2022 IEEE International Conference on Networking, Sensing and Control (ICNSC)最新文献_第7页

Effective-aggregation Graph Convolutional Network for Imbalanced Classification 不平衡分类的有效聚合图卷积网络

2022 IEEE International Conference on Networking, Sensing and Control (ICNSC) Pub Date : 2022-12-15 DOI: 10.1109/ICNSC55942.2022.10004069

Kefan Wang, Jing An, Qiaoyan Kang

{"title":"Effective-aggregation Graph Convolutional Network for Imbalanced Classification","authors":"Kefan Wang, Jing An, Qiaoyan Kang","doi":"10.1109/ICNSC55942.2022.10004069","DOIUrl":"https://doi.org/10.1109/ICNSC55942.2022.10004069","url":null,"abstract":"Classification is a common task and can be achieved by learning a predictive model from a labeled training dataset. However, the imbalanced data distribution makes the model tend to favor the majority class, which reduces the classification performance. Unlike traditional classification models, graph convolutional networks (GCNs) can extract useful feature information from unlabeled data. In this paper, a novel framework for imbalanced classification named effective-aggregation graph convolutional network (EGCN) is proposed. First, a graph generator constructs graph-structured data using both labeled and unlabeled data. Then, an aggregation control unit (ACU) is performed to improve the effectiveness of aggregation. ACU uses local estimation density to limit the aggregation of inter-class edges from a local perspective, and it enhances the aggregation of the minority class from a global perspective based on the imbalance ratio. Finally, the prediction results are obtained by a graph convolutional network. Experimental results on several real-world datasets show that EGCN has promising performance.","PeriodicalId":230499,"journal":{"name":"2022 IEEE International Conference on Networking, Sensing and Control (ICNSC)","volume":"278 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134308615","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: 2

Green scheduling optimization for flexible job shops considering multiple states of machines 考虑机器多状态的柔性作业车间绿色调度优化

2022 IEEE International Conference on Networking, Sensing and Control (ICNSC) Pub Date : 2022-12-15 DOI: 10.1109/ICNSC55942.2022.10004104

Liuya Xu, Zhengchao Liu, Chunrong Pan

{"title":"Green scheduling optimization for flexible job shops considering multiple states of machines","authors":"Liuya Xu, Zhengchao Liu, Chunrong Pan","doi":"10.1109/ICNSC55942.2022.10004104","DOIUrl":"https://doi.org/10.1109/ICNSC55942.2022.10004104","url":null,"abstract":"With the development of green production and industrial upgrading, the traditional production method of heavy manufacturing industry is in urgent need to change. Against the background that the energy structure cannot be changed in a short time, reasonable scheduling optimization is an effective solution to improve the production efficiency and energy utilization efficiency of enterprises. In the actual processing environment of the surveyed enterprises, the machines can have many different states during operation. These different states greatly increase the flexibility and complexity of the manufacturing shop, and the previous optimization methods are not suitable for this kind of manufacturing environment. For this reason, a multi-objective optimization model of flexible job shop scheduling considering multiple states of machines is proposed. Then, a two-stage optimization method is proposed for optimization. In the first stage, an improved genetic algorithm is proposed to solve the model. In the second stage, the green scheduling heuristic strategy is adopted to optimize the machine states. Finally, the feasibility of the model and the effectiveness of the solution method of this paper are verified by the optimization of practical cases.","PeriodicalId":230499,"journal":{"name":"2022 IEEE International Conference on Networking, Sensing and Control (ICNSC)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123674779","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

Distributed-Particle-Swarm-Optimization-Incorporated Second-order Latent Factor Model 基于分布式粒子群优化的二阶潜在因子模型

2022 IEEE International Conference on Networking, Sensing and Control (ICNSC) Pub Date : 2022-12-15 DOI: 10.1109/ICNSC55942.2022.10004102

Jialiang Wang, Yurong Zhong, Weiling Li

引用次数: 0

Accurate Occupational Pneumoconiosis Staging with Imbalanced Data 基于不平衡数据的职业性尘肺准确分期

2022 IEEE International Conference on Networking, Sensing and Control (ICNSC) Pub Date : 2022-12-15 DOI: 10.1109/ICNSC55942.2022.10004094

Kaiguang Yang, Ye Wang, Qianhao Luo, Xin Liu, Weiling Li

引用次数: 0

Detection of Face Mask Wearing for COVID-19 Protection based on Transfer Learning and Classic CNN Model 基于迁移学习和经典CNN模型的COVID-19防护口罩佩戴检测

2022 IEEE International Conference on Networking, Sensing and Control (ICNSC) Pub Date : 2022-12-15 DOI: 10.1109/ICNSC55942.2022.10004063

Yingzhu Han, Chuyi Dai, Ding Liu

{"title":"Detection of Face Mask Wearing for COVID-19 Protection based on Transfer Learning and Classic CNN Model","authors":"Yingzhu Han, Chuyi Dai, Ding Liu","doi":"10.1109/ICNSC55942.2022.10004063","DOIUrl":"https://doi.org/10.1109/ICNSC55942.2022.10004063","url":null,"abstract":"In 2020, COVID-19 swept the world. To prevent the spread of the outbreak, it is crucial to ensure that everyone wears a mask during daily travel and in public places. However, relying on human inspection alone is inevitably negligent and there is a potential risk of cross-contamination between people. Automated detection by means of cameras and artificial intelligence becomes a technical solution. By training convolutional neural networks, image recognition can be implemented and image classification can be performed as a solution to the target mask-wearing detection problem. To this end, in this thesis, three typical convolutional neural network architectures, VGG-16, Inception V3, and DenseNet-121, are used as models based on deep learning to investigate the mask-wearing detection problem by using transfer learning ideas. By building six different models and comparing the performance of different typical network architectures on the same dataset using two transfer learning methods, feature extraction and fine-tuning, we can conclude that DenseNet-121 is the typical architecture with the best performance among the three networks, and fine-tuning has better transfer ability than feature extraction in solving the target mask wearing detection problem.","PeriodicalId":230499,"journal":{"name":"2022 IEEE International Conference on Networking, Sensing and Control (ICNSC)","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127136892","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: 1

Optimal Data Allocation in the Environment of Edge and Cloud Servers 边缘和云服务器环境下的数据优化分配

2022 IEEE International Conference on Networking, Sensing and Control (ICNSC) Pub Date : 2022-12-15 DOI: 10.1109/ICNSC55942.2022.10004065

Chengyu Peng, Haibin Zhu, Linyuan Liu, R. Grewal

{"title":"Optimal Data Allocation in the Environment of Edge and Cloud Servers","authors":"Chengyu Peng, Haibin Zhu, Linyuan Liu, R. Grewal","doi":"10.1109/ICNSC55942.2022.10004065","DOIUrl":"https://doi.org/10.1109/ICNSC55942.2022.10004065","url":null,"abstract":"With the rise in popularity of cloud computing, there is a growing trend toward the storage of data in a cloud environment. However, there is a significant increase in the risk of privacy information leakage, and users could face serious challenges as a result of data leakage. In this paper, we propose an allocation scheme for the storage of data in a collaborative edge-cloud environment, with a focus on enhanced data privacy. Specifically, we first divide the datasets by fields to eliminate as much as possible the correlation between the leaked data. We then evaluate the sensitivity of the data and server trust to calculate the degree of fitting between them and combine the results with the performance score to obtain a server qualification value for the stored fields. Several constraints are also specified, and the E-CARGO model is used to formalize the problem. Based on the qualification value, we can find the optimal allocation using the IBM ILOG CPLEX Optimization (CPLEX) Package. In our experiments, our proposed solution allows the data to be stored in servers that better suit their requirements, while reducing the user overhead.","PeriodicalId":230499,"journal":{"name":"2022 IEEE International Conference on Networking, Sensing and Control (ICNSC)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127373371","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: 1

Event-Triggered Energy Optimization of Wireless Sensor Networks 事件触发的无线传感器网络能量优化

2022 IEEE International Conference on Networking, Sensing and Control (ICNSC) Pub Date : 2022-12-15 DOI: 10.1109/ICNSC55942.2022.10004164

Lu Liu, Ruizhuo Song, Qinglai Wei

引用次数: 0

Constraint Programming for a Novel Integrated Optimization of Blocking Job Shop Scheduling and Variable-Speed Transfer Robot Assignment 阻塞作业车间调度与变速搬运机器人分配的约束规划集成优化

2022 IEEE International Conference on Networking, Sensing and Control (ICNSC) Pub Date : 2022-12-15 DOI: 10.1109/ICNSC55942.2022.10004158

Xingyang Li, J. Fu, Zixi Jia, Ziyan Zhao, Siyi Li, Shixin Liu

{"title":"Constraint Programming for a Novel Integrated Optimization of Blocking Job Shop Scheduling and Variable-Speed Transfer Robot Assignment","authors":"Xingyang Li, J. Fu, Zixi Jia, Ziyan Zhao, Siyi Li, Shixin Liu","doi":"10.1109/ICNSC55942.2022.10004158","DOIUrl":"https://doi.org/10.1109/ICNSC55942.2022.10004158","url":null,"abstract":"Blocking job shop scheduling problems are common in industrial environments. Various existing studies tackle them to enhance the production efficiency of job shops with machine blocking properties. In the environment of intelligent manufacturing, robots are commonly used to transfer the jobs to be processed among different processes. However, no previous work considers the integrated optimization of blocking job shop scheduling and transfer robot assignment. Facing the new and key demand of production scheduling, this work considers a novel blocking job shop scheduling problem with transfer robots whose speed varies with or without cargo load. It is first formulated by using constraint programming as a baseline model. By analyzing the characteristics of both the considered problem and baseline model this work proposes an improved constraint programming model. Numerous experiments on an adapted benchmark dataset show that the improved constraint programming model can well solve the concerned problem. Comparing with a baseline model, it can greatly enhance the solution efficiency and accuracy. Its great performance shows its high potential to be used in practical industrial scenarios.","PeriodicalId":230499,"journal":{"name":"2022 IEEE International Conference on Networking, Sensing and Control (ICNSC)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129671316","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: 1

A review of observability issues in hospital information system 医院信息系统可观察性问题综述

2022 IEEE International Conference on Networking, Sensing and Control (ICNSC) Pub Date : 2022-12-15 DOI: 10.1109/ICNSC55942.2022.10004053

Haitao Song, Hongyu Ji, Ye Yu, Bing Xie

{"title":"A review of observability issues in hospital information system","authors":"Haitao Song, Hongyu Ji, Ye Yu, Bing Xie","doi":"10.1109/ICNSC55942.2022.10004053","DOIUrl":"https://doi.org/10.1109/ICNSC55942.2022.10004053","url":null,"abstract":"Observability is an important property of complex system. Achieving good system observability can help reveal information about the system's state and structure, providing great convenience to the operation and maintenance of the system. Moreover, observability makes the system more efficient in performance management, troubleshooting and updating. Observability means better user experience, less burden of operation and maintenance, and it helps save cost of dealing with system failures. The implementation and optimization of system observability in different scenarios have been heated topics since the concept was introduced. Importantly, hospital information system(HIS) is an infrastructure in the operation of modern public health institutions. HIS has many functions such as hospital management, patient medical information management and decision-making. Therefore, maintaining the normal and stable operation of HIS has far-reaching social and livelihood significance. In this paper, we take HIS as a scenario and discuss the issues related to the implementation of observability in HIS based on Artificial Intelligence for IT Operations(AIOps) and microservices architecture(MSA) by searching and summarizing different dimensions of the literature. In addition, focusing on some specific applications and service scenarios we analyze the potential observability requirements and provide possible solution ideas.","PeriodicalId":230499,"journal":{"name":"2022 IEEE International Conference on Networking, Sensing and Control (ICNSC)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129684302","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: 1

Mixed-integer linear programming for enterprise's inventory pledge financing decision 企业库存质押融资决策的混合整数线性规划

2022 IEEE International Conference on Networking, Sensing and Control (ICNSC) Pub Date : 2022-12-15 DOI: 10.1109/ICNSC55942.2022.10004127

Junheng Cheng, Yanhong Lin, Xiaoyu He

引用次数: 0