2nd International Conference on Digital Society and Intelligent Systems (DSInS 2022)最新文献_第8页

Design of engineering quality inspection and evaluation system 工程质量检验评定体系设计

2nd International Conference on Digital Society and Intelligent Systems (DSInS 2022) Pub Date : 2023-04-03 DOI: 10.1117/12.2673445

Yanjun Zhang, Yiyan Zhuang, Zhenzhao Zhang, Yong-Qiang Yao

{"title":"Design of engineering quality inspection and evaluation system","authors":"Yanjun Zhang, Yiyan Zhuang, Zhenzhao Zhang, Yong-Qiang Yao","doi":"10.1117/12.2673445","DOIUrl":"https://doi.org/10.1117/12.2673445","url":null,"abstract":"With the continuous development of construction projects, people have higher and higher requirements for project quality. Project quality inspection is the basis for measuring whether the project meets the construction standards, and a qualified project quality inspection and evaluation system can play an important role in the full-cycle inspection and management of project quality and supervising enterprises to regulate construction. However, today's engineering quality inspection has problems such as unclear assessment criteria, unintuitive data and slow processing speed, leading to a decrease in the authority of engineering quality inspection, inaccurate assessment and a significant decrease in public trust in quality inspection parties. Therefore, this paper adopts a new data sampling and strict analysis and evaluation, and researches and designs an engineering quality inspection and evaluation system, which is conducive to improving the supervision and management of engineering quality, facilitating engineering quality inspection, and thus reducing construction costs and enhancing the credibility of the quality inspection team. In addition, the design of the system effectively guarantees the quality of the project, avoids construction risks, greatly improves construction safety, and brings a positive impact on the healthy and sustainable development of the construction industry.","PeriodicalId":176918,"journal":{"name":"2nd International Conference on Digital Society and Intelligent Systems (DSInS 2022)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121931579","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

Design and application of online performance management system for lightweight enterprises based on J2EE 基于J2EE的轻量级企业在线绩效管理系统的设计与应用

2nd International Conference on Digital Society and Intelligent Systems (DSInS 2022) Pub Date : 2023-04-03 DOI: 10.1117/12.2673393

Jia Xu

引用次数: 0

Dominance relation similarity measure based on fuzzy hypergraph dominance matrix 基于模糊超图优势矩阵的优势关系相似性度量

2nd International Conference on Digital Society and Intelligent Systems (DSInS 2022) Pub Date : 2023-04-03 DOI: 10.1117/12.2673459

Mingcong Dang, Shenglin Geng

引用次数: 0

Detection of false information in environment-based complaint reports based on graph convolution 基于图卷积的环境投诉报告虚假信息检测

2nd International Conference on Digital Society and Intelligent Systems (DSInS 2022) Pub Date : 2023-04-03 DOI: 10.1117/12.2673482

Qingwu Fan, Xiaoning Sun

{"title":"Detection of false information in environment-based complaint reports based on graph convolution","authors":"Qingwu Fan, Xiaoning Sun","doi":"10.1117/12.2673482","DOIUrl":"https://doi.org/10.1117/12.2673482","url":null,"abstract":"To solve the problem of strong subjectivity and low credibility of complaints, a new detection model of false information in environment complaints based on graph convolution was proposed. Firstly, the text of environment complaint is preprocessed: then the word in the complaint text and lexicon are used as nodes, the edges between words are constructed by point mutual information, the edges between text and words are constructed by term frequency-inverse document frequency, and the edges between text and text are constructed by text similarity. The edges between words, text-word relationship and text-text relationship are used to construct the text graph of environmental complaint based on word co-occurrence, text-word relationship and text-text relationship; finally, the node information is passed between nodes through graph convolution, and the coupling between complaint information is used to detect complaint false information. Through designing experiments, the model is compared with the methods of common classification models, and the experimental results show that the model has good performance. It is suitable to be applied in the task of environment-based false complaint detection.","PeriodicalId":176918,"journal":{"name":"2nd International Conference on Digital Society and Intelligent Systems (DSInS 2022)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123856497","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 anti single event transient multi-objective optimization technology based on sensitive flip-flop replacement 基于敏感触发器替换的反单事件瞬态多目标优化技术研究

2nd International Conference on Digital Society and Intelligent Systems (DSInS 2022) Pub Date : 2023-04-03 DOI: 10.1117/12.2673429

Hao Huang, Yuanfu Zhao, Liang Wang, Chunxue Liu, Yan Li

引用次数: 0

One-to-many Image super resolution algorithm based on generative adversarial networks 基于生成对抗网络的一对多图像超分辨算法

2nd International Conference on Digital Society and Intelligent Systems (DSInS 2022) Pub Date : 2023-04-03 DOI: 10.1117/12.2673371

Liu Lin, Jiang Yu

{"title":"One-to-many Image super resolution algorithm based on generative adversarial networks","authors":"Liu Lin, Jiang Yu","doi":"10.1117/12.2673371","DOIUrl":"https://doi.org/10.1117/12.2673371","url":null,"abstract":"Aiming at the issues that the current Generative Adversarial Network (GAN) used for image super-resolution reconstruction is easy to produce false details and the mapping dependence is not flexible enough, a One-to-many Generative Adversarial Network (OTMGAN) based on Enhanced Super Resolution Generative Adversarial Network (ESRGAN) was proposed. First, the model uses one-to-many constraints to allow the estimated patches to dynamically seek the best supervision during training, instead of the one-to-one constraint from low-resolution (LR) images to high-resolution (HR) images, thus improving the loss function of the model. Then, a new region-aware adversarial learning strategy is used to distinguish between flat regions and textured regions, so that the model can adaptively generate more realistic details for textured regions during training. Finally, the experimental consequences of image super resolution reestablishment on the public datasets BSDS100, Set5, Set14 and DIV2K show that the new model is significantly superior to the classical models such as ESRGAN in terms of Peak Signal-to-Noise Ratio (PSNR), Structural Similarity (SSIM), and Learning Perception Image Patch Similarity (LPIPS).","PeriodicalId":176918,"journal":{"name":"2nd International Conference on Digital Society and Intelligent Systems (DSInS 2022)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114589255","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

Fault Diagnosis and trend analysis testing program of TT and C antenna transmission chain TT和C天线传输链故障诊断与趋势分析测试程序

2nd International Conference on Digital Society and Intelligent Systems (DSInS 2022) Pub Date : 2023-04-03 DOI: 10.1117/12.2673440

Lei Guo, Jihui Xu, Weihui He

{"title":"Fault Diagnosis and trend analysis testing program of TT and C antenna transmission chain","authors":"Lei Guo, Jihui Xu, Weihui He","doi":"10.1117/12.2673440","DOIUrl":"https://doi.org/10.1117/12.2673440","url":null,"abstract":"In order to prevent the TT&C antenna from having a significant impact on the aerospace measurement and control work due to the unexpected shutdown of the transmission chain, this paper collects vibration, noise, and rotational speed signals in real time, and obtains the characteristics of the traditional antenna system based on the physical model of the antenna transmission chain (reduction box, motor). After removing the random impact interference in the original vibration signal, the diagnosis can be made by analyzing the gear meshing frequency, meshing frequency multiplier and its variable frequency band of the vibration signal under multiple working conditions (the intervals of the side-band frequencies are equal, all of which are the rotation frequency of the gear shaft). The bearing characteristic frequency is obtained by resonance demodulation, and the fault type is judged according to the characteristic frequency. For the first time, the fault diagnosis and degradation trend analysis of the antenna transmission chain based on the physical model was completed, which solved the problem that the abnormal noise of the servo mechanism could not be clearly distinguished by the post personnel during the operation and maintenance process, and realized intelligent fault diagnosis and prognosis.","PeriodicalId":176918,"journal":{"name":"2nd International Conference on Digital Society and Intelligent Systems (DSInS 2022)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115096725","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

Thermal infrared face image data enhancement method based on deep learning 基于深度学习的热红外人脸图像数据增强方法

2nd International Conference on Digital Society and Intelligent Systems (DSInS 2022) Pub Date : 2023-04-03 DOI: 10.1117/12.2673366

Ruihan Xu, Junnian Wang, Jisi Liu, F. Ni, Bijia Cao

{"title":"Thermal infrared face image data enhancement method based on deep learning","authors":"Ruihan Xu, Junnian Wang, Jisi Liu, F. Ni, Bijia Cao","doi":"10.1117/12.2673366","DOIUrl":"https://doi.org/10.1117/12.2673366","url":null,"abstract":"The high accuracy of deep learning in various computer vision tasks often relies on massive image data, but there is usually not enough image data to complete the task in actual project applications. Aiming at the problem that thermal infrared face images are few and difficult to obtain in the absence of light, this paper proposes a method to generate thermal infrared face images based on color face images to obtain more thermal infrared face image data. This method takes the conditional generative adversarial (CGAN) network as the framework and uses the deep high-resolution network and the Patch Net network as the generator and discriminator to build the network model. By verifying the network model on the two datasets, it can be proved that the proposed method is clearer, and the details of the facial features are more obvious than the thermal infrared face images generated by the traditional image generation methods. Compared with the FID values of the original generation method, the FID values of the generated image using this method were reduced by 136 and 92. Therefore. The unsupervised data augmentation method based on HRNet network as a generator can also be applied to other visual tasks such as object recognition and detection that lack image data.","PeriodicalId":176918,"journal":{"name":"2nd International Conference on Digital Society and Intelligent Systems (DSInS 2022)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122149202","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

Electricity price forecasting model based on MLP-mixer 基于MLP-mixer的电价预测模型

2nd International Conference on Digital Society and Intelligent Systems (DSInS 2022) Pub Date : 2023-04-03 DOI: 10.1117/12.2673665

Ke Gao, Yanan Jiang, Qiaoyu Ma, Chunlei Zhang

引用次数: 0

Research on classroom evaluation system under the mode of educational informationization 教育信息化模式下的课堂评价体系研究

2nd International Conference on Digital Society and Intelligent Systems (DSInS 2022) Pub Date : 2023-04-03 DOI: 10.1117/12.2673369

Linlin Jin

引用次数: 0