Particle number and mass emission factors from combustion of wood samples collected from Queensland forest

Knowledge of particle emission characteristics associated with forest fires and in general, biomass burning, is becoming increasingly important due to the impact of these emissions on human health. Of particular importance is developing a better understanding of the size distribution of particles generated from forest combustion under different environmental conditions, as well as provision of emission factors for different particle size ranges. This study was aimed at quantifying particle emission factors from four types of wood found in South East Queensland forests: Spotted Gum (Corymbia citriodora), Red Gum (Eucalypt tereticornis), Blood Gum (Eucalypt intermedia), and Iron bark (Eucalypt decorticans); under controlled laboratory conditions. The experimental set up included a modified commercial stove connected to a dilution system designed for the conditions of the study. Measurements of particle number size distribution and concentration resulting from the burning of woods with a relatively homogenous moisture content (in the range of 15 to 26 %) and for different rates of burning were performed using a TSI Scanning Mobility Particle Sizer (SMPS) in the size range from 10 to 600 nm and a TSI Dust Trak for PM2.5. The results of the study in terms of the relationship between particle number size distribution and different condition of burning for different species show that particle number emission factors and PM2.5 mass emission factors depend on the type of wood and the burning rate; fast burning or slow burning. The average particle number emission factors for fast burning conditions are in the range of 3.3 x 1015 to 5.7 x 1015 particles/kg, and for PM2.5 are in the range of 139 to 217 mg/kg.

The function of property in creating an effective legal regime for trade in environmental offsets

Market-based environmental regulation is becoming increasingly common within international and national frameworks. Environmental offset and trading regimes are part of the market-based instrument revolution. This paper proposes that environmental market mechanisms could be used to introduce an ethic of land holder responsibility. In order for market based regimes to attract sufficient levels of stakeholder engagement, participants within such scheme require an incentive to participate and furthermore need to feel a sense of security about investing in such processes. A sense of security is often associated with property based interests. This paper explores the property related issues connected with environmental offset and trading scheme initiatives. Relevant property-related considerations include land tenure considerations, public versus private management of land choices, characteristics and powers associated with property interests, theories defining property and the recognition of legal proprietal interests. The Biodiversity Banking Scheme in New South Wales is then examined as a case study followed by a critique on the role of environmental markets.

Cipher cities : effective user interface design for building a digital social network around location-based gaming

In this paper we explore what is required of a User Interface (UI) design in order to encourage participation around playing and creating Location-Based Games (LBGs). To base our research in practice, we present Cipher Cities, a web based system. Through the design of this system, we investigate how UI design can provide tools for complex content creation to compliment and encourage the use of mobile phones for designing, distributing, and playing LBGs. Furthermore we discuss how UI design can promote and support socialisation around LBGs through the design of functional interface components and services such as groups, user profiles, and player status listings.

Effective web service discovery using a combination of a semantic model and a data mining technique

With the advent of Service Oriented Architecture, Web Services have gained tremendous popularity. Due to the availability of a large number of Web services, finding an appropriate Web service according to the requirement of the user is a challenge. This warrants the need to establish an effective and reliable process of Web service discovery. A considerable body of research has emerged to develop methods to improve the accuracy of Web service discovery to match the best service. The process of Web service discovery results in suggesting many individual services that partially fulfil the user’s interest. By considering the semantic relationships of words used in describing the services as well as the use of input and output parameters can lead to accurate Web service discovery. Appropriate linking of individual matched services should fully satisfy the requirements which the user is looking for. This research proposes to integrate a semantic model and a data mining technique to enhance the accuracy of Web service discovery. A novel three-phase Web service discovery methodology has been proposed. The first phase performs match-making to find semantically similar Web services for a user query. In order to perform semantic analysis on the content present in the Web service description language document, the support-based latent semantic kernel is constructed using an innovative concept of binning and merging on the large quantity of text documents covering diverse areas of domain of knowledge. The use of a generic latent semantic kernel constructed with a large number of terms helps to find the hidden meaning of the query terms which otherwise could not be found. Sometimes a single Web service is unable to fully satisfy the requirement of the user. In such cases, a composition of multiple inter-related Web services is presented to the user. The task of checking the possibility of linking multiple Web services is done in the second phase. Once the feasibility of linking Web services is checked, the objective is to provide the user with the best composition of Web services. In the link analysis phase, the Web services are modelled as nodes of a graph and an allpair shortest-path algorithm is applied to find the optimum path at the minimum cost for traversal. The third phase which is the system integration, integrates the results from the preceding two phases by using an original fusion algorithm in the fusion engine. Finally, the recommendation engine which is an integral part of the system integration phase makes the final recommendations including individual and composite Web services to the user. In order to evaluate the performance of the proposed method, extensive experimentation has been performed. Results of the proposed support-based semantic kernel method of Web service discovery are compared with the results of the standard keyword-based information-retrieval method and a clustering-based machine-learning method of Web service discovery. The proposed method outperforms both information-retrieval and machine-learning based methods. Experimental results and statistical analysis also show that the best Web services compositions are obtained by considering 10 to 15 Web services that are found in phase-I for linking. Empirical results also ascertain that the fusion engine boosts the accuracy of Web service discovery by combining the inputs from both the semantic analysis (phase-I) and the link analysis (phase-II) in a systematic fashion. Overall, the accuracy of Web service discovery with the proposed method shows a significant improvement over traditional discovery methods.

From mass communication to mass conversation : why 1984 wasn't like 1984

Marketers and commercial media alike are confronted by shifts in the social relations of media production and consumption in the global services economy, including the challenge of capturing, managing and commercialising media-user productivity. This trajectory of change in media cultures and economies is described here as ‘mass conversation’. Two media texts and a new media object provide a starting point for charting the ascendance and social impact of mass conversation. Apple’s 1984 television commercial, which launched the Macintosh computer, inverted George Orwell’s dystopian vision of the social consequences of panoptic communications systems. It invoked a revolutionary rhetoric to anticipate the social consequences of a new type of interactivity since theorised as ‘intercreativity’. This television commercial is contrasted with another used in Nike’s 2006 launch of its Nike+ (Apple iPod) system. The Nike+ online brand community is also used to consider how a multiplatform brand channel is seeking to manage the changing norms and practices of consumption and end-user agency. This analysis shows that intercreativity modifies the operations of ‘Big Brother’ but serves the more mundane than revolutionary purpose of generating commercial value from the affective labour of end-users.