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2021 IEEE 4th International Conference on Information Systems and Computer Aided Education (ICISCAE)最新文献

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Tracking Control of Neural System using Adaptive Sliding Mode Control for Unknown Nonlinear Function 基于自适应滑模控制的未知非线性神经系统跟踪控制
Chunrong Xia, Irfan Qaisar, M. S. Aslam, Lin Qiaoyu
In this article, a sliding mode control (SMC) is used to design the tracking control for the neural system based on a networked control system (NCS) that appeared with time delays. First, we established the mathematical forms for the stability analysis, and then proposed the radial basis function to approximate the nonlinear function. Second, we propose the discrete event-triggered scheme (ETS) as a way to make better use of existing bandwidth. Only when our sampled data of plant violates the specific event-triggered condition does the sensor release the data under this ETS. Finally, a nonlinear example is given to demonstrate the effectiveness of our co-design method.
本文采用滑模控制(SMC)设计了基于网络控制系统(NCS)的神经系统的跟踪控制。首先建立了稳定性分析的数学形式,然后提出了近似非线性函数的径向基函数。其次,我们提出离散事件触发方案(ETS)作为一种更好地利用现有带宽的方法。只有当我们的工厂采样数据违反特定的事件触发条件时,传感器才会在此ETS下释放数据。最后,通过一个非线性算例验证了协同设计方法的有效性。
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引用次数: 0
Random time delay analysis of Nb2O5 and OTS memristors Nb2O5和OTS忆阻器的随机时延分析
Zhong Ma, Hongqi Yu, Shiqing Zhang, Yi Sun, Jietao Diao, Day-Uei Li
Memristors show excellent ductility and low power consumption. They have broad applications in logic circuits, neuromorphic computing and non-volatile memory. Memristors show great potential in true random number generation (TRNG). To verify memristors' randomness, we made two kinds of memristors, measured the randomness of their delays, and investigated their different randomness mechanisms. We did thousands of experiments and verified the feasibility of making a new TRNG using these two kinds of memristors. We also found a new application of memristors to make non-linear device.
忆阻器具有良好的延展性和低功耗。它们在逻辑电路、神经形态计算和非易失性存储器中有着广泛的应用。忆阻器在真随机数生成(TRNG)中显示出巨大的潜力。为了验证忆阻器的随机性,我们制作了两种忆阻器,测量了它们延迟的随机性,并研究了它们不同的随机性机制。我们做了数千次实验,验证了使用这两种忆阻器制作新的TRNG的可行性。我们还发现了忆阻器在非线性器件中的新应用。
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引用次数: 1
Interactive multimedia Network teaching evaluation based on object segmentation algorithm 基于目标分割算法的交互式多媒体网络教学评价
Xiaocheng Gao, Yannan Mu
With the deepening of teaching reform and the development of computer technology and application, multimedia network teaching has become the development direction of traditional teaching mode. In recent years, a large number of multimedia teaching software have emerged at home and abroad, most of which have relatively similar characteristics, such as audio/video interaction, sharing the whiteboard, teaching broadcast, with specific user roles and permission control, etc. The transmission and synchronization of multimedia stream is a research hotspot in real-time multimedia system. In this paper, the transmission protocol, delay model and synchronization strategy in multimedia stream network transmission are discussed deeply, and the calculation method of static buffer size of receiver is given. A new algorithm of dynamically changing playback rate according to the change of buffer is proposed to realize multimedia synchronization. On J2EE platform, the functions of distributed and developable network teaching system based on SOA architecture are realized. According to the requirements of unified modelling language UML in software engineering, the network teaching system was modelled, and various types of model description diagrams needed by the system were completed in Rational Rose, a UML development tool. According to the requirements of software engineering, the outline design and detailed design of the network teaching system based on UML and the concrete implementation in the object-oriented development platform are completed. It greatly improves the level and work efficiency of multimedia teaching and network teaching, and provides reliable technical support and strong technical support for teachers to carry out multimedia teaching activities smoothly in network classroom.
随着教学改革的深入和计算机技术与应用的发展,多媒体网络教学已成为传统教学模式的发展方向。近年来,国内外涌现了大量的多媒体教学软件,它们大多具有相对相似的特点,如音视频交互、共享白板、教学直播、具有特定的用户角色和权限控制等。多媒体流的传输与同步是实时多媒体系统的研究热点。本文深入讨论了多媒体流网络传输中的传输协议、延迟模型和同步策略,给出了接收端静态缓冲区大小的计算方法。为了实现多媒体同步,提出了一种根据缓冲区的变化动态改变播放速率的新算法。在J2EE平台上,实现了基于SOA架构的分布式可开发网络教学系统的功能。根据软件工程中统一建模语言UML的要求,对网络教学系统进行了建模,并在UML开发工具Rational Rose中完成了系统所需的各类模型描述图。根据软件工程的要求,完成了基于UML的网络教学系统的概要设计和详细设计,并在面向对象的开发平台上进行了具体实现。大大提高了多媒体教学和网络教学的水平和工作效率,为教师在网络课堂中顺利开展多媒体教学活动提供了可靠的技术支持和强有力的技术支持。
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引用次数: 0
Fast Action Recognition Based on Local and Nonlocal Temporal Feature 基于局部和非局部时间特征的快速动作识别
Zhiang Dong
In this paper, we propose a mixed time-asymmetric (MTA) CNN which uses time-asymmetric convolution to extract non-local temporal feature and uses normal convolution to extract local temporal features. With the fusion of local and non-local temporal feature, our MTA CNN can achieve better action recognition accuracy while keeping the network lightweight and fast. Specially, temporal feature fusion method is designed to replace the common global average pooling in our MTA CNN so as to obtain higher-dimensional feature vector and retain more information. Extensive experimental results demonstrate that our methods can achieve comparable results on Kinetics-400 and UCF101 among leading methods with less parameters and more faster recognition speed.
在本文中,我们提出了一种混合时间不对称(MTA) CNN,它使用时间不对称卷积提取非局部时间特征,使用正态卷积提取局部时间特征。通过局部和非局部时间特征的融合,我们的MTA CNN可以在保持网络轻量和快速的同时获得更好的动作识别精度。特别地,我们设计了时间特征融合方法来取代我们的MTA CNN中常见的全局平均池化,从而获得更高维度的特征向量,保留更多的信息。大量的实验结果表明,我们的方法可以在tics-400和UCF101上获得与领先方法相当的结果,而且参数更少,识别速度更快。
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引用次数: 0
Inverter Fault Diagnosis Based on PNN Neural Network 基于PNN神经网络的变频器故障诊断
Weihao Zeng, Jidong Xu
A three-phase inverter is widely used in every aspect of life and production, and fault diagnosis becomes more important. In this paper, the working characteristics and process of the traditional three-phase three-wire inverter when an open-circuit fault occurs are analyzed in-depth, and the Simulink model is built to simulate it. At the same time, the M language written by MATLAB software is used to build the diagnosis model of single-phase open-circuit fault of three-phase inverter IGBT based on a PNN neural network. The first 20 harmonics of the three-phase output voltage were selected as the eigenvalues to construct the input training samples, which were trained to make them have a certain ability of fault diagnosis.
三相逆变器广泛应用于生活和生产的各个方面,故障诊断变得越来越重要。本文深入分析了传统三相三线制逆变器在发生开路故障时的工作特性和过程,并建立了Simulink模型对其进行仿真。同时,利用MATLAB软件编写的M语言,建立了基于PNN神经网络的三相逆变器IGBT单相开路故障诊断模型。选取三相输出电压的前20次谐波作为特征值构建输入训练样本,对其进行训练,使其具有一定的故障诊断能力。
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引用次数: 0
Role-oriented Task Allocation in Human-Machine Collaboration System 人机协作系统中面向角色的任务分配
Ji Liu, Yunpeng Zhao
In the past few years, collaborative AI-infused machines have been introduced as a new generation of industrial “workers”, working with humans to share the workload. These “workers” have the potential to realize Human-Machine Collaboration (HMC),which enables flexible automation. However, combining intelligent machines with humans to obtain more efficient and accuracy human-in-the-loop solutions is a nontrivial task. Therefore, how to allocate tasks between humans and machines has become an important issue in system design. Inspiring by the graph path searching, in this paper, we adopt an acyclic direction graph to construct the role-oriented task allocation problem, and develop an Ant colony optimization based Human-Machine Task Allocation (A-HMTA) approach to find an optimized allocation solution in the search space. Experimental results show that our approach is superior to traditional approaches in terms of cost and time consumption.
在过去的几年里,注入人工智能的协作机器作为新一代工业“工人”被引入,与人类一起工作,分担工作量。这些“工人”有可能实现人机协作(HMC),从而实现灵活的自动化。然而,将智能机器与人类结合起来以获得更高效、更准确的人在环解决方案是一项艰巨的任务。因此,如何在人与机器之间分配任务已成为系统设计中的一个重要问题。受图路径搜索的启发,本文采用无环方向图构造面向角色的任务分配问题,并提出了一种基于蚁群优化的人机任务分配(A-HMTA)方法,在搜索空间中寻找最优分配解。实验结果表明,该方法在成本和时间上都优于传统方法。
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引用次数: 0
Construction of Computer Mega Data Security Technology Platform Based on Machine Learning 基于机器学习的计算机大数据安全技术平台构建
Zhangrong Liu
With the wide popularization of the Internet, advanced technologies such as AI (artificial intelligence) and mega data have also been produced and widely used, effectively promoting the development and progress of related industries. In the era of mega data, people can get valuable information through data mining and analysis. The core goal of building a computer mega data security technology platform under AI environment is to build a corresponding computer mega data security technology platform through AI, so as to realize the protection of user data information. On the basis of simulating human behavior, ML (machine learning) technology enables computers to acquire more new skills and knowledge so as to complete the continuous optimization of organizational structure. This paper introduces the key technologies of network security and expounds the application of ML technology in the field of network security, then analyzes the solutions of ML in network security under the background of mega data, and finally looks forward to the development trend of ML in network security research.
随着互联网的广泛普及,人工智能、大数据等先进技术也应运而生并得到广泛应用,有力地推动了相关产业的发展进步。在大数据时代,人们可以通过数据挖掘和分析获得有价值的信息。构建AI环境下的计算机大数据安全技术平台的核心目标是通过AI构建相应的计算机大数据安全技术平台,从而实现对用户数据信息的保护。ML (machine learning)技术在模拟人类行为的基础上,使计算机能够获得更多新的技能和知识,从而完成组织结构的不断优化。本文介绍了网络安全的关键技术,阐述了机器学习技术在网络安全领域的应用,分析了大数据背景下机器学习在网络安全领域的解决方案,最后展望了机器学习在网络安全研究中的发展趋势。
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引用次数: 0
Research on Model of Seismic Anomaly Data Mining Based on Neural Network 基于神经网络的地震异常数据挖掘模型研究
Yancheng Long, J. Rong
Data mining in the seismic anomaly database will be affected by the instability of the seismic monitoring system signal and the environment, so in the development of practice should be based on the existing technology to comprehensively explore, pay attention to gradually break through the limitations of traditional mining methods, in order to effectively solve the problems existing in the previous data mining. Under the background of new era, the neural network as a machine learning algorithm is the most common way of mining, need according to the related theory had a clear standard equation of the minimum mean square error values, thus to build optimized mining model, and then using the calculation data of database, the feature vector to construct the corresponding to the monitoring data are accurate judgment. On the basis of understanding the current development of seismic monitoring technology, this paper proposes a new optimization model based on the constructed seismic anomaly database, and verifies its application effect in practice.
地震异常数据库中的数据挖掘会受到地震监测系统信号的不稳定性和环境的影响,因此在开发实践中应在现有技术的基础上进行全面探索,注意逐步突破传统挖掘方法的局限性,以有效解决以往数据挖掘中存在的问题。在新时代背景下,神经网络作为一种机器学习算法是最常用的挖掘方式,需要根据相关理论有一个明确的均方误差最小值的标准方程,从而构建优化的挖掘模型,然后利用数据库的计算数据、特征向量构建相应的对监测数据进行准确判断。在了解地震监测技术发展现状的基础上,基于已构建的地震异常数据库,提出了一种新的优化模型,并在实践中验证了其应用效果。
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引用次数: 0
Communication Technology and Application in Internet of Vehicles 通信技术及其在车联网中的应用
Min Wang, Sinan Wang
Internet of vehicles (IOV) is the application of internet of things technology in the intelligent transportation system, which has attracted the attention of relevant research institutions at home and abroad. By introducing the basic concept of IOV, combined with the specific application scenarios and actual characteristics of the internet of vehicles, this paper analyzes and discusses the research objectives of IOV: vehicle to vehicle, vehicle to road, vehicle to person, vehicle to equipment communication. Then, some technical problems in the development process of IOV are analyzed, and the application services that IOV can provide and the problems in the development are summarized. The technology of IOV involves many subjects and needs further research.
车联网(Internet of vehicles, IOV)是物联网技术在智能交通系统中的应用,已引起国内外相关研究机构的关注。本文通过介绍车联网的基本概念,结合车联网的具体应用场景和实际特点,对车联网的研究目标:车对车、车对路、车对人、车对设备通信进行了分析和探讨。然后,分析了车联网发展过程中存在的一些技术问题,总结了车联网能够提供的应用服务以及发展中存在的问题。车联网技术涉及众多学科,需要进一步研究。
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引用次数: 0
Network Resource Backup Algorithm Based on Multi-Attribute Analytic Hierarchy Process in IPv6 Networks 基于多属性层次分析法的IPv6网络资源备份算法
Xiaoyu Wang, Xue-Qin Lu, Zhonghua Liang, Gang Liu
To solve the problem of low utilization of underlying network resources, this paper proposes a network resource backup algorithm based on a multi-attribute analytic hierarchy process in IPv6 Networks. In the steps of calculating and ranking the importance of the underlying network nodes and underlying links, analysis is performed from the three dimensions of network characteristics, resource utilization, and power business importance of each underlying network node and underlying network link. To analyze the weight function of multiple attributes in the importance of resources more fairly, the attributes of the underlying network nodes and underlying network links are analyzed based on the multi-attribute hierarchical analysis algorithm. When performing resource backups on the underlying network nodes and underlying network links, it is evaluated from the two dimensions of whether the resource utilization rate exceeds the threshold and the importance of the resources, to improve the rationality of the underlying network resource backup mechanism. In the experimental part, it is verified that the algorithm in this paper has obtained good results in the two dimensions of the virtual network mapping success rate and the average utilization rate of the underlying network resources.
针对IPv6网络中底层网络资源利用率低的问题,提出了一种基于多属性层次分析法的网络资源备份算法。在对底层网络节点和底层链路的重要性进行计算和排序的步骤中,从网络特征、资源利用率、各底层网络节点和底层网络链路的电力业务重要性三个维度进行分析。为了更公平地分析资源重要性中多个属性的权重函数,基于多属性层次分析算法对底层网络节点和底层网络链路的属性进行了分析。在对底层网络节点和底层网络链路进行资源备份时,从资源利用率是否超过阈值和资源重要性两个维度进行评估,提高底层网络资源备份机制的合理性。在实验部分,验证了本文算法在虚拟网络映射成功率和底层网络资源平均利用率两个维度上取得了较好的效果。
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引用次数: 0
期刊
2021 IEEE 4th International Conference on Information Systems and Computer Aided Education (ICISCAE)
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