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Asia-Pacific signal and Information processing Association Annual Summit and Conference (APSIPA)

作者： Zheng Cheng Ping Han Binbin Han Jiahui Sun Basic Experiment Center Civil Aviation University of China Tianjin China Tianjin Key Laboratory of Adcanced Signal and Image Processing Civil Aviation University of China Tianjin China

ISBN: (数字)9781728132488

ISBN: (纸本)9781728132495

This paper presents an improved fuzzy clustering approach for Polarimetric SAR image by incorporating neighborhood information. Firstly, polarimetric scattering characteristics of the terrain in PolSAR image are used to generate appropriate initial centers to avoid the issue that FCM is sensitive to random class centers. Then to further enhance the robustness to speckle noise, the conventional robust fuzzy C-mean clustering approach is improved. The work mainly exists in two aspects: (1) The revised Wishart distance is adopted as the data distance measure instead of Euclidean distance to assign a label to each pixel. (2) A weighted fuzzy membership is established by considering local spatial distance and class membership between the central pixel and its neighborhood simultaneously. Finally, the real polarimetric SAR data is utilized for the validation of the proposed unsupervised classification method. Experimental results demonstrate the superiority of the proposed method over the comparisons.

关键词： Scattering Robustness Entropy Synthetic aperture radar Speckle Euclidean distance Classification algorithms

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Design of three-dimensional gesture recognition and motion tracking human-computer intelligent interaction system based on PAJ7620

Design of three-dimensional gesture recognition and motion t...

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2021 International Conference on Information Technology and Intelligent Control, CITIC 2021

作者： Wang, Jian-Liang Wei, Ye Li, Yang Meng, Yuan Li, Ming-Yu Xu, Jiang-Yan Jiao, Wan-Ming Ban, Lan Liu, Jun-Pei Zhang, Hong-Feng Zhang, Wei Wang, Li-Na Luo, Fu-Chen Wang, Yu-Duo Tianjin College University of Science and Technology Beijing Tianjin China Civil Aviation University of China Tianjin Key Laboratory of Intelligent Signal and Image Processing Tianjin China Tianjin Normal University Tianjin Key Laboratory of Wireless Mobile Communication and Radio Energy Transmission Tianjin China Binhai College Nankai University Tianjin China Tianjin Tianshi College Tianjin China

With the increasing degree of informatization and intelligence in modern society, human-computer interaction technology has become one of the commonly used scientific and technological achievements. "Gesture" can be used as inputing image information, and make more intuitive and convenient for perception of user interface. To a certain extent, it can complete the intelligent interaction function between human and computer. The design is a human-computer intelligent interaction system for 3D gesture recognition and motion tracking based on gesture sensor PAJ7620. STM32 chip is used as the main control unit to recognize accurately, analyze and process different gestures collected by the gesture sensor, and control the OLED screen to display the gesture information. It can further drive the carrier to take corresponding actions and realize the intelligent human-computer interaction recognition of gestures. The experimental test results show that the recognition rate is lose to 100% when the distance is within 10cm. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Gesture recognition

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Geometric Algebra Based Kalman Filter Trajectory Prediction

Geometric Algebra Based Kalman Filter Trajectory Prediction

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Aerospace Engineering and Systems (ISAES), International Symposium on

作者： Taiyu Li Weidong Jiao Tianjin Key Laboratory of Intelligent Signal and Image Processing Civil Aviation University of China Tianjin China

ISBN: (数字)9798350350418

ISBN: (纸本)9798350350425

To improve the safety and efficiency of aviation operation, a Kalman filtered trajectory prediction algorithm based on geometric algebra is proposed in this space. Firstly, the Kalman filter equations for trajectory prediction in geometric algebraic space are given by taking position, velocity and acceleration as state variables and position, velocity and acceleration in a typical trajectory as observations. Secondly, the matrix operation in the geometric algebraic space is simplified to the matrix operation by establishing a composite geometric algebraic space. Then, the versor operator in the conformal geometric algebraic space is introduced into the Kalman filter, and the steps of geometric algebra-based Kalman filter trajectory prediction are given to improve the prediction rate and accuracy. The experimental results show that the proposed trajectory prediction algorithm has the highest accuracy and the operation efficiency is improved by 27.66 % compared with the Kalman filter algorithm in Euclidean space and the DBSCAN clustering algorithm.

关键词： Accuracy Algebra Clustering algorithms Filtering algorithms Predictive models Prediction algorithms Mathematical models Trajectory Safety Kalman filters

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Conformal Geometric Algebraic Description of Flight Collision Detection Algorithm Based on Cylinder Protection Zone

Conformal Geometric Algebraic Description of Flight Collisio...

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Aerospace Engineering and Systems (ISAES), International Symposium on

作者： Haobo Wu Weidong Jiao Tianjin Key Laboratory of Intelligent Signal and Image Processing Civil Aviation University of China Tianjin China

ISBN: (数字)9798350350418

ISBN: (纸本)9798350350425

In order to provide sufficient reaction time for air traffic controllers and pilots, a Flight Conflict Detection Algorithm (FCDA) based on Cylindrical Protection Zone (CPZ) in the Conformal Geometric Algebra (CGA) is proposed. Initially, the CGA description of the CPZ is represented by using the CGA forms of the central circle and central axis segments of the cylinder. Then based on the inner and outer product and geometric product operations of CGA, the positional relationship of the two CPZs is judged to determine whether a flight conflict occurs or not. Subsequently, we compared the performance of flight conflict detection methods based on rectangular protection zones, spherical protection zones, and cylindrical protection zones through experiments in CGA and Euclidean space, respectively, the experimental results show that in CGA, the proposed method has a faster speed than the flight conflict method based on cuboids, and is basically equivalent to the method based on spherical protection zones. Significantly, all CGA-based methodologies demonstrated superior speed over their Euclidean space counterparts. Considering the propensity of rectangular and spherical zones to elicit false alarms due to their expansive coverage of airspace, the CGA-CPZ-FCDA method emerges as the superior choice.

关键词： Algebra Computational efficiency Trajectory Complexity theory Logic Protection Spatial resolution Detection algorithms Collision avoidance Aerospace engineering

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Numerical Simulation of Wind Field Based on Topography of Lanzhou Zhongchuan Airport

Numerical Simulation of Wind Field Based on Topography of La...

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2018 International Conference on Modeling, Simulation and Analysis(ICMSA 2018)

作者： Xing-long XIONG Feng-tian XU Zi-bo ZHUANG Xing CHEN Civil Aviation Meteorological Technology Research Institute Tianjin Key Laboratory of Intelligent Signal and Image Processing Civil Aviation University of China

Lanzhou Zhongchuan Airport is one of the Northwest's largest aviation hubs,and it is greatly affected by the wind *** to the low-lying terrain of the airport and the terraced terrain,the wind field around the airport is closely related to its *** paper set up the digital elevation model of the terrain near the runway with an area of 6 KM*6 KM*2 KM,and wind field numerical simulation is solved by Fluent *** wind speed and pressure distribution characteristics of the simulated wind field are obtained by iterative *** the method of horizontal plane at mountain area,the local influence of topographic factors on the wind field is *** results show that when the wind flows through the surrounding mountain area,due to the ups and downs of the mountain,the wind speed has a big difference in different height layers,and it is easy to cause crosswind shear,which has an impact on the flight *** results have important reference value for the research and low-level wind shear forming factors of wind field caused by complex terrain,and it is of great significance to deeply understand the mechanism of wind shear.

关键词： Numerical simulation Complex terrain Wind shear Fluent

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A Fast and Accurate Cluster Center Initialization Algorithm for PolSAR Superpixel Segmentation

A Fast and Accurate Cluster Center Initialization Algorithm ...

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Asia-Pacific signal and Information processing Association Annual Summit and Conference (APSIPA)

作者： Binbin Han Ping Han Zheng Cheng Tianjin Key Laboratory of Advanced Signal and Image Processing Civil Aviation University of China Tianjin China Basic Experiment Center Civil Aviation University of China Tianjin China

ISBN: (数字)9781728132488

ISBN: (纸本)9781728132495

Locate iterative clustering (LIC) gets good performance in superpixel segmentation for PolSAR images. However, there are also two problems in its cluster center initialization. One is that there is a lot of computational redundancy in calculating edge map, which slows down the segmentation speed. The other is that the calculated edge is much wider than the real one, which makes the fine-tuning of center seeds in 3 × 3 window not suitable. To solve these problems, a fast and accurate cluster center initialization algorithm for PolSAR superpixel segmentation is proposed in this paper. For the first problem, integral graph is introduced to eliminate the redundancy. For the second problem, a more reasonable window size is selected to conduct fine-tuning. Experiments with measured AIRSAR data sets demonstrate the speed of the proposed edge map calculation method increases 28 times and the center seed is farther away from the edge than before. Furthermore, LIC gets better superpixel segmentation results with the new initialization algorithm.

关键词： image edge detection Redundancy Clustering algorithms Detectors image segmentation Microsoft Windows Iterative algorithms

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Robot localization method based on adaptive sensor resetting algorithm

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Tien Tzu Hsueh Pao/Acta Electronica Sinica 2007年第11期35卷 2166-2171页

作者： Gao, Qing-Ji Lei, Ya-Li Hu, Dan-Dan Yu, Yong-Sheng Robotics Research Institute Civil Aviation University of China Tianjin 300300 China Northwest Electric Power Design Institute Xi'an 710032 China Tianjin Key Laboratory for Advanced Signal and Image Processing Tianjin 300300 China

An adaptive Sensor Resetting Localization (ASRL) algorithm based on traditional Particle Filter is proposed for mobile robot. The belief of robot is represented by a set of weighted samples, new necessary samples are calculated according to effective samples and resampled based on sensor data, and then old samples are replaced with new samples during ASRL algorithm. This algorithm is used on autonomous mobile robot AMR-ITL equipped with encoder and color camera sensor successfully, experiment result shows that ASRL is a more robust and quickly convergence algorithm.

关键词： Mobile robots

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An Insight Into Neurodegeneration: Harnessing Functional MRI Connectivity in the Diagnosis of Mild Cognitive Impairment

An Insight Into Neurodegeneration: Harnessing Functional MRI...

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17th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2024

作者： Han, Shuning Sun, Zhe Zhao, Kanhao Duan, Feng Caiafa, Cesar F. Zhang, Yu Solé-Casals, Jordi Data and Signal Processing Research Group University of Vic-Central University of Catalonia Catalonia Vic08500 Spain Image Processing Research Group RIKEN Center for Advanced Photonics Riken Saitama Wako-Shi Japan Faculty of Health Data Science Juntendo University Chiba Urayasu Japan Department of Bioengineering Lehigh University BethlehemPA18015 United States Tianjin Key Laboratory of Brain Science and Intelligent Rehabilitation Nankai University Tianjin China Instituto Argentino de Radioastronomía-CCT La Plata CONICET/ CIC-PBA/ UNLP V. Elisa 1894 Argentina Department of Electrical and Computer Engineering Lehigh University BethlehemPA18015 United States Department of Psychiatry University of Cambridge CambridgeCB20SZ United Kingdom

Alzheimer’s disease is a progressive form of memory loss that worsens over time. Detecting it early, when memory issues are mild, is crucial for effective interventions. Recent advancements in computer technology, specifically Graph Convolutional Networks (GCNs), have proven to be powerful tools for analyzing Magnetic Resonance Imaging (MRI) data comprehensively. In this study, we developed a GCN framework for diagnosing mild cognitive impairment (MCI) by examining the functional connectivity (FC) derived from resting-state functional MRI (rfMRI) data. Our research systematically explored various types and processing methods of FC, evaluating their performance on the OASIS-3 dataset. The experimental results revealed several key findings. On the one hand, the proposed GCN exhibited significantly superior performance over both the baseline GCN and the Support Vector Machine (SVM) models, with statistically significant differences. It attained the highest average accuracy of 80.3% and a peak accuracy of 88.2%. On the other hand, the GCN frame work obtained using individual FCs showed overall slightly better performance than the one using global FCs. However, it is important to note that GCNs using global networks with appropriate connectivity can achieve comparable or even better performance than individual networks in certain cases. Finally, our results also indicate that the connectivity within specific brain regions, such as VIS, DMN, SMN, VAN, and FPC, may play a more significant role in GCN-based MRI classification for MCI diagnosis. These findings significantly contribute to the understanding of neurodegenerative disorders and offer valuable insights into the diverse ap plications of GCNs in brain analysis and disease detection. © 2024 by SCITEPRESS– Science and Technology Publications, Lda.

关键词： Neurodegenerative diseases

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