中国工程院院刊《信息与电子工程前沿（英文）》 “智能可视分析”专题 征稿通知 2019年7月31日截稿 最近，以深度学习为代表的人工智能技术在计算机视觉、自然语言处理、语音识别等领域取得了突破性进展。深度学习的巨大成功激发了可视化领域“AI for VIS”的研究趋势，推动了若干重要进展。首先，最近的语义嵌入技术和深度神经网络技术带来了复杂数据的新表示方法，在时空数据、事件序列数据可视分析等若干案例中展现了揭示潜在语义的功能。其次，计算机视觉领域中图像内容理解等技术的进步，启发了数据驱动的质量度量等可视化理解的研究。再次，可视化的主要任务是生成数据的高质量可视表达；针对这一任务，AI技术催生了数据驱动的可视化设计方法。此外，还有预测式可视分析等大量可视分析应用受益于AI技术的进步。 但在可视化中应用AI技术仍然存在着理论和实践中的若干难题。首先，训练数据获取困难。计算机视觉中可以相对容易地获取大量有标签的图像数据。但在可视化中，很少有针对专门任务的有标签数据集。其次，自然图像中的视觉对象往往具有稳定的外形轮廓和纹理特征，但信息可视化中的视觉对象的特征与之存在较大差异。当前流行的深度神经网络是否能够用于信息可视化任务还存在争议。再次，当前的AI模型往往需要向量化的表达，而针对特定可视化任务的设计空间的形式化表达仍然是一个需要探索的问题。最后，一些交互可视分析任务本质上就是交互式、渐进式的，如何融合AI技术与交互技术仍然是一个挑战。 针对以上需求，为推动我国在智能可视分析领域的研究工作，为数据分析和可视化提供先进理论和应用成果，中国工程院院刊《信息与电子工程前沿（英文）》（FITEE）邀请潘云鹤院士担任主编，浙江大学CADCG国家重点实验室陈为教授担任执行主编，筹备“智能可视分析”专题。 为推动国际合作，专题特别鼓励中国学者与国外学者合作投稿。 专题编委会： 主编： 潘云鹤 教授，中国工程院院士，浙江大学 执行主编： 陈为 教授，浙江大学CADCG国家重点实验室 编委（按姓氏字母序）： Steffen Koch 博士 ， University of Stuttgart， 德国 Tobias Schreck 教授， Graze University of Technology， 奥地利 Han-Wei Shen 教授， The Ohio State University， 美国 夏佳志 副教授，中南大学，中国 Cong Xie 博士，Facebook， 美国 Ye Zhao 教授，Kent State University， 美国 联系人： 中南大学，夏佳志，xiajiazhi@csu.edu.cn FITEE编辑部：翟自洋，jzus_zzy@zju.edu.cn，86-571-88273162 专题学科范畴、文章类型、投稿要求、期刊简介等，请见下方Call for Papers。 欢迎国内外相关领域专家、学者踊跃投稿！ FITEE Special Issue on AI for Visualization Call for Papers Submission Deadline: July 31, 2019 Artificial intelligence (AI) techniques , such as deep learning, have achieved breakthrough in various tasks in recent years, such as computer vision, natural language processing and speech recognition. The great success of AI techniques has inspired a wide range of visualization applications. First, while data transformation is one of the core steps in visualization, recent embedding techniques and deep neural networks provide new representations for complex data, disclosing latent features and enabling efficient operations. Second, inspired by recent advances of understanding visual contents in computer vision, researchers have begun to introduce AI in visualization, such as data-driven quality metrics. Third, while the main goal of visualization is to create new visual representation, data-driven design has become a new methodology of visualization generation. In addition, a great many of applications, such as predictive visual analytics, have also been facilitated by recent AI techniques. Introducing recent AI techniques into visualization applications, however, yields new methodological and practical challenges that need to be addressed. First, unlike computer vision that can collect training data conveniently, high-quality training data for specific visualization tasks are scare. Second, visual contents in information visualization are rather different from natural visual objects. The latter often have specific contours and textures. Therefore, despite the high performance of deep neural networks in understanding natural images and videos, there are still debates on the applicability of deep neural networks in information visualization. Third, well-formulated design spaces for specific visualization suitable for vectorized representation of deep learning are yet to be investigated. Finally, many tasks of visual analytics are inherently interactive and progressive, integrating user interaction into learning process is also a challenge. For this special issue, we are looking for submissions that describe algorithms, data representations, tools and systems for visualization tasks based on AI techniques. We also welcome evaluations providing inspiring guidelines on the use of AI techniques in visualization and surveys providing comprehensive discussions on current development of AI for VIS. More specifically, we are looking for contributions that demonstrate practical impact of AI on (but not limited to) the following topics: Data synthesis for training of specific visualization tasks Data-driven quality metrics for visualization Data-driven design of visualization Deep learning model for visualization contents Interactive AI techniques for visual analytics Predictive visual analytics To promote international cooperation, we encourage submissions that are co-authored by domestic and international researchers. We also highly recommend the submission of multimedia to accompany each article as it may significantly increase the visibility, downloads and citations. All submitted manuscripts must be written in English and must not be under consideration elsewhere for publication. The authors must follow the FITEE guidelines (http://www.jzus.zju.edu.cn/manuscript.php) for preparation of their manuscripts. Either Word or LaTeX format is acceptable. When Word is used, please keep the layout of the text as simple as possible, e.g., single column, 1.5 lines spacing, 10.5 pt font size, and Times New Roman font. When LaTeX is used, a template is available at http://www.jzus.zju.edu.cn/download/FITEE_LaTex_template.zip Templates for accepted papers: Word: http://www.jzus.zju.edu.cn/download/FITEE_sample.doc LaTeX: http://www.jzus.zju.edu.cn/download/FITEE_LaTex_template.zip (At the initial submission stage, authors do not need to use these templates. Only when asked to revise manuscripts after peer reviews, these templates should be used.) FITEE is an international peer-reviewed journal launched by the Chinese Academy of Engineering (CAE) and Zhejiang University, and co-published by Springer Zhejiang University Press. FITEE aims to publish the latest implementation of applications, principles, and algorithms in the broad area of Electrical and Electronic Engineering. All articles published in this special issue will be indexed by SCI-E and will be available from http://www.springer.com/computer/journal/11714, www.jzus.zju.edu.cn, as well as http://engineering.cae.cn/fitee. Please note that all articles will undergo international peer review and Crosscheck processes before acceptance, to ensure that the special issue is of high quality, original, and thought-provoking. We look forward to your contribution to this special issue. Please send your manuscript via http://www.editorialmanager.com/zusc/. Remember to choose article type “S.I.-AI4VIS”. Manuscript submission by July 31, 2019 Acceptance notification by Nov. 15, 2019 Publication date: Jan. 31, 2020 Editorial Board: Editor-in-Chief: Prof. Yunhe Pan Academician of CAE, Zhejiang University, China Executive Lead Editor: Prof. Wei Chen CADCG State Key Lab, Zhejiang University, China Editors (in alphabetical order by last name): Dr. Steffen Koch University of Stuttgart, Germany Prof. Tobias Schreck Graze University of Technology, Austria Prof. Han-Wei Shen The Ohio State University, USA Assoc. Prof. Jiazhi Xia Central South University, China Dr. Cong Xie Facebook, USA Prof. Ye Zhao Kent State University, USA For inquiries regarding this special issue, please contact: Jiazhi Xia Central South University, China E-mail: xiajiazhi@csu.edu.cn Editorial Office: Ziyang Zhai (Managing Editor) jzus_zzy@zju.edu.cn 86-571-88273162 --------------------- 首发于微信公众号“信息与电子工程前沿FITEE”（fitee_cae)。 作者：陈为、夏佳志，等。
中国工程院院刊《信息与电子工程前沿（英文）》（ SCI-E 收录）拟于 2017 年第二季度推出“ 5G 无线通信系统与技术”专辑，由北京邮电大学张平教授担任客座主编，以约稿 + 自然投稿的方式组织内容，现面向海内外相关领域学者征稿。 投稿截止 ： 2017 年 1 月 10 日 出版日期 ： 2017 年第 6 期（ 6 月初出刊） 网投地址 ： http://www.editorialmanager.com/zusc/ （投稿时请选择文章类型为“ 5G ”） 投稿咨询 ： jzus_zzy@zju.edu.cn 以下为征稿信： FITEE Special Issue on 5G Wireless Communication Systems and Technologies CALL FOR PAPERS Recently, the explosive growth of data traffic due to ubiquitous smart devices has accelerated the current 4G systems towards yet more technological evolution. Indeed, we are now moving into the 5G era as we reach towards 2020 and beyond. Compared with 4G mobilecommunications, 5G needs to meet extremely high performance requirements in more diverse scenarios. Specifically, the requirements of 5G systems include: a user-experienced data rate over 0.1 -1 Gbps, a connection density of 1 million/km 2 , traffic volume density at tens of Tbps/km 2 , E2E latency at ms level, peak data rates at tens of Gbps, and a mobility of 500 km/h. These requirements are challenging and may even be conflicting, and need the design of new network architectures, new radio access techniques, and new transmission waveforms. In recent years, both academia and industry have shown a lot of interest in the key techniques of 5G systems, such as massive MIMO, cloud radio access, mm-wave communications, non-orthogonal multiple access, and network function virtualization. However, there are still many technical challenges to overcome before the deployment of 5G. Hence, the objective of this special issue is to attract contributions from both academia and industry to motivate discussions on advanced and innovative techniques for 5G. Authors are encouraged to submit different types of articles, e.g., perspective articles, communications articles, review articles, and research articles, on recent advances of key techniques for 5G, including but not limited to the following topics: - mm-wave communication techniques for 5G - Massive MIMO techniques - Spectrum sharing and aggregation techniques for 5G - Security and privacy issues in 5G - Heterogeneous networks for 5G - Interference cancellation in full-duplex communications - Resource allocation in ultra-dense/multi-tier networks - Interference-mitigation techniques for 5G - Massive access techniques for 5G - Ultra-reliable and low-latency coding and modulationtechniques for 5G Frontiers of Information Technology Electronic Engineering ( FITEE ), is an international peer-reviewed journal launched by Chinese Academy of Engineering (CAE) and Zhejiang University, and co-published by Springer Zhejiang University Press. FITEE aims to publish the latest implementation of applications, principles, and algorithms in the broad area of Electrical and Electronic Engineering. Allarticles published in this special issue will be indexed by SCI-E and will be available from Springerlink ( http://www.springe r.com/computer/journal/11714 ), www.zju.edu.cn/jzus, as well as http://engineering.cae.cn/fitee. Please note that, however, before acceptance all articles must undergo the international peer reviews and cross check processes, to ensure a high quality and original special issue. We would be delighted if you could confirm your contribution to this special issue. Please send your paper via http://www.editorialmanager.com/zusc/ based on the following schedule: Manuscript submission: Jan. 10, 2017 Acceptance notification: Apr. 10, 2017 Publication date: June, 2017 Guest Editors Prof. Ping Zhang, Beijing University of Posts and Telecommunications Prof. Shuguang Cui, University of California, Davis Prof. Kai-Kit Wong, University College London Prof. Zhaoyang Zhang, Zhejiang University Dr. Nan Yang, Australian National University Dr. Himal A. Suraweera, University of Peradeniya ---------------------------------- Frontiers of Information Technology Electronic Engineering ( FITEE ) 前身为 Journal of Zhejiang University-SCIENCEC (Computers Electronics) ， SCI-E 收录。 2015 年改为现名，由中国工程院与浙江大学共同主办，浙江大学出版社与 Springer 合作出版，为中国工程院院刊。出版计算机、信息、电力、电子领域原创研究论文、综述、科学快报、个人视点、新技术 / 方法，等。欢迎国内外学者赐稿，网投地址为 http://www.editorialmanager.com/zusc
中国工程院院刊《信息与电子工程前沿（英文）》推出 “ 未来网络 之 软件定义网络（ SDN ） ” 专辑 经过 40 多年发展，互联网已渗透到社会经济生活的各个方面。在其不断发展和演进的过程中，随着网络规模扩大，流量激增，传统基于分层协议的网络体系架构在诸如骨干网络、数据中心网络、移动网络等环境下产生了各式各样的问题。如何改变现有僵化的网络体系架构，以适应不断兴起的新型应用需求，成为未来网络技术发展的关键。 软件定义网络（ Software-Defined Networking ， SDN ）技术起源于 2006 年斯坦福大学 Clean Slate 项目组。 SDN 技术的核心是将网络的控制平面和转发平面分离，通过集中式的控制平面来为网络提供一种全新的、基于软件可编程的开放体系架构。它的出现很快得到学术界和工业界的关注，并带来新一轮网络技术变革，成为解决未来网络发展问题的关键技术之一。在学术界， SDN 蝉联了 2008 和 2009 年的 SIGCOMM“ 最佳演示 ” 奖，并被麻省理工学院和多家咨询机构评选为 IT 领域未来十大技术之一。在工业界， SDN 技术帮助谷歌公司将其覆盖全球的数据中心互连网络（ B4 ）的平均链路利用率从 30% 提升到 95% 以上，让人们看到了 SDN 的巨大潜力。美国电信运营商 ATT 提出的 Domain 2.0 计划，迈出了 SDN 在运营商网络部署的第一步，随后中国三大运营商也成功实现了 SDN 的小规模商用。 SDN 技术正在加速从学术走向产业， SDN 在云服务提供商和通信服务提供商的数据中心部署比例将从 2015 年的 20% 提高到 2016 年的 60% ；到 2019 年，应用于数据中心和企业局域网的 SDN 交换机和控制器收入将达到 122 亿美元。 在 SDN 技术快速发展的背景下，中国工程院院刊《信息与电子工程前沿（英文）》策划了 “ 未来网络之软件定义网络 ” 专辑，通过专题约稿和严格评审，选取了一些代表 SDN 研究前沿或热点的主题论文，涵盖了网络可扩展性、网络虚拟化、网络管理、 SDN 应用等诸多方面。例如，在 SDN 扩展性方面，由于单个控制器容易造成单点故障、高时延等问题，难以在骨干网等大网中落地部署， SDN 控制平面正逐步开始向层级化、分域化的方向演进。西安交通大学的 Peng Zhang 团队、大连海事大学的 Zhi-yang Li 团队和国家数字交换系统工程技术研究中心的 Gang Xiong 团队分别通过研究新的多控制器架构、新的控制器放置算法和虚拟服务放置算法，更加有效地完成多控制器协同控制、优化控制时延和服务时延。在网络虚拟化技术方面， SDN 使得虚拟网络的落地部署成为可能，并逐步成为云数据中心中网络虚拟化、租户网络隔离的关键技术。空军工程大学的 Shui-qing Gong 团队提出了新的虚拟网络映射算法来解决 SDN 网络虚拟化问题。在网络自动化管理方面，传统网络是封闭和非智能的，缺少自动排错与恢复的能力，需要人为参与来保障网络的可靠性，而 SDN 具有集中式控制、获取全局信息的能力，为网络添加了智能的大脑。加拿大卡尔顿大学的 Chung-Horng Lung 团队利用 SDN 技术完成了多播中的自诊断与自恢复，使网络变得更加可靠。在 SDN 应用方面，中国科学技术大学的 JianYang 团队和中国人民解放军理工大学的 MingChen 团队分别研究了新的多播调度算法和流量调度算法，为语音和视频等业务提供可靠的时延与带宽保障。美国奥本大学的 Shiwen Mao 团队则探讨了 SDN 在未来无线通信中的潜在应用以及未来研究方向。 感谢入选论文的作者们出色的工作以及国际同行评审人宝贵的意见。特别感谢三位客座编辑 —— 北京邮电大学的黄韬博士、加拿大卡尔顿大学的 F. Richard Yu 博士和工程院刘韵洁院士 —— 为专辑筹备付出诸多心力。期待我们选取的论文能够推动对这些前沿或热点技术的研究和探索，特别是能够服务于我国网络领域的发展需求，推动我国互联网向更加智能、安全的方向发展。 全文请见： http://www.zju.edu.cn/jzus/issue.php?issueid=458 Frontiers of InformationTechnology Electronic Engineering (FITEE) 的前身为 Journal of Zhejiang University-SCIENCE C (Computers Electronics) ， SCI-E 收录。 2015 年改为现名，由中国工程院与浙江大学共同主办，浙江大学出版社与 Springer 合作出版，为中国工程院院刊。出版计算机、信息、电力、电子领域原创研究论文、综述、科学快报、个人视点、新技术 / 方法，等。欢迎国内外学者赐稿，网投地址为 http://www.editorialmanager.com/zusc ------------------------ ------- ------- 首发于微信公众号 zdxbywb
标签: FITEE
