Advances in Computer and Communication最新文献_第4页

Analysis on the Application of New Media Technology in Computer Course Teaching 新媒体技术在计算机课程教学中的应用分析

Advances in Computer and Communication Pub Date : 2023-07-24 DOI: 10.26855/acc.2023.06.010

Hong Jing

{"title":"Analysis on the Application of New Media Technology in Computer Course Teaching","authors":"Hong Jing","doi":"10.26855/acc.2023.06.010","DOIUrl":"https://doi.org/10.26855/acc.2023.06.010","url":null,"abstract":"In recent years, with the rapid development of new media technology, its application in modern society has penetrated into various fields, including the field of education. As one of the core courses of computer science and technology majors, computer course teaching is facing many challenges, such as the traditional teaching method is single, and students' interest in learning is not high. New media technology, with its advantages of rich learning resources and strong interactive learning environment, has brought new possibilities for computer course teaching. New media technologies include social media, mobile Internet, virtual reality, etc., which are characterized by interactivity, immediacy and diversity. By making the use of new media technology, students can provide rich learning resources for computer course teaching. For example, online learning platform can provide rich teaching videos, case analysis, programming practices, etc., so that students can learn anytime and anywhere. Virtual laboratory can simulate the real experimental environment, allowing students to carry out experiments through virtual operation and improve their practical ability. Teaching games can increase students' participation and interest through gamification, and encourage students to actively participate in course learning. This paper explores the application of new media technology in computer course teaching, and hopes that on this basis, the teaching mode of computer course can be continuously optimized.","PeriodicalId":105895,"journal":{"name":"Advances in Computer and Communication","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132138603","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 Computer Development and Application in Network Environment 网络环境下计算机发展与应用分析

Advances in Computer and Communication Pub Date : 2023-07-24 DOI: 10.26855/acc.2023.06.019

Haonan Wang

引用次数: 0

Human-computer Interaction Gesture Control Recognition for High-performance Embedded AI Computing Platform 高性能嵌入式AI计算平台的人机交互手势控制识别

Advances in Computer and Communication Pub Date : 2023-07-24 DOI: 10.26855/acc.2023.06.021

Dongwei Fu

{"title":"Human-computer Interaction Gesture Control Recognition for High-performance Embedded AI Computing Platform","authors":"Dongwei Fu","doi":"10.26855/acc.2023.06.021","DOIUrl":"https://doi.org/10.26855/acc.2023.06.021","url":null,"abstract":"This article mainly introduces a gesture control recognition method based on embedded AI computing platform, which uses infrared cameras and AI processing units to recognize and track gestures. Using infrared cameras as detection tools can achieve low-cost, easy-to-use and other characteristics. In this algorithm, firstly, the Gesture recognition method based on color model is used to convert the color of the input gesture image and extract the corresponding skin color features; Then, by weighting the skin color features, richer color information is obtained; Finally, the recognition of gestures was achieved by calculating the similarity between color features and skin tone features. This article designs a gesture control recognition system based on infrared cameras and AI processing units. This article adopts a deep learning based object detection algorithm. The algo-rithm uses Convolutional Neural Network (CNN) to detect the target, and realizes Gesture recognition and tracking without increasing the hardware cost. In the training process, CNN is used to extract the color features and color information of gesture images for training, while in the testing process, infrared cameras of the same number and size are used to test the trained model. In addition, in order to achieve the characteristics of low cost and ease of use, this paper uses the target detection algorithm based on deep learning to verify the results of Gesture recognition.","PeriodicalId":105895,"journal":{"name":"Advances in Computer and Communication","volume":"137 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122929447","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

Construction of Computer Network Security System in the Era of Big Data 大数据时代计算机网络安全体系的构建

Advances in Computer and Communication Pub Date : 2023-07-24 DOI: 10.26855/acc.2023.06.015

Y. Lin

{"title":"Construction of Computer Network Security System in the Era of Big Data","authors":"Y. Lin","doi":"10.26855/acc.2023.06.015","DOIUrl":"https://doi.org/10.26855/acc.2023.06.015","url":null,"abstract":"Computer network security is one of the important factors affecting the development of computer technology. Analyzing and exploring computer network security in the era of big data is conducive to achieving effective protection of data information. In the era of big data, there are many problems in China's computer network security system, such as information leakage and data tampering. Therefore, it is necessary to analyze the construction of computer network security sys-tem in the context of the big data era, clarify the construction ideas of computer network security system in the big data era, and build a comprehensive computer network security system based on this. With the continuous development and progress of science and technology in our country, we have entered the era of big data. In this context, big data technology is widely applied in various fields. However, at the same time, there have also been some problems, such as data leakage and tampering, which have had a negative impact on the application of big data technology. Therefore, it is necessary to strengthen research on the construction of computer network security system in the context of the big data era. Only in this way can we effectively solve the computer network security issues in the context of China's big data era. The era of big data is an era based on the Internet, with information data as the main resource and content. In the context of the big data era, China's social and economic development has been rapid, which has also driven the development of various industries. Internet technology has been widely applied in various industries. In the context of the big data era, people can obtain various information and knowledge through the internet. For example, a large amount of latest information about a certain industry or field can be retrieved through the internet; Communicate and communicate with others through the internet; You can purchase goods, book services, and more through the internet.","PeriodicalId":105895,"journal":{"name":"Advances in Computer and Communication","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127611357","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 Deep Learning in Natural Language Processing 自然语言处理中的深度学习研究

Advances in Computer and Communication Pub Date : 2023-07-24 DOI: 10.26855/acc.2023.06.018

Zeyi Xu

引用次数: 2

Classification of Crop Disease Images Based on Convolutional Neural Network 基于卷积神经网络的作物病害图像分类

Advances in Computer and Communication Pub Date : 2023-07-24 DOI: 10.26855/acc.2023.06.020

Jian Guo

引用次数: 0

AI’s Ethical Implications: Job Displacement 人工智能的伦理含义:工作取代

Advances in Computer and Communication Pub Date : 2023-07-21 DOI: 10.26855/acc.2023.06.006

Yulin u, Xiangtao Meng, Anqi Li

引用次数: 0

Research on the Application of Artificial Intelligence Platform in Quantitative Investment 人工智能平台在量化投资中的应用研究

Advances in Computer and Communication Pub Date : 2023-07-21 DOI: 10.26855/acc.2023.06.009

Shuo Wen

{"title":"Research on the Application of Artificial Intelligence Platform in Quantitative Investment","authors":"Shuo Wen","doi":"10.26855/acc.2023.06.009","DOIUrl":"https://doi.org/10.26855/acc.2023.06.009","url":null,"abstract":"The purpose of this article is to provide for an in-depth discussion and examination of the application of AI platform in quantitative investment field. First, we introduce the background of the AI platform in quantitative investment as well as its development stage in early, recent and current time. Then in terms of methodology we take “Qlib” as a typical AI platform case to illustrate the impact of the application of AI platform in the development of quantitative investment strategy. To do it first the framework of the platform was sort out in detail with distinctive characteristics of modularization and process management in order to better understand the operation mechanism of the AI platform in the design of quantitative investment strategy. Then a performance evaluation method is introduced to make the comparison between the Qlib with other traditional solutions. The outcome shows that the application of AI platform will effectively shorten the loading time and make the design process more efficient by leveraging the utility of multi-core CPUs as well as making the development process more flexible due to modularization. Finally, we discuss the limitation of the application of AI platform and look forward to the development trend in the future.","PeriodicalId":105895,"journal":{"name":"Advances in Computer and Communication","volume":"18 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139356625","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

Feature Diagnosis of Alzheimer’s Disease Based on Stacking Fusion Algorithm and DBSCAN Clustering 基于堆叠融合算法和DBSCAN聚类的阿尔茨海默病特征诊断

Advances in Computer and Communication Pub Date : 2023-07-21 DOI: 10.26855/acc.2023.06.007

W. Wu, Bin Ma, Jingyi Zhu, Jiajun Huang

{"title":"Feature Diagnosis of Alzheimer’s Disease Based on Stacking Fusion Algorithm and DBSCAN Clustering","authors":"W. Wu, Bin Ma, Jingyi Zhu, Jiajun Huang","doi":"10.26855/acc.2023.06.007","DOIUrl":"https://doi.org/10.26855/acc.2023.06.007","url":null,"abstract":"Alzheimer's disease (AD) is a progressive neurodegenerative disease. It is characterized by a progressive decline in the ability to perform activities of daily living, accompanied by various neuropsychiatric symptoms and behavioral disorders. The disease usually develops progressively in older people, with progressive loss of independent living and death from complications 10 to 20 years after onset. First of all, we eliminate the indicators that the data vacancy accounts for 80% or more of the data volume, and eliminate similar duplicate indicators. Collaborative filtering algorithm and LOF abnormal data detection algorithm are used to process the data and get the original data. The importance of establishing a random forest model to calculate characteristic indexes, and combining Spearman correlation coefficient method to solve the correlation between the characteristics of original data and the diagnosis of Alzheimer's disease. Then divide the data into five categories. XGboost and SVM models with 50% cross-validation in stack fusion are used to classify characteristic indexes, study cognitive behavior and structural characteristics of brain, and design intelligent diagnosis of Alzheimer's disease. And we divided CN, MCI and AD into three categories, and screened the index data in nine categories. Unsupervised classification is carried out by DBSCAN clustering, and three subclasses are further refined into three subclasses by elbow method. Then, according to the classification results, the characteristic indexes and patients were analyzed by single factor, and some indexes were eliminated. The change trend of characteristic indicators with time was studied, and the evolution patterns of different types of diseases with time were obtained by combining descriptive statistics of indicators.","PeriodicalId":105895,"journal":{"name":"Advances in Computer and Communication","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131914706","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

The Application and Development of the Student Society Management System 学生社团管理系统的应用与开发

Advances in Computer and Communication Pub Date : 2023-07-21 DOI: 10.26855/acc.2023.06.008

Z. Wang, Zhaoxi Hua, Wenqing Yao

引用次数: 0