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

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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Exploration on teaching reform of "signal and System" Course based on "student-Centered" 2021

Exploration on teaching reform of "signal and System" Course...

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2nd International Conference on Computers, information Processing and Advanced Education, CIPAE 2021

作者： Wang, Sainan Meng, Xianjiao Liu, Tao Zuo, Zhenyu Li, Zhiqi Department of Information and Control Engineering Shenyang Institute of Science and Technology Liaoning China

ISBN: (纸本)9781450389969

This paper explores the teaching reform of signals and systems under the concept of "student-centered". Starting from the cultivation of students' practical ability and self-learning consciousness, this paper analyzes the characteristics of signal and system course and the main problems existing in the teaching process, and puts forward a series of feasible reform schemes. Through the innovation of teaching mode, teaching methods, teaching means and other ways, create a good classroom atmosphere, improve students' learning enthusiasm;teach students in accordance with their aptitude, stimulate their potential, guide them to study consciously and actively, so as to put "student and learning as the center"into practice, construct an efficient teaching classroom, and cultivate more excellent applied talents. Starting from the problems existing in the teaching process of signals and systems, this paper actively explores the method of teaching students in accordance with their aptitude, constructs a student-centered teaching mode and assessment system, puts forward the allocation mechanism of discourse power, and finally explores the teaching reform scheme of "signals and systems"course with students as the center, and finally divides the teaching results before and after the reform The results show that the implementation effect of the student-centered curriculum teaching reform is good. © 2021 ACM.

关键词： Students

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Design of Intelligent Pension Platform Based on Internet of Things

Design of Intelligent Pension Platform Based on Internet of ...

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2020 International Conference on Mechanical Automation and Computer engineering, MACE 2020

作者： Wang, Sainan Liu, Tao Wei, Wei Department of Information and Control Engineering Shenyang Institute of Science and Technology Liaoning China

This paper takes the construction of Shenyang intelligent old-age platform as the object of study, and puts forward a plan that conforms to the construction of Shenyang intelligent old-age platform under the background of the Internet of things. Intelligent pension platform construction should be based on internet of things information technology, integrate resources such as families, communities, community health service centers, large medical service institutions and government departments, provide real-time, intelligent, dynamic and whole-process services for the elderly at home and the elderly with chronic diseases, realize the organic integration of smart pension, information-based pension and healthy pension, and solve the health pension clothing of the elderly at home. Business requirements. In order to achieve the above goals, the research contents of this paper are as follows: First, the status quo and existing problems of smart old-age support in Shenyang are analyzed, then the social needs of smart old-age support in Shenyang are analyzed, then the design framework of smart old-age support platform is proposed, and finally, the construction scheme of smart old-age support platform in Shenyang under the background of the internet of things is proposed. © Published under licence by IOP Publishing Ltd.

关键词： Internet of things

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Comparison of Three Artificial Intelligence Methods for Predicting 90% Quantile Interval of Future Insulin Sensitivity of Intensive Care Patients

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IFAC-PapersOnLine 2023年第2期56卷 2091-2095页

作者： Bálint Szabó Ákos Szlávecz Béla Paláncz Katalin Kovács J. Geoffrey Chase Balázs István Benyó Budapest University of Technology and Economics Faculty of Electrical Engineering and Information Technology Department of Control Engineering and Information Technology Budapest Hungary Department of Informatics Széchenyi István University Győr Hungary Department of Mechanical Engineering University of Canterbury Christchurch New Zealand

Three alternative artificial intelligence-based insulin sensitivity prediction methods are compared in this study. Insulin sensitivity prediction is an essential step in calculating the optimal treatment options in model-based glycemic control protocol of insulin-dependent intensive care patients. The prediction methods must predict not only the expected value of the insulin sensitivity for a given time horizon but also the 90% confidence interval making the prediction problem more specific compared to the common prediction problems. All of the proposed prediction methods - proposed in our previous publications - use different neural network models: a classification deep neural network model, a Mixture Density Network based model, and a Quantile regression based model. The patent data set used for the development and accuracy assessment is from 3 clinical ICU cohorts, including 820 treatment episodes of 606 patients and 68,631 hours of treatment. To evaluate the efficacy of the prediction in the context of clinical requirements, three metrics are used Success rate, Interval ratio, and I-Score are applied.

关键词： Insulin Sensitivity Tight Glycaemic control Prediction Method Artificial Intelligence Artificial Neural Network

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A Lightweight Model of VGG-U-Net for Remote Sensing Image Classification

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Computers, Materials & Continua 2022年第12期73卷 6195-6205页

作者： Mu Ye Li Ji Luo Tianye Li Sihan Zhang Tong Feng Ruilong Hu Tianli Gong He Guo Ying Sun Yu Thobela Louis Tyasi Li Shijun College of Information Technology Jilin Agricultural UniversityChangchun130118China Jilin Province Agricultural Internet of Things Technology Collaborative Innovation Center Changchun130118China Jilin Province Intelligent Environmental Engineering Research Center Changchun130118China Jilin Province Information Technology and Intelligent Agriculture Engineering Research Center Changchun130118China College of Engineering and Technology Jilin Agricultural UniversityChangchun130118China Department of Agricultural Economics and Animal Production University of LimpopoSovenga0727PolokwaneSouth Africa College of Information Technology Wuzhou UniversityWuzhou543003China Guangxi Key Laboratory of Machine Vision and Intelligent Control Wuzhou543003China

Remote sensing image analysis is a basic and practical research hotspot in remote sensing *** sensing images contain abundant ground object information and it can be used in urban planning,agricultural monitoring,ecological services,geological exploration and other *** this paper,we propose a lightweight model combining vgg-16 and u-net *** combining two convolutional neural networks,we classify scenes of remote sensing *** ensuring the accuracy of the model,try to reduce the memory of *** to the experimental results of this paper,we have improved the accuracy of the model to 98%.The memory size of the model is 3.4 *** the same time,The classification and convergence speed of the model are greatly *** simultaneously take the remote sensing scene image of 64×64 as input into the designed *** the accuracy of the model is 97%,it is proved that the model designed in this paper is also suitable for remote sensing images with few target feature points and low ***,the model has a good application prospect in the classification of remote sensing images with few target feature points and low pixels.

关键词： VGG-16 U-Net fewer feature points nonlinear correction layer zero padding

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LPV control of Systems via Nonlinear Actuator Dynamics Mapping

LPV Control of Systems via Nonlinear Actuator Dynamics Mappi...

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International Conference on Methods and Models in Automation and Robotics (MMAR)

作者： Zoltán Téczely Csaba Fazekas Bálint Kiss Department of Control Engineering and Information Technology Budapest University of Technology and Economics Budapest Hungary thyssenkrupp Components Technology Hungary Ltd. Budapest Hungary

ISBN: (数字)9798350362343

ISBN: (纸本)9798350362350

The nonlinear nature of industrial actuators poses a major challenge in the design of mechatronic components. Variants of DC motors tend to exhibit more or less linear characteristics but are usually burdened with nonlinear marks especially due to friction, cogging, and magnetic current phenomena. Still, for an overwhelming majority of large-scale industrial applications, it is more common to employ sophisticated AC motors with nonlinear dynamics. Moreover, the load is rarely, if ever known, introducing a dramatic uncertainty in the actuator dynamics. This paper is concerned with a controller design scheme, in which nonlinear actuators are described as subsystems embedded into a higher-level control system. In the simplest form, the nonlinear actuator can be represented as a linear system by virtue of coordinate transformation coupled with linearizing feedback. However, the inclusion of technical constraints like measurement timing and disturbance handling results in an actuator description that makes exact linearization a less feasible option. Therefore, an alternative approach is presented in which the nonlinear character is mapped into a series of simple $1^{\text {st }}$ order systems and is subsequently handled by an LPV control structure. The control scheme is completed with an Unscented Kalman Filter as a load estimator. The design technique and validation tests are performed in a simulation environment, heavily based on a real-life motor and a general $2^{\text {nd }}$ order mechatronic system.

关键词： Linear systems Actuators Mechatronics Uncertainty Robot kinematics Friction control systems

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Self-Supervised Learning with Min-Max Distance Approach for Few-Shot Steel Surface Defects Recognition 43

Self-Supervised Learning with Min-Max Distance Approach for ...

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43rd Chinese control Conference, CCC 2024

作者： Wang, Tianlei Chen, Xinyao Li, Zeliang Zhou, Zhencai Zhou, Zhiheng Wuyi University School of Electronic and Information Engineering Jiangmen China Jiangmen Key Laboratory of Kejie Semiconductor Bonding Technology and Control System Jiangmen China Wuyi University School of Mechanical and Automation Engineering Jiangmen China Guangdong Province Kejie Machinery Automation Company Technical Department Jiangmen China

ISBN: (纸本)9789887581581

Surface defects in steel are crucial for quality inspection in the manufacturing of industrial metal products. While deep learning methods have been extensively studied in this field, the lack of large-scale annotated defect samples imposes significant labeling pressure, making training fully supervised deep models challenging. In response to this issue, we employ self-supervised learning for few-shot recognition, effectively learning representations from limited unlabeled data and achieving defect recognition with a small amount of labeled samples. In particular, we construct Other encoder with multi-view information and Base encoder with single view information based on the distillation self-supervised learning framework through the multi-crops mechanism, and the Other encoders and Base encoders perform information share. Our main contribution is that, based on this framework, we propose a new regularization method to solve the problem of instances deviating from the center of self-supervised clustering by minimizing the maximum instance distance (MMD). In testing, fine-tuning the MMD pre-trained model with a small number of labeled data achieves superior recognition performance on the steel surface defect dataset NEU, significantly outperforming other testing methods. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Self-supervised learning

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A New Belief-Based Incomplete Pattern Unsupervised Classification Method : Extended Abstract 39

A New Belief-Based Incomplete Pattern Unsupervised Classific...

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39th IEEE International Conference on Data engineering, ICDE 2023

作者： Zhang, Zuowei Liu, Zhe Ma, Zongfang Zhang, Yiru Wang, Hao University of Rennes 1 Institut de Recherche en Informatique et Systèmes Aléatoires France Xi'an University of Architecture and Technology School of Information and Control Engineering China Norwegian University of Science and Technology Department of Computer Science Norway

ISBN: (纸本)9798350322279

Imputing the incomplete patterns in clustering tasks is a common but risky procedure, because the estimated values may affect the real distribution of the data and deteriorate the results. To address this problem, a new belief-based incomplete pattern unsupervised classification method (BPC) with uncertainty and imprecision reasoning is proposed in this paper. First, the complete patterns are grouped into a few clusters to obtain the corresponding reliable centers, and thereby are divided into reliable patterns and unreliable ones by an optimization method. Second, a basic classifier trained by reliable patterns is employed to classify unreliable patterns and incomplete patterns edited by the neighbors. Finally, some imprecise patterns are carefully reassigned again by a new distance-based rule depending on the obtained reliable centers and belief functions theory. The simulation results show that the BPC has the potential to deal with real datasets. © 2023 IEEE.

关键词： Uncertainty analysis

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Resilient Nonlinear State Estimation Using the Median Operation for a Network of Droop-controlled Power Inverters

Resilient Nonlinear State Estimation Using the Median Operat...

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European control Conference (ECC)

作者： Anne van der Horst Michelle S. Chong Junsoo Kim Henrik Sandberg Department of Mechanical Engineering Eindhoven University of Technology Department of Electrical and Information Engineering Seoul National University of Science and Technology Korea Division of Decision and Control KTH Royal Institute of Technology Stockholm Sweden

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

We consider the problem of estimating the states of a continuous-time nonlinear dynamical system, where a subset of sensors can be maliciously corrupted using a potentially unbounded additive signal. The proposed estimation scheme employs a bank of observers which are robust with respect to disturbances and attacks, in conjunction with median operation to build the state estimate. The median operation is the key ingredient which guarantees that the state estimate is constructed using sensor(s) which are not under attack. A standing assumption in this scheme is that the system has to be observable from each sensor. We provide a constructive design method for the state observers for a class of nonlinear systems and illustrate the efficacy of the resilient median-based state estimation scheme using real data on an inverter-based power distribution network.

关键词： Additives Design methodology Europe Observers Sensor systems Inverters Sensors

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Composite Nonlinear control for Permanent Magnet Synchronous Motors Speed Regulation Systems 13

Composite Nonlinear Control for Permanent Magnet Synchronous...

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2022 IEEE International Conference on Power Systems technology, POWERCON 2022

作者： Che, Zhiyuan Yu, Haitao Mobayen, Saleh Ali, Murad Yang, Chunyu School of Electrical Engineering Southeast University Nanjing China University of Zanjan Department of Electrical Engineering Zanjan Iran School of Information and Control Engineering China University of Mining and Technology Xuzhou China

ISBN: (数字)9781665417754

ISBN: (纸本)9781665417754

This paper addresses the problems of a composite nonlinear control for the permanent magnet synchronous motors (PMSMs) speed regulation systems, which is primarily constituted by an extended state observer (ESO)-based feedforward compensation and nonlinear proportional feedback (NPF) control law. Firstly, an optimal control synthesis function-based tracking differentiator (TD) is developed to arrange the transition dynamic for the reference speed value, while its high quality differential signal is facilitated. Then, by taking the parametric perturbations and external disturbances into account, a nonlinear extended state observer is designed to estimate the lumped disturbance, such that the system anti-disturbance performance is preserved. Meanwhile, the estimations of system states are also performed. Furthermore, an adaptive proportional control law is proposed, resulting in the eventual composite nonlinear strategy by incorporating the estimate values into the designed NPF controller. Finally, a PMSM servo system is studied to demonstrate the advantages and effectiveness of the proposed approaches. © 2022 IEEE.

关键词： Permanent magnets

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