products considering government subsidies in the context of the internet of things

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Discover Internet of Things 2025年第1期5卷 1-20页

作者： Zhao, Jinghua Cui, Shaoyun Xu, Zheng School of Business University of Shanghai for Science and Technology Shanghai China School of Computer and Information Engineering Institute for Artificial Intelligence Shanghai Polytechnic University Shanghai201209 China

The rapid development of Internet of Things technology and the continuous improvement of consumer demand have spawned the emergence of intelligent products based on Internet of Things technology. The existing research on the closed-loop supply chain of intelligent products under the background of the Internet of Things still lacks consideration of different subsidy objects and recyclers. Therefore, for different subsidy objects in the three-stage closed-loop supply chain of intelligent products, a pricing decision model involving manufacturers, recyclers, retailers and consumers under the minimum standard supervision of recycling technology is constructed, and different recyclers are distinguished according to the characteristics of intelligent products. By comparing the profits of each subject in different models, the optimal model of government subsidy is obtained. It is found that under the four modes, subsidizing recyclers without self-recovery technology makes the total profit of the supply chain reach the optimal solution;capital recyclers can obtain the largest number of old intelligent product recycling by using self-recovery technology;when subsidizing manufacturers, the total profit and product recovery rate of the supply chain are at the bottom. In addition, recycling subsidies, subsidy impact coefficients and technical standards will affect the best profits of enterprises. Through the analysis of the closed-loop supply chain of intelligent products, the research provides theoretical support and decision-making basis for the supply chain members to formulate relevant strategies and the government to take relevant measures to promote resource utilization and environmental protection. © The Author(s) 2025.

关键词： Smart manufacturing

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Research on facial expression recognition based on multimodal data fusion and neural network

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International Journal of Wireless and Mobile Computing 2024年第1期27卷 47-55页

作者： Han, Yi Wang, Xubin Lu, Zhengyu School of Mechanical Science and Engineering Huazhong University of Science and Technology Hubei Wuhan China Anyang Institute of Technology Department of Computer Science and Information Engineering Henan Province Anyang China School of Computer Science and Information Engineering Shanghai Institute of Technology FengXian District Shanghai China

Facial expression recognition is a challenging task when neural network is applied to pattern recognition. Most of the current recognition research is based on single source facial data, which generally has the disadvantages of low accuracy and low robustness. In this paper, a neural network algorithm of facial expression recognition based on multimodal data fusion is proposed. The algorithm is based on the multimodal data, and it takes the facial image, the histogram of oriented gradient of the image and the facial landmarks as the input, and establishes Convolutional Neural Network (CNN) designed to extract features from facial image, neural network designed to extract features from facial Landmarks and Neural Network (LNN) designed to extract features from Histogram of gradient (HNN), three sub-neural networks to extract data features, using multimodal data feature fusion mechanism to improve the accuracy of facial expression recognition. Experimental results show that, the algorithm has a great improvement in accuracy, robustness and detection speed. Copyright © 2024 Inderscience Enterprises Ltd.

关键词： Data fusion

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Dual-Path Downsampling Algorithm Based on HWD-MP 3

Dual-Path Downsampling Algorithm Based on HWD-MP

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3rd International Conference on Cloud Computing, Big Data Application and Software Engineering, CBASE 2024

作者： Wang, Zilong Bai, Jia Zhang, Qihang Shao, Changbin School of Computer Jiangsu University of Science and Technology Zhenjiang China School of Computer Science Xi'an Polytechnic University Xian China School of Computer Science and Technology Guangdong University of Technology Guangzhou China

ISBN: (纸本)9798331506582

In object detection tasks, the quality of downsampling significantly impacts model performance. Conventional downsampling methods, such as max pooling which retains the maximum value within a window, often lead to the loss of critical feature information. This study proposes a plug-and-play dual-path downsampling module, designing the Haar Wavelet-based Downsampling and Max Pooling (HWD-MP) module based on the Haar Wavelet-based Downsampling (HWD) operation. One branch employs max pooling for downsampling, while the another branch utilizes the Haar wavelet transform to decrease the spatial resolution of feature maps while maintaining all the information., thereby addressing the issue of information loss caused by max pooling downsampling and achieving diversity in downsampled features. Experiments on the Yolov7-tiny model demonstrate that this approach can greatly enhance the detection effectiveness, increasing the mAP50 by 2.5% and 1.5% on the RSOD and NWPU VHR-10 remote sensing datasets, respectively. © 2024 IEEE.

关键词： Wavelet transforms

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A Task Offloading Method for Vehicular Edge Computing Based on Reputation Assessment

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computers, Materials & Continua 2025年第5期83卷 3537-3552页

作者： Jun Li Yawei Dong Liang Ni Guopeng Feng Fangfang Shan School of Computer Science Zhongyuan University of TechnologyZhengzhou450007China Henan Key Laboratory of Cyberspace Situation Awareness Zhengzhou450007China

With the development of vehicle networks and the construction of roadside units,Vehicular Ad Hoc Networks(VANETs)are increasingly promoting cooperative computing patterns among *** edge computing(VEC)offers an effective solution to mitigate resource constraints by enabling task offloading to edge cloud infrastructure,thereby reducing the computational burden on connected ***,this sharing-based and distributed computing paradigm necessitates ensuring the credibility and reliability of various computation *** vehicular edge computing platforms have not adequately considered themisbehavior of *** propose a practical task offloading algorithm based on reputation assessment to address the task offloading problem in vehicular edge computing under an unreliable *** approach integrates deep reinforcement learning and reputation management to address task offloading *** experiments conducted using Veins demonstrate the feasibility and effectiveness of the proposed method.

关键词： Vehicular edge computing task offloading reputation assessment

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THE HAUSDORFF DIMENSION OF THE SPECTRUM OF A CLASS OF GENERALIZED THUE-MORSE HAMILTONIANS

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Acta Mathematica Scientia 2023年第5期43卷 1997-2004页

作者：刘庆晖唐志毅 School of Computer Science and Technology Beijing Institute of TechnologyBeijing 100081China School of Mathematics and Physics Hubei Polytechnic UniversityHuangshi 435003China

Letτbe a generalized Thue-Morse substitution on a two-letter alphabet{a,b}:τ(a)=ambm,τ(b)=bmam for the integer m≥***ξbe a sequence in{a,b}Z that is generated byτ.We study the one-dimensional Schr?dinger operator Hm,λon l2(Z)with a potential given by v(n)=λVξ(n),whereλ>0 is the coupling and Vξ(n)=1(Vξ(n)=-1)ifξ(n)=a(ξ(n)=b).LetΛ2=2,and for m>2,letΛm=m if m≡0 mod 4;letΛm=m-3 if m≡1 mod 4;letΛm=m-2if m≡2 mod 4;letΛm=m-1 if m≡3 mod *** show that the Hausdorff dimension of the spectrumσ(Hm,λ)satisfies that dimHσ(Hm,λ)>logΛm/(log 64m+4).It is interesting to see that dimHσσ(Hm,λ)tends to 1 as m tends to infinity.

关键词： one-dimensional Schrodinger operator generalized Thue-Morse sequence Hausdorff dimension

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Lay CO:Achieving Least Lossy Accuracy for Most Efficient RRAM-Based Deep Neural Network Accelerator via Layer-Centric Co-Optimization

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计算机科学技术学报（英文版） 2023年第2期38卷 328-347页

作者： Shao-Feng Zhao Fang Wang Bo Liu Dan Feng Yang Liu Wuhan National Laboratory for Optoelectronics Huazhong University of Science and TechnologyWuhan 430074China School of Computer Science and Technology Huazhong University of Science and TechnologyWuhan 430074China Cloud Computing and Big Data Institute Henan University of Economics and LawZhengzhou 450001China Wuhan National Laboratory for Optoelectronics Huazhong University of Science and TechnologyWuhan 430074China School of Computer Science and Technology Huazhong University of Science and TechnologyWuhan 430074China Research Institute of Huazhong University of Science and Technology in Shenzhen Shenzhen 518057China School of Computer and Artificial Intelligence Zhengzhou UniversityZhengzhou 450001China Wuhan National Laboratory for Optoelectronics Huazhong University of Science and TechnologyWuhan 430074China School of Computer Science and Technology Huazhong University of Science and TechnologyWuhan 430074China Cloud Computing and Big Data Institute Henan University of Economics and LawZhengzhou 450001China

Resistive random access memory(RRAM)enables the functionality of operating massively parallel dot prod-ucts and ***-based accelerator is such an effective approach to bridging the gap between Internet of Things devices'constrained resources and deep neural networks'tremendous *** to the huge overhead of Analog to Digital(A/D)and digital accumulations,analog RRAM buffer is introduced to extend the processing in analog and in *** analog RRAM buffer offers potential solutions to A/D conversion issues,the energy consumption is still challenging in resource-constrained environments,especially with enormous intermediate data ***,criti-cal concerns over endurance must also be resolved before the RRAM buffer could be frequently used in reality for DNN in-ference *** we propose LayCO,a layer-centric co-optimizing scheme to address the energy and endurance con-cerns altogether while strictly providing an inference accuracy *** relies on two key ideas:1)co-optimizing with reduced supply voltage and reduced bit-width of accelerator architectures to increase the DNN's error tolerance and achieve the accelerator's energy efficiency,and 2)efficiently mapping and swapping individual DNN data to a correspond-ing RRAM partition in a way that meets the endurance *** evaluation with representative DNN models demonstrates that LayCO outperforms the baseline RRAM buffer based accelerator by 27x improvement in energy effi-ciency(over TIMELY-like configuration),308x in lifetime prolongation and 6x in area reduction(over RAQ)while main-taining the DNN accuracy loss less than 1％.

关键词： deep learning accelerator resistive random access memory (RRAM) energy efficiency error tolerance

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CPFU-Net: A Channel Position Wide Focus Mechanism based on U-Net for Building Image Segmentation Algorithm 24

CPFU-Net: A Channel Position Wide Focus Mechanism based on U...

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4th International Conference on Artificial Intelligence, Big Data and Algorithms, CAIBDA 2024

作者： Liu, Cheng Pang, Yue Li, Tiezhu Sun, Jiawei Zuo, Xianyu Dang, Lanxue Zhou, Liming Qiao, Baojun School of Computer and Information Engineering Henan University Kaifeng Henan China School of Computer Science and Technology Anhui University Hefei Anhui China

ISBN: (纸本)9798400710247

Building image segmentation is widely used in building area estimation and urban construction planning. However, there are problems in the building segmentation in high-resolution remote sensing images, such as small targets misclassified easily, and edge details lost easily. To address the front issues, an improvement channel -position-focus-U-Net (CPFU-Net) model is proposed. A wide focus module (WFM) is designed to increase the receptive field which can achieve higher edge integrity of building segmentation through preserving edge details and focusing on the area of interest. The Squeeze-and-Excitation module is integrated into the channel attention convolution module (CACM) which improves the sensitivity of the model to channel information features. The CPFU-Net uses attention mechanisms and wide focus module (WFM) to improve skip connections which can fully utilize low-level and high-level semantic information to extract more accurate building features. Large numbers of experiments are implemented on both Satellite datasets and Massachusetts Building datasets to verify the effectiveness of CPFU-Net. The experimental results show that CPFU-Net reduces the probability of small target misclassification and preserve more edge details in building segmentation which improves the accuracy of building segmentation and achieves higher performance in OA, Recall, IoU, and F1-Score metrics. © 2024 Copyright held by the owner/author(s).

关键词： Urban planning

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Design and Implementation of Intranet Abnormal Traffic Security Detection System 2

Design and Implementation of Intranet Abnormal Traffic Secur...

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2nd International Conference on Mechatronics, IoT and Industrial Informatics, ICMIII 2024

作者： Zhao, Aoran Tianjin Polytechnic University School of Computer Science and Technology Tianjin China

ISBN: (纸本)9798350386639

Intranet is the fundamental information network for various systems and units to conduct business applications, with the advantages of open system architecture and flexible information sharing. This paper analyzes the characteristics of intranet traffic and abnormal network traffic, discusses the abnormal traffic detection method and algorithm based on traffic whitelist, and designs a security detection system for abnormal network traffic to locate malicious attacks and abnormal traffic generated by sudden access. The detection system helps network administrators to timely detect problems, take targeted measures, mitigate the harm of abnormal traffic to the network and its business, and provide support for network maintenance personnel in troubleshooting. © 2024 IEEE.

关键词： Information dissemination

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