With the rapid development of wireless communication technology, high-frequency band microwaves (e.g., millimeter-wave and terahertz wave) show great potential in the field of high-speed data transmission due to their huge bandwidth resources. However, high-frequency band microwaves are seriously affected by atmospheric attenuation during transmission, especially at long distances, and this attenuation significantly reduces the signal strength and quality. Therefore, the study of accurate modeling of atmospheric attenuation as well as effective compensation techniques is crucial for improving the performance of long-distance transmission of high-frequency band microwaves.
{"title":"Research on Atmospheric Attenuation Compensation Technology of High-Frequency Band Microwave in Long-Distance Transmission","authors":"Yanping Chang, Qibin Li, Jianan Zhang","doi":"10.54097/9a1gdh15","DOIUrl":"https://doi.org/10.54097/9a1gdh15","url":null,"abstract":"With the rapid development of wireless communication technology, high-frequency band microwaves (e.g., millimeter-wave and terahertz wave) show great potential in the field of high-speed data transmission due to their huge bandwidth resources. However, high-frequency band microwaves are seriously affected by atmospheric attenuation during transmission, especially at long distances, and this attenuation significantly reduces the signal strength and quality. Therefore, the study of accurate modeling of atmospheric attenuation as well as effective compensation techniques is crucial for improving the performance of long-distance transmission of high-frequency band microwaves.","PeriodicalId":504530,"journal":{"name":"Frontiers in Computing and Intelligent Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141128701","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}
This paper focuses on the development of the integrated media teaching materials for the Linux network operating system that combines "paper-based teaching materials + electronic loose-leaf pages". It thoroughly analyzes the characteristics and advantages of this teaching material model, elaborating on its application and impact in the teaching process. Additionally, it delves into the challenges encountered during the development and presents corresponding solutions. By conducting this research, we aim to provide valuable references for enhancing the quality and effectiveness of teaching materials, and to facilitate better teaching and learning outcomes in the field of Linux network operating systems, ultimately contributing to the improvement of the overall teaching quality and learning efficiency.
本文重点介绍了 "纸质教材+电子活页 "相结合的Linux网络操作系统综合媒体教材的开发。它深入分析了这种教材模式的特点和优势，阐述了它在教学过程中的应用和影响。此外，还深入探讨了开发过程中遇到的挑战，并提出了相应的解决方案。通过开展这项研究，我们希望为提高教材的质量和效果提供有价值的参考，促进在 Linux 网络操作系统领域取得更好的教学效果，最终为提高整体教学质量和学习效率做出贡献。
{"title":"The Development of the Integrated Media Teaching Materials of Linux Network Operating System with \"Paper-based Teaching Materials + Electronic Loose-leaf Pages\"","authors":"Yingfang Liu, Wanchang Dai, Yuli Wang","doi":"10.54097/g6sgnx39","DOIUrl":"https://doi.org/10.54097/g6sgnx39","url":null,"abstract":"This paper focuses on the development of the integrated media teaching materials for the Linux network operating system that combines \"paper-based teaching materials + electronic loose-leaf pages\". It thoroughly analyzes the characteristics and advantages of this teaching material model, elaborating on its application and impact in the teaching process. Additionally, it delves into the challenges encountered during the development and presents corresponding solutions. By conducting this research, we aim to provide valuable references for enhancing the quality and effectiveness of teaching materials, and to facilitate better teaching and learning outcomes in the field of Linux network operating systems, ultimately contributing to the improvement of the overall teaching quality and learning efficiency.","PeriodicalId":504530,"journal":{"name":"Frontiers in Computing and Intelligent Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141128973","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}
With the rapid development of artificial intelligence technology, technology is empowering transform teaching in the field of education. as smart education models become widespread, the concept of smart ecological education is receiving increased attention. This paper explores how AI is transforming the education ecosystem from the perspectives of student learning, teacher research, school management, home-school collaboration, and teaching evaluation. By examining AI's impact on education from before class, in-class, and post-class perspectives, we reflect on how to construct a smart ecological system.
{"title":"Building a Smart Ecological Education in the AI Era","authors":"Zhenjing Zhou","doi":"10.54097/ag0dxn58","DOIUrl":"https://doi.org/10.54097/ag0dxn58","url":null,"abstract":"With the rapid development of artificial intelligence technology, technology is empowering transform teaching in the field of education. as smart education models become widespread, the concept of smart ecological education is receiving increased attention. This paper explores how AI is transforming the education ecosystem from the perspectives of student learning, teacher research, school management, home-school collaboration, and teaching evaluation. By examining AI's impact on education from before class, in-class, and post-class perspectives, we reflect on how to construct a smart ecological system.","PeriodicalId":504530,"journal":{"name":"Frontiers in Computing and Intelligent Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141128751","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}
Qianru Huang, Qingmei Dong, Yunlong Liu, Deqing Ji, Qinwei Fan
In recent years, Sigma-Pi-Sigma neural network (SPSNN) as a special kind of higher-order neural network has attracted wide attention for its fast convergence speed and good approximation ability. However, an inappropriate number of hidden layer neurons may also lead to model underfitting or overfitting, which affects the performance and generalization ability of the model. Therefore, we propose a Sigma-Pi-Sigma neural network with graph regularity by adding a graph regularity term to the network. The results show that the proposed algorithm performs well in terms of training accuracy, testing accuracy and efficiency.
{"title":"A Sigma-Pi-Sigma Neural Network Model with Graph Regularity Term","authors":"Qianru Huang, Qingmei Dong, Yunlong Liu, Deqing Ji, Qinwei Fan","doi":"10.54097/xwvpkd67","DOIUrl":"https://doi.org/10.54097/xwvpkd67","url":null,"abstract":"In recent years, Sigma-Pi-Sigma neural network (SPSNN) as a special kind of higher-order neural network has attracted wide attention for its fast convergence speed and good approximation ability. However, an inappropriate number of hidden layer neurons may also lead to model underfitting or overfitting, which affects the performance and generalization ability of the model. Therefore, we propose a Sigma-Pi-Sigma neural network with graph regularity by adding a graph regularity term to the network. The results show that the proposed algorithm performs well in terms of training accuracy, testing accuracy and efficiency.","PeriodicalId":504530,"journal":{"name":"Frontiers in Computing and Intelligent Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140252243","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}
In this paper, an advanced ADS-B trajectory filtering method combining Variable Structure Interactive Multi-Modeling (VSIMM) and Reduced Square Root Volume Kalman Filter (RSRCKF) is proposed. After deeply analyzing the operational characteristics of ADS-B system and the application requirements in the field of aviation, this paper aims to improve the accuracy of ADS-B trajectory tracking by this novel filtering method. In order to cope with the tracking performance problems that may be caused by the model set selection in the traditional interacting multi-model algorithm, the Variable Structure Interacting Multi-Model (VSIMM-RSRCKF) algorithm based on the Simplified Square Root Volume Kalman Filtering is adopted in this study for trajectory filtering. By constructing a comprehensive VSIMM model set to describe the dynamic system of maneuvering targets, the filtering method in this paper simplifies the computational process and reduces the computational complexity by squaring the covariance matrix in the iteration, and at the same time ensures the non-negative qualitative nature of the covariance matrix, which effectively avoids the divergence problem that may occur in the filtering process. The goal of this research is to significantly improve the positioning accuracy and reliability of aircraft using the ADS-B system.
{"title":"Study of Trajectory Filtering Methods for ADS-B Based on VSIMM-RSRCKF","authors":"Ruixin Li, Hongping Pu","doi":"10.54097/mmhwth95","DOIUrl":"https://doi.org/10.54097/mmhwth95","url":null,"abstract":"In this paper, an advanced ADS-B trajectory filtering method combining Variable Structure Interactive Multi-Modeling (VSIMM) and Reduced Square Root Volume Kalman Filter (RSRCKF) is proposed. After deeply analyzing the operational characteristics of ADS-B system and the application requirements in the field of aviation, this paper aims to improve the accuracy of ADS-B trajectory tracking by this novel filtering method. In order to cope with the tracking performance problems that may be caused by the model set selection in the traditional interacting multi-model algorithm, the Variable Structure Interacting Multi-Model (VSIMM-RSRCKF) algorithm based on the Simplified Square Root Volume Kalman Filtering is adopted in this study for trajectory filtering. By constructing a comprehensive VSIMM model set to describe the dynamic system of maneuvering targets, the filtering method in this paper simplifies the computational process and reduces the computational complexity by squaring the covariance matrix in the iteration, and at the same time ensures the non-negative qualitative nature of the covariance matrix, which effectively avoids the divergence problem that may occur in the filtering process. The goal of this research is to significantly improve the positioning accuracy and reliability of aircraft using the ADS-B system.","PeriodicalId":504530,"journal":{"name":"Frontiers in Computing and Intelligent Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140252965","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}
This paper delves into the utilization of NFT (Non-Fungible Token) technology for safeguarding and perpetuating Dunhuang culture, with a focus on media safety. It proposes a research methodology aimed at constructing a digital resource library and management platform utilizing this innovative technology. Addressing the imperative requirements of safeguarding work copyrights and establishing robust transaction mechanisms, it introduces the unique features of NFTs, such as non-fungibility and smart contract transactions, in a novel manner. By digitizing cultural artifacts, this approach establishes clear copyright and ownership attributes, facilitating transparent transactions and seamless transfers of ownership. Moreover, the paper explores the integration of NFT technology into the online dissemination and preservation of Dunhuang cultural works, which encompasses the creation of digital exhibitions and online museums. Through collaborative efforts both domestically and internationally, the digital works of Dunhuang culture are poised to garner global exposure, thereby enhancing its international significance. By delving into the future potential of NFT technology for safeguarding and perpetuating Dunhuang culture, this paper seeks to foster better cultural dissemination strategies, ultimately contributing to the enhanced protection, inheritance, and promotion of Dunhuang culture on a global scale.
{"title":"Media Safety Threshold for the Digital Protection and Inheritance of Dunhuang Culture","authors":"Ying Wang","doi":"10.54097/gkh9qh60","DOIUrl":"https://doi.org/10.54097/gkh9qh60","url":null,"abstract":"This paper delves into the utilization of NFT (Non-Fungible Token) technology for safeguarding and perpetuating Dunhuang culture, with a focus on media safety. It proposes a research methodology aimed at constructing a digital resource library and management platform utilizing this innovative technology. Addressing the imperative requirements of safeguarding work copyrights and establishing robust transaction mechanisms, it introduces the unique features of NFTs, such as non-fungibility and smart contract transactions, in a novel manner. By digitizing cultural artifacts, this approach establishes clear copyright and ownership attributes, facilitating transparent transactions and seamless transfers of ownership. Moreover, the paper explores the integration of NFT technology into the online dissemination and preservation of Dunhuang cultural works, which encompasses the creation of digital exhibitions and online museums. Through collaborative efforts both domestically and internationally, the digital works of Dunhuang culture are poised to garner global exposure, thereby enhancing its international significance. By delving into the future potential of NFT technology for safeguarding and perpetuating Dunhuang culture, this paper seeks to foster better cultural dissemination strategies, ultimately contributing to the enhanced protection, inheritance, and promotion of Dunhuang culture on a global scale.","PeriodicalId":504530,"journal":{"name":"Frontiers in Computing and Intelligent Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140254330","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}
With the rapid development of information technology and the increasing public power in universities, it has become necessary to establish a big data supervision platform for public power in universities. Based on the analysis of the existing supervision mechanism of public power in universities, this paper puts forward the necessity of building the big data supervision platform of public power in universities and discusses the key problems and challenges of platform construction. Through the research, we can provide effective technical support for the supervision of public power in universities and promote the transparency and efficiency of public power in universities and colleges.
{"title":"Research on The Construction of Big Data Supervision Platform for Public Power in Universities","authors":"Ying Lou, Wenhui Chen","doi":"10.54097/ysnxzh27","DOIUrl":"https://doi.org/10.54097/ysnxzh27","url":null,"abstract":"With the rapid development of information technology and the increasing public power in universities, it has become necessary to establish a big data supervision platform for public power in universities. Based on the analysis of the existing supervision mechanism of public power in universities, this paper puts forward the necessity of building the big data supervision platform of public power in universities and discusses the key problems and challenges of platform construction. Through the research, we can provide effective technical support for the supervision of public power in universities and promote the transparency and efficiency of public power in universities and colleges.","PeriodicalId":504530,"journal":{"name":"Frontiers in Computing and Intelligent Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140252408","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}
Based on the current level of social development, everyone's demand for cars has increased rapidly. At present, the total number of motor vehicles and drivers in China ranks first in the world. With the rapid development of deep learning, the method of vehicle flow statistics based on video can directly use the existing traffic monitoring camera to realize the detection of vehicles, and some traffic flow detection based on YOLOv1, YOLOv2, YOLOv3, YOLOv4 and other algorithms have problems such as insufficient accuracy and low efficiency. Therefore, this paper proposes to use YOLOv5 to replace the original algorithm to achieve object detection, tracking, and processing. I improve the efficiency of the statistics of the traffic flow.
{"title":"Research on the Detection of Traffic Flow based on Video Images","authors":"Jian He, Wei Teng, Zeyu Zhao, Binche Liu, Bing Qin, Jun Jiang","doi":"10.54097/yna4dt18","DOIUrl":"https://doi.org/10.54097/yna4dt18","url":null,"abstract":"Based on the current level of social development, everyone's demand for cars has increased rapidly. At present, the total number of motor vehicles and drivers in China ranks first in the world. With the rapid development of deep learning, the method of vehicle flow statistics based on video can directly use the existing traffic monitoring camera to realize the detection of vehicles, and some traffic flow detection based on YOLOv1, YOLOv2, YOLOv3, YOLOv4 and other algorithms have problems such as insufficient accuracy and low efficiency. Therefore, this paper proposes to use YOLOv5 to replace the original algorithm to achieve object detection, tracking, and processing. I improve the efficiency of the statistics of the traffic flow.","PeriodicalId":504530,"journal":{"name":"Frontiers in Computing and Intelligent Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140251780","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}
Stripe skeleton line method is one of the commonly used methods to extract the phase information of ESPI stripe maps, and the accuracy of the skeleton line extraction determines the accuracy of the stripe map phase information. In this paper, a fast parallel refinement algorithm for ESPI streak image is proposed for the commonly used ZS and OPTA fast parallel refinement algorithms, which improves the deletion template and retention template. It is experimentally verified that the algorithm can effectively reduce the burr bifurcation and fracture phenomenon of the refined image in ESPI skeleton line extraction, which has good practical value.
{"title":"Research of ESPI Stripe Skeleton Line Extraction Based on Improved Fast Parallel Algorithm","authors":"Yuancheng Zheng, Hongwei Ren","doi":"10.54097/pjxv2f62","DOIUrl":"https://doi.org/10.54097/pjxv2f62","url":null,"abstract":"Stripe skeleton line method is one of the commonly used methods to extract the phase information of ESPI stripe maps, and the accuracy of the skeleton line extraction determines the accuracy of the stripe map phase information. In this paper, a fast parallel refinement algorithm for ESPI streak image is proposed for the commonly used ZS and OPTA fast parallel refinement algorithms, which improves the deletion template and retention template. It is experimentally verified that the algorithm can effectively reduce the burr bifurcation and fracture phenomenon of the refined image in ESPI skeleton line extraction, which has good practical value.","PeriodicalId":504530,"journal":{"name":"Frontiers in Computing and Intelligent Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140251851","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}
In order to address the issue of small objects being difficult to detect effectively in intelligent surveillance videos, this study proposes an improved scheme for the YOLOv7-tiny algorithm. This scheme integrates the Convolutional Block Attention Module (CBAM) into YOLOv7-tiny, effectively enhancing the model's feature extraction and small object detection capabilities in complex backgrounds, thereby improving the overall detection precision. Experimental evaluations indicate that the improved algorithm shows enhanced performance in specific small object detection tasks, achieving an accuracy of 85.6%, a recall rate of 85.2%, and a mean average precision (mAP) of 90.2%. These results demonstrate the effectiveness and practical value of the improved scheme in enhancing the performance of YOLOv7-tiny in small object detection tasks.
{"title":"Research on Improved Algorithm for Small Object Detection in Intelligent Surveillance Video based on YOLOv7","authors":"Zhiwei Wang, Min Wang","doi":"10.54097/ehvf7754","DOIUrl":"https://doi.org/10.54097/ehvf7754","url":null,"abstract":"In order to address the issue of small objects being difficult to detect effectively in intelligent surveillance videos, this study proposes an improved scheme for the YOLOv7-tiny algorithm. This scheme integrates the Convolutional Block Attention Module (CBAM) into YOLOv7-tiny, effectively enhancing the model's feature extraction and small object detection capabilities in complex backgrounds, thereby improving the overall detection precision. Experimental evaluations indicate that the improved algorithm shows enhanced performance in specific small object detection tasks, achieving an accuracy of 85.6%, a recall rate of 85.2%, and a mean average precision (mAP) of 90.2%. These results demonstrate the effectiveness and practical value of the improved scheme in enhancing the performance of YOLOv7-tiny in small object detection tasks.","PeriodicalId":504530,"journal":{"name":"Frontiers in Computing and Intelligent Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140252386","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}
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