2018 10th International Conference on Communications, Circuits and Systems (ICCCAS)最新文献_第4页

An attempt to utilize LoRa for Intersatellite Communications 利用LoRa进行卫星间通信的尝试

2018 10th International Conference on Communications, Circuits and Systems (ICCCAS) Pub Date : 2018-12-01 DOI: 10.1109/ICCCAS.2018.8769213

Zhang Xuan, Zhang Xiaojie, Wang Shuo, Z. Ye

{"title":"An attempt to utilize LoRa for Intersatellite Communications","authors":"Zhang Xuan, Zhang Xiaojie, Wang Shuo, Z. Ye","doi":"10.1109/ICCCAS.2018.8769213","DOIUrl":"https://doi.org/10.1109/ICCCAS.2018.8769213","url":null,"abstract":"As individual satellite is limited by the mass and power constraints, formation or clusters contributing to the improved spatial and temporal resolution could be very useful in missions for space data collection or observation. Formation requires accurate orbital control for the system, while a cluster of spacecraft only requires cooperative control avoiding collision. Inter-satellite communication becomes critical for missions involving multiple satellites. As a solution for the Low–Power, Wide-Area Networks (LPWAN), LoRa technology is available for long-range and low-power communication in Internet of Things (IoT) areas. The purpose of this study is to take advantage of the LoRa technology to support autonomous operations with minimal human intervention in a wireless sensor network (WSN) building by a cluster of satellites. The paper will give an attempt to transplant IoT technology to space. We will design a typical space scenario for WSN and analyze the communication and topology requirement for its space application. Specific modification will be taken for the implementation of terrestrial IoT technology LoRa in the space cluster.","PeriodicalId":166878,"journal":{"name":"2018 10th International Conference on Communications, Circuits and Systems (ICCCAS)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132594600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

A Single Channel Subspace Speech Enhancement Approach Based on Optimal Lagrange Multiplier in Time Domain Constraint 时域约束下基于最优拉格朗日乘子的单信道子空间语音增强方法

2018 10th International Conference on Communications, Circuits and Systems (ICCCAS) Pub Date : 2018-12-01 DOI: 10.1109/ICCCAS.2018.8769246

Jingxian Tu, Guijiang Qin

引用次数: 0

A Programmable Network Management Architecture for Address Driven Network 地址驱动网络的可编程网络管理体系结构

2018 10th International Conference on Communications, Circuits and Systems (ICCCAS) Pub Date : 2018-12-01 DOI: 10.1109/ICCCAS.2018.8768952

Ziqiang Zhou, Changqing An, Jiahai Yang

引用次数: 0

A Low-Pass Filter Design Based on Split-Ring Resonator with Defected Ground Structure 基于缺陷接地结构的分环谐振器低通滤波器设计

2018 10th International Conference on Communications, Circuits and Systems (ICCCAS) Pub Date : 2018-12-01 DOI: 10.1109/ICCCAS.2018.8768937

Zhu Wei-gang, Wang Pei-zhang, Liu Han

引用次数: 0

Rocket Trajectory Real-time Generation System 火箭轨迹实时生成系统

2018 10th International Conference on Communications, Circuits and Systems (ICCCAS) Pub Date : 2018-12-01 DOI: 10.1109/ICCCAS.2018.8768948

Yan Liu, Zhen-hua Chen, Jian Wang, Weihuai Li

引用次数: 0

A Preconditioned Symmetric Successive Over Relaxation Method for Massive MIMO Signal Detection 海量MIMO信号检测的预条件对称逐次过松弛方法

2018 10th International Conference on Communications, Circuits and Systems (ICCCAS) Pub Date : 2018-12-01 DOI: 10.1109/ICCCAS.2018.8769292

Xin-yi Wang, Zhongtao Zhu, Xiaozhang Zhu

引用次数: 0

Rocket Image Classification Based on Deep Convolutional Neural Network 基于深度卷积神经网络的火箭图像分类

2018 10th International Conference on Communications, Circuits and Systems (ICCCAS) Pub Date : 2018-12-01 DOI: 10.1109/ICCCAS.2018.8769176

Liang Zhang, Zhen-hua Chen, Jian Wang, Zhaodun Huang

{"title":"Rocket Image Classification Based on Deep Convolutional Neural Network","authors":"Liang Zhang, Zhen-hua Chen, Jian Wang, Zhaodun Huang","doi":"10.1109/ICCCAS.2018.8769176","DOIUrl":"https://doi.org/10.1109/ICCCAS.2018.8769176","url":null,"abstract":"In the field of aerospace measurement and control field, optical equipment generates a large amount of image data. Thus it has great research value for how to process a huge number of images data quickly and effectively. With the development of deep learning, great progress has been made in the task of image classification. This paper attempts to classify the task images generated by optical measurement equipment using the deep learning method. Firstly, based on residual network, a general deep learning image classification framework, a binary image classification network namely rocket image and other image is built. Secondly, on the basis of the binary cross entropy loss function, the modified loss function is used to achieves a better generalization effect on those images difficult to classify. Then, the 2689 visible image data downloaded from optical equipment is randomly divided into training set, validation set and test set. The data augmentation method is used to train the binary classification model on a relatively small training set. The optimal model weight is selected according to the loss value on the validation set. Finally, the trained model achieved a 100% precision and a 83.33% recall on the test set of 97 images which include 24 rockets images. This paper has certain value for exploring the application of deep learning method in the intelligent and rapid processing of optical equipment task image in aerospace measurement and control field.","PeriodicalId":166878,"journal":{"name":"2018 10th International Conference on Communications, Circuits and Systems (ICCCAS)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130358011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Exploiting Semantic Structured Relationships Using Graph Models for Semantic Annotations 利用语义注释的图模型开发语义结构化关系

2018 10th International Conference on Communications, Circuits and Systems (ICCCAS) Pub Date : 2018-12-01 DOI: 10.1109/ICCCAS.2018.8769236

Yuhua Fan, Liya Fan

{"title":"Exploiting Semantic Structured Relationships Using Graph Models for Semantic Annotations","authors":"Yuhua Fan, Liya Fan","doi":"10.1109/ICCCAS.2018.8769236","DOIUrl":"https://doi.org/10.1109/ICCCAS.2018.8769236","url":null,"abstract":"This paper proposes a novel and efficient approach to exploit semantic relationships using semantic modeling for semantic annotation tasks. The existing methods learn knowledge of concepts and their relationships based on context cues. Starting with a large set of objects detectors, the proposed method refines the initial annotation results using the learned semantic relationships, which can preserve the consistency and effective of the annotation over a semantic graph. Different from the existing graph learning methods which capture relations among data instances, the semantic graphs treat concepts as nodes and concept affinities as the weights of edges. Particularly, the proposed method can not only learn the semantic cues effectively through the semantic graph models to improve the annotation results, but also can adapt the concept affinities to unseen images. The method provides a means to handle structured relationship change between training and test data, which occurs very often in semantic annotation tasks. Our experiments on NYUv2 demonstrate that the proposed approach outperform the state-of-the-art algorithms.","PeriodicalId":166878,"journal":{"name":"2018 10th International Conference on Communications, Circuits and Systems (ICCCAS)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115067848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Study of the Influence of Solder Thickness on the Thermal Resistance of Power VDMOS Device Package 焊料厚度对功率VDMOS器件封装热阻影响的研究

2018 10th International Conference on Communications, Circuits and Systems (ICCCAS) Pub Date : 2018-12-01 DOI: 10.1109/ICCCAS.2018.8769261

Wei Gao, Yining Ma, Zhaofeng Sun, Pengfei Yin, M. Ren, Jin-ping Zhang, Zehong Li, Bo Zhang, W. Du

引用次数: 1

The Research on Evolutionary Hardware Evolution Algorithm for Stall Effect 失速效应的进化硬件进化算法研究

2018 10th International Conference on Communications, Circuits and Systems (ICCCAS) Pub Date : 2018-12-01 DOI: 10.1109/ICCCAS.2018.8768921

Guo Zhen-xing, Xu Li-zhi, Song Xue-jun, Li Chong-cun, Li Ruoyi

{"title":"The Research on Evolutionary Hardware Evolution Algorithm for Stall Effect","authors":"Guo Zhen-xing, Xu Li-zhi, Song Xue-jun, Li Chong-cun, Li Ruoyi","doi":"10.1109/ICCCAS.2018.8768921","DOIUrl":"https://doi.org/10.1109/ICCCAS.2018.8768921","url":null,"abstract":"The fitness values increase rapidly in the early stages of circuit evolution design, while the fitness values grew slowly or stagnated, at the later stages of the evolution. The phenomenon is called the \"Stalling effect\" phenomenon. In response to this problem, the evolutionary redundancy repair technique of circuit evolution design is proposed. The repair module is built using the redundant nodes and activated nodes at the later of circuit evolution design. The circuit with partially correct functions is evolved using Cartesian Genetic Programming at the early stages of the algorithm. At the later stages of the algorithm, the repair modules repair the error output of minimum items, ensure the correct output of the minimum items not modified meanwhile. The target circuit obtained traditional repair techniques include the additional repair circuit modules and the partial correct circuit. The evolutionary redundancy repair technique combines the repair circuit module and the evolution circuit. The repair module is built through the redundant nodes and the activated nodes. The experiment of a three-bit multiplier is researched. The results show that the rate of convergence of evolution program is greatly accelerated.","PeriodicalId":166878,"journal":{"name":"2018 10th International Conference on Communications, Circuits and Systems (ICCCAS)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116469288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0