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SSRN 2023年

作者： Liu, Xuan Fang, Yue Gao, Hanyu State Key Laboratory for Turbulence and Complex System Department of Mechanics and Engineering Science College of Engineering Beijing Innovation Center for Engineering Science and Advanced Technology Peking University Beijing100871 China Department of Chemical and Biological Engineering Hong Kong University of Science and Technology Clear Water Bay Hong Kong

Natural fiber reinforced composites are emerging as a sustainable alternative to traditional materials in various industrial applications. However, their long-term performance under outdoor conditions is adversely affected by moisture absorption and interface failure. In this study, we design a SiO2 nano-interphase between the jute fibers (Jutes) and polypropylene (PP) to prevent the composites (Jute-SiO2/PP composites) against the interface aging under wet conditions. Combining molecular dynamic (MD) simulation, microstructure characterization and macroscopic water absorption test, we elaborate on the underlying mechanisms of water absorption for Jute-SiO2/PP composites at multi-scale levels. MD simulations reveal that the SiO2/PP interface and the Jute-SiO2 interface, with their strong interlocking of molecular chains and polar interaction, respectively, effectively protect the composites from water diffusion at molecular level. Moreover, SiO2 nano-interphase with the array structure provides superior shielding against water ingress into the composites at micro level. The cooperation of the strong molecular structure and the unique microstructure for Jute-SiO2/PP interphase results in enhanced water aging resistance and dimensional stability of the composites. The water uptake and the thickness swelling of Jute-SiO2/PP composites are reduced by 3.6% and 3.0%, respectively, compared to the control samples. Our study offers new insights into leveraging sustainable biomaterials in moisture-prone applications. © 2023, The Authors. All rights reserved.

关键词： Silica

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Effect of Sio2 Nano-Interphase on the Water Absorption Mechanism of Natural Fiber Reinforced Composites: A Multi-Scale Study

SSRN

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SSRN 2023年

作者： Liu, Xuan Fang, Yue Gao, Hanyu State Key Laboratory for Turbulence and Complex System Department of Mechanics and Engineering Science College of Engineering Beijing Innovation Center for Engineering Science and Advanced Technology Peking University Beijing100871 China Department of Chemical and Biological Engineering The Hong Kong University of Science and Technology Clear Water Bay Hong Kong

Natural fiber reinforced composites are emerging as a sustainable alternative to traditional materials in various industrial applications. However, their long-term performance under outdoor conditions is adversely affected by moisture absorption and interface failure. In this study, we design a SiO2 nano-interphase between the jute fibers (Jutes) and polypropylene (PP) to prevent the composites (Jute-SiO2/PP composites) against the interface failure caused by water absorption under wet conditions. Combining molecular dynamic (MD) simulation, microstructure characterization and macroscopic water absorption test, we elaborate on the underlying mechanisms of water absorption for Jute-SiO2/PP composites at multi-scale levels. MD simulations reveal that the SiO2/PP interface and the Jute-SiO2 interface, with their strong interlocking of molecular chains and polar interaction, respectively, effectively protect the composites from water diffusion at molecular level. Moreover, SiO2 nano-interphase with the array structure provides superior shielding against water ingress into the composites at micro level. The cooperation of the strong molecular structure and the unique microstructure for Jute-SiO2/PP interphase results in enhanced water resistance and dimensional stability of the composites. The water uptake and the thickness swelling of Jute-SiO2/PP composites are reduced by 3.6% and 3.0%, respectively. Our study offers new insights into leveraging sustainable biomaterials in moisture-prone applications. © 2023, The Authors. All rights reserved.

关键词： Silica

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Solving Ascent Trajectory Optimization Problems by Radua Pseudospectral Method

Solving Ascent Trajectory Optimization Problems by Radua Pse...

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Intelligent Robotics and systems (ISoIRS), International Symposium on

作者： Liaochao Deng Cheng Xu Weishuai You Beijing Institute of Mechanical and Electrical Engineering Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

Ascent trajectory optimization problem of air-breathing hypersonic vehicles is a highly nonlinear and nonconvex problems. Most of the early works focus on the traditional indirect method, which needs to derive the complete first-order necessary conditions of the trajectory optimization problem. The derivation process is too complicated and error-prone. Additionally, indirect method has a high demand on the initial guess, and it needs to give the initial guess of covariant variables without physical significance. In this paper, we solve the ascent trajectory optimization problem directly using Radau Pseudospectral Method (RPM). Firstly, the complex three-dimensional ascent trajectory optimization problem is established in detail. Conmmon inequality path constraints including those on dynamic pressure and aerodynamic bending moment are taken into account. The performance index is given as maximizing the final mass considering minimizing the fuel consumption. Subsequently, the ascent trajectory optimization problem is transformed into a nonlinear programming problem (NLP) by RPM. Finally, the ascent trajectory optimization for Generic Hypersonic Aerodynamic Model Example (GHAME) is solved by RPM and the optimal results demonstrate the rapidity, effectiveness and high precision of RPM. The comparison between optimal trajectories with and without path constraints shows that path constraints increase fuel consumption.

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Seamless Detection: Unifying Salient Object Detection and Camouflaged Object Detection

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arXiv 2024年

作者： Liu, Yi Li, Chengxin Dong, Xiaohui Li, Lei Zhang, Dingwen Xu, Shoukun Han, Jungong School of Computer Science and Artificial Intelligence Changzhou University Changzhou213159 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China School of Automation Northwestern Polytechnical University Xi’an710129 China Department of Automation Tsinghua University Beijing100084 China

Achieving joint learning of Salient Object Detection (SOD) and Camouflaged Object Detection (COD) is extremely challenging due to their distinct object characteristics, i.e., saliency and camouflage. The only preliminary research treats them as two contradictory tasks, training models on large-scale labeled data alternately for each task and assessing them independently. However, such task-specific mechanisms fail to meet real-world demands for addressing unknown tasks effectively. To address this issue, in this paper, we pioneer a task-agnostic framework to unify SOD and COD. To this end, inspired by the agreeable nature of binary segmentation for SOD and COD, we propose a Contrastive Distillation Paradigm (CDP) to distil the foreground from the background, facilitating the identification of salient and camouflaged objects amidst their surroundings. To probe into the contribution of our CDP, we design a simple yet effective contextual decoder involving the interval-layer and global context, which achieves an inference speed of 67 fps. Besides the supervised setting, our CDP can be seamlessly integrated into unsupervised settings, eliminating the reliance on extensive human annotations. Experiments on public SOD and COD datasets demonstrate the superiority of our proposed framework in both supervised and unsupervised settings, compared with existing state-of-the-art approaches. Code is available on https://***/liuyi1989/Seamless-Detection. Copyright © 2024, The Authors. All rights reserved.

关键词： Contrastive Learning

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Multi-agent Distributed Formation Control Based on Improved Artificial Potential Field and Neural Network for Connectivity Preservation

Multi-agent Distributed Formation Control Based on Improved ...

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2021 IEEE International Conference on Unmanned systems, ICUS 2021

作者： Chen, Bao Ma, Hongjun Kang, Haobo Liang, Xinkai College of Information Science and Engineering Northeastern University Shenyang China Shenyang Institute of Automation Chinese Academy of Science Shenyang China Beijing Electro-Mechanical Engineering Institute Science and Technology on Complex System Conroland InelligentAgent Cooperation Laboratory Beijing China

ISBN: (纸本)9780738146577

In this brief, the collision avoidance and connectivity-preserving problems of autonomous underwater vehicles (AUVs) are investigated. For the sake of achieving these two goals more effectively, a novel distributed formation control scheme combined with artificial potential function is designed. Considering the disturbances of control input nonlinearities and the model uncertainties, we design a sliding mode controller based on RBF neural network. Then by Lyapunov method, we verify the stability of control strategy. At last, we establish a multi-AUVs model and simulate the control scheme with MATLAB. The effectiveness of the control strategy is testified by the simulations. © 2021 IEEE.

关键词： Lyapunov methods

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Automated system for Accounting of Customers and Orders

Automated System for Accounting of Customers and Orders

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International Symposium on INFOTEH-JAHORINA (INFOTEH)

作者： Ksenia Degtyarevaa Vadim Tynchenko Tatyana Panfilova Svetlana Kukartseva Department of Information Economic System Reshetnev Siberian State University of Science and Technology Krasnoyarsk Russia Department of Technological Machines and Equipment of Oil and Gas Complex name of organization School of Petroleum and Natural Gas Engineering Siberian Federal University Krasnoyarsk Russia Department of Systems Analysis Operations Research Reshetnev Siberian State University of Science and Technology

This study presents the operating model of a computer repair centre, a specialised enterprise dedicated to the refurbishment of devices from various manufacturers. The centre offers a wide range of services, including both warranty and post-warranty repairs and troubleshooting assistance. Customers are responsible for bringing their computers to the service centre, where an acceptance certificate is drawn up indicating the nature of the fault, model, serial number and date of receipt of the device. Both parties - the client and the service provider - sign this document. If the computer is under warranty, a warranty card must be provided. The repair process starts with diagnostics to identify faults, after which the necessary work and components to be replaced, as well as the associated costs, are discussed with the client. The customer has the right to refuse any part of the proposed repair. Repairs are carried out by highly trained technicians only after obtaining the customer's consent. Upon completion of the work, the customer is notified that the repair is complete and a date is set for picking up the unit. Upon collection of the device, the customer pays for the agreed work supported by warranty support for the serviced product.

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Research on Simulation technology of Cooperative Guidance for Aircraft Formation

Research on Simulation Technology of Cooperative Guidance fo...

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Chinese Intelligent systems Conference, CISC 2020

作者： Tong, Jiahui Liu, Jin Li, Jing Zhan, Tianming Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China Beijing Electro-Mechanical Engineering Institute Beijing China TAIJI Computer Corporation Limited Beijing China

ISBN: (纸本)9789811584572

This paper analyzed the structure and characteristics of cooperative guidance system of aircraft formation, puts forward a multi-level simulation system architecture of centralized/distributed driving to solve the cooperative guidance for aircraft formation, realized the modeling of aircraft formation members and interaction by using multi-agent method, discussed the simulation methods of data link networking transmission and positioning, space-time registration of simulation system, and so on. The simulation is carried out based on a certain combat scenario, and the results show that the simulation system constructed in this paper can simulate the whole process of cooperative guidance of aircraft formation. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Computer architecture

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Robust Imagined Speech Production Using AI-Generated Content Network for Patients with Language Impairments

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IEEE Transactions on Consumer Electronics 2024年

作者： Xu, Xu Fu, Chong Dalian University of Technology School of Software Dalian116621 China Northeastern University School of Computer Science and Engineering Shenyang110004 China Northeastern University Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Shenyang110819 China Ministry of Education Engineering Research Center of Security Technology of Complex Network System Shenyang110004 China

Imagined speech production is critical for brain-computer interface systems. It is able to provide the communication ability for patients with language impairments. Nowadays, many studies have developed algorithms for this purpose. However, they often struggle with an issue that is the noise in physiological signals from various devices. This makes current methods have low robustness when performing speech generation. To this end, we propose a framework to robustly producing imagined speech for patients with language impairments. It is based on artificial intelligent-generated content (AIGC). In specific, this work develops a diffusion model to remove noise from brain signals, which are then converted and normalized into log-mel spectrograms. Next, the product feeds into a transformer-based model to extract local and global features. Finally, these enhanced features are inputted into full connected layers to generate the imagined speech. The effectiveness of our model is validated using the high-quality, i.e., single-word-production-Dutch-iBIDS dataset. It achieves Pearson correlation scores above 0.8 and standard deviations below 0.2 across different volunteers. Experimental results well demonstrate that our model is robust and has advantages over peer methods. © 2024 IEEE.

关键词： Deep learning

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Event Trigger Mechanism-Based Robust Control for Cyber-Physical systems under DoS Attack

Event Trigger Mechanism-Based Robust Control for Cyber-Physi...

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Chinese Automation Congress (CAC)

作者： Peng Tian Huiling Xu Jiajia Zhao Lewei Dong School of Mathematics and Statistics Nanjing University of Science and Technology Nanjing P-R-China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing P.R.China

In this paper, the event trigger mechanism-based robust control problem is investigated for cyber-physical systems under denial of service attacks and disturbances. The effects of DoS attacks are regarded as a type of data packet loss. An event trigger mechanism is introduced into the control scheme design to effectively compensate the packet loss data. The robust attenuation technology is composited into control scheme to reduce the impact of disterbances. Then, by modeling the cyber-physical systems under denial of service(DoS) attack as a class of bounded sequential switching system, and constructing the corresponding Lyapunov function, the stability of the system is verified and analyzed. Finally, simulation experiments are given to verify the correctness of the above theoretical results.

关键词： Robust control Automation Switching systems Packet loss Switches Cyber-physical systems Control systems

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Identity Re recognition technology Based on Improved Lightweight ConvNetx Model

Identity Re recognition Technology Based on Improved Lightwe...

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Chinese Control Conference (CCC)

作者： Peng Siting Li Lei Hongbo Zhu Ren Jun Song Zhichao Jiabing Yang The Beijing Electro-Mechanical Engineering Institute Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China Beihang University School of Electronics and Information Engineering Beijing China

In the engineering field, there is a requirement for re recognition, including the identity recognition of cooperative and non-cooperative targets, that is, different sensors shoot targets in the same scene, and the identity recognition of targets from two perspectives is required, also known as target accurate retrieval. This method is widely used in fields such as automatic driving and military strikes. In the actual application scenario, deploying the re-recognition algorithm on the embedded processor needs to ensure the real-time computing speed and accuracy, so the complexity of the deep learning algorithm must be reduced, and pruning and lightweight processing are required. In the engineering field, when the image acquired by the sensor is subject to natural interference such as cloud and fog weather or fire and smoke, the difficulty of re-recognition increases. This paper adopts the lightweight improvement of ConvNeXt network model, and fine-tuned it on the basis of its original feature extraction function, so that it can successfully migrate to infrared image classification and also complete the extraction of infrared image target detail distinguishing features, and at the same time introduce the alignment of similar targets in infrared cross-view recognition. In the original similarity calculation, the average value is directly obtained from the spatial dimension of the output feature layer, which is replaced by the weight of the position in each space for estimation. The feature information of the multi-view marine ship target is extracted from the multi-sensor marine image, and its similarity is calculated, so as to determine the identity, thus reducing the support conditions and reconnaissance costs, and improving the accurate detection and tracking ability under the diverse dynamic reconnaissance conditions.

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