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AFPN Based YOLOX for Rotation Object Detection in Remote Sensing Image

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AFPN Based YOLOX for Rotation Object Detection in Remote Sen...

Chinese automation Congress (CAC)

作者： Wen Zhou Xiaobo Liu Yiting Zheng Dongsen Zhang Hongbo Xiang School of Automation China University of Geosciences Wuhan China Hubei Key Lab of Advanced Control and Intelligent Automation China University of Geosciences Wuhan China Key Laboratory of Geological Survey and Evaluation of Ministry of Education China University of Geosciences Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

Rotation Object Detection in Remote Sensing Image is a big challenge, as it has different sizes and orientations. In this paper, we proposed an AFPN and YOLOX based Rotation Object Detection method, named AFPN-RYOLOX. In the AFPN-RYOLOX, an angle prediction branch added into the detection head of YOLOX and revised the loss function to incorporate Kullback-Leibler Divergence (KLD) loss firstly, which enhanced loss continuity and ensuring scale invariance. Then, the Asymptotic Feature Pyramid Network (AFPN) is integrated in the neck layer of YOLOX, which boosts the network's capability to extract features and decreases the number of model parameters through a dual-phase adaptive spatial fusion process. Through compare with other SOTA method, the proposed AFPN-RYOLOX achieved superior performances on DOTA and HRSC2016 datasets.

关键词： Adaptation models Head automation Noise Object detection Feature extraction Prediction algorithms Neck Sensors Remote sensing

A Generalized Probabilistic Monitoring Model with Both Randomand Sequential Data

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arXiv 2022年

作者： Yu, Wanke Wu, Min Huang, Biao Lu, Chengda The School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China The Department of Chemical and Materials Engineering University of Alberta EdmontonABT6G 2G6 Canada

Many multivariate statistical analysis methods and their corresponding probabilistic counterparts have been adopted to develop process monitoring models in recent decades. However, the insightful connections between them have rarely been studied. In this study, a generalized probabilistic monitoring model (GPMM) is developed with both random and sequential data. Since GPMM can be reduced to various probabilistic linear models under specific restrictions, it is adopted to analyze the connections between different monitoring methods. Using expectation maximization (EM) algorithm, the parameters of GPMM are estimated for both random and sequential cases. Based on the obtained model parameters, statistics are designed for monitoring different aspects of the process system. Besides, the distributions of these statistics are rigorously derived and proved, so that the control limits can be calculated accordingly. After that, contribution analysis methods are presented for identifying faulty variables once the process anomalies are detected. Finally, the equivalence between monitoring models based on classical multivariate methods and their corresponding probabilistic graphic models is further investigated. The conclusions of this study are verified using a numerical example and the Tennessee Eastman (TE) process. Experimental results illustrate that the proposed monitoring statistics are subject to their corresponding distributions, and they are equivalent to statistics in classical deterministic models under specific restrictions. Copyright © 2022, The Authors. All rights reserved.

关键词： Process monitoring

A Two-stage ARMAX Identification Approach Based on Bias-eliminated Least Squares and Parameter Relationship between MA Process and Its Inverse

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Acta Automatica Sinica 2012年第3期38卷 491-496页

作者： Bin XIN Jie CHEN School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing 100081 China Decision and Cognitive Sciences Research Centre Manchester Business School University of Manchester M15 6PB Manchester UK

In this paper, a two-stage approach is proposed for the parameter identification of autoregressive moving average with exogenous (ARMAX) variable model. The proposed approach identifies the autoregressive part with exogenous variable (ARX) by a bias-eliminated least squares method, and the moving average (MA) part by utilizing the parameter relationship between MA process and its inverse. Finally, the noise variance can be computed by using the identified MA parameters. Numerical simulations validate the effectiveness of the proposed approach.

关键词： Autoregressive moving average with exogenous (ARMAX) model parameter identification inverse model least-squares method bias compensation

An overview of sensing platform-technological aspects for vector magnetic measurement: A case study of the application in different scenarios

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arXiv 2020年

作者： Liu, Huan Dong, Haobin Ge, Jian Liu, Zheng School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China School of Engineering University of British Columbia Okanagan KelownaBCV1V 1V7 Canada

Magnetic sensing platform techniques have been used in many years in an attempt to better evaluate the likelihood of recoverable hydrocarbon reservoirs by determining the depth and pattern of sedimentary rock formations containing magnetic minerals, such as magnetite. Utilizing airplanes, large-area magnetic surveys have been conducted to estimate, for example, the depth of igneous rock and the thickness of sedimentary rock formations. In this case, the vector magnetic survey method can simultaneously obtain the modulus and direction information of the Earth's magnetic field, which can effectively reduce the multiplicity on data inversion, contribute to the quantitative interpretation of the magnetic body and obtain more precise information and characteristics of magnetic field resource, so as to improve the detection resolution and positioning accuracy of the underground target body. This paper presents a state-of-the-art review of the application situations, the technical features, and the development of the vector magnetic sensing platform-technical aspects for different application scenarios, i.e., ground, wells, marine, airborne, and satellites, respectively. The potential of multi-survey sensing platform technique fusion for magnetic field detection is also discussed. Copyright © 2020, The Authors. All rights reserved.

关键词： Geological surveys

DATA SMOOTHING FILLING METHOD BASED ON SCRNA-SEQ DATA ZERO-VALUE IDENTIFICATION

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arXiv 2024年

作者： Jiang, Linfeng Zhu, Yuan School of Automation China University of Geosciences Hongshan District No. 388 Lumo Road Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Hongshan District No. 388 Lumo Road Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Hongshan District No. 388 Lumo Road Wuhan430074 China

Single-cell RNA sequencing (scRNA-seq) determines RNA expression at single-cell resolution. It provides a powerful tool for studying immunity, regulation, and other life activities of cells. However, due to the limitations of the sequencing technique, the scRNA-seq data are represented with sparsity, which contains missing gene values, i.e., zero values, called dropout. Therefore, it is necessary to impute missing values before analyzing scRNA-seq data. However, existing imputation computation methods often only focus on the identification of technical zeros or imputing all zeros based on cell similarity. This study proposes a new method (SFAG) to reconstruct the gene expression relationship matrix by using graph regularization technology to preserve the high-dimensional manifold information of the data, and to mine the relationship between genes and cells in the data, and then uses a method of averaging the clustering results to fill in the identified technical zeros. Experimental results show that SFAG can help improve downstream analysis and reconstruct cell trajectory. © 2024, CC BY.

关键词： RNA

Semi-global Periodic Event-triggered Output Regulation for Nonlinear Multi-agent systems

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arXiv 2022年

作者： Zheng, Shiqi Shi, Peng Zhang, Huiyan the School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China the School of Electrical and Electronic Engineering The University of Adelaide AdelaideSA5005 Australia the College of Engineering and Science Victoria University MelbourneVIC8001 Australia the National Research Base of Intelligent Manufacturing Service Chongqing Technology and Business University Chongqing400067 China

This study focuses on periodic event-triggered (PET) cooperative output regulation problem for a class of nonlinear multi-agent systems. The key feature of PET mechanism is that event-triggered conditions are required to be monitored only periodically. This approach is beneficial for Zeno behavior exclusion and saving of battery energy of onboard sensors. At first, new PET distributed observers are proposed to estimate the leader information. We show that the estimation error converges to zero exponentially with a known convergence rate under asynchronous PET communication. Second, a novel PET output feedback controller is designed for the underlying strict feedback nonlinear multi-agent systems. Based on a state transformation technique and a local PET state observer, the cooperative semi-global output regulation problem can be solved by the proposed new control design technique. Simulation results of multiple Lorenz systems illustrate that the developed control scheme is effective. © 2022, CC BY.

关键词： Multi agent systems

Design of a Capsule Robot system for Gastric Hemorrhage Detection using Luminol 20

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Design of a Capsule Robot System for Gastric Hemorrhage Dete...

20th IEEE International Conference on Mechatronics and automation, ICMA 2023

作者： Mao, Yuchen Guo, Jian Guo, Shuxiang Fu, Qiang Tianjin University of Technology Tianjin Key Laboratory for Control Theory & Application Complicated Systems Intelligent Robot Laboratory School of Electrical Engineering and Automation Binshui Xidao Extension 391 Tianjin300384 China Shenzhen Institute of Advanced Biomedical Robot Co. Ltd No.12 Ganli Sixth Road Jihua Street Longgang District Shenzhen518100 China Key Laboratory of Convergence Medical Engineering System and Healthcare Technology The Ministry of Industry and Information Technology School of Life Science Beijing Institute of Technology No.5 Zhongguancun South Street Beijing100081 China

ISBN: (纸本)9798350320831

Gastric hemorrhage in upper gastrointestinal bleeding is an obvious indicator of deteriorating gastric disease. This paper proposes a capsule robot system for detecting bleeding in the stomach. The patient ingests a capsule robot containing luminol reagent, which detects bleeding in the stomach via chemiluminescence. The MCU receives the optical sensor signal, and the data is transmitted via radio frequency. The external lower computer receives and forwards the data to the upper computer for processing and display. The data is used to determine the presence and amount of stomach bleeding. Chemiluminescence is an excellent sensor, requiring no external energy supply, and demonstrating excellent sensitivity and selectivity. Combining chemical and electronic sensors presents opportunities for further development. Capsule robot detection reduces the discomfort and risk of secondary injury associated with traditional endoscopy. This paper establishes an experimental platform using porcine blood to simulate human blood, demonstrating the feasibility of the system. © 2023 IEEE.

关键词： Chemiluminescence

Stick-Slip Vibration Suppression Based on Multi-modal Analysis and Equivalent - Input-Disturbance Method

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Stick-Slip Vibration Suppression Based on Multi-modal Analys...

Asian control Conference

作者： Lingfeng Mu Hengyu Huang Haitao Song Zhejiaqi Ma Chengda Lu Min Wu School of Future Technology China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan China School of Automation China University of Geosciences Wuhan China CCTEG Xi 'an Research Institute (Group) Co. Ltd. Xi'an China

ISBN: (数字)9789887581598

ISBN: (纸本)9798331540845

This work investigates the active suppression of stick-slip vibration based on the multi-modal analysis and equivalent-input-disturbance (EID) method. By building a lumped parameter model with a high degree of freedom, the multi-modal properties of the vibration are examined. The multi-modal disturbance signals of the drilling string system are analyzed using the variational modal decomposition method. The EID method is used to design a vibration suppression controller. The parameters in the EID method are adjusted based on the primary modal frequencies to obtain the equivalent disturbance at the appropriate frequency. According to the simulation results, the proposed approach improves the effectiveness of active vibration suppression of the drill string, which is of some significance in guiding the drilling operation.

关键词： Vibrations Drilling Accuracy Perturbation methods Modal analysis Simulation Buildings

New stability criteria for linear systems with time-varying interval delay

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New stability criteria for linear systems with time-varying ...

UKACC International Conference on control (control)

作者： Jian Sun Jie Chen G.P. Liu School of Automation Key Laboratory of Complex Systems Intelligent Control and Decision Ministry of Education Beijing Institute of Technology Beijing China CTGT Center Harbin Institute of Technology Harbin China Faculty of Advanced Technology University of Glamorgan Pontypridd UK

This paper is concerned with the problem of stability of systems with time-varying delay in a given interval. A novel Lyapunov-Krasovskii functional is proposed to obtain new stability conditions. Some triple integral terms are introduced in the Lyapunov-Krasovskii functional and the information on the lower bound on the delay are sufficiently used. New delay-dependent stability criteria are derived using integral inequalities and formulated in terms of linear matrix inequality (LMI). Comparing numerical examples show that the proposed criteria yield a larger upper bound on the delay for a given lower bound on the delay than existing results.

关键词： Delay Stability criteria Time varying systems Linear matrix inequalities Numerical stability Linear systems