Professions without borders : global ethics and the international rule of law

The emergence of strong sovereign states after the Treaty of Westphalia turned two of the most cosmopolitan professions (law and arms) into two of the least cosmopolitan. Sovereign states determined the content of the law within their borders – including which, if any, ecclesiastical law was to be applied; what form of economic regulation was adopted; and what, if any, international law applied. Similarly, states sought to ensure that all military force was at their disposal in national armies. The erosion of sovereignty in a post-Westphalian world may significantly reverse these processes. The erosion of sovereignty is likely to have profound consequences for the legal profession and the ethics of how, and for what ends, it is practised. Lawyers have played a major role in the civilization of sovereign states through the articulation and institutionalisation of key governance values – starting with the rule of law. An increasingly global profession must take on similar tasks. The same could be said of the military. This essay will review the concept of an international rule of law and its relationship to domestic conceptions and outline the task of building the international rule of law and the role that lawyers can and should play in it.

Practical stability with respect to model mismatch of approximate discrete-time output feedback control

This paper establishes a practical stability result for discrete-time output feedback control involving mismatch between the exact system to be stabilised and the approximating system used to design the controller. The practical stability is in the sense of an asymptotic bound on the amount of error bias introduced by the model approximation, and is established using local consistency properties of the systems. Importantly, the practical stability established here does not require the approximating system to be of the same model type as the exact system. Examples are presented to illustrate the nature of our practical stability result.

Approximate Membership Localization within a Web-Based Join Framework

In this paper, we propose a search-based approach to join two tables in the absence of clean join attributes. Non-structured documents from the web are used to express the correlations between a given query and a reference list. To implement this approach, a major challenge we meet is how to efficiently determine the number of times and the locations of each clean reference from the reference list that is approximately mentioned in the retrieved documents. We formalize the Approximate Membership Localization (AML) problem and propose an efficient partial pruning algorithm to solve it. A study using real-word data sets demonstrates the effectiveness of our search-based approach, and the efficiency of our AML algorithm.

Failed states and the rule of law

The last decade has seen an emerging consensus that the rule of law is critical in both domestic and international affairs. ‘Failed’ states generate important issues for both the rule of law and, importantly, for their intersection or interaction. A ‘failed’ state almost inevitably involves a breakdown of the domestic rule of law. When international intervention occurs, it raises concerns over substantive issues. Among these is the application of international law and international norms, including among other, the conventions and treaties, the responsibility to protect and protection of civilians. Where international missions seek to assist the people of ‘failed’ states in rebuilding their nations, establishing the rule of law is often the primary or initial pursuit. Any such international assistance/intervention is more effective if it is clearly subject to the rule of law and provides an exemplar/demonstration of how power should be exercised

Non-redundant sequential association rule mining based on closed sequential patterns

In many applications, e.g., bioinformatics, web access traces, system utilisation logs, etc., the data is naturally in the form of sequences. People have taken great interest in analysing the sequential data and finding the inherent characteristics or relationships within the data. Sequential association rule mining is one of the possible methods used to analyse this data. As conventional sequential association rule mining very often generates a huge number of association rules, of which many are redundant, it is desirable to find a solution to get rid of those unnecessary association rules. Because of the complexity and temporal ordered characteristics of sequential data, current research on sequential association rule mining is limited. Although several sequential association rule prediction models using either sequence constraints or temporal constraints have been proposed, none of them considered the redundancy problem in rule mining. The main contribution of this research is to propose a non-redundant association rule mining method based on closed frequent sequences and minimal sequential generators. We also give a definition for the non-redundant sequential rules, which are sequential rules with minimal antecedents but maximal consequents. A new algorithm called CSGM (closed sequential and generator mining) for generating closed sequences and minimal sequential generators is also introduced. A further experiment has been done to compare the performance of generating non-redundant sequential rules and full sequential rules, meanwhile, performance evaluation of our CSGM and other closed sequential pattern mining or generator mining algorithms has also been conducted. We also use generated non-redundant sequential rules for query expansion in order to improve recommendations for infrequently purchased products.

Psychosocial predictors of rule following in hostels for women experiencing homelessness

This study examined the psychosocial factors impacting upon the rule-following behaviour of residents of a hostel providing crisis accommodation to women who are homeless. After their arrival, residents of a women’s hostel (N = 83) completed questionnaires assessing the Theory of Planned Behaviour constructs of attitude, subjective norm, perceived behavioural control (PBC), and intentions related to rule-following while residing at the hostel. Perceived resident group norms for rule-following were assessed also. Follow-up staff evaluations of the target behaviour were completed after participants ceased their hostel residence. As expected, attitude, subjective norm, PBC, and group norm significantly predicted intention to follow hostel rules, and intention and PBC predicted rule following behaviour. As rule following is a crucial requirement for continuation of their stay, these findings can inform strategies to improve the experiences and outcomes of women’s short-term hostel stays.

Transfer of Title by a Non-Owner : Personal Property Securities Act 2009 (Cth) exceptions to the nemo dat quod non habet rule

The fundamental personal property rule – no one can transfer a better title to property than they had – is subject to exceptions in the Sale of Goods legislation, which aim to protect innocent buyers who are deceived by a seller’s apparent physical possession of property. These exceptions cover a limited range of transactions and are restrictive in their operation. Australia now has national legislation - the Personal Property Securities Act 2009 (Cth) - which will apply to many transactions outside the scope of the Sale of Goods Act and which includes rules for sales by non-owners which will provide exceptions to the nemo dat quod non habet rule for many common commercial transactions. This article explores the effect of the Personal Property Securities Act 2009 (Cth) on the Sale of Goods exceptions, explains that the new provisions are so wide that there is little continuing relevance for the Sale of Goods Act exceptions, and indicates where they may still apply.

An approximate Bayesian computation approach for estimating parameters of complex environmental processes in a cellular automata

Modelling an environmental process involves creating a model structure and parameterising the model with appropriate values to accurately represent the process. Determining accurate parameter values for environmental systems can be challenging. Existing methods for parameter estimation typically make assumptions regarding the form of the Likelihood, and will often ignore any uncertainty around estimated values. This can be problematic, however, particularly in complex problems where Likelihoods may be intractable. In this paper we demonstrate an Approximate Bayesian Computational method for the estimation of parameters of a stochastic CA. We use as an example a CA constructed to simulate a range expansion such as might occur after a biological invasion, making parameter estimates using only count data such as could be gathered from field observations. We demonstrate ABC is a highly useful method for parameter estimation, with accurate estimates of parameters that are important for the management of invasive species such as the intrinsic rate of increase and the point in a landscape where a species has invaded. We also show that the method is capable of estimating the probability of long distance dispersal, a characteristic of biological invasions that is very influential in determining spread rates but has until now proved difficult to estimate accurately.

Quo Vadis? Reliable and Practical Rule Extraction from Neural Networks

Rule extraction from neural network algorithms have been investigated for two decades and there have been significant applications. Despite this level of success, rule extraction from neural network methods are generally not part of data mining tools, and a significant commercial breakthrough may still be some time away. This paper briefly reviews the state-of-the-art and points to some of the obstacles, namely a lack of evaluation techniques in experiments and larger benchmark data sets. A significant new development is the view that rule extraction from neural networks is an interactive process which actively involves the user. This leads to the application of assessment and evaluation techniques from information retrieval which may lead to a range of new methods.