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2020 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS)最新文献

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SVGAN: Semi-supervised Generative Adversarial Network for Image Captioning 图像标注的半监督生成对抗网络
Pub Date : 2020-12-11 DOI: 10.1109/TOCS50858.2020.9339713
Yi Zhang, Weizhen Zeng, Gangqiang He, Yueyuan Liu
Image captioning is a task that enables computer to naturally describe the contents of an image like a human, moreover it involves two different major research fields of computer vision and natural language processing. In this paper, a new image captioning system is proposed, which can address the challenges of automatically describing images in the wild. Built on the state-of-the-art caption framework, we designed a deep visual detector to catch a broad range of visual concepts, a GAN(Generative Adversarial Network) with graph embedding is developed to generate accurate sentences for wild images.
图像字幕是一项使计算机能够像人类一样自然地描述图像内容的任务,它涉及计算机视觉和自然语言处理两个不同的主要研究领域。本文提出了一种新的图像字幕系统,解决了野外图像自动描述的难题。在最先进的标题框架的基础上,我们设计了一个深度视觉检测器来捕捉广泛的视觉概念,开发了一个带有图嵌入的GAN(生成对抗网络)来为野生图像生成准确的句子。
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引用次数: 0
Detection and Research on Unsafe Driving of Taxi Drivers 出租车司机不安全驾驶的检测与研究
Pub Date : 2020-12-11 DOI: 10.1109/TOCS50858.2020.9339721
Xiaoyu Wu, Yu Wang, Naimeng Cang
In response to the unsafe driving of taxi drivers during the epidemic, the design and implementation of the driver's face registration and detection of whether the driver wears a mask, detection of the driver's fatigue physiological signals and multiple integration are designed. Target detection algorithm based on MobileNetV2 to realize mask detection. Combine MTCNN and Face-Net organically to realize driver's face login. The cerebellar neural network model is used to fuse the 12 fatigue monitoring signals EMG, EEG, etc. extracted by the simulated driving experiment platform to obtain a multi-integrated fatigue monitoring control model. After the fatigue driving multiple physiological indicators of the simulated driving platform, the technical model is studied and verified. It is concluded that the multiple fusion fatigue monitoring control model has higher accuracy than the traditional single signal monitoring.
针对疫情期间出租车司机的不安全驾驶,设计并实现了司机面部登记及司机是否戴口罩检测、司机疲劳生理信号检测及多重积分。基于MobileNetV2的目标检测算法,实现掩码检测。将MTCNN与face - net有机结合,实现驾驶员人脸登录。利用小脑神经网络模型对模拟驾驶实验平台提取的肌电、脑电等12个疲劳监测信号进行融合,得到多积分的疲劳监测控制模型。在对仿真驾驶平台的多项生理指标进行疲劳驾驶后,对技术模型进行了研究和验证。结果表明,多信号融合疲劳监测控制模型比传统的单信号监测具有更高的精度。
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引用次数: 0
Dual-Band BPF with Independently Controllable Center Frequencies Using Narrow-Closed-Loop Loaded Resonator 中心频率独立可控的窄带闭环负载谐振器双带BPF
Pub Date : 2020-12-11 DOI: 10.1109/TOCS50858.2020.9339700
Xingbing Ma
To gain separately controlled center frequencies and realize miniaturization, this article presents a dual-band bandpass filter (BPF) adopting narrow-closed-loop loaded resonator (NCLLR). By adjusting two narrow-side positions (namely the size of narrow-closed-loop), center frequencies of two passbands can be independently shifted in a certain area, respectively. Moreover, in order to achieve high selectivity in frequency characteristic domain, tapped-line coupling is applied to introduce three/four transmission zeroes (TZs) on either side of two target passbands. Good characteristics in passbands can be obtained by optimizing coupling gap and tapping position of stepped impedance I/O feed lines. Simulated and measured results are in good agreement.
为了获得单独控制的中心频率并实现小型化,本文提出了一种采用窄闭环负载谐振器(NCLLR)的双带带通滤波器。通过调整两个窄边位置(即窄闭环的大小),可以分别在一定区域内独立移动两个通带的中心频率。此外,为了在频率特征域中实现高选择性,采用抽头线耦合在两个目标带的两侧引入3 / 4个传输零点(TZs)。通过优化阶跃阻抗I/O馈线的耦合间隙和分接位置,可以获得良好的通带特性。仿真结果与实测结果吻合较好。
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引用次数: 0
Research on the Construction of Smart Factory for Mass Personalization Production 面向大规模个性化生产的智能工厂建设研究
Pub Date : 2020-12-11 DOI: 10.1109/TOCS50858.2020.9339751
Minghuo Xia, Yu'an He
According to the concept and characteristics of the mass personalization production mode, combined with the concept of “Internet + Manufacturing” and related technologies of the industry 4.0 strategy, this paper proposes an overall framework of a smart factory for mass personalization production, and analyzes the key technologies and functional modules of the framework in detail. Taking the production of personalization bicycles in a bicycle intelligent manufacturing laboratory as an example to illustrate the process of achieving mass personalization production.
本文根据大规模个性化生产模式的概念和特点,结合“互联网+制造”的概念和工业4.0战略的相关技术,提出了面向大规模个性化生产的智能工厂总体框架,并详细分析了该框架的关键技术和功能模块。以某自行车智能制造实验室生产个性化自行车为例,说明实现大规模个性化生产的过程。
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引用次数: 1
Application of Intelligent Clustering Algorithm in Image Processing 智能聚类算法在图像处理中的应用
Pub Date : 2020-12-11 DOI: 10.1109/TOCS50858.2020.9339705
Lu Rui
In order to solve the limitation of traditional K-means algorithm in dealing with large-scale data, a fast approximate k-means algorithm (FAKM) is proposed based on the approximate k-means algorithm (AKM) and the idea of classifying the cluster centers. The algorithm omits the cluster centers which only obtain a few samples in the AKM clustering results, and makes full use of the cluster centers with dense and stable samples in the cluster, In the iterative process, the number of samples and categories to be clustered is gradually reduced, which improves the speed of the algorithm and simplifies the clustering results. The FAKM algorithm is applied to the actual image retrieval system, and the experimental results show that the retrieval accuracy, retrieval time and clustering time of the system are greatly improved
为了解决传统K-means算法在处理大规模数据时的局限性,基于近似K-means算法和聚类中心分类的思想,提出了一种快速近似K-means算法(FAKM)。该算法省略了在AKM聚类结果中只获得少量样本的聚类中心,充分利用了聚类中样本密集且稳定的聚类中心,在迭代过程中,逐渐减少了待聚类的样本和类别数量,提高了算法的速度,简化了聚类结果。将FAKM算法应用到实际的图像检索系统中,实验结果表明,系统的检索精度、检索时间和聚类时间均有较大提高
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引用次数: 0
Research on Integrated Electro-mechanical (EMA)Servo System 集成机电伺服系统的研究
Pub Date : 2020-12-11 DOI: 10.1109/TOCS50858.2020.9339615
Helong Wang, Y. Jiang, Chong Qi, Junyan Li
This paper designs an integrated electromechanical servo system of control, drive and actuator to solve the technical problems of large weight and volume caused by the low degree of integration of traditional servo systems. It mainly includes the following aspects, the design composition and working principle of the integrated integrated electromechanical servo system, the simulation analysis of integrated integrated servo system, and the experimental research of integrated integrated servo system.
为解决传统伺服系统集成度低造成的重量大、体积大的技术问题,设计了一种集控制、驱动、执行器于一体的机电伺服系统。主要包括集成化机电伺服系统的设计组成及工作原理、集成化机电伺服系统的仿真分析、集成化机电伺服系统的实验研究等几个方面。
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引用次数: 2
An overview of biological data generation using generative adversarial networks 使用生成对抗网络生成生物数据的概述
Pub Date : 2020-12-11 DOI: 10.1109/TOCS50858.2020.9339748
Lin Liu, Yujing Xia, Lin Tang
Due to the high cost of biological data access and the privacy issues, collecting a large amount of biological data for training deep learning model is difficult in the field of biology. Concerning this issue, this article focuses on generative adversarial networks (GANs), which is a special type of deep learning model, and reviews their representative applications for generating biological data. We briefly introduced the working principle of GAN, and numerous applications to the areas of various biological data. In this paper, the types of biological data generated by GAN are categorized into two areas: biological sequences and two-dimensional data. These related studies indicated that GANs are able to explore the space of possible data configurations, and tuning the generated data to have specific target properties. This article will provide valuable insights and serve as a starting point for carrying out further studies for researchers.
由于生物数据访问的高成本和隐私问题,收集大量的生物数据用于训练深度学习模型在生物学领域是困难的。针对这一问题,本文重点介绍了一种特殊类型的深度学习模型——生成对抗网络(GANs),并综述了它们在生成生物数据方面的代表性应用。我们简要介绍了氮化镓的工作原理,以及在各种生物数据领域的众多应用。本文将GAN生成的生物数据类型分为生物序列和二维数据两大类。这些相关研究表明,gan能够探索可能的数据配置空间,并调整生成的数据以具有特定的目标属性。本文将为研究人员提供有价值的见解,并作为开展进一步研究的起点。
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引用次数: 0
A chromatography workstation built on a database and its applications 建立在数据库上的色谱工作站及其应用
Pub Date : 2020-12-11 DOI: 10.1109/TOCS50858.2020.9339701
Linjun Li, Bo Wang, Xinyong Zhu, Denggang Yin
Chromatography is a technique used to separate, quantify each component in a mixture and is widely used in chemistry and biology. In experiments, the control of the segments of the equipment, the acquisition of data, and the complex analysis of data determine the results of chromatography. The chromatography workstation is a unique tool for experimenters to make the quantitative analysis. However, the existed workstations inherit the traditional frameworks and only partially introduce the database to manage the experimental process. This paper introduces a chromatography workstation that is completely built on a database and can use high-efficient data sheets to implement a thorough procedure from the control of the equipment, data acquisition to data analysis, user management, and report printing, and therefore substantially improves the efficiency of the analysis and the maintainability of data.
色谱法是一种用于分离和定量混合物中每种成分的技术,广泛应用于化学和生物学。在实验中,设备各环节的控制、数据的获取以及数据的复杂分析决定了色谱的结果。色谱工作站是实验人员进行定量分析的独特工具。然而,现有的工作站继承了传统的框架,只是部分地引入了数据库来管理实验过程。本文介绍了一种完全建立在数据库基础上的色谱工作站,可以利用高效的数据表实现从设备控制、数据采集到数据分析、用户管理、报表打印的完整流程,从而大大提高了分析效率和数据的可维护性。
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引用次数: 0
Routing Algorithm in Networks on the Globe 全球网络中的路由算法
Pub Date : 2020-12-11 DOI: 10.1109/TOCS50858.2020.9339716
S. Bose
Packet switching of data in networks is done by either the distance-vector or the link-state routing protocols. These protocols use the Bellman-Ford and the Dijkstra's algorithms respectively for the least cost path from a source base station to a destination station. For inter-network transmission, the path-vector routing protocol is in use. With progress of time, the network topologies are becoming huge in size, requiring large demand on book keeping of routing tables and transmission of the data packets dynamically to several other stations of the net-work by broadcast, increasing the load on the network. Here, assuming the router stations to be terrestrially located with links along the ground, a large network is assumed to lie on a spherical surface, and so the shortest geodesic path from source to destination becomes a great circular arc. For fast transmission, the cost of a link to a node is multicast to its neighboring nodes only for selection of the path lying as close as possible to the geodesic line between the source and the destination. As the arrival and dispatch of data packets at a nodal station occurs randomly, the cost of a link is estimated in this paper by the waiting time of a queueing process. This process at a router station is thus modeled by the Markovian M/M/c model, where c is the number of servers at the router station. If other commercial fixed charge is involved for the use of a link, then that can be included in the total cost of a link. Finally, a method of search of a mobile destination is also presented using sphericity of the network. Algorithms for the near geodesic path, costs of links as waiting times and destination search in mobile environment are clearly presented.
网络中数据的分组交换由距离矢量或链路状态路由协议完成。这些协议分别使用Bellman-Ford和Dijkstra算法来寻找从源基站到目的基站的最低成本路径。对于网络间传输,使用路径矢量路由协议。随着时间的推移,网络拓扑结构变得越来越庞大,需要大量的路由表的记账,并且需要通过广播的方式将数据包动态地传输到网络的其他几个站点,从而增加了网络的负载。在这里,假设路由器站位于陆地上,链路沿着地面,假设一个大的网络位于球面上,因此从源到目的的最短测地线路径成为一个大圆弧。为了实现快速传输,只要选择尽可能靠近源和目的之间的测地线的路径,到一个节点的链路的代价就是多播到它的相邻节点。由于节点站的数据包到达和分发是随机发生的,因此本文通过排队过程的等待时间来估计链路的成本。因此,路由器站的这个过程用马尔可夫M/M/c模型来建模,其中c是路由器站的服务器数量。如果其他商业固定费用涉及使用一个链接,那么可以包括在一个链接的总成本。最后,提出了一种利用网络球度的移动目的地搜索方法。给出了移动环境下的近测地线路径算法、链路等待时间代价算法和目的地搜索算法。
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引用次数: 0
Prediction of Respirable Dust Concentration in Coal Mine Based on Neural Network 基于神经网络的煤矿呼吸性粉尘浓度预测
Pub Date : 2020-12-11 DOI: 10.1109/TOCS50858.2020.9339759
Lifeng Hui
Pneumoconiosis is the most important occupational disease in China, and respiratory respirable dust is the main cause of pneumoconiosis. It can effectively reduce the incidence of pneumoconiosis by improving the monitoring and supervision level of respiratory dust concentration in the workplace. In order to solve the shortcomings of obtaining the concentration of respirable dust in mines by methods such as sampling by respirable dust samplers and numerical simulation experiments, an artificial neural network is proposed to predict the concentration of respirable dust. The factors affecting the concentration of respirable dust in coal mining face were analyzed, and the neural network structure for predicting respirable dust was established in this paper. Through training by selecting measured data, it was found that the error between the predicted result and the measured concentration was less than 15%, which was better than the error of regulations of dust measuring instruments. The results of the study have a certain reference effect on the prediction and prevention of respiratory dust in coal mines and the reduction of the incidence of pneumoconiosis.
尘肺病是中国最重要的职业病,而呼吸性可吸入粉尘是尘肺病的主要病因。通过提高工作场所呼吸性粉尘浓度的监测和监管水平,可以有效降低尘肺病的发病率。针对目前矿山呼吸性粉尘采样和数值模拟实验等方法获取矿井呼吸性粉尘浓度的不足,提出了一种人工神经网络预测矿井呼吸性粉尘浓度的方法。分析了影响采煤工作面呼吸性粉尘浓度的因素,建立了预测呼吸性粉尘浓度的神经网络结构。通过选取实测数据进行训练,发现预测结果与实测浓度的误差小于15%,优于粉尘测量仪器规定的误差。研究结果对煤矿呼吸性粉尘的预测和防治,降低尘肺发病率具有一定的参考作用。
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引用次数: 0
期刊
2020 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS)
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