IEEE SMC Magazine

The scope of the IEEE Systems, Man, and Cybernetics Magazine matches the technology areas within the Society’s Field of Interest (FoI). Article subjects include the integration of the theories of communication, control, cybernetics, systems engineering, human-factors engineering, as well as their application to the variety of systems including human-machine, biological, technological, and societal. The Magazine is intended to communicate to readers about the activities and actions of the SMC Society’s governing body, its Technical Committees, and its Chapters. Furthermore, the Magazine will offer educational material such as technical review papers, publish contributions on educational activities, industrial and university profiles, conference news, book reviews, and a calendar of important events.

Potential contributions must follow the guidelines set in the Information for Authors.

Send e-mail correspondence to [email protected]


Tingwen Huang, PhD

Texas A&M University at Qatar

Email Tingwen Huang

Associate Editors

    • Bernadetta Kwintiana Ane
    • Hossam Gaber
    • Kazuo Kiguchi
    • Chris Nemeth
    • Vinod Prasad
    • Mehrdad Saif
    • Ying Tan
    • Yingxu Wang
    • Xingming Zhao
    • Mali Abdollahian
    • Mohammad Abdullah-Al-Wadud
    • Choon Ki Ahn
    • György EIgner
    • Liping Fang
    • Jason Gu
    • Abdollah Homaifar
    • Abbas Khosravi
    • Vladik Kreinovich
    • Kevin Kelly
    • Wei Lei
    • Kovács Levente
    • Darius Nahavandi
    • Vinod Prasad
    • Hong Qiao
    • S.P. Raja
    • Ferat Sahin
    • Bahram Shafai
    • Liqiong Tang
    • Peter Whitehead
    • Laurence T. Yang
    • Dongning Liu
    • Jing Li
    • Claudio Savaglio
    • Agostino Marcello Mangini
    • injun Shan, Canada
    • Michael Zhou, China
    • Dengxiu Yu, China
    • Keke Huang, China
    • Junjie Fu, China
    • Zi-Peng Wang, China
    • Qiang Xiao, China
    • Jinliang Wang, China
    • Xin Wang, China
    • Yuezu Lv, China
    • Hongjing Liang, China
    • Shiping Wen, Australia
    • Yushuai Li, Denmark
    • Jiacun Wang
    • Jinshan Tang


01 July 2023
A smart building is an emerging technology that has the potential to be used in a variety of ubiquitous computing applications. The majority of existing work for smart building monitoring consumes a significant amount of energy to communicate the sensory data from the building to the end users (EUs). This...
01 July 2023
The emerging fourth industrial revolution (industry 4.0) is leading the healthcare system toward more digitalization and smart management. For instance, recent digital healthcare solutions can help dentists/practitioners save time by managing their schedules and managing diagnosis and treatment. The proposed solution is a diagnostic module that can be integrated into...
01 April 2023
Deep vein thrombosis (DVT) is a venous reflux disorder disease caused by abnormal blood coagulation in the deep veins. It frequently occurs in the lower limbs of orthopedic patients, pregnant women, and the elderly. DVT can easily cause a pulmonary embolism (PE), a disease with a high mortality rate. Therefore,...
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18 April 2024
Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers....
18 April 2024
The prisoner’s dilemma (PD) is one of the most popular concepts in scientific literature. This concept is widely used to study various social interactions where participants choose to give up or cooperate in an uninformed environment. This article finds that the matchmaking problem, such as in multiplayer online battle arena...
18 April 2024
Smart energy management encompasses energy consumption prediction and energy data analytics. Energy consumption prediction or electric load forecasting leverages autoregressive and moving-average models. Recently, there has been a lot of traction in data-driven models for energy consumption prediction. In this article, a self-attention-based Transformer model is proposed. The deep-learning model...
18 April 2024
Selective optimal disassembly sequencing (SODS) is a methodology for the disassembly of waste products. Mathematically, it is an optimization problem. However, in the existing research, the connection between the optimization algorithms and the established model is limited to some specific processes, and their generality is poor. Due to the unique...
18 April 2024
A downsampling strategy based on negative selection density clustering (NSDC-DS) is proposed to improve classifier performance while employing random downsampling for unbalanced communication text. The discovery of self-anomalies via negative selection enhances traditional clustering. The detector and self-set are the sample center point and the sample to be clustered, respectively;...

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