2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)最新文献_第10页

Students Performance Monitoring and Customized Recommendation Prediction in Learning Education using Deep Learning 基于深度学习的学习教育中学生表现监测和定制推荐预测

2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) Pub Date : 2023-04-29 DOI: 10.1109/ICDCECE57866.2023.10151286

Vivek Kumar Sharma, A. Goel

{"title":"Students Performance Monitoring and Customized Recommendation Prediction in Learning Education using Deep Learning","authors":"Vivek Kumar Sharma, A. Goel","doi":"10.1109/ICDCECE57866.2023.10151286","DOIUrl":"https://doi.org/10.1109/ICDCECE57866.2023.10151286","url":null,"abstract":"This paper is focused on the development of a student academic result alert system using Short Service Message (SMS). The motivation behind the work was borne out of the numerous problems that students encounter before seeing their results. The issue of checking examination results through notice boards in anxiety has been a challenge from time immemorial. In some cases where results are posted on websites, students will have to pay for internet services to check their grades. Similarly, the privacy that should be upheld with respect to results publishing is not through public display. With these problems in mind, the authors developed a system to deliver students’ results and grades through SMS using a dedicated Application Programming Interface (API). The factfinding methods employed in the work were both primary and secondary methods. Primary method involved the use of questionnaire and observation of documents, while we deployed Object Oriented Analysis and Design Methodology (OOADM) as the design methodology. The software tools used are HTML (Hyper Text Markup Language), PHP (Hypertext PreProcessor) for the front-end and MYSQL for the database solution. The software developed is a highly interactive and has the capability of preventing unauthorized access or mutilation of students’ results, thus maintaining data integrity. It also sends student’s results directly to their phones and that of their sponsors.","PeriodicalId":221860,"journal":{"name":"2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"21 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114125851","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 a Machine Vision-based Image Tracking System for Sports 基于机器视觉的运动图像跟踪系统研究

2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) Pub Date : 2023-04-29 DOI: 10.1109/ICDCECE57866.2023.10151130

Xiaojing Zhang, Jianfeng Jiang

{"title":"Research on a Machine Vision-based Image Tracking System for Sports","authors":"Xiaojing Zhang, Jianfeng Jiang","doi":"10.1109/ICDCECE57866.2023.10151130","DOIUrl":"https://doi.org/10.1109/ICDCECE57866.2023.10151130","url":null,"abstract":"Most of the information perceived by humans is obtained visually, and all the dynamic information in visual information is attractive to people. Along with the rapid development of information technology, network technology and multimedia technology, sports target tracking technology has received more and more attention. Today, intelligent moving target tracking technology has become one of the research hotspots. The aim of this paper is to study a sports image tracking system based on machine vision. OpenCV, an open-source computer visualisation library, is chosen as the implementation tool for the system design, and a system process view and software system hierarchy are planned based on the research content. The KNN-based motion recognition model proposed in this paper was tested and the test results show that the average recall of the KNN action recognition model for this subject is 90.1% under three different lights and the average recall when the cross-merge ratio is greater than 0.5 is 89.1% with some performance. the system functions properly and has a certain performance.","PeriodicalId":221860,"journal":{"name":"2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125863898","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

A Hybrid Particle Swarm Algorithm for Financial Risk Early Warning Optimization 金融风险预警优化的混合粒子群算法

2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) Pub Date : 2023-04-29 DOI: 10.1109/ICDCECE57866.2023.10151072

Yuping Zhu

{"title":"A Hybrid Particle Swarm Algorithm for Financial Risk Early Warning Optimization","authors":"Yuping Zhu","doi":"10.1109/ICDCECE57866.2023.10151072","DOIUrl":"https://doi.org/10.1109/ICDCECE57866.2023.10151072","url":null,"abstract":"Risk early warning is the main content of financial management, however in the risk early warning process, the amount of financial information and early warning means will have an impact on the results, reduce the risk early warning accuracy, and cause the alert result is incorrect. Based on this, this study proposes a hybrid particle swarm algorithm to warn the financial management data risk to increase the level of financial management, and shorten the financial early warning time. Then comprehensive early warning of financial management data is carried out. Finally, continuous monitoring is used to manage risk early warning and output the results of final warning. The results provide the mixed particle swarm algorithm can accurately take the risk early warning, improve the level of risk early warning, as well as accuracy of risk early warning is greater, which is better than the continuous monitoring method. In this study, the hybrid particle swarm optimization algorithm can increase the financial risk early warning accuracy (90%), ensure the integrity of analysis results (85%), and shorten the early warning time, as well as control the early warning time within 20 seconds, so the overall results of hybrid particle swarm optimization algorithm are better than previous early warning algorithms. Therefore, the hybrid particle swarm algorithm can accommodate the early financial warning selection essentials and is advisable for continuous financial management analysis.","PeriodicalId":221860,"journal":{"name":"2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126271608","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

Bangladeshi Traffic Sign Recognition and Classification using CNN with Different Kinds of Transfer Learning through a new (BTSRB) Dataset 通过一个新的(BTSRB)数据集，使用CNN和不同类型的迁移学习对孟加拉国交通标志进行识别和分类

2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) Pub Date : 2023-04-29 DOI: 10.1109/ICDCECE57866.2023.10151254

Md. Abu Sayeed, Md. Saiful Islam, Md. Babul Islam, Piyush Kumar Pareek, Tanbin Islam Rohan

{"title":"Bangladeshi Traffic Sign Recognition and Classification using CNN with Different Kinds of Transfer Learning through a new (BTSRB) Dataset","authors":"Md. Abu Sayeed, Md. Saiful Islam, Md. Babul Islam, Piyush Kumar Pareek, Tanbin Islam Rohan","doi":"10.1109/ICDCECE57866.2023.10151254","DOIUrl":"https://doi.org/10.1109/ICDCECE57866.2023.10151254","url":null,"abstract":"An accident is the cry of a lifetime. The role of traffic signs is most important in preventing or mitigating accidents. In many cases, while driving, traffic signs are not visible in the conventional approach; if traffic sign detection and recognition can alert the driver of important sign guidance ahead, it will help in accident mitigation. Traffic sign recognition plays a monumental role in expert systems, such as traffic assistance driving systems and automatic driving systems. The prime purpose of this paper is to design and identify a computer-based system that can spontaneously detect the direction of a road sign. For this research work, we have created our own dataset, which is called the Bangladeshi Traffic Sign Recognition Benchmark (BTSRB) dataset. The dataset, BTSRB, was created by capturing images from different angles and under different parameters and conditions. A total of 7320 images were collected to create this comprehensive database. This dataset called BTSRB all the images collected from Bangladesh. In this paper, we used five different types of models (CNN, Inception V3, MobileNetV2, ResNet50, and VGG16), which are pre-trained on the ImageNet dataset. Later, we finetuned the pre-trained model and used transfer learning. The main challenge of this research is collecting datasets from a country like Bangladesh, where no recognized dataset is available. When compared to another model, the accuracy of this model is greater than 91%. This paper emphasizes the significance of traffic sign recognition in expert systems and the necessity for a well-established dataset in nations where such resources are not readily available.","PeriodicalId":221860,"journal":{"name":"2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126762148","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

Novel Model of Product Sales in Financial and Trade Activities Participation based on the Variation Coefficient Method 基于变异系数法的金融贸易活动参与中产品销售的新模型

2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) Pub Date : 2023-04-29 DOI: 10.1109/ICDCECE57866.2023.10151010

Lei-Yu Wu

{"title":"Novel Model of Product Sales in Financial and Trade Activities Participation based on the Variation Coefficient Method","authors":"Lei-Yu Wu","doi":"10.1109/ICDCECE57866.2023.10151010","DOIUrl":"https://doi.org/10.1109/ICDCECE57866.2023.10151010","url":null,"abstract":"The trade of cultural products is a new industry arising from the big background of economic globalization, and it is of strong permeability, wide cross-industry, and relatively intensive knowledge. It stands at the top of the commodity industry chain, is gradually recognized and cherished by people. Its development is also one of the obvious signs to measure the regional competitiveness. In view of the corresponding evaluation index of the sales route of cultural products in financial and trade activities participation, the study carries out the comprehensive weighting, and optimizes the results of the weighting based on the variation coefficient method. The importance between the subjective weight and objective weight is verified according to the instance data and the operating income margin of cultural products is predicted. The results show that this method takes full account of the relative variation range of the original data, and realizes the dynamic weighting value of the index, which greatly reduces the influence of the subjective factors. The network microstructure analysis results based on the node influence and node instability under time windows display that the partition characteristic of the index network weakens in the financial crisis period, and the network’s community structure evolves smoothly in the financial stable period. These results provide cases and references for further empirical researches on the correlations of financial markets, also are helpful for speeding up the opening process of the domestic capital market and the prevention of international financial market risks.","PeriodicalId":221860,"journal":{"name":"2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123846763","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

Enhanced Video Streaming Based Computing Encoder for Digital Visual Processing 基于增强型视频流的数字视觉处理计算编码器

2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) Pub Date : 2023-04-29 DOI: 10.1109/ICDCECE57866.2023.10150486

T. Kumar, Amita Shukla

{"title":"Enhanced Video Streaming Based Computing Encoder for Digital Visual Processing","authors":"T. Kumar, Amita Shukla","doi":"10.1109/ICDCECE57866.2023.10150486","DOIUrl":"https://doi.org/10.1109/ICDCECE57866.2023.10150486","url":null,"abstract":"The rise of video streaming for digital visual processing has been a boon for the industry of visual processing. Video streaming technology has made it easier for companies to capture, analyze, and interpret visual data faster than ever before. It has allowed for the storage and transmission of large amounts of visual data at high speeds, providing businesses with the ability to process and interpret this data in real-time. Video streaming technology can be used in a wide variety of applications, including facial recognition, 3D mapping, and object recognition. By streaming video data, companies can quickly and accurately identify individuals, recognize objects, and track movement. This technology can also be used in security applications, such as surveillance and monitoring, as well as in medical imaging, such as MRI and CT scans. Video streaming technology has also allowed companies to create more efficient visual processing systems. The streaming video data can be used to automate the process of image recognition and object classification. This has allowed companies to reduce the amount of time and effort needed to interpret visual data. Additionally, streaming video data can be used to create virtual reality experiences, providing users with an immersive experience when viewing digital images.","PeriodicalId":221860,"journal":{"name":"2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128660617","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

Analysis of The Various Techniques Used for Breast Segmentation from Mammograms 从乳房x光片中分割乳房的各种技术分析

2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) Pub Date : 2023-04-29 DOI: 10.1109/ICDCECE57866.2023.10150579

Athira K S, Janaki Peruvamba Dharmarajan, Vijaykumar D K, Nagesh Subbanna

引用次数: 0

Design and Implementation of Digital Book Recommendation Platform Based on Data Mining Visualization Technology 基于数据挖掘可视化技术的数字图书推荐平台的设计与实现

2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) Pub Date : 2023-04-29 DOI: 10.1109/ICDCECE57866.2023.10150633

Xiaoyu Wang, Heng Wang

{"title":"Design and Implementation of Digital Book Recommendation Platform Based on Data Mining Visualization Technology","authors":"Xiaoyu Wang, Heng Wang","doi":"10.1109/ICDCECE57866.2023.10150633","DOIUrl":"https://doi.org/10.1109/ICDCECE57866.2023.10150633","url":null,"abstract":"The rapid development of Internet technology in the information age incurs serious problems of overloaded network data resources and complicated operation of website pages due to their dynamics and multi-structural operation patterns. Consequently, information resources are obtained from certain interfaces ineffectively. The purpose of this paper is to use the association rules in the data mining visualization technology to complete the design and implementation of the digital book recommendation system. With the Apriori book recommendation algorithm, an in-depth analysis is conducted on the reader borrowing data in this system, and the association rule visualization model is optimized in all aspects to produce a visualization model of diamond graphs. Moreover, the digital book recommendation system is established on the basis of professional knowledge and skills, whose system interface is easy for readers to understand and use such that shortening the time required for book borrowing. The readers’ basic demand can be met, with the provision of scientific technical services which further increases the utilization rate of library resources.","PeriodicalId":221860,"journal":{"name":"2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117089503","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

Carbon Productivity Improvement for Manufacturing Based on AI 基于人工智能的制造业碳生产率提升

2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) Pub Date : 2023-04-29 DOI: 10.1109/ICDCECE57866.2023.10150532

Zhuo Wang, Xuhai Wang

{"title":"Carbon Productivity Improvement for Manufacturing Based on AI","authors":"Zhuo Wang, Xuhai Wang","doi":"10.1109/ICDCECE57866.2023.10150532","DOIUrl":"https://doi.org/10.1109/ICDCECE57866.2023.10150532","url":null,"abstract":"Nowadays, with the rapid development of Internet technology, artificial intelligence (AI) technology plays an increasingly important role in addressing global climate issues. How to use AI technology driving manufacturing industry carbon productivity improvement has become a more and more important issue. Taking 27 sub-sectors of manufacturing business in China as the research object, this paper uses the fsQCA method to explore the synergistic effects relationships among factors such as artificial intelligence technology which affect the carbon productivity of the manufacturing business, and finds that there are three upgrade paths to ameliorate the carbon productivity of the manufacturing business driven by AI technology, namely environment-inspired path, energy-driven path and technology-coordinated path. According to the conclusions of this paper, relevant policies and suggestions on artificial intelligence technology to improve manufacturing carbon productivity are put forward. The research findings of this paper are that, through theoretical analysis and empirical tests, the positive effect of AI technology on manufacturing carbon productivity is verified, and the path of AI technology driving manufacturing carbon productivity improvement is found, which provides a theoretical basis for using AI technology to improve manufacturing carbon productivity in the context of Internet plus.","PeriodicalId":221860,"journal":{"name":"2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114278861","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

Breast Cancer Detection Using Deep Learning Technique 利用深度学习技术检测乳腺癌

2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) Pub Date : 2023-04-29 DOI: 10.1109/ICDCECE57866.2023.10150859

Sachin A Urabinahatti, D. Jayadevappa

引用次数: 0