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2024 International Conference on Advances in Modern Age Technologies for Health and engineering Science, AMATHE 2024

作者： Gopu, G. Sathish, S. Shanmathan, T.S. Suthakar, G. Sivakumaran, N. Geetha Devasena, M.S. Sri Ramakrishna Engineering College Electronics And Communication Engineering Coimbatore India National Institute Of Technology Instrumentation And Control Engineering Tiruchirappalli India Sri Ramakrishna Engineering College Computer Science And Engineering Coimbatore India

ISBN: (纸本)9798350371567

This study investigates whether high-resolution brain-functional connectivity, which is measured by using Electroencephalography (EEG) combined with Hilbert Huang Transform (HHT) can be useful in Alzheimer Disease Diagnosis. The major issue with Alzheimer's disease (AD) is that it leads to cognitive decline and affects millions of people worldwide. Early prediction of the disease is mandatory and crucial for timely intervention and effective care. EEG signals, a non-invasive and cost-effective method to assess brain activity, have shown potential in predicting this disease. In this study, we propose an approach that utilizes EEG data combined with Hilbert-Huang Transform (HHT) and machine learning algorithms for classification which is a novelty of the study that enables early prediction of Alzheimer's disease. Our methodology was tested on a dataset comprising EEG signals recorded using 19 electrodes from both healthy individuals and patients with Alzheimer's and the Mild Cognitive Impairment (MCI). The results were promising, demonstrating high accuracy, sensitivity, and specificity. Machine learning techniques can be employed for categorizing EEG signals, but it essential to validate their effectiveness using large and diverse datasets. This research highlights the potential of HHT and EEG data in the prediction of this disease. Principal Component Analysis (PCA) is used for dimensional reduction of the dataset. Notably EEG signals combined with Hilbert Huang Transform and Principal Component Analysis gives better accuracy of 98.6% for KNN. This research highlights the potential of EEG analysis combined with advanced techniques for accurate classification of dementia-related disorders. © 2024 IEEE.

关键词： Empirical mode decomposition

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UAV 3D Trajectory Planning Based on Improved A* Algorithm and Differential Evolution

Journal of Network Intelligence

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Journal of Network Intelligence 2023年第4期8卷 1150-1163页

作者： Yang, Li Tan, Liang Zhang, Fuquan Department of information engineering Sichuan Vocational and Technical College of Communications Chengdu611130 China Thai-Chinese International College Assumption University of Thailand Bangkok100027 Thailand College of Computer and Control Engineering Minjiang University Fuzhou350108 China

Track planning technology, as a key technology for UAV mission planning, has always been a major research hotspot in the field of UAVs. In real-life applications, due to the complex and constrained UAV flight environment, how to establish an accurate environment model and how to select an efficient planning algorithm become the elements to solve the trajectory planning problem. In this work, after studying existing trajectory planning algorithms, a method using a combination of improved A* algorithm and differential evolution algorithm is proposed for 3D trajectory planning in complex environments. Firstly, the mathematical modelling of the UAV track planning related problems, including the UAV model, manoeuvrability constraints and equivalent digital maps, is carried out. Secondly, an improved sparse A* algorithm is proposed for solving the winding path problem of the sparse A* algorithm, which reduces the winding path of the trajectory by extracting path feature points and quadratic optimisation. Finally, the improved sparse A* algorithm is combined with the differential evolutionary algorithm and applied to the UAV real-time trajectory planning, where the improved sparse A* algorithm is used for the UAV global trajectory planning and the differential evolutionary algorithm is applied to the emergent threat avoidance, i.e. local trajectory planning. The results of MATLAB simulations show that the proposed method can solve the patharound problem of the sparse A* algorithm and can be flexible in complex environments to achieve dynamic trajectory planning, thus effectively guaranteeing the flight safety of UAVs in practical environments. © 2023, Taiwan Ubiquitous Information CO LTD. All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

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Rice Variety Classification Based on Optimized Near-Infrared Spectral Classification Model

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Rice science 2024年第1期31卷 6-9,I0009-I0012页

作者： YANG Sen WANG Zhenmin ZHANG Houqing SONG Wenlong College of Computer and Control Engineering Northeast Forestry UniversityHarbin 150040China The 49th Research Institute of China Electronics Technology Group Corporation Harbin 150000China

Accurate classification of rice variety is essential to ensure the brand value of high-quality rice *** the impact of sample state on modeling optimization algorithms,rice samples after grinding and sealing were *** enhance the accuracy of rice variety classification,we introduced a spectral characteristic wavelength selection method based on adaptive sliding window permutation entropy(ASW-PE).

关键词： sealing Infrared grinding

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Invariant Set Analysis and control Synthesis of Multi-Equilibrium Switched Systems under control Constraints 13

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

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13th International Conference on Intelligent control and Information Processing, ICICIP 2025

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

ISBN: (纸本)9798331516147

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. © 2025 IEEE.

关键词： control system synthesis

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Continuous and Discrete Similarity Coefficient for Identifying Essential Proteins Using Gene Expression Data

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Big Data Mining and Analytics 2023年第2期6卷 185-200页

作者： Jiancheng Zhong Zuohang Qu Ying Zhong Chao Tang Yi Pan College of Information Science and Engineering Hunan Normal UniversityChangsha 410081China Faculty of Computer Science and Control Engineering Shenzhen Institute of Advanced TechnologyChinese Academy of Sciences ShenzhenGuangzhou 518055China

Essential proteins play a vital role in biological processes,and the combination of gene expression profiles with Protein-Protein Interaction(PPI)networks can improve the identification of essential ***,gene expression data are prone to significant fluctuations due to noise interference in topological *** this work,we discretized gene expression data and used the discrete similarities of the gene expression spectrum to eliminate noise *** then proposed the Pearson Jaccard coefficient(PJC)that consisted of continuous and discrete similarities in the gene expression *** the graph theory as the basis,we fused the newly proposed similarity coefficient with the existing network topology prediction algorithm at each protein node to recognize essential *** strategy exhibited a high recognition rate and good *** validated the new similarity coefficient PJC on PPI datasets of Krogan,Gavin,and DIP of yeast species and evaluated the results by receiver operating characteristic analysis,jackknife analysis,top analysis,and accuracy *** with that of node-based network topology centrality and fusion biological information centrality methods,the new similarity coefficient PJC showed a significantly improved prediction performance for essential proteins in DC,IC,Eigenvector centrality,subgraph centrality,betweenness centrality,closeness centrality,NC,PeC,and *** also compared the PJC coefficient with other methods using the NF-PIN algorithm,which predicts proteins by constructing active PPI networks through dynamic gene *** experimental results proved that our newly proposed similarity coefficient PJC has superior advantages in predicting essential proteins.

关键词： Protein-Protein Interaction(PPI)network continuous and discrete similarity coefficient essential proteins

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A Novel Hybrid DC Circuit Breaker Topology with Current Limiting Capability and Rapid Fault Isolation Time 7

A Novel Hybrid DC Circuit Breaker Topology with Current Limi...

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7th IEEE International Electrical and Energy Conference, CIEEC 2024

作者： Yin, Laicheng Liu, Jiayi Wu, Yucheng Liu, Wei Zhaobo Liu, Yiqi College of Mechanical and Electrical Engineerding Northeast Forestry University Harbin China College of Computer and Control Engineering Northeast Forestry University Harbin China

ISBN: (纸本)9798350359558

When fault currents in Modular Multilevel Converter High Voltage Direct Current (MMC-HVDC) transmission systems rise too rapid, the DC circuit breakers (DCCBs) often have insufficient capacity. Therefore, this paper proposes a current-limited hybrid DC circuit breaker (CL-HCB) with fault current limiting and fast fault isolation of the dc grid to reduce the capacity requirement of the DCCB. The topology of the proposed CL-HCB discusses the operation process, metal-oxide arrester (MOA) properties, and parameter design. Besides, the energy dissipation circuit (EDC) is parallel to reduce the energy dissipation in MOA and decrease fault isolation time (FIT), which could reduce the thermal effects of the MOA and improve its reliability. Extensive simulation results verify the working principle and advantages of the proposed CL-HCB. Compared to conventional HCB under the same simulation parameters, the proposed CL-HCB has more advantages in limiting fault current and fault isolation. © 2024 IEEE.

关键词： Energy dissipation

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Analysis of the spatiotemporal trends and influencing factors of Hyphantria cunea in China

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Journal of Forestry Research 2024年第6期35卷 294-305页

作者： Hongwei Zhou Chaoqun Gong Xiaodong Li Yue Wang Yunbo Yan College of Computer and Control Engineering Northeast Forestry UniversityHarbin 150040People’s Republic of China Key Laboratory of National Forestry and Grassland Administration On Forest and Grassland Pest Monitoring and Warning Center for Biological Disaster Prevention and ControlNational Forestry and Grassland AdministrationShenyang 110034People’s Republic of China

In recent years,the situation of the Hyphantria cunea(Drury)(Lepidoptera:Erebidae),infestation in China has been serious and has a tendency to continue to spread.A comprehensive analysis was carried out to examine the spa-tial distribution trends and influencing factors of *** analysis involved integrating administrative division and boundary data,distribution data of ***,and envi-ronmental variables for *** and gravity analysis techniques were employed for data processing and *** results show that *** exhibited high aggregation patterns in 2021 and 2022 concentrated mainly in eastern *** these years,the focal point of the infestation was in Shandong Province with a spread towards the *** such as high vegetation density in eastern China provided favorable situations for growth and development of *** China,the spatial distribution of the moth is primarily influenced by two critical factors:precipitation during the driest month and *** play a pivotal role in determining the spread of the *** on these results,suggestions are provided for a mul-tifaceted approach to prevention and control of *** infestation.

关键词： Hyphantria cunea Temporal trends GeoDetector spatial analysis Spatial heterogeneity

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Object Helps U-Net Based Change Detectors

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IEEE/CAA Journal of Automatica Sinica 2024年第2期11卷 548-550页

作者： Lan Yan Qiang Li Kenli Li College of Computer Science and Electronic Engineering Hunan UniversityChangsha 410082China State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China

Dear Editor,This letter focuses on leveraging the object information in images to improve the performance of the U-Net based change *** detection is fundamental to many computer vision *** existing solutions based on ... 详细信息

关键词： Net computer networks

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Human-object interaction detection via interactive visual-semantic graph learning

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Science China(Information Sciences) 2022年第6期65卷 81-82页

作者： Tongtong WU Fuqing DUAN Liang CHANG Ke LU College of Artificial Intelligence Beijing Normal University School of Computer and Control Engineering University of Chinese Academy of Sciences

Dear editor,Human-object interaction(HOI) detection is an important human-centric visual understanding task with several applications in visual monitoring, intelligent robot, etc. It aims at localizing and inferring interaction relationships between humans and objects in images. As a result of their success in object detection, many object detectors can be used to localize human and object instances. Therefore, the key to HOI detection mainly lies in the second part, namely interaction recognition.

关键词： Human-object interaction Context modeling Graph Learning Interactive Graph Visual-Semantic Graph

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A dual adaptive unscented Kalman filter algorithm for SINS-based integrated navigation system

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Journal of Systems engineering and Electronics 2024年第3期35卷 732-740页

作者： LYU Xu MENG Ziyang LI Chunyu CAI Zhenyu HUANG Yi LI Xiaoyong YU Xingkai Department of Precision Instrument Tsinghua UniversityBeijing 100084China College of Mechanical and Power Engineering Three Gorges UniversityYichang 443002China Unit 91001 of the PLA Beijing 100161China School of Control and Computer Engineering North China Electric Power UniversityBeijing 100096China

In this study, the problem of measuring noise pollution distribution by the intertial-based integrated navigation system is effectively suppressed. Based on nonlinear inertial navigation error modeling, a nested dual Kalman filter framework structure is developed. It consists of unscented Kalman filter (UKF)master filter and Kalman filter slave filter. This method uses nonlinear UKF for integrated navigation state estimation. At the same time, the exact noise measurement covariance is estimated by the Kalman filter dependency filter. The algorithm based on dual adaptive UKF (Dual-AUKF) has high accuracy and robustness, especially in the case of measurement information interference. Finally, vehicle-mounted and ship-mounted integrated navigation tests are conducted. Compared with traditional UKF and the Sage-Husa adaptive UKF (SH-AUKF), this method has comparable filtering accuracy and better filtering stability. The effectiveness of the proposed algorithm is verified.

关键词： Kalman filter dual-adaptive integrated navigation unscented Kalman filter(UKF) robust

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