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Temperature Control Method for Batch Reactors Based on Adaptive Delay Compensation

Temperature Control Method for Batch Reactors Based on Adapt...

引用

2024 China Automation Congress, CAC 2024

作者： Mao, Dehui Li, Peng Ai, Mingxi Wu, Jiande Yang, Chuangyan Wang, Hancheng School of Information Science and Engineering Yunnan University Kunming China Yunnan Key Laboratory of Intelligent Systems and Computing Yunnan University Kunming China

ISBN: (纸本)9798350368604

To address the instability issue caused by time-delay and nonlinear characteristics of intermittent reactions in batch reactors, a temperature control method for batch reactors based on adaptive delay compensation was proposed. By integrating the chemical reaction mechanism inside the reactor with graphical analysis and actual production data, a time-varying second-order delayed transfer function model for the reactor is established. The adaptive rate for controlling the time-varying delayed system is designed based on the control error between the actual controlled object and the nominal model. Furthermore, standard Smith predictor is employed to compensate for the delay in the error term. When applied to temperature control in batch reactors, experimental results demonstrate that this method effectively reduces the temperature control errors caused by time-varying delays, significantly accelerates the convergence speed and diminishes the oscillation amplitude of the temperature curve. © 2024 IEEE.

关键词： Batch reactors

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Lightweight Small Target Detection Algorithm for UAV Infrared Aerial Photography Based on YOLOv8 5

Lightweight Small Target Detection Algorithm for UAV Infrare...

引用

5th International Conference on Artificial Intelligence and Computer Engineering, ICAICE 2024

作者： Li, Jinfeng Zhu, Xiaodong Shan, Wei College of Physics and Electronic Information Huaibei Normal University Huaibei China Anhui Provincial Key Laboratory of Intelligent Computing and Application Huaibei China

ISBN: (纸本)9798331528911

Aiming at the complexity of UAV infrared air target detection model,a lightweight target detection algorithm based on YOLOv8 n is proposed. By introducing a lightweight Depthwise Convolution module, the model size is reduced to facilitate deployment on mobile devices. The experimental results on the HIT-UAV dataset show that compared with the benchmark model YOLOv8n, the improved algorithm reduces the number of parameters and GFLOPs by 0.6M and 1.2G, respectively. In summary, the effectiveness of the algorithm is verified, which provides the possibility for the UAV to perform real-time target detection tasks. © 2024 IEEE.

关键词： Aerial photography

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Video Rumor Classification Based on Multi-modal Theme and keyframe Fusion 17th

Video Rumor Classification Based on Multi-modal Theme and ...

引用

17th CCF Conference on Computer Supported Cooperative Work and Social computing, ChineseCSCW 2022

作者： You, Jinpeng Lin, Yanghao Lin, Dazhen Cao, Donglin Artificial Intelligence Department Xiamen University Xiamen361005 China The Key Laboratory of Cognitive Computing and Intelligent Information Processing of Fujian Education Institutions Wuyi University Wuyishan354300 China

ISBN: (纸本)9789819923557

In recent years, short video platforms have become the main source of online rumors. According to the statistics of Shanghai online rumor refutation platform in 2021, the number of short video rumors was about five times that of short video rumors in 2020, which makes it necessary to detect rumors of short videos. At present, short video rumor detection has the problem of multi-modal information fusion, the traditional multi-modal fusion uses deep learning to obtain the underlying features of multi-modality and then aggregate them into cross-modal features. However, there are distortions of theme and tampering with key-frame in rumor videos. Therefore, short video rumors need to learn features from the perspective of theme and key-frame. Aiming at the problem of multi-modal information fusion of short video rumors, this paper proposes a short video rumor detection model (TKCM) based on theme and key-frame. It uses aggregation network to obtain the theme feature of video, attention network to obtain the key-frame feature, and fuses multi-modality by modal adjustment mechanism for short video rumor detection. Experimental results show that the F1 score of the proposed method on the short video rumor dataset is improved by 2%–5% compared with some state-of-the-art video classification models. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Deep learning

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Lightweight Monocular 3D Object Detection Based on Attention Mechanism 5

Lightweight Monocular 3D Object Detection Based on Attention...

引用

5th Asia-Pacific Conference on Image processing, Electronics and Computers, IPEC 2024

作者： Zhan, Feng Zhang, Zhi Wuhan University of Science and Technology College of Computer Science and Technology Hubei Wuhan430065 China Information Processing and Real-time Industrial System Hubei Province Key Laboratory of Intelligent Hubei Wuhan430065 China Information Processing and Real-time Industrial System Hubei Province Key Laboratory of Intelligent Hubei Wuhan30065 China

ISBN: (纸本)9798350374407

In the field of autonomous driving, 3D target detection is an important technology. In view of the shortcomings of existing monocular 3D detection algorithms in terms of accuracy and real-time performance, we propose a lightweight 3D target detection algorithm based on the attention mechanism. In order to ensure the real-time performance of the model, we use depthwise separable convolutions in the backbone network. The feature maps of each scale are then connected to an EMA module, which can fuse spatial attention and cross-dimensional Coordinate attention is used to enhance the feature extraction capability of the network, and BiFPN is subsequently used for multi-scale feature fusion. Finally, experiments were conducted on the KITTI dataset, and the results showed that our algorithm was superior to other methods in both accuracy and speed. © 2024 IEEE.

关键词： Object recognition

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Research on Electrical Activity and Synchronization Behavior of Electromagnetic Coupled FHN Neural Networks

Research on Electrical Activity and Synchronization Behavior...

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2024 Prognostics and System Health Management Conference, PHM 2024

作者： Jing, Yuancheng Xian, Yanhua School of Electronic and Information Engineering Guangxi Key Laboratory of Brain-inspired Computing and Intelligent Chips Guangxi Normal University Guilin541004 China

ISBN: (纸本)9798350360585

This paper proposes three models based on FHN neurons: a neuron model introducing a magnetic field variable through a magnetoresistive memristor, a neuron model introducing an external electric field, and a chain neural network model under the combined action of an electromagnetic field. (1) Detailed numerical simulations were performed on the two neuron models. The results show that under the action of a magnetic field, different external DC current stimulations and different feedback gains can lead to various discharge modes of neurons, such as resting state, spike discharge, and periodic spike discharge;while under the action of an electric field, different external DC current stimulations and different charge sizes can cause neurons to exhibit cluster discharges of different periods. (2) An in-depth analysis of the electromagnetic coupled neural network was conducted. The results found that increasing the synaptic coupling strength can enhance the synchronization effect of the neural network. However, changing the charge size and memristor feedback gain does not change the synchronization effect of the network. These findings provide new perspectives and methods for understanding and designing neural computing systems. © 2024 IEEE.

关键词： Electromagnetic fields

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Complex Industrial Process Monitoring Using Improved Dynamic Latent Variables - Neighborhood Preserving Embedding

Complex Industrial Process Monitoring Using Improved Dynamic...

引用

2024 China Automation Congress, CAC 2024

作者： Wang, Hancheng Li, Peng Ai, Mingxi Wu, Jiande Yang, Chuangyan Xu, Qingmin School of Information Science and Engineering Yunnan University Kunming China Yunnan Key Laboratory of Intelligent Systems and Computing Yunnan University Kunming China

ISBN: (纸本)9798350368604

In complex industrial process monitoring, prevalent challenges include high dimensionality, extensive redundancies, and dynamic characteristics. In this paper, we propose an Improved Dynamic Latent Variable-Neighborhood Preserving Embedding (DLV-NPE) algorithm specifically designed to tackle these issues. The methodology begins with the implementation of a variance-covariance feature selection method to minimize redundancies among monitoring variables. This is followed using a dynamic latent variable algorithm to extract dynamic regression properties from the selected variables. Subsequently, the NPE algorithm is employed to preserve the residuals of high-dimensional dynamic latent variables and the high-dimensional residuals of selected variables, thereby preserving the integrity of the low-dimensional manifold structure. Finally, Bayesian inference is applied to develop comprehensive monitoring indicators. The efficacy of the DLV-NPE algorithm is validated through its application to the Tennessee Eastman (TE) process, where it demonstrates superior fault detection capabilities compared to other algorithms. © 2024 IEEE.

关键词： Embeddings

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Research on intelligent Traffic Pedestrian Detection Algorithm Based on Improved YOLOv8 5

Research on Intelligent Traffic Pedestrian Detection Algorit...

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5th International Conference on Artificial Intelligence and Computer Engineering, ICAICE 2024

作者： Yue, Yurong Kong, Xiaoyang Pan, Rui Shan, Wei College of Physics and Electronic Information Huaibei Normal University Huaibei China Anhui Provincial Key Laboratory of Intelligent Computing and Application Huaibei China

ISBN: (纸本)9798331528911

Aiming at the problem of poor detection of long-distance pedestrians in intelligent traffic scenarios, an improved YOLOv8 pedestrian detection algorithm is proposed. Using YOLOv8 as the basic network, SPD-Conv is embedded before the C2f layer of backbone and after the Conv layer of neck as the key preprocessing step. Experimental results on the public dataset Caltech Pedestrian Dataset show that compared with the baseline algorithm, mAP0.5 is increased by 3%, mAP0.5: 0.95 is increased by 5.8%, and LAMR is reduced by 5.5%. Compared with the popular algorithm, mAP0.5 and mAP0.5: 0.95 are as high as 0.892 and 0.598, respectively, and LAMR is as low as 0.249, which is better than the popular algorithm. The results show that the algorithm achieves a significant improvement in accuracy in pedestrian detection tasks, and effectively reduces the occurrence of missed detection. It can serve intelligent transportation more effectively and reduce the potential safety hazards caused by missed detection. © 2024 IEEE.

关键词： intelligent transportation pedestrian detection spatial to deep convolution

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Accuracy verification of sulfur dioxide data based on ultraviolet hyperspectral solar radiometer observations 3

Accuracy verification of sulfur dioxide data based on ultrav...

引用

3rd International Conference on Environmental Remote Sensing and Geographic information Technology, ERSGIT 2024

作者： Zeng, Hao Wang, Shun Xun, Lina The Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Electrical Engineering and Automation Anhui University Hefei China

ISBN: (纸本)9781510690219

One of the primary air pollutants that has a detrimental effect on both the environment and human health is sulfur dioxide. The ecosystem and climate greatly depend on the high-precision monitoring of sulfur dioxide. In this study, SO2 ground-based data in Xi'an and Hangzhou were calculated using the UV continuous spectral inversion method, and the accuracy was confirmed using OMI satellite data that had undergone bilinear spatial interpolation. Although there are still some discrepancies in the comparative analysis results, the results indicate a good correlation between the ground-based measurement results of the UV hyperspectral solar radiometer and OMI data products;the correlation numbers are 0.938 and 0.941, respectively, and the relative errors are roughly 10%. The ultraviolet hyperspectral solar radiometer can complement this study's findings with accuracy and is a valuable tool for environmental monitoring. © 2025 SPIE.

关键词： Air quality

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Sparsity-aware Subband Adaptive Filtering in Impulsive Interferences 7

Sparsity-aware Subband Adaptive Filtering in Impulsive Inter...

引用

7th IEEE International Conference on Electronic information and Communication Technology, ICEICT 2024

作者： Gong, Zhikai Li, Yingsong Pang, Baohe Li, Xueyan Xiao, Wudang Li, Liping Zlatanov, Nikola Harbin Engineering University College of Information and Communication Engineering Harbin150001 China Ministry of Education Anhui University Key Laboratory of Intelligent Computing and Signal Processing China Innopolis University Faculty of Computer and Engineering Sciences Russia

ISBN: (纸本)9798350384437

In this paper, we propose two new subband adaptive filtering (SAF) algorithms based on the cost function of the logistic distance metric cost function and use the proportionate proximal gradient algorithm to exploit the sparsity of the system fully. Compared with prior works, the proposed algorithms can handle many different situations better. Through computer simulations, we prove that the algorithm performs excellently in sparse systems disturbed by impulse noises. The algorithm can be used in areas like system identifications. © 2024 IEEE.

关键词： Adaptive filtering

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Research on intelligent traffic pedestrian detection algorithm based on improved YOLOv8 24

Research on intelligent traffic pedestrian detection algorit...

引用

2024 2nd International Conference on Internet of Things and Cloud computing Technology, IoTCCT 2024

作者： Yue, Yurong Pan, Lihui Shan, Wei School of Physics and Electronic Information Huaibei Normal University Huaibei China Anhui Provincial Key Laboratory of Intelligent Computing and Application Huaibei China

ISBN: (纸本)9798400710148

Aiming at the problem that the pedestrian detection effect of illumination change, occlusion and different postures is not good in intelligent traffic scene, an optimized YOLOv8 is proposed to enhance its pedestrian detection ability. Based on YOLOv8, Coordinate Attention (CoordAtt) is introduced into the backbone network to enhance the sensitivity of the model to pedestrian location information and improve the detection accuracy. On the public test benchmark of Caltech Pedestrian Dataset, compared with the baseline algorithm, the proposed algorithm improves mAP0.5 by 1.3%, mAP0.5: 0.95 by 0.3%, and LAMR by 1.8%. Compared with the popular algorithm, mAP0.5 and mAP0.5: 0.95 are as high as 0.875 and 0.543 respectively, and LAMR is as low as 0.286, which is better than the popular algorithm. The algorithm has been tested to show that the accuracy of excellent performance detection has been significantly improved, and the phenomenon of missed detection has been greatly reduced, which can serve the intelligent transportation more effectively and reduce the potential safety hazards caused by missed detection. © 2024 Copyright held by the owner/author(s).

关键词： CoordAtt

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