2018 International Conference on Information Networking (ICOIN)最新文献_第10页

Reliable vehicle-to-vehicle communication using spectrum environment map 利用频谱环境图实现可靠的车对车通信

2018 International Conference on Information Networking (ICOIN) Pub Date : 1900-01-01 DOI: 10.1109/ICOIN.2018.8343131

S. Tsurumi, T. Fujii

引用次数: 6

Analysis of world trends in the field of cloud technology 云技术领域的世界趋势分析

2018 International Conference on Information Networking (ICOIN) Pub Date : 1900-01-01 DOI: 10.1109/ICOIN.2018.8343188

A. Bataev, D. Rodionov, Darya A. Andreyeva

{"title":"Analysis of world trends in the field of cloud technology","authors":"A. Bataev, D. Rodionov, Darya A. Andreyeva","doi":"10.1109/ICOIN.2018.8343188","DOIUrl":"https://doi.org/10.1109/ICOIN.2018.8343188","url":null,"abstract":"The financial and economic crisis that erupted in 2008 gradually moved into a protracted recession, which led to the slowdown in the economy, instability in commodity markets, increased unemployment. Many companies have faced the need of decrease in expenses; the vector of development was directed to introduction of new innovative technologies in the sphere of information and communication technologies. One of the promising directions in the area of information management is the adoption and use of cloud technology that have been widespread both in the segment of small and medium-sized businesses and among large corporations in the last decade. One of attractive advantages to business is significant cost cutting under introduction and use of cloud computing. The paper analyzes both traditional models of cloud computing and new innovative models that have spread over the past few years. The tendencies and perspectives of the world cloud computing market development are considered. The dynamics of all market segments extension is assessed, leaders in the implementation of cloud computing are identified. Spheres of cloud computing use by branches of economy are examined. On the basis of carried out analysis further ways of development of cloud technology are defined.","PeriodicalId":228799,"journal":{"name":"2018 International Conference on Information Networking (ICOIN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129496335","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: 8

Intelligent accident detection classification using mobile phones 手机智能事故检测分类

2018 International Conference on Information Networking (ICOIN) Pub Date : 1900-01-01 DOI: 10.1109/ICOIN.2018.8343170

I. Zualkernan, F. Aloul, Fayiz Basheer, Gurdit Khera, S. Srinivasan

引用次数: 10

Enhanced cluster-based CoAP in Internet-of-Things networks 物联网网络中基于集群的增强CoAP

2018 International Conference on Information Networking (ICOIN) Pub Date : 1900-01-01 DOI: 10.1109/ICOIN.2018.8343199

D. Choi, Joong-Hwa Jung, S. Koh

引用次数: 4

Analysis of deployment approaches for virtual customer premises equipment 虚拟客户端设备的部署方法分析

2018 International Conference on Information Networking (ICOIN) Pub Date : 1900-01-01 DOI: 10.1109/ICOIN.2018.8343127

Tri-Hai Nguyen, Tri Minh Nguyen, Myungsik Yoo

引用次数: 9

Top-down parsing for Neural Network Exchange Format (NNEF) in TensorFlow-based deep learning computation 基于tensorflow的深度学习计算中神经网络交换格式(NNEF)的自顶向下解析

2018 International Conference on Information Networking (ICOIN) Pub Date : 1900-01-01 DOI: 10.1109/ICOIN.2018.8343173

Bokyung Seo, Myungjae Shin, Yeong Jong Mo, Joongheon Kim

{"title":"Top-down parsing for Neural Network Exchange Format (NNEF) in TensorFlow-based deep learning computation","authors":"Bokyung Seo, Myungjae Shin, Yeong Jong Mo, Joongheon Kim","doi":"10.1109/ICOIN.2018.8343173","DOIUrl":"https://doi.org/10.1109/ICOIN.2018.8343173","url":null,"abstract":"As the demand for neural network technology grows in recent years, there is an increasing interest in the standardization related to the technology, and research on standardization independent file format for data exchange between deep learning data and learning systems is underway. In this paper, we introduce a more reasonable standardized method called the NNEF. Neural Network Exchange Format (NNEF) is one of the standardized methods of neural network. Neural network graph defined by NNEF is possible to exchange various neural network configuration platform. Accordingly, NNEF provides the simple process of using constant format to create a network and train network, and it has a significant impact on configuring neural network used in cross-platform. Tensorflow framework is the most common and widely adopted today. The Tensorflow provide independent frameworks for neural network configuration. In TensorFlow frameworks, artificial neural networks are represented by computational graphs. In addition, represented data (tensor) are shared among nodes. Therefore, a standardized method is desired because the method of representing a computational graph in each framework is all different. This paper introduces the Neural Network Exchange Format (NNEF) at first and then presents the purpose of such an exchange format, i.e., enabling neural network training in deep learning frameworks to be executed in a standardization manner. The aim of this approach is to describe neural network computations in a platform independent manner, while enabling the possibility for inference engines to highly optimize the run-time execution.","PeriodicalId":228799,"journal":{"name":"2018 International Conference on Information Networking (ICOIN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121359939","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: 9

Modified rendezvous scheme with inferring access channel probability of slave by master 用主节点来推断从节点接入信道概率的改进交会方案

2018 International Conference on Information Networking (ICOIN) Pub Date : 1900-01-01 DOI: 10.1109/ICOIN.2018.8343115

Hayato Soya, O. Takyu, K. Shirai, F. Sasamori, S. Handa, M. Ohta, T. Fujii

引用次数: 0

Intelligent sensor network for fence protection 用于围栏保护的智能传感器网络

2018 International Conference on Information Networking (ICOIN) Pub Date : 1900-01-01 DOI: 10.1109/ICOIN.2018.8343150

B. Voneki

引用次数: 0

An energy and link aware next node selection protocol for body area networks 基于能量和链路感知的体域网络下一节点选择协议

2018 International Conference on Information Networking (ICOIN) Pub Date : 1900-01-01 DOI: 10.1109/ICOIN.2018.8343213

K. Qureshi, F. Bashir, A. Abdullah

引用次数: 14

Novel Korean finger language recognition using EMG and motion sensors 使用肌电和运动传感器的新型韩语手指语言识别

2018 International Conference on Information Networking (ICOIN) Pub Date : 1900-01-01 DOI: 10.1109/ICOIN.2018.8343238

Inseok Yeo, Hyun-Chool Shin

引用次数: 3