Communication Interception Technology (CIT) and its use in the fight against Transnational Organised Crime (TOC) in Australia : a review of the literature

In recent times, technology has advanced in such a manner that the world can now communicate in means previously never thought possible. Transnational organised crime groups, who have exploited these new technologies as basis for their criminal success, however, have not overlooked this development, growth and globalisation. Law enforcement agencies have been confronted with an unremitting challenge as they endeavour to intercept, monitor and analyse these communications as a means of disrupting the activities of criminal enterprises. The challenge lies in the ability to recognise and change tactics to match an increasingly sophisticated adversary. The use of communication interception technology, such as phone taps or email interception, is a tactic that when used appropriately has the potential to cause serious disruption to criminal enterprises. Despite the research that exists on CIT and TOC, these two bodies of knowledge rarely intersect. This paper builds on current literature, drawing them together to provide a clearer picture of the use of CIT in an enforcement and intelligence capacity. It provides a review of the literature pertaining to TOC, the structure of criminal enterprises and the vulnerability of communication used by these crime groups. Identifying the current contemporary models of policing it reviews intelligence-led policing as the emerging framework for modern policing. Finally, it assesses the literature concerning CIT, its uses within Australia and the limitations and arguments that exist. In doing so, this paper provides practitioners with a clearer picture of the use, barriers and benefits of using CIT in the fight against TOC. It helps to bridge the current gaps in modern policing theory and offers a perspective that can help drive future research.

Indexing and efficient instance-based retrieval of process models using untanglings

Process-Aware Information Systems (PAISs) support executions of operational processes that involve people, resources, and software applications on the basis of process models. Process models describe vast, often infinite, amounts of process instances, i.e., workflows supported by the systems. With the increasing adoption of PAISs, large process model repositories emerged in companies and public organizations. These repositories constitute significant information resources. Accurate and efficient retrieval of process models and/or process instances from such repositories is interesting for multiple reasons, e.g., searching for similar models/instances, filtering, reuse, standardization, process compliance checking, verification of formal properties, etc. This paper proposes a technique for indexing process models that relies on their alternative representations, called untanglings. We show the use of untanglings for retrieval of process models based on process instances that they specify via a solution to the total executability problem. Experiments with industrial process models testify that the proposed retrieval approach is up to three orders of magnitude faster than the state of the art.

Playing with Grammar in the Early Years : Learning about Language in the Australian Curriculum : English

As teacher/researchers interested in the pursuit of socially-just outcomes in early childhood education, the form and function of language occupies a special position in our work. We believe that mastering a range of literacy competences includes not only the technical skills for learning, but also the resources for viewing and constructing the world (Freire and Macdeo, 1987). Rather than seeing knowledge about language as the accumulation of technical skills alone, the viewpoint to which we subscribe treats knowledge about language as a dialectic that evolves from, is situated in, and contributes to a social arena (Halliday, 1978). We do not shy away from this position just because children are in the early years of schooling. In ‘Playing with Grammar’, we focus on the Foundation to Year 2 grouping, in line with the Australian Curriculum, Assessment and Reporting Authority’s (hereafter ACARA) advice on the ‘nature of learners’ (ACARA, 2013). With our focus on the early years of schooling comes our acknowledgement of the importance and complexity of play. At a time where accountability in education has moved many teachers to a sense of urgency to prove language and literacy achievement (Genishi and Dyson, 2009), we encourage space to revisit what we know about literature choices and learning experiences and bring these together to facilitate language learning. We can neither ignore, nor overemphasise, the importance of play for the development of language through: the opportunities presented for creative use and practice; social interactions for real purposes; and, identifying and solving problems in the lives of young children (Marsh and Hallet, 2008). We argue that by engaging young children in opportunities to play with language we are ultimately empowering them to be active in their language learning and in the process fostering a love of language and the intricacies it holds. Our goal in this publication is to provide a range of highly practical strategies for scaffolding young children through some of the Content Descriptions from the Australian Curriculum English Version 5.0, hereafter AC:E V5.0 (ACARA, 2013). This recently released curriculum offers a new theoretical approach to building children’s knowledge about language. The AC:E V5.0 uses selected traditional terms through an approach developed in systemic functional linguistics (see Halliday and Matthiessen, 2004) to highlight the dynamic forms and functions of multimodal language in texts. For example, the following statement, taken from the ‘Language: Knowing about the English language’ strand states: English uses standard grammatical terminology within a contextual framework, in which language choices are seen to vary according to the topics at hand, the nature and proximity of the relationships between the language users, and the modalities or channels of communication available (ACARA, 2013). Put simply, traditional grammar terms are used within a functional framework made up of field, tenor, and mode. An understanding of genre is noted with the reference to a ‘contextual framework’. The ‘topics at hand’ concern the field or subject matter of the text. The ‘relationships between the language users’ is a description of tenor. There is reference to ‘modalities’, such as spoken, written or visual text. We posit that this innovative approach is necessary for working with contemporary multimodal and cross-cultural texts (see Exley and Mills, 2012). We believe there is enormous power in using literature to expose children to the richness of language and in turn develop language and literacy skills. Taking time to look at language patterns within actual literature is a pathway to ‘…capture interest, stir the imagination and absorb the [child]’ into the world of language and literacy (Saxby, 1993, p. 55). In the following three sections, we have tried to remain faithful to our interpretation of the AC:E V5.0 Content Descriptions without giving an exhaustive explanation of the grammatical terms. Other excellent tomes, such as Derewianka (2011), Humphrey, Droga and Feez (2012), and Rossbridge and Rushton (2011) provide these more comprehensive explanations as does the AC:E V5.0 Glossary. We’ve reproduced some of the AC:E V5.0 glossary at the end of this publication. Our focus is on the structure and unfolding of the learning experiences. We outline strategies for working with children in Foundation, Year 1 and Year 2 by providing some demonstration learning experiences based on texts we’ve selected, but maintain that the affordances of these strategies will only be realised when teaching and learning is purposively tied to authentic projects in local contexts. We strongly encourage you not to use only the resource texts we’ve selected, but to capitalise upon your skill for identifying the language features in the texts you and the children are studying and adapt some of the strategies we have outlined. Each learning experience is connected to one of the Content Descriptions from the AC:E V5.0 and contains an experience specific purpose, a suggested resource text and a sequence for the experience that always commences with an orientation to text followed by an examination of a particular grammatical resource. We expect that each of these learning experiences will take a couple if not a few teaching episodes to work through, especially if children are meeting a concept for the first time. We hope you use as much, or as little, of each experience as is needed. Our plans allow for focused discussion, shared exploration and opportunities to revisit the same text for the purpose of enhancing meaning making. We do not want the teaching of grammar to slip into a crisis of irrelevance or to be seen as a series of worksheet drills with finite answers. Strategies for effective practice, however, have much portability. We are both very keen to hear from teachers who are adopting and adapting these learning experiences in their classrooms. Please email us on b.exley@qut.edu.au or lkervin@uow.edu.au. We’d love to continue the conversation with you over time.

A reciprocal collaborative method using relevance feedback and feature importance

In a people-to-people matching systems, filtering is widely applied to find the most suitable matches. The results returned are either too many or only a few when the search is generic or specific respectively. The use of a sophisticated recommendation approach becomes necessary. Traditionally, the object of recommendation is the item which is inanimate. In online dating systems, reciprocal recommendation is required to suggest a partner only when the user and the recommended candidate both are satisfied. In this paper, an innovative reciprocal collaborative method is developed based on the idea of similarity and common neighbors, utilizing the information of relevance feedback and feature importance. Extensive experiments are carried out using data gathered from a real online dating service. Compared to benchmarking methods, our results show the proposed method can achieve noticeable better performance.

Testing second order cyclostationarity in the squared envelope spectrum of non-white vibration signals

Cyclostationary models for the diagnostic signals measured on faulty rotating machineries have proved to be successful in many laboratory tests and industrial applications. The squared envelope spectrum has been pointed out as the most efficient indicator for the assessment of second order cyclostationary symptoms of damages, which are typical, for instance, of rolling element bearing faults. In an attempt to foster the spread of rotating machinery diagnostics, the current trend in the field is to reach higher levels of automation of the condition monitoring systems. For this purpose, statistical tests for the presence of cyclostationarity have been proposed during the last years. The statistical thresholds proposed in the past for the identification of cyclostationary components have been obtained under the hypothesis of having a white noise signal when the component is healthy. This need, coupled with the non-white nature of the real signals implies the necessity of pre-whitening or filtering the signal in optimal narrow-bands, increasing the complexity of the algorithm and the risk of losing diagnostic information or introducing biases on the result. In this paper, the authors introduce an original analytical derivation of the statistical tests for cyclostationarity in the squared envelope spectrum, dropping the hypothesis of white noise from the beginning. The effect of first order and second order cyclostationary components on the distribution of the squared envelope spectrum will be quantified and the effectiveness of the newly proposed threshold verified, providing a sound theoretical basis and a practical starting point for efficient automated diagnostics of machine components such as rolling element bearings. The analytical results will be verified by means of numerical simulations and by using experimental vibration data of rolling element bearings.

Retrieving dynamic origin-destination matrices from Bluetooth data

The Bluetooth technology is being increasingly used, among the Automated Vehicle Identification Systems, to retrieve important information about urban networks. Because the movement of Bluetooth-equipped vehicles can be monitored, throughout the network of Bluetooth sensors, this technology represents an effective means to acquire accurate time dependant Origin Destination information. In order to obtain reliable estimations, however, a number of issues need to be addressed, through data filtering and correction techniques. Some of the main challenges inherent to Bluetooth data are, first, that Bluetooth sensors may fail to detect all of the nearby Bluetooth-enabled vehicles. As a consequence, the exact journey for some vehicles may become a latent pattern that will need to be estimated. Second, sensors that are in close proximity to each other may have overlapping detection areas, thus making the task of retrieving the correct travelled path even more challenging. The aim of this paper is twofold: to give an overview of the issues inherent to the Bluetooth technology, through the analysis of the data available from the Bluetooth sensors in Brisbane; and to propose a method for retrieving the itineraries of the individual Bluetooth vehicles. We argue that estimating these latent itineraries, accurately, is a crucial step toward the retrieval of accurate dynamic Origin Destination Matrices.

Training-free probability models for whole-image based place recognition

Whole-image descriptors such as GIST have been used successfully for persistent place recognition when combined with temporal filtering or sequential filtering techniques. However, whole-image descriptor localization systems often apply a heuristic rather than a probabilistic approach to place recognition, requiring substantial environmental-specific tuning prior to deployment. In this paper we present a novel online solution that uses statistical approaches to calculate place recognition likelihoods for whole-image descriptors, without requiring either environmental tuning or pre-training. Using a real world benchmark dataset, we show that this method creates distributions appropriate to a specific environment in an online manner. Our method performs comparably to FAB-MAP in raw place recognition performance, and integrates into a state of the art probabilistic mapping system to provide superior performance to whole-image methods that are not based on true probability distributions. The method provides a principled means for combining the powerful change-invariant properties of whole-image descriptors with probabilistic back-end mapping systems without the need for prior training or system tuning.

Acquiring user information needs for recommender systems

Most recommender systems attempt to use collaborative filtering, content-based filtering or hybrid approach to recommend items to new users. Collaborative filtering recommends items to new users based on their similar neighbours, and content-based filtering approach tries to recommend items that are similar to new users' profiles. The fundamental issues include how to profile new users, and how to deal with the over-specialization in content-based recommender systems. Indeed, the terms used to describe items can be formed as a concept hierarchy. Therefore, we aim to describe user profiles or information needs by using concepts vectors. This paper presents a new method to acquire user information needs, which allows new users to describe their preferences on a concept hierarchy rather than rating items. It also develops a new ranking function to recommend items to new users based on their information needs. The proposed approach is evaluated on Amazon book datasets. The experimental results demonstrate that the proposed approach can largely improve the effectiveness of recommender systems.

Slicing big data - Twitter, gambling and time sensitive information

Big Data presents many challenges related to volume, whether one is interested in studying past datasets or, even more problematically, attempting to work with live streams of data. The most obvious challenge, in a ‘noisy’ environment such as contemporary social media, is to collect the pertinent information; be that information for a specific study, tweets which can inform emergency services or other responders to an ongoing crisis, or give an advantage to those involved in prediction markets. Often, such a process is iterative, with keywords and hashtags changing with the passage of time, and both collection and analytic methodologies need to be continually adapted to respond to this changing information. While many of the data sets collected and analyzed are preformed, that is they are built around a particular keyword, hashtag, or set of authors, they still contain a large volume of information, much of which is unnecessary for the current purpose and/or potentially useful for future projects. Accordingly, this panel considers methods for separating and combining data to optimize big data research and report findings to stakeholders. The first paper considers possible coding mechanisms for incoming tweets during a crisis, taking a large stream of incoming tweets and selecting which of those need to be immediately placed in front of responders, for manual filtering and possible action. The paper suggests two solutions for this, content analysis and user profiling. In the former case, aspects of the tweet are assigned a score to assess its likely relationship to the topic at hand, and the urgency of the information, whilst the latter attempts to identify those users who are either serving as amplifiers of information or are known as an authoritative source. Through these techniques, the information contained in a large dataset could be filtered down to match the expected capacity of emergency responders, and knowledge as to the core keywords or hashtags relating to the current event is constantly refined for future data collection. The second paper is also concerned with identifying significant tweets, but in this case tweets relevant to particular prediction market; tennis betting. As increasing numbers of professional sports men and women create Twitter accounts to communicate with their fans, information is being shared regarding injuries, form and emotions which have the potential to impact on future results. As has already been demonstrated with leading US sports, such information is extremely valuable. Tennis, as with American Football (NFL) and Baseball (MLB) has paid subscription services which manually filter incoming news sources, including tweets, for information valuable to gamblers, gambling operators, and fantasy sports players. However, whilst such services are still niche operations, much of the value of information is lost by the time it reaches one of these services. The paper thus considers how information could be filtered from twitter user lists and hash tag or keyword monitoring, assessing the value of the source, information, and the prediction markets to which it may relate. The third paper examines methods for collecting Twitter data and following changes in an ongoing, dynamic social movement, such as the Occupy Wall Street movement. It involves the development of technical infrastructure to collect and make the tweets available for exploration and analysis. A strategy to respond to changes in the social movement is also required or the resulting tweets will only reflect the discussions and strategies the movement used at the time the keyword list is created — in a way, keyword creation is part strategy and part art. In this paper we describe strategies for the creation of a social media archive, specifically tweets related to the Occupy Wall Street movement, and methods for continuing to adapt data collection strategies as the movement’s presence in Twitter changes over time. We also discuss the opportunities and methods to extract data smaller slices of data from an archive of social media data to support a multitude of research projects in multiple fields of study. The common theme amongst these papers is that of constructing a data set, filtering it for a specific purpose, and then using the resulting information to aid in future data collection. The intention is that through the papers presented, and subsequent discussion, the panel will inform the wider research community not only on the objectives and limitations of data collection, live analytics, and filtering, but also on current and in-development methodologies that could be adopted by those working with such datasets, and how such approaches could be customized depending on the project stakeholders.

A topic based document relevance ranking model

Topic modelling has been widely used in the fields of information retrieval, text mining, machine learning, etc. In this paper, we propose a novel model, Pattern Enhanced Topic Model (PETM), which makes improvements to topic modelling by semantically representing topics with discriminative patterns, and also makes innovative contributions to information filtering by utilising the proposed PETM to determine document relevance based on topics distribution and maximum matched patterns proposed in this paper. Extensive experiments are conducted to evaluate the effectiveness of PETM by using the TREC data collection Reuters Corpus Volume 1. The results show that the proposed model significantly outperforms both state-of-the-art term-based models and pattern-based models.

In vivo confocal microscopy of the ocular surface : from bench to bedside

In vivo confocal microscopy (IVCM) is an emerging technology that provides minimally invasive, high resolution, steady-state assessment of the ocular surface at the cellular level. Several challenges still remain but, at present, IVCM may be considered a promising technique for clinical diagnosis and management. This mini-review summarizes some key findings in IVCM of the ocular surface, focusing on recent and promising attempts to move “from bench to bedside”. IVCM allows prompt diagnosis, disease course follow-up, and management of potentially blinding atypical forms of infectious processes, such as acanthamoeba and fungal keratitis. This technology has improved our knowledge of corneal alterations and some of the processes that affect the visual outcome after lamellar keratoplasty and excimer keratorefractive surgery. In dry eye disease, IVCM has provided new information on the whole-ocular surface morphofunctional unit. It has also improved understanding of pathophysiologic mechanisms and helped in the assessment of prognosis and treatment. IVCM is particularly useful in the study of corneal nerves, enabling description of the morphology, density, and disease- or surgically induced alterations of nerves, particularly the subbasal nerve plexus. In glaucoma, IVCM constitutes an important aid to evaluate filtering blebs, to better understand the conjunctival wound healing process, and to assess corneal changes induced by topical antiglaucoma medications and their preservatives. IVCM has significantly enhanced our understanding of the ocular response to contact lens wear. It has provided new perspectives at a cellular level on a wide range of contact lens complications, revealing findings that were not previously possible to image in the living human eye. The final section of this mini-review provides a focus on advances in confocal microscopy imaging. These include 2D wide-field mapping, 3D reconstruction of the cornea and automated image analysis.

New directions for digital video creation in the classroom : spatiality, embodiment, and creativity

This column features a conversation (via email, image sharing, and Facetime) that took place over several months between two international theorists of digital filmmaking from schools in two countries—Professors Jason Ranker (Portland State University, Oregon, United States) and Kathy Mills (Queensland University of Technology, Australia). The authors discuss emerging ways of thinking about video making, sharing tips and anecdotes from classroom experience to inspire teachers to explore with adolescents the meaning potentials of digital video creation. The authors briefly discuss their previous work in this area, and then move into a discussion of how the material spaces in which students create videos profoundly shape the films' meanings and significance. The article ends with a discussion of how students can take up creative new directions, pushing the boundaries of the potentials of classroom video making and uncovering profound uses of the medium.

Comparison of historic exploration with contemporary space policy suggests a retheorisation of settings

The 2008 NASA Astrobiology Roadmap provides one way of theorising this developing field, a way which has become the normative model for the discipline: science-and scholarship-driven funding for space. By contrast, a novel re-evaluation of funding policies is undertaken in this article to reframe astrobiology, terraforming and associated space travel and research. Textual visualisation, discourse and numeric analytical methods, and value theory are applied to historical data and contemporary sources to re-investigate significant drivers and constraints on the mechanisms of enabling space exploration. Two data sets are identified and compared: the business objectives and outcomes of major 15th-17th century European joint-stock exploration and trading companies and a case study of a current space industry entrepreneur company. Comparison of these analyses suggests that viable funding policy drivers can exist outside the normative science and scholarship-driven roadmap. The two drivers identified in this study are (1) the intrinsic value of space as a territory to be experienced and enjoyed, not just studied, and (2) the instrumental, commercial value of exploiting these experiences by developing infrastructure and retail revenues. Filtering of these results also offers an investment rationale for companies operating in, or about to enter, the space business marketplace.

Prevalence of undiagnosed urinary tract infections on admission to a rehabilitation unit

Background Through clinical observation nursing staff of an inpatient rehabilitation unit identified a link between incontinence and undiagnosed urinary tract infections (UTIs). Further, clinical observation and structured continence management led to the realisation that urinary incontinence often improved, or resolved completely, after treatment with antibiotics. In 2009 a small study found that 30% of admitted rehabilitation patients had an undiagnosed UTI, with the majority admitted post-orthopaedic fracture. We suspected that the frequent use of indwelling urinary catheters (IDCs) in the orthopaedic environment may have been a contributing factor. Therefore, a second, more thorough, study was commenced in 2010 and completed in 2011. Aim The aim of this study was to identify what proportion of patients were admitted to one rehabilitation unit with an undiagnosed UTI over a 12-month period. We wanted to identify and highlight the presence of known risk factors associated with UTI and determine whether urinary incontinence was associated with the presence of UTI. Methods Data were collected from every patient that was admitted over a 12-month period (n=140). The majority of patients were over the age of 65 and had an orthopaedic fracture (36.4%) or stroke (27.1%). Mid-stream urine (MSU) samples, routinely collected and sent for culture and sensitivity as part of standard admission procedure, were used by the treating medical officer to detect the presence of UTI. A data collection sheet was developed, reviewed and trialled, before official data collection commenced. Data were collected as part of usual practice and collated by a research assistant. Inferential statistics were used to analyse the data. Results This study found that 25 (17.9%) of the 140 patients admitted to rehabilitation had an undiagnosed UTI, with a statistically significant association between prior presence of an IDC and the diagnosis of UTI. Urinary incontinence improved after the completion of treatment with antibiotics. Results further demonstrated a significant association between the confirmation of a UTI on culture and sensitivity and the absence of symptoms usually associated with UTI, such as burning or stinging on urination. Overall, this study suggests careful monitoring of urinary symptoms in patients admitted to rehabilitation, especially in patients with a prior IDC, is warranted.

On the hardness of the sum of K mins problem

The sum of k mins protocol was proposed by Hopper and Blum as a protocol for secure human identification. The goal of the protocol is to let an unaided human securely authenticate to a remote server. The main ingredient of the protocol is the sum of k mins problem. The difficulty of solving this problem determines the security of the protocol. In this paper, we show that the sum of k mins problem is NP-Complete and W[1]-Hard. This latter notion relates to fixed parameter intractability. We also discuss the use of the sum of k mins protocol in resource-constrained devices.