International Journal of Systems, Control and Communications
- Editor in Chief
- Prof. Jianbo Su
- ISSN online
- ISSN print
- 4 issues per year
- CiteScore 1.3 (2021)
A fundamental, omnipresent feature of the global information age is that cyber-capabilities, e.g. computing, communication and control, are inherently embedded in numerous physical/engineered systems from the nano-world to large-scale systems-of-systems. Many scientific/technological challenges require intensive multidisciplinary studies, calling for new formulations, techniques and innovative solutions from a spectrum of communities in systems engineering/control/communications. IJSCC offers a vibrant discussion forum in this interdisciplinary area, especially communication systems augmented by control techniques and control systems whose components are interconnected via communication networks.
Topics covered include
- Information-based control systems
- Distributed and cooperative control systems
- Networked control systems (NCS)
- Wired and wireless networks
- Network control (admission/flow/congestion control, etc.)
- Network scheduling and bandwidth allocation
- Informatics in control and communication
- Cyber-physical systems (CPSs)
- Sensor and actuator networks
- Multi-agent systems
- Case studies and applications
- Disturbance rejection in control and communications
The main objectives of IJSCC are to form a vibrant international forum to report on the interdisciplinary developments of theoretical studies, modelling and design methods, computational algorithms and successful applications. Furthermore, it aims at establishing an effective channel of communication between systems engineers, control scientists and communication experts from industries, academe and research laboratories within this field. It particularly welcomes new theoretical results with practical applications.
IJSCC provides a vehicle to help professionals, academics and researchers working in the interdisciplinary field of systems, control and communications engineering to disseminate valuable knowledge and novel findings.
IJSCC publishes original papers, review papers, technical reports, book reviews, notes and commentaries. Special Issues devoted to important and timely topics in integrated control and communication systems will occasionally be published.
IJSCC is indexed in:
- Scopus (Elsevier)
- Compendex [formerly Ei] (Elsevier)
- Academic OneFile (Gale)
- ACM Digital Library
- cnpLINKer (CNPIEC)
- Expanded Academic ASAP (Gale)
- Google Scholar
- Info Trac (Gale)
- Inspec (Institution of Engineering and Technology)
IJSCC is listed in:More journal lists/directories...
- Pedrycz, Witold, University of Alberta, Canada
Editor in Chief
- Su, Jianbo, Shanghai Jiao Tong University, China
- Guo, Ge, Northeastern University, China
Editorial Board Members
- Castelano, Giovanna, University of Bari, Italy
- Chen, Long, University of Macau, China
- Dhaka, Arvind, Manipal University Jaipur, India
- Ding, Lei, Nanjing University of Posts and Telecommunications, China
- Ekel, Petr, Pontifical Catholic University of Minas Gerais, Brazil
- Gao, Weinan, Northeastern University, China
- Gao, Zhenyu, Northeastern University, China
- Jiang, Zhong-Ping, Polytechnic Institute of New York University, USA
- Koczy, Laszlo T., Budapest University of Technology and Economics, Hungary
- Lim, Sangsoon, Sungkyul University, South Korea
- Liu, Huaping, Tsinghua University, China
- Lu, Jun-Guo, Shanghai Jiao Tong University, China
- Mo, Huadong, University of New South Wales, Australia
- Parthasarathy, Velusamy, Karpagam Academy of Higher Education, India
- Sahu, Aditya Kumar, Amrita Vishwa Vidyapeetham, India
- Shen, Yantao, University of Nevada, USA
- Wang, Kevin I-Kai, University of Auckland, New Zealand
- Watada, Junzo, Waseda University, Japan
- Wen, Shixi, Dalian University, China
- Xiang, Linying, Northeastern University, China
- Xue, Wenchao, Academy of Mathematics and Systems Science, China
- Yang, Guang-Hong, Northeastern University, China
- Yun, Jong Nam, Kim Il Sung University, Democratic People|S South Korea
- Zhang, Jun, University of Michigan–Shanghai Jiao Tong University Joint Institute, China
- Zhang, Xuebo, Nankai University, China
- Zheng, Qing, California Baptist University, USA
- Zong, Guangdeng, Qufu Normal University, China
- Li, Zhaokun, Xidian University, China
A few essentials for publishing in this journal
- Submitted articles should not have been previously published or be currently under consideration for publication elsewhere.
- Conference papers may only be submitted if the paper has been completely re-written (more details available here) and the author has cleared any necessary permissions with the copyright owner if it has been previously copyrighted.
- Briefs and research notes are not published in this journal.
- All our articles go through a double-blind review process.
- All authors must declare they have read and agreed to the content of the submitted article. A full statement of our Ethical Guidelines for Authors (PDF) is available.
- There are no charges for publishing with Inderscience, unless you require your article to be Open Access (OA). You can find more information on OA here.
- All articles for this journal must be submitted using our online submissions system.
- View Author guidelines.
12 December, 2022
The accurate identification of insects is critical in research of ecosystems and in pest control in agriculture and forestry. Writing in the International Journal of Systems, Control and Communications, a team from China has focused on the identification of insects in the Wudalianchi Scenic Area in Heilongjiang Province. This region of China is considered one of the most useful for studying species adaption and the evolution of biological communities. In such studies, rapid and accurate insect identification in the field is critical. Yao Xiao, Aocheng Zhou, Lin Zhou, and Yue Zhao of The School of Technology at Beijing Forestry University have developed an automatic insect identification system based on the SE-ResNeXt convolutional neural network, which they suggest could reduce the researchers' workload as well as reducing the incorrect assignment to species. The team demonstrated 98 percent accuracy with their system, which coupled with field expertise could improve such studies in a meaningful way. The development of a website and app using the neural network will improve data storage and visualisation. Such efforts will ultimately supplant the archaic storage of insect specimens, especially given that such specimens do not represent the currency of ecosystems [...]More details...