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Multi-Objective Optimization for NOMA-Based Mobile Edge Computing Offloading by Maximizing System Utility

China communications 2023年第12期20卷 156-165页

作者： Hong Qin Haitao Du Huahua Wang Li Su Yunfeng Peng Chongqing University of Post and Telecom Chongqing 400065China China Mobile Research Institute Beijing 100000China School of Computer and Communication Engineering University of Science and Technology BeijingBeijing 100083China

Mobile Edge Computing(MEC)is a technology for the fifth-generation(5G)wireless communications to enable User Equipment(UE)to offload tasks to servers deployed at the edge of ***,taking both delay and energy consumption into consideration in the 5G MEC system is usually complex and ***-orthogonal multiple access(NOMA)enable more UEs to offload their computing tasks to MEC servers using the same spectrum resources to enhance the spectrum efficiency for 5G,which makes the problem even more complex in the NOMA-MEC *** this work,a system utility maximization model is present to NOMA-MEC system,and two optimization algorithms based on Newton method and greedy algorithm respectively are proposed to jointly optimize the computing resource allocation,SIC order,transmission time slot allocation,which can easily achieve a better trade-off between the delay and energy *** simulation results prove that the proposed method is effective for NOMA-MEC systems.

关键词： computation offloading mobile edge computing non-orthogonal multiple access resource allocation

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Age estimation from facial images based on Gabor feature fusion and the CIASO-SA algorithm

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CAAI Transactions on Intelligence technology 2023年第2期8卷 518-531页

作者： Di Lu Dapeng Wang Kaiyu Zhang Xiangyuan Zeng School of Measurement and Communication Engineering Harbin University of Science and TechnologyHarbinChina Cheriton School of Computer Science University of WaterlooWaterlooOntarioCanada

Aiming at the problem of long time-consuming and low accuracy of existing age estimation approaches,a new age estimation method using Gabor feature fusion,and an improved atomic search algorithm for feature selection is ***,texture features of five scales and eight directions in the face region are extracted by Gabor wavelet *** statistical histogram is introduced to encode and fuse the directional index with the largest feature value on Gabor ***,a new hybrid feature selection algorithm chaotic improved atom search optimisation with simulated annealing(CIASO-SA)is presented,which is based on an improved atomic search algorithm and the simulated annealing ***,the CIASO-SA algorithm introduces a chaos mechanism during atomic initialisation,significantly improving the convergence speed and accuracy of the ***,a support vector machine(SVM)is used to get classification results of the age *** verify the performance of the proposed algorithm,face images with three resolutions in the Adience dataset are *** the Gabor real part fusion feature at 48�48 resolution,the average accuracy and 1-off accuracy of age classification exhibit a maximum of 60.4%and 85.9%,*** results prove the superiority of the proposed algorithm over the state-of-the-art methods,which is of great referential value for application to the mobile terminals.

关键词： age estimation atom search algorithm feature selection Gabor feature simulated annealing

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ACbot:an IIoT platform for industrial robots

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Frontiers of computer science 2025年第4期19卷 13-27页

作者： Rui WANG Xudong MOU Tianyu WO Mingyang ZHANG Yuxin LIU Tiejun WANG Pin LIU Jihong YAN Xudong LIU School of Computer Science and Engineering Beihang UniversityBeijing 100191China Zhongguancun Laboratory Beijing 100194China School of Software Beihang UniversityBeijing 100191China School of Mechatronics Engineering Harbin Institute of TechnologyHarbin 150001China Hangzhou Innovation Institute Beihang UniversityHangzhou 310051China School of Information Engineering China University of GeosciencesBeijing 100083China

As the application of Industrial Robots(IRs)scales and related participants increase,the demands for intelligent Operation and Maintenance(O&M)and multi-tenant collaboration *** methods could no longer cover the requirements,while the Industrial Internet of Things(IIoT)has been considered a promising ***,there’s a lack of IIoT platforms dedicated to IR O&M,including IR maintenance,process optimization,and knowledge *** this context,this paper puts forward the multi-tenant-oriented ACbot platform,which attempts to provide the first holistic IIoT-based solution for O&M of *** on an information model designed for the IR field,ACbot has implemented an application architecture with resource and microservice management across the cloud and multiple *** this basis,we develop four vital applications including real-time monitoring,health management,process optimization,and knowledge *** have deployed the ACbot platform in real-world scenarios that contain various participants,types of IRs,and *** date,ACbot has been accessed by 10 organizations and managed 60 industrial robots,demonstrating that the platform fulfills our ***,the application results also showcase its robustness,versatility,and adaptability for developing and hosting intelligent robot applications.

关键词： IIoT platform industrial robots cloud-edge collaboration intelligent applications

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Improving Micro-expression Recognition using Multi-sequence Driven Face Generation

Improving Micro-expression Recognition using Multi-sequence ...

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Chen, Yuan Zhong, Chongju Huang, Pinyi Cai, Wangyang Wang, Lei School of Computer Science and Engineering Central South University China School of Computer and Communication Engineering Changsha University of Science and Technology China

ISBN: (纸本)9798350368741

Micro-expression (ME) recognition holds great potential for revealing true human emotions. A significant barrier to effective ME recognition is the lack of sufficient annotated ME video data because MEs are subtle and involuntary facial expressions that are very hard to capture. To address this issue, data augmentation techniques, such as ME migration based on a driven video, have been employed to enrich training samples. Considering that MEs can be complex facial movements involving multiple action unit (AU) changes, we propose a novel ME generation approach that enables the creation of more realistic facial sequences by fusing MEs from multiple videos rather than just single driven video. To enhance the effectiveness of multi-sequence ME transfer, we adapt the thin plate spline motion model and improve traditional face alignment methods to better suit the model, facilitating multi-sequence driven ME generation. In our experiments, we conduct a downstream ME recognition task using models trained on our augmented ME sequences to demonstrate the effectiveness of our approach on the SAMM, SMIC, and CASME II datasets. The results confirm that our proposed approach outperforms state-of-the-art (SOTA) augmentation and generation methods in terms of F1 score and recognition accuracy. © 2025 IEEE.

关键词： face alignment micro-expression generation thin plate spline motion model video fusion

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Outage Behaviors of Active Intelligent Reflecting Surface Enabled NOMA communications

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computer Modeling in engineering & sciences 2023年第10期137卷 789-812页

作者： Zhiping Lu Xinwei Yue Shuo Chen Weiguo Ma School of Information and Communication Engineering Beijing University of Posts and TelecommunicationsState Key Laboratory of Wireless Mobile CommunicationsChina Academy of Telecommunications Technology(CATT)BeijingChina School of Information and Communication Engineering Beijing Information Science and Technology UniversityBeijing100101China

Active intelligent reflecting surface(IRS)is a novel and promising technology that is able to overcome the multiplicative fading introduced by passive *** this paper,we consider the application of active IRS to nonorthogonalmultiple access(NOMA)networks,where the incident signals are amplified actively through integrating amplifier to reflecting *** specifically,the performance of active/passive IRS-NOMA networks is investigated over large and small-scale fading *** to characterize the performance of active IRSNOMA networks,the exact and asymptotic expressions of outage probability for a couple of users,i.e.,near-end user n and far-end user m are derived by exploiting a 1-bit coding *** on approximated analyses,the diversity orders of user n and user m are obtained for active *** addition,the system throughput of active IRS-NOMA is discussed in the delay-sensitive *** simulation results are carried out to verify that:i)The outage behaviors of active IRS-NOMAnetworks are superior to that of passive IRS-NOMAnetworks;ii)As the reflection amplitude factors increase,the active IRS-NOMAnetworks are capable of furnishing the enhanced outage performance;and iii)The active IRS-NOMA has a larger system throughput than passive IRS-NOMA and conventional communications.

关键词： Active intelligent reflecting surface amplification noise non-orthogonal multiple access outage probability

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Class-conditional domain adaptation for semantic segmentation

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Computational Visual Media 2024年第5期10卷 1013-1030页

作者： Yue Wang Yuke Li James H.Elder Runmin Wu Huchuan Lu School of Information and Communication Engineering Dalian University of TechnologyDalian 116024China School of Computer Science Wuhan UniversityWuhan 430072China Department of Electrical Engineering and Computer Science York UniversityToronto M3J 1P3Canada Department of Computer Science the University of Hong KongHong Kong 999077China

Semantic segmentation is an important sub-task for many ***,pixel-level ground-truth labeling is costly,and there is a tendency to overfit to training data,thereby limiting the generalization *** domain adaptation can potentially address these problems by allowing systems trained on labelled datasets from the source domain(including less expensive synthetic domain)to be adapted to a novel target *** conventional approach involves automatic extraction and alignment of the representations of source and target domains *** limitation of this approach is that it tends to neglect the differences between classes:representations of certain classes can be more easily extracted and aligned between the source and target domains than others,limiting the adaptation over all ***,we address:this problem by introducing a Class-Conditional Domain Adaptation(CCDA)*** incorporates a class-conditional multi-scale discriminator and class-conditional losses for both segmentation and ***,they measure the segmentation,shift the domain in a classconditional manner,and equalize the loss over *** results demonstrate that the performance of our CCDA method matches,and in some cases,surpasses that of state-of-the-art methods.

关键词： domain adaptation generative adversarial networks semantic segmentation cityscapes

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Channel Correlation Based User Grouping Algorithm for Nonlinear Precoding Satellite communication System

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China communications 2024年第1期21卷 200-214页

作者： Ke Wang Baorui Feng Jingui Zhao Wenliang Lin Zhongliang Deng Dongdong Wang Yi Cen Genan Wu School of Information and Communication Engineering Beijing University of Posts and TelecommunicationsBeijing 100876China School of Information Engineering Minzu University of ChinaBeijing 100081China Institute of Spacecraft Application System Engineering China Academy of Space TechnologyBeijing 100094China Academy for Network and Communications of CETC Science and Technology on Communication Networks LaboratoryShijiazhuang 050081China

Low Earth Orbit(LEO)multibeam satellites will be widely used in the next generation of satellite communication systems,whose inter-beam interference will inevitably limit the performance of the whole *** precoding such as Tomlinson-Harashima precoding(THP)algorithm has been proved to be a promising technology to solve this problem,which has smaller noise amplification effect compared with linear ***,the similarity of different user channels(defined as channel correlation)will degrade the performance of THP *** this paper,we qualitatively analyze the inter-beam interference in the whole process of LEO satellite over a specific coverage area,and the impact of channel correlation on Signal-to-Noise Ratio(SNR)of receivers when THP is *** user grouping algorithm is proposed based on the analysis of channel correlation,which could decrease the number of users with high channel correlation in each precoding group,thus improve the performance of ***,our algorithm is designed under the premise of co-frequency deployment and orthogonal frequency division multiplexing(OFDM),which leads to more users under severe inter-beam interference compared to the existing research on geostationary orbit satellites broadcasting *** results show that the proposed user grouping algorithm possesses higher channel capacity and better bit error rate(BER)performance in high SNR conditions relative to existing works.

关键词： channel correlation inter-beam interference multibeam satellite Tomlinson-Harashima precoding user grouping

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A deep decentralized privacy-preservation framework for online social networks

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Blockchain(Research and Applications) 2024年第4期5卷 163-174页

作者： Samuel Akwasi Frimpong Mu Han Emmanuel Kwame Effah Joseph Kwame Adjei Isaac Hanson Percy Brown School of Computer Science and Communication Engineering Jiangsu UniversityZhenjiang212013China Department of Computer Engineering Ghana Communication Technology UniversityAccraPMB 100Ghana Department of Electrical&Electronic Engineering Ghana Communication Technology UniversityAccraPMB 100Ghana Department of Computer Science and Information Systems Ashesi UniversityAccra3042Ghana Department of Telecommunication Engineering Ghana Communication Technology UniversityAccraPMB 100Ghana

This paper addresses the critical challenge of privacy in Online Social Networks(OSNs),where centralized designs compromise user *** propose a novel privacy-preservation framework that integrates blockchain technology with deep learning to overcome these *** methodology employs a two-tier architecture:the first tier uses an elitism-enhanced Particle Swarm Optimization and Gravitational Search Algorithm(ePSOGSA)for optimizing feature selection,while the second tier employs an enhanced Non-symmetric Deep Autoencoder(e-NDAE)for anomaly ***,a blockchain network secures users’data via smart contracts,ensuring robust data *** tested on the NSL-KDD dataset,our framework achieves 98.79%accuracy,a 10%false alarm rate,and a 98.99%detection rate,surpassing existing *** integration of blockchain and deep learning not only enhances privacy protection in OSNs but also offers a scalable model for other applications requiring robust security measures.

关键词： Preprocessing Privacy-preservation Blockchain Deep learning Online social network

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MalFSM: Feature Subset Selection Method for Malware Family Classification

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Chinese Journal of Electronics 2023年第1期32卷 26-38页

作者： KONG Zixiao XUE Jingfeng WANG Yong ZHANG Qian HAN Weijie ZHU Yufen School of Computer Science and Technology Beijing Institute of Technology School of Space Information Space Engineering University

Malware detection has been a hot spot in cyberspace security and academic research. We investigate the correlation between the opcode features of malicious samples and perform feature extraction, selection and fusion by filtering redundant features, thus alleviating the dimensional disaster problem and achieving efficient identification of malware families for proper classification. Malware authors use obfuscation technology to generate a large number of malware variants, which imposes a heavy analysis burden on security researchers and consumes a lot of resources in both time and space. To this end, we propose the MalFSM framework. Through the feature selection method, we reduce the 735 opcode features contained in the Kaggle dataset to 16, and then fuse on metadata features(count of file lines and file size)for a total of 18 features, and find that the machine learning classification is efficient and high accuracy. We analyzed the correlation between the opcode features of malicious samples and interpreted the selected features. Our comprehensive experiments show that the highest classification accuracy of MalFSM can reach up to 98.6% and the classification time is only 7.76 s on the Kaggle malware dataset of Microsoft.

关键词： Correlation Fuses Filtering Cyberspace Machine learning Metadata Feature extraction

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Facial Expression Recognition Algorithm Based on Swin Transformer 9

Facial Expression Recognition Algorithm Based on Swin Transf...

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9th International Conference on Systems and Informatics, ICSAI 2023

作者： Han, Shumin Chang, Heming Shi, Zhiguo Hu, Siquan University of Science and Technology Beijing School of Computer and Communication Engineering Beijing10083 China

ISBN: (纸本)9798350383706

Expressions are an important non-verbal behavior for humans to convey their emotional information, reflecting their inner activities. As attention in Transformers has excellent feature representation capabilities, it is catching more interests in computer vision field. Swin Transformer is a successful implementation of transformer in computer vision field. This paper proposes a Swin Transformer-based emotion recognition algorithm called Swin Emotion. The algorithm utilizes Swin Transformer as the backbone network and fuses the varying-sized feature vectors extracted from multiple stages, taking into account both the detailed features of the image and its macroscopic characteristics while preserving the integrity of the modeling process. The multi-scale feature fusion network simultaneously uses both low-level and high-level features of images, thereby improving the model's perception ability for objects of different scales and its capture ability of detail and contextual information. Experimental results show that the model demonstrates better understanding of emotions and achieves outstanding performance on all tasks. With an accuracy of up to 99.38% in peak expressions on the CK+ dataset, Swin Emotion holds broad application prospects in the field of emotion recognition. © 2023 IEEE.

关键词： Emotion Recognition

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