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Application and Analysis of Education and Teaching Mode Based on 5G and Smart Technology 基于5G和智能技术的教育教学模式应用与分析
Pub Date : 2022-01-13 DOI: 10.1155/2022/7861157
Ran Yan
The development of information technology has brought tremendous changes to our country’s education. Based on the 5G + Internet, the article proposes a brand-new intelligent education model and proposes an ST analysis method, which mainly studies the teacher and students in the classroom. Class performance, based on Yebes network, proposed a learning decision method and application. The research results of the article show the following: (1) The article compares the monthly test scores of three variables under two different teaching modes. The results show that the performance of the online teaching mode is generally better than that of the traditional teaching mode, and the performance of the experimental class has increased more, with an average growth score of 4.83, indicating that there are significant differences in students’ learning and cognitive abilities under different teaching models. (2) The article compares the students’ knowledge mastery under two different teaching modes. The results show that under the traditional teaching mode, the students’ knowledge mastery is low, and the complete mastery rate is only 15%. In the network multimedia teaching mode, the students’ knowledge mastery rate has been greatly improved, the complete mastery rate is as high as 45%, and the students’ mastery of knowledge has been extremely improved, indicating that the network multimedia teaching mode can stimulate students’ learning interest more, improve learning efficiency. (3) Studying the differences in the source of curriculum resources of three different types of teachers, and the results show that the proportion of curriculum resources downloaded through the Internet is the largest; in the investigation of the impact of multimedia teaching on the classroom, the cooperation rate of students when multimedia teaching is not used, classroom practice accuracy and classroom completion rate are low, but after using multimedia teaching, students’ cooperation rate and classroom practice accuracy rate have been greatly improved, among which the accuracy rate of the experimental class is as high as 62.4%, and the students’ thinking ability is also good. Great improvement.
信息技术的发展给我国的教育带来了巨大的变化。基于5G +互联网,本文提出了一种全新的智能教育模式,并提出了一种以课堂上的老师和学生为研究对象的ST分析方法。基于Yebes网络,提出了一种学习决策方法及应用。本文的研究结果表明:(1)本文比较了两种不同教学模式下三个变量的月测试成绩。结果表明,网络教学模式的表现普遍优于传统教学模式,实验班的表现提高更多,平均成长分数为4.83,说明不同教学模式下学生的学习和认知能力存在显著差异。(2)比较了两种不同教学模式下学生的知识掌握情况。结果表明,在传统教学模式下,学生对知识的掌握程度较低,完全掌握率仅为15%。在网络多媒体教学模式下,学生的知识掌握率得到了很大的提高,完全掌握率高达45%,学生对知识的掌握程度得到了极大的提高,说明网络多媒体教学模式更能激发学生的学习兴趣,提高学习效率。(3)研究三种不同类型教师的课程资源来源差异,结果表明,通过互联网下载的课程资源比例最大;在对多媒体教学对课堂影响的调查中,不使用多媒体教学时学生的合作率、课堂实践准确率和课堂完成率都较低,但使用多媒体教学后,学生的合作率和课堂实践准确率都有了很大的提高,其中实验班的准确率高达62.4%,学生的思维能力也有了较好的提高。伟大的进步。
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引用次数: 2
A Liquid Democracy Enabled Blockchain-Based Electronic Voting System 基于区块链的流动民主电子投票系统
Pub Date : 2022-01-13 DOI: 10.1155/2022/1383007
Ch. Anwar ul Hassan, Muhammad Hammad, Jawaid Iqbal, Saddam Hussain, Syed Sajid Ullah, Hussain Alsalman, Mogeeb A. A. Mosleh, S. M. Arif
Developing an electronic voting system that meets the practical needs of administrators has been a difficult task for a long time. Now, blockchain technologies solve this problem by providing a distributed ledger with immutable, encrypted, and secure transactions. Distributed ledger technologies are an interesting technological leap in the field of data innovation, transparency, and trustability. In public blockchain, distributed ledger technology is widely used. The blockchain technology can be used in an almost infinite number of ways to benefit from sharing economies. The purpose of this study is to assess how blockchain may be utilized to build electronic voting systems that can be used as a service. The purpose of electronic voting systems is explained in this article, as are the technological and legal limitations of employing blockchain as a service. Then, using blockchain as a foundation, we propose a new electronic voting system that fixes the flaws we observed. In general, this paper evaluates the capabilities of distributed ledger technologies by depicting a contextual investigation in order to fine-tune the process of political election decisions and employing a blockchain-based application that improves security and lowers the cost of conducting nationwide elections.
长期以来,开发满足管理员实际需要的电子投票系统一直是一项艰巨的任务。现在,区块链技术通过提供具有不可变、加密和安全事务的分布式分类账解决了这个问题。分布式账本技术是数据创新、透明度和可信赖性领域的一个有趣的技术飞跃。在公共领域,分布式账本技术得到了广泛的应用。区块链技术可以以几乎无限的方式从共享经济中受益。本研究的目的是评估如何利用区块链来建立可作为服务使用的电子投票系统。本文将解释电子投票系统的目的,以及使用区块链作为服务的技术和法律限制。然后,使用区块链作为基础,我们提出了一个新的电子投票系统,修复了我们观察到的缺陷。总的来说,本文通过描述上下文调查来评估分布式账本技术的能力,以便微调政治选举决策的过程,并采用基于区块链的应用程序来提高安全性并降低进行全国选举的成本。
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引用次数: 8
Research on the Intelligent Assignment Model of Urban Traffic Planning Based on Optimal Path Optimization Algorithm 基于最优路径优化算法的城市交通规划智能分配模型研究
Pub Date : 2022-01-13 DOI: 10.1155/2022/3002923
Yuan Lu, Shengyong Yao, Yifeng Yao
Congestion and complexity in the field of highway transportation have risen steadily in recent years, particularly because the growth rate of vehicles has far outpaced the growth rate of roads and other transportation facilities. To ensure smooth traffic, reduce traffic congestion, improve road safety, and reduce the negative impact of air pollution on the environment, an increasing number of traffic management departments are turning to new scientifically developed technology. The urban road traffic is simulated by nodes and sidelines in this study, which is combined with graph theory, and the information of real-time changes of road traffic is added to display and calculate the relevant data and parameters in the road. On this foundation, the dynamic path optimization algorithm model is discussed in the context of high informationization. Although the improved algorithm’s optimal path may not be the conventional shortest path, its actual travel time is the shortest, which is more in line with users’ actual travel needs to a large extent.
近年来,公路运输领域的拥堵和复杂性稳步上升,特别是因为车辆的增长速度远远超过道路和其他交通设施的增长速度。为了保证交通畅通,减少交通拥堵,提高道路安全性,减少空气污染对环境的负面影响,越来越多的交通管理部门正在转向科学开发的新技术。本研究采用节点和边线模拟城市道路交通,并结合图论,加入道路交通实时变化信息,对道路中相关数据和参数进行显示和计算。在此基础上,讨论了高信息化背景下的动态路径优化算法模型。虽然改进算法的最优路径可能不是传统的最短路径,但其实际出行时间最短,在很大程度上更符合用户的实际出行需求。
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引用次数: 4
Online Teaching Wireless Video Stream Resource Dynamic Allocation Method considering Node Ability 考虑节点能力的在线教学无线视频流资源动态分配方法
Pub Date : 2022-01-13 DOI: 10.1155/2022/4391188
Jingrong Lu, Hongtao Gao
At present, wireless network technology is advancing rapidly, and intelligent equipment is gradually popularized, which rapidly developed the mobile streaming media business. All kinds of mobile video applications have enriched people’s lives by carrying huge traffic randomly. Wireless networks (WNs) are facing an unprecedented burden, which allocates very important wireless video resources. Similarly, in WNs, the network status is dynamic and the terminal is heterogeneous, which causes the traditional video transmission system to fail to meet the needs of users. Hence, Scalable Video Coding (SVC) has been introduced in the video transmission system to achieve bit rate adaptation. However, in a strictly hierarchical traditional computer network, the wireless resource allocation strategy usually takes throughput as the only way to optimize the target, and it is terrible to make more optimizations for scalable video transmission. This article proposed a cross-layer design to enable information to be transmitted between the wireless base station and the video server to achieve joint optimization. To improve users’ satisfaction with video services, the wireless resource allocation problem and the video stream scheduling problem are jointly considered, which keep the optimization space larger. Based on the proposed architecture, we further study the design of wireless resource allocation algorithms and rate-adaptive algorithms for the scenario of multiuser transmission of scalable video in the Long-Term Evolution (LTE) downlink. Experimental outcomes have shown substantial performance enhancement of the proposed work.
当前,无线网络技术突飞猛进,智能设备逐渐普及,使得移动流媒体业务迅速发展。各种移动视频应用随机承载着巨大的流量,丰富了人们的生活。无线网络(WNs)面临着前所未有的负担,它分配了非常重要的无线视频资源。同样,在无线网络中,网络状态是动态的,终端是异构的,这使得传统的视频传输系统无法满足用户的需求。因此,在视频传输系统中引入了可伸缩视频编码(SVC)来实现码率自适应。然而,在严格分层的传统计算机网络中,无线资源分配策略通常以吞吐量作为优化目标的唯一途径,对于可扩展的视频传输进行更多的优化是很糟糕的。本文提出了一种跨层设计,实现无线基站与视频服务器之间的信息传输,实现联合优化。为了提高用户对视频业务的满意度,将无线资源分配问题和视频流调度问题结合起来考虑,使优化空间更大。基于所提出的架构,我们进一步研究了长期演进(LTE)下行链路中多用户可扩展视频传输场景的无线资源分配算法和速率自适应算法的设计。实验结果表明,所提出的工作有实质性的性能提高。
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引用次数: 2
The Path of Film and Television Animation Creation Using Virtual Reality Technology under the Artificial Intelligence 人工智能下运用虚拟现实技术进行影视动画创作的路径
Pub Date : 2022-01-13 DOI: 10.1155/2022/1712929
Xin Liu, Hua Pan
The purpose is to provide a more reliable human-computer interaction (HCI) guarantee for animation works under virtual reality (VR) technology. Inspired by artificial intelligence (AI) technology and based on the convolutional neural network—support vector machine (CNN-SVM), the differences between animation works under VR technology and traditional animation works are analyzed through a comprehensive analysis of VR technology. The CNN-SVM gesture recognition algorithm using the error correction strategy is designed based on HCI recognition. To have better recognition performance, the advantages of depth image and color image are combined, and the collected information is preprocessed including the relations between the times of image training iterations and the accuracy of different methods in the direction of the test set. After experiments, the maximum accuracy of the preprocessed image can reach 0.86 showing the necessity of image preprocessing. The recognition accuracy of the optimized CNN-SVM is compared with other algorithm models. Experiments show that the accuracy of the optimized CNN-SVM has an upward trend compared with the previous CNN-SVM, and the accuracy reaches 0.97. It proves that the designed algorithm can provide good technical support for VR animation, so that VR animation works can interact well with the audience. It is of great significance for the development of VR animation and the improvement of people’s artistic life quality.
目的是为虚拟现实(VR)技术下的动画作品提供更可靠的人机交互(HCI)保障。以人工智能(AI)技术为灵感,基于卷积神经网络支持向量机(CNN-SVM),通过对VR技术的综合分析,分析VR技术下的动画作品与传统动画作品的区别。基于HCI识别,设计了基于纠错策略的CNN-SVM手势识别算法。为了获得更好的识别性能,结合深度图像和彩色图像的优势,对采集到的信息进行预处理,包括图像训练迭代次数与不同方法在测试集方向上的准确率之间的关系。经过实验,预处理后的图像精度最高可达0.86,说明了图像预处理的必要性。将优化后的CNN-SVM识别精度与其他算法模型进行了比较。实验表明,优化后的CNN-SVM与之前的CNN-SVM相比准确率有上升趋势,准确率达到0.97。实践证明,所设计的算法能够为VR动画提供良好的技术支持,使VR动画作品能够与观众进行良好的互动。这对于VR动画的发展和人们艺术生活质量的提高具有重要意义。
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引用次数: 19
Bike-Sharing Fleet Allocation Optimization Based on Demand Gap and Cycle Rebalancing Strategies 基于需求缺口和周期再平衡策略的共享单车车队配置优化
Pub Date : 2022-01-13 DOI: 10.1155/2022/1892836
Jianhua Cao, Wei-Xiong Xu, Wenzheng Wang
In Bike-Sharing System (BSS), the initial number of bikes at station will affect the time interval and the amount of rebalancing, which is usually empirically determined and does not reflect the characteristics of consumer demand in finer time granularity, thus possibly leading to biased conclusions. In this paper, a fleet allocation method considering demand gap is first proposed to calculate the initial number of bikes at each station. Then, taking the number of demand gap periods as the decision variable, an optimization model is built to minimize the total rebalancing amount. Furthermore, the research periods are divided into multiple subcycles, the single-cycle and multicycle rebalancing strategies are presented, and the additional subcycle rebalancing method is introduced to amend the number of bikes between subcycles to decrease the rebalancing amount of the next subcycle. Finally, our methods are verified in effectively decreasing the rebalancing amount in a long-term rebalancing problem.
在共享单车系统(BSS)中,初始站点的自行车数量会影响时间间隔和再平衡量,这通常是经验确定的,不能反映更细时间粒度的消费者需求特征,从而可能导致有偏差的结论。本文首先提出了一种考虑需求缺口的车队分配方法来计算每个站点的初始自行车数量。然后,以需求缺口期数为决策变量,构建以总再平衡量最小为目标的优化模型。将研究周期划分为多个子周期,提出了单周期和多周期再平衡策略,并引入附加子周期再平衡方法来修正子周期之间的自行车数量,以减少下一个子周期的再平衡量。最后,我们的方法在长期再平衡问题中有效地减少了再平衡量。
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引用次数: 0
Remote English Teaching Resource Sharing Based on Internet O2O Model 基于互联网O2O模式的远程英语教学资源共享
Pub Date : 2022-01-13 DOI: 10.1155/2022/1217807
Zuoxun Hou
Aiming at the problems of low success rate, delay, and high communication cost in distance English teaching resource sharing, this paper puts forward a method of distance English teaching resource sharing based on Internet O2O mode. Based on the model of distance English teaching resource sharing, this paper designs four processes: query, reply, resource substitution, and resource sharing optimization. Experimental results show that the proposed method can achieve high success rate of resource sharing, low latency, communication cost, and high transmission efficiency. Therefore, it is an effective method.
针对远程英语教学资源共享存在的成功率低、延迟、沟通成本高等问题,提出了一种基于互联网O2O模式的远程英语教学资源共享方法。基于远程英语教学资源共享模型,设计了查询、回复、资源替代和资源共享优化四个流程。实验结果表明,该方法具有资源共享成功率高、时延低、通信成本低、传输效率高等优点。因此,这是一种有效的方法。
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引用次数: 1
Colour Recognition Algorithm Based on Colour Mapping Knowledge for Wooden Building Image 基于颜色映射知识的木质建筑图像颜色识别算法
Pub Date : 2022-01-12 DOI: 10.1155/2022/1313819
Siyi Jia, Heng Chen
In the cross-media image reproduction technology, the accurate transfer and reproduction of colour between different media are an important issue in the reproduction process, and the colour mapping technology is the key technology to effectively maintain the image details and improve the level of colour reproduction. Wooden structure in the image colour and colour piece is different, the image of each colour of visual perception is not independent, and every colour in the image pixels is affected by the surrounding pixels, but in the process of image map, without thinking of the pixel space, adjacent pixels of mutual influence in particular, do not let a person particularly be satisfied with the resulting map figure. In the process of image processing by traditional colour mapping algorithm, the colour distortion caused by colour component is ignored and the block diagram of colour mapping system is constructed. With the continuous development of mapping recognition algorithms, the maximum and minimum brightness values in the image are mapped to the maximum and minimum brightness values of the display device by linear mapping algorithm according to the flow of the established recognition algorithm. By establishing the colour adjustment method of the colour mapping image, the processing effect of the mapping algorithm is analysed. The results show that the brightness deviation of the image is reduced and the colour resolution is improved by the colour brightness compensation.
在跨媒体图像再现技术中,色彩在不同媒体之间的准确传递和再现是再现过程中的一个重要问题,而色彩映射技术是有效保持图像细节、提高色彩再现水平的关键技术。木结构在图像中的颜色与色块是不同的,图像中的每一种颜色的视觉感知并不是独立的,而且图像中的每一种颜色的像素都受到周围像素的影响,但是在图像映射的过程中,没有考虑到像素的空间,相邻像素的相互影响特别大,不会让人对所得到的地图图形特别满意。传统的色彩映射算法在图像处理过程中忽略了色彩分量引起的色彩失真,构造了色彩映射系统的框图。随着映射识别算法的不断发展,根据所建立的识别算法的流程,通过线性映射算法将图像中的最大和最小亮度值映射到显示设备的最大和最小亮度值。通过建立彩色映射图像的色彩调整方法,分析了该映射算法的处理效果。结果表明,该方法减小了图像的亮度偏差,提高了图像的色彩分辨率。
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引用次数: 0
Toward Piano Teaching Evaluation Based on Neural Network 基于神经网络的钢琴教学评价研究
Pub Date : 2022-01-12 DOI: 10.1155/2022/6328768
Wanshu Luo, Bin Ning
With the rise of piano teaching in recent years, many people participated in the team of learning steel playing. However, expensive piano teaching fees and its unique one-to-one teaching model have caused piano education resources to be very short, so learning piano performance has become a very extravagant event. The factors affecting music performance are varying, and there are many types of their evaluation such as rhythm, expressiveness, music, and style grasp. The computer is used to simulate this evaluation process to essentially identify the mathematical relationship between factors affecting music performance and evaluation indicators. The use of computer multimedia software for piano teaching has become a feasible way to alleviate the contradiction. This paper discusses the implementation method of piano teaching software, the issues of computer piano teaching, the computer teaching as one-way knowledge, and the lack of interaction. The neural network (NN) model is used to evaluate the piano performance and simulate teachers to guide students through their exercise. The performance of the proposed system is tested for the piano music of “Ode to Joy,” which is different from the collection of NN training samples, and is delivered ten times by another piano teacher, student A (piano level 6), and student B (piano level 5).
随着近年来钢琴教学的兴起,很多人参加了学习钢弹的团队。然而,昂贵的钢琴教学费用和其独特的一对一教学模式导致钢琴教育资源非常短缺,因此学习钢琴演奏成为一件非常奢侈的事情。影响音乐表演的因素是多种多样的,对其的评价有节奏、表现力、音乐、风格把握等多种类型。利用计算机模拟这一评价过程,从本质上识别影响音乐演奏的因素与评价指标之间的数学关系。利用计算机多媒体软件进行钢琴教学已成为缓解这一矛盾的可行途径。本文论述了钢琴教学软件的实施方法、计算机钢琴教学存在的问题、计算机教学是单向知识、缺乏互动性等问题。运用神经网络(NN)模型对钢琴演奏进行评价,并模拟教师指导学生练习。针对不同于NN训练样本集合的“欢乐颂”钢琴音乐测试了所提出系统的性能,并由另一位钢琴老师,学生A(钢琴级别6)和学生B(钢琴级别5)交付了10次。
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引用次数: 3
Teaching Design of Online Ideological and Political Course Based on Deep Learning Model Evaluation 基于深度学习模型评价的网络思政课教学设计
Pub Date : 2022-01-12 DOI: 10.1155/2022/4754972
Lijun Qiao
In practical terms, teachers are supported to use more straightforward teaching methods, such as creating real-life contextual problems, to help students develop deep learning skills. In this paper, using Bayesian theory and Bayesian classifier research methods, a machine learning model was constructed using Python to establish the correspondence between online teaching of civics and high-level semantic features and to achieve computer learning through text and teaching design evaluation research that can identify high-frequency knowledge points. The inter-relationship model knowledge mapping, the accuracy is 90%, and the continuous knowledge update help to improve the model accuracy.
实际上,教师可以使用更直接的教学方法,比如创造现实生活中的情境问题,来帮助学生培养深度学习技能。本文运用贝叶斯理论和贝叶斯分类器研究方法,利用Python构建机器学习模型,建立公民学在线教学与高级语义特征的对应关系,通过文本和教学设计评价研究实现计算机学习,识别高频知识点。相互关系的模型知识映射,准确率达90%,知识的持续更新有助于提高模型的准确率。
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引用次数: 6
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