GYAN: A methodology for rule extraction from artificial neural networks

Artificial neural network (ANN) learning methods provide a robust and non-linear approach to approximating the target function for many classification, regression and clustering problems. ANNs have demonstrated good predictive performance in a wide variety of practical problems. However, there are strong arguments as to why ANNs are not sufficient for the general representation of knowledge. The arguments are the poor comprehensibility of the learned ANN, and the inability to represent explanation structures. The overall objective of this thesis is to address these issues by: (1) explanation of the decision process in ANNs in the form of symbolic rules (predicate rules with variables); and (2) provision of explanatory capability by mapping the general conceptual knowledge that is learned by the neural networks into a knowledge base to be used in a rule-based reasoning system. A multi-stage methodology GYAN is developed and evaluated for the task of extracting knowledge from the trained ANNs. The extracted knowledge is represented in the form of restricted first-order logic rules, and subsequently allows user interaction by interfacing with a knowledge based reasoner. The performance of GYAN is demonstrated using a number of real world and artificial data sets. The empirical results demonstrate that: (1) an equivalent symbolic interpretation is derived describing the overall behaviour of the ANN with high accuracy and fidelity, and (2) a concise explanation is given (in terms of rules, facts and predicates activated in a reasoning episode) as to why a particular instance is being classified into a certain category.

Probabilistic visual recognition of artificial landmarks for simultaneous localization and mapping

Probabilistic robotics, most often applied to the problem of simultaneous localisation and mapping (SLAM), requires measures of uncertainly to accompany observations of the environment. This paper describes how uncertainly can be characterised for a vision system that locates coloured landmark in a typical laboratory environment. The paper describes a model of the uncertainly in segmentation, the internal camera model and the mounting of the camera on the robot. It =plains the implementation of the system on a laboratory robot, and provides experimental results that show the coherence of the uncertainly model,

Identification and control of induction machines using artificial neural networks

The use of artificial neural networks (ANNs) to identify and control induction machines is proposed. Two systems are presented: a system to adaptively control the stator currents via identification of the electrical dynamics, and a system to adaptively control the rotor speed via identification of the mechanical and current-fed system dynamics. Both systems are inherently adaptive as well as self-commissioning. The current controller is a completely general nonlinear controller which can be used together with any drive algorithm. Various advantages of these control schemes over conventional schemes are cited, and the combined speed and current control scheme is compared with the standard vector control scheme

Identification and control of induction machines using artificial neural networks

This paper proposes the use of artificial neural networks (ANNs) to identify and control an induction machine. Two systems are presented: a system to adaptively control the stator currents via identification of the electrical dynamics; and a system to adaptively control the rotor speed via identification of the mechanical and current-fed system dynamics. Various advantages of these control schemes over other conventional schemes are cited and the performance of the combined speed and current control scheme is compared with that of the standard vector control scheme

Model-order selection in Zernike polynomial expansion of corneal surfaces using the efficient detection criterion

Corneal-height data are typically measured with videokeratoscopes and modeled using a set of orthogonal Zernike polynomials. We address the estimation of the number of Zernike polynomials, which is formalized as a model-order selection problem in linear regression. Classical information-theoretic criteria tend to overestimate the corneal surface due to the weakness of their penalty functions, while bootstrap-based techniques tend to underestimate the surface or require extensive processing. In this paper, we propose to use the efficient detection criterion (EDC), which has the same general form of information-theoretic-based criteria, as an alternative to estimating the optimal number of Zernike polynomials. We first show, via simulations, that the EDC outperforms a large number of information-theoretic criteria and resampling-based techniques. We then illustrate that using the EDC for real corneas results in models that are in closer agreement with clinical expectations and provides means for distinguishing normal corneal surfaces from astigmatic and keratoconic surfaces.

Fast hole surface conduction observed for indoline sensitizer dyes immobilized at fluorine-doped tin oxide - TiO2 surfaces

The indoline dyes D102, D131, D149, and D205 have been characterized when adsorved on fluorine-doped tin oxide (FTO) and TiO2 electrode surfaces. Adsorption from 50:50 acetonitrile - tert-butanol onto flourine-doped tin oxide (FTO) allows approximate Langmuirian binding constants of 6.5 x 10(4), 2.01 x 10(3), 2.0 x 10(4), and 1.5 x 10(4) mol-1 dm3, respectively, to be determined. Voltammetric data obtained in acetonitrile/0.1 M NBu4PF6 indicate reversible on-electron oxidation at Emid = 0.94, 0.91, 0.88, and 0.88 V vs Ag/AgCI(3 M KCI), respectively, with dye aggregation (at high coverage) causing additional peak features at more positive potentials. Slow chemical degradation processes and electron transfer catalysis for iodine oxidation were observed for all four oxidezed indolinium cations. When adsorbed onto TiO2 nanoparticle films (ca. 9nm particle diameter and ca.3/um thickness of FTO0, reversible voltammetric responses with Emid = 1.08, 1.156, 0.92 and 0.95 V vs Ag/AgCI(3 M KCI), respectively, suggest exceptionally fast hole hopping diffusion (with Dapp > 5 x 10(-9) m2 s-1) for adsorbed layers of four indoline dyes, presumably due to pie-pie stacking in surface aggregates. Slow dye degradation is shown to affect charge transport via electron hopping. Spectrelectrochemical data for the adsorbed indoline dyes on FTO-TiO2 revealed a red-shift of absorption peaks after oxidation and the presence of a strong charge transfer band in the near-IR region. The implications of the indoline dye reactivity and fast hole mobility for solar cell devices are discussed.

Early osteogenic response of osteoprogenitor cells on modified titanium implant surfaces leads to improved osteogenesis

Background: Implant surface micro-roughness and hydrophilicity are known to improve the osteogenic differentiation potential of osteoprogenitor cells. This study was aimed to determine whether topographically and chemically modified titanium implant surfaces stimulate an initial osteogenic response in osteoprogenitor cells, which leads to their improved osteogenesis. ----- ----- Methods: Statistical analysis of microarray gene expression profiling data available from studies (at 72 hours) on sand-blasted, large grit acid etched (SLA) titanium surfaces was performed. Subsequently, human osteoprogenitor cells were cultured on SLActive (hydrophilic SLA), SLA and polished titanium surfaces for 24 hours, 3 days and 7 days. The expression of BMP2, BMP6, BMP2K, SP1, ACVR1, FZD6, WNT5A, PDLIM7, ITGB1, ITGA2, OCN, OPN, ALP and RUNX2 were studied using qPCR. ----- ----- Results: Several functional clusters related to osteogenesis were highlighted when genes showing statistically significant differences (from microarray data at 72 hours) in expression on SLA surface (compared with control surface) were analysed using DAVID (online tool). This indicates that differentiation begins very early in response to modified titanium surfaces. At 24 hours, ACVR1 (BMP pathway), FZD6 (Wnt pathway) and SP1 (TGF-β pathway) were significantly up-regulated in cultures on the SLActive surface compared to the other surfaces. WNT5A and ITGB1 also showed higher expression on the modified surfaces. Gene expression patterns on Day 3 and Day 7 did not reveal any significant differences.----- ----- Conclusion: These results suggest that the initial molecular response of osteoprogenitor cells to modified titanium surfaces may be responsible for an improved osteogenic response via the BMP and Wnt signalling pathways.