Reputation modelling in citizen science for environmental acoustic data analysis

Citizen Science projects are initiatives in which members of the general public participate in scientific research projects and perform or manage research-related tasks such as data collection and/or data annotation. Citizen Science is technologically possible and scientifically significant. However, as the gathered information is from the crowd, the data quality is always hard to manage. There are many ways to manage data quality, and reputation management is one of the common approaches. In recent year, many research teams have deployed many audio or image sensors in natural environment in order to monitor the status of animals or plants. The collected data will be analysed by ecologists. However, as the amount of collected data is exceedingly huge and the number of ecologists is very limited, it is impossible for scientists to manually analyse all these data. The functions of existing automated tools to process the data are still very limited and the results are still not very accurate. Therefore, researchers have turned to recruiting general citizens who are interested in helping scientific research to do the pre-processing tasks such as species tagging. Although research teams can save time and money by recruiting general citizens to volunteer their time and skills to help data analysis, the reliability of contributed data varies a lot. Therefore, this research aims to investigate techniques to enhance the reliability of data contributed by general citizens in scientific research projects especially for acoustic sensing projects. In particular, we aim to investigate how to use reputation management to enhance data reliability. Reputation systems have been used to solve the uncertainty and improve data quality in many marketing and E-Commerce domains. The commercial organizations which have chosen to embrace the reputation management and implement the technology have gained many benefits. Data quality issues are significant to the domain of Citizen Science due to the quantity and diversity of people and devices involved. However, research on reputation management in this area is relatively new. We therefore start our investigation by examining existing reputation systems in different domains. Then we design novel reputation management approaches for Citizen Science projects to categorise participants and data. We have investigated some critical elements which may influence data reliability in Citizen Science projects. These elements include personal information such as location and education and performance information such as the ability to recognise certain bird calls. The designed reputation framework is evaluated by a series of experiments involving many participants for collecting and interpreting data, in particular, environmental acoustic data. Our research in exploring the advantages of reputation management in Citizen Science (or crowdsourcing in general) will help increase awareness among organizations that are unacquainted with its potential benefits.

Measuring neighbourhood sustainability : a comparative analysis of residential types in Malaysia

The expansion of city-regions, the increase in the standard of living and changing lifestyles have collectively led to an increase in housing demand. New residential areas are encroaching onto the city fringes including suburban and green field areas. Large and small developers are actively building houses ranging from a few blocks to master-planned style projects. These residential developments, particularly in major urban areas, represent a large portion of urban land use in Malaysia, and, thus, have become a major contributor to overall urban sustainability. There are three main types that comprise the mainstream, and form integral parts to contemporary urban residential developments, namely, subdivision developments, piecemeal developments, and master-planned developments. Many new master-planned developments market themselves as environmentally friendly, and provide layouts that encompass sustainable design and development. To date, however, there have been limited studies conducted to examine such claims or to ascertain which of these three residential development layouts is more sustainable. To fill this gap, this research was undertaken to develop a framework for assessing the level of sustainability of residential developments, focusing on their layouts at the neighbourhood level. The development of this framework adopted a mixed method research strategy and embedded research design to achieve the study aim and objectives. Data were collected from two main sources, where quantitative data were gathered from a three-round Delphi survey and spatial data from a layout plan. Sample respondents for surveys were selected from among experts in the field of the built environment, both from Malaysia and internationally. As for spatial data, three case studies – master-planned, piecemeal and subdivision developments representing different types of neighbourhood developments in Malaysia have been selected. Prior to application on the case studies, the appropriate framework was subjected to validation to ascertain its robustness for application in Malaysia. Following the application of the framework on the three case studies the results revealed that master-planned development scored a better level of sustainability compared to piecemeal and subdivision developments. The results generated from this framework are expected to provide evidence to the policy makers and development agencies as well as provide an awareness of the level of sustainability and the necessary collective efforts required for developing sustainable neighbourhoods. Continuous assessment can facilitate a comparison of sustainability over time for neighbourhoods as a means to monitor changes in the level of sustainability. In addition, the framework is able to identify any particular indicator (issue) that causes a significant impact on sustainability.

Coming to belong : a narrative analysis of international students’ experiences in an Australian university

This thesis reports on an interview study with 17 international students about their experiences of coming to belong in an Australian university. All used English as an additional language (EAL). The students’ narratives of ‘coming to belong’ are conceptualised through the theory of Bourdieu, in particular the concepts of field, capital, habitus and legitimation; and the methodological premises of critical realism’s layered ontology. The literature review argues that access to and accrual of a range of capital is critical to successful adaptation to a new educational system. This, and processes of legitimation by others in the fields, affects the senses of belonging for students of various linguistic backgrounds, of different countries of origin, studying from primary to higher education in diverse parts of the world. Data were collected by semi-structured interviews and email dialogues at three points during the students’ first year of study in Australia. The analysis shows how the students’ empirical experiences were ordered in terms of narrative structure—orientation, complication, evaluation, resolution and coda—and highlight the emotions generated by the sequence of events. The findings show that EAL international students sought new field positions through legitimation in multiple senses across (sub-)fields. They also show that academic, social and linguistic legitimacy granted by others produced a spectrum of belonging: in the centre, at the margin, and/or to meaningful intercultural encounters. This study makes a contribution to the growing literature around the experience of international students in higher education, and to empirical literature using Bourdieu to understand educational relations.

Analysis of indirect message injection for MAC generation using stream ciphers

This paper presents a model for generating a MAC tag with a stream cipher using the input message indirectly. Several recent proposals represent instances of this model with slightly different options. We investigate the security of this model for different options, and identify cases which permit forgery attacks. Based on this, we present a new forgery attack on version 1.4 of 128-EIA3. Design recommendations to enhance the security of proposals following this general model are given.

Analysis of Cone-Beam CT using prior information

Treatment plans for conformal radiotherapy are based on an initial CT scan. The aim is to deliver the prescribed dose to the tumour, while minimising exposure to nearby organs. Recent advances make it possible to also obtain a Cone-Beam CT (CBCT) scan, once the patient has been positioned for treatment. A statistical model will be developed to compare these CBCT scans with the initial CT scan. Changes in the size, shape and position of the tumour and organs will be detected and quantified. Some progress has already been made in segmentation of prostate CBCT scans [1],[2],[3]. However, none of the existing approaches have taken full advantage of the prior information that is available. The planning CT scan is expertly annotated with contours of the tumour and nearby sensitive objects. This data is specific to the individual patient and can be viewed as a snapshot of spatial information at a point in time. There is an abundance of studies in the radiotherapy literature that describe the amount of variation in the relevant organs between treatments. The findings from these studies can form a basis for estimating the degree of uncertainty. All of this information can be incorporated as an informative prior into a Bayesian statistical model. This model will be developed using scans of CT phantoms, which are objects with known geometry. Thus, the accuracy of the model can be evaluated objectively. This will also enable comparison between alternative models.