检索结果-南通市图书馆

维普期刊数据库

A Multi-Condition Sequential Network Ensemble for Industrial Energy Storage Prediction Considering the Condition Switching Characteristics

在线全文

学校读者我要写书评

暂无评论

IEEE/CAA Journal of Automatica Sinica 2025年第2期12卷 369-380页

作者： Tianyu Wang Fan Zhou Yangjie Wu Jun Zhao Wei Wang IEEE the school of Control science and Engineering Dalian University of Technology the school of information science and Engineering Dalian Polytechnic University

As a crucial storage and buffering apparatus for balancing the production and consumption of byproduct gases in industrial processes, accurate prediction of gas tank levels is essential for optimizing energy system scheduling. Considering that the continuous switching of the pressure and valve status(mechanism knowledge) would bring about multiple working conditions of the equipment, a multi-condition time sequential network ensembled method is proposed. In order to especially consider the time dependence of different conditions, a centralwise condition sequential network is developed, where the network branches are specially designed based on the condition switching sequences. A branch combination transfer learning strategy is developed to tackle the sample imbalance problem of different condition data. Since the condition or status data are real-time information that cannot be recognized during the prediction process, a pre-trained and ensemble learning approach is further proposed to fuse the outputs of the multi-condition networks and realize a transient-state involved prediction. The performance of the proposed method is validated on practical energy data coming from a domestic steel plant, comparing with the state-of-the-art algorithms. The results show that the proposed method can maintain a high prediction accuracy under different condition switching cases, which would provide effective guidance for the optimal scheduling of the industrial energy systems.

关键词： Ensemble learning industrial energy prediction multi-working condition structural deep network transfer learning

Characterization of size-resolved aerosol hygroscopicity and liquid water content in Nanjing of the Yangtze River Delta

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Journal of Environmental sciences 2025年第5期151卷 26-41页

作者： Youling Jiang Yan Ma Jun Zheng Nan Ye Cheng Yuan school of Environmental science and Engineering Nanjing University of Information Science and TechnologyNanjing 210044China Collaborative Innovation Center of Atmospheric Environment and Equipment Technology Nanjing University of Information Science&TechnologyNanjing 210044China school of Emergency Management Nanjing University of Information Science&TechnologyNanjing 210044China

Aerosol hygroscopicity and liquid water content(ALWC)have important influences on the environmental and climate effect of *** this study,we measured the hygroscopic growth factors(GF)of particles with dry diameters of 40,80,150,and 200 nm during the wintertime in *** the GF-derived hygroscopicity parameter(κ_(gf))and ALWC increased with particle size,but displayed differing diurnal variations,withκ_(gf)peaking around the midday,while ALWC peaking in the early ***,ammonium and oxygenated organic aerosols(OOA)were found as the chemical components mostly strongly correlated with ALWC.A closure study suggests that during midday photo-oxidation and nighttime high ALWC periods,theκof organic aerosols(κ_(org))was underestimated when using previous ***,we re-constructed parameterizations forκ_(org)and the oxidation level of organics for these periods,which indicates a higher hygroscopicity of photochemically formed OOA than the aqueous OOA,yet both being much higher than the generally assumed OOA ***,in a typical high ALWC episode,concurrently increased ALWC,nitrate,OOA as well as aerosol surface area and mass concentrations were observed under elevated ambient *** strongly indicates a coupled effect that the hygroscopic secondary aerosols,in particular nitratewith strong hygroscopicity,led to large increase in ALWC,which in turn synergistically boosted nitrate and OOA formation by heterogeneous/aqueous *** interaction may represent an important mechanism contributing to enhanced formation of secondary aerosols and rapid growth of fine particulate matter under relatively high RH conditions.

关键词： Aerosol hygroscopicity Aerosol liquid water content Photo-oxidation Aqueous/heterogeneous reactions

IDSSCNN-XgBoost:Improved Dual-Stream Shallow Convolutional Neural Network Based on Extreme Gradient Boosting Algorithm for Micro Expression Recognition

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2025年第1期82卷 729-749页

作者： Adnan Ahmad Zhao Li Irfan Tariq Zhengran He school of information science and Engineering Southeast UniversityNanjing210016China

Micro-expressions(ME)recognition is a complex task that requires advanced techniques to extract informative features fromfacial *** deep neural networks(DNNs)with convolutional structures have been ***,unlike DNNs,shallow convolutional neural networks often outperform deeper models in mitigating overfitting,particularly with small ***,many of these methods rely on a single feature for recognition,resulting in an insufficient ability to extract highly effective *** address this limitation,in this paper,an Improved Dual-stream Shallow Convolutional Neural Network based on an Extreme Gradient Boosting Algorithm(IDSSCNN-XgBoost)is introduced for ME *** proposed method utilizes a dual-stream architecture where motion vectors(temporal features)are extracted using Optical Flow TV-L1 and amplify subtle changes(spatial features)via EulerianVideoMagnification(EVM).These features are processed by IDSSCNN,with an attention mechanism applied to refine the extracted effective *** outputs are then fused,concatenated,and classified using the XgBoost *** comprehensive approach significantly improves recognition accuracy by leveraging the strengths of both temporal and spatial information,supported by the robust classification power of *** proposed method is evaluated on three publicly available ME databases named Chinese Academy of sciences Micro-expression Database(CASMEII),Spontaneous Micro-Expression Database(SMICHS),and Spontaneous Actions and Micro-Movements(SAMM).Experimental results indicate that the proposed model can achieve outstanding results compared to recent *** accuracy results are 79.01%,69.22%,and 68.99%on CASMEII,SMIC-HS,and SAMM,and the F1-score are 75.47%,68.91%,and 63.84%,*** proposed method has the advantage of operational efficiency and less computational time.

关键词： ME recognition dual stream shallow convolutional neural network euler video magnification TV-L1 XgBoost

Experimental demonstration of 220-GHz terahertz signals wireless transmission over 4.6 km

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

science China(information sciences) 2025年第1期68卷 386-388页

作者： Yi WEI Jianjun YU Mingxu WANG Xiongwei YANG Qiutong ZHANG Jingwen TAN Bing ZHANG Ying WU Yang HAN Peng TIAN Wen ZHOU Kaihui WANG Feng ZHAO State Key Laboratory of ASIC and System Key Laboratory for Information Science of Electromagnetic Waves (MoE)School of Information Science and Technology Fudan University school of Electronic Engineering Xi'an University of Posts and Telecommunications

The advancement of terahertz (THz) communication technology drives the evolution of wireless communication systems,offering novel pathways and technical means for the development of future 6G communication *** wireless communication systems are often constrained by bandwidth limitations of electronic devices in high frequency ***,THz communication technology leverages the characteristics of electromagnetic waves to transcend these limitations,enabling communication athigher frequencies and wider bandwidths.

关键词：

同方期刊数据库

Privacy-preserving explainable AI: a survey

在线全文

学校读者我要写书评

暂无评论

science China(information sciences) 2025年第1期68卷 23-56页

作者： Thanh Tam NGUYEN Thanh Trung HUYNH Zhao REN Thanh Toan NGUYEN Phi Le NGUYEN Hongzhi YIN Quoc Viet Hung NGUYEN school of information and Communication Technology Griffith University school of Computer and Communication sciences Ecole Polytechnique Federale de Lausanne Faculty of Mathematics and Computer science University of Bremen Faculty of information Technology HUTECH University Department of Computer science Hanoi University of Science and Technology school of Electrical Engineering and Computer science The University of Queensland

As the adoption of explainable AI(XAI) continues to expand, the urgency to address its privacy implications intensifies. Despite a growing corpus of research in AI privacy and explainability, there is little attention on privacy-preserving model explanations. This article presents the first thorough survey about privacy attacks on model explanations and their countermeasures. Our contribution to this field comprises a thorough analysis of research papers with a connected taxonomy that facilitates the categorization of privacy attacks and countermeasures based on the targeted explanations. This work also includes an initial investigation into the causes of privacy leaks. Finally, we discuss unresolved issues and prospective research directions uncovered in our analysis. This survey aims to be a valuable resource for the research community and offers clear insights for those new to this domain. To support ongoing research, we have established an online resource repository, which will be continuously updated with new and relevant findings.

关键词： privacy-preserving explainable AI privacy attacks privacy defences PrivEx PPXAI

New results on finite-time stability and instability theorems for stochastic nonlinear time-varying systems

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

science China(information sciences) 2025年第2期68卷 186-199页

作者： Weihai ZHANG Liqiang YAO College of Electrical Engineering and Automation Shandong University of Science and Technology school of Mathematics and information science Yantai University

This paper studies finite-time stability and instability theorems in the probability sense for stochastic nonlinear timevarying systems. Firstly, a new sufficient condition is proposed to guarantee that the considered system has a global ***, we propose new finite-time stability and instability criteria that relax the constraints on LV(the infinitesimal operator of Lyapunov function V) by the uniformly asymptotically stable function. On the one hand, these obtained results make up for the shortcomings of the existing results. On the other hand, the new finite-time stability theorems can be viewed as natural extensions of the existing results and also allow LV to be indefinite(negative or positive) rather than just only allow LV < ***, some simulation examples verify the validity of the theoretical results.

关键词： stochastic nonlinear systems finite-time stability finite-timeinstability uniformly asymptotically stable function

Privacy Distributed Constrained Optimization Over Time-Varying Unbalanced Networks and Its Application in Federated Learning

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

IEEE/CAA Journal of Automatica Sinica 2025年第2期12卷 335-346页

作者： Mengli Wei Wenwu Yu Duxin Chen Mingyu Kang Guang Cheng the school of Cyber science and Engineering Southeast University IEEE the school of Mathematics Frontiers Science Center for Mobile Information Communication and Security Southeast University the Purple Mountain Laboratories the school of Mathematics Southeast University

This paper investigates a class of constrained distributed zeroth-order optimization(ZOO) problems over timevarying unbalanced graphs while ensuring privacy preservation among individual agents. Not taking into account recent progress and addressing these concerns separately, there remains a lack of solutions offering theoretical guarantees for both privacy protection and constrained ZOO over time-varying unbalanced *** hereby propose a novel algorithm, termed the differential privacy(DP) distributed push-sum based zeroth-order constrained optimization algorithm(DP-ZOCOA). Operating over time-varying unbalanced graphs, DP-ZOCOA obviates the need for supplemental suboptimization problem computations, thereby reducing overhead in comparison to distributed primary-dual methods. DP-ZOCOA is specifically tailored to tackle constrained ZOO problems over time-varying unbalanced graphs,offering a guarantee of convergence to the optimal solution while robustly preserving privacy. Moreover, we provide rigorous proofs of convergence and privacy for DP-ZOCOA, underscoring its efficacy in attaining optimal convergence without constraints. To enhance its applicability, we incorporate DP-ZOCOA into the federated learning framework and formulate a decentralized zeroth-order constrained federated learning algorithm(ZOCOA-FL) to address challenges stemming from the timevarying imbalance of communication topology. Finally, the performance and effectiveness of the proposed algorithms are thoroughly evaluated through simulations on distributed least squares(DLS) and decentralized federated learning(DFL) tasks.

关键词： Constrained distributed optimization decentralized federated learning (DFL) differential privacy (DP) time-varying unbalanced graphs zeroth-order gradient

A Correntropy-Based Echo State Network With Application to Time Series Prediction

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

IEEE/CAA Journal of Automatica Sinica 2025年第2期12卷 425-435页

作者： Xiufang Chen Zhenming Su Long Jin Shuai Li the school of information science and Engineering Lanzhou University IEEE the Hangzhou Institute for Advanced Study University of Chinese Academy of Science

As a category of recurrent neural networks, echo state networks(ESNs) have been the topic of in-depth investigations and extensive applications in a diverse array of fields, with spectacular triumphs achieved. Nevertheless, the traditional ESN and the majority of its variants are devised in the light of the second-order statistical information of data(e.g., variance and covariance), while more information is neglected. In the context of information theoretic learning, correntropy demonstrates the capacity to grab more information from data. Therefore, under the guidelines of the maximum correntropy criterion, this paper proposes a correntropy-based echo state network(CESN) in which the first-order and higher-order information of data is captured, promoting robustness to noise. Furthermore, an incremental learning algorithm for the CESN is presented, which has the expertise to update the CESN when new data arrives, eliminating the need to retrain the network from scratch. Finally, experiments on benchmark problems and comparisons with existing works are provided to verify the effectiveness and superiority of the proposed CESN.

关键词： Correntropy echo state network (ESN) noise time series prediction

Phase-matching enhanced quantum phase and amplitude estimation of a two-level system in a squeezed reservoir

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Chinese Physics B 2025年第1期34卷 257-263页

作者： Yan-Ling Li Cai-Hong Liao Xing Xiao school of information Engineering Jiangxi University of Science and TechnologyGanzhou 341000China College of Physics and Electronic information Gannan Normal UniversityGanzhou 341000China

Squeezed reservoir engineering is a powerful technique in quantum information that combines the features of squeezing and reservoir engineering to create and stabilize non-classical quantum states. In this paper, we focus on the previously neglected aspect of the impact of the squeezing phase on the precision of quantum phase and amplitude estimation based on a simple model of a two-level system(TLS) interacting with a squeezed reservoir. We derive the optimal squeezed phase-matching conditions for phase φ and amplitude θ parameters, which are crucial for enhancing the precision of quantum parameter estimation. The robustness of the squeezing-enhanced quantum Fisher information against departures from these conditions is examined, demonstrating that minor deviations from phase-matching can still result in remarkable precision of estimation. Additionally, we provide a geometric interpretation of the squeezed phase-matching conditions from the classical motion of a TLS on the Bloch sphere. Our research contributes to a deeper understanding of the operational requirements for employing squeezed reservoir engineering to advance quantum parameter estimation.

关键词： quantum parameter estimation squeezed reservoir phase-matching conditions quantum Fisher information

维普期刊数据库