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Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on

Issue 5 • Date Sep 2000

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Displaying Results 1 - 9 of 9
  • TADEUS: seamless development of task-based and user-oriented interfaces

    Publication Year: 2000 , Page(s): 509 - 525
    Cited by:  Papers (6)  |  Patents (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (448 KB)  

    Task-based and user-oriented user interfaces utilize knowledge about user tasks and user characteristics to the utmost extent. They support users throughout their work flows, and must be constructed by a development process that avoids loss of application context and involves user feedback, from requirements specification to code generation. The concepts behind the task analysis/design/end users systems (TADEUS) approach to enable seamless task-based development are a semantically rich representation scheme, a model-driven development procedure, a diagrammatic notation and unifying specification scheme. Thus, interactive applications can be developed seamlessly. Specifications comprise problem domain knowledge, work processes, user roles and personal profiles, as well as interaction modalities (required for task accomplishment). For user-interface prototyping the TADEUS environment contains a model interpreter that executes structure and behavior specifications. This way, early feedback on task-based portals can be provided by users. In this paper we detail the latest developments in the TADEUS project when implementing a work-process based usability life cycle. We review the underlying methodology and the features of the TADEUS environment, in order to demonstrate the benefits for developers and users resulting of smooth transition support for and between the different stages of development View full abstract»

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  • Recurrent learning algorithms for designing optimal controllers of continuous systems

    Publication Year: 2000 , Page(s): 580 - 588
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (256 KB)  

    Proposes a recurrent learning algorithm for designing the controllers of continuous dynamical systems in optimal control problems. The controllers are in the form of unfolded recurrent neural nets embedded with physical laws from classical control techniques. The learning algorithm is characterized by a double forward-recurrent-loops structure for solving both temporal recurrent and structure recurrent problems. The first problem results from the nature of general optimal control problems, where the objective functions are often related to (evaluated at) some specific time steps or system states only, causing missing learning signals at some steps or states. The second problem is due to the high-order discretization of continuous systems by the Runge-Kutta method that we perform to increase accuracy. This discretization transforms the system into several identical interconnected subnetworks, like a recurrent neural net expanded in the time axis. Two recurrent learning algorithms with different convergence properties are derived; first- and second-order learning algorithms. Their computations are local and performed efficiently as net signal propagation. We also propose two new nonlinear control structures for the 2D guidance problem and the optimal PI control problem. Under the training of the recurrent learning algorithms, these controllers can be easily tuned to be suboptimal for given objective functions. Extensive computer simulations show the controllers' optimization and generalization abilities View full abstract»

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  • On the Dempster-Shafer evidence theory and non-hierarchical aggregation of belief structures

    Publication Year: 2000 , Page(s): 526 - 536
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (324 KB)  

    The Dempster's rule of combination is a widely used technique to integrate evidence collected from different sources. In this paper, it is shown that the values of certain functions defined on a family of belief structures decrease (by scale factors depending on the degree of conflict) when the belief structures are combined according to the Dempster's rule. Similar results also hold when an arbitrary belief structure is prioritized while computing the combination. Furthermore, the length of the belief-plausibility interval is decreased during a nonhierarchical aggregation of belief structures. Several types of inheritance networks are also proposed each of which allows considerable flexibility in the choice of prioritization View full abstract»

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  • A novel text-independent speaker verification method based on the global speaker model

    Publication Year: 2000 , Page(s): 598 - 602
    Cited by:  Papers (2)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (132 KB)  

    This correspondence introduces a new text-independent speaker verification method, which is derived from the basic idea of pattern recognition that the discriminating ability of a classifier can be improved by removing the common information between classes. In looking for the common speech characteristics between a group of speakers, a global speaker model can be established. By subtracting the score acquired from this model, the conventional likelihood score is normalized with the consequence of more compact score distribution and lower equal error rates. Several experiments are carried out to demonstrate the effectiveness of the proposed method View full abstract»

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  • Adaptive learning of hypergame situations using a genetic algorithm

    Publication Year: 2000 , Page(s): 562 - 572
    Cited by:  Papers (8)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (488 KB)  

    In this paper, we propose and examine adaptive learning procedures for supporting a group of decision-makers with a common set of strategies and preferences who face uncertain behaviors of “nature.” First, we describe the decision situation as a hypergame situation, where each decision-maker is explicitly assumed to have misperceptions about the nature's set of strategies and preferences. Then, we propose three learning procedures about the nature, each of which consists of several activities. One of the activities is to choose “rational” actions based on current perceptions and rationality adopted by the decision-makers, while the other activities are represented by the elements of a genetic algorithm (GA) to improve current perceptions. The three learning procedures are different from each other with respect to at least one of such activities as fitness evaluation, modified crossover, and action choice, though they use the same definition for the other GA elements. Finally, we point out that examining the simulation results how to employ preference- and strategy-oriented information is critical to obtaining good performance in clarifying the nature's set of strategies and the outcomes most preferred by the nature View full abstract»

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  • A design process based on a model combining scenarios with goals and functions

    Publication Year: 2000 , Page(s): 537 - 551
    Cited by:  Papers (19)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (332 KB)  

    While promising approaches to early system design using scenarios have been proposed, no design process is available that guides scenario-based design. We present a model that combines scenarios both with functions and goals. Functions are required to make the desired behavior of some scenario happen in order to achieve one or more goals. Using this model, we propose a systematic and concrete design process that is both model-driven and data-driven. Our design process supports the transition from the current to a new system and guides the design of a new system. In addition, this process makes it possible to detect a certain kind of redundancy and to improve both completeness and understandability of the resulting design. We have applied our approach in real-world projects, and our experience suggests the utility of this approach View full abstract»

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  • Self-organizing fuzzy aggregation models to rank the objects with multiple attributes

    Publication Year: 2000 , Page(s): 573 - 580
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (268 KB)  

    In this paper, a kind of ranking system, called agent-clients evaluation system, is proposed and investigated where there is no such authority with the right to predetermine weights of attributes of the entities evaluated by multiple evaluators for obtaining an aggregated evaluation result from the given fuzzy multiattribute values of these entities. Three models are proposed to evaluate the entities in such a system based on fuzzy inequality relation, possibility, and necessity measures, respectively. In these models, firstly the weights of attributes are automatically sought by fuzzy linear programming (FLP) problems based on the concept of data envelopment analysis (DEA) to make a summing-up assessment from each evaluator. Secondly, the weights for representing each evaluator's credibility are obtained by FLP to make an integrated evaluation of entities from the viewpoints of all evaluators. Lastly, a partially ordered set on a one-dimensional space is obtained so that all entities can be ranked easily. Because the weights of attributes and evaluators are obtained by DEA-based FLP problems, the proposed ranking models can be regarded as fair-competition and self-organizing ones so that the inherent feature of evaluation data can be reflected objectively View full abstract»

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  • A novel genetic algorithm based on immunity

    Publication Year: 2000 , Page(s): 552 - 561
    Cited by:  Papers (107)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (264 KB)  

    A novel algorithm, the immune genetic algorithm (IGA), is proposed based on the theory of immunity in biology which mainly constructs an immune operator accomplished by two steps: 1) a vaccination and 2) an immune selection. IGA proves theoretically convergent with probability 1. Strategies and methods of selecting vaccines and constructing an immune operator are also given. IGA is illustrated to be able to restrain the degenerate phenomenon effectively during the evolutionary process with examples of TSP, and can improve the searching ability and adaptability, greatly increase the convergence rate View full abstract»

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  • A next-best-view system for autonomous 3-D object reconstruction

    Publication Year: 2000 , Page(s): 589 - 598
    Cited by:  Papers (19)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (968 KB)  

    The focus of this paper is to design and implement a system capable of automatically reconstructing a prototype 3D model from a minimum number of range images of an object. Given an ideal 3D object model, the system iteratively renders range and intensity images of the model from a specified position, assimilates the range information into a prototype model, and determines the sensor pose (position and orientation) from which an optimal amount of previously unrecorded information may be acquired. Reconstruction is terminated when the model meets a given threshold of accuracy. Such a system has applications in the context of robot navigation, manufacturing, or hazardous materials handling. The system has been tested successfully on several synthetic data models, and each set of results was found to be reasonably consistent with an intuitive human search. The number of views necessary to reconstruct an adequate 3D prototype depends on the complexity of the object or scene and the initial data collected. The prototype models which the system recovers compare well with the ideal models View full abstract»

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Aims & Scope

The fields of systems engineering and human machine systems: systems engineering includes efforts that involve issue formulation, issue analysis and modeling, and decision making and issue interpretation at any of the lifecycle phases associated with the definition, development, and implementation of large systems.

 

This Transactions ceased production in 2012. The current retitled publication is IEEE Transactions on Systems, Man, and Cybernetics: Systems.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Dr. Witold Pedrycz
University of Alberta