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The Role of the Combination of 3D Simulation Sequence Diagram and Video Motion Recognition Technology in Evaluating and Correcting Dancers' Dance Moves 三维模拟序列图与视频动作识别技术相结合在评估和纠正舞者舞蹈动作中的作用
IF 0.4 Q4 TELECOMMUNICATIONS Pub Date : 2024-07-17 DOI: 10.4018/ijmcmc.348662
Hua Wei, Vinh Chau
This paper combines the dance 3D space simulation sequence diagram with video motion recognition technology, filters, denoises, grays and background removal the collected dance video images, analyzes the motion characteristics of people in the sequence diagram, uses support vector machine to learn and train 3D space models, classifies and recognizes people's dance movements, and extracts 3D-SIFT and optical flow characteristics of various areas of human body. Form a three-dimensional space simulation sequence diagram, reduce and normalize the extracted features, get the feature vectors of various characters, and input them into the classifier to realize the recognition of dance movements. The results show that the combination of 3D-SIFT and optical flow can realize the dynamic change of human static information, the illumination invariance of SIFT features can make up for the illumination sensitivity of optical flow features, and the optical flow features can solve the instability problem of determining the key points of SIFT features.
本文将舞蹈三维空间模拟序列图与视频动作识别技术相结合,对采集到的舞蹈视频图像进行滤波、去噪、去灰、去背景等处理,分析序列图中人物的动作特征,利用支持向量机学习和训练三维空间模型,对人物的舞蹈动作进行分类和识别,提取人体各部位的三维-SIFT和光流特征。形成三维空间模拟序列图,对提取的特征进行还原和归一化处理,得到各种人物的特征向量,并将其输入分类器,实现对舞蹈动作的识别。结果表明,三维-SIFT与光流的结合可以实现人体静态信息的动态变化,SIFT特征的光照不变性可以弥补光流特征的光照敏感性,光流特征可以解决SIFT特征关键点确定的不稳定性问题。
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引用次数: 0
Fuzzy Learning-Based Electric Measurement Data Circulation Monitoring and Security Risk Anomaly Evaluation 基于模糊学习的电力测量数据流通监控与安全风险异常评估
IF 0.4 Q4 TELECOMMUNICATIONS Pub Date : 2024-07-17 DOI: 10.4018/ijmcmc.346990
Xinjia Li, Yahong Li, Lei Fang, Liwei Liu, Ke Wang
With the circulation of massive electric measurement data, data anomaly caused by security attacks imposes security risks on reliable operation of smart grid. Long short-term memory (LSTM) based data circulation monitoring and security risk anomaly evaluation has been intensively studied. However, some issues remain unsolved, including learning overfitting and large prediction error. In this paper, we investigate fuzzy learning to infer the abnormal level of security risk. In particular, an adaptive grey wolf optimization-LSTM-fuzzy petri network (AGWO-LSTM-FPN) based electrical measurement data circulation monitoring and security risk anomaly evaluation algorithm is proposed. Specifically, AGWO is utilized to optimize LSTM parameter updating and improve traffic prediction accuracy. Furthermore, FPN is combined with multi-dimensional monitoring indicators to enhance anomaly level evaluation. Simulation results illustrate the excellent performance of AGWO-LSTM-FPN.
随着海量电力测量数据的流通,由安全攻击引起的数据异常给智能电网的可靠运行带来了安全隐患。基于长短期记忆(LSTM)的数据流通监控和安全风险异常评估已得到深入研究。然而,一些问题仍未得到解决,包括学习过拟合和预测误差过大。在本文中,我们研究了模糊学习来推断安全风险的异常级别。具体而言,本文提出了一种基于自适应灰狼优化-LSTM-模糊 petri 网络(AGWO-LSTM-FPN)的电气测量数据循环监测和安全风险异常评估算法。具体来说,AGWO 用于优化 LSTM 参数更新,提高流量预测精度。此外,还将 FPN 与多维监测指标相结合,以加强异常级别评估。仿真结果表明了 AGWO-LSTM-FPN 的卓越性能。
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引用次数: 0
Youth Sources of News During the COVID-19 Period COVID-19 期间青少年的新闻来源
IF 0.6 Q3 Computer Science Pub Date : 2024-05-17 DOI: 10.4018/ijmcmc.343789
Badreya Al-jenaibi (536d4bda-1d8b-42f0-94b7-3346c1
Coronavirus disease 2019 (COVID-19) pandemic has produced a global health crisis that has had a deep impact on the way we perceive our world and everyday lives. Not only the spread rate of contagion and patterns of transmission endangered our sense of security, but the safety measures put in place to contain the spread of the virus also require social distancing. In this context of physical threat, social and physical distancing, the role of the different mass media channels and social media in lives of individual, social and societal levels cannot be underestimated.
2019 年冠状病毒病(COVID-19)大流行引发了一场全球性的健康危机,对我们认识世界和日常生活的方式产生了深刻影响。不仅传染率和传播模式危及我们的安全感,而且为遏制病毒传播而采取的安全措施也需要拉开社会距离。在这种物理威胁、社会和物理距离的背景下,不同的大众媒体渠道和社交媒体在个人、社会和社会生活中的作用不可低估。
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引用次数: 0
An End-to-End Network Evaluation Method for Differentiated Multi-Service Bearing in VPP VPP 中差异化多服务承载的端到端网络评估方法
IF 0.6 Q3 Computer Science Pub Date : 2024-03-12 DOI: 10.4018/ijmcmc.340381
Wanqiao Wang, Jian Su, Hui Zhang, Luyao Guan, Qingrong Zheng, Zhuofan Tang, Huixia Ding
Virtual power plant (VPP) plays an important role in improving the balance and regulation abilities of new power system. The safe and reliable operation is support by the VPP end-to-end communication network with differentiated multi-service bearing capability. For the requirement of unified and standard VPP end-to-end networking scheme, the VPP service communication metrics, as well as the communication network architecture of VPP aggregation and control are analyzed. Then, a multi-dimension hierarchical VPP end-to-end network evaluation index system is put forward. In addition, an end-to-end VPP network evaluation method considering differentiated time-sensitive and granular requirements of multiple services is proposed. Finally, the suitability analysis results of various end-to-end networking schemes and multiple services with differentiated time-sensitive and granular requirements are given, which plays a guiding role in establishing a unified standard VPP end-to-end networking scheme.
虚拟电厂(VPP)在提高新电力系统的平衡和调节能力方面发挥着重要作用。具有差异化多业务承载能力的 VPP 端到端通信网络是 VPP 安全可靠运行的支撑。针对统一标准的 VPP 端到端组网方案的要求,分析了 VPP 业务通信指标以及 VPP 汇聚和控制的通信网络架构。然后,提出了多维度分层的 VPP 端到端网络评价指标体系。此外,还提出了一种考虑多种业务的差异化时敏性和粒度要求的端到端 VPP 网络评价方法。最后,给出了各种端到端组网方案与具有差异化时敏性和粒度要求的多种业务的适用性分析结果,为建立统一标准的 VPP 端到端组网方案起到了指导作用。
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引用次数: 0
Biometric Authentication Methods on Mobile Platforms 移动平台上的生物识别认证方法
IF 0.6 Q3 Computer Science Pub Date : 2023-11-28 DOI: 10.4018/ijmcmc.334130
Agnitè Maxim Wilfrid Straiker Edoh, Tahirou Djara, Abdou-Aziz Sobabe Ali Tahirou, A. Vianou
In this work, the authors propose a new biometric authentication system on mobile devices, enhancing security at these terminals and preserving user privacy. The proposed system uses a method of extracting strong features from minutiae with refinement of the method with regard to the further elimination of false minutiae by the calculation of geometric information (orientations and distances between minutiae) to obtain true terminations and stronger bifurcations facilitating the recognition of individuals. A series of tests carried out using a recognition and authentication application allowed us to achieve a false rejection rate of 13.81% and a false acceptance rate of almost zero (0.021%). The authors also propose a security model using hash functions and a random number to make the recognition system revocable, more difficult to compromise and thus reducing the risk of usurpation.
在这项工作中,作者提出了一种新的移动设备生物识别身份验证系统,以提高这些终端的安全性并保护用户隐私。所提议的系统采用了一种从细微特征中提取强特征的方法,并通过计算几何信息(细微特征之间的方向和距离)对该方法进行了改进,以进一步消除虚假细微特征,从而获得真正的终止点和更强的分叉点,促进对个人的识别。通过使用识别和认证应用程序进行一系列测试,我们实现了 13.81% 的错误拒绝率和几乎为零的错误接受率(0.021%)。作者还提出了一个使用哈希函数和随机数的安全模型,使识别系统具有可撤销性,更难受到破坏,从而降低了被篡改的风险。
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引用次数: 0
Reverse Chronology: The Nature of News Stories——Based on the Investigation of the Typical Reports of the Model of the Times 逆年代学:新闻故事的本质——基于对《时代模式》典型报道的考察
IF 0.6 Q3 Computer Science Pub Date : 2023-08-20 DOI: 10.38007/ijmc.2023.040110
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引用次数: 0
Design of Accounting Information System Based on Computer Network 基于计算机网络的会计信息系统设计
IF 0.6 Q3 Computer Science Pub Date : 2023-07-19 DOI: 10.38007/ijmc.2023.040109
Baifang Liu, Yingqi Jia
: With the progress of information technology and the popularity of the Internet, the traditional Accounting information system (AIS) has been unable to meet the growing information processing needs of enterprises. The traditional AIS has problems such as inconvenient data storage and sharing, low efficiency of information transmission, etc. The AIS based on computer network can effectively solve these problems. This paper aimed to study the design of AIS based on computer network to improve the efficiency and accuracy of enterprise financial management. This paper first introduced the importance of computer network in enterprise management and the application of AIS in modern enterprises. Then, this paper put forward the demand of using computer network technology to design and establish AIS, and expounded the advantages of computer network in realizing real-time sharing and collaborative processing of financial data. This paper put forward indicators to evaluate different design schemes in terms of performance, security and reliability, and emphasized the importance of security in the design of enterprise AIS. This paper was committed to providing reference for enterprises to select appropriate AIS design scheme based on computer network through research and experiment.
随着信息技术的进步和互联网的普及,传统的会计信息系统(AIS)已经不能满足企业日益增长的信息处理需求。传统AIS存在数据存储和共享不方便、信息传输效率低等问题。基于计算机网络的AIS系统可以有效地解决这些问题。本文旨在研究基于计算机网络的AIS系统的设计,以提高企业财务管理的效率和准确性。本文首先介绍了计算机网络在企业管理中的重要性以及AIS在现代企业中的应用。然后,提出了利用计算机网络技术设计和建立AIS系统的需求,并阐述了计算机网络在实现财务数据实时共享和协同处理方面的优势。本文从性能、安全性和可靠性三个方面提出了评价不同设计方案的指标,强调了安全性在企业AIS设计中的重要性。本文致力于通过研究和实验,为企业选择合适的基于计算机网络的AIS设计方案提供参考。
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引用次数: 0
Challenges and Solutions for Network Security in Data Centers Driven by Information Technology 信息技术驱动下数据中心网络安全的挑战与解决方案
IF 0.6 Q3 Computer Science Pub Date : 2023-07-15 DOI: 10.38007/ijmc.2023.040108
Shenze Li
: With the rapid development of information technology, data center network security issues have become increasingly complex and severe. In order to address this challenge, various information technology driven solutions have been proposed, aimed at improving the security performance of data center networks. This article will explore these solutions and provide relevant numerical data support. By comparing the performance of traditional and new solutions in key indicators such as attack detection rate, false alarm rate, response time, and number of security events, it can be seen that the new solution has achieved significant results in improving network security performance. For example, the attack detection rate of the new solution has reached 95%, which is a significant improvement compared to 75% of traditional solutions. At the same time, the false alarm rate has been reduced to 5%, with a decrease of 50% compared to the traditional solution of 10%. The background significance of information technology driven data center network security solutions is significant, and remarkable numerical results have been achieved in key indicators.
随着信息技术的飞速发展,数据中心网络安全问题日益复杂和严峻。为了应对这一挑战,人们提出了各种信息技术驱动的解决方案,旨在提高数据中心网络的安全性能。本文将探讨这些解决方案,并提供相关的数值数据支持。通过对比传统方案和新方案在攻击检测率、虚警率、响应时间、安全事件数量等关键指标上的性能,可以看出新方案在提升网络安全性能方面取得了显著效果。例如,新方案的攻击检测率达到95%,相比传统方案的75%有了显著提高。同时,虚警率降低到5%,比传统方案的10%降低了50%。信息技术驱动的数据中心网络安全解决方案的背景意义重大,在关键指标上取得了显著的数值结果。
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引用次数: 0
Using Eye Tracking to Measure Overall Usability of Online Grocery Shopping Websites 使用眼动追踪来衡量在线杂货购物网站的整体可用性
IF 0.6 Q3 Computer Science Pub Date : 2023-07-14 DOI: 10.4018/ijmcmc.326129
A. B. Naeini, A. Mahdipour, Rasam Dorri
This article examines usability evaluation methodologies, then presents a non-conscious behavioral indicator based on user eye movements and pupil dilation. The authors test how gender and online buying history affect the behavioral index's usability scores. This study uses three Iranian online food retailers. Thirty participants were asked to add things from predetermined grocery stores to virtual shopping carts before the experiment took them to the other two websites in a random order to collect eye movement data. Each group's presentation order was randomized. The number of fixations, number of saccades, total duration of fixations, scan-path length, pupil size, and task time were inversely linked with self-report usability measures. This research evaluates groups with different levels of online shopping expertise and gender based on experienced usability. Differences between groups suggest that user demographics affect usability.
本文研究了可用性评估方法,然后提出了一个基于用户眼球运动和瞳孔扩张的无意识行为指标。作者测试了性别和在线购买历史如何影响行为指数的可用性得分。本研究使用了三家伊朗在线食品零售商。30名参与者被要求将从预定的杂货店购买的东西放入虚拟购物车中,然后实验以随机顺序将他们带到另外两个网站,以收集眼球运动数据。每组的陈述顺序是随机的。注视次数、扫视次数、注视总持续时间、扫描路径长度、瞳孔大小和任务时间与自我报告可用性指标呈负相关。本研究基于经验可用性对不同网购专业水平和性别的群体进行评估。群组之间的差异表明用户的人口统计数据会影响可用性。
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引用次数: 0
Deep Learning-Based Machine Color Emotion Generation 基于深度学习的机器色彩情感生成
IF 0.6 Q3 Computer Science Pub Date : 2023-07-10 DOI: 10.4018/ijmcmc.325349
Tongyao Nie, Xinguang Lv
This paper investigates generating machine color emotion through deep learning. The grayscale image colorization model's training process resembles human memory color. Sixty images were recolored and quality evaluated to explore machine generated color impressions. Six experimental samples were recolored under D65, A, CWF, and TL84 light sources. Changes in lightness, chroma, and hue angle compared the original and colorized images, exploring light source effects on machine color perception. Analyzing differences in coloring results within the CIEL* a* b* color space for pixels with equal grayscale verified machine color emotion generation. Results show the machine learns to form color impressions from samples. Different light source color temperatures impact color prediction accuracy. The machine accurately colors images based on semantic context, demonstrating spontaneous color emotion generation through deep learning. This research positively contributes to the development of intelligent devices with color emotion.
本文研究了通过深度学习生成机器色彩情感的方法。灰度图像着色模型的训练过程类似于人类记忆颜色。60幅图像被重新着色和质量评估,以探索机器产生的色彩印象。在D65、A、CWF和TL84光源下对6个实验样品进行重显色。亮度、色度和色调角度的变化比较了原始图像和彩色图像,探索光源对机器色彩感知的影响。分析具有等灰度像素的CIEL* a* b*色彩空间内着色结果的差异,验证机器颜色情感生成。结果显示,这台机器学会了从样本中形成颜色印象。不同的光源色温会影响颜色预测的准确性。该机器根据语义上下文准确地为图像上色,通过深度学习展示自发的颜色情感生成。本研究对色彩情感智能设备的开发具有积极的促进作用。
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引用次数: 0
期刊
International Journal of Mobile Computing and Multimedia Communications
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