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2009 Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2009

作者： Yang, Shuyuan Meng, Huixiao Wu, Ruixia Jiao, Licheng Key Laboratory of Intelligent Perception Image Understanding of Ministry of Education Institute of Intelligence Information Processing Xi'an 710071 China

ISBN: (纸本)9781424427314

Synthetic aperture radar (SAR) is an imaging system which provides high-resolution images of earth surface. Nowadays there is an ever-growing interest in the SAR data compression because of the huge resources which require for storage and transmission. In this paper, we address the problem of SAR image compression and apply the multiscale Bandelet with adaptive quadtree partition to solve it. Because Bandelet can provide an efficient representation of geometric structures existed in images, the Bandelet based method can capture abundant textures in SAR images. Moreover, the multiscale Bandelet with adaptive quadtree partition can approximate any piecewise Cα-regular functions when α is unknown, so Bandelet can represent the hierarchy textures of SAR images efficiently. Embedded Block Coding with Optimal Truncation (EBCOT) coding algorithm is employed in our proposed method. Experimental results show that our method outperforms JPEG2000 and the second generation Bandelet (2G-Bandelet) compression methods on SAR image encoding at low bit rates. ©2009 IEEE.

关键词： Synthetic aperture radar

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control design of 60kW PEMFC generation system for residential applications

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2013年第9期14卷 679-685页

作者： Ying-ying ZHANG Ying ZHANG Xi LI Guang-yi CAO Shandong Provincial Key Laboratory of Ocean Environment Monitoring Technology Institute of Oceanographic Instrumentation Shandong Academy of Sciences Control Science and Engineering Department Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Fuel Cell Institute Department of Automation Shanghai Jiao Tong University

This paper presented a control design methodology for a proton exchange membrane fuel cell (PEMFC) generation system for residential applications. The dynamic behavior of the generation system is complex in such applications. A comprehensive control design is very important for achieving a steady system operation and efficiency. The control strategy for a 60 kW generation system was proposed and tested based on the system dynamic model. A two-variable single neuron proportional-integral (PI) decoupling controller was developed for anode pressure and humidity by adjusting the hydrogen flow and water injection. A similar controller was developed for cathode pressure and humidity by adjusting the exhaust flow and water injection. The desired oxygen excess ratio was kept by a feedback controller based on the load current. An optimal seeking controller was used to trace the unique optimal power point. Two negative feedback controllers were used to provide AC power and a suitable voltage for residential loads by a power conditioning unit. control simulation tests showed that 60 kW PEMFC generation system responded well for computer-simulated step changes in the load power demand. This control methodology for a 60 kW PEMFC generation system would be a competitive solution for system level designs such as parameter design, performance analysis, and online optimization.

关键词： Proton exchange membrane fuel cell （PEMFC） Generation system control strategy decoupling control Optimalseeking control

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Applications of artificial intelligence to lipid nanoparticle delivery

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Particuology 2024年第7期90卷 88-97页

作者： Ye Yuan Yuqi Wu Jiabei Cheng Kaiyuan Yang Yilin Xia Hongguang Wu Xiaoyong Pan Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong UniversityKey Laboratory of System Control and Information ProcessingMinistry of Education of ChinaChina Songjiang Research Institute Songjiang District Central HospitalShanghai Jiao Tong University School of MedicineShanghaiChina

Lipid nanoparticles(LNPs)are nanocarriers composed of four lipid components and can be used for gene therapy,protein replacement,and vaccine ***,LNPs also face several challenges,such as toxicity,immune activation,and low delivery *** overcome these challenges,artificial intelligence can be used to optimize the design and formulation of LNPs,as well as to predict their properties and ***,antibody-targeted conjugation can be used to enhance the specificity and selectivity of LNPs by attaching an antibody that recognizes a specific antigen on the cell surface to LNPs.

关键词： Artificial intelligence Lipid nanoparticles Antibody Targeted conjugation

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Second-Order Consensus of Multi-agent Systems via Periodically Intermittent Pinning control

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Circuits, Systems, and Signal processing 2016年第7期35卷 2413-2431页

作者： Wang, Xiaoling Su, Housheng Wang, Xiaofan Liu, Bo Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China School of Automation Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan430074 China College of Science North China University of Technology Beijing100144 China

In this paper, we investigate the leader-following consensus of second-order multi-agent systems with nonlinear dynamics and time delay by employing periodically intermittent pinning control. All member agents and the virtual leader share the same nonlinear dynamics relating to the velocity and delayed velocity information. Based on Lyapunov stability theory, we obtain a novel criterion that is independent of the time delay and control width to guarantee the second-order consensus of multi-agent systems with time delay and periodically intermittent controllers. Numerical simulations are presented to illustrate the theoretical results. © 2015, Springer Science+Business Media New York.

关键词： Time delay

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Resilient Distributed Predefined Time Secondary control for Cyber-Physical Microgrids

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IET Renewable Power Generation 2025年第1期19卷

作者： Junfeng Tan Fan Zhang Yanlu Huang Shuai Zhao Hongyu Su China Southern Power Grid Digital Grid Research Institute Co. Ltd. China Southern Power Grid Artificial Intelligence Technology Co. Ltd. Guangzhou China School of Artificial Intelligence and Automation and Technology and also with the Key Laboratory of Image Processing and Intelligent Control Ministry of Education Huazhong University of Science and Technology Wuhan China

This paper proposed a resilient distributed predefined-time sliding mode control for islanded AC microgrids with external disturbances caused by noisy circumstances or cyber-attacks. By utilizing the predefined-time convergence theory, the voltage regulation and frequency restoration as well as active power sharing can be achieved within a predefined time, which is directly equal to an adjustable parameter. Furthermore, based on the integral sliding mode control approach, the proposed method can completely compensate the external disturbance. Different from some voltage control methods based on complex second-order consensus, a novel secondary controller is designed by adopting the virtual control technique, such that the voltage regulation can be achieved under a first-order consensus with a corresponding tracking controller. In addition, the direct Lyapunov method is utilized to prove the stability of islanded AC microgrids under the proposed controller, and the analysis of predefined-time convergence is also given. Finally, case studies on a microgrid test system with four distributed generator is built in the MATLAB/SimPowerSystems software environment are conducted to demonstrate the effectiveness and superior performance of the proposed control scheme.

关键词： distributed power generation Microgrids robust control

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Solving Nonlinear Equations Systems with a Two-Phase Root-Finder Based on Niching Differential Evolution 15th

Solving Nonlinear Equations Systems with a Two-Phase Root-Fi...

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15th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2020

作者： Duan, Lianlang Xu, Fei Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9789811613531

Solving nonlinear equation systems (NESs) is a challenging problems in numerical computation. Two goals should be considered for solving NESs. One is to locate as many roots as possible and the other is to improve the solving precision. In this work, in order to achieve these two goals, a two-phase niching differential evolution (TPNDE) is proposed. The innovation of TPNDE is mainly reflected in the following three aspects. First, a probabilistic mutation mechanism is designed to increase the diversity of the population. Second, a novel reinitialization procedure is proposed to detect converged individuals and explore more new regions that may contain global optima. Third, distribution adjustment local search (DALS) is proposed to deal with the isolated solution and enhance the convergence of the algorithm. To evaluate the performance of TPNDE, we test our TPNDE and 5 state-of-the-art algorithms on 20 NESs with diverse features. The experimental results show that the proposed TPNDE algorithm is better than the other methods. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Nonlinear equations

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Semisupervised Transfer Boosting (SS-TrBoosting)

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial intelligence 2024年第7期5卷 3431-3444页

作者： Deng, Lingfei Zhao, Changming Du, Zhenbang Xia, Kun Wu, Dongrui Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan 430074 China and also with Shenzhen Huazhong University of Science and Technology Research Institute Shenzhen 518063 China

Semisupervised domain adaptation (SSDA) aims at training a high-performance model for a target domain using few labeled target data, many unlabeled target data, and plenty of auxiliary data from a source domain. Previous works in SSDA mainly focused on learning transferable representations across domains. However, it is difficult to find a feature space where the source and target domains share the same conditional probability distribution. Additionally, there is no flexible and effective strategy extending existing unsupervised domain adaptation (UDA) approaches to SSDA settings. In order to solve the above two challenges, we propose a novel fine-tuning framework, semisupervised transfer boosting (SS-TrBoosting). Given a well-trained deep learning-based UDA or SSDA model, we use it as the initial model, generate additional base learners by boosting, and then use all of them as an ensemble. More specifically, half of the base learners are generated by supervised domain adaptation, and half by semisupervised learning. Furthermore, for more efficient data transmission and better data privacy protection, we propose a source data generation approach to extend SS-TrBoosting to semisupervised source-free domain adaptation (SS-SFDA). Extensive experiments showed that SS-TrBoosting can be applied to a variety of existing UDA, SSDA, and SFDA approaches to further improve their performance. © 2020 IEEE.

关键词： Supervised learning

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Emotion Prediction in Conversation Based on Relationship Extraction

Emotion Prediction in Conversation Based on Relationship Ext...

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2022 IEEE International Conference on Cyborg and Bionic Systems, CBS 2022

作者： Yingjian, Liu Xiaoping, Wang Shanglin, Lei Huazhong University of Science and Technology School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan430074 China

ISBN: (纸本)9781665490283

With the development of human-computer interaction systems, emotion recognition in conversation (ERC) has attracted increasing interest in recent years. Motivated by recent studies which have proven that generating emotional conversation responses can effectively improve the performance of the ERC model. However, accurate emotional response is complicated due to the limited number of dialogue samples. Therefore, we propose a simple and effective framework for emotion prediction in conversation based on relationship extraction (DiaRP), consisting of two curricula: (1) Dialogue Relationship Capture (DRC);and (2) Next Emotion Prediction (NEP). In DRC, we capture the current emotional self-dependence and interpersonal dependence according to the influence of self and others on the current moment emotion in the conversation. We integrate self-dependence and interpersonal dependence for NEP to predict their emotional state without current utterance. We also measure the similarity between recognized emotion distribution and predicted emotion distribution by the KL divergence. With the proposed model-agnostic DiaRP strategy, we observe a significant performance improvement over a wide range of existing ERC models and achieve new state-of-the-art results on three public ERC datasets. © 2023 IEEE.

关键词： Emotion Recognition

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A Physiological Signal Emotion Recognition Method Based on Domain Adaptation and Incremental Learning 1

A Physiological Signal Emotion Recognition Method Based on D...

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1st International Conference on Cyber-Energy Systems and Intelligent Energy, ICCSIE 2022

作者： Li, Junnan Wang, Xiaoping Huazhong University of Science and Technology The School of Artificial Intelligence and Automation The Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan430074 China

ISBN: (纸本)9781665452151

Temporal concept shift (TCS) is an unavoidable problem in physiological signal-based emotion recognition tasks, i.e., the data distribution of physiological signals is constantly changing over time, which gradually degrades the model accuracy. To this end, we propose a method based on a combination of domain adaptation and incremental learning to reduce the impact of temporal concept drift. In this paper, domain adaptation is used to reduce the distribution differences and incremental learning is used to prevent the learned knowledge from being forgotten. Finally, we validate the effectiveness of our approach on two real datasets. © 2023 IEEE.

关键词： Emotion Recognition

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Cortical Neural P Systems 15th

Cortical Neural P Systems

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15th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2020

作者： Fu, Zhongzheng Zhang, Luping Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9789811613531

P systems are distributed and parallel computing models inspired from living cells. In this work, a variant of spiking neural P systems, cortical neural P systems, are proposed in the frame work of P systems combining the topology structure of basic P system and information processing style in spiking neurons. The computational power of cortical neural P systems is investigated. It is proved that cortical neural P systems are equivalent to Turing machines as number generators. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Turing machines

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