Identification and classification of animal fibres using artificial neural networks

It has been an important and challenging task to classify and evaluate the contents in wool blends. Quantitative characterisation of animal fibre scale patterns has attracted considerable attention, since it is the major evidence for identification and subsequent classification purpose. Although techniques such as imaging processing and linear demarcation functions have been used to identify unknown fibre type with some success, a more comprehensive approach is required to perform this task. In this paper, a new approach is presented, which employs non-linear demarcation functions by using an artificial neural network (ANN). Based on scale pattern features extracted by using image processing techniques the artificial neural network (ANN) model is to classify mohair and merino fibres. It is observed that the techniques developed in this work are very effective and have the potential to be applied to other animal fibres.

(Pan-)animal magics : ecofeminist ethics and aesthetics in the Web

The 1990s has often been dubbed 'The Decade of the Environment'. Pollution, deforestation and desertification, ozone destruction, endangerment of species of animals and wildlife, vanishing wildernesses, and energy conservation are some of the visible environmental concerns which have gained international recognition. A less visible but potentially just as important environmental concern has been raised by ecological feminists. This is a concern about the connections historical, empirical, theoretical, symbolic, and experiential between the domination of women and the domination of non-human nature.

Intelligent animal fibre identification and classification

To develop an objective and repeatable method of identification and classification of animal fibres, two different integrated systems were developed to mimic the human brain's ability to undertake feature extraction and discrimination of animal fibres. Both integrated systems are basically composed of an image processing system and an artificial neural network system.

Australian legal regime on animal based bio-medical research

This thesis, by using evaluative criteria based on overseas law, scientific evidence, philosophy and ethics, concluded that the Australian legal regime regarding animal based bio-medical research for human benefit only partly met one of that regime's major objectives of adequately protecting research animals during the entire research process.

Companion animal visitation and its effectiveness with stroke patients

The study employed a randomised controlled trial design to determine whether a companion animal intervention had any effect on wellbeing and quality of life in patients who were admitted to hospital after suffering a stroke. The study found significant benefits for their wellbeing and improvements in quality of life.

Variation of fibre diameter coefficient of variation and fibre curvature across mohair fleeces: Implications for animal selection, genetic selection and fleece evaluation

The presentwork aimed to determine howthe average fibre diameter coefficient of variation (CVD) and fibre curvature (FC) differences between nine sampling sites vary between sex and flock, to identify differences in variability between sampling sites as a result of between animal and between sire variability and to determine correlations between sampling sites in between animal and between sire variability. Australian Angoras (n = 313) from two farms in southern Australia were sampled at 12 and 18 months of age at nine sites (mid side, belly, brisket, hind flank, hip, hock, mid back, neck, shoulder). Staples were taken prior to shearing at skin level and CVD and FC determined. For each shearing, differences in CVD and FC between sampling sites, how these differences were affected by farm, sex, and sire, and the covariance between sites for sire and individual animal effects were investigated by restricted maximum likelihood (REML) analyses. The median mid side CVD at 12 and 18 months of age ranged from 23.6 to 25.1% but the actual range was 16.8–34.2%. The median mid side FC at 12 and 18 months of age ranged from 14.4 to 18.6◦/mm but the actual range was 10.5–26.3◦/mm. The general pattern for CVDwas for the mid back, hip and neck sites to have similar CVD, the brisket, hind flank and hock sites to have larger CVD and the belly to have smaller CVD than the mid side site. The between animal variation for CVD was lowest at the mid back site. This implies that the mid back would be the most effective site for between animal selection for CVD. Heritabilities for CVD (range at 18 months 0.18–0.30) were only about half the heritabilities for mean fibre diameter in the same study. There was a marked anterior–posterior increase in FC at both farms and with both ages. The results give no clear indication of the best site for between animal selection for FC, other than that the hock should be avoided. Heritabilities for FC are moderate to high (range at 18 months 0.44–0.77) and the genetic correlations are high except for the hock. Thus genetic selection for FC at any site, other than the hock, should be effective for changing FC over the entire fleece. There was more variability between animals than between sites and sires. These results are put into context with associated research on variation in mean fibre diameter and staple length.

Variation of mohair staple length across Angora goat fleeces : implications for animal selection and fleece evaluation

The present study aimed to determine how the average mohair staple length (SL) differences between nine sampling sites vary between sex and flock, to identify differences in SL variability between sampling sites as a result of between-animal and between-sire variability and to determine SL correlations between sampling sites in between-animal and between-sire variability. Australian Angora goats (n=301) from two farms in southern Australia were sampled at 12 and 18 months of age at nine sites (mid side, belly, brisket, hind flank, hip, hock, mid back, neck and shoulder). Staples were taken prior to shearing at skin level and stretched SL determined. For each shearing, differences in SL between sampling sites, how these differences were affected by farm, sex and sire, and the covariance between sites for sire and individual animal effects were investigated by restricted maximum likelihood (REML) analyses. The median mid-side SL at 12 and 18 months of age was 110 and 130 mm, respectively, but the actual range in mid-side SL was 65–165 mm. There was an anterior–posterior decline in SL with the hock being particularly short. There was no evidence that the between-site correlation of the sire effects differed from 1, indicating that genetic selection for SL at one site will be reflected in SL over the whole fleece. However, low heritabilities of SL at the hock, belly and brisket or at any site at 12 months of age were obtained. There was more variability between sites than between sires, but the between-animal variation was greater. The hip and mid-back sites can be recommended for within-flock (culling) and genetic selection for SL due to their low sampling variability, moderate heritability and ease of location.

Identification of animal fibers with wavelet texture analysis

This paper presents the use of the wavelet transform to extract fiber surface texture features for classifying cashmere and superfine merino wool fibers. Extracting features from brightness variations caused by the cuticular scale height, shape and interval provides an effective way for characterizing different animal fibers and subsequently classifying them. This may enable the development of a completely automated and objective system for animal fiber identification.