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2nd IEEE International Conference on Sensors, Electronics and Computer engineering, ICSECE 2024

作者： Su, Xing Wang, Pan Jiao, Rui Liu, Hongfei Liu, Yuxuan Ningxia Tiandi Benniu Industrial Group Co. Ltd National and Local Joint Engineering Laboratory of Intelligent Manufacturing Technology for Coal Mine Comprehensive Mining and Transportation Equipment Yinchuan China

ISBN: (纸本)9798350373646

Addressing the insufficient monitoring accuracy and subpar control efficacy in tension management of chains in coal mine scraper conveyors, a novel dynamic and agile adjustment approach based on data fusion is introduced. This method integrates multisource sensory data to form an intelligent decision-making model that blends fuzzy logic with a probabilistic neural network, facilitating precise detection and optimal control of the chain tension states. Initially, sensors measuring force, displacement, and current are strategically placed at pivotal sections of the scraper conveyor to collect multifaceted data pertinent to chain tension. Subsequently, fuzzy logic is applied to perform feature extraction and synthesis of various data types, yielding a comprehensive tension assessment index. Building on this, probabilistic neural networks are utilized for intelligent recognition of chain tension conditions and prediction of future trends. Lastly, tension is dynamically adjusted based on predictive outcomes and real-time feedback, ensuring the chain consistently operates at peak efficiency. This method's data fusion control strategy profoundly taps into the inherent connections among multisource information, overcoming the constraints of a single-source signal. The fusion of complex data via fuzzy logic and the learning and predictive capacities endowed by the probabilistic neural network substantially enhance the precision of tension monitoring and the promptness of control adjustments. © 2024 IEEE.

关键词： Chains

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Optimization of ultrasonic-assisted freezing of Penaeus chinensis by response surface methodology

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Food Quality and Safety 2021年第2期5卷 143-151页

作者： Yubin Ying Yingchun Xiang Jialin Liu Xin Chen Lingping Hu Yujin Li Yaqin Hu College of Biosystems Engineering and Food Science National-Local Joint Engineering Laboratory of Intelligent Food Technology and EquipmentZhejiang Key Laboratory for Agro-Food ProcessingIntegrated Research Base of Southern Fruit and Vegetable Preservation TechnologyZhejiang International Scientific and Technological Cooperation Base of Health Food Manufacturing and Quality ControlNingbo Research InstituteFuli Institute of Food ScienceZhejiang UniversityHangzhouChina College of Food Science and Technology Hainan Tropical Ocean UniversitySanyaChina College of Food Science and Engineering Ocean University of ChinaQingdaoChina

Objectives:Optimization of ultrasonic-assisted freezing of Penaeus chinensis by response surface methodology was studied in order to(1)obtain frozen Penaeus chinensis of high quality and(2)provide practical guidance for the application of ultrasonic-assisted freezing in Penaeus *** and Methods:Three independent and major variables were selected,including initial ultrasonic temperature(℃),ultrasonic power(W)and ultrasonic time(s on/2 s off).On the basis of one-factor experiments,17 groups of experiments were established by response surface methodology according to Box-Behnken *** multiple regression analysis the experimental data were fitted into a second-order polynomial equation,which was tested by proper statistical ***:The optimal ultrasonic conditions were as follows:initial ultrasonic temperature 0℃,ultrasonic power 180 W,ultrasonic time 5 son/2 s *** the optimization conditions,the time of passing through maximum ice crystal generation zone was 105.500 s,which was very close to the predictive passage time of 101.541 ***:Initial ultrasonic temperature,ultrasonic time and ultrasonic power played an important role in the process of ultrasonic-assisted freezing of Penaeus *** surface methodology was used to optimize the three factors in ultrasonic-assisted freezing,which could greatly shorten the time of passing through the maximum ice crystal generation zone and maintain the tissue structure of Penaeus chinensis well.

关键词： Ultrasonic-assisted freezing Penaeus chinensis response surface methodology time of passing through the maximum ice crystal generation zone optimization

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Dynamic Memristor based Cyclic Echo State Network for Time Series Prediction

Dynamic Memristor based Cyclic Echo State Network for Time S...

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Neural Networks, Information and Communication engineering (NNICE), International Conference on

作者： Guangli Li Lei Xia Jun Fu Shukai Duan Jianfeng Tang Lidan Wang College of Artificial Intelligence Southwest University Chongqing China National & Local Joint Engineering Research Center of Intelligent Transmission and Control Technology Chongqing China

Compared with traditional recurrent neural networks, the training cost of echo-state network computing is lower because the neurons in the reservoir are randomly connected. We only need to train the weight of the connection between the reservoir and the output layer. Due to its high accuracy and low training cost for time series forecasting tasks, it is widely used as a time series forecasting model in many fields. It is very important to provide rich reservoir state for echo state network system, which is the key to hardware implementation. In this paper, we propose a cyclic echo state network (DC-ESN) based on dynamic memristors, which generates rich reservoir states through cyclic structure, and can predict complex time series well even with a single memristor. Compared with the traditional echo state network, the size of the reservoir is reduced and the prediction accuracy is greatly improved. Our work can provide an idea for more efficient memristor based echo state network systems in the future to cope with complex time series prediction tasks.

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开式泵控非对称缸负载容腔独立控制系统（英文）

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Journal of Zhejiang University-Science A(Applied Physics & engineering) 2018年第3期19卷 203-210页

作者： Jing YAO Pei WANG Xiao-ming CAO Zhuo WANG The Laboratory of Heavy Machinery Fluid Power Transmission and Control in Hebei Yanshan University Qinhuangdao 066004 China National and Local Joint Engineering Center for Advanced Forging Press Forming Technology and Equipment Faculty of Engineering Yanshan University Qinhuangdao 066004 China Yanshan University Qinhuangdao 066004 China

目的:为减少能量排放和提升节能效果,并解决非对称缸系统的流量不对称问题,本文对开式泵控非对称缸负载容腔独立控制系统的控制特性及能耗特性进行了深入的研究,以期为其实际应用提供理论支撑。创新点:1.提出开式泵控非对称缸负载容腔... 详细信息

目的:为减少能量排放和提升节能效果,并解决非对称缸系统的流量不对称问题,本文对开式泵控非对称缸负载容腔独立控制系统的控制特性及能耗特性进行了深入的研究,以期为其实际应用提供理论支撑。创新点:1.提出开式泵控非对称缸负载容腔独立控制系统,建立其能量传输模型;2.以压机为对象进行实验研究,采用位置压力负载容腔独立控制方法,获得其能耗与控制特性。方法:1.介绍开式泵控非对称缸负载容腔独立控制系统的构型;2.通过理论推导,建立能量传输模型,得到具有能量回收功能的系统;3.通过实验研究和分析,验证所提系统和方法的有效性。结论:1.基于能量传输模型得到的系统具有较好的节能特性;2.开式泵控非对称缸负载容腔独立控制系统增加了系统控制自由度,验证了负载容腔独立控制方法的有效性;3.开式泵控非对称缸负载容腔独立控制系统采用无杆腔位置控制和有杆腔压力控制组合的控制方法;随着有杆腔压力的提高,在不增加系统能耗的前提下该方法改善了系统的位置控制精度。

关键词：泵控系统非对称缸能耗位置压力组合控制负载容腔独立控制

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Spatio- Temporal Neural Network with Contrastive Learning for Vehicle Trajectory Prediction

Spatio- Temporal Neural Network with Contrastive Learning fo...

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Complex Systems and intelligent Science (CSIS-IAC), International Annual Conference on

作者： Jiufa Li Shukai Duan Lidan Wang College of Artificial Intelligence Southwest University Chongqing China National & Local Joint Engineering Laboratory of Intelligent Transmission and Control Technology College of Artificial Intelligence Southwest University Chongqing China

In the field of autonomous driving vehicles, accurately predicting vehicle trajectories is crucial for ensuring safety and enhancing ride comfort. However, predicting the trajectory of a target vehicle is challenging due to complex interaction dynamics with nearby vehicles in different scenarios. To improve prediction accuracy, we introduce a novel spatiotemporal neural network with contrastive learning capabilities. This method delves deep into potential encodings within interaction scenes from both local and global perspectives and incorporates future trajectory features through a Conditional Variational Autoencoder (CVAE). We rigorously evaluate this approach through ablation experiments using the US-101 and I–80 datasets from the national Highway Traffic Safety Administration's Next Generation Simulation (NGSIM) dataset. The research results demonstrate that our method outperforms the current state-of-the-art techniques in terms of performance.

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Adaptive modulation coding method based on minimum packet loss rate in AOS communication system

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International Journal of Performability engineering 2019年第4期15卷 1151-1160页

作者： Liu, Qingli Yang, Yanjun Liu, Zhiguo National and Local Joint Engineering Laboratory of Intelligent Shipping and Logistics Network Technology Dalian University Dalian116622 China

Aiming at the problem of increasing packet loss rate and decreasing throughput caused by the characteristics of high data burst and high channel error rate in the AOS space communication system, this paper considers the factors of queue packet loss and transmission error packet loss and proposes an adaptive modulation coding method based on minimum packet loss rate in the AOS communication system. Firstly, a system packet loss objective function is established, and the modulation coding mode can be determined by solving the objective function minimum. Secondly, the modulation coding mode is dynamically adjusted according to certain rules, determined by the channel state and the queue state jointly. Finally, the system packet loss rate is reduced and the transmission performance of the system is improved. The theoretical analysis and simulation results show that compared with the SLBCCQ method, this method can reduce the system packet loss rate by up to 30%. Meanwhile, compared with the AMC algorithm, it can reduce the system packet loss rate by 41.7%. © 2019 Totem Publisher, Inc. All rights reserved.

关键词： Packet loss

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Remote sensing image encryption algorithm using chaos and differential coding 23

Remote sensing image encryption algorithm using chaos and di...

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15th International Conference on Digital Image Processing, ICDIP 2023

作者： Wang, Quanyv Zhou, Wei Zhao, Xiaohu National and Local Joint Engineering Laboratory of Internet Application Technology on Mine China University of Mining and Technology Jiangsu Xuzhou China School of Information and Control Engineering China University of Mining and Technology Jiangsu Xuzhou China School of Information Engineering Suzhou University Anhui Suzhou China

ISBN: (纸本)9798400708237

As remote sensing images are widely used, their security has also received extensive attention. This paper proposes a novel remote sensing image encryption algorithm (RSIEA) using the designed one-dimensional (1D) chaos and differential coding. Firstly, the pixels in the plain image are permuted using the index sequence of chaotic sequence. Secondly, we design a differential coding scheme, which can permute and diffuse the image at the same time. Finally, chaotic image and XOR operation are used together to further enhance the diffusion effect. Experiment results and security analyses demonstrate the high security of our algorithm. In other words, our algorithm can guarantee the secure transmission and storage of remote sensing images. © 2023 ACM.

关键词： Security of data

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High-Performance Convolutional Neural Network Emulation Via Fpga-Integrated Memristive Circuitry

SSRN

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SSRN 2024年

作者： Yang, Yucheng Tan, Aolong Duan, Shukai Wang, Lidan State Key Laboratory of Intelligent Vehicle Safety Technology China College of Artificial Intelligence Southwest University China National & Local Joint Engineering Research Center of Intelligent Transmission and Control Technology China Chongqing Key Laboratory of Brain-inspired Computing and Intelligent Chips China

In this study, to tackle the challenges of high cost, insufficient reliability, and short lifespan associated with physical memristors, a FPGA-based memristor simulation circuit is proposed. This circuit is deployed on the Xilinx ZYNQ-7000 FPGA XC7Z020, with a resource utilization rate of less than 1%, and has been successfully integrated and validated. Moreover, the paper leverages a memristor model to build a convolutional neural network for MNIST image recognition, which achieves an accuracy of 90.22% with a parameter count of 512. © 2024, The Authors. All rights reserved.

关键词： Memristors

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Microstructural evolution and mechanical properties of 55NiCrMoV7 hot-work die steel during quenching and tempering treatments

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Advances in Manufacturing 2021年第4期9卷 520-537页

作者： Xing-Sheng Yu Chuan Wu Ru-Xing Shi Ya-Sha Yuan Luoyang CITIC HIC Casting&Forging Co. LtdLuoyang 471039HenanPeople’s Republic of China National-Local Joint Engineering Laboratory of Intelligent Manufacturing Oriented Automobile Die&Mould Tianjin University of Technology and EducationTianjin 300222People’s Republic of China CITIC Heavy Industries Co. LtdLuoyang 471039HenanPeople’s Republic of China

55NiCrMoV7 hot-work die steel is mainly used to manufacture heavy forgings in the fields of aerospace and *** study aims to clarify the effects of heat treatment on the microstructural evolution and mechanical properties of the steel,in order to find out an optimal heat treatment scheme to obtain an excellent balance of strength,ductility and *** steel was quenched at temperature from 790℃ to 910℃ followed by tempering treatments of 100–650℃ for 5 *** mechanical property tests were carried out by tensile,impact toughness and *** microscope(OM),scanning electron microscope(SEM)and transmission electron microscope(TEM)were used to observe the austenite grains,lath martensite,carbides and fracture *** results show that the quenching temperature mainly influences the austenite grain size and the volume fraction of undissolved carbides(UCs),while the tempering temperature mainly influences the size and morphology of the martensite with a body centered cubic(BCC)and the carbides with a face centered cubic(FCC).The mechanical properties of the steel,including yield and tensile strength,ductility,impact toughness and hardness,get an excellent balance at a quenching range of 850–870*** the tempering temperature increases,the yield and tensile strength and hardness decrease,while the ductility and impact toughness *** variation trends can be further verified by fracture SEM observation and *** with a macro-micro coupled finite element(MMFE)modeling technique,the cooling rate,microstructural evolution and yield strength of the steel were predicted and compared with the tested data.

关键词： Hot-work die steel Microstructural evolution Mechanical properties Heat treatment Macro-micro coupled modeling and simulation

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Analysis on D2D Heterogeneous Networks with State-Dependent Priority Traffic

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Computers, Materials & Continua 2023年第2期74卷 2981-2998页

作者： Guangjun Liang Jianfang Xin Linging Xia Xueli Ni Yi Cao Department of Computer Information and Cyber Security Jiangsu Police InstituteNanjingChina National and Local Joint Engineering Laboratory of Radio Frequency Integration and Microassembly Technology Nanjing University of Posts and TelecommunicationsNanjingChina School of Intelligent Engineering Nanjing Institute of Railway TechnologyNanjingChina Jiangsu Province Electronic Data Forensics and Analysis Engineering Research Center NanjingChina Department of Electrical and Computer Engineering University of WindsorWindsorONN9B 3P4Canada

In this work,we consider the performance analysis of state dependent priority traffic and scheduling in device to device(D2D)heterogeneous *** are two priority transmission types of data in wireless communication,such as video or telephone,which always meet the requirements of high priority(HP)data transmission *** there is a large amount of low priority(LP)data,there will be a large amount of LP data that cannot be *** situation will cause excessive delay of LP data and packet dropping *** order to solve this problem,the data transmission process of high priority queue and low priority queue is *** the priority jump strategy to the priority queuing model,the queuing process with two priority data is modeled as a two-dimensionalMarkov chain.A state dependent priority jump queuing strategy is proposed,which can improve the discarding performance of low priority *** quasi birth and death process method(QBD)and fixed point iterationmethod are used to solve the causality,and the steady-state probability distribution is further ***,performance parameters such as average queue length,average throughput,average delay and packet dropping probability for both high and low priority data can be *** simulation results verify the correctness of the theoretical ***,the proposed priority jump queuing strategy can significantly improve the drop performance of low-priority data.

关键词： Stochastic geometry queuing theory D2D heterogeneous networks quasi-birth and death process

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