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Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on

Issue 3 • Date May 2007

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Displaying Results 1 - 17 of 17
  • Table of contents

    Publication Year: 2007 , Page(s): C1
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  • IEEE Transactions on Systems, Man, and Cybernetics—Part C: Applications and Reviews publication information

    Publication Year: 2007 , Page(s): C2
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  • Machine Learning With AIBO Robots in the Four-Legged League of RoboCup

    Publication Year: 2007 , Page(s): 297 - 310
    Cited by:  Papers (62)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (410 KB) |  | HTML iconHTML  

    Robot learning is a growing area of research at the intersection of robotics and machine learning. The main contributions of this paper include a review of how machine learning has been used on Sony AIBO robots and at RoboCup, with a focus on the four-legged league during the years 1998-2004. The review shows that the application-oriented use of machine learning in the four-legged league was still conservative and restricted to a few well-known and easy-to-use methods such as standard decision trees, evolutionary hill climbing, and support vector machines. Method-oriented spin-off studies emerged more frequently and increasingly addressed new and advanced machine learning techniques. Further, the paper presents some details about the growing impact of machine learning in the software system developed by the authors' robot soccer team-the NUbots View full abstract»

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  • Gesture Recognition: A Survey

    Publication Year: 2007 , Page(s): 311 - 324
    Cited by:  Papers (193)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (199 KB) |  | HTML iconHTML  

    Gesture recognition pertains to recognizing meaningful expressions of motion by a human, involving the hands, arms, face, head, and/or body. It is of utmost importance in designing an intelligent and efficient human-computer interface. The applications of gesture recognition are manifold, ranging from sign language through medical rehabilitation to virtual reality. In this paper, we provide a survey on gesture recognition with particular emphasis on hand gestures and facial expressions. Applications involving hidden Markov models, particle filtering and condensation, finite-state machines, optical flow, skin color, and connectionist models are discussed in detail. Existing challenges and future research possibilities are also highlighted View full abstract»

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  • Molecular Computation and Evolutionary Wetware: A Cutting-Edge Technology for Artificial Life and Nanobiotechnologies

    Publication Year: 2007 , Page(s): 325 - 336
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (342 KB) |  | HTML iconHTML  

    Focusing on the new frontiers opened by the integration of artificial life and nanobiotechnologies, this paper reviews mainstream biomolecular computation from the viewpoint of an information processing mechanism, computing methods, and problem-solving algorithms. We also discuss evolutionary wetware as a tool for unconventional computing, inspired by biomolecular systems in nature. Biomolecular computation uses a different paradigm of computing than that of the semiconductor computer. It includes several branches based on different molecular materials or molecular structures. Wetware can be used to demonstrate molecular evolution by engineered operations in test tubes. This makes evolutionary wetware capable of bridging the two domains of molecular computation and artificial life so that molecular information processing methods can be extended from carrying out computational tasks to modeling scalable complex systems. From a systematic study of nanobiomachines, we expect to designate models of artificial life, and to search for a novel methodology of nanobioICT (Information and Communication Technology) in the near future View full abstract»

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  • Robust Neural-Network-Based Data Association and Multiple Model-Based Tracking of Multiple Point Targets

    Publication Year: 2007 , Page(s): 337 - 351
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1003 KB) |  | HTML iconHTML  

    Data association and model selection are important factors for tracking multiple targets in a dense clutter environment without using a priori information about the target dynamic. We propose a neural-network-based tracking algorithm, incorporating a interacting multiple model and show that it is possible to track both maneuvering and nonmaneuvering targets simultaneously in the presence of dense clutter. Moreover, it can be used for real-time application. The proposed method overcomes the problem of data association by using the method of expectation maximization and Hopfield network to evaluate assignment weights. All validated observations are used to update the target state. In the proposed approach, a probability density function (pdf) of an observed data, given target state and observation association, is treated as a mixture pdf. This allows to combine the likelihood of an observation due to each model, and the association process is defined to incorporate an interacting multiple model, and consequently, it is possible to track any arbitrary trajectory View full abstract»

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  • Incorporating Web Analysis Into Neural Networks: An Example in Hopfield Net Searching

    Publication Year: 2007 , Page(s): 352 - 358
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (136 KB) |  | HTML iconHTML  

    Neural networks have been used in various applications on the World Wide Web, but most of them only rely on the available input-output examples without incorporating Web-specific knowledge, such as Web link analysis, into the network design. In this paper, we propose a new approach in which the Web is modeled as an asymmetric Hopfield Net. Each neuron in the network represents a Web page, and the connections between neurons represent the hyperlinks between Web pages. Web content analysis and Web link analysis are also incorporated into the model by adding a page content score function and a link score function into the weights of the neurons and the synapses, respectively. A simulation study was conducted to compare the proposed model with traditional Web search algorithms, namely, a breadth-first search and a best-first search using PageRank as the heuristic. The results showed that the proposed model performed more efficiently and effectively in searching for domain-specific Web pages. We believe that the model can also be useful in other Web applications such as Web page clustering and search result ranking View full abstract»

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  • Therapeutic Drug Monitoring of Kidney Transplant Recipients Using Profiled Support Vector Machines

    Publication Year: 2007 , Page(s): 359 - 372
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (716 KB) |  | HTML iconHTML  

    This paper proposes a twofold approach for therapeutic drug monitoring (TDM) of kidney recipients using support vector machines (SVMs), for both predicting and detecting Cyclosporine A (CyA) blood concentrations. The final goal is to build useful, robust, and ultimately understandable models for individualizing the dosage of CyA. We compare SVMs with several neural network models, such as the multilayer perceptron (MLP), the Elman recurrent network, finite/infinite impulse response networks, and neural network ARMAX approaches. In addition, we present a profile-dependent SVM (PD-SVM), which incorporates a priori knowledge in both tasks. Models are compared numerically, statistically, and in the presence of additive noise. Data from 57 renal allograft recipients were used to develop the models. Patients followed a standard triple therapy, and CyA trough concentration was the dependent variable. The best results for the CyA blood concentration prediction were obtained using the PD-SVM (mean error of 0.36 ng/mL and root-mean-square error of 52.01 ng/mL in the validation set) and appeared to be more robust in the presence of additive noise. The proposed PD-SVM improved results from the standard SVM and MLP, specially significant (both numerical and statistically) in the one-against-all scheme. Finally, some clinical conclusions were obtained from sensitivity rankings of the models and distribution of support vectors. We conclude that the PD-SVM approach produces more accurate and robust models than do neural networks. Finally, a software tool for aiding medical decision-making including the prediction models is presented View full abstract»

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  • Multiagent Coordination Techniques for Complex Environments: The Case of a Fleet of Combat Ships

    Publication Year: 2007 , Page(s): 373 - 385
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (515 KB) |  | HTML iconHTML  

    The use of agent and multiagent techniques to assist humans in their daily routines has been increasing for many years, notably in command and control C2 systems. In this context, we propose using multiagent planning and coordination techniques for resources management in C2 systems. The particular problem we studied is the design of a decision-support for antiair warfare on combat ships. In this paper, we refer to the specific case of several combat ships defending against incoming threats and where coordination of their respective resources is a complex problem of capital importance. Efficient coordination mechanisms between the different combat ships are then important to avoid redundancy in engagements and inefficient defence caused by the conflicting actions. To this end, we present four different coordination mechanisms based on task sharing. Three of these mechanisms are communication-based: central coordination, contract Net coordination, and ~ Brown coordination, while the last one is a zone defence coordination and is based on conventions. Finally, we present the results obtained while simulating these various mechanisms View full abstract»

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  • Agent-Based Approach to Mass-Oriented Production Planning: Case Study

    Publication Year: 2007 , Page(s): 386 - 395
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (455 KB) |  | HTML iconHTML  

    This paper discusses the potential of multiagent planning techniques in the production-planning domain, with special focus on mass-oriented production. The research presented in the paper has been centered around ExPlanTech-a specific implementation of a production-planning multiagent system. Suitability of ExPlanTech for mass-oriented and project-driven manufacturing is also discussed in the paper. Applicability of multiagent concepts is demonstrated on a multiagent planning architecture and production-planning case study at a Skoda Auto Engine Plant View full abstract»

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  • Information Sharing as a Coordination Mechanism for Reducing the Bullwhip Effect in a Supply Chain

    Publication Year: 2007 , Page(s): 396 - 409
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (683 KB) |  | HTML iconHTML  

    The bullwhip effect is an amplification of the variability of the orders placed by companies in a supply chain. This variability reduces the efficiency of supply chains, since it incurs costs due to higher inventory levels and supply chain agility reduction. Eliminating the bullwhip effect is surely simple; every company just has to order following the market demand, i.e., each company should use a lot-for-lot type of ordering policy. However, many reasons, such as inventory management, lot-sizing, and market, supply, or operation uncertainties, motivate companies not to use this strategy. Therefore, the bullwhip effect cannot be totally eliminated. However, it can be reduced by information sharing, which is the form of collaboration considered in this paper. More precisely, we study how to separate demand into original demand and adjustments. We describe two principles explaining how to use the shared information to reduce the amplification of order variability induced by lead times, which we propose as a cause of the effect. Simulations confirm the value of these two principles with regard to costs and customer service levels View full abstract»

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  • A Recurrent Fuzzy-Network-Based Inverse Modeling Method for a Temperature System Control

    Publication Year: 2007 , Page(s): 410 - 417
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (246 KB) |  | HTML iconHTML  

    Temperature control by a Takagi-Sugeno-Kang (TSK)-type recurrent fuzzy network (TRFN) designed by modeling plant inverse is proposed in this paper. TRFN is a recurrent fuzzy network developed from a series of TSK-type fuzzy if--then rules, and is characterized by structure and parameter learning. In parameter learning, two types of learning algorithms, the Kalman filter and the gradient descent learning algorithms, are applied to consequent parameters depending on the learning situation. The TRFN has the following advantages when applied to temperature control problems: 1) high learning ability, which considerably reduces the controller training time; 2) no a priori knowledge of the plant order is required, which eases the design process; 3) good and robust control performance; 4) online learning ability, i.e., the TRFN can adapt itself to unpredictable plant changes. The TRFN-based direct inverse control configuration is applied to a real water bath temperature control plant, where various control conditions are experimented. The same experiments are also performed by proportional-integral (PI), fuzzy, and neural network controllers. From comparisons, the aforementioned advantages of a TRFN have been verified View full abstract»

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  • A Real-Time Visual Inspection System for Railway Maintenance: Automatic Hexagonal-Headed Bolts Detection

    Publication Year: 2007 , Page(s): 418 - 428
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1076 KB) |  | HTML iconHTML  

    Rail inspection is a very important task in railway maintenance, and it is periodically needed for preventing dangerous situations. Inspection is operated manually by trained human operator walking along the track searching for visual anomalies. This monitoring is unacceptable for slowness and lack of objectivity, as the results are related to the ability of the observer to recognize critical situations. The correspondence presents a patent-pending real-time Visual Inspection System for Railway (VISyR) maintenance, and describes how presence/absence of the fastening bolts that fix the rails to the sleepers is automatically detected. VISyR acquires images from a digital line-scan camera. Data are simultaneously preprocessed according to two discrete wavelet transforms, and then provided to two multilayer perceptron neural classifiers (MLPNCs). The "cross validation" of these MLPNCs avoids (practically-at-all) false positives, and reveals the presence/absence of the fastening bolts with an accuracy of 99.6% in detecting visible bolts and of 95% in detecting missing bolts. A field-programmable gate array-based architecture performs these tasks in 8.09 mus, allowing an on-the-fly analysis of a video sequence acquired at 200 km/h View full abstract»

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  • Trust Modeling for Networked Organizations Using Reputation and Collaboration Estimates

    Publication Year: 2007 , Page(s): 429 - 439
    Cited by:  Papers (12)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (541 KB) |  | HTML iconHTML  

    The main motivation for organizations and individuals to collaborate is to enable knowledge and resource sharing in order to effectively fulfil a joint business opportunity. This correspondence focuses on virtual organizations (VOs) and virtual teams (VTs), whose strengths lie in the range of competencies of their members, offered jointly through collaboration. One of the difficulties in VO and VT creation is partner selection using partners' mutual trust as one of the selection criteria. This correspondence provides an analysis of trust relationships based on the principal-agent theory, and proposes an approach to hierarchical multiattribute decision-support-based trust estimation applied to a network of collaborating organizations (VO) and a network of collaborating individuals (VT). The correspondence presents two case studies, one using a questionnaire-based approach and the other using automated reputation and collaboration estimation from data gathered by Web crawling View full abstract»

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  • 2008 IEEE International Conference on Distributed Human-Machine Systems (DHMS 2008)

    Publication Year: 2007 , Page(s): 440
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  • IEEE Systems, Man, and Cybernetics Society Information

    Publication Year: 2007 , Page(s): C3
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    Freely Available from IEEE
  • IEEE Transactions on Systems, Man, and Cybernetics—Part C: Applications and Reviews Information for authors

    Publication Year: 2007 , Page(s): C4
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    Freely Available from IEEE

Aims & Scope

Overview, tutorial and application papers concerning all areas of interest to the SMC Society: systems engineering, human factors and human machine systems, and cybernetics and computational intelligence. 

Authors should submit human-machine systems papers to the IEEE Transactions on Human-Machine Systems.

Authors should submit systems engineering papers to the IEEE Transactions on Systems, Man and Cybernetics: Systems.

Authors should submit cybernetics papers to the IEEE Transactions on Cybernetics.

Authors should submit social system papers to the IEEE Transactions on Computational Social Systems.

 

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