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7th Chinese Conference on Swarm Intelligence and Cooperative Control, CCSICC 2023

作者： Tang, Xiangyu Yu, Jianglong Dong, Xiwang Yang, Xiangyu Ren, Zhang School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Institute of Artificial Intelligence Beihang University Beijing100191 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9789819733279

This paper investigates practical distance-based formation stabilization and tracking issues for nonholonomic multi-agent systems (MASs). Firstly, the agent’s nonholonomic kinematics is represented as a left invariant system on a Lie group. Through the introduction of an auxiliary state and a virtual control guided by the transverse function method, the original system is effectively converted into a fully actuated one. Secondly, under the assumption of infinitesimal and minimal rigidity in the graph, a gradient-descent-based virtual controller is devised for the transformed MASs, facilitating practical rigid formation stabilization. Thirdly, a discontinuous distributed velocity estimator is designed for formation tracking. The nonholonomic MASs achieve the desired formation shape while effectively tracking the reference trajectory. Finally, the effectiveness of the proposed method is verified by numerical examples. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Multi agent systems

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An unsupervised deep learning framework for gene regulatory network inference from single-cell expression data

An unsupervised deep learning framework for gene regulatory ...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Mao, Guo Liu, Jie National University of Defense Technology Science and Technology on Parallel and Distributed Processing Laboratory Changsha410073 China National University of Defense Technology Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Laboratory of Software Engineering for Complex System Changsha410073 China

ISBN: (纸本)9798350337488

Recent advances in single-cell RNA sequencing (scRNA-seq) technology provides unprecedented opportunities for reconstruction gene regulation networks (GRNs). At present, many different models have been proposed to infer GRN from a large number of RNA-seq data, but most deep learning models use a priori gene regulatory network to infer potential GRNs. It is a challenge to reconstruct GRNs from scRNA-seq data due to the noise and sparsity introduced by the dropout effect. Here, we propose GAALink, a novel unsupervised deep learning method. It first constructs the gene similarity matrix and then refines it by threshold value. It then learns feature representations of genes through a graphical attention autoencoder that propagates information across genes with different weights. Finally, we use gene feature expression for matrix completion such that the GRNs are reconstructed. Compared with seven existing GRNs reconstruction methods, GAALink achieves more accurate performance on seven scRNA-seq dataset with four ground truth networks. GAALink can provide a useful tool for inferring GRNs for scRNA-seq expression data. © 2023 IEEE.

关键词： Feature representations Gene similarity matrix Graphical attention autoencoder Matrix completion Unsupervised deep learning method

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Nitrocellulose Thermodynamic Parameters Based on Calorimetric Testing 2nd

Nitrocellulose Thermodynamic Parameters Based on Calorimetri...

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2nd International Conference of Mechanical system Dynamics, ICMSD 2023

作者： Ding, Yangyang Rong, Bao Wang, Yan Fang, Yulong Institute of Launch Dynamics Nanjing University of Science and Technology Nanjing210000 China National Key Laboratory of Complex Multibody System Dynamics Nanjing University of Science and Technology Nanjing210000 China Luzhou North Chemical Industries Co. Ltd. Luzhou646600 China

ISBN: (纸本)9789819980475

Nitrocellulose (NC), a highly flammable and energetic cellulose derivative widely used in civilian and military applications;However, its flammable and explosive characteristics have become a major risk factor for many industrial accidents. Understanding the thermal properties of this material is fundamental to effective hazard control. Therefore, we studied the thermal stability parameters of nitrocellulose by thermogravimetric method, differential scanning calorimetry and differential calorimetry analysis method, and explored its stability by vacuum stability test. The activation energy of nitrocellulose was analyzed by Friedman, Kissinger-Akahira-Sunose, Ozawa-Flynn-Wall and Vyazovkin, and the thermal safety parameters such as the initial decomposition temperature and Onset point temperature of nitrocellulose were obtained. The research results can provide a reference for the rational production, storage, transportation and use of nitrocellulose. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Differential scanning calorimetry

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Multi-view and Multi-target Association Algorithm for Unmanned Aerial Vehicle Clusters Based on Siamese Network

Multi-view and Multi-target Association Algorithm for Unmann...

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International Conference on Guidance, Navigation and Control, ICGNC 2022

作者： Zhang, Hang Song, Chuang Zheng, JiangBin Hao, MingRui School of Software Northwestern Polytechnical University Shaanxi Xi’an710072 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9789811966125

The multi-target association algorithm of unmanned aerial vehicles (UAV) clusters in unknown environments is used to solve the problem of multiple UAVs, which can correctly determine whether the data from different perspectives contain the same target and eliminate redundant targets. This problem is different from that of multi-target tracking under the same perspective. However, the inherent relationship and differences of data from various perspectives of UAV clusters contribute to the problem of inaccurate target positioning information caused by low-cost detectors and inertial measurement units of UAVs and the constraints of limited communication capability between UAV clusters. Thus, using multi-perspective data is the key to improving the accuracy of multi-perspective situational awareness. This paper proposes a multi-view and multi-target association algorithm for UAV clusters based on the Siamese network. This algorithm can realise the problem of multi-view and multi-target identity judgement with high accuracy, achieve the requirements of high accuracy and high generalisation performance with the depth model based on convolution neural networks, extract the depth features from the optical image and map the original data to the depth feature space. Thus, the same target is matched by comparing the distance measurement of multi-view data in the feature space. The algorithm is verified by an aircraft cluster flight test, which proves the feasibility and accuracy of the algorithm. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Unmanned aerial vehicles (UAV)

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FPGA-Based Hardware Modeling on Pigeon-Inspired Optimization Algorithm 21st

FPGA-Based Hardware Modeling on Pigeon-Inspired Optimization...

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21st Asia Simulation Conference, AsiaSim 2022

作者： Zhao, Yu Zhao, Chun Liu, Yue Beijing Information Science and Technology University School of Computer Science Institution of Smart Manufacturing & Complex System BISTU Beijing100101 China

ISBN: (纸本)9789811991974

By learning behavioral characteristics and biological phenomena in nature, such as birds, ants, and fireflies, intelligent optimization algorithms (IOA) is proposed. IOA shows feasibility in solving complex optimization problems in reality. Pigeon-inspired optimization (PIO) algorithm, which belongs to intelligent optimization algorithms, is proposed by the pigeons homing navigation behavior inspired. PIO is superior to other algorithms in dealing with many optimization problems. However, the performance of PIO processing large-scale complex optimization problems is poor and the execution time is long. Population-based optimization algorithms (such as PIO) can be optimized by parallel processing, which enables PIO to be implemented in hardware for improving execution times. This paper proposes a hardware modeling method of PIO based on FPGA. The method focuses on the parallelism of multi-individuals and multi-dimensions in pigeon population. For further acceleration, this work uses parallel bubble sort algorithm and multiply-and-accumulator (MAC) pipeline design. The simulation result shows that the implementation of PIO based on FPGA can effectively improve the computing capability of PIO and deal with complex practical problems. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Field programmable gate arrays (FPGA)

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The Synthetic Aperture Radar-based Image Augmentation Using Generative Adversarial Network 23

The Synthetic Aperture Radar-based Image Augmentation Using ...

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Proceedings of the 2023 8th International Conference on systems, Control and Communications

作者： Kai Zhao Wei Xiong Xiaolan Yu Space Engineering University Science and Technology on Complex Electronic System Simulation Laboratory China

ISBN: (纸本)9798400707810

Synthetic aperture radars (SARs), characterized by their excellent performance, have found wide use in military applications. SAR-based image recognition is an important research area. Neural networks (NNs) have been widely used for image recognition and have demonstrated high recognition accuracy. However, NNs require a significant amount of data for training. In situations with limited training data, it is difficult to obtain satisfactory recognition accuracy using NNs. One approach toward alleviating the problems associated with small training sets is data augmentation. Here, we propose a novel SAR-based image augmentation method: using CycleGAN, aerial images are transformed into SARformat images, thereby allowing expansion of the SAR dataset. To improve the quality of these transformed images, we designed two filters: 1) a pre-filter for selecting images that are suitable for the transformation and 2) a post-filter for selecting suitable images after the transformation; this allows approximating the transformed images as real SAR images. We validated our method on the SSDD dataset. Our experimental results show that compared with the traditional data augmentation method, our method exhibits better recognition performance. With only 300 transformed images, the mean average precision improved from 66% to 76%, using only a small fraction of the SSDD dataset, thus overcoming the problem of small-sized training sets.

关键词： Cycle GAN Image augmentation Synthetic aperture radars

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A Stable and Symmetric FDTD Subgridding Method with Arbitrary Grid Ratio

A Stable and Symmetric FDTD Subgridding Method with Arbitrar...

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2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio science Meeting, AP-S/URSI 2023

作者： Deng, Langran Gong, Ningbo Diao, Guijie Yang, Shunchuan Research Institute for Frontier Science Beihang University Beijing China Beijing Electro-mechanical Engineering Institute Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory China

ISBN: (纸本)9781665442282

A stable and symmetric finite-difference time-domain (FDTD) subgridding method is proposed to effectively and accurately solve the three-dimensional electromagnetic prob-lems. The linear interpolation coefficient (LIC) and the length cutoff coefficient (LCC) are carefully designed to guarantee the stability of the proposed method. In addition, the proposed method is applicable to arbitrary grid ratios and nested meshes. A practical multiscale example is used to validate its accuracy and efficiency. © 2023 IEEE.

关键词： Finite difference time domain method

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A Service Mining Scheme Based on Semantic for Internet of Things

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Chinese Journal of Electronics 2025年第2期23卷 236-242页

作者： Xinming Li Yan Sun The Science and Technology on Complex Electronic System Simulation Laboratory Academy of Equipment Beijing China The School of Computer Science Beijing University of Posts and Telecommunication Beijing China

As the development of Internet of things (IOT), massive sensors have been deployed as the public infrastructure. With the development of in-depth applications in IOT, service discovery and composition are challenges to the end users. To handle this challenge, we develop a service mining scheme based on semantic for IOT to provide users with interesting composite services. In this scheme, services can be combined and recommended to users actively according to the calculation of service similarity and an updatable semantic database. By the results of service similarity, useless compositions can be filtered out so that energy consumption on service flooding will be reduced. The update strategy of semantic database is also given out, by which the composite services can keep up with time and be more applicative. The benefits of the proposed method are that all operations such as calculating, filtering, and updating are simple enough to be performed in sensor networks.

关键词： Smart buildings Databases Filtering Semantics Public infrastructure Ontologies Sensor systems Internet of Things Floods Intelligent sensors

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A Provably Stable SBP-SAT FDTD Subgridding Method without Modifying Yee's Grids

A Provably Stable SBP-SAT FDTD Subgridding Method without Mo...

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2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio science Meeting, AP-S/URSI 2023

作者： Wang, Yuhui Diao, Guijie Ni, Hong Yang, Shunchuan Research Institute for Frontier Science Beihang University Beijing China Beijing Electro-mechanical Engineering Institute Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory China

ISBN: (纸本)9781665442282

A stable finite-difference time-domain (FDTD) sub-grid ding method using the summation-by-parts simultaneous approximation term (SBP-SAT) technique is proposed. To meet the SBP properties and keep Yee's grids unchanged, the projection operators are carefully designed to extrapolate fields on the boundaries. Then, the SATs are used to weakly enforce the boundary conditions between multiple mesh blocks with different mesh sizes. Therefore, its long-term stability is theoretically guaranteed. An iris filter is simulated to validate the effectiveness of the proposed method. Results show that the proposed SBP-SAT FDTD subgridding method is stable, accurate and efficient. © 2023 IEEE.

关键词： Finite difference time domain method

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Adaptive SOM neural network algorithm 3

Adaptive SOM neural network algorithm

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3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing, AIAHPC 2023

作者： Wang, Xin Yan, Taishan School of Information Science and Engineering Hunan Institute of Science and Technology Hunan Yueyang China Hunan Institute of Science and Technology School of Information Science and Engineering China Key Laboratory of Hunan Province on Intelligent Control and Optimization of Complex Industrial Logistics System Hunan Yueyang China

ISBN: (数字)9781510666580

ISBN: (纸本)9781510666573

In order to improve the performance of traditional SOM model, an adaptive SOM neural network algorithm is proposed. By introducing the error square sum solution formula, the clustering error of the model sub-data set is calculated by using the method of cutting the data set, and the change trend of the clustering error is quickly obtained. Then the learning rate of the SOM network is adaptively adjusted according to this, and the convergence speed is accelerated on the basis of ensuring that the network is fully trained, thereby improving the performance of the SOM network. © 2023 SPIE.

关键词： Errors

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