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Transforming 6G Mobile Edge Intelligence with Large Models

IEEE Network 2025年

作者： He, Xiaoming Jiang, Yunzhe Liu, Yinqiu Cui, Huajun Pan, Heng Mao, Yingchi Nanjing University of Posts and Telecommunications College of Internet of Things Nanjing China University of Electronic Science and Technology of China College of Communication and Information Engineering Chengdu China Nanyang Technological University College of Computing and Data Science Singapore PowerChina Beijing Engineering Corporation Limited Digital Intelligence Research Institute Beijing China Zhongyuan University of Technology Zhengzhou China Hohai University College of Computer Science and Software Engineering Nanjing China

Large models (LMs) exhibit transformative power in 6G Mobile-Edge Intelligence (MEI) scenarios, which can effectively address key challenges regarding network complexity, resource optimization, intelligent decision-making, and user experience. In this article, we first introduce the basics of LM and explain the potential applications and existing solutions for integrating LMs into 6G MEI. Afterward, we conduct a case study oriented to LM-assisted 6G MEI scenarios, focusing on how to use LMs to predict the size of traffic. Specifically, we employ two attention modules named Dartboard Spatial Multi-head Self-Attention (DS-MSA) and Causal Temporal Multi-head Self-Attention (CT-MSA) to extract spatio-temporal features. A Large Language Model (LLM) named GPT-2 is utilized as the backbone model. To fit time-series data, the original token encoding layer is replaced by the convolutional encoding layer. Additionally, to handle multi-scale temporal information, we adopt an additional temporal encoding layer. During training, the majority of the pre-trained parameters are frozen, with only the input/output layers and the fully connected layer involved in parameter updates. The simulation results demonstrate that, compared to the traditional AI-based baselines, the proposed LM-based framework acquires a lower training loss and converges faster. Moreover, it achieves better prediction accuracy with less resource consumption. © 1986-2012 IEEE.

关键词： Spatio-temporal data

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Dendrite Growth Behaviors and Optimization Models for Predicting Primary and Secondary Dendrite Arm Spacing in Directionally Solidified High Mn-Cr-C Wear-Resistant Alloy

SSRN

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SSRN 2024年

作者： Liu, Hongbo Min, Li Rongyuan, Xie Xiaorui, Che Ying, Liu Jianhua, Liu Yang, He Hao, Xu Zhang, Caidong Zhiqiang, Tian Shuangjiang, Li Material Technology Research Institute HBIS Group Hebei Shijiazhuang050023 China Digital Technology Co. Ltd HBIS Group Hebei Shijiazhuang050100 China National Engineering Research Center for Advanced Rolling and Intelligent Manufacturing University of Science and Technology Beijing Beijing Beijing100083 China

The dendrite growth behaviors and solidification microstructure of high Mn-Cr-C wear-resistant alloy (high Mn-Cr-C alloy) were systematically investigated by means of series of directional solidification experiments and theoretical calculation. The primary dendrite arm spacing (PDAS) decreased from 423.6μm to 179.6μm when the growth velocities increased from 5μm/s to 300μm/s. Meanwhile, the secondary dendrite arm spacing (SDAS) narrowed from 110.38μm to 30.66μm. Six classical models were used to predict PDAS and SDAS of high Mn-Cr-C alloy in the present study, the prediction results of which could not fit well with the experimental results. Thus, the optimization models for predicting PDAS and SDAS were established in directionally solidified high Mn-Cr-C alloy. The relational expression between PDAS, SDAS and dendrite growth velocities were Y=173.01+264.21•e(-X/86.77) and Y=180.05•X-0.299, the regression coefficients of which were up to 0.999 and 0.993, respectively. © 2024, The Authors. All rights reserved.

关键词： Manganese alloys

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Advance and Application of Single‑cell Transcriptomics in Auditory research

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Neuroscience Bulletin 2024年第7期40卷 963-980页

作者： Xiangyu Ma Jiamin Guo Mengyao Tian Yaoyang Fu Pei Jiang Yuan Zhang Renjie Chai State Key Laboratory of Digital Medical Engineering Department of Otolaryngology Head and Neck SurgeryZhongda HospitalSchool of Life Sciences and TechnologyAdvanced Institute for Life and HealthJiangsu Province High‑Tech Key Laboratory for Bio‑Medical ResearchSoutheast UniversityNanjing 210096China Department of Psychiatry Affiliated Hangzhou First People’s HospitalZhejiang University school of MedicineHangzhou 310030China Department of Otolaryngology Head and Neck Surgery Affiliated Drum Tower Hospital of Nanjing University Medical SchoolJiangsu Provincial Key Medical Discipline(Laboratory)NanjingChina Research Institute of Otolaryngology Nanjing 210008China Department of Otolaryngology Head and Neck Surgery Sichuan Provincial People’s HospitalUniversity of Electronic Science and Technology of ChinaChengdu 610072China Co‑Innovation Center of Neuroregeneration Nantong UniversityNantong 226001China Institute for Stem Cell and Regeneration Chinese Academy of ScienceBeijing 101408China Beijing Key Laboratory of Neural Regeneration and Repair Capital Medical UniversityBeijing 100069China

Hearing loss and deafness,as a worldwide disability disease,have been troubling human ***,the auditory organ of the inner ear is highly heterogeneous and has a very limited number of cells,which are largely uncharacterized in ***,with the development and utilization of single-cell RNA sequencing(scRNA-seq),researchers have been able to unveil the complex and sophisticated biological mechanisms of various types of cells in the auditory organ at the single-cell level and address the challenges of cellular heterogeneity that are not resolved through by conventional bulk RNA sequencing(bulk RNAseq).Herein,we reviewed the application of scRNA-seq technology in auditory research,with the aim of providing a reference for the development of auditory organs,the pathogenesis of hearing loss,and regenerative *** about spatial transcriptomic scRNA-seq,single-cell based genome,and Live-seq technology will also be discussed.

关键词： Single-cell RNA sequencing Inner ear Cochlear Auditory sensory epithelium Spiral ganglion neuron

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Imperceptible and Reliable Adversarial Attack 1

引用

4th International Conference on Frontiers in Cyber Security, FCS 2021

作者： Zhang, Jiawei Wang, Jinwei Luo, Xiangyang Ma, Bin Xiong, Naixue School of Computer and Software Engineering Research Center of Digital Forensics Ministry of Education Nanjing University of Information Science and Technology Nanjing210044 China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhenzhou450001 China Shandong Provincial Key Laboratory of Computer Networks and Qilu University of Technology Jinan250353 China Department of Computer Science and Mathematics Sul Ross State University AlpineTX79830 United States

ISBN: (数字)9789811905230

ISBN: (纸本)9789811905223

Deep neural networks are vulnerable to adversarial examples, which can fool classifiers by adding small perturbations. Various adversarial attack methods have been proposed in the past several years, and most of them add the perturbation in a "sparse" or "global" way. Since the number of pixels perturbed by the "sparse" method and the perturbation intensity of each pixel added by the "global" method are both small, the adversarial property can be destroyed easily. Finally, it makes the adversarial attack and the adversarial training based on these samples unreliable. To address this issue, we present an "pixel-wise" method which is somewhere in between the "sparse" or "global" way. First, the perception of human eyes to the error of different image regions is different. Second, image processing methods have different effects on the different areas of the image. Based on these two considerations, we propose an imperceptible and reliable adversarial attack method, which projects the perturbation to the different areas differently. Extensive experiments demonstrate our method can preserve the attack ability while maintaining good view quality. More importantly, the proposed projection can be combined with existing attack methods to generate a stronger generation algorithm which improves the robustness of adversarial examples. Based on the proposed method, the reliability of adversarial attacks can be greatly improved. © 2022, Springer Nature Singapore Pte Ltd.

关键词： Pixels

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LarTap: A Luminance-aware Framework with Text-correlation Priors for Multi-Exposure Image Fusion

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IEEE Transactions on Circuits and Systems for Video Technology 2025年

作者： Wang, Enlong Li, Jiawei Yan, Tiantian Lei, Jia Zhou, Shihua Wang, Bin Liu, Jinyuan Kasabov, Nikola K. Dalian University Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian116622 China University of the Science and Technology Beijing School of Computer and Communication Engineering Beijing100083 China Xi’an Jiaotong University School of Software Engineering Shaanxi Xi’an710049 China Dalian Univer sity of Technology School of Mechanical Engineering Dalian116024 China Auckland University of Technology Knowledge Engineering and Discovery Research Institute Auckland1061 New Zealand

Conventional imaging devices often struggle to produce high-dynamic-range (HDR) images that accurately represent natural scenes. To overcome this limitation, multi-exposure image fusion (MEF) techniques have been introduced as a viable solution. Existing MEF approaches aim to enhance performance by optimizing or searching architectures. However, they face challenges in precise feature extraction and scene reconstruction, leading to distortion in the fused images. Additionally, most methods do not adequately address luminance variations across different image regions, which may result in the loss of essential details. To address these challenges, we present a novel luminance-aware MEF framework that integrates text-correlation priors (LarTap). By embedding textual information into fusion process, the proposed framework enhances content extraction and comprehension. Specifically, it consist of two key components: the text-image correlation network (N1) and the multi-exposure fusion network (N2). First, N1 performs correlation training to achieve a holistic alignment between text and image pairs. Its iterative vision encoders (VEs) generate text-correlated prior knowledge to facilitate the fusion process in N2. Second, N2 leverages these priors for scene reconstruction and dynamically adjusts luminance based on comparative perception. Extensive experiments on multiple datasets demonstrate that LarTap outperforms state-of-the-art methods. © 1991-2012 IEEE.

关键词： Image correlation

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Generation of highly-pure single-photon states at telecommunication wavelength

Generation of highly-pure single-photon states at telecommun...

引用

Frontiers in Optics, FiO 2022

作者： Kawasaki, Akito Takase, Kan Nomura, Takefumi Miki, Sigehito Terai, Hirotaka Yabuno, Masahiro China, Fumihiro Asavanant, Warit Endo, Mamoru Yoshikawa, Jun-Ichi Furusawa, Akira Department of Applied Physics School of Engineering The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-8656 Japan Optical Quantum Computing Research Team RIKEN Center for Quantum Computing 2-1 Hirosawa Saitama Wako351-0198 Japan Advanced ICT Research Institute National Institute of Information and Communications Technology 588-2 Iwaoka Nishi-ku Hyogo Kobe651-2492 Japan Graduate School of Engineering Kobe University 1-1 Rokkodai-cho Nada-ku Hyogo Kobe657-0013 Japan

We generate highly-pure single-photon states at the telecommunication wavelength with the best record of the minimum Wigner negativity, paving the way toward the integration of universal quantum computers and construc...

ISBN: (纸本)9781557528209

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Efficient Finite-Difference Time-Domain Method for Solving Electromagnetic Scattering in Layered Anisotropies

Efficient Finite-Difference Time-Domain Method for Solving E...

引用

International Symposium on Antennas, Propagation and EM Theory (ISAPE)

作者： Yilin Kang Yuxian Zhang Xiaoli Feng Lixia Yang Zhixiang Huang Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education and with the Information Materials and Intelligent Sensing Laboratory of Anhui Province Industry-Education-Research Institute of Advanced Materials and Technology for Integrated Circuits and with School of Electronic and Information Engineering Anhui University Hefei China

ISBN: (数字)9798350353129

ISBN: (纸本)9798350353136

In this article, we propose an efficient numerical method for layered models based on the conventional finite difference time-domain (FDTD) method. The three-dimensional (3-D) layered model is compressed into one-dimensional (1-D) calculation, which improves the problem of large space memory and long running time for 3-D modeling while ensuring the accuracy and feasibility of the algorithm. On the one hand, by employing the transformation relationship between the transverse wave vector and the field in space, the expanded Maxwell's rotation equations are simplified, so that the equation system only retains the spatial transformation in the propagation direction. This processing allows for the calculation of the propagation characteristics of layered media without requiring more computational resources. On the other hand, to ensure the universality of the algorithm, a fully tensor anisotropic medium is selected for detecting the propagation data. At the same time, we design the layered structure and conduct the consistent 3-D modeling in the simulation software COMSOL. The results showed that our proposed efficient numerical algorithm greatly reduced the loss of computing resources while ensuring accuracy.

关键词： Solid modeling Three-dimensional displays Accuracy Tensors Software algorithms Vectors Mathematical models Numerical models Time-domain analysis Finite difference methods

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Ultrafiltration Polyethersulfone-Mxene Mixed Matrix Membranes with Enhanced Air Dehumidification and Oil-Water Separation Performance

SSRN

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SSRN 2023年

作者： Nabeeh, Ahmed Abdalla, Omnya Rehman, Abdul Ghouri, Zafar Khan Khan Abdel-Wahab, Ahmed Abdala, Ahmed Mahmoud, Khaled Chemical Engineering Program Texas A&M University at Qatar POB 23874 Doha Qatar Qatar Environment and Energy Research Institute Hamad Bin Khalifa University Doha Qatar School of Computing Engineering & Digital Technologies Teesside University Middlesbrough United Kingdom

Membrane technology holds significant potential for water treatment and air dehumidification. However, current membranes are constrained by limitations in water flux and pollutant rejection. This study introduces a novel approach to enhance the performance of microfiltration membranes by incorporating Ti3C2Tx MXene nanomaterials into polyethersulfone to fabricate a series of mixed matrix membranes (MMMs). Comprehensive characterization through SEM, TEM, XRD, and AFM reveals enhanced morphology, hydrophilicity and mechanical robustness. These improvements directly contribute to performance metrics that surpass the control PES membrane reach pure water of 2280 LMH/bar and an oil rejection of 98%. The fortified mechanical properties further enable the membranes to operate effectively under elevated pressures, reducing both flux degradation and operational failures. Significantly, the study marks the first application of MXene-based membranes in air dehumidification, with the MMM membranes exhibiting a water vapor permeance (WVP) of 18,100 GPU, compared to 15,900 GPU for the control PES membranes. These advancements affirm PES-MXene MMMs as scalable, high-performance solutions with new avenues for application in water treatment and air dehumidification. © 2023, The Authors. All rights reserved.

关键词： Ultrafiltration

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Enhancing Cybersecurity in Sustainable Energy: Regulatory Compliance, Challenges, and Policy Innovations

Enhancing Cybersecurity in Sustainable Energy: Regulatory Co...

引用

Sustainable Energy Technologies and Computational Intelligence (SETCOM), International Conference on

作者： Shruti Saxena Shivani Saxena Nikunj Tahilramani Ujjawal Patel Vandana P. Talreja Ashish Patel Dept. of School of Cyber Security & Digital Forensics National Forensics Sciences University Gandhinagar India Dept. of Computer Sciences & Engineering Institute of Advanced Research Gandhinagar India Dept. of Big Data Analytics Adani Institute of Digital Technology Management Gandhinagar India Electrical engg.dept R.C.Technical Institute Ahmedabad India Sr AWS AI ML Solution Architect IBM India

ISBN: (数字)9798331520540

ISBN: (纸本)9798331520557

The global switch to renewable energy is both a necessity for sustainable development and climate change mitigation. However, this transition is coupled with unique cyber security issues because of the greater reliance on networked digital systems. This paper identifies significant flaws in the current cyber security regulations and procedures while highlighting their effectiveness in the renewable energy sector. Recent research with the analysis highlighted the necessity of adaptable regulatory tools and the particular vulnerabilities that exist in renewable energy networks. According to the report, stronger regulations on the policymaking side must be enforced: rigorous regulatory compliance, increased robustness, and the incorporation of newer security practices that address changing threats. We explore how the integration of cutting-edge technology such as artificial intelligence (AI) could strengthen system resilience using current case studies like China’s renewable energy projects and Germany’s Energiewende. Furthermore, the importance of cybersecurity in the attainment of the Sustainable Development Goals (SDGs) is evaluated based on how it supports environmental conservation, economic development, and renewable energy. This research will aid the stakeholders and policymakers in making a safe and sustainable energy future.

关键词： Renewable energy sources Climate change Energy measurement Regulation Stakeholders Sustainable development Artificial intelligence Computer crime Computer security Risk management

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A Sensitive Image Generation Method Based on Improved PatchGAN

A Sensitive Image Generation Method Based on Improved PatchG...

引用

Information and Communication Technology (ICTech), International Conference of

作者： Shilin Zhang Hongliang Wang Liang Wang Chinese Academy of Sciences Shenyang Institute of Computing Technology Shenyang China University of Chinese Academy of Sciences Beijing China Liaoning Province Human-Computer Interaction System Engineering Research Center Based on Digital Twin Shenyang China

Aiming at the problem of less data and unbalanced number of sensitive image samples in the deep learning task of sensitive image detection, this paper proposes a sensitive image generation method SI-GAN based on improved PatchGAN. The SI-GAN generator uses the DUD module, and uses the concat method to increase the number of channels of the feature map in the quantitative dimension, which improves the generation ability of the generator. The SI-GAN discriminator uses the RBL module to improve PatchGAN, extract more advanced feature information, and increase the discriminant's discriminative ability. The experimental results show that SI-GAN has better results in terms of generated image quality. The FID value of SI-GAN is 5.87 lower than that of PatchGAN. The IS value of SI-GAN is 5.09 more than PatchGAN. The SI-GAN proposed in this paper is able to optimize the quality of the generated images and generate images with more details.

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