Kindred spirits

A real life conversation with different friends often reveals more information about the same story: so too is the case in Willowbrook.

Lawyers behaving badly in mediations : lessons for legal educators

This article will discuss some real life case examples of what will be termed “lawyers behaving badly” where it will be argued that legal representatives have not performed as effectively as they could have in mediation settings. These instances of “lawyer misbehaviour” will be grouped under several broad headings: the Process Thwarter, the Zealous Adversarial Advocate, the Misguided Advisor, the Distributive Bargainer, the Passive Advocate, and the Legal Takeover. Reflecting on these situations will provide guidance to legal educators as to the specific areas of dispute resolution knowledge and skills that future lawyers need to learn and develop.

Text mining with semantic annotation : using enriched text representation for entity-oriented retrieval, semantic relation identification and text clustering

This project is a step forward in the study of text mining where enhanced text representation with semantic information plays a significant role. It develops effective methods of entity-oriented retrieval, semantic relation identification and text clustering utilizing semantically annotated data. These methods are based on enriched text representation generated by introducing semantic information extracted from Wikipedia into the input text data. The proposed methods are evaluated against several start-of-art benchmarking methods on real-life data-sets. In particular, this thesis improves the performance of entity-oriented retrieval, identifies different lexical forms for an entity relation and handles clustering documents with multiple feature spaces.

A BIM-based collaborative design platform for variegated specialty design

With the increase in complexity of engineering projects and design quality in the construction industry, the traditional two-dimensional "Information Island" approach to design is becoming less able to meet current design needs due to its lack of coordination and information sharing. Collaborative design using a Build Information Modeling (BIM) technology platform promises to provide an effective means of designing and communicating through networking and real-time data sharing. This paper first analyzes the shortcomings of the two-dimensional design process and the potential application of collaborative design. By combining the attributes of BIM, a preliminary BIM-based building design collaborative platform is developed to improve the design approach and support a more collaborative design process. A real-life case is presented to demonstrate the feasibility and validity of the platform and its use in practice. From this, it is shown that BIM has the potential to realize effective information sharing and reduce errors, thereby improving design quality. The BIM-based building design collaborative platform presented is expected to provide the support needed for the extensive application of BIM in collaborative design and promote a new attitude to project management.

Power quality improvements in low voltage distribution networks containing distributed energy resources

In this thesis various schemes using custom power devices for power quality improvement in low voltage distribution network are studied. Customer operated distributed generators makes a typical network non-radial and affect the power quality. A scheme considering different algorithm of DSTATCOM is proposed for power circulation and islanded operation of the system. To compensate reactive power overflow and facilitate unity power factor, a UPQC is introduced. Stochastic analysis is carried out for different scenarios to get a comprehensive idea about a real life distribution network. Combined operation of static compensator and voltage regulator is tested for the optimum quality and stability of the system.

Efficiency of parallelisation of genetic algorithms in the data analysis context

Most real-life data analysis problems are difficult to solve using exact methods, due to the size of the datasets and the nature of the underlying mechanisms of the system under investigation. As datasets grow even larger, finding the balance between the quality of the approximation and the computing time of the heuristic becomes non-trivial. One solution is to consider parallel methods, and to use the increased computational power to perform a deeper exploration of the solution space in a similar time. It is, however, difficult to estimate a priori whether parallelisation will provide the expected improvement. In this paper we consider a well-known method, genetic algorithms, and evaluate on two distinct problem types the behaviour of the classic and parallel implementations.

Noise Filtering of Process Execution Logs based on Outliers Detection

This paper presents a technique for the automated removal of noise from process execution logs. Noise is the result of data quality issues such as logging errors and manifests itself in the form of infrequent process behavior. The proposed technique generates an abstract representation of an event log as an automaton capturing the direct follows relations between event labels. This automaton is then pruned from arcs with low relative frequency and used to remove from the log those events not fitting the automaton, which are identified as outliers. The technique has been extensively evaluated on top of various auto- mated process discovery algorithms using both artificial logs with different levels of noise, as well as a variety of real-life logs. The results show that the technique significantly improves the quality of the discovered process model along fitness, appropriateness and simplicity, without negative effects on generalization. Further, the technique scales well to large and complex logs.

Indigenous Australia is deadly – and Leah Purcell shows it (Documentary review)

Urban skyline, as seen from inside a medium-density apartment block, opens Australian director Leah Purcell’s Who We Are: Brave New Clan (2014), which was broadcast on Foxtel’s Bio Channel last night. The one-off documentary – which deserves another run – follows the lives of six Indigenous Australians (not connected in real life but our “clan” for the sake of the documentary). Does it work? Oh yes...

Log delta analysis: Interpretable differencing of Business process event logs

This paper addresses the problem of identifying and explaining behavioral differences between two business process event logs. The paper presents a method that, given two event logs, returns a set of statements in natural language capturing behavior that is present or frequent in one log, while absent or infrequent in the other. This log delta analysis method allows users to diagnose differences between normal and deviant executions of a process or between two versions or variants of a process. The method relies on a novel approach to losslessly encode an event log as an event structure, combined with a frequency-enhanced technique for differencing pairs of event structures. A validation of the proposed method shows that it accurately diagnoses typical change patterns and can explain differences between normal and deviant cases in a real-life log, more compactly and precisely than previously proposed methods.

BPMN Miner: Automated Discovery of BPMN Process Models with Hierarchical Structure

Existing techniques for automated discovery of process models from event logs gen- erally produce flat process models. Thus, they fail to exploit the notion of subprocess as well as error handling and repetition constructs provided by contemporary process modeling notations, such as the Business Process Model and Notation (BPMN). This paper presents a technique for automated discovery of hierarchical BPMN models con- taining interrupting and non-interrupting boundary events and activity markers. The technique employs functional and inclusion dependency discovery techniques in order to elicit a process-subprocess hierarchy from the event log. Given this hierarchy and the projected logs associated to each node in the hierarchy, parent process and subprocess models are then discovered using existing techniques for flat process model discovery. Finally, the resulting models and logs are heuristically analyzed in order to identify boundary events and markers. By employing approximate dependency discovery tech- niques, it is possible to filter out noise in the event log arising for example from data entry errors or missing events. A validation with one synthetic and two real-life logs shows that process models derived by the proposed technique are more accurate and less complex than those derived with flat process discovery techniques. Meanwhile, a validation on a family of synthetically generated logs shows that the technique is resilient to varying levels of noise.

Rapid detection of TNT in aqueous media by selective label free surface enhanced Raman spectroscopy

We report rapid and ultra-sensitive detection system for 2,4,6-trinitrotoluene (TNT) using unmodified gold nanoparticles and surface-enhanced Raman spectroscopy (SERS). First, Meisenheimer complex has been formed in aqueous solution between TNT and cysteamine in less than 15 min of mixing. The complex formation is confirmed by the development of a pink colour and a new UV–vis absorption band around 520 nm. Second, the developed Meisenheimer complex is spontaneously self-assembled onto unmodified gold nanoparticles through a stable Au–S bond between the cysteamine moiety and the gold surface. The developed mono layer of cysteamine-TNT is then screened by SERS to detect and quantify TNT. Our experimental results demonstrate that the SERS-based assay provide an ultra-sensitive approach for the detection of TNT down to 22.7 ng/L. The unambiguous fingerprint identification of TNT by SERS represents a key advantage for our proposed method. The new method provides high selectivity towards TNT over 2,4 DNT and picric acid. Therefore it satisfies the practical requirements for the rapid screening of TNT in real life samples where the interim 24-h average allowable concentration of TNT in waste water is 0.04 mg/L.

Endangered species and the precautionary principle

This discussion paper is intended to provide background material for the workshop organised by Queensland University Technology (QUT) on 17 October 2014. The overall purpose of the workshop is to better understand the relationship between the precautionary principle and endangered species management in Australia. In particular, we are looking for real life examples (or hypotheticals) of where the principle is (or is not) being applied in relation to Australia’s endangered species. A wide variety of participants have been invited to the workshop including scientists, representatives of NGOs, lawyers and academics. Whilst some very general information is outlined below, we encourage all participants to bring their own thoughts on how the precautionary principle should operate and to reflect on examples of where you have seen it work (or not work) in Australia. The sharing of your own case studies is thus encouraged.

No time for compliance

In the past few years several business process compliance framework based on temporal logic have been proposed. In this paper we investigate whether the use of temporal logic is suitable for the task at hand: namely to check whether the specifications of a business process are compatible with the formalisation of the norms regulating the business process. We provide an example inspired by real life norms where the use of linear temporal logic produces a result that is not compatible with the legal understanding of the norms in the example.

The Piper Fatigue Scale-Revised: Translation and psychometric evaluation in Spanish-speaking breast cancer survivors

Background Cancer-related fatigue (CRF) is the most common and distressing symptom reported by breast cancer survivors. The primary aim of this study was to translate and evaluate psychometrically for the first time a Spanish version of the Piper Fatigue Scale-Revised (S-PFS-R). Methods One hundred and eleven women with stage I–IIIA breast cancer who had completed their primary cancer therapy in the previous 6 months with the exception of hormone therapy completed the S-PFS-R, the Profile of Mood States (POMS) Fatigue (POMS-F) and Vigor subscales (POMS-V), and bilateral force handgrip testing. Data analysis included test–retest reliability, construct validity, criterion-related validity, and exploratory factor analyses. Results Test–retest reliability was satisfactory (r > 0.86), and all subscales showed moderate to high construct validity estimates [corrected item-subscale correlations (Pearson r = ≥ 0.65)]. The exploratory factor analysis revealed four dimensions with 75.5 % of the common variance explained. The S-PFS-R total score positively correlated with the POMS-F subscale (r = 0.50–0.78) and negatively with the POMS-V subscale (r = −0.13 to −0.44) confirming criterion-related validity. Negative correlations among force handgrip testing, subscales, and total scores were weak (r = −0.26 to −0.29). Conclusions The Spanish version of PFS-R shows satisfactory psychometric properties in a sample of breast cancer survivors. This is the first study to translate the PFS-R into Spanish and further testing is warranted.

Yellow Peril

This catalogue essay was written to accompany Eugenia Lim's 2015 exhibition at Metro Arts, Brisbane, 'Yellow Peril'. It discusses Lim's exploration of her identity as a Chinese-Australian, providing contextual information of Chinese immigration during Australia's gold rush years and the work of Hong Kong born American artist, Tseng Kwong Chi. It presents Yellow Peril as an exhibition that speaks critically about art and our cultural history amidst a fine layering of imagery, object and context, with a vitality that is derived from its rich and compelling base in real life moments and connections.