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1
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How to secure a high quality knowledge base in a rulebased system with uncertainty

100%
Jankowska B. M.
International Journal of Applied Mathematics and Computer Science
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2006
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tom 16
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nr 2
251-262
EN
Although the first rule-based systems were created as early as thirty years ago, this methodology of expert systems designing still proves to be useful. It becomes especially important in medical applications, while treating evidence given in an electronic format. Constructing the knowledge base of a rule-based system and, especially, of a system with uncertainty is a difficult task because of the size of this base as well as its heterogeneous character. The base consists of facts, ordinary rules and meta-rules, which differ from each other regarding both the syntax structure and the semantics. Having no tool to aid designing and maintaining the knowledge base of a rule-based system with uncertainty, we propose the algebra of rules with uncertainty which gives us theoretical foundations to build such a tool. Using the tool, it will be possible to indicate the facts and rules of a redundant character, as well as the pairs of facts and the pairs of rules which are contradictory to each other. The above tool is used in designing and maintaining the knowledge base of a system intended to prognosticate the effects of a medical treatment of the bronchial asthma disease.
2
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Fuzzy diagnostic reasoning that takes into account the uncertainty of the relation between faults and symptoms

100%
Kościelny J. M., Syfert M.
International Journal of Applied Mathematics and Computer Science
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2006
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tom 16
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nr 1
27-35
EN
Knowledge about the relation between faults and the observed symptoms is necessary for fault isolation. Such a relation can be expressed in various forms, including binary diagnostic matrices or information systems. The paper presents the use of fuzzy logic for diagnostic reasoning. This method enables us to take into account various kinds of uncertainties connected with diagnostic reasoning, including the uncertainty of the faults-symptoms relation. The presented methods allow us to determine the fault certainty factor as well as certainty factors of the normal and unknown process states. The unknown process state factor groups all the states with unknown and multiple faults with the states with improper residual values, while the normal state factor indicates similarity between the observed state and the pattern fault-free state.
3
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RGB-D terrain perception and dense mapping for legged robots

100%
Belter D., Łabecki P., Fankhauser P., Siegwart R.
International Journal of Applied Mathematics and Computer Science
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2016
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tom 26
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nr 1
81-97
EN
This paper addresses the issues of unstructured terrain modeling for the purpose of navigation with legged robots. We present an improved elevation grid concept adopted to the specific requirements of a small legged robot with limited perceptual capabilities. We propose an extension of the elevation grid update mechanism by incorporating a formal treatment of the spatial uncertainty. Moreover, this paper presents uncertainty models for a structured light RGB-D sensor and a stereo vision camera used to produce a dense depth map. The model for the uncertainty of the stereo vision camera is based on uncertainty propagation from calibration, through undistortion and rectification algorithms, allowing calculation of the uncertainty of measured 3D point coordinates. The proposed uncertainty models were used for the construction of a terrain elevation map using the Videre Design STOC stereo vision camera and Kinect-like range sensors. We provide experimental verification of the proposed mapping method, and a comparison with another recently published terrain mapping method for walking robots.
4
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Robust stabilization of discrete linear repetitive processes with switched dynamics

88%
Bochniak J., Galkowski K., Rogers E., Kummert A.
International Journal of Applied Mathematics and Computer Science
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2006
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tom 16
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nr 4
441-462
EN
Repetitive processes constitute a distinct class of 2D systems, i.e., systems characterized by information propagation in two independent directions, which are interesting in both theory and applications. They cannot be controlled by a direct extension of the existing techniques from either standard (termed 1D here) or 2D systems theories. Here we give new results on the design of physically based control laws. These results are for a sub-class of discrete linear repetitive processes with switched dynamics in both independent directions of information propagation.
5
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Set membership estimation of parameters and variables in dynamic networks by recursive algorithms with a moving measurement window

88%
Duzinkiewicz K.
International Journal of Applied Mathematics and Computer Science
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2006
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tom 16
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nr 2
209-217
EN
The paper considers a set membership joint estimation of variables and parameters in complex dynamic networks based on parametric uncertain models and limited hard measurements. A recursive estimation algorithm with a moving measurement window is derived that is suitable for on-line network monitoring. The window allows stabilising the classic recursive estimation algorithm and significantly improves estimate tightness. The estimator is validated on a case study regarding a water distribution network. Tight set estimates of unmeasured pipe flows, nodal heads, tank level and pipe resistances are obtained.
6
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Uses of new sensitivity and DAE solving methods in SmartMOBILE for verified analysis of mechanical systems

88%
Auer E., Luther W.
International Journal of Applied Mathematics and Computer Science
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2009
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tom 19
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nr 3
455-467
EN
Software for modeling and simulation (MSS) of mechanical systems helps to reduce production costs for industry. Usually, such software relies on (possibly erroneous) finite precision arithmetic and does not take into account uncertainty in the input data. The program SmartMOBILE enhances the existing MSS MOBILE with verified techniques to provide a guarantee that the obtained results are correct and measure the influence of data uncertainty. In this paper, we outline the main features and functionalities of SmartMOBILE. In particular, we focus on its use of newly developed methods for sensitivity analysis and DAE solving for several practically relevant mechanical systems.
7
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Uncertainty models of vision sensors in mobile robot positioning

75%
Skrzypczyński P.
International Journal of Applied Mathematics and Computer Science
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2005
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tom 15
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nr 1
73-88
EN
This paper discusses how uncertainty models of vision-based positioning sensors can be used to support the planning and optimization of positioning actions for mobile robots. Two sensor types are considered: a global vision with overhead cameras, and an on-board camera observing artificial landmarks. The developed sensor models are applied to optimize robot positioning actions in a distributed system of mobile robots and monitoring sensors, and to plan the sequence of actions for a robot cooperating with the external infrastructure supporting its navigation.
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