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Grouping Decision Algorithm for Dynamic Terminals in Random Access Networks

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Journal of Communications and information Networks 2024年第2期9卷 176-183页

作者： Hongliang Sun Tongfei Chen Chuangye Zhao Mengxin Chen College of information and control Engineering Jilin Institute of Chemical TechnologyJilin 132022China

This paper proposes a grouping decision algorithm for random access networks with the carrier sense multiple access (CSMA) mechanism, which can balance the traffic load and solve the hidden terminal issue. Considering the arrival characteristics of terminals and quality of service (QoS) requirements, the traffic load is evaluated based on the effective bandwidth theory. Additionally, a probability matrix of hidden terminals is constructed to take into account the dynamic nature of hidden terminal relations. In the grouping process, an income function is established with a view to the benefits of decreasing the probability of hidden terminal collisions and load balancing. Then, we introduce the grey wolf optimization (GWO) algorithm to implement the grouping decision. Simulation results demonstrate that the grouping algorithm can effectively alleviate the performance degradation and facilitate the management of network resources.

关键词： random access network hidden terminal collision probability effective bandwidth traffic load grey wolf optimization

State estimation for delayed switched positive systems: delayed radius approach

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Science China(information Sciences) 2024年第8期67卷 190-205页

作者： Weizhong CHEN Zhongyang FEI Xudong ZHAO Zheng-Guang WU School of Electronics and information Xi'an Polytechnic University Research institute of Intelligent control and Systems Harbin Institute of Technology Key Laboratory of Intelligent control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology School of control Science and Engineering Dalian University of Technology State Key Laboratory of Industrial control Technology Institute of Cyber-Systems and ControlZhejiang University

In this paper, an interval estimation scheme is developed for delayed switched positive systems（DSPS） with mode-dependent average dwell time switching. A lossless zonotopic estimation approach is proposed for the delayed intersection zonotope with the positive generator matrix. First, considering the existence of asynchronism between the system mode and the correction matrix mode, the mismatched intersection zonotope is constructed for DSPS to verify the consistency between the system model and ***, by utilizing the introduced radius definitions, the ?∞performance is addressed to optimize the size of delayed intersection zonotopes. Subsequently, we present a joint-design approach of switching signals and the mode-dependent correction matrix by constructing positive generator matrix-based delayed radius functions. Furthermore, guaranteed nonnegative state bounds are derived for the considered DSPS based on the proposed lossless zonotopic estimation criteria. Finally, detailed simulations are conducted to validate the feasibility and superiority of the developed methods.

关键词： delayed switched positive systems interval estimation asynchronous correction matrix zonotopes mode-dependent average dwell time

An Improved UNet Lightweight Network for Semantic Segmentation of Weed Images in Corn Fields

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Computers, Materials & Continua 2024年第6期79卷 4413-4431页

作者： Yu Zuo Wenwen Li School of information and control Engineering Jilin Institute of Chemical TechnologyJilin132022China School of Mechanical and control Engineering Baicheng Normal UniversityBaicheng137000China

In cornfields,factors such as the similarity between corn seedlings and weeds and the blurring of plant edge details pose challenges to corn and weed *** addition,remote areas such as farmland are usually constrained by limited computational resources and limited collected ***,it becomes necessary to lighten the model to better adapt to complex cornfield scene,and make full use of the limited data *** this paper,we propose an improved image segmentation algorithm based on ***,the inverted residual structure is introduced into the contraction path to reduce the number of parameters in the training process and improve the feature extraction ability;secondly,the pyramid pooling module is introduced to enhance the network’s ability of acquiring contextual information as well as the ability of dealing with the small target loss problem;and lastly,Finally,to further enhance the segmentation capability of the model,the squeeze and excitation mechanism is introduced in the expansion *** used images of corn seedlings collected in the field and publicly available corn weed datasets to evaluate the improved *** improved model has a total parameter of 3.79 M and miou can achieve 87.9%.The fps on a single 3050 ti video card is about *** experimental results show that the network proposed in this paper can quickly segment corn weeds in a cornfield scenario with good segmentation accuracy.

关键词： Semantic segmentation deep learning UNet pyramid pooling module

Research on Performance Optimization of Spark Distributed Computing Platform

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Computers, Materials & Continua 2024年第5期79卷 2833-2850页

作者： Qinlu He Fan Zhang Genqing Bian Weiqi Zhang Zhen Li School of information and control Engineering Xi’an University of Architecture and TechnologyXi’an710054China Shaanxi institute of Metrology Science Xi’an710043China

Spark,a distributed computing platform,has rapidly developed in the field of big *** in-memory computing feature reduces disk read overhead and shortens data processing time,making it have broad application prospects in large-scale computing applications such as machine learning and image ***,the performance of the Spark platform still needs to be *** a large number of tasks are processed simultaneously,Spark’s cache replacementmechanismcannot identify high-value data partitions,resulting inmemory resources not being fully utilized and affecting the performance of the Spark *** address the problem that Spark’s default cache replacement algorithm cannot accurately evaluate high-value data partitions,firstly the weight influence factors of data partitions are modeled and ***,based on this weighted model,a cache replacement algorithm based on dynamic weighted data value is proposed,which takes into account hit rate and data *** integration and usage strategies are implemented based on LRU(LeastRecentlyUsed).Theweight update algorithm updates the weight value when the data partition information changes,accurately measuring the importance of the partition in the current job;the cache removal algorithm clears partitions without useful values in the cache to releasememory resources;the weight replacement algorithm combines partition weights and partition information to replace RDD partitions when memory remaining space is ***,by setting up a Spark cluster environment,the algorithm proposed in this paper is experimentally *** have shown that this algorithmcan effectively improve cache hit rate,enhance the performance of the platform,and reduce job execution time by 7.61%compared to existing improved algorithms.

关键词： Spark memory optimization memory replacement strategy

Data-driven active vibration control for helicopter with trailing-edge flaps using adaptive dynamic programming

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Chinese Journal of Aeronautics 2024年第6期37卷 151-166页

作者： Yu CHEN Qun ZONG Xiuyun ZHANG Jinna LI School of Electrical and information Engineering Tianjin UniversityTianjin 300072China School of information and control Engineering Liaoning Petrochemical UniversityFushun 113001China

The helicopter Trailing-Edge Flaps(TEFs)technology is one of the recent hot topics in morphing wing *** employing controlled deflection,TEFs can effectively reduce the vibration level of ***,designing specific vibration reduction control methods for the helicopters equipped with trailing-edge flaps is of significant practical *** paper studies the optimal control problem for helicopter-vibration systems with TEFs under the framework of adaptive dynamic programming combined with Reinforcement Learning(RL).Time-delay and disturbances,caused by complexity of helicopter dynamics,inevitably deteriorate the control performance of vibration *** solve this problem,a zero-sum game formulation with a linear quadratic form for reducing vibration of helicopter systems is presented with a virtual *** this context,an off-policy reinforcement learning algorithm is developed to determine the optimal control *** algorithm utilizes only vertical vibration load data to achieve a policy that reduces vibration,attains Nash equilibrium,and addresses disturbances while compensating for time-delay without knowledge of the dynamics of the helicopter *** effectiveness of the proposed method is demonstrated in a virtual platform.

关键词： Active control Adaptive dynamic program-ming Helicopter rotor Vibration control Zero-sum game

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Generic and flexible self-correction method for nonlinearity-induced phase error in three-dimensional imaging

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Chinese Optics Letters 2024年第6期22卷 129-135页

作者： Jianhua Wang Peng Xu Yanxi Yang School of information and control Engineering Qingdao University of TechnologyQingdao 266520China School of Automation and information Engineering Xi’an University of TechnologyXi’an 710048China

In three-dimensional imaging employing phase-shifting profilometry(PSP), the nonlinear response of projector and camera makes the fringe gray distribution non-sinusoidal, which further leads to phase error. Although the double 3-step phaseshifting method is simple and effective, it needs to add an additional set of fringe sequences, which reduces the measurement efficiency. To this end, this paper introduces a generic and flexible self-correction method for nonlinearity-induced phase ***, according to the nonlinearity-induced phase error model, we introduce an additional wrapped phase with a phase difference of π/3. The error waveform of the two wrapped phases is opposite but not coincident. Then, we introduce an estimation algorithm for the additional wrapped phase offset. Finally, we fuse the two wrapped phases to correct the phase error. Experiments confirm that the root mean squared error of the proposed method is 64.1% lower than that of the traditional method and 13.3% lower than that of the Hilbert transform method. The proposed method does not require any additional fringes or hardware assistance and can be easily extended to 4-step or 5-step PSP.

关键词： three-dimensional imaging phase-shifting profilometry nonlinear response self-correction Hilbert transform

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Detection of Oscillations in Process control Loops From Visual Image Space Using Deep Convolutional Networks

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 982-995页

作者： Tao Wang Qiming Chen Xun Lang Lei Xie Peng Li Hongye Su the Department of Electronic Engineering the School of InformationYunnan UniversityKunming 650091China DAMO Academy Alibaba GroupHangzhou 311100China the State Key Laboratory of Industrial control Technology Institute of Cyber-Systems and ControlZhejiang UniversityHangzhou 310027China

Oscillation detection has been a hot research topic in industries due to the high incidence of oscillation loops and their negative impact on plant *** numerous automatic detection techniques have been proposed,most of them can only address part of the practical *** oscillation is heuristically defined as a visually apparent periodic ***,manual visual inspection is labor-intensive and prone to missed *** neural networks(CNNs),inspired by animal visual systems,have been raised with powerful feature extraction *** this work,an exploration of the typical CNN models for visual oscillation detection is ***,we tested MobileNet-V1,ShuffleNet-V2,Efficient Net-B0,and GhostNet models,and found that such a visual framework is well-suited for oscillation *** feasibility and validity of this framework are verified utilizing extensive numerical and industrial *** with state-of-theart oscillation detectors,the suggested framework is more straightforward and more robust to noise and *** addition,this framework generalizes well and is capable of handling features that are not present in the training data,such as multiple oscillations and outliers.

关键词： Convolutional neural networks(CNNs) deep learning image processing oscillation detection process industries

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A Constraint Adaptive Multi-Tasking Differential Evolution Algorithm:Designed for Dispatch of Integrated Energy System in Coal Mine

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Tsinghua Science and Technology 2024年第2期29卷 368-385页

作者： Canyun Dai Xiaoyan Sun Hejuan Hu Yong Zhang Dunwei Gong School of information and control Engineering China University of Mining and TechnologyXuzhou 221116China School of information Science and Technology Qingdao University of Science and TechnologyQingdao 266061China

The dispatch of integrated energy systems in coal mines(IES-CM)with mine-associated supplies is vital for efficient energy utilization and carbon emissions ***,IES-CM dispatch is highly challenging due to its feature as multi-objective and strong *** constrained multi-objective evolutionary algorithms often fall into locally feasible domains with poorly distributed Pareto front,which greatly deteriorates dispatch *** tackle this problem,we transform the traditional dispatch model of IES-CM into two tasks:the main task with all constraints and the helper task with constraint *** we propose a constraint adaptive multi-tasking differential evolution algorithm(CA-MTDE)to optimize these two tasks *** helper task with constraint adaptive is developed to obtain infeasible solutions near the feasible *** purpose of this infeasible solution is to transfer guiding knowledge to help the main task move away from local ***,a dynamic dual-learning strategy using DE/current-to-rand/1 and DE/current-to-best/1 is developed to maintain task diversity and ***,we comprehensively evaluate the performance of CA-MTDE by applying it to a coal mine in Shanxi Province,considering two IES-CM *** demonstrate the feasibility of CA-MTDE and its ability to generate a Pareto front with exceptional convergence,diversity,and distribution.

关键词： dispatch integrated energy system coal mine evolutionary multi-tasking constraint differential evolution

Gas sensor array based on carbon-based thin-film transistor for selective detection of indoor harmful gases

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Rare Metals 2024年第9期43卷 4401-4411页

作者： Can Liu Yu Sun Jia-Yi Guo Xiu-Lei Li Lu Tao Jin-Yong Hu Jue-Xian Cao Ping-Hua Tang Yong Zhang School of Electrical and information Engineering Hunan Institute of Engineering Physics and Optoelectronics&Hunan institute of Advanced Sensing and information Technology Xiangtan University

The identification of indoor harmful gases is imperative due to their significant threats to human health and *** achieve accurate identification,an effective strategy of constructing a sensor array combined with the pattern recognition algorithm is ***-based thin-film transistors are selected as the sensor array unit,with semiconductor carbon nanotubes （CNTs） within the TFT channels modified with different metals （Au,Cu and Ti） for selective responses to NH3,H2S and HCHO,*** accurate gas species identification,an identification mode that combines linear discriminant analysis algorithms and logistic regression classifier is *** test results demonstrate that by preprocessing the sensor array’s sensing data with the LDA algorithm and subsequently employing the LR classifier for identification,a 100% recognition rate can be achieved for three target gases （NH3,H2S and HCHO）.This work provides significant guidance for future applications of chip-level gas sensors in the realms of the Internet of Things and Artificial Intelligence.

关键词： Carbon-based thin-film transistors Gas sensor arrays Linear discriminant analysis Multi-gas detection Semiconductor carbon nanotubes