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15th IEEE International Conference on Wireless Communications and Signal Processing, WCSP 2023

作者： Feng, Shaohan Lu, Xiao Niyato, Dusit Wu, Yuan Wang, Wenbo Zhejiang Gongshang University School of Information and Electronic Engineering Hangzhou China Ericsson Research and Development Canada Nanyang Technological University School of Computer Science and Engineering Singapore University of Macau State Key Laboratory of Internet of Things for Smart City China Kunming University of Science and Technology School of Mechanical and Electrical Engineering Kunming China

ISBN: (纸本)9798350324662

This paper focuses on the problem of secure communications in a D2D-underlaid cellular network, where device-to-device (D2D) communication operates in a hybrid manner using both millimeter-wave (mmWave) and microwave frequency bands. To combat vigilant adversaries, we employ the technique of covert communication to conceal the presence of legitimate D2D transmissions. The D2D transmitters employ power control, communication-mode switching, and leverage the cellular signals to evade detection by adversaries. The conflict situation between the D2D transmitters and the adversaries is modeled as a Stackelberg game. To mathematically characterize the network's spatial configuration, we utilize the stochastic geometry modeling and consider a large-scale D2D-underlaid network, enabling a system-level analysis of communication strategies. We analyze the game equilibrium and thereafter search for equilibrium by using a bi-level algorithm. Insightful findings are drawn from numerical simulation results. © 2023 IEEE.

关键词： covert communication hybrid device-to-device communication stochastic geometry Wireless security

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Literature Review of Circulating Current of Parallel Voltage Source Converters

Literature Review of Circulating Current of Parallel Voltage...

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PELS Students and Young Professionals Symposium (SYPS), IEEE

作者： Haoyu Zhang Man-Chung Wong Department of Electrical and Computer Engineering Faculty of Science and Technology State Key Laboratory of Internet of Things for Smart City University of Macau Macau China Department of Electrical Computer Engineering Faculty of Science and Technology State Key Laboratory of Internet of Things for Smart City University of Macau Macao China

To increase the power density of voltage source converters (VSC) usually use parallel structures. However, parallel VSC will easily introduce circulating current, which can cause a power efficiency decline. This paper gives a review of the circulating current and the solutions of it. Through the analysis of the principle of circulating current generation and the detail of the solutions, this paper gives an overview of the current research stage of circulating current. The technology can be divided into hardware solutions and software solutions are then analyzed and evaluated.

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Prepartition: Load Balancing Approach for Virtual Machine Reservations in a Cloud Data Center

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Journal of computer science & technology 2023年第4期38卷 773-792页

作者：田文洪徐敏贤周光耀吴逵须成忠 Rajkumar Buyya School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu 610054China Yangtze Delta Region Institute(Huzhou) University of Electronic Science and Technology of ChinaHuzhou 313001China Institute of Advanced Computing and Digital Engineering Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China Department of Computer Science University of VictoriaVictoriaBCV8W 3P6Canada State Key Laboratory of Internet of Things for Smart City University of MacaoMacao 999078China School of Computing and Information Systems University of MelbourneMelbourne 3010Australia

Load balancing is vital for the efficient and long-term operation of cloud data *** virtualization,post(reactive)migration of virtual machines(VMs)after allocation is the traditional way for load balancing and consoli***,it is not easy for reactive migration to obtain predefined load balance objectives and it may interrupt services and bring ***,we provide a new approach,called Prepartition,for load *** partitions a VM request into a few sub-requests sequentially with start time,end time and capacity demands,and treats each sub-request as a regular VM *** this way,it can proactively set a bound for each VM request on each physical machine and makes the scheduler get ready before VM migration to obtain the predefined load balancing goal,which supports the resource allocation in a fine-grained *** with real-world trace and synthetic data show that our proposed approach with offline version(PrepartitionOff)scheduling has 10%–20%better performance than the existing load balancing baselines under several metrics,including average utilization,imbalance degree,makespan and Capacity_*** also extend Prepartition to online load *** results show that our proposed approach also outperforms state-of-the-art online algorithms.

关键词： cloud computing physical machine(PM) virtual machine(VM) reservation load balancing Prepartition

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Red Piranha Optimization Based Fast and Robust Fuzzy C-Means Clustering for Precise Glioma Segmentation in Therapeutic Applications 10

Red Piranha Optimization Based Fast and Robust Fuzzy C-Means...

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10th International Conference on Advanced Computing and Communication Systems, ICACCS 2024

作者： Sophia, G. Ramaraj, Kottaimalai Karthikeyan, K. Prasath Alias Surendhar, S. Ambika, B. Thilagaraj, M. Mv J College of Engineering Department of Computer Science and Engineering Bengaluru India Kalasalingam Academy of Research and Education Department of Electronics and Communication Engineering Tamil Nadu Krishnankoil India Ramco Institute of Technology Department of Electrical and Electronics Engineering Tamil Nadu Rajapalayam India Aarupadai Veedu Institute of Technology Department of Biomedical Engineering Tamil Nadu Chennai India Thiagarajar College of Engineering Department of Electrical and Electronics Engineering Tamil Nadu Madurai India Mvj College of Engineering Department of Industrial Internet of Things Bengaluru India

ISBN: (纸本)9798350384369

Gliomas have cells that resemble glial cells., which are normal brain cells. They are the prevalent kind of tumors;however., in patients with several years to live., they may be a lesser threat., or in patients with only two years to live., they may be more deadly. Chemotherapy and radiation are able to be utilized to decrease the development of brain tumors which are unable to be practically taken away even though medical intervention is still the preferred therapy for these tumors. Magnetic resonance imaging (MRI) for tumor diagnosis because they offer comprehensive images of the structure of the brain. Accurately segmenting tumors from MRls is crucial for both preparing for surgery and diagnostic purposes. Further investigations may not be able to justify manual tumor segmentation. Furthermore., tumor delineation can significantly influence the scheduling of treatment., rate of growth forecasting., and better diagnosis. The present study uses an integrated segmentation algorithm that combines optimization and clustering techniques. One method for creating clusters or groups of identical pixels is fuzzy C-means (FCM) clustering., an unsupervised learning technique. Fast and Robust FCM (FRFCM) addresses the drawbacks of traditional method. Red Piranha Optimization (RPO) is a recently introduced optimization technique that draws inspiration from nature and emulates the community-based hunting act of red piranhas. The suggested RPO-based FCM method was evaluated on a number of BraTS challenge datasets to guarantee its effectiveness. The results of the dissection are contrasted with the corresponding ground truth images. The enhanced dice score value of 92 % is obtained using the developed method. Medical professionals can use findings to help schedule surgical procedures., diagnose patients promptly, and treat them. © 2024 IEEE.

关键词： Chemotherapy

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A Facial Expression Recognition Method based on Residual Separable Convolutional Neural Network

Journal of Network Intelligence

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Journal of Network Intelligence 2022年第1期7卷 59-69页

作者： Xu, Xiaoyu Cui, Jianfeng Chen, Xuhui Chen, Chin-Ling College of Computer and Information Engineering Xiamen University of Technology Xiamen361024 China College of Software Engineering Xiamen University of Technology Xiamen361024 China Fujian Key Laboratory of Internet of things application technology Xiamen361024 China Xiamen City University of Technology Xiamen361024 China School of Computer and Information Engineering Xiamen City University of Technology Xiamen361024 China School of Information Engineering Changchun Sci-Tech University Changchun130600 China Department of Computer Science and Information Engineering Chaoyang University of Technology Taichung41349 Taiwan

Facial expression recognition is a typical application of artificial intelligence. It has practical value and commercial prospects in application scenarios such as safe driving, medical assistance, online classrooms, and human-computer interaction. Traditional convolutional neural networks have low accuracy in facial expression recognition. To solve this problem, we propose a residual separable convolutional neural network, which combines depth-wise separable convolution with an improved residual network. When transmitting feature information, it fuses facial expression features through skip connection and utilizes global average pooling to reduce dimension, thus preventing gradient disappearance. We conduct experiments based on the data set FER2013. The results show that it can improve the accuracy of facial expression recognition, reduce model parameters and raise the utilization efficiency of the parameters effectively. © The Authors.

关键词： Convolution

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Enhancing Transformer Tracking Using NF-ResNet and ResNeXT Backbones 1

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1st International Conference on Machine Intelligence for Research and Innovations, MAiTRI 2023

作者： Verma, Sourabh Singla, Rajesh Verma, Om Prakash Sharma, Richa Gupta, Himanshu Sharma, Tarun Muthanna, Ammar Department of Instrumentation and Control Engineering Dr. B R Ambedkar National Institute of Technology Jalandhar Punjab Jalandhar India Department of Computer Science—Internet of Things ABES Institute of Technology Ghaziabad India University Meerut India Saint-Petersburg State University of Telecommunications Saint Petersburg Russia

ISBN: (数字)9789819981359

ISBN: (纸本)9789819981342

Residual networks play a foremost role in the domain of tracking, specifically in the extraction of features. The residual networks are using a simple technique of skipping connections to overcome the problem of vanishing gradient. Also, it is using batch normalization after each layer of convolution to accelerate the training by reducing the dependency over the parameters. Though, we have tried to solve these issues by introducing ResNeXt and NF-ResNet one by one into the TransT tracker as feature extractors in the place of ResNet. Finally, we present a ResNeXt-based TransT tracker (named as TransT_NeXt) and NF-Net-based TransT tracker (named as TransT_NFNet). We have evaluated proposed trackers on three large-scale benchmark datasets and four small-scale benchmark datasets but unfortunately, our trackers haven’t performed well. At last, we have discussed about the future work on the basis of this study. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Large datasets

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Research on Task Decomposition and Motion Trajectory Optimization of Robotic Arm Based on VLA Large Model 5

Research on Task Decomposition and Motion Trajectory Optimiz...

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5th International Conference on Machine Learning and computer Application, ICMLCA 2024

作者： Lu, Wentao Wu, Xiaofeng Gao, Shuyong He, Wei Zhao, Qing Zhang, Lunning Li, Maodong Zhang, Wenqiang Fudan University Department of Electronic Engineering Shanghai China School of Computer Science Fudan University Shanghai China Academy for Engineering & Technology Fudan University Shanghai China Shanghai Future Space-Time Technology Co. Ltd. Department of hardware support Shanghai China University of Macau State Key Laboratory of Internet of Things for Smart City China

ISBN: (纸本)9798331530334

With the continuous advancement of intelligent robotics, efficient execution of multiple tasks in complex environments has emerged as a critical research area. In this paper, we propose an innovative framework based on visual-linguistic alignment and visual-language-action (VLA) models to enhance the task decomposition and motion trajectory optimization capabilities of robotic arms. Our model leverages multimodal fusion of visual information and natural language instructions to automatically understand and decompose complex tasks. While existing VLA models demonstrate strong integration of vision, language, and motion, they often depend heavily on the diversity and coverage of training data, limiting their generalization to diverse tasks, especially in cross-domain scenarios. Furthermore, the simplistic treatment of inputs by current VLA models can hinder the deep understanding of visual content and create ambiguities in interpreting abstract or unclear linguistic commands, which reduces the accuracy of task decomposition and execution. To address these limitations,this paper proposes a more robust multimodal fusion mechanism that integrates a hybrid module combining multiple cross-attention and self-attention mechanisms. By incorporating appropriate image and language encoding modalities, the model improves the processing of complex natural language instructions, enhances multimodal fusion, and refines task decomposition and execution. This provides a significant improvement over traditional VLA models, while also enhancing generalization across diverse task scenarios. Experimental results demonstrate that the model achieves faster response times and greater robustness, particularly in noisy environments. These advancements make the model more suitable for practical applications and lay a solid foundation for the future deployment of single-arm robots in varied task environments. © 2024 IEEE.

关键词： Robotic arms

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Weighted Fuzzy C Means: A Novel Tumor Segmentation Approach in MR Brain Images 2

Weighted Fuzzy C Means: A Novel Tumor Segmentation Approach ...

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2nd International Conference on Automation, Computing and Renewable Systems, ICACRS 2023

作者： Poshitha, M. Ramaraj, Kottaimalai Dilipkumar, S. Meena, Durga R. Ambika, B. Thilagaraj, M. Department of Computer Science and Engineering MVJ College of Engineering Bengaluru India Department of Electronics and Communication Engineering Kalasalingam Academy of Research and Education Tamilnadu Krishnankoil India Department of Electrical and Electronics Engineering Sri Krishna College of Technology Tamilnadu Coimbatore India Department of Computer Science and Engineering Kalasalingam Academy of Research and Education Tamilnadu Krishnankoil India Department of Electrical and Electronics Engineering Thiagarajar College of Engineering Tamilnadu Madurai India Department of Industrial Internet of Things MVJ College of Engineering Bengaluru India

ISBN: (纸本)9798350340235

The most prevalent primary brain tumor, glioma, is caused by glial cell carcinogenesis in the central nervous system. For numerous applications in the area of health care evaluation, brain tumor localization and separation from magnetic resonance images (MRI) are challenging yet crucial tasks. Several recently developed methods utilized four modalities: T1, T1c, T2, and FLAIR. This is because each brain imaging modality provides distinct and important information concerning every region of the tumor. The process of diagnosis, therapy selection, and risk variables detection depends on trustworthy and precise tumor segmentation and survival of patients forecasting. In this article, a state-of-the-art fuzzy-based system is introduced that uses multimodal MRI images to categorize brain tumors and estimate glioma survival. To address the drawbacks of the FCM, the suggested approach combined the weight function with the conventional Fuzzy C-means (FCM). Extensive tests are carried out on the different BRATS challenge datasets, demonstrating that the suggested approach achieves competitive outcomes. Evaluation on the BraTS dataset confirms the effectiveness of the developed Weighted FCM (WFCM), and the segmented results are compared with the ground truth images. A small number of performance metrics were also used for assessing the qualitative as well as quantitative outcomes. The resulting dissected images help medical professionals diagnose, medicate, or plan for medical intervention for the affected individuals earlier. © 2023 IEEE.

关键词： Brain tumor Brain Tumor Segmentation (BraTS) dataset Glioma Magnetic Resonance Imaging (MRI) Segmentation Weighted Fuzzy C-means (WFCM)

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Delay Minimization for Intelligent Reflecting Surface Assisted Federated Learning

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China Communications 2022年第4期19卷 216-229页

作者： Ning Huang Tianshun Wang Yuan Wu Suzhi Bi Liping Qian Bin Lin State Key Laboratory of Internet of Things for Smart City University of MacaoMacaoChina Department of Computer and Information Science University of MacaoMacaoChina Zhuhai-UM Science and Technology Research Institute Zhuhai 519031China College of Electronics and Information Engineering Shenzhen UniversityShenzhen 518060China College of Information Engineering Zhejiang University of TechnologyHangzhou 310014China Department of Communication Engineering Dalian Maritime UniversityDalian 116026China

Federated learning(FL), which allows multiple mobile devices to cooperatively train a machine learning model without sharing their data with the central server, has received widespread ***, the process of FL involves frequent communications between the server and mobile devices,which incurs a long latency. Intelligent reflecting surface(IRS) provides a promising technology to address this issue, thanks to its capacity to reconfigure the wireless propagation environment. In this paper, we exploit the advantage of IRS to reduce the latency of FL. Specifically, we formulate a latency minimization problem for the IRS assisted FL system, by optimizing the communication resource allocations including the devices’ transmit-powers, the uploading time, the downloading time, the multi-user decomposition matrix and the phase shift matrix of IRS. To solve this non-convex problem, we propose an efficient algorithm which is based on the Block Coordinate Descent(BCD) and the penalty difference of convex(DC) algorithm to compute the solution. Numerical results are provided to validate the efficiency of our proposed algorithm and demonstrate the benefit of deploying IRS for reducing the latency of FL. In particular, the results show that our algorithm can outperform the baseline of Majorization-Minimization(MM) algorithm with the fixed transmit-power by up to 30%.

关键词： federated learning intelligent reflecting surface latency minimization

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Dual-Polarized 3-D Microwave Absorbers With Synthesizable Operating Bandwidth, Absorptive Resistance, and Absorption Ratio

Dual-Polarized 3-D Microwave Absorbers With Synthesizable Op...

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IEEE International Wireless Symposium (IWS)

作者： Tian-Xi Feng Lei Zhu Hui Li School of Information and Communication Engineering Dalian University of Technology Dalian China Department of Electrical and Computer Engineering Faculty of Science and Technology State Key Laboratory of Internet of Things for Smart City University of Macau Macau China

ISBN: (数字)9798350389999

ISBN: (纸本)9798350390001

This paper proposes dual-polarized 3-D microwave absorbers. The working strategy of single-polarized design is firstly analyzed with the equivalent transmission line model. In this way, the absorptive performance, including operating bandwidth, absorptive resistance, and absorption ratio, can be easily synthesized. Characteristic impedances for different absorptive performance are given to provide more design selection. Besides, only one absorptive resistor is employed in the proposed absorber element, avoiding complex structure with multiple resistors. Two absorbers are successfully implemented with different operating bandwidths and absorptive resistances to verify the selectable performance. Finally, the single-polarized designs are extended to dual-polarized versions. Good agreement can be seen for two perpendicular polarizations with expected performance, which further prove the proposed design concept.

关键词： Resistance Resistors Microwave measurement Wireless communication Analytical models Solid modeling Power transmission lines Absorption Bandwidth Transmission line measurements

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