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3D printed-electrospun PCL/hydroxyapatite/MWCNTs scaffolds for the repair of subchondral bone

Regenerative Biomaterials 2023年第1期10卷 294-305页

作者： Yanyan Cao Lei Sun Zixian Liu Zhizhong Shen Wendan Jia Peiyi Hou Shengbo Sang College of Information Science and Engineering Hebei North UniversityZhangjiakou 075000China Shanxi Key Laboratory of Micro Nano Sensors&Artificial Intelligence Perception College of Information and ComputerTaiyuan University of TechnologyTaiyuan 030024China Key Lab of Advanced Transducers and Intelligent Control System of the Ministry of Education Taiyuan University of TechnologyTaiyuan 030024China Shanxi Research Institute of 6D Artificial Intelligence Biomedical Science Taiyuan 030031China

Osteochondral defect caused by trauma or osteoarthritis exhibits a major challenge in clinical treatment with limited symptomatic effects at *** regeneration and remodeling of subchondral bone play a positive effect on cartilage regeneration and further promotes the repair of osteochondral *** use of the strengths of each preparation method,the combination of 3D printing and electrospinning is a promising method for designing and constructing multi-scale scaffolds that mimic the complexity and hierarchical structure of subchondral bone at the microscale and nanoscale,*** this study,the 3D printed-electrospun poly(ɛ-caprolactone)/nano-hydroxyapatites/multi-walled carbon nanotubes(PCL/nHA/MWCNTs)scaffolds were successfully constructed by the combination of electrospinning and layer-by-layer 3D *** resulting dual-scale scaffold consisted of a dense layer of disordered nanospun fibers and a porous microscale 3D scaffold layer to support and promote the ingrowth of subchondral ***,the biomimetic PCL/nHA/MWCNTs scaffolds enhanced cell seeding efficiency and allowed for higher cell-cell interactions that supported the adhesion,proliferation,activity,morphology and subsequently improved the osteogenic differentiation of bone marrow mesenchymal stem cells in ***,this study elucidates that the construction of 3D printed-electrospun PCL/nHA/MWCNTs scaffolds provides an alternative strategy for the regeneration of subchondral bone and lays a foundation for subsequent in vivo studies.

关键词： additive manufacturing 3D printing electrospinning subchondral bone

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Distilled one-shot federated learning for heterogeneous residential load forecasting 3

Distilled one-shot federated learning for heterogeneous resi...

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3rd International Conference on Electronic Information Engineering, Big Data, and Computer technology, EIBDCT 2024

作者： Guan, Chengcheng Xie, Zongchao Ding, Zhinan Xie, Xinlin Taiyuan University of Science and Technology Shanxi Key Laboratory of Advanced Control and Equipment Intelligence 66 Waliu RoadShanxi 030024 China Faculty of Science University of Melbourne Grattan Street ParkvilleVIC Australia

ISBN: (纸本)9781510680449

Load prediction is the foundation of power system operation and analysis. It also plays a decisive role in the safety, stability, and economic operation of the smart grid. Traditional load forecasting methods are too difficult to meet the needs of the modern smart grid. As technology evolves, federated learning (FL) offers a new solution for load forecasting. However, in the training of global model, FL multiple iterations are needed to converge, which largely depends on the repeated transmission of model parameter updates between client and server. When the global model structure is complicated or the local data heterogeneity of each client is serious, more iterations are needed to converge the model. Therefore, we designed a load prediction method based on distillated one-shot federated learning to solve these problems. The proposed method distills the training data through a dataset distillation algorithm and uses the distilled data instead of gradients for transmission, greatly reducing communication costs. In addition, we propose a double-weight self-checking mechanism to avoid each client updating the global model of the server on average and improve the accuracy of load forecasting. The results of the British example show that the prediction performance and privacy of distillated one-shot federated learning are better than those of FedAvg and FedDM. Particularly, our proposed method requires only 0.28 MB of communication consumption during the training process, which is much lower than the above two algorithms. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Smart power grids

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Rapid Autonomous Navigation of Geosynchronous Satellite Using Novel Infrared Earth Measurements

Rapid Autonomous Navigation of Geosynchronous Satellite Usin...

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Chinese control Conference (CCC)

作者： Xiaoxiang Liu Heng Shi Shuo Wang Chunling Wei Kai Xiong Beijing Institute of Control Engineering Beijing China Science and Technology on Space Intelligence Control Laboratory Beijing China

This paper presents a rapid autonomous navigation technology for Earth satellites using static infrared Earth sensor (SIES). Conventional Earth sensor has limitations in target and background segmentation, geocentric vector direction extraction, and interference rejection. A novel SIES sensor design is proposed that incorporates new technologies to increase light transmittance, reduce circuit noise, and improve image processing and attitude determination algorithms. This enables higher angular accuracy and new geocentric distance measurement information, resulting in significantly improved satellite attitude measurement accuracy of ±0. 01 °. The rapid autonomous navigation system framework for Geosynchronous (GEO) satellites using novel geocentric measurements by SIES is presented, including observability analysis, accuracy metrics acquisition, and autonomous navigation information fusion algorithms. This technology has been successfully verified on China's new generation of geosynchronous orbit satellite platform, as well as other Earth-centered orbit types.

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Cross-Modality Comprehensive Feature Aggregation Network for Road Scene Segmentation 8

Cross-Modality Comprehensive Feature Aggregation Network for...

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8th International Symposium on Computer science and Intelligent control, ISCSIC 2024

作者： Yang, Yale Zhang, Zihao Hou, Huifang Zhang, Wenwen Zhuang, Chunsheng Henan University of Technology College of Information Science and Engineering Zhengzhou China Henan University of Technology Key Laboratory of Grain Information Processing and Control Ministry of Education Henan Key Laboratory of Grain Photoelectric Detection and Control School of Artificial Intelligence and Big Data Zhengzhou China Data Henan University of Technology School of Artificial Intelligence and Big Zhengzhou China Henan Academy of Sciences Zhengzhou China

ISBN: (纸本)9798350380286

RGB-thermal semantic segmentation is a potential solution for reliable semantic scene understanding under adverse weather and complex lighting conditions. However, past studies have primarily focused on the design of fusion paradigms. Unfortunately, these methods have not fully considered the modality differences caused by different imaging mechanisms, thereby reducing the performance of pixel-level semantic analysis. In response to this issue, this paper proposes an innovative Cross-Modality Comprehensive Feature Aggregation Network (CFANet). This method first designs a Cross-Modality Feature Rectification Module (CFRM) to align modality differences;then, it constructs a Global-Local Fusion Module (GLF) to sharpen object edges and refine the segmentation map. Results on two urban scene understanding datasets demonstrate that CFANet can effectively aggregate multi-layer deep features and outperform existing advanced deep learning methods in scene understanding performance. © 2024 IEEE.

关键词： Semantic Segmentation

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A Mode-Suppression Circuit for the Ka-Band TE01Gyrotron Travelling Wave Tube: Design and Measurement 24

A Mode-Suppression Circuit for the Ka-Band TE01Gyrotron Trav...

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24th International Vacuum Electronics Conference, IVEC 2023

作者： Ma, Yuan Liu, Guo Cao, Yingjian Wang, Weijie Wang, Yu Jiang, Wei Yao, Yelei J., Wang Y., Luo University of Electronic Science and Technology of China Chengdu610054 China Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing100089 China

ISBN: (纸本)9781665473217

In this paper, the design and measurement of a mode-suppression circuit (MSC) applied in the nonlinear interaction region of a Ka-band gyrotron travelling wave tube (gyro-TWT) are presented. The proposed MSC is capable to suppress the spurious TE11 mode with no influence on the operating TE01 mode which helps to improve the tube stability for the high-power operation. Simulation result shows MSC can provide a loss of more than -5 dB around 23.1 GHz for the spurious TE11 mode which agrees well with the measured results. © 2023 IEEE.

关键词： Timing circuits

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RUL Prediction of Turbofan Engine Based on WGAN-Trans under Small Samples

RUL Prediction of Turbofan Engine Based on WGAN-Trans under ...

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2023 China Automation Congress, CAC 2023

作者： Qi, Chenman Mao, Zehui Liu, Wenjing College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing China Laboratory of Science and Technology on Space Intelligent Control Beijing China

ISBN: (纸本)9798350303759

The prediction of the remaining useful life of the turbofan engine of an aircraft is a very important part of its PHM. With the arrival of the era of Big data, data driven RUL prediction methods are gradually emerging, however, in the actual industry, it is often difficult to collect sufficient data to predict the RUL under deep learning which means there will be a problem of small samples. Moreover, in the early stage of degradation, it is difficult to accurately classify the health status of equipment, resulting in the inability to provide early warning before the rapid degradation of equipment performance, thus losing the significance of developing maintenance strategies in advance. To solve this problem, this paper proposes a WGAN-Trans model, which expands the data set by improving the Gener-ative adversarial network, uses the one-dimensional Convolutionl Neural Network to divide the health state, and finally uses the Transformer model to predict the RUL, which is verified on the commercial aircraft turbofan engine data set provided by NASA. The results show that the proposed model has good performance. © 2023 IEEE.

关键词： Turbofan engines

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Imbalanced Fault Diagnosis of Key Components in spacecraft ACS via Collaborative ResNet

Imbalanced Fault Diagnosis of Key Components in Spacecraft A...

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2023 China Automation Congress, CAC 2023

作者： Ma, Shujun Mao, Zehui Liang, Hanyu Li, Shuyu College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing China Laboratory of Science and Technology on Space Intelligent Control Beijing China

ISBN: (纸本)9798350303759

In this paper, a fault diagnosis method based on Collaborative Residual Network (Collaborative ResNet) is proposed to address the problem of imbalanced fault diagnosis for key components of spacecraft attitude control system (ACS). The designed Collaborative ResNet consists of two branches, the conventional learning branch and rebalancing learning branch, which conduct representation learning and classifier learning, respectively. A new Dynamic Complementary Loss (DC Loss) is introduced in the rebalancing learning to dynamically alleviate the excessive gradient of negative samples on the few sample classes and compensate for the gradient of misdiagnosed samples, which enhances the network sensitivity to the class with few number samples. Then the features extracted by two branches are adaptively integrated through the collaborative learning strategy to combine the strengths of both approaches. The effectiveness of the proposed method was validated on the imbalanced data collected on a ground semi-physical platform. © 2023 IEEE.

关键词： Failure analysis

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A novel guidance law based on proximal policy optimization 41

A novel guidance law based on proximal policy optimization

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第41届中国控制会议

作者： Yang Jiang Jianglong Yu Qingdong Li Zhang Ren Xiwang Dong Yongzhao Hua School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control LaboratoryBeihang University Institute of Artificial Intelligence Beihang University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In this paper,a new guidance law based on deep reinforcement learning is proposed for the high-speed maneuvering target attack ***,the missile-target kinematic model is established,and the action space and state space of reinforcement learning are ***,according to the missile strike process,the reward function suitable for this scenario is *** proximal policy optimization(PPO) based guidance law construction is ***,the strike effect in multiple sets of experiments verifies the effectiveness of the method proposed in this paper.

关键词： reinforcement learning proximal policy optimization high-speed maneuvering target

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The TAO of Blockchain intelligence for Intelligent Web 3.0

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IEEE/CAA Journal of Automatica Sinica 2023年第12期10卷 2183-2186页

作者： Juanjuan Li Fei-Yue Wang IEEE the State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China the State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China

WE are in an exciting new intelligent era where various Web 3.0 systems emerge and flourish.[1]–[3].In this new epoch,the collaboration of data and knowledge,humans and machines,actual and virtual worlds is undergoing an unprecedented diversification and community-driven transformation,unveiling an open future full of boundless ***,the value of dispersed data extends far beyond passive storage and application.

关键词： Web TAO knowledge

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A multi-source data fusion navigation method of spacecraft with limited GNSS signals

A multi-source data fusion navigation method of Spacecraft w...

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第十四届中国卫星导航年会

作者： Leyao Li Jiansong Chang Jianxin Guo Beijing Institute of Control Engineering Science and Technology on Space Intelligent Control Laboratory

Global Navigation Satellite system(GNSS) is initially designed to provide services to objects on the earth surfaces, or in the earth-orbits with altitude below 3000 km. However, previous researches show that GNSS receivers mounted on GEO satellites can receive GNSS signals and generate positioning and navigation results as well. Considering that in some harsh situations, such as bad observation geometry, weak signal acquisition, etc., the on-board GNSS receivers can only transfer pseudo-range data to GEO satellites, this paper proposed an autonomous navigation method in which the information from GNSS receiver, optical attitude sensors, and inter-satellite links are fused together: at first, the extended state equation and measurement equation of a GEO satellite with optical sensor's errors are deduced;then, an extended Kalman filter is designed to evaluate and compensate optical sensor's errors via constructed earthcentered vector bias;later, a sequential correction is carried out using intersatellite link measurements;finally, the performance of proposed method is analyzed through Monte-Carlo simulation. It shows that the average distance and velocity evaluation errors of proposed method are around 0.2 Km and 0.05 m/s individually;the performance can meet the requirements of survivability of a class of high-orbit, long-life and high-value satellites.

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