2023 IEEE 6th Information Technology,Networking,Electronic and Automation Control Conference (ITNEC)最新文献_第9页

Mean-gradient based two-dimensional histogram image segmentation algorithm in polar coordinate system 极坐标下基于均值梯度的二维直方图图像分割算法

2023 IEEE 6th Information Technology,Networking,Electronic and Automation Control Conference (ITNEC) Pub Date : 2023-02-24 DOI: 10.1109/ITNEC56291.2023.10082347

Tingting Shen, Yi Wei, Lishou Liu

{"title":"Mean-gradient based two-dimensional histogram image segmentation algorithm in polar coordinate system","authors":"Tingting Shen, Yi Wei, Lishou Liu","doi":"10.1109/ITNEC56291.2023.10082347","DOIUrl":"https://doi.org/10.1109/ITNEC56291.2023.10082347","url":null,"abstract":"Traditional two-dimensional histogram image segmentation algorithms are susceptible to noise interference, poor segmentation accuracy and huge computational effort to find the best threshold. To solve these problems, this paper proposes a two-dimensional histogram image segmentation algorithm based on mean-gradient in-formation in polar coordinate system. Based on the traditional two-dimensional histogram, the image gradient information is introduced, and the mean and gradient values of the neighbouring pixels of the image are selected to form a two-dimensional histogram to increase the noise immunity and improve the segmentation accuracy. In addition, this paper maps the pixel points from the right-angle coordinate system to the polar coordinate system, and through the processing of noise and boundary points, the image pixel points are concentrated around 90°, so that the threshold segmentation can be performed only by the polar diameter information in the polar coordinate system, which greatly shortens the running time. Experimental results show that the algorithm improves segmentation accuracy and running speed in the case of more severe noise.","PeriodicalId":218770,"journal":{"name":"2023 IEEE 6th Information Technology,Networking,Electronic and Automation Control Conference (ITNEC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129619763","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Research on PID Parameter Tuning Method of Brushless DC Motor with ITAE Index 基于ITAE指标的无刷直流电动机PID参数整定方法研究

2023 IEEE 6th Information Technology,Networking,Electronic and Automation Control Conference (ITNEC) Pub Date : 2023-02-24 DOI: 10.1109/ITNEC56291.2023.10082641

Wei Xu, Xikai Yue, Shuai Yin, Hao Wang, Shuke Zhang

引用次数: 1

A Hybrid Variable Neighborhood Search Algorithm on Routing and Scheduling for Truck-Assisted Multi-Drone Parcel Delivery 基于混合变量邻域搜索的卡车辅助多无人机包裹递送路径与调度算法

2023 IEEE 6th Information Technology,Networking,Electronic and Automation Control Conference (ITNEC) Pub Date : 2023-02-24 DOI: 10.1109/ITNEC56291.2023.10082608

Meng Cai, Hongyan Qian

引用次数: 0

Design and implementation of intelligent curtain control system 智能窗帘控制系统的设计与实现

2023 IEEE 6th Information Technology,Networking,Electronic and Automation Control Conference (ITNEC) Pub Date : 2023-02-24 DOI: 10.1109/ITNEC56291.2023.10082317

Linze Shen, Guoqin Zhang, Disheng Luo, Jinyuan Zhang, Zhichao Pei, Yuxin Fang

引用次数: 0

Classification of Galaxy Morphology Based on Multi-Channel Deep Residual Networks 基于多通道深度残差网络的星系形态分类

2023 IEEE 6th Information Technology,Networking,Electronic and Automation Control Conference (ITNEC) Pub Date : 2023-02-24 DOI: 10.1109/ITNEC56291.2023.10082415

Ying He, Yanxia Zhang, Shuxin Chen, Yue Hu

引用次数: 0

An Improved Feature-Based Visual Slam Using Semantic Information 基于语义信息的改进特征视觉Slam

2023 IEEE 6th Information Technology,Networking,Electronic and Automation Control Conference (ITNEC) Pub Date : 2023-02-24 DOI: 10.1109/ITNEC56291.2023.10082109

Songyu Ma, Huawei Liang, Hanqi Wang, Tiejuan Xu

{"title":"An Improved Feature-Based Visual Slam Using Semantic Information","authors":"Songyu Ma, Huawei Liang, Hanqi Wang, Tiejuan Xu","doi":"10.1109/ITNEC56291.2023.10082109","DOIUrl":"https://doi.org/10.1109/ITNEC56291.2023.10082109","url":null,"abstract":"The traditional visual slam method for feature extraction is single and has poor robustness. This paper proposes an improved feature-based SLAM (Simultaneous localization and mapping) by adding weights to the features of objects matching the same semantic category and incorporating semantic information into loop closure detection. The basic idea is to use the deep neural network YOLOV5 to classify things, associate feature points with objects appearing in the bounding box, and thus assign the feature points to the semantic labels of these objects. In the feature matching process of the SLAM algorithm, the matching of feature points with the same semantic label will be weight, which increases the matching of similar features on the same category of objects, and at the same time intefrates semantic information into loop detection to improve the accuracy of loop closure detection. The test results show that the absolute trajectory error of the improved algorithm is more minor, the pose estimation accuracy is higher, and the tracking robustness can be effectively improved.","PeriodicalId":218770,"journal":{"name":"2023 IEEE 6th Information Technology,Networking,Electronic and Automation Control Conference (ITNEC)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116338618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Study on Application of Multi-source Data Fusion Method in Environmental Control of Enclosed Layer House 多源数据融合方法在封闭层屋环境控制中的应用研究

2023 IEEE 6th Information Technology,Networking,Electronic and Automation Control Conference (ITNEC) Pub Date : 2023-02-24 DOI: 10.1109/ITNEC56291.2023.10082074

Hualong Li, Miao Li, K. Zhan, Panpan Guo, Xianwang Liu, Xuanjiang Yang, Zhirun Ma

{"title":"Study on Application of Multi-source Data Fusion Method in Environmental Control of Enclosed Layer House","authors":"Hualong Li, Miao Li, K. Zhan, Panpan Guo, Xianwang Liu, Xuanjiang Yang, Zhirun Ma","doi":"10.1109/ITNEC56291.2023.10082074","DOIUrl":"https://doi.org/10.1109/ITNEC56291.2023.10082074","url":null,"abstract":"The health and laying performance of laying hens are seriously affected by the environment of enclosed layer house. At present, the environmental control system is generally based on single environmental parameters. The interaction among multiple environmental factors has not been comprehensively analyzed, which is difficult to meet the requirements of laying hens' healthy breeding. Therefore, the adaptive weighted fusion algorithm and multi-source data fusion technology were introduced into the environmental monitoring system of enclosed layer house. Firstly, the same kind of data collected by the key environmental monitoring sensors of enclosed layer house are calculated by using group adaptive fusion algorithm. Then, combined with a multi-source data fusion algorithm D-S evidence theory algorithm, the influence of the interaction of environmental parameters is analyzed, so as to improve the accuracy of environmental quality evaluation of layer house. Experiments showed that the application of multi-source data fusion algorithm in layer house environment regulation can provide decision-making results and scientific basis for accurate regulation of layer house environment, which has broad application prospects.","PeriodicalId":218770,"journal":{"name":"2023 IEEE 6th Information Technology,Networking,Electronic and Automation Control Conference (ITNEC)","volume":"94 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125978788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

VTFL: A Blockchain Based Vehicular Trustworthy Federated Learning Framework 基于区块链的车辆可信联邦学习框架

2023 IEEE 6th Information Technology,Networking,Electronic and Automation Control Conference (ITNEC) Pub Date : 2023-02-24 DOI: 10.1109/ITNEC56291.2023.10082698

Aojie Li, Xingyan Chang, Jingxiao Ma, Shousheng Sun, Yantao Yu

{"title":"VTFL: A Blockchain Based Vehicular Trustworthy Federated Learning Framework","authors":"Aojie Li, Xingyan Chang, Jingxiao Ma, Shousheng Sun, Yantao Yu","doi":"10.1109/ITNEC56291.2023.10082698","DOIUrl":"https://doi.org/10.1109/ITNEC56291.2023.10082698","url":null,"abstract":"With the rapid development of 5G and Internet of Vehicle (IoV) technology, vehicles require a mass of data-sharing to ensure the traffic safety and improve user’s driving experience. However, the traditional way of sharing the original data leads to inefficient communication and the risk of privacy leakage when data leaves the vehicle’s local-storage. The recent advances of privacy-preserving Federated Learning (FL) bring a solution to these challenges, which allows to train models locally based on user’s data and only transmit the parameters with the raw data. But the lack of identity management in the dynamic topology of vehicles makes the FL’s training process vulnerable to be attacked by malicious vehicles, which spoilages the accuracy of the global model seriously. Therefore, how to ensure the security of the FL process has become a crucial challenge. In our work, we propose a trustworthy FL framework based on blockchain, which relies on consensus mechanism to ensure safe aggregation of models, and uses digital signatures to ensure the traceability of malicious vehicles and prevent the malicious vehicles from doing harm again. Our experiment results show that the proposed scheme effectively improves the precision of global model in the malicious scene and the efficiency of model convergence.","PeriodicalId":218770,"journal":{"name":"2023 IEEE 6th Information Technology,Networking,Electronic and Automation Control Conference (ITNEC)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124071891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Operation safety analysis of substation main wiring based on new risk assessment model 基于新风险评估模型的变电站主接线运行安全性分析

2023 IEEE 6th Information Technology,Networking,Electronic and Automation Control Conference (ITNEC) Pub Date : 2023-02-24 DOI: 10.1109/ITNEC56291.2023.10082349

Yuanling Wang, Jing Chen, Zhanyuan Tang, Zhihuan An, Zhichao Lu

{"title":"Operation safety analysis of substation main wiring based on new risk assessment model","authors":"Yuanling Wang, Jing Chen, Zhanyuan Tang, Zhihuan An, Zhichao Lu","doi":"10.1109/ITNEC56291.2023.10082349","DOIUrl":"https://doi.org/10.1109/ITNEC56291.2023.10082349","url":null,"abstract":"The safe and stable operation of power system is an important guarantee to maintain the harmonious and stable development of society and improve people's living standard. Substation, as a key part of power system, plays an important role in collecting and distributing electric energy, and its operation condition determines the reliability of power supply and operation risk of regional grid. At present, the traditional evaluation model is often used to analyze the operation safety of substation main wiring. This model has certain limitations, and the evaluation results can not objectively reflect the real operation risk of substation and regional grid, so the results do not have enough reference value. Therefore, this paper firstly constructs the operation safety evaluation index system of power grid operation, and then improves the traditional risk assessment model of substation main wiring, forming a safety analysis method of substation main wiring operation based on the new risk assessment model. The results show that compared with the traditional risk model of substation main wiring, the model used in this paper considers a more comprehensive and scientific scope, and the evaluation results are more conservative, which provides a new idea for the operation risk assessment of substation main wiring.","PeriodicalId":218770,"journal":{"name":"2023 IEEE 6th Information Technology,Networking,Electronic and Automation Control Conference (ITNEC)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124386146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Anomaly Detection of Credit Data based on Sparse Subspace Clustering Undersampling 基于稀疏子空间聚类欠采样的信贷数据异常检测

2023 IEEE 6th Information Technology,Networking,Electronic and Automation Control Conference (ITNEC) Pub Date : 2023-02-24 DOI: 10.1109/ITNEC56291.2023.10082623

Ruyao Sun, Lingling Wang, Jinping Tang, Bo Bi

{"title":"Anomaly Detection of Credit Data based on Sparse Subspace Clustering Undersampling","authors":"Ruyao Sun, Lingling Wang, Jinping Tang, Bo Bi","doi":"10.1109/ITNEC56291.2023.10082623","DOIUrl":"https://doi.org/10.1109/ITNEC56291.2023.10082623","url":null,"abstract":"The promotion of digitalization has brought many emerging risks to the internet finance and other fields. For example, the fraudulent behavior in credit data can be regarded as outliers, which means that outliers themselves have very important significance. However, due to the high dimension of the real data set and the small number of outliers, most anomaly detection algorithms directly based on clustering are not effective, so it is necessary to find a method that can effectively solve the anomaly detection of non-balanced credit data sets in high-dimensional space. This paper detects outliers in credit data based on sparse subspace clustering undersampling, uses it to cluster high-dimensional and unbalanced credit data sets, uses clustering results as undersampling means to construct balanced data sets, and then uses classifier to detect outliers. Finally, the effectiveness of the proposed algorithm in credit data outlier detection is verified by comparative experiments, which makes up for the shortcomings of traditional clustering and high-dimensional space outlier detection algorithms.","PeriodicalId":218770,"journal":{"name":"2023 IEEE 6th Information Technology,Networking,Electronic and Automation Control Conference (ITNEC)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127995541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0