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Systems, Man, and Cybernetics: Systems, IEEE Transactions on

Issue 4 • Date July 2013

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Displaying Results 1 - 25 of 25
  • Table of contents

    Page(s): C1 - 741
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  • IEEE Transactions on Systems, Man, and Cybernetics publication information

    Page(s): C2
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  • A Three-Level Strategy for the Design and Performance Evaluation of Hospital Departments

    Page(s): 742 - 756
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (760 KB) |  | HTML iconHTML  

    The efficient management of hospital departments (HDs) has recently become an important issue. Indeed, the increased demand and design for hospital services have saturated the capacity of HD that requires suitable tools for the efficient use of resources and flow of patients, staff, and drugs. This paper proposes a model based on a three-level strategy to design at the tactical level in a concise and effective way the structure, the resources, and the dynamics of a critically congested HD. The design strategy is composed of three basic elements: the modeling module, the optimization module, and the simulation and decision module. The first module employs a Unified Modeling Language tool and a timed Petri net (PN) model to effectively capture the detailed flow and dynamics of patients, starting from their arrival to the HD until their discharge. The optimization module employs the fluid relaxation to concisely approximate in a continuous PN framework the HD model and optimize suitable performance indices. The simulation module verifies that the optimized parameters allow an effective workflow organization while maximizing the patient flow. In case of inconsistencies due to the fluid approximation between the continuous model used in the design phase by the optimization module and the discrete one used in the subsequent verification phase by the simulation module, the latter module revises the values of some HD model parameters. A real case study on the Emergency Cardiology Department of the General Hospital of Bari (Italy) shows the efficiency and accuracy of the proposed method. View full abstract»

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  • R-TNCES: A Novel Formalism for Reconfigurable Discrete Event Control Systems

    Page(s): 757 - 772
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    This study deals with the formal modeling and verification of reconfigurable discrete event control systems (RDECSs). The behavior of an RDECS is represented by that of control components (CCs) and the communication among them. A new formalism, called Reconfigurable Timed Net Condition/Event Systems (TNCES) (R-TNCES), is proposed for the optimal functional and temporal specification of RDECS, which is defined by a behavior module and a control module. The former is a union of various superposed TNCESs, where TNCES-based CC modules are basic units. The latter is a set of reconfiguration functions dealing with the automatic transformations of these TNCESs in response to errors or user requirements by enabling or disabling CC modules, changing condition signals and/or event signals among them, and also treating the state feasibility before and after reconfigurations. To control the verification complexity of R-TNCES, a layer-by-layer verification method is developed, where the similarities of different TNCESs in the behavior module are considered. The contribution of this original paper is applied to a benchmark production system. View full abstract»

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  • Sensing-Driven Energy Purchasing in Smart Grid Cyber-Physical System

    Page(s): 773 - 784
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (851 KB) |  | HTML iconHTML  

    Distributed and renewable-energy resources are likely to play an important role in the future energy landscape as consumers and enterprise energy users reduce their reliance on the main electricity grid as their source of electricity. Environmental or ambient sensing of parameters such as temperature and humidity, and amount of sunlight and wind, can be used to predict electricity demand from users and supply from renewable sources, respectively. In this paper, we describe a Smart Grid Cyber-Physical System (SG-CPS) comprising sensors that transmit real-time streams of sensed information to predictors of demand and supply of electricity and an optimization-based decision maker that uses these predictions together with real-time grid electricity prices and historical information to determine the quantity and timing of grid electricity purchases throughout the day and night. We investigate two forms of the optimization-based decision maker, one that uses linear programming and another that uses multi-stage stochastic programming. Our results show that sensing-driven predictions combined with the optimization-based purchasing decision maker hosted on the SG-CPS platform can cope well with uncertainties in demand, supply, and electricity prices and make grid electricity purchasing decisions that successfully keep both the occurrence of electricity shortfalls and the cost of grid electricity purchases low. We then examine the computational and memory requirements of the aforementioned prediction and optimization algorithms and find that they are within the capabilities of modern embedded system microprocessors and, hence, are amenable for deployment in typical households and communities. View full abstract»

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  • Multiobjective Optimization in Multifunction Multicapability System Development Planning

    Page(s): 785 - 800
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1766 KB) |  | HTML iconHTML  

    Properly allocating resources to achieve system development objectives has remained a challenge in systems engineering management. Various optimization models have been developed to optimize respective figures of merit (FOMs) subject to development constraints. System readiness level (SRL) is a system FOM that was originally introduced to assess the maturity of a system during its development lifecycle and has evolved to cover the development of multifunction multicapability (MFMC) systems. Optimization models which include SRL as either the objective or a constraint have been proposed for system development planning. Building on the definition of the recently enhanced MFMC SRL, this paper proposes a multiobjective optimization model, called MO_SRL, to simultaneously optimize the following: 1) the maturity of the system's selected functions or capabilities and 2) the consumption of development resources. An evolutionary algorithm is used to obtain a Pareto set of optimal solutions, where each solution represents a development plan informing which system components should be advanced to which maturity levels without exceeding a certain amount of resource consumption. With the consideration of SRL correlation to typical system development lifecycle, this model can identify several development alternatives for improving the system maturity to more advanced phases with minimum resource consumption, and these multiple alternatives provide systems engineering managers with flexibility in planning system development. View full abstract»

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  • Concept Drift-Oriented Adaptive and Dynamic Support Vector Machine Ensemble With Time Window in Corporate Financial Risk Prediction

    Page(s): 801 - 813
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (478 KB) |  | HTML iconHTML  

    This paper proposes a novel method of corporate financial risk prediction (FRP) modeling called the adaptive and dynamic ensemble (ADE) of support vector machine (SVM) (ADE-SVM), which integrates the inflow of new data batches for FRP with the process of time. Namely, the characteristic change of corporate financial distress hidden in the data flow is considered as the concept drift of financial distress, and it is handled by ADE-SVM that keeps updating in time. Using the criteria of predictive ability and classifier diversity, the SVM ensemble is dynamically constructed by adaptively selecting the current base SVMs from candidate ones. The candidate SVMs are incrementally updated by considering the newest data batch at each new current time point. The results of the base SVMs are dynamically weighted by their validation accuracies on the latest data batch to generate the final prediction. Experiments were carried out on real-world data sets with current data for training and future data for testing. The results show that ADE-SVM overall outperforms the other three traditional dynamic modeling methods, particularly for harder FRP task with more insufficient information and more obvious concept drift. View full abstract»

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  • Realization of an Adaptive Memetic Algorithm Using Differential Evolution and Q-Learning: A Case Study in Multirobot Path Planning

    Page(s): 814 - 831
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2556 KB) |  | HTML iconHTML  

    Memetic algorithms (MAs) are population-based meta-heuristic search algorithms that combine the composite benefits of natural and cultural evolutions. An adaptive MA (AMA) incorporates an adaptive selection of memes (units of cultural transmission) from a meme pool to improve the cultural characteristics of the individual member of a population-based search algorithm. This paper presents a novel approach to design an AMA by utilizing the composite benefits of differential evolution (DE) for global search and Q-learning for local refinement. Four variants of DE, including the currently best self-adaptive DE algorithm, have been used here to study the relative performance of the proposed AMA with respect to runtime, cost function evaluation, and accuracy (offset in cost function from the theoretical optimum after termination of the algorithm). Computer simulations performed on a well-known set of 25 benchmark functions reveal that incorporation of Q-learning in one popular and one outstanding variants of DE makes the corresponding algorithm more efficient in both runtime and accuracy. The performance of the proposed AMA has been studied on a real-time multirobot path-planning problem. Experimental results obtained for both simulation and real frameworks indicate that the proposed algorithm-based path-planning scheme outperforms the real-coded genetic algorithm, particle swarm optimization, and DE, particularly its currently best version with respect two standard metrics defined in the literature. View full abstract»

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  • A Path-Planning Algorithm Using Vector Potential Functions in Triangular Regions

    Page(s): 832 - 842
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (854 KB) |  | HTML iconHTML  

    A path-planning algorithm for a complex workspace split into triangular regions is investigated. The algorithm, which is formulated to achieve a goal configuration subject to the desired goal-point orientation, generates a collision-free region-to-region-compliant path. To that end, a set of vector potential functions is used. These functions are calculated using information on the triangular regions' vertices, the obstacles' positions, and the goal configuration. Path-planning procedures based on these constraint-satisfying functions are constructed. The proposed path-planning method, entailing velocity-and-orientation tracking control and configuration control, is applied to a unicycle vehicle, and its performance is compared with that of an existing path-planning scheme. View full abstract»

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  • Designing and Implementing a Human–Robot Team for Social Interactions

    Page(s): 843 - 859
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2350 KB) |  | HTML iconHTML  

    This study provides an in-depth analysis and practical solution to the problem of designing and implementing a human-robot team for simple conversational interactions. Models for operation timing, customer satisfaction and customer-robot interaction are presented, based on which a simulation tool is developed to estimate fan-out and robot team performance. Techniques for managing interaction flow and operator task assignment are introduced. In simulation, the effectiveness of different techniques and factors related to team performance are studied. A case study on deploying multiple robots in a shopping mall is then presented to demonstrate the usefulness of our study in helping the design and implementation of social robots in real-world settings. View full abstract»

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  • Incorporating Human Factor Considerations in Unmanned Aerial Vehicle Routing

    Page(s): 860 - 874
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (865 KB) |  | HTML iconHTML  

    Unmanned aerial vehicles (UAVs) have become increasingly valuable military assets, and reliance upon them will continue to increase. Despite lacking an onboard pilot, UAVs require crews of up to three human operators. These crews are already experiencing high workload levels, which is a problem that will be likely compounded as the military envisions a future where a single operator controls multiple UAVs. To accomplish this goal, effective scheduling of UAVs and human operators is crucial to future mission success. We present a mathematical model for simultaneously routing UAVs and scheduling human operators, subject to operator workload considerations. This model is thought to be the first of its kind. Numerical examples demonstrate the dangers of ignoring the human element in UAV routing and scheduling. View full abstract»

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  • Realistic Human Action Recognition With Multimodal Feature Selection and Fusion

    Page(s): 875 - 885
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1192 KB) |  | HTML iconHTML  

    Although promising results have been achieved for human action recognition under well-controlled conditions, it is very challenging to recognize human actions in realistic scenarios due to increased difficulties such as dynamic backgrounds. In this paper, we propose to take multimodal (i.e., audiovisual) characteristics of realistic human action videos into account in human action recognition for the first time, since, in realistic scenarios, audio signals accompanying an action generally provide a cue to the nature of the action, such as phone ringing to answering the phone . In order to cope with diverse audio cues of an action in realistic scenarios, we propose to identify effective features from a large number of audio features with the generalized multiple kernel learning algorithm. The widely used space-time interest point descriptors are utilized as visual features, and a support vector machine is employed for both audio- and video-based classifications. At the final stage, fuzzy integral is utilized to fuse recognition results of both audio and visual modalities. Experimental results on the challenging Hollywood-2 Human Action data set demonstrate that the proposed approach is able to achieve better recognition performance improvement than that of integrating scene context. It is also discovered how audio context influences realistic action recognition from our comprehensive experiments. View full abstract»

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  • Probabilistic Modeling of Anticipation in Human Controllers

    Page(s): 886 - 900
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1656 KB) |  | HTML iconHTML  

    This paper presents a methodology for determining whether human operators anticipate future control needs in order to compensate for time delays when controlling remote vehicles. The approach utilizes techniques drawn from the machine learning community in order to learn statistical models of human decision making. Models are fit to an experimental data set generated by remote operations of a robot subjected to time delays between 0 and 2.5 s, using the least angle regression (LARS) and sparse multinomial logistic regression (SMLR) algorithms. These algorithms make use of regularization to reduce the effects of overparameterization due to redundant or noisy environmental features. Models learned by LARS achieve an average prediction rate between 81% and 98%, depending on time delay, while those learned by SMLR achieve average rates between 68% and 86%. A novel metric of feature “importance” is used to evaluate the relative contributions of environmental features to model performance, motivated by the structure of the LARS algorithm. The degree to which human operators rely on anticipation is determined by examining how “importance” scores for features representing different prediction horizons vary with increasing time delay. View full abstract»

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  • Emotional Sea: Showing Valence and Arousal Through the Sharpness and Movement of Digital Cartoonish Sea Waves

    Page(s): 901 - 910
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (663 KB) |  | HTML iconHTML  

    This paper proposes and explores a nonanthropomorphic approach to express emotions. Emotions are represented in terms of valence and arousal dimensions, and they are visually expressed through the shape and movement of a series of digital cartoonish sea waves which are modeled as simple Bèzier curves. In particular, the valence value is expressed through the sharpness of the curves (the more negative the valence, the sharper the curves), while the arousal value is expressed through their movement (controlled by a flocking algorithm). Furthermore, this paper describes a user study which investigated whether the valence and arousal expressed by our model are appropriately perceived by the users or not. The results suggest that combinations of sharpness and movement are perceived correctly as particular emotions and that sharpness and movement are perceived as valence and arousal, respectively. We also found that valence in our model has a slight side effect in the perception of arousal. The more negative the valence, the higher the arousal is perceived. View full abstract»

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  • InteSe: An Integrated Model for Resolving Ambiguities in Multimodal Sentences

    Page(s): 911 - 931
    Multimedia
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    The pervasiveness of ambiguity in communication processes suggests addressing the problem of semantic and syntactic ambiguities in multimodal interaction languages. This paper presents an integrated model based on layered, hierarchical, and hidden Markov models for dealing with the complex process of multimodal ambiguity resolution. The proposed model consists of different levels, from the terminals of a multimodal language (terminal elements) to the level of multimodal sentences. A software module implemented the model that has been evaluated in terms of accuracy and robustness. The experimental results show good levels of accuracy and robustness compared with other existing approaches. View full abstract»

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  • A New Modified Reachability Tree Approach and Its Applications to Unbounded Petri Nets

    Page(s): 932 - 940
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (595 KB) |  | HTML iconHTML  

    This paper proposes a new modified reachability tree (NMRT) approach for a class of unbounded generalized Petri nets called ω-independent nets. The NMRT of an ω-independent net consists of all and only reachable markings from its initial marking. Moreover, the applications of the NMRT to deadlock analysis for ω-independent nets are developed. The proposed method has a larger application scope than all the existing methods. Several examples are provided to show its superiority over them. View full abstract»

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  • Design and Implementation of a Web-Service-Based Public-Oriented Personalized Health Care Platform

    Page(s): 941 - 957
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (711 KB) |  | HTML iconHTML  

    The use of information technology and management systems for the betterment of health care is more and more important and popular. However, existing efforts mainly focus on informatization of hospitals or medical institutions within the organizations, and few are directly oriented to the patients, their families, and other ordinary people. The strong demand for various medical and public health care services from customers calls for the creation of powerful individual-oriented personalized health care service systems. Service computing and related technologies can greatly help one in fulfilling this task. In this paper, we present PHISP: a Public-oriented Health care Information Service Platform, which is based on such technologies. It can support numerous health care tasks, provide individuals with many intelligent and personalized services, and support basic remote health care and guardianship. In order to realize the personalized customization and active recommendation of intelligent services for individuals, several key techniques for service composition are integrated, which can support branch and parallel control structures in the process models of composite services and are highlighted in this paper. View full abstract»

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  • A Multiphase Decision Model for System Reliability Growth With Latent Failures

    Page(s): 958 - 966
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (359 KB) |  | HTML iconHTML  

    Reliability growth testing becomes difficult to implement as the product development cycle continues to shrink. As a result, the new design is prone to latent failures due to design immaturity and uncertain operating condition. Reliability growth planning emerged as a new methodology to drive the reliability across the product lifetime. We propose a multiphase reliability growth model that sequentially determines and implements corrective actions (CAs) against surfaced and latent failure modes. Such a holistic approach enables the manufacturer to attain the reliability goal while ensuring the product time to market. We devise a CA effectiveness function to assess the tradeoff between the failure removal rate and the required resources. Rosen's gradient projection algorithm is used to determine the optimal resource allocation in each phase. The applicability and performance of the reliability growth model are demonstrated on a fleet of semiconductor testing equipment. View full abstract»

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  • Reliability of Nonrepairable Phased-Mission Systems With Common Cause Failures

    Page(s): 967 - 978
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (295 KB) |  | HTML iconHTML  

    Phased-mission systems (PMSs) are systems supporting missions characterized by multiple, consecutive, and nonoverlapping phases of operation. Examples of PMSs abound in many practical applications such as aerospace, nuclear power, and airborne weapon systems. Reliability analysis of a PMS must consider statistical dependence of component states across different phases, as well as dynamics in system structure functions and component behavior. In this paper, we propose a recursive method for exact reliability evaluation of a binary-state or multistate PMS consisting of nonidentical, binary, and nonrepairable elements. The system elements can fail individually or due to common-cause failures (CCFs) caused by some external factors. The proposed method is based on the branch-and-bound principle, and can be fully automated. The method is applicable to PMSs with nonoverlapping or overlapping sets of elements that can fail as a result of CCFs. The method is illustrated using both analytical and numerical examples. View full abstract»

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  • Analysis and Critique of the System Readiness Level

    Page(s): 979 - 987
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (275 KB) |  | HTML iconHTML  

    The system readiness level (SRL) developed by Sauser <;etal/> (referred to as the S&C_SRL in this paper) has recently been introduced as a system development metric on several major defense acquisition programs without having received adequate scrutiny for modeling realism and mathematical validity. The use of matrix operations on a technology readiness level (TRL) vector and an integration readiness level (IRL) matrix gives the S&C_SRL characteristics of a quantitative measure. Given that the TRL and IRL are ordinal data, these operations are meaningless, and the S&C_SRL is a potentially misleading metric. Its use can have harmful consequences on a system's development. Fortunately, there is no need for the S&C_SRL given the availability of valid qualitative models that provide visibility and valid information on both the achieved system readiness and the difficulty to achieve operational readiness; but they have limited usefulness. The effective and efficient development of technically advanced systems and upgrades of heritage systems requires a systems engineering (SE) process based on a sound quantitative assessment and management of technical, cost, and schedule risks. The use of the S&C_SRL and other flawed decision and risk analysis models is symptomatic of a mathematical vulnerability in the SE practice. Corrective actions are presented. View full abstract»

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  • Transsituational Individual-Specific Biopsychological Classification of Emotions

    Page(s): 988 - 995
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (510 KB) |  | HTML iconHTML  

    The goal of automatic biopsychological emotion recognition of companion technologies is to ensure reliable and valid classification rates. In this paper, emotional states were induced via a Wizard-of-Oz mental trainer scenario, which is based on the valence-arousal-dominance model. In most experiments, classification algorithms are tested via leave-out cross-validation of one situation. These studies often show very high classification rates, which are comparable with those in our experiment (92.6%). However, in order to guarantee robust emotion recognition based on biopsychological data, measurements have to be taken across several situations with the goal of selecting stable features for individual emotional states. For this purpose, our mental trainer experiment was conducted twice for each subject with a 10-min break between the two rounds. It is shown that there are robust psychobiological features that can be used for classification (70.1%) in both rounds. However, these are not the same as those that were found via feature selection performed only on the first round (classification: 53.0%). View full abstract»

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  • Tracking Generic Human Motion via Fusion of Low- and High-Dimensional Approaches

    Page(s): 996 - 1002
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    Tracking generic human motion is highly challenging due to its high-dimensional state space and the various motion types involved. In order to deal with these challenges, a fusion formulation which integrates low- and high-dimensional tracking approaches into one framework is proposed. The low-dimensional approach successfully overcomes the high-dimensional problem of tracking the motions with available training data by learning motion models, but it only works with specific motion types. On the other hand, although the high-dimensional approach may recover the motions without learned models by sampling directly in the pose space, it lacks robustness and efficiency. Within the framework, the two parallel approaches, low- and high-dimensional, are fused via a probabilistic approach at each time step. This probabilistic fusion approach ensures that the overall performance of the system is improved by concentrating on the respective advantages of the two approaches and resolving their weak points. The experimental results, after qualitative and quantitative comparisons, demonstrate the effectiveness of the proposed approach in tracking generic human motion. View full abstract»

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  • Wildfire Smoke Detection Using Computational Intelligence Techniques Enhanced With Synthetic Smoke Plume Generation

    Page(s): 1003 - 1012
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    An early wildfire detection is essential in order to assess an effective response to emergencies and damages. In this paper, we propose a low-cost approach based on image processing and computational intelligence techniques, capable to adapt and identify wildfire smoke from heterogeneous sequences taken from a long distance. Since the collection of frame sequences can be difficult and expensive, we propose a virtual environment, based on a cellular model, for the computation of synthetic wildfire smoke sequences. The proposed detection method is tested on both real and simulated frame sequences. The results show that the proposed approach obtains accurate results. View full abstract»

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  • IEEE Systems, Man, and Cybernetics Society Information

    Page(s): C3
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  • IEEE Transactions on Human-Machine Systems information for authors

    Page(s): C4
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Aims & Scope

The scope of the IEEE Transactions on Systems, Man, and Cybernetics: Systems includes the fields of systems engineering.

 

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Editor-in-Chief
C. L. Philip Chen
The University of Macau