Robust mean super-resolution for less cooperative NIR iris recognition at a distance and on the move

Less cooperative iris identification systems at a distance and on the move often suffers from poor resolution. The lack of pixel resolution significantly degrades the iris recognition performance. Super-resolution has been considered to enhance resolution of iris images. This paper proposes a pixelwise super-resolution technique to reconstruct a high resolution iris image from a video sequence of an eye. A novel fusion approach is proposed to incorporate information details from multiple frames using robust mean. Experiments on the MBGC NIR portal database show the validity of the proposed approach in comparison with other resolution enhancement techniques.

Do programs to improve business performance in small and medium manufacturing enterprise improve opportunity recognition?

Increasing awareness of the benefits of stimulating entrepreneurial behaviour in small and medium enterprises has fostered strong interest in innovation programs. Recently many western countries have invested in design innovation for better firm performance. This research presents some early findings from a study of companies which participated in an holistic approach to design innovation, where the outcomes include better business performance and better market positioning in global markets. Preliminary findings from in-depth semi-structured interviews indicate the importance of firm openness to new ways of working and developing new processes of strategic entrepreneurship. Implications for theory and practice are discussed.

Feature-domain super-resolution for IRIS recognition

Uncooperative iris identification systems at a distance suffer from poor resolution of the captured iris images, which significantly degrades iris recognition performance. Superresolution techniques have been employed to enhance the resolution of iris images and improve the recognition performance. However, all existing super-resolution approaches proposed for the iris biometric super-resolve pixel intensity values. This paper considers transferring super-resolution of iris images from the intensity domain to the feature domain. By directly super-resolving only the features essential for recognition, and by incorporating domain specific information from iris models, improved recognition performance compared to pixel domain super-resolution can be achieved. This is the first paper to investigate the possibility of feature domain super-resolution for iris recognition, and experiments confirm the validity of the proposed approach.

A vibrational spectroscopic study of the mixed anion mineral sanjuanite Al2(PO4)(SO4)(OH)•9H2O

The mineral sanjuanite Al2(PO4)(SO4)(OH)•9H2O has been characterised by Raman spectroscopy complimented by infrared spectroscopy. The mineral is characterised by an intense Raman band at 984 cm-1, assigned to the (PO4)3- ν1 symmetric stretching mode. A shoulder band at 1037 cm-1 is attributed to the (SO4)2- ν1 symmetric stretching mode. Two Raman bands observed at 1102 and 1148 cm-1 are assigned to (PO4)3- and (SO4)2- ν3 antisymmetric stretching modes. Multiple bands provide evidence for the reduction in symmetry of both anions. This concept is supported by the multiple sulphate and phosphate bending modes. Raman spectroscopy shows that there are more than one non-equivalent water molecules in the sanjuanite structure. There is evidence that structural disorder exists, shown by the complex set of overlapping bands in the Raman and infrared spectra. At least two types of water are identified with different hydrogen bond strengths. The involvement of water in the sanjuanite structure is essential for the mineral stability.

Monitoring mesenchymal stem cell cultures using image processing and pattern recognition techniques

Stem cells have attracted tremendous interest in recent times due to their promise in providing innovative new treatments for a great range of currently debilitating diseases. This is due to their potential ability to regenerate and repair damaged tissue, and hence restore lost body function, in a manner beyond the body's usual healing process. Bone marrow-derived mesenchymal stem cells or bone marrow stromal cells are one type of adult stem cells that are of particular interest. Since they are derived from a living human adult donor, they do not have the ethical issues associated with the use of human embryonic stem cells. They are also able to be taken from a patient or other donors with relative ease and then grown readily in the laboratory for clinical application. Despite the attractive properties of bone marrow stromal cells, there is presently no quick and easy way to determine the quality of a sample of such cells. Presently, a sample must be grown for weeks and subject to various time-consuming assays, under the direction of an expert cell biologist, to determine whether it will be useful. Hence there is a great need for innovative new ways to assess the quality of cell cultures for research and potential clinical application. The research presented in this thesis investigates the use of computerised image processing and pattern recognition techniques to provide a quicker and simpler method for the quality assessment of bone marrow stromal cell cultures. In particular, aim of this work is to find out whether it is possible, through the use of image processing and pattern recognition techniques, to predict the growth potential of a culture of human bone marrow stromal cells at early stages, before it is readily apparent to a human observer. With the above aim in mind, a computerised system was developed to classify the quality of bone marrow stromal cell cultures based on phase contrast microscopy images. Our system was trained and tested on mixed images of both healthy and unhealthy bone marrow stromal cell samples taken from three different patients. This system, when presented with 44 previously unseen bone marrow stromal cell culture images, outperformed human experts in the ability to correctly classify healthy and unhealthy cultures. The system correctly classified the health status of an image 88% of the time compared to an average of 72% of the time for human experts. Extensive training and testing of the system on a set of 139 normal sized images and 567 smaller image tiles showed an average performance of 86% and 85% correct classifications, respectively. The contributions of this thesis include demonstrating the applicability and potential of computerised image processing and pattern recognition techniques to the task of quality assessment of bone marrow stromal cell cultures. As part of this system, an image normalisation method has been suggested and a new segmentation algorithm has been developed for locating cell regions of irregularly shaped cells in phase contrast images. Importantly, we have validated the efficacy of both the normalisation and segmentation method, by demonstrating that both methods quantitatively improve the classification performance of subsequent pattern recognition algorithms, in discriminating between cell cultures of differing health status. We have shown that the quality of a cell culture of bone marrow stromal cells may be assessed without the need to either segment individual cells or to use time-lapse imaging. Finally, we have proposed a set of features, that when extracted from the cell regions of segmented input images, can be used to train current state of the art pattern recognition systems to predict the quality of bone marrow stromal cell cultures earlier and more consistently than human experts.

Raman microscopy study of tyrolite : a multi-anion arsenate mineral

The Raman spectrum of tyrolite, CaCu5(AsO4)2(CO3)(OH) 4.6H2O, from Brixlegg, Tyrol, Austria, is reported. Comparison with copper hydroxy-arsenate and basic carbonates was used to achieve assignments of the observed bands. The AsO43- group is characterized by two υ4 modes around 433 and 480 cm-1 plus a broad band around 840 cm-1 as the υ overlapping with the υ. The υ3 mode is observed as a single band around 355 cm -1. The CO32- υ1 mode is observed around 1035 and 1088 cm-1, although this assignment is difficult because of the in-plane OH bending vibrations at similar frequencies. Two υ4 modes are assigned to the 717 and 755 cm-1 bands. The υ3 mode is present as three bands at 1431, 1463, and 1498 cm-1. A large split caused by bridging carbonates may explain the band at 1370 cm -1. The H2O bending region shows two bands at 1635 and 1667 cm-1 together with stretching modes around 3204 and 3303 cm-1, the first associated with adsorbed H2O, while the second indicates more strongly bonded H2O. Three bands around 3534, 3438, and 3379 cm -1 are assigned to OH stretching modes of the OH groups in the crystal structure. The 202, 262, 301, 524, and 534 cm-1 bands are assigned to Cu-OH bending and stretching modes, whereas the bands around 179, 202, and 217 cm-1 are ascribed to O-(Ca, Cu)-O(H) with the O(H) at much greater distance from the cation. The bands around 503, 570, and 598 cm-1 are ascribed to the Cu-O stretching modes.

Facial expression recognition using facial movement features

Facial expression is an important channel for human communication and can be applied in many real applications. One critical step for facial expression recognition (FER) is to accurately extract emotional features. Current approaches on FER in static images have not fully considered and utilized the features of facial element and muscle movements, which represent static and dynamic, as well as geometric and appearance characteristics of facial expressions. This paper proposes an approach to solve this limitation using ‘salient’ distance features, which are obtained by extracting patch-based 3D Gabor features, selecting the ‘salient’ patches, and performing patch matching operations. The experimental results demonstrate high correct recognition rate (CRR), significant performance improvements due to the consideration of facial element and muscle movements, promising results under face registration errors, and fast processing time. The comparison with the state-of-the-art performance confirms that the proposed approach achieves the highest CRR on the JAFFE database and is among the top performers on the Cohn-Kanade (CK) database.

Improving the performance of facial expression recognition using dynamic, subtle and regional features

Human facial expression is a complex process characterized of dynamic, subtle and regional emotional features. State-of-the-art approaches on facial expression recognition (FER) have not fully utilized this kind of features to improve the recognition performance. This paper proposes an approach to overcome this limitation using patch-based ‘salient’ Gabor features. A set of 3D patches are extracted to represent the subtle and regional features, and then inputted into patch matching operations for capturing the dynamic features. Experimental results show a significant performance improvement of the proposed approach due to the use of the dynamic features. Performance comparison with pervious work also confirms that the proposed approach achieves the highest CRR reported to date on the JAFFE database and a top-level performance on the Cohn-Kanade (CK) database.

Recognition of expertise : an important concept in the acquisition of nephrology nursing expertise

The present article, which is abstracted from a larger study into the acquisition and exercise of nephrology nursing expertise, aims to explore the concept of recognition of expertise. The study used grounded theory methodology and involved 17 registered nurses who were practising in a metropolitan renal unit in New South Wales, Australia. Concurrent data collection and analysis was undertaken, incorporating participant observations and interviews. According to nurses in this study, patients, doctors and other nurses recognized that some nurses were experts while others were not. In addition, being trusted, being a role model and teaching others were important components of being recognized as an expert nephrology nurse. Of importance for nursing, the results of the present study indicate that knowledge and experience are not sufficient to ensure expert practice; recognition of expertise by others is an important function of expertise acquisition.

Evaluation of texture and geometry for dimensional facial expression recognition

Facial expression recognition (FER) algorithms mainly focus on classification into a small discrete set of emotions or representation of emotions using facial action units (AUs). Dimensional representation of emotions as continuous values in an arousal-valence space is relatively less investigated. It is not fully known whether fusion of geometric and texture features will result in better dimensional representation of spontaneous emotions. Moreover, the performance of many previously proposed approaches to dimensional representation has not been evaluated thoroughly on publicly available databases. To address these limitations, this paper presents an evaluation framework for dimensional representation of spontaneous facial expressions using texture and geometric features. SIFT, Gabor and LBP features are extracted around facial fiducial points and fused with FAP distance features. The CFS algorithm is adopted for discriminative texture feature selection. Experimental results evaluated on the publicly accessible NVIE database demonstrate that fusion of texture and geometry does not lead to a much better performance than using texture alone, but does result in a significant performance improvement over geometry alone. LBP features perform the best when fused with geometric features. Distributions of arousal and valence for different emotions obtained via the feature extraction process are compared with those obtained from subjective ground truth values assigned by viewers. Predicted valence is found to have a more similar distribution to ground truth than arousal in terms of covariance or Bhattacharya distance, but it shows a greater distance between the means.

Anion induced displacement studies in naphthalene diimide containing interpenetrated and interlocked structures

This article describes investigations into the development of supramolecular systems capable of sensing anions through either displacement type assays or molecular motion. An electron deficient naphthalene diimide thread and electron rich isophthalamide naphthohydroquinone macrocycle was shown to form a coloured pseudorotaxane assembly. Investigations into the ability of such interpenetrated systems to sense anions colorimetrically were undertaken. Anion complexation to the isophthalamide group of the macrocycle causes displacement of the naphthodiimide thread resulting in the loss of colour. The enhanced mechanically bonded binding strength between the naphthodiimide axle and the naphthohydroquinone groups of the macrocycle wheel in the corresponding rotaxane structure however, was found to negate the anion induced displacement process.

Health professionals' recognition of co-occurring alcohol and depressive disorders in youth: a survey of Australian general practitioners, psychiatrists, psychologists and mental health nurses using case vignettes

Objective: To examine whether health professionals who commonly deal with mental disorder are able to identify co occurring alcohol misuse in young people presenting with depression. Method: Between September 2006 and January 2007, a survey examining beliefs regarding appropriate interventions for mental disorder in youth was sent to 1710 psychiatrists, 2000 general practitioners (GPs), 1628 mental health nurses, and 2000 psychologists in Australia. Participants within each professional group were randomly given one of four vignettes describing a young person with a DSM-IV mental disorder. Herein is reported data from the depression and depression with alcohol misuse vignettes. Results: A total of 305 psychiatrists, 258 GPs, 292 mental health nurses and 375 psychologists completed one of the depression vignettes. A diagnosis of mood disorder was identified by at least 83.8% of professionals, with no significant differences noted between professional groups. Rates of reported co-occurring substance use disorders were substantially lower, particularly among older professionals and psychologists. Conclusions: GPs, psychologists and mental health professionals do not readily identify co-occurring alcohol misuse in young people with depression. Given the substantially negative impact of co-occurring disorders, it is imperative that health-care professionals are appropriately trained to detect such disorders promptly, to ensure young people have access to effective, early intervention.