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18th Chinese Intelligent Systems Conference, CISC 2022

作者： Gao, Libin Hu, Zhongyi Li, Zuoyong Lu, Xingjin Li, Rui Tong, Yinsheng Lin, Dehou College of Computer Science and Aritificial Intelligence Wenzhou University Wenzhou325035 China Key Laboratory of Intelligent Image Processing and Analysis Wenzhou325035 China College of Computer and Control Engineering Minjiang University Fuzhou350108 China

ISBN: (纸本)9789811962028

In this study, a novel training method is innovatively proposed to address the problem of poor generalisation of trained models due to imbalance in Alzheimer’s disease (AD) data. The method alternates AD image data with dog and cat data from natural images for collaborative learning training across datasets, enhancing the generalisation ability of the models. At the same time, inspired by current work related to attention mechanisms under the field of computer vision, the model is reconstructed and an attention module is added to the model to further improve the accuracy of the model. The experimental results show that the method has good classification performance and provides new ideas for the diagnosis of other brain diseases. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Convolutional neural networks

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Wind disturbance compensated path-following control for fixed-wing UAVs in arbitrarily strong winds

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Chinese Journal of Aeronautics 2024年第2期37卷 431-445页

作者： Hao LU Lan GAO Yunda YAN Mingzhe HOU Chenliang WANG Hangzhou Innovation Institute Beihang UniversityHangzhou 310051China School of Information Science and Technology Hangzhou Normal UniversityHangzhou 311121China Department of Computer Science University College LondonLondon WC1E 6BTUnited Kingdom Center for Control Theory and Guidance Technology Harbin Institute of TechnologyHarbin 150001China School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China

Wind is the primary challenge for low-speed fixed-wing unmanned aerial vehicles to follow a predefined flight *** cope with various wind conditions,this paper proposes a wind disturbance compensated path following control strategy where the wind disturbance estimate is incorporated with the nominal guiding vector field to provide the desired airspeed direction for the *** the control input vector for the outer-loop kinematic subsystem needs to satisfy a magnitude constraint,a scaling mechanism is introduced to tune the proportions of the compensation and nominal ***,an optimization problem is formulated to pursue a maximum wind compensation in strong winds,which can be solved analytically to yield two scaling factors.A cascaded inner-loop tracking controller is also designed to fulfill the outer-loop wind disturbance compensated guiding vector ***-fidelity simulation results under sensor noises and realistic winds demonstrate that the proposed path following algorithm is less sensitive to sensor noises,achieves promising accuracy in normal winds,and mitigates the deviation from a desired path in wild winds.

关键词： Path following Guiding vector field Wind disturbance Disturbance rejection Fixed wings

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EEG-GNet: GCN-Based EEG Signal Fatigue Detection Network for Edge Devices

EEG-GNet: GCN-Based EEG Signal Fatigue Detection Network for...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Zhang, Fuquan Wu, Yu Xu, Xinxin Wang, Chuansheng Ma, Minjia Grau, Antoni Huang, Jiayan School of Computer and Big Data Minjiang University Fuzhou China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou China College of New Engineering Industry Putian University Putian China Department of Automatic Control Polytechnic University of Catalonia Barcelona Spain School of Robotics Xi'an Jiaotong-Liverpool University Suzhou China College of New Engineering Industry Putian University Fujian Ruituo Information Technology Limited Company Putian China

ISBN: (纸本)9798350386226

Fatigue driving is a common potential traffic safety hazard. To detect and analysis the driver Fatigue degree in real-time, more attention have been increasing paid to application research of EEG fatigue detection device. However, existing methods suffer from complex model structure or large-scale model parameters. In the other words, they requires high computational consumption and large memory footprint, which creates a contradiction between model and portable EEG machine with limited hardware resources. In this work, we take both time and frequency domains of EEG signal into account and design an lightweight and efficient driver fatigue detection network based on GCN (EEG-GNet), which is available edge-end device application. Experiments on 4th Raspberry Pi on a public baseline dataset show that our EEG-GNet outperforms the state-of-the-art methods and takes good tradeoff between detection accuracy and resource consumption. Our EEG-GNet provides a new potential opportunity for future applications in practical portable/wearable (P/W) devices. © 2024 IEEE.

关键词： Electrocardiography

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Proposed Intelligent Energy Management Systems for Hybrid Electric Traction System 30th

Proposed Intelligent Energy Management Systems for Hybrid El...

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Advances in Systems engineering - Proceedings of the 30th International Conference on Systems engineering, ICSEng 2023

作者： Gaber, Mohab Khamis, Ahmed Zydek, Dawid Egyptian Navy R&D Center Alexandria Egypt Guidance & Control Department Military Technical College Cairo Egypt Electrical and Computer Engineering Department University of Nevada Las Vegas United States

ISBN: (纸本)9783031405785

The global development of electrical power and generation systems has been accelerated by regulations to reduce greenhouse gas emissions and improve ecologically friendly energy sources. For the industry, designing and producing systems that meet these criteria is extremely challenging. The best option for electrification technologies is to rely on electricity to run all systems instead of burning fossil fuels. To cut greenhouse gas emissions, the diversification of renewable energy sources is adopted. These electrification strategies are supported by intelligent Energy Management Systems (EMSes). In this paper, hybrid electric traction system with a fuel cell serving as the primary power source is considered, while a battery bank serves as an auxiliary power source. The EMS between the hybrid system and the system load is challenging to implement. This paper proposes an EMS for hybrid electric power system based on Adaptive Neuro-Fuzzy Interface System (ANFIS) technology. The performance of ANFIS is simulated in the MATLAB Simulink. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Fuel cells

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

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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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Earthquake detection probabilities and completeness magnitude in the northern margin of the Ordos Block

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Applied Geophysics 2024年第4期21卷 777-793,881页

作者： Zhang Fan Yang Xiao-Zhong Cui Feng-Zhi College of Control and Computer Engineering North China Electric Power UniversityBeijing 102206China College of Mathematics and Physics North China Electric Power UniversityBeijing 102206China Inner Mongolia Autonomous Region Seismological Bureau Hohhot 010051China

The assessment of the completeness of earthquake catalogs is a prerequisite for studying the patterns of seismic *** traditional approaches,the minimum magnitude of completeness(MC)is employed to evaluate catalog completeness,with events below MC being discarded,leading to the underutilization of the *** probability is a more detailed measure of the catalog's completeness than MC;its use results in better model compatibility with data in seismic activity modeling and allows for more comprehensive utilization of seismic observation data across temporal,spatial,and magnitude *** the magnitude-rank method and Maximum Curvature(MAXC)methods,we analyzed temporal variations in earthquake catalog completeness,finding that MC stabilized after 2010,which closely coincides with improvements in monitoring capabilities and the densification of seismic *** the probability-based magnitude of completeness(PMC)and entire magnitude range(EMR)methods,grounded in distinct foundational assumptions and computational principles,we analyzed the 2010-2023 earthquake catalog for the northern margin of the Ordos Block,aiming to assess the detection probability of earthquakes and the completeness of the earthquake *** PMC method yielded the detection probability distribution for 76 stations in the distance-magnitude space.A scoring metric was designed based on station detection capabilities for small earthquakes in the near *** the detection probabilities of stations,we inferred detection probabilities of the network for diff erent magnitude ranges and mapped the spatial distribution of the probability-based completeness *** the EMR method,we employed a segmented model fitted to the observed data to determine the detection probability and completeness magnitude for every grid point in the study *** discussed the sample dependency and low-magnitude failure phenomena of the PMC method,noting the potential overestimatio

关键词： magnitude of completeness northern margin of the Ordos Block PMC method EMR method earthquake detection probability

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Gauss Gradient and SURF Features for Landmine Detection from GPR Images

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computers, Materials & Continua 2022年第6期71卷 4457-4486页

作者： Fatma M.El-Ghamry Walid El-Shafai Mahmouad I.Abdalla Ghada M.El-Banby Abeer D.Algarni Moawad I.Dessouky Adel S.Elfishawy Fathi E.Abd El-Samie Naglaa F.Soliman Department of Electronics and Communications Engineering Faculty of EngineeringZagazig UniversityZagazigSharqia44519Egypt Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenoufia32952Egypt Department of Industrial Electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia

Recently,ground-penetrating radar(GPR)has been extended as a well-known area to investigate the subsurface ***,its output has a low resolution,and it needs more processing for more *** paper presents two algorithms for landmine detection from GPR *** first algorithm depends on a multi-scale technique.A Gaussian kernel with a particular scale is convolved with the image,and after that,two gradients are estimated;horizontal and vertical ***,histogram and cumulative histogram are estimated for the overall gradient *** bin values on the cumulative histogram are used for discrimination between images with and without ***,a neural classifier is used to classify images with cumulative histograms as feature *** second algorithm is based on scale-space analysis with the number of speeded-up robust feature(SURF)points as the key parameter for *** addition,this paper presents a framework for size reduction of GPR images based on decimation for efficient *** further classification steps can be performed on images after *** sensitivity of classification accuracy to the interpolation process is studied in detail.

关键词： GPR images cumulative histogram gradient image neural classifier SURF

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Combined Effect of Concept Drift and Class Imbalance on Model Performance During Stream Classification

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computers, Materials & Continua 2023年第4期75卷 1827-1845页

作者： Abdul Sattar Palli Jafreezal Jaafar Manzoor Ahmed Hashmani Heitor Murilo Gomes Aeshah Alsughayyir Abdul Rehman Gilal Department of Computer and Information Sciences Universiti Teknologi PETRONAS(UTP)Seri Iskandar32610Malaysia Centre for Research in Data Science UTPPerak32610Malaysia High Performance Cloud Computing Centre(HPC3) UTPPerak32610Malaysia School of Engineering and Computer Science Victoria University of WellingtonWellington6012New Zealand AI Institute University of Waikato WellingtonHamilton3240New Zealand Anti-Narcotics Force Ministry of Narcotics ControlIslamabad46000Pakistan College of Computer Science and Engineering Taibah UniversityMadinah42353Saudi Arabia

Every application in a smart city environment like the smart grid,health monitoring, security, and surveillance generates non-stationary datastreams. Due to such nature, the statistical properties of data changes overtime, leading to class imbalance and concept drift issues. Both these issuescause model performance degradation. Most of the current work has beenfocused on developing an ensemble strategy by training a new classifier on thelatest data to resolve the issue. These techniques suffer while training the newclassifier if the data is imbalanced. Also, the class imbalance ratio may changegreatly from one input stream to another, making the problem more *** existing solutions proposed for addressing the combined issue of classimbalance and concept drift are lacking in understating of correlation of oneproblem with the other. This work studies the association between conceptdrift and class imbalance ratio and then demonstrates how changes in classimbalance ratio along with concept drift affect the classifier’s *** analyzed the effect of both the issues on minority and majority classesindividually. To do this, we conducted experiments on benchmark datasetsusing state-of-the-art classifiers especially designed for data stream ***, recall, F1 score, and geometric mean were used to measure theperformance. Our findings show that when both class imbalance and conceptdrift problems occur together the performance can decrease up to 15%. Ourresults also show that the increase in the imbalance ratio can cause a 10% to15% decrease in the precision scores of both minority and majority *** study findings may help in designing intelligent and adaptive solutionsthat can cope with the challenges of non-stationary data streams like conceptdrift and class imbalance.

关键词： Classification data streams class imbalance concept drift class imbalance ratio

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Invariant Set Analysis and control Synthesis of Multi-Equilibrium Switched Systems under control Constraints

Invariant Set Analysis and Control Synthesis of Multi-Equili...

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International Conference on Intelligent control and Information Processing (ICICIP)

作者： Yuejiang Han Lixian Zhang Yihang Ding Yifei Dong Ye Liang School of Astronautics Harbin Institute of Technology Harbin China College of Computer and Control Engineering Northeast Forestry University Harbin China

ISBN: (数字)9798331516147

ISBN: (纸本)9798331516154

This paper investigates the problems of invariant set analysis and control synthesis for multi-equilibrium switched systems under control constraints. A control strategy based on the invariant set method is proposed, accompanied by criteria formulated as linear matrix inequalities, ensuring that the state remains within the mode-dependent invariant sets. Furthermore, considering the control constraints in practical scenarios, a multi-equilibrium switched controller with control constraints (MESCC controller) is designed. Compared to existing works, the proposed method incorporates mode-dependent dwell time conditions and mode-dependent invariant sets, thereby offering enhanced design flexibility. An example of an aero-engine control system is presented to demonstrate the effectiveness and potential of the theoretical results.

关键词： Switched systems Robust control Switches Information processing control systems Linear matrix inequalities Closed loop systems Aircraft propulsion Intelligent control

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Wi-Wheat+:Contact-free wheat moisture sensing with commodity WiFi based on entropy

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Digital Communications and Networks 2023年第3期9卷 698-709页

作者： Weidong Yang Erbo Shen Xuyu Wang Shiwen Mao Yuehong Gong Pengming Hu College of Information Science and Engineering Henan University of TechnologyZhengzhou450001China Henan Key Laboratory of Grain Photoelectric Detection and Control Zhengzhou450001China College of International Education Kaifeng UniversityKaifengHenan475004China Knight Foundation School of Computing&Information Sciences Florida International UniversityMiamiFL33199USA Department of Electrical and Computer Engineering Auburn UniversityAuburnAL36849-5201USA

In this paper,we propose a contact-free wheat moisture monitoring system,termed Wi-Wheatþ,to address the several limitations of the existing grain moisture detection technologies,such as time-consuming process,expensive equipment,low accuracy,and difficulty in real-time *** proposed system is based on Commodity WiFi and is easy to *** WiFi CSI data,this paper proposes a feature extraction method based on multi-scale and multi-channel *** feasibility and stability of the system are validated through experiments in both Line-Of-Sight(LOS)and Non-Line-Of-Sight(NLOS)scenarios,where ten types of wheat moisture content are tested using multi-class Support Vector Machine(SVM).Compared with the Wi-Wheat system proposed in our prior work,Wi-Wheatþhas higher efficiency,requiring only a simple training process,and can sense more wheat moisture content levels.

关键词： Channel state information(CSI) WiFi Multi-scale entropy Multi-class support vector machine(SVM) Radio frequency(RF)sensing

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