Port decoupling for small arrays by means of an eigenmode feed network

An alternative approach to port decoupling and matching of arrays with tightly coupled elements is proposed. The method is based on the inherent decoupling effect obtained by feeding the orthogonal eigenmodes of the array. For this purpose, a modal feed network is connected to the array. The decoupled external ports of the feed network may then be matched independently by using conventional matching circuits. Such a system may be used in digital beam forming applications with good signal-to-noise performance. The theory is applicable to arrays with an arbitrary number of elements, but implementation is only practical for smaller arrays. The principle is illustrated by means of two examples.

New modal feed network for a compact monopole array with isolated ports

An element spacing of less than half a wavelength introduces strong mutual coupling between the ports of compact antenna arrays. The strong coupling causes significant system performance degradation. A decoupling network may compensate for the mutual coupling. Alternatively, port decoupling can be achieved using a modal feed network. In response to an input signal at one of the input ports, this feed network excites the antenna elements in accordance with one of the eigenvectors of the array scattering parameter matrix. In this paper, a novel 4-element monopole array is described. The feed network of the array is implemented as a planar ring-type circuit in stripline with four coupled line sections. The new configuration offers a significant reduction in size, resulting in a very compact array.

Designing participation : Reconsidering agile ridesharing with evolutionary distributed design thinking

This paper explores design thinking from the perspective of designing new forms of interaction to engage people in community change initiatives. A case study of an agile ridesharing system is presented. We describe the fundamental premise of the design approach taken—deploying simple interactive prototypes for use by communities in order to test the design hypothesis, evolve the design in use and grow the community of participants. Real-time use data and feedback from participants influences our understanding of the design approach and feeds into the gradual evolution of the prototype while it continues to be used. We then reflect upon this form of evolutionary distributed design thinking. In contrast to the conventional IT wisdom of building systems to automate ride matching and fare calculation using structured forms, our initial phase of design revealed a preference for informal messaging, negotiation and caution in the sharing of specific location information.

Mapping the Australian networked public sphere

This article reports on a research program that has developed new methodologies for mapping the Australian blogosphere and tracking how information is disseminated across it. The authors improve on conventional web crawling methodologies in a number of significant ways: First, the authors track blogging activity as it occurs, by scraping new blog posts when such posts are announced through Really Simple Syndication (RSS) feeds. Second, the authors use custom-made tools that distinguish between the different types of content and thus allow us to analyze only the salient discursive content provided by bloggers. Finally, the authors are able to examine these better quality data using both link network mapping and textual analysis tools, to produce both cumulative longer term maps of interlinkages and themes, and specific shorter term snapshots of current activity that indicate current clusters of heavy interlinkage and highlight their key themes. In this article, the authors discuss findings from a yearlong observation of the Australian political blogosphere, suggesting that Australian political bloggers consistently address current affairs, but interpret them differently from mainstream news outlets. The article also discusses the next stage of the project, which extends this approach to an examination of other social networks used by Australians, including Twitter, YouTube, and Flickr. This adaptation of our methodology moves away from narrow models of political communication, and toward an investigation of everyday and popular communication, providing a more inclusive and detailed picture of the Australian networked public sphere.

Robust suspicious behaviour detection for smart surveillance systems

Video surveillance technology, based on Closed Circuit Television (CCTV) cameras, is one of the fastest growing markets in the field of security technologies. However, the existing video surveillance systems are still not at a stage where they can be used for crime prevention. The systems rely heavily on human observers and are therefore limited by factors such as fatigue and monitoring capabilities over long periods of time. To overcome this limitation, it is necessary to have “intelligent” processes which are able to highlight the salient data and filter out normal conditions that do not pose a threat to security. In order to create such intelligent systems, an understanding of human behaviour, specifically, suspicious behaviour is required. One of the challenges in achieving this is that human behaviour can only be understood correctly in the context in which it appears. Although context has been exploited in the general computer vision domain, it has not been widely used in the automatic suspicious behaviour detection domain. So, it is essential that context has to be formulated, stored and used by the system in order to understand human behaviour. Finally, since surveillance systems could be modeled as largescale data stream systems, it is difficult to have a complete knowledge base. In this case, the systems need to not only continuously update their knowledge but also be able to retrieve the extracted information which is related to the given context. To address these issues, a context-based approach for detecting suspicious behaviour is proposed. In this approach, contextual information is exploited in order to make a better detection. The proposed approach utilises a data stream clustering algorithm in order to discover the behaviour classes and their frequency of occurrences from the incoming behaviour instances. Contextual information is then used in addition to the above information to detect suspicious behaviour. The proposed approach is able to detect observed, unobserved and contextual suspicious behaviour. Two case studies using video feeds taken from CAVIAR dataset and Z-block building, Queensland University of Technology are presented in order to test the proposed approach. From these experiments, it is shown that by using information about context, the proposed system is able to make a more accurate detection, especially those behaviours which are only suspicious in some contexts while being normal in the others. Moreover, this information give critical feedback to the system designers to refine the system. Finally, the proposed modified Clustream algorithm enables the system to both continuously update the system’s knowledge and to effectively retrieve the information learned in a given context. The outcomes from this research are: (a) A context-based framework for automatic detecting suspicious behaviour which can be used by an intelligent video surveillance in making decisions; (b) A modified Clustream data stream clustering algorithm which continuously updates the system knowledge and is able to retrieve contextually related information effectively; and (c) An update-describe approach which extends the capability of the existing human local motion features called interest points based features to the data stream environment.

Digital broadcasting : a double edge sword in protecting children from disturbing news content

New technologies have the potential to both expose children to and protect them from television news footage likely to disturb or frighten. The advent of cheap, portable and widely available digital technology has vastly increased the possibility of violent news events being captured and potentially broadcast. This material has the potential to be particularly disturbing and harmful to young children. But on the flipside, available digital technology could be used to build in protection for young viewers especially when it comes to preserving scheduled television programming and guarding against violent content being broadcast during live crosses from known trouble spots. Based on interviews with news directors, parents and a review of published material two recommendations are put forward: 1. Digital television technology should be employed to prevent news events "overtaking" scheduled children's programming and to protect safe harbours placed in the classifications zones to protect children. 2. Broadcasters should regain control of the images that go to air during "live" feeds from obviously volatile situations by building in short delays in G classification zones.

Single-layer decoupling networks for circulant symmetric arrays

Reduced element spacing in antenna arrays gives rise to strong mutual coupling between array elements and may cause significant performance degradation. These effects can be alleviated by introducing a decoupling network consisting of interconnected reactive elements. The existing design approach for the synthesis of a decoupling network for circulant symmetric arrays allows calculation of element values using closed-form expressions, but the resulting circuit configuration requires multilayer technology for implementation. In this paper, a new structure for the decoupling of circulant symmetric arrays of more than four elements is presented. Element values are no longer obtained in closed form, but the resulting circuit is much simpler and can be implemented on a single layer.

A suspicious behaviour detection using a context space model for smart surveillance systems

Video surveillance systems using Closed Circuit Television (CCTV) cameras, is one of the fastest growing areas in the field of security technologies. However, the existing video surveillance systems are still not at a stage where they can be used for crime prevention. The systems rely heavily on human observers and are therefore limited by factors such as fatigue and monitoring capabilities over long periods of time. This work attempts to address these problems by proposing an automatic suspicious behaviour detection which utilises contextual information. The utilisation of contextual information is done via three main components: a context space model, a data stream clustering algorithm, and an inference algorithm. The utilisation of contextual information is still limited in the domain of suspicious behaviour detection. Furthermore, it is nearly impossible to correctly understand human behaviour without considering the context where it is observed. This work presents experiments using video feeds taken from CAVIAR dataset and a camera mounted on one of the buildings Z-Block) at the Queensland University of Technology, Australia. From these experiments, it is shown that by exploiting contextual information, the proposed system is able to make more accurate detections, especially of those behaviours which are only suspicious in some contexts while being normal in the others. Moreover, this information gives critical feedback to the system designers to refine the system.

How long is a tweet? Mapping dynamic conversation networks on Twitter using Gawk and Gephi

Twitter is now well established as the world’s second most important social media platform, after Facebook. Its 140-character updates are designed for brief messaging, and its network structures are kept relatively flat and simple: messages from users are either public and visible to all (even to unregistered visitors using the Twitter website), or private and visible only to approved ‘followers’ of the sender; there are no more complex definitions of degrees of connection (family, friends, friends of friends) as they are available in other social networks. Over time, Twitter users have developed simple, but effective mechanisms for working around these limitations: ‘#hashtags’, which enable the manual or automatic collation of all tweets containing the same #hashtag, as well allowing users to subscribe to content feeds that contain only those tweets which feature specific #hashtags; and ‘@replies’, which allow senders to direct public messages even to users whom they do not already follow. This paper documents a methodology for extracting public Twitter activity data around specific #hashtags, and for processing these data in order to analyse and visualize the @reply networks existing between participating users – both overall, as a static network, and over time, to highlight the dynamic structure of @reply conversations. Such visualizations enable us to highlight the shifting roles played by individual participants, as well as the response of the overall #hashtag community to new stimuli – such as the entry of new participants or the availability of new information. Over longer timeframes, it is also possible to identify different phases in the overall discussion, or the formation of distinct clusters of preferentially interacting participants.

The association between maternal infant feeding practices and child weight at 11-17 months in first-time Australian mothers

Introduction: Emerging evidence reveals that early feeding practices are associated with child food intake, eating behaviour and weight status. This cross-sectional analysis examined the association between maternal infant feeding practices/beliefs and child weight in Australian infants aged 11-17 months. Methods: Participants were 293 first-time mothers of healthy term infants (144 boys, mean age 14±1 months) enrolled in the NOURISH RCT. Mothers self-reported infant feeding practices and beliefs using the Infant Feeding Questionnaire (Baughcum, 2001). Anthropometric data were also measured at baseline (infants aged 4 months). Multiple regression analysis was used, adjusting for infant age, gender, birth weight, infant feeding mode (breast vs. formula), maternal perceptions of infant weight status, pre-pregnancy weight, weight concern, age and education. Results: The average child weight-for-age z-score (WAZ) was 0.62±0.83 (range:-1.56 to 2.94) and the mean change in WAZ (WAZ change) from 4 to 14 months was 0.62±0.69 (range:-1.50 to 2.76). Feeding practices/beliefs partly explained child WAZ (R2=0.28) and WAZ change (R2=0.13) in the adjusted models. While child weight status at 14 months was inversely associated with responsive feeding (e.g. baby feeds whenever she wants, feeding to stop baby being unsettled) (β=-0.104, p=0.06) and maternal concern about the child becoming underweight (β=-0.224, p<0.001), it was positively associated with mother’s concern about child overweight (β=0.197, p<0.05). Birth weight, infant’s age, maternal weight concern and perceiving her child as overweight were significant covariates. WAZ change was only significantly associated with responsive feeding (β=-0.147, p<0.05). Conclusion: Responsive feeding may be an important strategy to promote healthy child weight.

UWB antenna array for wireless transmission along corridors

A 2-element elliptical patch antenna array with a bi-directional radiation pattern has been developed for ultra wideband indoor wireless communications. The array is constructed by means of feeding two omni-directional elliptical patch elements with a 3-section hybrid power divider. Experimental results show that the array has a stable radiation pattern and low return loss over a broad bandwidth of 64% (3.1 - 6 GHz).

Tools and methods for capturing Twitter data during natural disasters

During the course of several natural disasters in recent years, Twitter has been found to play an important role as an additional medium for many–to–many crisis communication. Emergency services are successfully using Twitter to inform the public about current developments, and are increasingly also attempting to source first–hand situational information from Twitter feeds (such as relevant hashtags). The further study of the uses of Twitter during natural disasters relies on the development of flexible and reliable research infrastructure for tracking and analysing Twitter feeds at scale and in close to real time, however. This article outlines two approaches to the development of such infrastructure: one which builds on the readily available open source platform yourTwapperkeeper to provide a low–cost, simple, and basic solution; and, one which establishes a more powerful and flexible framework by drawing on highly scaleable, state–of–the–art technology.

Enhancing opportunities to feed forward ; developing problem solving skills using web based scenarios

Universities often struggle to satisfy students’ need for feedback. This is an area where student satisfaction with courses of study can be low. Yet it is clear that one of the properties of good teaching is giving the highest quality feedback on student work. The term ‘feedback’ though is most commonly associated with summative assessment given by a teacher after work is completed. The student can often be a passive participant in the process. This paper looks at the implementation of a web based interactive scenario completed by students prior to summative assessment. It requires students to participate actively to develop and improve their legal problem solving skills. Traditional delivery of legal education focuses on print and an instructor who conveys the meaning of the written word to students. Today, mixed modes of teaching are often preferred and they can provide enhanced opportunities for feeding forward with greater emphasis on what students do. Web based activities allow for flexible delivery; they are accessible off campus, at a time that suits the student and may be completed by students at their own pace. This paper reports on an online interactive activity which provides valuable formative feedback necessary to allow for successful completion of a final problem solving assignment. It focuses on how the online activity feeds forward and contributes to the development of legal problem solving skills. Introduction to Law is a unit designed and introduced for completion by undergraduate students from faculties other than law but is focused most particularly on students enrolled in the Bachelor of Entertainment Industries degree, a joint initiative of the faculties of Creative Industries, Business and Law at the Queensland University of Technology in Australia. The final (and major) assessment for the unit is an assignment requiring students to explain the legal consequences of particular scenarios. A number of cost effective web based interactive scenarios have been developed to support the unit’s classroom activities. The tool commences with instruction on problem solving method. Students then view the stimulus which is a narrative produced in the form of a music video clip. A series of questions are posed which guide students through the process and they can compare their responses with sample answers provided. The activity clarifies the problem solving method and expectations for the summative assessment and allows students to practise the skill. The paper reports on the approach to teaching and learning taken in the unit including the design process and implementation of the activity. It includes an evaluation of the activity with respect to its effectiveness as a tool to feed forward and reflects on the implications for the teaching of law in higher education.