45372122
Interrogating the structure of fuzzy cognitive maps
Abstract Causal algebra in fuzzy cognitive maps (FCMs) plays a critical role in the analysis and design of FCMs. Improving causal algebra in FCMs to model complicated situations has been one of the major research topics in this area. In this paper we propose a dynamic causal algebra in FCMs which can improve FCMs' inference and representation capability. The dynamic causal algebra shows that the indirect, strongest, weakest and total effects a vertex influences another in the FCM not only depend on the weights along all directed paths between the two vertices but also the states of the vertices on the directed paths. Therefore, these effects are nonlinear dynamic processes determined by initial conditions and propagated in the FCM to reach a static or cyclic pattern. We test our theory with a simple example.
14780024
Fuzzy causal networks: general model, inference, and convergence
In this paper, we first propose a general framework for fuzzy causal networks (FCNs). Then, we study the dynamics and convergence of such general FCNs. We prove that any general FCN with constant weight matrix converges to a limit cycle or a static state, or the trajectory of the FCN is not repetitive. We also prove that under certain conditions a discrete state general FCN converges to its limit cycle or static state in O(n) steps, where n is the number of vertices of the FCN. This is in striking contrast with the exponential running time 2/sup n/, which is accepted widely for classic FCNs.
7502395
Dynamic image sequence analysis using fuzzy measures
In this paper, we present an image understanding system using fuzzy sets and fuzzy measures. This system is based on a symbolic object-oriented image interpretation system. We apply a simple, powerful three-dimensional (3-D) recursive filter to tracking moving objects in a dynamic image sequence. This filter has a time-varying 3-D frequency-planar passband that is adapted in a feedback system to automatically track moving objects. However, as objects in the image sequence are not well-defined and are engaged in dynamic activities, their shapes and trajectories in most cases can be described only vaguely. In order to handle these uncertainties, we use fuzzy measures to capture subtle variations and manage the uncertainties involved. This enables us to develop an image understanding system that produces a very natural output. We demonstrate the effectiveness of our system with complex real traffic scenes.
2364735
Embodied categorisation for vision-guided mobile robots
This paper outlines a philosophical and psycho-physiological basis for embodied perception, and develops a framework for conceptual embodiment of vision-guided robots. We argue that categorisation is important in all stages of robot vision. Further, that classical computer vision is unsuitable for this categorisation, however, through conceptual embodiment, active perception can be effective. We present a methodology for developing vision-guided robots that applies embodiment, explicitly and implicitly, in categorising visual data to facilitate efficient perception and action. Finally, we present systems developed using this methodology, and demonstrate that embodied categorisation can make algorithms more efficient and robust.
35062719
Vision Guided Circumnavigating Autonomous Robots
We present a system for vision guided autonomous circumnavigation, allowing a mobile robot to navigate safely around objects of arbitrary pose, and avoid obstacles. The system performs model-based object recognition from an intensity image. By enabling robots to recognize and navigate with respect to particular objects, this system empowers robots to perform deterministic actions on specific objects, rather than general exploration and navigation as emphasized in much of the current literature. This paper describes a fully integrated system, and, in particular, introduces canonical-views. Further, we derive a direct algebraic method for finding object pose and position for the four-dimensional case of a ground-based robot with uncalibrated vertical movement of its camera. Vision for mobile robots can be treated as a very different problem to traditional computer vision, as mobile robots have a characteristic perspective, and there is a causal relation between robot actions and view changes. Canonical-views are a novel, active object representation designed specifically to take advantage of the constraints of the robot navigation problem to allow efficient recognition and navigation.
207320245
Hidden Markov models with factored Gaussian mixtures densities
We present a factorial representation of Gaussian mixture models for observation densities in hidden Markov models (HMMs), which uses the factorial learning in the HMM framework. We derive the reestimation formulas for estimating the factorized parameters by the Expectation Maximization (EM) algorithm and propose a novel method for initializing them. To compare the performances of the proposed models with that of the factorial hidden Markov models and HMMs, we have carried out extensive experiments which show that this modelling approach is effective and robust.
9905546
Mean eccentricities of de Bruijn networks
Given a graph G = (V; E) we deene e(X), the mean eccentricity of a vertex X, as the average distance from X to all the other vertices of the graph. The computation of this parameter appears to be nontrivial in the case of the de Bruijn networks. In this paper we consider upper and lower bounds for e(X). For the directed de Bruijn network, we provide tight bounds as well as the extremal vertices which reach these bounds. These bounds are expressed as the diameter minus some constants. In the case of undirected networks, the computation turns out to be more diicult. We provide lower and upper bounds which diier from the diameter by some small constants. We conjecture that the vertices of the form a a have the largest mean eccentricity. Numerical computations indicate that the conjecture holds for binary de Bruijn networks with diameters up to 18. We prove that the asymptotic diierence, when the diameter goes to innnity, between the mean eccentricities of an arbitrary vertex and that of a a is smaller than a small constant tending to zero with the degree. We also provide a simple recursive scheme for the computation of the asymptotic mean eccentricity of the vertices a a. A by-product of our analysis is that in both directed and undirected de Bruijn networks, most of the vertices are at distance near from the diameter and that all of the mean eccentricities tend to the diameter when the degree goes to innnity.
62682777
Texture classification through directional empirical mode decomposition
This work presents a method for texture classification through directional empirical mode decomposition (DEMD). Although there have been many filtering based techniques proposed for texture retrieval, problems of non-adaptivity and redundancy are still hard to solve simultaneously. As a technique being introduced into signal processing, empirical mode decomposition (EMD) is an adaptive and approximately orthogonal filtering process. To apply EMD to texture classification, we propose a new method of extending 1-D EMD to 2-D case called DEMD. The approach adaptively decomposes images into local narrow band ingredients-intrinsic mode functions (IMFs) and extracts their features including frequency and envelopes. To improve its classification ability the fractal dimensions of the IMFs are also considered. Decomposition of several directions is computed for rotation invariance. Experiments for textures in Brodatz set and USC database indicate the effectiveness of our technique.
14189544
Verification, refinement and scheduling of real-time programs
Abstract A real-time program can be developed by refining a specification into program code. Verification of the timing properties of the program is then usually done at two levels: verification of the ordering of timed actions in the program and proof that execution of the program on a specific system will meet its timing requirements. Refinement is done within a formal model but the second step requires a different framework in which scheduling theory analysis is used and actual program execution times can be taken into account. The implementation of a program on a system is said to be feasible or schedulable if it will meet all the timing deadlines. This paper shows how the feasibility of scheduling a real-time program can also be proved as a step in the refinement of the program from its specification. Verification of this step of refinement makes use of methods from scheduling theory within a formal system development framework.
13865796
Virtual Screening of Novel Noncovalent Inhibitors for SARS-CoV 3C-like Proteinase
The SARS coronavirus 3C-like proteinase is considered as a potential drug design target for the treatment of severe acute respiratory syndrome (SARS). Owing to the lack of available drugs for the treatment of SARS, the discovery of inhibitors for SARS coronavirus 3C-like proteinase that can potentially be optimized as drugs appears to be highly desirable. We have built a "flexible" three-dimensional model for SARS 3C-like proteinase by homology modeling and multicanonical molecular dynamics method and used the model for virtual screening of chemical databases. After Dock procedures, strategies including pharmocophore model, consensus scoring, and "drug-like" filters were applied in order to accelerate the process and improve the success rate of virtual docking screening hit lists. Forty compounds were purchased and tested by HPLC and colorimetric assay against SARS 3C-like proteinase. Three of them including calmidazolium, a well-known antagonist of calmodulin, were found to inhibit the enzyme with an apparent K(i) from 61 to 178 microM. These active compounds and their binding modes provide useful information for understanding the binding sites and for further selective drug design against SARS and other coronavirus.
5771284
Face relighting with radiance environment maps
A radiance environment map pre-integrates a constant surface reflectance with the lighting environment. It has been used to generate photo-realistic rendering at interactive speed. However, one of its limitations is that each radiance environment map can only render the object, which has the same surface reflectance as what it integrates. We present a ratio-image based technique to use a radiance environment map to render diffuse objects with different surface reflectance properties. This method has the advantage that it does not require the separation of illumination from reflectance, and it is simple to implement and runs at interactive speed. In order to use this technique for human face relighting, we have developed a technique that uses spherical harmonics to approximate the radiance environment map for any given image of a face. Thus we are able to relight face images when the lighting environment rotates. Another benefit of the radiance environment map is that we can interactively modify lighting by changing the coefficients of the spherical harmonics basis. Finally we can modify the lighting condition of one person's face so that it matches the new lighting condition of a different person's face image assuming the two faces have similar skin albedos.