The problem child in Australian patent law : "fair" basing

The concept of "fair basing" is widely acknowledged as a difficult area of patent law. This article maps the development of fair basing law to demonstrate how some of the difficulties have arisen. Part I of the article traces the development of the branches of patent law that were swept under the nomenclature of "fair basing" by British legislation in 1949. It looks at the early courts' approach to patent construction, examines the early origin of fair basing and what it was intended to achiever. Part II of the article considers the modern interpretation of fair basing, which provides a striking contrast to its historical context. Without any consistent judicial approach to construction the doctrine has developed inappropriately, giving rise to both over-strict and over-generous approaches.

The nine lives of Vietnam's new competition law

Vietnam's present draft of the proposed new Law on Competition is currently in its ninth version. Although there is a need to enact legislation as quickly as possible, Vietnam cannot rush the drafting process. Under its Bilateral Trade Agreement with the USA, Vietnam has committed to improve the quality of its laws and consistency of its legislative framework. Since the Law on Competition will be fundamental in establishing the legal framework for a more coherent and effective competition regime, and will have profound influences on Vietnam's objective of becoming a socialist-oriented market economy, its provisions must be well constructed and well considered, and this takes time. This article shows how the proposed Law is being crafted as compared to older drafts which sheds light on changes in policy during the drafting process. Where possible, the Draft is also compared with the laws in other jurisdictions for any assistance they might lend. In this author's opinion not all the changes are positive but any defects in the draft are not intractable and can be remedied prior to promulgation.

More legislative traffic on the 'Doi Moi' superhighway : technology transfer, IP and competition law in Vietnam

Since 1986 Vietnam has been engaged in the transition from a centrally-controlled economy to a socialist-oriented market economy (the 'doi moi' renovation). The process for global economic integration has been slow given the magnitude of necessary reforms. Consequently technology entrepreneurs often discount Vietnam as a possible commercialization base which means that it is not realising its economic potential as a hub of technology transfer in the Asia-Pacific region. Three significant factors in the current uncertainty are Vietnam's laws on competition, intellectual property and technology transfer. Another problem is the lack of literature on these laws. This article first discusses the conceptual relationship between competition, intellectual property and technology transfer. Hopefully the article will provide some guidance for the technology entrepreneur considering foreign direct investment (FDI) in Vietnam. The bottom line is that these laws still need further reform to bolster entrepreneurial confidence.

Elliptic curves, group law, and efficient computation

This thesis is about the derivation of the addition law on an arbitrary elliptic curve and efficiently adding points on this elliptic curve using the derived addition law. The outcomes of this research guarantee practical speedups in higher level operations which depend on point additions. In particular, the contributions immediately find applications in cryptology. Mastered by the 19th century mathematicians, the study of the theory of elliptic curves has been active for decades. Elliptic curves over finite fields made their way into public key cryptography in late 1980’s with independent proposals by Miller [Mil86] and Koblitz [Kob87]. Elliptic Curve Cryptography (ECC), following Miller’s and Koblitz’s proposals, employs the group of rational points on an elliptic curve in building discrete logarithm based public key cryptosystems. Starting from late 1990’s, the emergence of the ECC market has boosted the research in computational aspects of elliptic curves. This thesis falls into this same area of research where the main aim is to speed up the additions of rational points on an arbitrary elliptic curve (over a field of large characteristic). The outcomes of this work can be used to speed up applications which are based on elliptic curves, including cryptographic applications in ECC. The aforementioned goals of this thesis are achieved in five main steps. As the first step, this thesis brings together several algebraic tools in order to derive the unique group law of an elliptic curve. This step also includes an investigation of recent computer algebra packages relating to their capabilities. Although the group law is unique, its evaluation can be performed using abundant (in fact infinitely many) formulae. As the second step, this thesis progresses the finding of the best formulae for efficient addition of points. In the third step, the group law is stated explicitly by handling all possible summands. The fourth step presents the algorithms to be used for efficient point additions. In the fifth and final step, optimized software implementations of the proposed algorithms are presented in order to show that theoretical speedups of step four can be practically obtained. In each of the five steps, this thesis focuses on five forms of elliptic curves over finite fields of large characteristic. A list of these forms and their defining equations are given as follows: (a) Short Weierstrass form, y2 = x3 + ax + b, (b) Extended Jacobi quartic form, y2 = dx4 + 2ax2 + 1, (c) Twisted Hessian form, ax3 + y3 + 1 = dxy, (d) Twisted Edwards form, ax2 + y2 = 1 + dx2y2, (e) Twisted Jacobi intersection form, bs2 + c2 = 1, as2 + d2 = 1, These forms are the most promising candidates for efficient computations and thus considered in this work. Nevertheless, the methods employed in this thesis are capable of handling arbitrary elliptic curves. From a high level point of view, the following outcomes are achieved in this thesis. - Related literature results are brought together and further revisited. For most of the cases several missed formulae, algorithms, and efficient point representations are discovered. - Analogies are made among all studied forms. For instance, it is shown that two sets of affine addition formulae are sufficient to cover all possible affine inputs as long as the output is also an affine point in any of these forms. In the literature, many special cases, especially interactions with points at infinity were omitted from discussion. This thesis handles all of the possibilities. - Several new point doubling/addition formulae and algorithms are introduced, which are more efficient than the existing alternatives in the literature. Most notably, the speed of extended Jacobi quartic, twisted Edwards, and Jacobi intersection forms are improved. New unified addition formulae are proposed for short Weierstrass form. New coordinate systems are studied for the first time. - An optimized implementation is developed using a combination of generic x86-64 assembly instructions and the plain C language. The practical advantages of the proposed algorithms are supported by computer experiments. - All formulae, presented in the body of this thesis, are checked for correctness using computer algebra scripts together with details on register allocations.

Health law in Australia

Health Law in Australia is the first book to deal with health law on a comprehensive national basis. In a field of law that is becoming increasingly important and where the demand for expertise is rapidly expanding, Health Law in Australia takes a logical, structured approach to an examination of the law in all Australian jurisdictions. By covering all the major areas in this diverse field of law, Health Law in Australia enhances the understanding of the discipline as a whole. Beginning with an exploration of the general principles of health law, including chapters on “Medical Negligence”, “Children and Consent”, and “Confidentiality, Privacy, and Access to Health Records”, the book goes on to consider beginning-of-life and end-of-life issues before concluding with chapters on emerging areas in health law, such as biotechnology and medical research. The contributing authors include national leaders in the field who are specialists in these areas of health law and who can therefore reveal to readers the results of their research. Health Law in Australia has been written for those with a legal background and is essential reading for undergraduate law students, postgraduate law students, researchers and scholars in the disciplines of law, health and medicine, as well as legal practitioners, government departments and bodies in the health area, and private health providers.

Health law : scope, sources and forces

• For the purposes of this chapter, “health law” encapsulates regulation of the medical and health professions, the administration of health services and the maintenance of public health to the extent that it is connected to the provision of health services. • There are diverging views as to whether health law can be regarded as a discrete “area of law”. • Health law draws on other areas of law such as tort law, criminal law and family law. It is also draws upon other disciplines, most notably medical and health ethics. • Social and economic forces have influenced the development and direction of health law, and these forces may become even more influential as the century develops. • The increasingly globalised world has implications for Australia’s health systems and raises questions and creates commitments in respect of the international community. • Technological developments, including in respect of treatment, diagnosis and information management, create ongoing challenges for health law. • Patient rights, human rights and consumerism are increasingly key drivers in the development of health law. • Health law is significant to contemporary Australian society because of the gravity of the topics that fall within its ambit, its social relevance to so many aspects of human existence and endeavour, the important role it plays in protecting the vulnerable, and the extent to which it engages with fundamental principles of justice.

Mining robotics

Mining is the process of extracting mineral resources from the Earth for commercial value. It is an ancient human activity which can be traced back to Palaeolithic times (43 000 years ago), where for example the mineral hematite was mined to produce the red pigment ochre. The importance of many mined minerals is reflected in the names of the major milestones in human civilizations: the stone, copper, bronze, and iron ages. Much later coal provided the energy that was critical to the industrial revolution and still underpins modern society, creating 38% of world energy generation today. Ancient mines used human and later animal labor and broke rock using stone tools, heat, and water, and later iron tools. Today’s mines are heavily mechanized with large diesel and electrically powered vehicles, and rock is broken with explosives or rock cutting machines.

Reactive navigation and opportunistic localization for autonomous underground mining vehicles

This paper describes an autonomous navigation system for a large underground mining vehicle. The control architecture is based on a robust reactive wall-following behaviour. To make it purposeful we provide driving hints derived from an approximate nodal-map. For most of the time, the vehicle is driven with weak localization (odometry). This need only be improved at intersections where decisions must be made – a technique we refer to as opportunistic localization. The paper briefly reviews absolute and relative navigation strategies, and describes an implementation of a reactive navigation system on a 30 tonne Load-Haul-Dump truck. This truck has achieved full-speed autonomous operation at an artificial test mine, and subsequently, at a operational underground mine.

Dragline automation - a decade of development : shared autonomy for improving mining equipment productivity

Draglines are massive machines commonly used in surface mining to strip overburden, revealing the targeted minerals for extraction. Automating some or all of the phases of operation of these machines offers the potential for significant productivity and maintenance benefits. The mining industry has a history of slow uptake of automation systems due to the challenges contained in the harsh, complex, three-dimensional (3D), dynamically changing mine operating environment. Robotics as a discipline is finally starting to gain acceptance as a technology with the potential to assist mining operations. This article examines the evolution of robotic technologies applied to draglines in the form of machine embedded intelligent systems. Results from this work include a production trial in which 250,000 tons of material was moved autonomously, experiments demonstrating steps towards full autonomy, and teleexcavation experiments in which a dragline in Australia was tasked by an operator in the United States.

Overview of the INEX 2009 XML mining track : clustering and classification of XML documents

This report explains the objectives, datasets and evaluation criteria of both the clustering and classification tasks set in the INEX 2009 XML Mining track. The report also describes the approaches and results obtained by the different participants.

Access to public sector information : law, technology and policy

On the back of the growing capacity of networked digital information technologies to process and visualise large amounts of information in a timely, efficient and user-driven manner we have seen an increasing demand for better access to and re-use of public sector information (PSI). The story is not a new one. Share knowledge and together we can do great things; limit access and we reduce the potential for opportunity. The two volumes of this book seek to explain and analyse this global shift in the way we manage public sector information. In doing so they collect and present papers, reports and submissions on the topic by leading authors and institutions from across the world. These in turn provide people tasked with mapping out and implementing information policy with reference material and practical guidance. Volume 1 draws together papers on the topic by policymakers, academics and practitioners while Volume 2 presents a selection of the key reports and submissions that have been published over the last few years.

Drugs, dental professionals and the law

Dentists have the privilege of possessing, administering and prescribing drugs, including highly addictive medications, to their patients. But because drugs are often vulnerable to being abused by all members of society, including dentists and their patients, and because drugs can be dangerous, they are tightly regulated in Canada by the federal and provincial/territorial governments. Regulatory and professional dental bodies also provide guidance for their members about how to best administer and prescribe drugs. This chapter outlines the regulation by federal and provincial/territorial governments in this area, examines the professional practice requirements set out by regulatory/professional bodies and the issue of drug abuse by dental professional and patients. It is important to note from the outset that governmental and professional regulations, policies and practices differ from province to province and territory to territory. This chapter aims to alert dentists to possible legal and professional issues surrounding the possession, administration and prescription of drugs. For detailed specific information about regulation, policies, ethical standards and professional practice standards in Canada or their province/ territory, dentists should contact their insurer or professional association.

Application of data mining techniques in the prediction of coronary artery disease : use of anaesthesia time-series and patient risk factor data

The high morbidity and mortality associated with atherosclerotic coronary vascular disease (CVD) and its complications are being lessened by the increased knowledge of risk factors, effective preventative measures and proven therapeutic interventions. However, significant CVD morbidity remains and sudden cardiac death continues to be a presenting feature for some subsequently diagnosed with CVD. Coronary vascular disease is also the leading cause of anaesthesia related complications. Stress electrocardiography/exercise testing is predictive of 10 year risk of CVD events and the cardiovascular variables used to score this test are monitored peri-operatively. Similar physiological time-series datasets are being subjected to data mining methods for the prediction of medical diagnoses and outcomes. This study aims to find predictors of CVD using anaesthesia time-series data and patient risk factor data. Several pre-processing and predictive data mining methods are applied to this data. Physiological time-series data related to anaesthetic procedures are subjected to pre-processing methods for removal of outliers, calculation of moving averages as well as data summarisation and data abstraction methods. Feature selection methods of both wrapper and filter types are applied to derived physiological time-series variable sets alone and to the same variables combined with risk factor variables. The ability of these methods to identify subsets of highly correlated but non-redundant variables is assessed. The major dataset is derived from the entire anaesthesia population and subsets of this population are considered to be at increased anaesthesia risk based on their need for more intensive monitoring (invasive haemodynamic monitoring and additional ECG leads). Because of the unbalanced class distribution in the data, majority class under-sampling and Kappa statistic together with misclassification rate and area under the ROC curve (AUC) are used for evaluation of models generated using different prediction algorithms. The performance based on models derived from feature reduced datasets reveal the filter method, Cfs subset evaluation, to be most consistently effective although Consistency derived subsets tended to slightly increased accuracy but markedly increased complexity. The use of misclassification rate (MR) for model performance evaluation is influenced by class distribution. This could be eliminated by consideration of the AUC or Kappa statistic as well by evaluation of subsets with under-sampled majority class. The noise and outlier removal pre-processing methods produced models with MR ranging from 10.69 to 12.62 with the lowest value being for data from which both outliers and noise were removed (MR 10.69). For the raw time-series dataset, MR is 12.34. Feature selection results in reduction in MR to 9.8 to 10.16 with time segmented summary data (dataset F) MR being 9.8 and raw time-series summary data (dataset A) being 9.92. However, for all time-series only based datasets, the complexity is high. For most pre-processing methods, Cfs could identify a subset of correlated and non-redundant variables from the time-series alone datasets but models derived from these subsets are of one leaf only. MR values are consistent with class distribution in the subset folds evaluated in the n-cross validation method. For models based on Cfs selected time-series derived and risk factor (RF) variables, the MR ranges from 8.83 to 10.36 with dataset RF_A (raw time-series data and RF) being 8.85 and dataset RF_F (time segmented time-series variables and RF) being 9.09. The models based on counts of outliers and counts of data points outside normal range (Dataset RF_E) and derived variables based on time series transformed using Symbolic Aggregate Approximation (SAX) with associated time-series pattern cluster membership (Dataset RF_ G) perform the least well with MR of 10.25 and 10.36 respectively. For coronary vascular disease prediction, nearest neighbour (NNge) and the support vector machine based method, SMO, have the highest MR of 10.1 and 10.28 while logistic regression (LR) and the decision tree (DT) method, J48, have MR of 8.85 and 9.0 respectively. DT rules are most comprehensible and clinically relevant. The predictive accuracy increase achieved by addition of risk factor variables to time-series variable based models is significant. The addition of time-series derived variables to models based on risk factor variables alone is associated with a trend to improved performance. Data mining of feature reduced, anaesthesia time-series variables together with risk factor variables can produce compact and moderately accurate models able to predict coronary vascular disease. Decision tree analysis of time-series data combined with risk factor variables yields rules which are more accurate than models based on time-series data alone. The limited additional value provided by electrocardiographic variables when compared to use of risk factors alone is similar to recent suggestions that exercise electrocardiography (exECG) under standardised conditions has limited additional diagnostic value over risk factor analysis and symptom pattern. The effect of the pre-processing used in this study had limited effect when time-series variables and risk factor variables are used as model input. In the absence of risk factor input, the use of time-series variables after outlier removal and time series variables based on physiological variable values’ being outside the accepted normal range is associated with some improvement in model performance.