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14th International Conference on Bio-inspired Computing: Theories and Applications, BIC-TA 2019

作者： Wang, Zhiyu Hu, Yingxin Chen, Zhekun Liao, Sulin Huang, Yabing Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan730074 China School of Computer Science and Technology Huazhong University of Science and Technology Wuhan730074 China Department of Pathology Renmin Hospital of Wuhan University Wuhan430060 China

ISBN: (纸本)9789811534140

Significant improvements to the dynamic DNA nano science have emerged in recent years, primarily due to the elaborate design of toehold-mediated DNA strand displacement (TMSD). However, it remains an ongoing challenge to design huge-scaled TMSD based sophisticated dynamic DNA structures without base-pair mismatching or unwanted secondary structures, because the sequence design complexity of TMSD will dramatically increase as the scale increases. Here we report a new polymerase triggered strand displacement (PTSD) mechanism to realize DNA strand displacement with the potential of constructing complicated dynamic DNA nanostructures. By employing proper polymerase with strand displacement activity, the target strand in a duplex will be displaced and freed during the polymerization. In this manner, DNA strand displacement takes place without considering the design complexity of branch migration domain. The mechanism was successfully applied in constructing one-layer and two-layer circuits in which the parameters involved were explored, suggesting that PTSD is feasible and able to be harnessed to construct cascading DNA circuits with high complexity. © 2020, Springer Nature Singapore Pte Ltd.

关键词： DNA

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Scaling properties of scale-free networks in degree-thresholding renormalization flows

arXiv

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arXiv 2021年

作者： Chen, Dan Cai, Defu Su, Housheng The School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China The Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Huazhong University of Science and Technology Wuhan430074 China The State Grid Hubei Electric Power Research Institute Wuhan China

We study the statistical properties of observables of scale-free networks in the degree-thresholding renormalization (DTR) flows. For BA scale-free networks with different sizes, we find that their structural and dynamical observables have similar scaling behavior in the DTR flow. The finite-size scaling analysis confirms this view and reveals a scaling function with a single scaling exponent that collectively captures the changes of these observables. Furthermore, for the scale-free network with a single initial size, we use its DTR snapshots as the original networks in the DTR flows, then perform a similar finite-size scaling analysis. Interestingly, the initial network and its snapshots share the same scaling exponent as the BA synthetic network. Our findings have important guiding significance for analyzing the structure and dynamic behavior of large-scale networks. Such as, in large-scale simulation scenarios with high time complexity, the DTR snapshot could serve as a substitute or guide for the initial network and then quickly explore the scaling behavior of initial networks. © 2021, CC BY.

关键词： Scaling laws

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A novel TSK fuzzy system incorporating multiview collaborative transfer learning for personalized epileptic EEG detection

arXiv

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arXiv 2021年

作者： Li, Andong Deng, Zhaohong Lou, Qiongdan Choi, Kup-Sze Shen, Hongbin Wang, Shitong School of Artificial Intelligence and Computer Science Jiangnan University Jiangsu Key Laboratory of Digital Design and Software Technology Wuxi214122 China Centre for Smart Health Hong Kong Polytechnic University Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China

—In clinical practice, electroencephalography (EEG) plays an important role in the diagnosis of epilepsy. EEG-based computer-aided diagnosis of epilepsy can greatly improve the accuracy of epilepsy detection while reducing the workload of physicians. However, there are many challenges in practical applications for personalized epileptic EEG detection (i.e., training of detection model for a specific person), including the difficulty in extracting effective features from one single view, the undesirable but common scenario of lacking sufficient training data in practice, and the no guarantee of identically distributed training and test data. To solve these problems, we propose a TSK fuzzy system-based epilepsy detection algorithm that integrates multi-view collaborative transfer learning. To address the challenge due to the limitation of single-view features, multi-view learning ensures the diversity of features by extracting them from different views. The lack of training data for building a personalized detection model is tackled by leveraging the knowledge from the source domain (reference scene) to enhance the performance of the target domain (current scene of interest), where mismatch of data distributions between the two domains is resolved with adaption technique based on maximum mean discrepancy. Notably, the transfer learning and multi-view feature extraction are performed at the same time. Furthermore, the fuzzy rules of the TSK fuzzy system equip the model with strong fuzzy logic inference capability. Hence, the proposed method has the potential to detect epileptic EEG signals effectively, which is demonstrated with the positive results from a large number of experiments on the CHB-MIT dataset. © 2021, CC BY-NC-ND.

关键词： Electrophysiology

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Advancing Cross-Subject Domain Generalization in Brain–Computer Interfaces With Multiadversarial Strategies

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IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Liu, Yici Qin, Lang Chen, Xin Le Bouquin Jeannes, Regine Louis Coatrieux, Jean Shu, Huazhong Southeast University LIST Key Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications Jiangsu Provincial Joint International Research Laboratory of Medical Information Processing Ministry of Education Nanjing210096 China INSERM RennesF-3502 France The First Affiliated Hospital With Nanjing Medical University Department of Radiology Nanjing210029 China Laboratoire Traitement du Signal et de l’Image Universit de Rennes 1 Rennes35000 France Centre de Recherche en Information Biomedicale Sino-Francais Rennes35042 France National Institute for Health and Medical Research Rennes35000 France

A cross-subject domain generalization (DG) approach with multiadversarial strategies (DGMA) is introduced to reduce brain-computer interfaces (BCIs) systems' dependency on high-quality, subject-specific electroencephalographic (EEG) data, making it adaptable to unseen domains. DGMA leverages annotated training data from other subjects and consists of three modules: 1) prefeature extraction (PFE), enhancing EEG signal separability through preprocessing, data augmentation, and tangent space mapping;2) distribution feature updater (DFU), aligning intersubject feature distributions with marginal maximum mean discrepancy (MMD);and 3) multiadversarial training (MAT), initially using gradient reversal layer (GRL) to amplify domain differences and classification loss, allowing the model to learn diverse domain-specific features before minimizing these differences to balance domain transferability and discriminability. DGMA is capable of better capturing domain-specific features while achieving stronger generalization compared with traditional methods focused solely on minimizing domain differences. Validated on four motor imagery datasets, DGMA achieved state-of-the-art accuracies of 76.1% on BCI Competition IV 2a and 72.4% on the 002-2014 dataset. Additional tests on a private fatigue dataset and the SEED dataset yielded accuracies of 99.5% and 86.6%, respectively. © 1963-2012 IEEE.

关键词： Signal reconstruction

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Depth-Aware Multi-Modal Fusion for Generalized Zero-Shot Learning

Depth-Aware Multi-Modal Fusion for Generalized Zero-Shot Lea...

引用

IEEE International Conference on Industrial Informatics (INDIN)

作者： Weipeng Cao Xuyang Yao Zhiwu Xu Yinghui Pan Yixuan Sun Dachuan Li Bohua Qiu Muheng Wei Guangdong Laboratory of Artificial Intelligence and Digital Economy (Shenzhen) Shenzhen China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen China College of Computer Science and Software Engineering Shenzhen University Shenzhen China Stony Brook University New York United States Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology Shenzhen China Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China ZhenDui Industry Artificial Intelligence Co. Ltd Shenzhen China Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China

ISBN: (数字)9798331527471

ISBN: (纸本)9798331527488

Realizing Generalized Zero-Shot Learning (GZSL) based on large models is emerging as a prevailing trend. However, most existing methods merely regard large models as black boxes, solely leveraging the features output by the final layer while disregarding potential performance enhancements from other layers. Indeed, numerous researchers have visually depicted variations in the features learned across different layers of neural networks. Motivated by this observation, we propose a Vision Transformer (ViT)-based GZSL method named Depth-Aware Multi-Modal ViT (DAM2ViT), which exploits multi-level features of ViT. DAM2ViT incorporates a multi-modal interaction block to align semantic information of categories across multiple layers, thereby augmenting the model's capacity to learn associations between visual and semantic spaces. Extensive experiments conducted on three benchmark datasets (i.e., CUB, SUN, AWA2) have showcased that DAM2ViT achieves competitive results compared to state-of-the-art methods.

关键词： Visualization Adaptation models Semantics Zero shot learning Neural networks Termination of employment Transformers Market research Sun Optimization

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Research on Public Opinion Guidance Strategy based on Interaction Constraints

Research on Public Opinion Guidance Strategy based on Intera...

引用

IEEE Information Technology and Mechatronics Engineering Conference (ITOEC)

作者： Yuanyuan Xu Zhan Wu Xi Chen School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Image Processing and Intelligent Control Key Laboratory of the Education Ministry of China Wuhan China

ISBN: (数字)9781728143231

ISBN: (纸本)9781728143248

The dissemination of public opinion has a considerable impact on people's social lives, and the question of how both the government and the media can correctly guide public opinion and restore social stability is an issue that requires urgent attention. Combining the characteristics of public opinion dissemination in the network society leads to individual interaction. Considering the interaction between individual views and network topology, this paper combines the collaborative network model with the distance-constrained Hegselmann-Krause (HK) model to propose a consensus-guided strategy based on interaction constraints. It does this by changing the network topology and limiting the scope of individual interactions, thereby affecting the spread of public opinion. Based on the small-world network, the collaborative network model introduces the two parameters of Connection edge probability p and broken edge probability q, while also proposing a collaborative network model for Connection edge's breaking of the network based on the difference of individual opinion values. This paper designs simulation experiments by changing p, q, and the interaction distance, while also analyzing the results of public opinion's evolution from the perspectives of timeliness and the diversity of viewpoints. The experimental results show that when individuals are restricted from interacting with the surrounding environment and the scope of interaction between individuals is restricted, this will slow down the evolution of public opinion and increase the number of opinion clusters. By contrast, when it is encouraged, the interaction between individuals and the surrounding environment will make the entire system communicate more effectively within a short period of time, promoting the evolutionary benefits of public opinion considerably, shortening the convergence time of public opinion evolution to reach a steady state, and reducing the number of opinion clusters. The strategy is consist

关键词： Network topology Collaborative work Social network services Economics Government Bridges Media

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End-to-end 2D-3D Registration between image and LiDAR Point Cloud for Vehicle Localization

arXiv

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arXiv 2023年

作者： Wang, Guangming Zheng, Yu Guo, Yanfeng Liu, Zhe Zhu, Yixiang Burgard, Wolfram Wang, Hesheng Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China China Department of Artificial Intelligence Shanghai Jiao Tong University Shanghai200240 China Electrical and Computer Engineering University of California Los Angeles United States Institute of Artificial Intelligence Shanghai Jiao Tong University Shanghai200240 China Department of Electrical Engineering Shanghai Jiao Tong University Shanghai200240 China Department of Engineering University of Technology Nuremberg Germany

Robot localization using a previously built map is essential for a variety of tasks including highly accurate navigation and mobile manipulation. A popular approach to robot localization is based on image-to-point cloud registration, which combines illumination-invariant LiDAR-based mapping with economical image-based localization. However, the recent works for image-to-point cloud registration either divide the registration into separate modules or project the point cloud to the depth image to register the RGB and depth images. In this paper, we present I2PNet, a novel end-to-end 2D-3D registration network. I2PNet directly registers the raw 3D point cloud with the 2D RGB image using differential modules with a unique target. The 2D-3D cost volume module for differential 2D-3D association is proposed to bridge feature extraction and pose regression. 2D-3D cost volume module implicitly constructs the soft point-to-pixel correspondence on the intrinsic-independent normalized plane of the pinhole camera model. Moreover, we introduce an outlier mask prediction module to filter the outliers in the 2D-3D association before pose regression. Furthermore, we propose the coarse-to-fine 2D-3D registration architecture to increase localization accuracy. We conduct extensive localization experiments on the KITTI Odometry and nuScenes datasets. The results demonstrate that I2PNet outperforms the state-of-the-art by a large margin. In addition, I2PNet has a higher efficiency than the previous works and can perform the localization in real-time. Moreover, we extend the application of I2PNet to the camera-LiDAR online calibration and demonstrate that I2PNet outperforms recent approaches on the online calibration task. Copyright © 2023, The Authors. All rights reserved.

关键词： Calibration

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Fault detection of lithium-ion batteries subject to probabilistic parametric uncertainties 11

Fault detection of lithium-ion batteries subject to probabil...

引用

11th CAA Symposium on Fault Detection, Supervision, and Safety for Technical Processes, SAFEPROCESS 2019

作者： Liu, Yuhao Wan, Yiming Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan430074 China

ISBN: (纸本)9781728106816

The fault detection task in lithium-ion battery management system (BMS) is critical to the safety and reliability of rechargeable and hybrid electric vehicles. To explicitly account for inevitable errors of battery model parameters, a robust fault detection method is proposed in this paper. The residual generator is established by exploiting an equivalent circuit model. The effect of uncertainties on the residual is parametrized as polynomial dependence on probabilistic uncertain parameters and noises. Then Gaussian mixtures are adopted to derive the residual distribution. To account for residual uncertainties in the detection decision, the weighted sum of distances from the generated residual to each Gaussian component of the residual distribution is proposed. Simulation results illustrate that our proposed method outperforms the conventional approach that does not consider parametric uncertainties. © 2019 IEEE.

关键词： Fault detection

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Resilient Distributed Predefined Time Secondary control for Cyber-Physical Microgrids

引用

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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Modeling and Analysis of Pumping Cell of Nox Sensor - Part Ii: Nox Pumping Cell

SSRN

引用

SSRN 2022年

作者： Wang, Zhen Deng, Zhong-Hua Wang, Jie Lin, Wei-Xun Fu, Xiao-Wei Li, Xi School of Artificial Intelligence and Automation Key Laboratory of Imaging Processing and Intelligent Control Education Ministry Huazhong University of Science and Technology Hubei Wuhan430074 China Shenzhen Huazhong University of Science and Technology Research Institute Guangdong Shenzhen518055 China Lambda Company Jiangsu Changzhou213100 China College of Computer Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Hubei Wuhan430081 China

To improve the performance of the NOx sensor, a combined model based on the electrochemical model and the diffusion model is developed for the NOx pumping cell of the NOx sensor. Considering that a small amount of oxygen enters the third chamber and part of NO is decomposed in the second chamber, the electrochemical model simultaneously considers the reactions of NO and oxygen at cathode, and the diffusion model additionally considers the diffusion of oxygen and the decomposition of NO. To validate the model at different gas concentrations, the sensor is mounted on the designed test rig. Then, the simulation results are compared with experimental data from the test rig and good agreement is obtained. In addition, three key parameters of the model of the NOx pumping cell are analyzed. The values and changing trends of these three parameters are given in the paper. © 2022, The Authors. All rights reserved.

关键词： Diffusion

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