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arXiv 2023年

作者： Shi, Zhaoyuan Lu, Huabing Xie, Xianzhong Yang, Helin Huang, Chongwen Cai, Jun Ding, Zhiguo The Key Laboratory of Intelligent Perception and Computing of Anhui Province Anqing Normal University Anqing China The Key Laboratory of Intelligent Control and Optimization for Industrial Equipment Ministry of Education Dalian University of Technology Dalian116024 China Chongqing Key Lab of Computer networks and Communication Technology Chongqing University of Posts and Telecommunications Chongqing China The Department of Information and Communication Engineering School of Informatics Xiamen University Xiamen361005 China The College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China Department of Electrical and Computer Engineering Concordia University MontrealQCH3G 1M8 Canada The Department of Electrical Engineering Princeton University PrincetonNJ08544 United States The School of Electrical and Electronic Engineering The University of Manchester Manchester United Kingdom

An active reconfigurable intelligent surface (RIS)-aided multi-user downlink communication system is investigated, where non-orthogonal multiple access (NOMA) is employed to improve spectral efficiency, and the active RIS is powered by energy harvesting (EH). The problem of joint control of the RIS’s amplification matrix and phase shift matrix is formulated to maximize the communication success ratio with considering the quality of service (QoS) requirements of users, dynamic communication state, and dynamic available energy of RIS. To tackle this non-convex problem, a cascaded deep learning algorithm namely long short-term memory-deep deterministic policy gradient (LSTM-DDPG) is designed. First, an advanced LSTM based algorithm is developed to predict users’ dynamic communication state. Then, based on the prediction results, a DDPG based algorithm is proposed to joint control the amplification matrix and phase shift matrix of the RIS. Finally, simulation results verify the accuracy of the prediction of the proposed LSTM algorithm, and demonstrate that the LSTM-DDPG algorithm has a significant advantage over other benchmark algorithms in terms of communication success ratio performance. Copyright © 2023, The Authors. All rights reserved.

关键词： Energy harvesting

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Dual-View Pyramid Pooling in Deep Neural Networks for Improved Medical Image Classification and Confidence Calibration

arXiv

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arXiv 2024年

作者： Zhang, Xiaoqing Nie, Qiushi Xiao, Zunjie Zhao, Jilu Wu, Xiao Guo, Pengxin Li, Runzhi Liu, Jin Wei, Yanjie Pan, Yi Center for High Performance Computing Shenzhen Key Laboratory of Intelligent Bioinformatics Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Shenzhen518055 China Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China Department of Statistics and Actuarial Science The University of Hong Kong 999077 Hong Kong Cooperative Innovation Center of Internet Healthcare Zhengzhou University Zhengzhou450001 China Hunan Provincial Key Lab on Bioinformatics School of Computer Science and Engineering Central South University Changsha410083 China Xinjiang Engineering Research Center of Big Data and Intelligent Software School of software Xinjiang University Wulumuqi830046 China Faculty of Computer Science and Control Engineering Shenzhen University of Advanced Technology Shenzhen China

Spatial pooling (SP) and cross-channel pooling (CCP) operators have been applied to aggregate spatial features and pixel-wise features from feature maps in deep neural networks (DNNs), respectively. Their main goal is to reduce computation and memory overhead without visibly weakening the performance of DNNs. However, SP often faces the problem of losing the subtle feature representations, while CCP has a high possibility of ignoring salient feature representations, which may lead to both miscalibration of confidence issues and suboptimal medical classification results. To address these problems, we propose a novel dual-view framework, the first to systematically investigate the relative roles of SP and CCP by analyzing the difference between spatial features and pixel-wise features. Based on this framework, we propose a new pooling method, termed dual-view pyramid pooling (DVPP), to aggregate multi-scale dual-view features. DVPP aims to boost both medical image classification and confidence calibration performance by fully leveraging the merits of SP and CCP operators from a dual-axis perspective. Additionally, we discuss how to fulfill DVPP with five parameter-free implementations. Extensive experiments on six 2D/3D medical image classification tasks show that our DVPP surpasses state-of-the-art pooling methods in terms of medical image classification results and confidence calibration across different DNNs. © 2024, CC BY.

关键词： Deep neural networks

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Design of High Temperature Anticorrosion Diagnosis System for Atmospheric and Vacuum Distillation Unit Based on Forcecontrol and SQL Sever2014 5

Design of High Temperature Anticorrosion Diagnosis System fo...

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5th International Conference on Automation, control and Robotics engineering, CACRE 2020

作者： Zhao, Liang Zhang, Zexin Wang, Lida Liu, Guichang Dalian University of Technology School of Control Science and Engineering Key Lab. of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian China Dalian University of Technology School of Control Science and Engineering Dalian China Dalian University of Technology School of Chemical Engineering Dalian China

ISBN: (纸本)9781728198880

Due to the complex composition of the oil flowing through the refining unit, the equipment anticorrosion work has always been a major problem in petrochemical enterprises, and the corrosion problem is a key factor related to shortening the service life of the atmospheric and vacuum distillation unit. Aiming at the problem of high temperature corrosion of atmospheric and vacuum unit in a petrochemical enterprise and the current situation of corrosion management in the enterprise, this paper designs a high temperature corrosion diagnosis system of atmospheric and vacuum unit based on Forcecontrol configuration development platform. The system uses three dimensional interpolation algorithm to calculate the corrosion rate, and uses Microsoft SQL sever2014 database technology and Forcecontrol 7.1 configuration development platform to realize the comprehensive management of corrosion data, corrosion rate calculation, early warning, expert advice and other functions. Through the function test of each module in the system, and using the actual corrosion data provided by the enterprise to simulate and verify the system, the test results show that the system can achieve the expected functions, and ensure the calculation accuracy of corrosion rate. © 2020 IEEE.

关键词： Distillation

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Multi-level Coordinated Energy Management for Energy Hub in Hybrid Markets with Distributionally Robust Scheduling

arXiv

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arXiv 2022年

作者： Cao, Jiaxin Yang, Bo Zhu, Shanying Chung, Chi Yung Guan, Xinping Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education China Shanghai Engineering Research Center of Industrial Intelligent Control and Management Shanghai200240 China Department of Electrical and Computer Engineering University of Saskatchewan SaskatoonSKS7N 5A9 Canada

Maintaining energy balance and economical operation is significant for multi-energy systems such as the energy hub (EH). However, it is usually challenged by the frequently changing and unpredictable uncertain parameters at different timescales. Under this scope, this paper investigates the coordinated energy management problem for day-ahead and intra-day conditions considering uncertainties of source-load and market prices concurrently. Note that the precise knowledge of distributions about uncertainties may be unaccessible before the decision-making in day-ahead phase. A two-stage chance-constrained model based on distributionally robust approach with ambiguous moment information is proposed to immunize scheduling strategies against the worst-case probability distributions. The first stage is dedicated to obtaining more energy arbitrage and operation flexibility by optimizing bidding strategies in day-ahead power, natural gas and carbon trading markets. The second stage focuses on the optimization of the worst-case expected operation cost. It provides a robust energy equipment and load scheduling strategy for the reference of subsequent intra-day arrangements. With respect to different variations of electrical and thermal components, an intra-day two-timescale coordination is implemented step by step. The energy scheduling is re-dispatched circularly to minimize the operation and penalty costs. The possible energy imbalance is also compensated by this way. As the energy management program is nonlinear, chance-constrained and multi-stage, some linearization and dual transformation techniques are designed to enhance tractability of the program. Experimental results show that the developed multi-level framework results in a carbon emission decrease of 37%, and reduces energy cost averagely 3% compared with corresponding contrasting cases. The obtained strategy validates a good tradeoff between robustness and optimality. Copyright © 2022, The Authors. All rights reser

关键词： Power markets

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Joint high-resolution feature learning and vessel-shape aware convolutions for efficient vessel segmentation

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computers in Biology and Medicine 2025年 191卷 109982-109982页

作者： Zhang, Xiang Zhu, Qiang Hu, Tao Guo, Song Bian, Genqing Dong, Wei Hong, Rao Lin, Xia Ling Wu, Peng Zhou, Meili Yan, Qingsen Mohi-ud-din, Ghulam Ai, Chen Li, Zhou College of Information and Control Engineering Xi'an University of Architecture and Technology Xi'an China Shaanxi Provincial Key Lab of Bigdata of Energy and Intelligence Processing School of Physics and Electronic Information Yanan University Yanan China School of Computer Science and Engineering Northwestern Polytechnical University Xi'an China School of Software Nanchang University Nanchang China School of Cyber Security Zhejiang University Hangzhou China Department of Basic Education and Research Jiangxi Police College Nanchang China Northwestern Polytechnical University China

Clear imagery of retinal vessels is one of the critical shreds of evidence in specific disease diagnosis and evaluation, including sophisticated hierarchical topology and plentiful-and-intensive capillaries. In this work, we propose a new topology- and shape-aware model named Multi-branch Vessel-shaped Convolution Network (MVCN) to adaptively learn high-resolution representations from retinal vessel imagery and thereby capture high-quality topology and shape information thereon. Two steps are involved in our pipeline. The former step is proposed as Multiple High-resolution Ensemble Module (MHEM) to enhance high-resolution characteristics of retinal vessel imagery via fusing scale-invariant hierarchical topology thereof. The latter is a novel vessel-shaped convolution that captures the retinal vessel topology to emerge from unrelated fundus structures. Moreover, our MVCN of separating such topology from the fundus is a dynamical multiple sub-label generation via using epistemic uncertainty, instead of manually separating raw labels to distinguish definitive and uncertain vessels. Compared to other existing methods, our method achieves the most advanced AUC values of 98.31%, 98.80%, 98.83%, and 98.65%, and the most advanced ACC of 95.83%, 96.82%, 97.09%,and 96.66% in DRIVE, CHASE_DB1, STARE, and HRF datasets. We also employ correctness, completeness, and quality metrics to evaluate skeletal similarity. Our method's evaluation metrics have doubled compared to previous methods, thereby demonstrating the effectiveness thereof. © 2025 Elsevier Ltd

关键词： Ophthalmology

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Enhancing The Sulfur Resistance of Mn/Hzsm-5 Catalyst For Selective Catalytic Reduction Of No X By Coupling the Adsorbent

SSRN

引用

SSRN 2024年

作者： Wang, Jiachen He, Ning Zhang, Yanxue Chang, Yuan Liu, Chunyan Jiang, Xiangmei Xie, Hongbin Chen, Shaoyun Liu, Jixing Gao, Junfeng Zhu, Wenshuai Liu, Jiaxu Department of Catalytic Chemistry and Engineering State Key Laboratory of Fine Chemicals Dalian University of Technology Dalian116012 China Shanxi Research Institute of Huairou Laboratory Xiaodian District Huazhang Street Taiyuan030032 China State Key Laboratory of Structural Analysis for Industrial Equipment Dalian University of Technology Dalian116024 China School of Environmental Science and Technology Dalian University of Technology Dalian116024 China School of Chemistry and Chemical Engineering Jiangsu University Zhenjiang212013 China State Key Laboratory of Heavy Oil and Beijing Key Lab of Oil & Gas Pollution Control China University of Petroleum Beijing102249 China

Mn modified ZSM-5 zeolites has attracted considerable attention in selective catalytic reduction of NOx emitted from flue gas of industry because of its excellent low-temperature catalytic activity. However, the inferior sulfur resistance and the uncertain state of the active sites have remained unresolved to date. Here, a novel catalyst coupling the adsorbent (Ce-doped TiO2) and Mn/HZSM-5 with distinct Mn loading in a tandem fashion was designed, which avoided the direct contact of SO2 with the Mn/HZSM-5 by preferentially trapping SO2 to form the sulfate on the surface of adsorbent due to the proximity in millimeter-scale, thereby significantly protecting the active Mn species in ZSM-5 from SO2 poisoning. As a result, the tandem fashion with the coupling of adsorbent and 20Mn/HZSM-5 in millimeter-scale proximity exhibit superior deNOx performance and excellent SO2 resistance. This study provides a promising approach for efficient deNOx in the presence of SO2 toward the green development goal. © 2024, The Authors. All rights reserved.

关键词： Catalyst activity

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Anti-asthmatic mechanism of the Huashanshen dripping pill via suppressing contraction of the airway smooth muscle

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Traditional Medicine Research 2022年第3期7卷 19-27页

作者： Yu Liu Ni-Na Cui Xuan-Shuo Liu Peng-Cheng Lin Lorenzo Pecoraro Giuseppe Venturella Shu-Li Man Wen-Yuan Gao The Innovation Platform for the Development and Construction of Special Project of Key Laboratory for Tibet Plateau Phytochemistry of Qinghai Province(2017-ZJ-Y19) College of pharmacyQinghai Nationalities UniversityXining 810007China State Key Laboratory of Food Nutrition and Safety Key Laboratory of Industrial MicrobiologyMinistry of EducationTianjin Key Laboratory of Industry MicrobiologyNational and Local United Engineering Lab of Metabolic Control Fermentation TechnologyChina International Science and Technology Cooperation Base of Food Nutrition/Safety and Medicinal ChemistryCollege of BiotechnologyTianjin University of Science&TechnologyTianjin 300457China Tianjin Key Laboratory for Modern Drug Delivery and High Efficiency School of Pharmaceutical Science and TechnologyTianjin UniversityTianjin 300072China Department of Agricultural Food and Forest SciencesUniversity of PalermoPalermoItaly

Background:The Huashanshen(HSS)dripping pill has been widely used in asthma for a long time in ***,the relaxant mechanism of HSS is not well ***:In this report,high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry was used to identify the constituents in rat plasma after oral administration of ***-sensitized allergic asthma and isolated trachea were studied for the anti-asthmatic mechanism of ***:D-anisodamine,L-anisodamine,scopolamine and atropine were detected in the rat plasma containing *** was clear that the HSS inhibited the release of inflammatory mediators,regulated the balance of T-helper 1 and T-helper 2 to reduce the airway inflammation,and relaxed the tracheal smooth muscle by controlling the KCa channel,Ca^(2+)influx and release to reduce the airway ***:Atropine,anisodamine and scopolamine might be active compounds of HSS which inhibited the release of inflammatory mediators,regulated the balance of Th1/Th2,and relaxed the tracheal smooth muscle to reduce airway hyperresponsiveness.

关键词： Huashanshen dripping pill HPLC-QTOF-MS allergic asthma airway remodeling inflammation airway smooth muscle

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Blockchain-Based Homomorphic Transaction Framework for Enhanced Consumer Security and Business Scalability

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IEEE Transactions on Consumer Electronics 2024年

作者： Guo, Tao Shang, Fengjun Dai, Xiangguang Liu, Qilie Chongqing University of Posts and Telecommunications School of Computer Science and Technology Chongqing400065 China Key Laboratory of Big Data Intelligent Computing Chongqing400065 China Chongqing Three Gorges University Key Lab. of Intelligent Info. Proc. and Contr. of Chongqing Munic. Institutions of Higher Education Chongqing Engineering Research Center of Internet of Things and Intelligent Control Technology School of Three Gorges Artificial Intelligence Chongqing400044 China Chongqing University of Posts and Telecommunications School of Communications and Information Engineering Chongqing400065 China

Energy trading in distributed microgrids represents an effective means of enhancing the utilization of renewable energy. However, the aggregation of large-scale consumption data may encounter business scalability issues and potential privacy exposure concerns, necessitating the development of novel secure and scalable frameworks for integrating consumption demands between prosumer and microgrid entities. we research focuses on providing a user-friendly transaction model for consumers and microgrid operators. Firstly, a privacy aggregation scheme for user resource requests is designed to ensure the security and decentralization of user data. In addition, the model employs a bidirectional heterogeneous resource allocation mechanism to support the optimal allocation of multiple resources, such as renewable energy, power assets, energy storage devices, and carbon credits, among different microgrids. Finally, a microgrid transaction prototype has been constructed on the Truffle development framework. In this context, smart contracts has been designed to ensure that the transactions are carried out automatically. Experimental results indicate that the scheme provides enhanced security for multi-resource trading in a cluster context relative to existing methodologies. The number of transactions increases linearly with the resource overhead, resulting in more efficient utilization of energy trading. Furthermore, the framework's scalability has been demonstrated through both temporal and spatial considerations. © 1975-2011 IEEE.

关键词： Decentralized finance

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Joining Edge-Enabled Metaverse Services with Network Externality: A Stackelberg Game Approach

Joining Edge-Enabled Metaverse Services with Network Externa...

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Metaverse Computing, Networking and Applications (MetaCom), IEEE International Conference on

作者： Yuna Jiang Jiawen Kang Dusit Niyato Xiaohu Ge Zehui Xiong Minrui Xu Ruilong Deng School of Electronic Information and Communications Huazhong University of Science and Technology Wuhan China School of Automation Guangdong University of Technology Guangzhou China School of Computer Science and Engineering Nanyang Technological University Singapore Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China

The metaverse is defined as a three-dimensional virtual-real fusion network focused on social connection. Edge computing can empower the metaverse by providing computing resources to realize real-time motion tracking, visual or auditory rendering and virtual scene dynamic change at the edge of networks. Users enjoy the immersive experience provided by the Metaverse Service Provider (MSP), and interact through digital avatars in the virtual world by requesting metaverse services. In this paper, we formulate the edge computing resources pricing, metaverse service rendering bitrate pricing and request problem in the metaverse. Especially, we model the interactions among edge servers, the MSP and Metaverse Service Users (MSUs) as a hierarchical three-stage Stackelberg game. The problem of joining edge-enabled metaverse services is also studied with the consideration of network externality, including the network effect and congestion effect. Based on the backward induction method, we derive the optimal computing resources pricing of edge servers, rendering bitrate pricing of the MSP, and rendering bitrate requests of MSUs. We also prove the existence and uniqueness of the Stackelberg game equilibrium. Simulation results show that the network effect can bring more positive utilities to entities when the social tie coefficient among MSUs is higher. Besides, all entities in the edge-enabled metaverse are affected negatively by the congestion effect.

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TSGN: Transaction Subgraph Networks Assisting Phishing Detection in Ethereum

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IEEE Transactions on Dependable and Secure Computing 2025年

作者： Wang, Jinhuan Chen, Pengtao Xu, Xinyao Wu, Jiajing Shen, Meng Xuan, Qi Yang, Xiaoniu Zhejiang University of Technology Institute of Cyberspace Security College of Information Engineering Hangzhou310023 China ZJUT Binjiang Institute of Artificial Intelligence Hangzhou310056 China Fudan University Adaptive Networks and Control Lab Department of Electronic Engineering School of Information Science and Technology Shanghai200433 China Sun Yat-sen University School of Computer Science and Engineering Guangzhou510006 China Beijing Institute of Technology School of Cyberspace Science and Technology Beijing100081 China Shenzhen518066 China National Key Laboratory of Electromagnetic Space Security Jiaxing314033 China

Due to the decentralized and public nature of the blockchain ecosystem, malicious activities on the Ethereum platform impose immeasurable losses on users. At the same time, the transparency of cryptocurrency transactions provides a unique opportunity to analyze illegal activities, such as phishing scams, from a network perspective. Most existing phishing scam detection methods focus primarily on analyzing account interaction networks, which limits their ability to uncover transaction behavior patterns embedded within transaction interactions. To address this, we construct the Transaction SubGraph Network (TSGN) by using transaction subgraphs as basic elements and further propose a novel framework for Ethereum phishing account detection. Specifically, we rebuild the graph structures via three well-designed mapping mechanisms, yielding TSGN and its two variants, i.e., Directed-TSGN and Temporal-TSGN, to obtain direction-aware and time-aware transfer flow features. By further incorporating the mapping strategy into transaction multidigraphs, we develop the Multiple-TSGN, which could preserve more transaction flow features while concurrently reducing the time consumption of modeling large-scale networks. TSGN models based on transaction subgraph interactions can capture complex higher-order dependencies, which lay beyond the reach of models that exclusively capture pairwise account interactions. As a general framework, our model can incorporate various feature extraction methods to improve the performance of phishing detection. Extensive experimental results on Ethereum datasets show that our method achieves superior performance in phishing detection, yielding 3.27%∼6.71% relative improvement over previous state-of-the-art. © 2004-2012 IEEE.

关键词： Phishing

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