Too cool for homeschool? Accessing underground unschoolers with Web 2.0

There is a new type of home education parent challenging long-held assumptions about homeschooling (cf. Morton 2012). These parents are well educated (cf. Beck 2010) but have chosen to eschew the social and cultural capital (Bourdieu & Wacquant 1992) of school in favour of some- thing completely different. They are unschoolers, which involves ‘allow- ing children as much freedom to learn in the world as their parents can possibly bear’ (cf. Holt & Farenga 2003: 238). This chapter presents the approach taken by one researcher to explore the reasons families choose unschooling. These families can be difficult to access, because they often fail to register with home education units and thus remain outside the education system (cf. Townsend 2012). Their lack of registration makes them largely invisible, affecting their ability to make an important contribution to debates around education. In spite of this invisibility, many unschoolers are keen to talk to researchers to increase wider understanding of unschooling.

Responsible reconstruction : The architect's role

This paper investigates the role of the architect in post-disaster reconstruction and questions their ability to facilitate per- manent building solutions. There is an ever-increasing population of refugees and internally displaced persons due to disasters and conflicts who have a basic need for shelter. To date, housing solutions for such people has tended to focus on short-term, temporary shelter solutions that have been largely unsuccessful. This increasing demand for shelter has led to an emerging group of architects skilled in post-disaster reconstruction. These architects acknowledge that shelter is critical to survival, but believe architects should focus on rebuilding in a manner that is quick, durable but permanent. They believe that an architect skilled in post-disaster reconstruction can produce solutions that meet the requirement of the emergency phase, through to semi-permanent and even permanent homes, without wasting time and money on interim shelters. Case Study Research was used to examine and evaluate the assistance provided by Emergency Architects Australia (EAA) to the Kei Gold community in the Solomon Islands after the 2007 earthquake and tsunami. The results indicate that an architect’s response to a disaster must go beyond providing temporary shelter; they must create permanent building solutions that respond to the site and the culture while servicing the needs of the communi- ty. The vernacular reconstruction methods implemented by EAA in Kei Gold Village have been successful in develop- ing permanent housing solutions. Further research and development is required to gain a broader understanding of the role of the architect in disasters of varying scales and typologies.

Analyzing and predicting events in soccer and tennis using spatiotemporal data

In this paper, we summarize our recent work in analyz- ing and predicting behaviors in sports using spatiotemporal data. We specifically focus on two recent works: 1) Predicting the location of shot in tennis using Hawk-Eye tennis data, and 2) Clustering spatiotemporal plays in soccer to discover the methods in which they get a shot on goal from a professional league.

Factors influencing robustness and effectiveness of conditional random fields in active learning frameworks

Active learning approaches reduce the annotation cost required by traditional supervised approaches to reach the same effectiveness by actively selecting informative instances during the learning phase. However, effectiveness and robustness of the learnt models are influenced by a number of factors. In this paper we investigate the factors that affect the effectiveness, more specifically in terms of stability and robustness, of active learning models built using conditional random fields (CRFs) for information extraction applications. Stability, defined as a small variation of performance when small variation of the training data or a small variation of the parameters occur, is a major issue for machine learning models, but even more so in the active learning framework which aims to minimise the amount of training data required. The factors we investigate are a) the choice of incremental vs. standard active learning, b) the feature set used as a representation of the text (i.e., morphological features, syntactic features, or semantic features) and c) Gaussian prior variance as one of the important CRFs parameters. Our empirical findings show that incremental learning and the Gaussian prior variance lead to more stable and robust models across iterations. Our study also demonstrates that orthographical, morphological and contextual features as a group of basic features play an important role in learning effective models across all iterations.

Hardware design and implementation of a MAVLink interface for an FPGA-based autonomous UAV flight control system

This paper details the initial design and planning of a Field Programmable Gate Array (FPGA) implemented control system that will enable a path planner to interact with a MAVLink based flight computer. The design is aimed at small Unmanned Aircraft Vehicles (UAV) under autonomous operation which are typically subject to constraints arising from limited on-board processing capabilities, power and size. An FPGA implementation for the de- sign is chosen for its potential to address such limitations through low power and high speed in-hardware computation. The MAVLink protocol offers a low bandwidth interface for the FPGA implemented path planner to communicate with an on-board flight computer. A control system plan is presented that is capable of accepting a string of GPS waypoints generated on-board from a previously developed in- hardware Genetic Algorithm (GA) path planner and feeding them to the open source PX4 autopilot, while simultaneously respond- ing with flight status information.

Efficient web browsing with a single-switch

This paper presents a new approach to web browsing in situ- ations where the user can only provide the device with a sin- gle input command device (switch). Switches have been de- veloped for example for people with locked-in syndrome and are used in combination with scanning to navigate virtual keyboards and desktop interfaces. Our proposed approach leverages the hierarchical structure of webpages to operate a multi-level scan of actionable elements of webpages (links or form elements). As there are a few methods already exist- ing to facilitate browsing under these conditions, we present a theoretical usability evaluation of our approach in com- parison to the existing ones, which takes into account the average time taken to reach any part of a web page (such as a link or a form) but also the number of clicks necessary to reach the goal. We argue that these factors contribute together to usability. In addition, we propose that our ap- proach presents additional usability benefits.

Translocation of bats as a conservation strategy : previous attempts and potential problems

Translocation is an increasingly popular conservation tool from which a wide range of taxa have benefited. However, to our knowledge, bats have not been translocated successfully. Bats differ behaviourally, morphologically and physiologically from the taxa for which translocation the- ory has been developed, so existing guidelines may not be directly transferable. We review previous translocations of bats and discuss characteristics of bats that may require special consideration dur- ing translocation. Their vagility and homing ability, coloniality, roost requirements, potential ability to transmit diseases, susceptibility to anthropomorphic impacts, and cryptic nature have implications for establishing populations, effects of these populations on the release site, and ability to monitor translocation success following release. We hope that our discussion of potential problems will be able to supplement the existing, more generic guidelines to provide a starting point for the planning of bat translocations.

Cryptic marketing : strategic targeting of subculture markets

This research aims to understand what factors influence consumers' behaviour to subculture marketing and how companies can strategically overcome potential brand alienation. Findings validate cryptic marketing as a strategy for organizations to communicate effectively with their chosen market through the use of cryptic cues, symbols and messages while circumventing negative responses from non-target audiences. The thesis contributes to extending current understanding of marketing communication through the use of covert strategies, employing covert tactics on the non-target, wider market instead of the target, subculture market.

Using extended random set to find specific patterns

With the overwhelming increase in the amount of data on the web and data bases, many text mining techniques have been proposed for mining useful patterns in text documents. Extracting closed sequential patterns using the Pattern Taxonomy Model (PTM) is one of the pruning methods to remove noisy, inconsistent, and redundant patterns. However, PTM model treats each extracted pattern as whole without considering included terms, which could affect the quality of extracted patterns. This paper propose an innovative and effective method that extends the random set to accurately weigh patterns based on their distribution in the documents and their terms distribution in patterns. Then, the proposed approach will find the specific closed sequential patterns (SCSP) based on the new calculated weight. The experimental results on Reuters Corpus Volume 1 (RCV1) data collection and TREC topics show that the proposed method significantly outperforms other state-of-the-art methods in different popular measures.

Interpreting discovered patterns in terms of ontology concepts

Semantic Web offers many possibilities for future Web technologies. Therefore, it is a need to search for ways that can bring the huge amount of unstructured documents from current Web to Semantic Web automatically. One big challenge in searching for such ways is how to understand patterns by both humans and machine. To address this issue, we present an innovative model which interprets patterns to high level concepts. These concepts can explain the patterns' meanings in a human understandable way while improving the information filtering performance. The model is evaluated by comparing it against one state-of-the-art benchmark model using standard Reuters dataset. The results show that the proposed model is successful. The significance of this model is three fold. It gives a way to interpret text mining output, provides a technique to find concepts relevant to the whole set of patterns which is an essential feature to understand the topic, and to some extent overcomes information mismatch and overload problems of existing models. This model will be very useful for knowledge based applications.