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2020 5th International Conference on Computer and Communication Systems (ICCCS)最新文献

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CIASM-Net: A Novel Convolutional Neural Network for Dehazing Image CIASM-Net:一种新型的图像去雾卷积神经网络
Pub Date : 2020-05-01 DOI: 10.1109/ICCCS49078.2020.9118601
W. Qian, Chao Zhou, Deng-yin Zhang
When light propagates in the medium such as haze, the image information collected by the imaging sensor is seriously degraded due to the scattering of particles, which greatly limits the application value of the image. In this paper, a novel convolutional neural network model called CIASM-Net is proposed to implement image dehazing. CIASM-Net includes color feature extraction convolutional networks and deep defogging convolutional networks. The color feature extraction convolution network is used to extract the color features of foggy images; the deep dehazing convolution network improves the inverse atmospheric scattering model convolution network, and uses a multi-scale convolution layer instead of the original convolution layer to estimate the transmittance value. Moreover, we add a pyramid pooling layer to the network to extract global features. To obtain the optimized network model, we use the classic RESIDE training set to train the network model. We have performed extensive experiments on the synthetic hazy dataset and the real-world hazy dataset in the RESIDE test set. The experimental results have proved that the model has satisfactory results.
当光在雾霾等介质中传播时,由于粒子的散射,成像传感器采集到的图像信息严重退化,极大地限制了图像的应用价值。本文提出了一种新的卷积神经网络模型CIASM-Net来实现图像去雾。CIASM-Net包括颜色特征提取卷积网络和深度去雾卷积网络。采用颜色特征提取卷积网络提取雾图像的颜色特征;深度除雾卷积网络对大气散射逆模型卷积网络进行了改进,使用多尺度卷积层代替原始卷积层估算透光率值。此外,我们在网络中添加了一个金字塔池层来提取全局特征。为了得到优化后的网络模型,我们使用经典的驻留训练集对网络模型进行训练。我们在live测试集中对合成雾霾数据集和真实雾霾数据集进行了大量的实验。实验结果表明,该模型具有令人满意的效果。
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引用次数: 3
The Resource Dynamic Recombination and Its Technology Development of Space TT&C Equipment 空间测控设备资源动态重组及其技术发展
Pub Date : 2020-05-01 DOI: 10.1109/ICCCS49078.2020.9118541
Qin Mingnuan, Zhang Yao, Yan Yalong, Liang Zhen
For large satellite ground stations with multiple parabolic antennas or multi-beam digital array antennas, the construction of tracking, telemetry and command (TT&C) equipment is suitable for an architecture based on resource dynamic recombination technology. Facing engineering application, system structure and equipment configuration scheme of resource recombination system are designed, and a method of resource recombination and scheduling is put forward. At the same time, aiming at the development requirements of integration, digitization, generalization and intelligence of satellite TT&C equipment, the technology development direction of resources dynamic recombination and the key technologies needed to be broken through are discussed in this paper.
对于具有多抛物面天线或多波束数字阵列天线的大型卫星地面站,跟踪、遥测和指挥(TT&C)设备的建设适合基于资源动态重组技术的体系结构。面向工程应用,设计了资源重组系统的系统结构和设备配置方案,提出了资源重组与调度的方法。同时,针对卫星测控装备集成化、数字化、通用化、智能化的发展要求,探讨了资源动态重组的技术发展方向和需要突破的关键技术。
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引用次数: 0
Proposal of Distributed e-Learning System Using Idle Resources 利用空闲资源的分布式电子学习系统的构想
Pub Date : 2020-05-01 DOI: 10.1109/ICCCS49078.2020.9118598
Toshiya Kawato, Masayuki Higashino, Kenichi Takahashi, T. Kawamura
E-Learning systems that enable students to study by themselves without a teacher have widely deployed in universities, high schools and companies. Such an e-learning system is usually implemented as a client-server model. The client-server model, however, has problems with fault tolerance and concentration of system resources such as computation and storage. These problems can be solved by the installation of high-performance servers. These solutions, however, require many costs to purchase high-performance servers; it is difficult to purchase them because of a limited budget. In this paper, we propose a distributed e-learning system that utilizes idle resources of computers in an organization. Many computers in organizations are used for office works, and their computers have excessive computational power and storage space. Thus, we try to utilize such computation and storage of these computers as idle resources. Since our proposed system uses these idle resources, our e-learning system enables us to realize high fault tolerance and a load balancing function without any additional costs.
使学生在没有老师的情况下自主学习的电子学习系统已广泛应用于大学、高中和公司。这样的电子学习系统通常以客户机-服务器模型实现。然而,客户机-服务器模型在容错和系统资源(如计算和存储)集中方面存在问题。这些问题可以通过安装高性能服务器来解决。然而,这些解决方案需要花费很多成本来购买高性能服务器;由于预算有限,很难购买。本文提出了一种利用组织中空闲计算机资源的分布式电子学习系统。组织中的许多计算机用于办公工作,他们的计算机具有过大的计算能力和存储空间。因此,我们试图利用这些计算机的计算和存储作为空闲资源。由于我们提出的系统利用了这些空闲资源,我们的电子学习系统使我们能够在没有任何额外成本的情况下实现高容错性和负载均衡功能。
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引用次数: 2
Telegram-Based Chatbot Application for Foreign People in Japan to Share Disaster-Related Information in Real-Time 基于电报的聊天机器人应用程序,用于在日本的外国人实时分享灾害相关信息
Pub Date : 2020-05-01 DOI: 10.1109/ICCCS49078.2020.9118510
Sayed Ehsanullah Ahmady, O. Uchida
When a disaster occurs, early evacuation of residents is one of the effective ways for the reduction of human damage. Then, the rapid collection and delivery of accurate disaster-related information are essential. In this study, we develop a chatbot application as an add-on to the Telegram platform interface. This chatbot provides emergency information to foreign people in Japan at the time of disasters. The information provided by the proposed application is, for example, the nearby evacuation points such as the evacuation centers and train stations, and the real-time disaster information based on the user’s current location. People can also share disaster-related pictures via the proposed application. Such pictures may be useful not only for disaster-affected people but also for governmental agencies to gain a better understanding of current conditions and thus help them make informed decisions.
灾害发生时,尽早疏散居民是减少人员伤亡的有效途径之一。因此,快速收集和提供准确的灾害相关信息至关重要。在本研究中,我们开发了一个聊天机器人应用程序,作为Telegram平台界面的附加组件。这个聊天机器人在灾难发生时向在日本的外国人提供紧急信息。提议的应用程序提供的信息,例如,附近的疏散点,如疏散中心和火车站,以及基于用户当前位置的实时灾难信息。人们还可以通过拟议的应用程序分享与灾难有关的图片。这些图片可能不仅对受灾人民有用,而且对政府机构更好地了解目前的情况也有用,从而帮助他们做出明智的决定。
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引用次数: 8
Analysis and Application Based on GTF Infrared and Visible Image Fusion 基于GTF红外与可见光图像融合的分析与应用
Pub Date : 2020-05-01 DOI: 10.1109/ICCCS49078.2020.9118445
Tingting Lv, Lei Zhang
From 1997 to 2006, China's railway has undergone six large-scale speed-raising reconstruction, and some of the speed has reached 250KM/h. With the development of train speed, the pantograph-cantenary system becomes more and more important. Since infrared image has light penetration, this paper fuses infrared and visible images to get more information about the pantograph-cantenary so that train drivers can learn more about the pantograph-cantenary situation. Existing fusion methods typically use the same representations and extract the similar characteristics for different source images. However, it may don’t work for infrared and visible images. In this paper, we use the fusion algorithm named Gradient Transfer Fusion (GTF), which can keep the thermal radiation and appearance information simultaneously. To prove the effectiveness of the GTF method, it is compared with other 17 fusion algorithms from quantitative aspects. Furthermore, the parameter in the GTF method is analyzed and selected for better fusion results. Finally, color image fusion which is an improvement to the GTF method preserving the color information of the visible image in the fused image is proposed and it is tested on publicly available data sets to prove its availability.
从1997年到2006年,中国铁路经历了6次大规模提速改造,部分提速速度达到250公里/小时。随着列车运行速度的提高,受电弓供电系统变得越来越重要。由于红外图像具有透光性,本文将红外图像与可见光图像进行融合,得到更多的受电弓区信息,使列车驾驶员能够更好地了解受电弓区情况。现有的融合方法通常对不同的源图像使用相同的表示,提取相似的特征。然而,它可能不适用于红外线和可见光图像。本文采用梯度转移融合(GTF)融合算法,可以同时保留热辐射和外观信息。为了证明GTF方法的有效性,从定量方面与其他17种融合算法进行了比较。此外,为了获得更好的融合效果,对GTF方法中的参数进行了分析和选择。最后,提出了一种改进GTF方法的彩色图像融合方法,该方法在融合图像中保留了可见图像的颜色信息,并在公开数据集上进行了测试,以证明其有效性。
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引用次数: 1
A New Kind of Measuring Tooling and Closed-loop Control for Gough-Stewart Parallel Robot Gough-Stewart并联机器人一种新型测量工具及闭环控制
Pub Date : 2020-05-01 DOI: 10.1109/ICCCS49078.2020.9118525
Chen Liang, Sun Hanxv, Jia Qingxuan, Cao Shaozhong, Zhao Wei, Yu Tao
Due to the lack of reliable way to obtain its position/speed information, the closed-loop control in Gough-Stewart parallel robot’s workspace cannot be realized, therefore the application of Gough-Stewart parallel robot is restricted. In this paper, a peg-hole relative position and orientation measuring tooling for Gough Stewart parallel robot is designed. The kinematics model of the peg-hole relative position and orientation measuring tooling which establishes the relative pose relations between the readings of the measuring tooling and the through-holes is established. The relationship between the readings of the measuring tooling and the pose of the top plate is then obtained, based on which the velocity and acceleration of the top plate can be obtained and the closed-loop control of peg-in-hole assembly Gough-Stewart parallel robot in its workspace may be realized. The sliding mode controller and the super twisting controller is established for control this robot. Results of simulation can prove the validity of the dynamic model and the stability of two controllers. By compare this two controllers we can obtain the conclusion that the super twisting controller is better than the sliding mode controller especially used in peg in hole operations. The application range of Gough-Stewart parallel robot could be widen by this work.
由于缺乏可靠的位置/速度信息获取途径,无法实现Gough-Stewart并联机器人工作空间的闭环控制,限制了Gough-Stewart并联机器人的应用。设计了一种用于Gough Stewart并联机器人的销孔相对位置和方位测量工具。建立了钉孔相对位置和方位测量工具的运动学模型,建立了测量工具的读数与通孔的相对位姿关系。然后得到测量工具的读数与顶板位姿之间的关系,以此为基础得到顶板的速度和加速度,从而实现对钉孔装配Gough-Stewart并联机器人在其工作空间内的闭环控制。建立了滑模控制器和超扭转控制器对机器人进行控制。仿真结果证明了动态模型的有效性和控制器的稳定性。通过对这两种控制器的比较,得出了超扭转控制器优于滑模控制器的结论,特别是在钉孔作业中。该工作可拓宽Gough-Stewart并联机器人的应用范围。
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引用次数: 0
Spreading Factor Allocation for Large-Scale Deployment In LoRaWAN Network LoRaWAN网络中大规模部署的扩频因子分配
Pub Date : 2020-05-01 DOI: 10.1109/ICCCS49078.2020.9118543
Haofei Xie, Xingwei Yuan, Zhejian Jia, Zhihui Wang
Network resource allocation for large-scale terminal node deployment is arousing general interest in LoRaWAN research. And the spreading factor is one of the most important resource parameters in the LoRaWAN network, which affects the data transmission rate, transmission time and distance. Therefore, it is of great significance to improve network performance by constructing a resource allocation scheme to allocate spreading factors to terminal nodes. In order to improve the reliability of the network, this paper proposes a spreading factor allocation method based on LoRaWAN network.
大规模终端节点部署的网络资源分配问题引起了LoRaWAN研究的广泛关注。而扩频因子是LoRaWAN网络中最重要的资源参数之一,它影响着数据的传输速率、传输时间和传输距离。因此,构建一种资源分配方案,将传播因子分配给终端节点,对提高网络性能具有重要意义。为了提高网络的可靠性,本文提出了一种基于LoRaWAN网络的扩频因子分配方法。
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引用次数: 3
Cascading Framework for Multi-level Image Quality Evaluation 多层次图像质量评价的级联框架
Pub Date : 2020-05-01 DOI: 10.1109/ICCCS49078.2020.9118560
Haishan Zhang, Xiaonan Liu
Due to the light interference, mobile terminal iris recognition on the visible light cannot accurately extract texture information that used for iris recognition. In order to solve the problem, image quality evaluation is used to ensure that the iris image quality meets the recognition needs, find an excellent and complete iris structure, and extract the iris texture information to complete the matching. In this paper, a multi-level quality evaluation cascade framework is designed. This paper preprocesses the iris image, and then uses the Tenegrad evaluation function to complete the first level image quality evaluation, and then uses the wavelet transform and BP neural network to accomplish the second level image quality evaluation. To test the effectiveness of the algorithm, 900 iris images in the UBIRIS.v2 iris gallery are used for testing. The accuracy of quality evaluation is 96.1%. The result shows that the method can correctly evaluate the iris image quality, exclude the images that cannot be used for iris recognition, and effectively improve iris recognition on the mobile terminal.
由于光的干扰,移动终端虹膜识别对可见光无法准确提取用于虹膜识别的纹理信息。为了解决这一问题,采用图像质量评价的方法,保证虹膜图像质量满足识别需求,寻找优秀完整的虹膜结构,提取虹膜纹理信息,完成匹配。本文设计了一个多层次质量评价级联框架。本文对虹膜图像进行预处理,然后利用teneggrad评价函数完成第一级图像质量评价,然后利用小波变换和BP神经网络完成第二级图像质量评价。为了测试算法的有效性,在UBIRIS中使用了900幅虹膜图像。使用V2虹膜图库进行测试。质量评价准确率为96.1%。结果表明,该方法能够正确评价虹膜图像质量,排除不能用于虹膜识别的图像,有效提高移动终端上的虹膜识别能力。
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引用次数: 0
Fractal Stable Effect of the External Disturbance on the Generalized Diffusion Limited Aggregation by Backstepping Control Method 外扰动对广义扩散有限聚集的分形稳定效应
Pub Date : 2020-05-01 DOI: 10.1109/ICCCS49078.2020.9118443
Li Zhang
It is well known that external disturbance has complexity effect on algorithms for data analysis in different fields. From the point of view of control theory, a model about fractal growth and inner reaction-diffusion system is presented and the fractal stable effect is deduced and simulated by backstepping control method and a generalized diffusion limited aggregation algorithm.
众所周知,外界干扰对不同领域的数据分析算法具有复杂性影响。从控制理论的角度出发,建立了分形生长和内反应扩散系统的模型,推导了分形稳定效应,并采用步进控制方法和广义扩散有限聚集算法进行了模拟。
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引用次数: 0
ICCCS 2020 Preface ICCCS 2020序言
Pub Date : 2020-05-01 DOI: 10.1109/icccs49078.2020.9118513
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引用次数: 0
期刊
2020 5th International Conference on Computer and Communication Systems (ICCCS)
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