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6th International Conference on Electronic Engineering and Informatics, EEI 2024

作者： Huang, Tingting Yang, Shiju He, Hongsen Zhou, Yuting Guo, Zhiwei Chongqing Technology and Business University Chongqing Key Laboratory of Intelligent Perception and BlockChain Technology Chongqing400067 China

ISBN: (纸本)9798350353594

This article mainly investigates the unidirectional interlayer stability of the Two-Layer networks with pinning impulsive control. Firstly, by using multi-span step-function method, the interlayer stability of Two-Layer networks with pinning impulsive control can be analyzed. In addition, the novel pinning impulsive controllers are formulated. Secondly, a comparison system is constructed by using auxiliary system method and impulsive control theory, and several new sufficient criteria are given to ensure the stability. Finally, the correctness of theoretical analysis is proved by experimental cases. © 2024 IEEE.

关键词： Stability criteria

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Multi-Skeleton Joint Behavior Recognition Method Based on a Dual-Stream Network 13

Multi-Skeleton Joint Behavior Recognition Method Based on a ...

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13th International Conference on Electronics, Communications and Networks, CECNet 2023

作者： Mou, Hongda Tang, Lianggui Ran, Jing Wang, Xue Peng, Song Zhu, Xiuling Tang, Chan College of Artificial Intelligence Chongqing Technology and Business University China Chongqing Key Laboratory of Intelligent Perception and Blockchain Technology China

ISBN: (纸本)9781643684802

Skeleton joint data, as a representation closely related to human actions, has received significant attention in the field of human behavior recognition in recent years. However, current methods for behavior recognition using skeleton data face several challenges, such as insufficient accuracy and reliance on a single modality. To address these challenges, a multi-stream network approach for behavior recognition using multiple skeleton joints is proposed. Firstly, a top-down approach is employed to extract the coordinates of 133 key skeleton joints from the human body, which are then represented as heatmaps. Subsequently, in the PoseRgb model, RGB data is used as input for the RGB channel to capture spatial features, while the heatmap representations of skeleton data are utilized as input for the Pose channel to capture temporal features. Leveraging the fusion capabilities of heatmaps, these two channels are merged using lateral connections, ultimately yielding behavior recognition results. Experimental results demonstrate that on widely-used UCF101 and HMDB51 datasets, the accuracy reaches 99.05% and 86.1%, respectively. Compared to the Temporal Shift Module (TSM) network, there is a 5% and 15% improvement in accuracy, respectively. The proposed method effectively combines spatial and temporal information in videos, resulting in more accurate behavior recognition. © 2024 The authors and IOS Press.

关键词： Behavioral research

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Directed Acyclic Graph blockchain for Secure Spectrum Sharing and Energy Trading in Power IoT

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China Communications 2023年第5期20卷 182-197页

作者： Zixi Zhang Mingxia Zhang Yu Li Bo Fan Li Jiang School of Automation Guangdong-HongKong-Macao Joint Laboratory for Smart Discrete Manufacturing(Guangdong University of Technology)Guangzhou 510006China Chongqing Key Laboratory of Intelligent Perception and BlockChain Technology (Chongqing Technology and Business University)Chongqing 40067China Beijing Key Laboratory of Traffic Engineering College of Metropolitan Transportation(Beijing University of Technology)Beijing 100124China

Peer-to-peer(P2P)spectrum sharing and energy trading are promising solutions to locally satisfy spectrum and energy demands in power Internet of Things(IoT).However,implementation of largescale P2P spectrum sharing and energy trading confronts security and privacy *** this paper,we exploit consortium blockchain and Directed Acyclic Graph(DAG)to propose a new secure and distributed spectrum sharing and energy trading framework in power IoT,named spectrum-energy chain,where a set of local aggregators(LAGs)cooperatively confirm the identity of the power devices by utilizing consortium blockchain,so as to form a main ***,the local power devices verify spectrum and energy micro-transactions simultaneously but asynchronously to form local spectrum tangle and local energy tangle,***,an iterative double auction based micro transactions scheme is designed to solve the spectrum and energy pricing and the amount of shared spectrum and energy among power *** analysis and numerical results illustrate that the developed spectrum-energy chain and the designed iterative double auction based microtransactions scheme are secure and efficient for spectrum sharing and energy trading in power IoT.

关键词： power Internet of Things(IoT) spectrum sharing energy trading security and privacy consortium blockchain Directed Acyclic Graph(DAG) iterative double auction

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Multi-stage Pricing Mechanism in Duopoly Computation Markets 17th

Multi-stage Pricing Mechanism in Duopoly Computation Market...

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CCF 17th International Conference on Service Science, CCF ICSS 2024

作者： Chen, Pengyang Wang, Quyuan Liu, Jiadi Wang, Ying Guo, Zhiwei Chongqing Key Laboratory of Intelligent Perception and BlockChain Technology Chongqing Technology and Business University Chongqing400067 China College of Computer and Information Science College of Software Southwest University Chongqing400710 China

ISBN: (纸本)9789819757596

A new generation of computing paradigms has been proposed to facilitate people’s daily lives, and there is a lot of literature on resource allocation in these paradigms to enhance the user experience. It is also essential to investigate how to incentive users to participate in these computing paradigms to share their surplus resources. In this paper, we formulate multi-stage profit-maximizing optimization problems in duopoly computation market considering consumer value, provider reputation, Bandwagon Effect, and consumer heterogeneity from an economic perspective. In the pre-sale phase we propose the Demand Priority Pricing Algorithm (DPPA) algorithm to help providers find optimal pre-sale prices. For the formal sales phase, we design the Community Proportion Prediction Algorithm (CPPA) to predict key parameters and the Incremental Priority Pricing Algorithm (IPPA) to help providers choose pricing schemes. Finally, experimental results show that our model describes market laws well and our algorithms assist providers in finding profit-maximizing pricing schemes for fair and stable markets. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Computational cost

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Deep learning approaches to recover the plasma current density profile from the safety factor based on Grad–Shafranov solutions across multiple tokamaks

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Plasma Science and technology 2024年第5期26卷 17-28页

作者：张瀚予周利娜刘钺强郝广周王硕杨旭苗雨田段萍陈龙 College of Science Dalian Maritime UniversityDalian 116026People’s Republic of China General Atomics San Diego 92186-5608United States of America Southwestern Institute of Physics Chengdu 610041People’s Republic of China Chongqing Key Laboratory of Intelligent Perception and BlockChain Technology Chongqing Technology and Business UniversityChongqing 400067People’s Republic of China

Many magnetohydrodynamic stability analyses require generation of a set of equilibria with a fixed safety factor q-profile while varying other plasma parameters.A neural network(NN)-based approach is investigated that facilitates such a *** multilayer perceptron(MLP)-based NN and convolutional neural network(CNN)models are trained to map the q-profile to the plasma current density J-profile,and vice versa,while satisfying the Grad–Shafranov radial force balance *** the initial target models are trained,using a database of semianalytically constructed numerical equilibria,an initial CNN with one convolutional layer is found to perform better than an initial MLP *** particular,a trained initial CNN model can also predict the q-or J-profile for experimental tokamak *** performance of both initial target models is further improved by fine-tuning the training database,*** adding realistic experimental equilibria with Gaussian *** fine-tuned target models,referred to as fine-tuned MLP and fine-tuned CNN,well reproduce the target q-or J-profile across multiple tokamak *** an important application,these NN-based equilibrium profile convertors can be utilized to provide a good initial guess for iterative equilibrium solvers,where the desired input quantity is the safety factor instead of the plasma current density.

关键词： plasma equilibrium deep learning safety factor profile current density profile tokamak

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Spatiotemporal deformation analysis of glaciers and surrounding landscapes in the Shishapangma region using InSAR techniques

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Journal of Mountain Science 2025年第1期22卷 210-229页

作者： LIANG Wenli LIU Rui JI Qin KOU Pinglang Chongqing Key Laboratory of GIS Application School of Geography and TourismChongqing Normal UniversityChongqing 401331China National Earth System Science Data Center Beijing 100000China Chongqing Engineering Research Center of Spatial Big Data Intelligent Technology Chongqing University of Posts and TelecommunicationsChongqing 400065China Key Laboratory of Tourism Multisource Data Perception and Decision Ministry of Culture and Tourism(TMDPDMCT)Chongqing University of Posts and TelecommunicationsChongqing 400065China

Glacier dynamics in the Himalayan midlatitudes,particularly in regions like the Shishapangma,are not yet fully understood,especially the localized topographic and climatic impacts on glacier *** study analyzes the spatiotemporal characteristics of glacier surface deformation in the Shishapangma region using the Small Baseline Subset(SBAS)Interferometric Synthetic Aperture Radar(In SAR)*** analysis reveals an average deformation rate of-4.02±17.65 mm/yr across the entire study area,with glacier regions exhibiting significantly higher rates of uplift(16.87±13.20 mm/yr)and subsidence(20.11±14.55 mm/yr)compared to non-glacier *** identifies significant surface lowering on the mountain flanks and localized uplift in certain catchments,emphasizing the higher deformation rates in glacial areas compared to non-glacial *** found a strong positive correlation between temperature and cumulative deformation(correlation coefficient of 0.63),particularly in glacier areas(0.82).The research highlights the role of temperature as the primary driver of glacier wastage,particularly at lower elevations,with strong correlations found between temperature and cumulative *** also indicates the complex interactions between topographic features,notably,slope gradient,which shows a positive correlation with subsidence rates,especially for slopes below 35°.South-,southwest-,and west-facing slopes exhibit significant uplift,while north-,northeast-,and east-facing slopes predominantly ***,we identified transition zones between debris-covered glaciers and clean ice as areas of most intense deformation,with average rates exceeding 30 mm/yr,highlighting these as potential high-risk zones for *** study comprehensively analyzes the deformation characteristics in both glacier and non-glacier areas in the Shishapangma region,revealing the complex interplay of topographic,climatic,and hydrological factors influencing glacier dynamic

关键词： Glacier melting SBAS-InSAR Topographic factors Temperature change Middle Himalayas

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Interlayer Stability Analysis of Two-Layer Networks with Pinning Impulsive by Step Function Method

Interlayer Stability Analysis of Two-Layer Networks with Pin...

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International Conference on Electronic Engineering and Informatics (EEI)

作者： Tingting Huang Shiju Yang Hongsen He Yuting Zhou Zhiwei Guo Chongqing Key Laboratory of Intelligent Perception and BlockChain Technology Chongqing Technology and Business University Chongqing China

ISBN: (数字)9798350353594

ISBN: (纸本)9798350353600

关键词： Delay effects Stability criteria Numerical simulation Delays Control theory Synchronization Informatics Numerical stability Lyapunov methods

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Transformer-based high-fidelity StyleGAN inversion for face image editing 23

Transformer-based high-fidelity StyleGAN inversion for face ...

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7th International Conference on Big Data and Internet of Things, BDIOT 2023

作者： Yang, Chutian He, Xiping Kuang, Qixian Huang, Ling Tao, Lingling Chongqing Technology and Business University Chongqing Key Laboratory of Intelligent Sensing and Blockchain Technology School of Artificial Intelligence China

ISBN: (纸本)9798400708015

Recently, there have been many methods utilizing pre-Trained GAN generators for image editing. To apply these methods to the editing of real images, it is necessary to invert real images into the latent space before proceeding with the editing *** GAN inversion methods have difficulty providing both high-fidelity inversion and high editability for face images. The most common inversion method based on the W+ space has enough ability to describe image details, but sacrifices editability. To address this problem, this paper proposes a Transformer-based StyleGAN inversion model to achieve high-quality editing of real face images. This paper uses the code of the StyleGAN2 mapping network as the initial query vector and the image features extracted by a CNN encoder as the key and value. Multiple updates to the query vector are made using a multi-head cross-Attention module, and the final output query vector is used as the latent code of the inverted image and fed into the generator. The experimental results prove that our method can provide high-fidelity inversion for face images, and the edited images can effectively preserve identity information while achieving precise control over attributes. © 2023 ACM.

关键词： Computer vision

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Embedding diverse features in latent space for face attribute editing 5

Embedding diverse features in latent space for face attribut...

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5th International Conference on Computer Information Science and Artificial Intelligence, CISAI 2022

作者： Yuan, Rui He, Xiping He, Dan Li, Yue Chongqing Key Laboratory of Intelligent Sensing and Blockchain Technology School of Artificial Intelligence Chongqing Technology and Business University Chongqing400067 China

ISBN: (纸本)9781510662520

Face attribute editing, one of the important research directions in face image synthesis and processing techniques, aims to photorealistic editing single or multiple attributes of face images on demand using editing and generation models. Most existing methods are based on generative adversarial networks, using target attribute vectors to control the editing region or Gaussian noise as conditional input to capture texture details. However, these cannot better control the consistency of attributes in irrelevant regions, while the generation of fidelity is also limited. In this paper, we propose a method that uses an optimized latent space to fuse the attribute feature maps into the latent space. At the same time, make full use of the conditional information for additional constraints. Then, in the image generation phase, we use a progressive architecture for controlled editing of face attributes at different granularities. At last, we also conducted an ablation study on the selected training scheme further to demonstrate the stability and accuracy of our chosen method. The experiments show that our proposed approach, using an end-to-end progressive image translation network architecture, obtained qualitative (FID) as well as quantitative (LPIPS) face image editing results. © 2023 SPIE.

关键词： Generative adversarial networks

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intelligent cache and buffer optimization for mobile VR adaptive transmission in 5G edge computing networks

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Digital Communications and Networks 2024年第5期10卷 1234-1244页

作者： Junchao Yang Ali Kashif Bashir Zhiwei Guo Keping Yu Mohsen Guizani Chongqing Key Laboratory of Intelligent Perception and BlockChain Technology School of Artificial IntelligenceChongqing Technology and Business UniversityChongqing400067China Department of Computing and Mathematics Manchester Metropolitan UniversityUK Woxsen School of Business Woxsen UniversityHyderabad 502345India Department of Computer Science and Mathematics Lebanese American UniversityBeirutLebanon Graduate School of Science and Engineering Hosei UniversityTokyo184-8584Japan Machine Learning Department Mohamed Bin Zayed University of Artificial Intelligence(MBZUAI)United Arab Emirates

Virtual Reality(VR)is a key industry for the development of the digital economy in the *** VR has advantages in terms of mobility,lightweight and cost-effectiveness,which has gradually become the mainstream implementation of *** this paper,a mobile VR video adaptive transmission mechanism based on intelligent caching and hierarchical buffering strategy in Mobile Edge Computing(MEC)-equipped 5G networks is proposed,aiming at the low latency requirements of mobile VR services and flexible buffer management for VR video adaptive *** support VR content proactive caching and intelligent buffer management,users’behavioral similarity and head movement trajectory are jointly used for viewpoint *** tile-based content is proactively cached in the MEC nodes based on the popularity of the VR ***,a hierarchical buffer-based adaptive update algorithm is presented,which jointly considers bandwidth,buffer,and predicted viewpoint status to update the tile chunk in client ***,according to the decomposition of the problem,the buffer update problem is modeled as an optimization problem,and the corresponding solution algorithms are ***,the simulation results show that the adaptive caching algorithm based on 5G intelligent edge and hierarchical buffer strategy can improve the user experience in the case of bandwidth fluctuations,and the proposed viewpoint prediction method can significantly improve the accuracy of viewpoint prediction by 15%.

关键词： Virtual reality Adaptive transmission Edge cache Buffer management 5G Mobile edge computing

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