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CYBR 780 - Design and Operations for Cyber Human Systems

This is a research guide for masters level students enrolled in CYBR 780 - Design and Operations for Cyber Human Systems on the Salina Campus

Library Research Guide

Stay Informed!

As you pursue your master's degree, it is essential that you stay informed on the latest research and developments in your field.  Remember that you are not a mere consumer of information, but rather a contributor of knowledge in your field of study.  To remain an active participant in the conversation, you must remain engaged in the latest news and research.

This page provides the latest articles from some of the top publications and conferences in Cyber Human Systems. Some articles are distributed through RSS, while others are accessed through K-State Databases.  This page will update as new articles are added to the respective journals.

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Humans-in-the-Loop Articles from ACM

Here you will find some of the latest articles from ACM on humans-in-the-loop design, procedures, events, and research.

ACM Transactions on Autonomous and Adaptive Systems

TAAS aims to publish papers that provably advance the state of the art, or that provide new insights and knowledge into specific issues related to autonomous and adaptive systems. Here you will find some of the latest and best articles on Machine Learning and Autonomous Systems research.

IEEE Transactions on Systems, Man, and Cybernetics: Systems

IEEE Transactions on Systems, Man, and Cybernetics: Systems covers the fields of systems engineering. It addresses issue formulation, analysis, modeling, decision making, and interpretation for any of the systems engineering lifecycle phases associated with the definition, development, and deployment of large systems.

  • Table of ContentsThis link opens in a new windowMay 16, 2025
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  • IEEE Transactions on Systems, Man, and Cybernetics: Systems Publication InformationThis link opens in a new windowMay 16, 2025
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  • Stability Region Analysis for Nabla Linear Time Invariant Fractional Order SystemsThis link opens in a new windowApr 1, 2025
    This article considers the stability of nabla linear time invariant (LTI) fractional order systems with the order $\alpha \in (0,+\infty)$ . First, the stable criterion is developed, by using the nabla Laplace transform. Compared with the existing case of $\alpha \in (0,1)$ , our work introduces a wide range of dynamic behaviors for future applications. Second, many essential properties are discussed for the developed criterion, including the changing trend of the stable/unstable region regarding the order, the containment relationship between the imaginary axis, the negative semi-axis and the stable region, the evolution of the modulus with the absolute value of argument for the point lying in the critical stable region. Third, the linear matrix inequality (LMI) condition is tentatively derived to evaluate the stability. Finally, the elaborated results are supported by three illustrative numerical examples.
  • Interval Observer-Based Coordination Control for Discrete-Time Multi-Agent SystemsThis link opens in a new windowMar 26, 2025
    In this article, the coordination control problem of discrete-time multiagent systems (MASs) affected by uncertainties, namely unknown initial states and external disturbances, is considered. Inspired by the interval observer constructed by the single system, the definition of distributed interval observer for discrete-time MASs is given, in which the control protocol of each agent obtained by solving a modified algebraic Riccati equation depends on the bounded information of the interval observer connected to itself and its neighbors. By the cooperativity theory and Lyapunov stability theory, it is established that the distributed interval observer can not only access some information about MASs at any instant, that is, the upper and lower bounds of each component of the agent state, but also realize the cooperative behavior of MASs under some essential conditions involving network synchronization and the unstable eigenvalue of the system matrix. In addition, with the help of a new time-varying transformation matrix, the new interval observer is constructed to eliminate the non-negative constraint. Finally, two numerical simulations are provided to confirm the validity of the derived results.
  • Fault Detection for Discrete-Time Takagi-Sugeno Fuzzy Systems With Unmeasurable Premise Variable With L₂ – L∞/H∞ Mixed Observer and Zonotopic AnalysisThis link opens in a new windowApr 1, 2025
    For complex fuzzy nonlinear systems, the set membership estimation technique is often applied to fault detection or safety monitoring by giving a guaranteed estimation of the state. The main difficulty affecting the accuracy of existing set membership estimation methods for fuzzy system is the inability to obtain accurate model information online due to the unmeasurable premise variables. Therefore, a fault detection method based on membership function dependent (MFD) ${\mathcal {L}}_{2}-{\mathcal {L}}_{\infty }/{\mathcal {H}}_{\infty }$ mixed performance observer and zonotopic analysis is proposed for discrete fuzzy systems with unmeasurable premise variables. First, a novel MFD ${\mathcal {L}}_{2}-{{\mathcal {L}}}_{\infty }/{{\mathcal {H}}}_{\infty }$ performance is proposed, which reduces the conservatism of the traditional approach and provides more freedom to design. Second, on the basis of the proposed performance, the design conditions for the fault detection observer adopting the T-N-L structure are given using fuzzy basis-dependent Lyapunov functions, taking into account the effect of imprecise premise variables. Further, the effects caused by disturbances in the error dynamics of the observer as well as imprecise premise variables are handled using zonotopic analysis. The estimation results of the states and outputs in zonotopic and interval forms are given and applied to fault detection. Finally, the simulation shows that the proposed method provides guaranteed estimation in the absence of system faults and facilitates rapid fault detection when the system is faulty.
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IEEE Transactions on Cybernetics

 IEEE Transactions on Cybernetics includes computational approaches to the field of cybernetics. This journal publishes papers on communication and control across machines or machine, human, and organizations. The scope includes such areas as computational intelligence, computer vision, neural networks, genetic algorithms, machine learning, fuzzy systems, cognitive systems, decision making, and robotics, to the extent that they contribute to the theme of cybernetics or demonstrate an application of cybernetics principles.

  • Table of ContentsThis link opens in a new windowMay 16, 2025
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  • IEEE SYSTEMS, MAN, AND CYBERNETICS SOCIETYThis link opens in a new windowMay 16, 2025
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  • Quality Control in Extrusion-Based Additive Manufacturing: A Review of Machine Learning ApproachesThis link opens in a new windowApr 18, 2025
    Additive manufacturing (AM) revolutionizes product creation with its unique layer-by-layer construction method but faces obstacles in widespread industrial use due to quality assurance and defect challenges. Integrating machine learning (ML) into AM quality control (QC) systems presents a viable solution, utilizing ML’s ability to autonomously detect patterns and extract important data, reducing the reliance on manual intervention. This study conducts an in-depth literature review to scrutinize the role of ML in augmenting QC mechanisms within extrusion-based AM processes. Our primary objective is to pinpoint ML models that excel in monitoring manufacturing activities and facilitating instantaneous defect corrections via parameter adjustments. Our analysis highlights the efficacy of convolutional neural networks (CNNs) models in defect detection, leveraging camera-based systems for an in-depth examination of printed parts. For 1-D data processing, support vector machines (SVMs) and long short-term memory (LSTM) networks have shown significant application and effectiveness. Furthermore, the study classifies various sensors and defects that can effectively benefit from ML-driven QC approaches. Our findings accentuate the essential role of ML, especially CNNs, in detecting and rectifying production flaws and also detail the synergy between different sensor technologies in creating a comprehensive monitoring framework. By integrating ML with a multisensor approach and employing real-time corrective strategies, such as dynamic parameter adjustments and the use of advanced control systems, this research underscores ML’s transformative potential in elevating AM QC. Thus, our contribution lays the groundwork for harnessing ML technologies to ensure superior quality parts production in AM, paving the way for its broader industrial adoption.
  • On Consensus Control of Uncertain Multiagent Systems Based on Two Types of Interval ObserversThis link opens in a new windowApr 18, 2025
    In this article, we investigate the multiagent robust consensus problem under model uncertainties, where the uncertain matrices and initial values are bounded by prior intervals. Based on the positive system theory, the related upper and lower dynamic systems are constructed to guarantee that the state value remains within a specified range. Subsequently, in accordance with the Lyapunov stability principle, the observation and consensus errors converge to zero, that is, the real states are reconstructed and consensus is achieved. Both local and neighborhood protocols, which are utilized to realize robust consensus, are presented. Notably, the proposed methods increase the design freedom and eliminate the Metzler constraint on the error matrix by introducing two novel parametric matrices. Without loss of generality, the topology in this article is assumed to contain a directed spanning tree, which can be directly degenerated to the undirected graph. Finally, numerical simulations validating the theoretical results are described.
  • Markov Switching Topology-Based Reliable Control Design for Delayed Discrete-Time System: An Ellipsoidal Attracting ApproachThis link opens in a new windowApr 2, 2025
    This article presents reachable set synthesis for a discrete-time Markov jump system (DTMJS) with mode-dependent time-varying delays, subjected to uncertain transition probabilities and actuator faults, based on the ellipsoidal attracting approach. The focus is mainly to reflect more realistic control behaviors for the proposed DTMJS, in which the class of partially asynchronous reliable control (PARC) scheme is designed for the first time under the Markov switching topology. In this regard, the state-feedback and mode-dependent time-varying delayed state-feedback controllers are coupled by employing the Bernoulli variable. Under this framework, the hidden Markov model is formulated, revealing the asynchronism among switching topology, controller, actuators and proposed system in different operational modes. By constructing a double mode-dependent stochastic Lyapunov-Krasovskii functional, the sufficient conditions are derived in terms of linear matrix inequalities, which not only ascertain the stochastic stability of the resultant Markov jump system but also ensure that all reachable states remain within compact ellipsoidal boundaries. Finally, numerical simulations are provided to verify the effectiveness and merits of the presented method.
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