Security and Communication Networks is part of an exciting new pilot partnership between Wiley and Hindawi. From 1st January 2017, the journal will become fully open access. Security and Communication Networks will remain a Wiley title but will be published and hosted by Hindawi, and will benefit...
Security and Communication Networks provides a prestigious forum for the R&D community in academia and industry working at the interdisciplinary nexus of next generation communications technologies for security implementations in all network layers. About this journal Editor spotlight Chief Editor Dr Di Pietr...
Security And Communication Networks近三年发文量分别为183、241、718,其中国人发文373篇,占比约52.00%。 审稿周期 据网友经验分享,Security And Communication Networks平均审稿周期52天。 出版费用 Security And Communication Networks是一份同行评议的开放获取期刊,所有公开发表的文章都将立即永久免费供所有人阅读、下载、...
Security and Communication Networks 期刊简称 SCN Print ISSN 1939-0114 Online ISSN 1939-0122 期刊出版社 Hindawi 是否开放获取 Open Access,OA 是 官网地址 https://www.hindawi.com/journals/scn/ 期刊所属领域 网络与信息安全 期刊简介 安全与通信网络(Security and Communication Networks)是一份国际期刊,发表...
Security and Communication Networks《安全与通信网络》 (官网投稿) 简介 期刊简称SECUR COMMUN NETW 参考译名《安全与通信网络》 核心类别 目次收录(知网),外文期刊, IF影响因子 自引率 主要研究方向计算机科学-COMPUTER SCIENCE, INFORMATION SYSTEMS计算机:信息系统;TELECOMMUNICATIONS电信学 Security and Communication ...
《安全和通信网络》(Security And Communication Networks)是一本以COMPUTER SCIENCE, INFORMATION SYSTEMS-TELECOMMUNICATIONS综合研究为特色的国际期刊。该刊由Hindawi出版商创刊于2008年,刊期Bimonthly。该刊已被国际重要权威数据库SCIE收录。期刊聚焦COMPUTER SCIENCE, INFORMATION SYSTEMS-TELECOMMUNICATIONS领域的重点研究和前沿...
Security And Communication Networks ISSN:1939-0114 ESSN:1939-0122 国际标准简称:SECUR COMMUN NETW 出版地区:ENGLAND 出版周期:Bimonthly 研究方向:COMPUTER SCIENCE, INFORMATION SYSTEMS - TELECOMMUNICATIONS 出版年份:2008 语言:English 是否OA:开放 学科领域...
Security and Communication Networks《安全与通信网络》 (官网投稿)的纠错信息 各位老师、同学们好: 全站一万多个期刊,我们都是每天人工滚动核实、更新其投稿信息,循环一遍大概需要七八个月时间,其间肯定会有变更了的期刊信息难以被及时发现,为保证信息准确不耽误大家投稿,欢迎您积极参与纠错!为表感谢,凡对国内期刊以下...
点击这里查看 Security and Communication Networks 的JCR分区、影响因子等信息 Volume 2020, 2020 Wearable Sensor-Based Human Activity Recognition Using Hybrid Deep Learning Techniques. Huaijun Wang Jing Zhao Junhuai Li Ling Tian Pengjia Tu Ting Cao Yang An Kan Wang Shancang Li 原文链接 谷歌学术...
United States Patent US8875236 Note: If you have problems viewing the PDF, please make sure you have the latest version ofAdobe Acrobat. Back to full text