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

The Eat Smart Study : a randomised controlled trial of a reduced carbohydrate versus a low fat diet for weight loss in obese adolescents

Background Despite the recognition of obesity in young people as a key health issue, there is limited evidence to inform health professionals regarding the most appropriate treatment options. The Eat Smart study aims to contribute to the knowledge base of effective dietary strategies for the clinical management of the obese adolescent and examine the cardiometablic effects of a reduced carbohydrate diet versus a low fat diet. Methods and design Eat Smart is a randomised controlled trial and aims to recruit 100 adolescents over a 2½ year period. Families will be invited to participate following referral by their health professional who has recommended weight management. Participants will be overweight as defined by a body mass index (BMI) greater than the 90th percentile, using CDC 2000 growth charts. An accredited 6-week psychological life skills program ‘FRIENDS for Life’, which is designed to provide behaviour change and coping skills will be undertaken prior to volunteers being randomised to group. The intervention arms include a structured reduced carbohydrate or a structured low fat dietary program based on an individualised energy prescription. The intervention will involve a series of dietetic appointments over 24 weeks. The control group will commence the dietary program of their choice after a 12 week period. Outcome measures will be assessed at baseline, week 12 and week 24. The primary outcome measure will be change in BMI z-score. A range of secondary outcome measures including body composition, lipid fractions, inflammatory markers, social and psychological measures will be measured. Discussion The chronic and difficult nature of treating the obese adolescent is increasingly recognised by clinicians and has highlighted the need for research aimed at providing effective intervention strategies, particularly for use in the tertiary setting. A structured reduced carbohydrate approach may provide a dietary pattern that some families will find more sustainable and effective than the conventional low fat dietary approach currently advocated. This study aims to investigate the acceptability and effectiveness of a structured reduced dietary carbohydrate intervention and will compare the outcomes of this approach with a structured low fat eating plan. Trial Registration: The protocol for this study is registered with the International Clinical Trials Registry (ISRCTN49438757).

The influence of maternal ethnic group and diet on breast milk fatty acid composition

INTRODUCTION: Breast milk fatty acids play a major role in infant development. However, no data have compared the breast milk composition of different ethnic groups living in the same environment. We aimed to (i) investigate breast milk fatty acid composition of three ethnic groups in Singapore and (ii) determine dietary fatty acid patterns in these groups and any association with breast milk fatty acid composition. MATERIALS AND METHODS: This was a prospective study conducted at a tertiary hospital in Singapore. Healthy pregnant women with the intention to breastfeed were recruited. Diet profile was studied using a standard validated 3-day food diary. Breast milk was collected from mothers at 1 to 2 weeks and 6 to 8 weeks postnatally. Agilent gas chromatograph (6870N) equipped with a mass spectrometer (5975) and an automatic liquid sampler (ALS) system with a split mode was used for analysis. RESULTS: Seventy-two breast milk samples were obtained from 52 subjects. Analysis showed that breast milk ETA (Eicosatetraenoic acid) and ETA:EA (Eicosatrienoic acid) ratio were significantly different among the races (P = 0.031 and P = 0.020), with ETA being the highest among Indians and the lowest among Malays. Docosahexaenoic acid was significantly higher among Chinese compared to Indians and Malays. No difference was demonstrated in n3 and n6 levels in the food diet analysis among the 3 ethnic groups. CONCLUSIONS: Differences exist in breast milk fatty acid composition in different ethnic groups in the same region, although no difference was demonstrated in the diet analysis. Factors other than maternal diet may play a role in breast milk fatty acid composition.

Frequency response function based structural damage detection using artificial neural networks

Damage detection in structures has become increasingly important in recent years. While a number of damage detection and localization methods have been proposed, few attempts have been made to explore the structure damage with frequency response functions (FRFs). This paper illustrates the damage identification and condition assessment of a beam structure using a new frequency response functions (FRFs) based damage index and Artificial Neural Networks (ANNs). In practice, usage of all available FRF data as an input to artificial neural networks makes the training and convergence impossible. Therefore one of the data reduction techniques Principal Component Analysis (PCA) is introduced in the algorithm. In the proposed procedure, a large set of FRFs are divided into sub-sets in order to find the damage indices for different frequency points of different damage scenarios. The basic idea of this method is to establish features of damaged structure using FRFs from different measurement points of different sub-sets of intact structure. Then using these features, damage indices of different damage cases of the structure are identified after reconstructing of available FRF data using PCA. The obtained damage indices corresponding to different damage locations and severities are introduced as input variable to developed artificial neural networks. Finally, the effectiveness of the proposed method is illustrated and validated by using the finite element modal of a beam structure. The illustrated results show that the PCA based damage index is suitable and effective for structural damage detection and condition assessment of building structures.

Inhibition of guinea-pig renal [Na + K]-ATPase by normotensive human plasma : effects of a high sodium diet

The effect of plasma taken from normotensive humans, while on a low and high sodium diet, on [Na + K]-ATPase and 3H-ouabain binding was measured in tubules from guinea-pig kidneys. Plasma from the high sodium, compared to the low sodium, diet period: (a) inhibited [Na + K]-ATPase activity; (b) decreased 3H-ouabain affinity for binding sites; (c) increased the number of available 3H-ouabain binding sites; (d) decreased [Na + K]-ATPase turnover (activity/3H-ouabain binding sites). The inhibition of [Na + K]-ATPase suggests an increase in a (possible) natriuretic factor. The decreased affinity of 3H-ouabain binding suggests an endogenous ouabainoid, which may be the natriuretic factor.