Farm it right : the sustainable farming simulation

Farm It Right is an innovative creative work that simulates sustainable farming techniques using ecological models prepared by academics at Bradford University (School of Life Sciences). This interactive work simulates the farming conditions and options of our ancestors and demonstrates the direct impact their actions had on their environment and on the ’future of their cultures’ (Schmidt 2008). Specifically, the simulation allows users to explore and experiment with the complex relationships between environmental factors and human decision making within the harsh conditions of an early (9th century) Nordic farm. The simulation interface displays both statistical and graphical feedback in response to the users selections regarding animal reproduction rates, shelter provisions, food supplies etc. as well as demonstrating resulting impacts to soil erosion, water supply, animal population sizes etc.---------- 'Farm It Right' is now used at Bradford University (School of Life Sciences) as a dynamic e-Learning resource for incorporating environmental archaeology with sustainable development education, improving the engagement with complex data and the appreciation of human impacts on the environment and the future of their cultures. 'Farm It Right' is also demonstrated as an exemplar case study for interaction design students at Queensland University of Technology.

Modelling urban public transit users’ route choice behaviour : a review and outlook

Public transport is one of the key promoters of sustainable urban transport. To encourage and increase public transport patronage it is important to investigate the route choice behaviours of urban public transit users. This chapter reviews the main developments of modelling urban public transit users’ route choice behaviours in a historical perspective, from the 1960s to the present time. The approaches re- viewed for this study include the early heuristic studies on finding the least-cost transit route and all-or- nothing transit assignment, the bus common lines problem, the disaggregate discrete choice models, the deterministic and stochastic user equilibrium transit assignment models, and the recent dynamic transit assignment models. This chapter also provides an outlook for the future directions of modelling transit users’ route choice behaviours. Through the comparison with the development of models for motorists’ route choice and traffic assignment problems, this chapter advocates that transit route choice research should draw inspiration from the research outcomes from the road area, and that the modelling practice of transit users’ route choice should further explore the behavioural complexities.

Dealing with the problem of cybercrime

Lack of a universally accepted and comprehensive taxonomy of cybercrime seriously impedes international efforts to accurately identify, report and monitor cybercrime trends. There is, not surprisingly, a corresponding disconnect internationally on the cybercrime legislation front, a much more serious problem and one which the International Telecommunication Union (ITU) says requires „the urgent attention of all nations‟. Yet, and despite the existence of the Council of Europe Convention on Cybercrime, a proposal for a global cybercrime treaty was rejected by the United Nations (UN) as recently as April 2010. This paper presents a refined and comprehensive taxonomy of cybercrime and demonstrates its utility for widespread use. It analyses how the USA, the UK, Australia and the UAE align with the CoE Convention and finds that more needs to be done to achieve conformance. We conclude with an analysis of the approaches used in Australia, in Queensland, and in the UAE, in Abu Dhabi, to fight cybercrime and identify a number of shared problems.

Using Association Rules to Solve the Cold-Start Problem in Recommender Systems

Recommender systems are widely used online to help users find other products, items etc that they may be interested in based on what is known about that user in their profile. Often however user profiles may be short on information and thus it is difficult for a recommender system to make quality recommendations. This problem is known as the cold-start problem. Here we investigate using association rules as a source of information to expand a user profile and thus avoid this problem. Our experiments show that it is possible to use association rules to noticeably improve the performance of a recommender system under the cold-start situation. Furthermore, we also show that the improvement in performance obtained can be achieved while using non-redundant rule sets. This shows that non-redundant rules do not cause a loss of information and are just as informative as a set of association rules that contain redundancy.

Identifying interests of web users for effective recommendations

Search log data is multi dimensional data consisting of number of searches of multiple users with many searched parameters. This data can be used to identify a user’s interest in an item or object being searched. Identifying highest interests of a Web user from his search log data is a complex process. Based on a user’s previous searches, most recommendation methods employ two-dimensional models to find relevant items. Such items are then recommended to a user. Two-dimensional data models, when used to mine knowledge from such multi dimensional data may not be able to give good mappings of user and his searches. The major problem with such models is that they are unable to find the latent relationships that exist between different searched dimensions. In this research work, we utilize tensors to model the various searches made by a user. Such high dimensional data model is then used to extract the relationship between various dimensions, and find the prominent searched components. To achieve this, we have used popular tensor decomposition methods like PARAFAC, Tucker and HOSVD. All experiments and evaluation is done on real datasets, which clearly show the effectiveness of tensor models in finding prominent searched components in comparison to other widely used two-dimensional data models. Such top rated searched components are then given as recommendation to users.

Information sharing in Onesocialweb using a multiple profile manager to better informed medical decision making processes

The study shows an alternative solution to existing efforts at solving the problem of how to centrally manage and synchronise users’ Multiple Profiles (MP) across multiple discrete social networks. Most social network users hold more than one social network account and utilise them in different ways depending on the digital context (Iannella, 2009a). They may, for example, enjoy friendly chat on Facebook1, professional discussion on LinkedIn2, and health information exchange on PatientsLikeMe3 In this thesis the researcher proposes a framework for the management of a user’s multiple online social network profiles. A demonstrator, called Multiple Profile Manager (MPM), will be showcased to illustrate how effective the framework will be. The MPM will achieve the required profile management and synchronisation using a free, open, decentralized social networking platform (OSW) that was proposed by the Vodafone Group in 2010. The proposed MPM will enable a user to create and manage an integrated profile (IP) and share/synchronise this profile with all their social networks. The necessary protocols to support the prototype are also proposed by the researcher. The MPM protocol specification defines an Extensible Messaging and Presence Protocol (XMPP) extension for sharing vCard and social network accounts information between the MPM Server, MPM Client, and social network sites (SNSs). . Therefore many web users need to manage disparate profiles across many distributed online sources. Maintaining these profiles is cumbersome, time-consuming, inefficient, and may lead to lost opportunity. The writer of this thesis adopted a research approach and a number of use cases for the implementation of the project. The use cases were created to capture the functional requirements of the MPM and to describe the interactions between users and the MPM. In the research a development process was followed in establishing the prototype and related protocols. The use cases were subsequently used to illustrate the prototype via the screenshots taken of the MPM client interfaces. The use cases also played a role in evaluating the outcomes of the research such as the framework, prototype, and the related protocols. An innovative application of this project is in the area of public health informatics. The researcher utilised the prototype to examine how the framework might benefit patients and physicians. The framework can greatly enhance health information management for patients and more importantly offer a more comprehensive personal health overview of patients to physicians. This will give a more complete picture of the patient’s background than is currently available and will prove helpful in providing the right treatment. The MPM prototype and related protocols have a high application value as they can be integrated into the real OSW platform and so serve users in the modern digital world. They also provide online users with a real platform for centrally storing their complete profile data, efficiently managing their personal information, and moreover, synchronising the overall complete profile with each of their discrete profiles stored in their different social network sites.

Right-angle crash vulnerability of motorcycles at signalized intersections : mixed logit analysis

Motorcycles are particularly vulnerable in right-angle crashes at signalized intersections. The objective of this study is to explore how variations in roadway characteristics, environmental factors, traffic factors, maneuver types, human factors as well as driver demographics influence the right-angle crash vulnerability of motorcycles at intersections. The problem is modeled using a mixed logit model with a binary choice category formulation to differentiate how an at-fault vehicle collides with a not-at-fault motorcycle in comparison to other collision types. The mixed logit formulation allows randomness in the parameters and hence takes into account the underlying heterogeneities potentially inherent in driver behavior, and other unobserved variables. A likelihood ratio test reveals that the mixed logit model is indeed better than the standard logit model. Night time riding shows a positive association with the vulnerability of motorcyclists. Moreover, motorcyclists are particularly vulnerable on single lane roads, on the curb and median lanes of multi-lane roads, and on one-way and two-way road type relative to divided-highway. Drivers who deliberately run red light as well as those who are careless towards motorcyclists especially when making turns at intersections increase the vulnerability of motorcyclists. Drivers appear more restrained when there is a passenger onboard and this has decreased the crash potential with motorcyclists. The presence of red light cameras also significantly decreases right-angle crash vulnerabilities of motorcyclists. The findings of this study would be helpful in developing more targeted countermeasures for traffic enforcement, driver/rider training and/or education, safety awareness programs to reduce the vulnerability of motorcyclists.

‘My people right here…’ Indigenous young people, alienation and paint sniffing in inner Brisbane

This paper describes and explains the social worlds of a group of young Murris who are engaged in chroming (paint sniffing) and who sleep rough in inner Brisbane. In particular, the paper considers the ways young Indigenous drug users describe their marginalisation from wider society and its structures of opportunity, but it also includes some reflections from their youth worker and a young man who frequents the young people’s squat. The paper demonstrates the centrality of racism and material disadvantage to the experience of a group of young Aboriginal and Torres Strait Islander sniffers, a perspective largely unreflected in the literature on Indigenous volatile substance misuse. Further, the young people’s ways of interacting with the broader society are described to explain the ways their rejection of mainstream norms form a significant political response to their marginality and reflect, at least in part, the wider Indigenous historical experience. The work draws on theories of alienation and subculture to analyse the young people’s descriptions of their social estrangement and the formation of the ‘paint sniffer group’. It is concluded that paint sniffing among urban Indigenous youth is, at least in part, an obnoxious and encoded distillation of a wider Indigenous rebuttal of broader societal norms, and that the dominant — normalising — modes of treatment risk further alienating an already oppositional group of young people.

The state-of-the-art in personalized recommender systems for social networking

With the explosion of Web 2.0 application such as blogs, social and professional networks, and various other types of social media, the rich online information and various new sources of knowledge flood users and hence pose a great challenge in terms of information overload. It is critical to use intelligent agent software systems to assist users in finding the right information from an abundance of Web data. Recommender systems can help users deal with information overload problem efficiently by suggesting items (e.g., information and products) that match users’ personal interests. The recommender technology has been successfully employed in many applications such as recommending films, music, books, etc. The purpose of this report is to give an overview of existing technologies for building personalized recommender systems in social networking environment, to propose a research direction for addressing user profiling and cold start problems by exploiting user-generated content newly available in Web 2.0.

Thai family support (TFS) : working with families of young substance users in primary health care

Living with substance users negatively impacts upon family members in many ways, and distress is common. Despite these deep and wide-ranging impacts, supportive interventions for family members in their own right are rarely available. Thailand has substantial and growing problems with substance use, and there is very little support or family members of drug users, especially in community setting. The Thai Family Support (TFS) program was designed for implementation in primary health care units (PCUs) in Thailand. TFS was based on two approaches with existing empirical support in Western contexts—the 5-step method and CRAFT—with adaptations to a Thai setting that included integration with Buddhist practices. Its aims were to increase well-being of family members, reduce mental distress, improve family relationships between family members, and engage substance users in behaviour change. A small-scale randomised controlled trial on TFS with a Delayed Treatment control was conducted, with assessments at 8 weeks (Post 1) and 20-24 weeks (Post 2). Structured interviews with participants and PCU staff and an examination of five case studies augmented the quantitative results. Mixed Model Analyses were applied to quantitative outcomes, and thematic analysis was used for qualitative data. Thirty-six participants (18 in each of Immediate and Delayed Conditions) were recruited. A significant difference at Baseline between the two conditions was observed on the Thai GHQ-28 and Gender, but it was not possible to statistically control for these effects. There was a significant Time by Condition interaction on the Thai GHQ-28, WHOQOL-BREF-THAI and FAS, reflecting greater improvements in the Immediate condition by Post 1, but with the Delayed condition meeting or exceeding that effect by Post 2. On FES Cohesion and Conflict, there were falls across conditions at Post 2, but only Cohesion also showed a Time by Condition interaction, and that effect was consistent with a delayed impact of treatment. Overall, TFS by PCU staff in the Delayed Condition gave similar results to TFS conducted by the researcher, supporting the viability of its dissemination to standard health services. Qualitative data also confirmed the quantitative results. Most participants reported physiological and psychological improvements even though their substance-using relative did not change their drug use behaviour. After completing TFS, participants reported increased knowledge, group support and sharing feeling, having positive patient-professional relationship, having greater knowledge of substance abuse and social support. In particular, they changed their behaviour towards the substance user, resulting in improvements to family relationships. PCU staff gave similar responses on the efficacy of TFS, and saw it as feasible for routine use, although some implementation challenges were identified. The cultural adaptation and in particular the religious activities, were recognised by participants and PCU staff as an important component of TFS to support psychological health and well-being. Findings from this study showed the impact of substance use on family members and difficulties that they experienced when living with the substance users, resulting distresses and burden that may develop severe mental health disease. Drug use policies should be modified to support family members and response to their needs effectively for early prevention. This study also gave preliminary support for application of the TFS program in rural primary care settings and identified some policies that will be required for it to be disseminated more broadly.

Naming or creating a problem?

In this chapter, we are going to consider how language and practice interact in the process of supporting the learning of students with diverse abilities. You will learn that it is necessary for teachers to understand that while labels carry an administrative function in schools, when used carelessly they operate to stigmatise and exclude those whom we are working to include. This chapter will introduce the concept of equity and explain how the dilemma of difference emerges when we try to determine who should receive support and how. The chapter will also explain how an appreciation of language can help to inform and transform our pedagogy. An example of inclusion in action is provided to illustrate how inclusive language in practice can promote deep cultural changes that benefit both students and teachers. The process of determining appropriate and effective education of students with additional support requirements is troubled by what some refer to as the ‘dilemma of difference’. This dilemma derives mainly from the nature of language and our need to use certain words, terms and categories in order to share common understandings. Without these, educators cannot hope to arrive on the same page, yet such words can take on a life of their own; influencing thoughts, perspectives and attitudes in ways that far outstrip original intentions. The drive for clarity, however, through definition and diagnostic classification can ultimately obscure because of the cultural meanings that become invested within these terms through their use over time and in different professional contexts. In effect, trying to define “difference” in order to provide the right support to particular students is a process that entrenches normative boundaries that in turn create, accentuate and stigmatise whatever we have decided constitutes difference. Language is thus a powerful and dangerous weapon but, like other weapons, language can both hurt and defend. Understanding the power of language enables educators to use it both wisely and safely to the maximum benefit of their students. This chapter will discuss how teachers can recognise and support their students in ways that avoid stigma and the closure of stereotyping.

Modelling users' contextual querying behaviour for web image searching

The rapid growth of visual information on Web has led to immense interest in multimedia information retrieval (MIR). While advancement in MIR systems has achieved some success in specific domains, particularly the content-based approaches, general Web users still struggle to find the images they want. Despite the success in content-based object recognition or concept extraction, the major problem in current Web image searching remains in the querying process. Since most online users only express their needs in semantic terms or objects, systems that utilize visual features (e.g., color or texture) to search images create a semantic gap which hinders general users from fully expressing their needs. In addition, query-by-example (QBE) retrieval imposes extra obstacles for exploratory search because users may not always have the representative image at hand or in mind when starting a search (i.e. the page zero problem). As a result, the majority of current online image search engines (e.g., Google, Yahoo, and Flickr) still primarily use textual queries to search. The problem with query-based retrieval systems is that they only capture users’ information need in terms of formal queries;; the implicit and abstract parts of users’ information needs are inevitably overlooked. Hence, users often struggle to formulate queries that best represent their needs, and some compromises have to be made. Studies of Web search logs suggest that multimedia searches are more difficult than textual Web searches, and Web image searching is the most difficult compared to video or audio searches. Hence, online users need to put in more effort when searching multimedia contents, especially for image searches. Most interactions in Web image searching occur during query reformulation. While log analysis provides intriguing views on how the majority of users search, their search needs or motivations are ultimately neglected. User studies on image searching have attempted to understand users’ search contexts in terms of users’ background (e.g., knowledge, profession, motivation for search and task types) and the search outcomes (e.g., use of retrieved images, search performance). However, these studies typically focused on particular domains with a selective group of professional users. General users’ Web image searching contexts and behaviors are little understood although they represent the majority of online image searching activities nowadays. We argue that only by understanding Web image users’ contexts can the current Web search engines further improve their usefulness and provide more efficient searches. In order to understand users’ search contexts, a user study was conducted based on university students’ Web image searching in News, Travel, and commercial Product domains. The three search domains were deliberately chosen to reflect image users’ interests in people, time, event, location, and objects. We investigated participants’ Web image searching behavior, with the focus on query reformulation and search strategies. Participants’ search contexts such as their search background, motivation for search, and search outcomes were gathered by questionnaires. The searching activity was recorded with participants’ think aloud data for analyzing significant search patterns. The relationships between participants’ search contexts and corresponding search strategies were discovered by Grounded Theory approach. Our key findings include the following aspects: - Effects of users' interactive intents on query reformulation patterns and search strategies - Effects of task domain on task specificity and task difficulty, as well as on some specific searching behaviors - Effects of searching experience on result expansion strategies A contextual image searching model was constructed based on these findings. The model helped us understand Web image searching from user perspective, and introduced a context-aware searching paradigm for current retrieval systems. A query recommendation tool was also developed to demonstrate how users’ query reformulation contexts can potentially contribute to more efficient searching.

An ontology-based method for sparsity problem in tag recommendation

Tags or personal metadata for annotating web resources have been widely adopted in Web 2.0 sites. However, as tags are freely chosen by users, the vocabularies are diverse, ambiguous and sometimes only meaningful to individuals. Tag recommenders may assist users during tagging process. Its objective is to suggest relevant tags to use as well as to help consolidating vocabulary in the systems. In this paper we discuss our approach for providing personalized tag recommendation by making use of existing domain ontology generated from folksonomy. Specifically we evaluated the approach in sparse situation. The evaluation shows that the proposed ontology-based method has improved the accuracy of tag recommendation in this situation.

A combined method for mitigating sparsity problem in tag recommendation

Tag recommendation is a specific recommendation task for recommending metadata (tag) for a web resource (item) during user annotation process. In this context, sparsity problem refers to situation where tags need to be produced for items with few annotations or for user who tags few items. Most of the state of the art approaches in tag recommendation are rarely evaluated or perform poorly under this situation. This paper presents a combined method for mitigating sparsity problem in tag recommendation by mainly expanding and ranking candidate tags based on similar items’ tags and existing tag ontology. We evaluated the approach on two public social bookmarking datasets. The experiment results show better accuracy for recommendation in sparsity situation over several state of the art methods.

The effect of surface tension and kinetic undercooling on a radially-symmetric melting problem

The addition of surface tension to the classical Stefan problem for melting a sphere causes the solution to blow up at a finite time before complete melting takes place. This singular behaviour is characterised by the speed of the solid-melt interface and the flux of heat at the interface both becoming unbounded in the blow-up limit. In this paper, we use numerical simulation for a particular energy-conserving one-phase version of the problem to show that kinetic undercooling regularises this blow-up, so that the model with both surface tension and kinetic undercooling has solutions that are regular right up to complete melting. By examining the regime in which the dimensionless kinetic undercooling parameter is small, our results demonstrate how physically realistic solutions to this Stefan problem are consistent with observations of abrupt melting of nanoscaled particles.