Constructing detectors in schema complementary space for anomaly detection

This paper proposes an extended negative selection algorithm for anomaly detection. Unlike previously proposed negative selection algorithms which directly construct detectors in the complementary space of self-data space, our approach first evolves a number of common schemata through coevolutionary genetic algorithm in self-data space, and then constructs detectors in the complementary space of the schemata. These common schemata characterize self-data space and thus guide the generation of detection rules. By converting data space into schema space, we can efficiently generate an appropriate number of detectors with diversity for anomaly detection. The approach is tested for its effectiveness through experiment with the published data set iris.

An extended negative selection algorithm for anomaly detection

This paper proposes an extended negative selection algorithm for anomaly detection. Unlike previously proposed negative selection algorithms which do not make use of non-self data, the extended negative selection algorithm first acquires prior knowledge about the characteristics of the Problem space from the historial sample data by using machine learning techniques. Such data consists of both self data and non-self data. The acquired prior knowledge is represented in the form of production rules and thus viewed as common schemata which characterise the two subspaces: self-subspace and non-self-subspace, and provide important information to the generation of detection rules. One advantage of our approach is that it does not rely on the structured representation of the data and can be applied to general anomaly detection. To test the effectiveness, we test our approach through experiments with the public data set iris and KDDrsquo99 published data set.

Applying both positive and negative selection to supervised learning for anomaly detection

This paper presents a novel approach of applying both positive selection and negative selection to supervised learning for anomaly detection. It first learns the patterns of the normal class via co-evolutionary genetic algorithm, which is inspired from the positive selection, and then generates synthetic samples of the anomaly class, which is based on the negative selection in the immune system. Two algorithms about synthetic generation of the anomaly class are proposed. One deals with data sets containing a few anomalous samples; while the other deals with data sets containing no anomalous samples at all. The experimental results on some benchmark data sets from UCI data set repertory show that the detection rate is improved evidently, accompanied by a slight increase in false alarm rate via introducing novel synthetic samples of the anomaly class. The advantages of our method are the increased ability of classifiers in identifying both previously known and innovative anomalies, and the maximal degradation of overfitting phenomenon.

Preparation and characterisation of new titanium based alloys for orthopaedic and dental applications

Various types of titanium alloys with high strength and low elastic modulus and, at the same time, vanadium and aluminium free have been developed as surgical biomaterials in recent years. Moreover, porous metals are promising hard tissue implants in orthopaedic and dentistry, where they mimic the porous structure and the low elastic modulus of natural bone. In the present study, new biocompatible Ti-based alloy foams with approximate relative densities of 0.4, in which Sn and Nb were added as alloying metals, were synthesised through powder metallurgy method.
The new alloys were prepared by mechanical alloying and subsequently sintered at high temperature using a vacuum furnace. The characteristics and the processability of the ball milled powders and the new porous titanium-based alloys were characterised by X-ray diffraction, optical
microscopy and scanning electron microscopy .The mechanical properties of the new titanium alloys were examined by Vickers microhardness measurements and compression testing.

Computer aided analysis of dental radiographic images

This paper is a result of a fruitful cooperation between the computer science and the dental diagnosis experiences. The study presents a new approach of applying computer algorithms to radiographic images of dental implantation used for bone regeneration. We focus here only on the contribution of the computer assistance to the clinical research as the periodontal therapy is beyond the scope of this paper. The proposed system is based on a pattern recognition approach, directed to recognize density changes in the intra-bony affected areas of patients. It comprises different modules with new algorithms specially designed to treat the patients’ radiographic images more accurately. The system includes digitizing, detecting the complicated region of interest (ROI), defining reference area to correct any projection discrepancy of the follow up images, and finally to extract the distinguishing features of the ROI as a basis for determining the rate of new bone density accumulation. This study is applied to two typical dental cases for a patient who received two different operations. The results are very encouraging and more accurate than traditional techniques reported before.

Immunology-based subspace detectors for anomaly detection

A key problem in high dimensional anomaly detection is that the time spent in constructing detectors by the means of generateand-test is tolerable. In fact, due to the high sparsity. of the data, it is ineffective to construct detectors in the whole data space. Previous investigations have shown that most essentIal patterns can be discovered in different subspaces. This inspires us to construct detectors in signIficant subspaces only for anomaly detection. We first use ENCLUS-based method to discover all significant subspaces and .then use a greedy-growth algorithm to construct detectors in each subspace. The elements used to constItute a detector are gods Instead of data points, which makes the time-consumption irrelevant to the size of the nonnal data. We test the effectiveness and efficiency of our method on both synthetic and benchmark datasets. The results reveal that our method is particularly useful in anomaly detection in high dimensional data spaces.

Wait no more : the use of private dental services by welfare recipients in Australia

Dental services in Australia are available both privately and publicly. However, access to public dental services, like access to public hospital services for non-urgent treatment, is subject to a considerable waiting period. Moreover, access to public dental services is restricted to certain categories of welfare beneficiaries who qualify for a health care card. Because of the waiting time for public treatment, there is a frequent call for more public dental resources. This paper addresses the issue of what the waiting time for public dental services represents. One view largely confirmed by our research is that state governments are using the waiting time as a way of trying to push more and more people into the private sector. We find that more and more health care card holders are using the
private sector for dental services.

Australian dental policy reform and the use of dental therapists and hygienists

Oral diseases including dental caries and periodontal disease are among the most prevalent and costly diseases in Australia today. Around 5.4% of Australia’s health dollar is spent on dental services totalling around $2.6 billion, 84% of which are delivered through the private sector (AIHW 2001). The other 16% is spent providing public sector services in varied and inadequate ways. While disease rates among school children have declined significantly in the past 20 years the gains made among children are not flowing on to adult dentitions and our aging population will place increasing demands on an inadequate system into the future (AHMAC 2001). Around 50% of adults do not received regular care and this has implications for widening health inequalities as the greatest burden falls on lower income groups (AIHW DSRU 2001). The National Competition Policy agenda has initiated, Australia-wide, reviews of dental legislation applying to delivery of services by dentists, dental specialists, dental therapists and hygienists and dental technicians and prosthetists. The review of the Victorian Dentists Act 1972, was completed first in 1999, followed by the other Australian states with Queensland, the ACT and the Northern Territory still developing legislation. One of the objectives of the new Victorian Act is to ‘…promote access to dental care’. This study has grown out of the need to know more about how dental therapists and hygienists might be utilised to achieve this and the legislative frameworks that could enable such roles. This study used qualitative methods to explore dental health policy making associated with strategies that may increase access to dental care using dental therapists and hygienists. The study used a multiple case study design to critically examine the dental policy development process around the Review of the Dentists Act 1972 in Victoria; to assess legislative and regulatory dental policy reforms in other states in Australia and to conduct a comparative analysis of dental health policy as it relates to dental auxiliary practice internationally. Data collection has involved (I) semi-structured interviews with key participants and stakeholders in the policy development processes in Victoria, interstate and overseas, and (ii) analysis of documentary data sources. The study has taken a grounded theory approach whereby theoretical issues that emerged from the Victorian case study were further developed and challenged in the subsequent interstate and international case studies. A component of this study has required the development of indicators in regulatory models for dental hygienists and therapists that will increase access to dental care for the community. These indicators have been used to analyse regulation reform and the likely impacts in each setting. Despite evidence of need, evidence of the effectiveness and efficiency of dental therapists and hygienists, and the National Competition Policy agenda of increasing efficiency, the legislation reviews have mostly produces only minor changes. Results show that almost all Australian states have regulated dental therapists and hygienists in more prescriptive ways than they do dentists. The study has found that dental policy making is still dominated by the views of private practice dentists under elitist models that largely protect dentist authority, autonomy and sovereignty. The influence of dentist professional dominance has meant that governments have been reluctant to make sweeping changes. The study has demonstrated alternative models of regulation for dental therapists and hygienists, which would allow wider utilisation of their skills, more effective use of public sector funding, increased access to services and a grater focus on preventive care. In the light of theses outcomes, there is a need to continue to advocate for changes that will increase the public health focus of oral health care.

The halloween effect and Japanese equity prices : myth or exploitable anomaly

Bouman and Jacobsen (American Economic Review 92(5), 1618–1635, 2002) examine monthly stock returns for major world stock markets and conclude that returns are significantly lower during the May–October periods versus the November–April periods in 36 of 37 markets examined. They argue that, in general, the Halloween strategy outperforms the buy and hold strategy thereby casting doubt on the validity of the efficient market paradigm. More recently, Maberly and Pierce (Econ Journal Watch 1(1), 29–46, 2004) re-examine the evidence for U.S. equity prices and conclude that Bouman and Jacobsen’s results are not robust to alternative model specifications. Extending prior research, this paper examines the robustness of the Halloween strategy to alternative model specifications for Japanese equity prices. The Halloween effect is concentrated in the period prior to the introduction of Nikkei 225 index futures in September 1986. After the internationalization of Japanese financial markets in the mid-1980s, the Halloween effect disappears.

Computational immunology for anomaly detection

The thesis makes a significant contribution to the issue of anomaly detection by introducing a computational immunology approach. Immunity-based anomaly detection in high dimensional space is systematically investigated and the proposed hybrid method (combining data mining techniques and computational immunology) improves both accuracy and efficiency.

Theory of planned behaviour and implementation intentions in dental attendance

The thesis used a model of health behaviour to examine the predictors of dental attendance. Older respondents who had strong intentions, low perceived vulnerability, stable plans to attend, and were influenced by significant others were more likely to have attended the dentist for preventive care in the last 12 months. The portfolio concludes that attachment theory is a useful conceptual framework for enhancing our understanding of the antecedents and consequences of childhood sexual abuse.

Biomimetic porous titanium scaffolds for orthopaedic and dental applications

The development of artificial organs and implants for replacement of injured and diseased hard tissues such as bones, teeth and joints is highly desired in orthopedic surgery. Orthopedic prostheses have shown an enormous success in restoring the function and offering high quality of life to millions of individuals each year. Therefore, it is pertinent for an engineer to set out new approaches to restore the normal function of impaired hard tissues.

Over the last few decades, a large number of metals and applied materials have been developed with significant improvement in various properties in a wide range of medical applications. However, the traditional metallic bone implants are dense and often suffer from the problems of adverse reaction, biomechanical mismatch and lack of adequate space for new bone tissue to grow into the implant. Scientific advancements have been made to fabricate porous scaffolds that mimic the architecture and mechanical properties of natural bone. The porous structure provides necessary framework for the bone cells to grow into the pores and integrate with host tissue, known as osteointegration. The appropriate mechanical properties, in particular, the low elastic modulus mimicking that of bone may minimize or eliminate the stress-shielding problem. Another important approach is to develop biocompatible and corrosion resistant metallic materials to diminish or avoid adverse body reaction. Although numerous types of materials can be involved in this fast developing field, some of them are more widely used in medical applications. Amongst them, titanium and some of its alloys provide many advantages such as excellent biocompatibility, high strength-to-weight ratio, lower elastic modulus, and superior corrosion resistance, required for dental and orthopedic implants. Alloying elements, i.e. Zr, Nb, Ta, Sn, Mo and Si, would lead to superior improvement in properties of titanium for biomedical applications.

New processes have recently been developed to synthesize biomimetic porous titanium scaffolds for bone replacement through powder metallurgy. In particular, the space holder sintering method is capable of adjusting the pore shape, the porosity, and the pore size distribution, notably within the range of 200 to 500 m as required for osteoconductive applications. The present chapter provides a review on the characteristics of porous metal scaffolds used as bone replacement as well as fabrication processes of porous titanium (Ti) scaffolds through a space holder sintering method. Finally, surface modification of the resultant porous Ti scaffolds through a biomimetic chemical technique is reviewed, in order to ensure that the surfaces of the scaffolds fulfill the requirements for biomedical applications.