Water uptake of aerosols with a focus on seeded aerosols and instrumentation techniques

This thesis focuses on the volatile and hygroscopic properties of mixed aerosol species. In particular, the influence organic species of varying solubility have upon seed aerosols. Aerosol studies were conducted at the Paul Scherrer Institut Laboratory for Atmospheric Chemistry (PSI-LAC, Villigen, Switzerland) and at the Queensland University of Technology International Laboratory for Air Quality and Health (QUT-ILAQH, Brisbane, Australia). The primary measurement tool employed in this program was the Volatilisation and Hygroscopicity Tandem Differential Mobility Analyser (VHTDMA - Johnson et al. 2004). This system was initially developed at QUT within the ILAQH and was completely re-developed as part of this project (see Section 1.4 for a description of this process). The new VHTDMA was deployed to the PSI-LAC where an analysis of the volatile and hygroscopic properties of ammonium sulphate seeds coated with organic species formed from the photo-oxidation of á-pinene was conducted. This investigation was driven by a desire to understand the influence of atmospherically prevalent organics upon water uptake by material with cloud forming capabilities. Of particular note from this campaign were observed influences of partially soluble organic coatings upon inorganic ammonium sulphate seeds above and below their deliquescence relative humidity (DRH). Above the DRH of the seed increasing the volume fraction of the organic component was shown to reduce the water uptake of the mixed particle. Below the DRH the organic was shown to activate the water uptake of the seed. This was the first time this effect had been observed for á-pinene derived SOA. In contrast with the simulated aerosols generated at the PSI-LAC a case study of the volatile and hygroscopic properties of diesel emissions was undertaken. During this stage of the project ternary nucleation was shown, for the first time, to be one of the processes involved in formation of diesel particulate matter. Furthermore, these particles were shown to be coated with a volatile hydrophobic material which prevented the water uptake of the highly hygroscopic material below. This result was a first and indicated that previous studies into the hygroscopicity of diesel emission had erroneously reported the particles to be hydrophobic. Both of these results contradict the previously upheld Zdanovksii-Stokes-Robinson (ZSR) additive rule for water uptake by mixed species. This is an important contribution as it adds to the weight of evidence that limits the validity of this rule.

Using ontology for the representational analysis of process modelling techniques

Selecting an appropriate business process modelling technique forms an important task within the methodological challenges of a business process management project. While a plethora of available techniques has been developed over the last decades, there is an obvious shortage of well-accepted reference frameworks that can be used to evaluate and compare the capabilities of the different techniques. Academic progress has been made at least in the area of representational analyses that use ontology as a benchmark for such evaluations. This paper reflects on the comprehensive experiences with the application of a model based on the Bunge ontology in this context. A brief overview of the underlying research model characterizes the different steps in such a research project. A comparative summary of previous representational analyses of process modelling techniques over time gives insights into the relative maturity of selected process modelling techniques. Based on these experiences suggestions are made as to where ontology-based representational analyses could be further developed and what limitations are inherent to such analyses.

Topological SLAM Using Fast Vision Techniques

In this paper we propose a method for vision only topological simultaneous localisation and mapping (SLAM). Our approach does not use motion or odometric information but a sequence of colour histograms from visited places. In particular, we address the perceptual aliasing problem which occurs using external observations only in topological navigation. We propose a Bayesian inference method to incrementally build a topological map by inferring spatial relations from the sequence of observations while simultaneously estimating the robot's location. The algorithm aims to build a small map which is consistent with local adjacency information extracted from the sequence measurements. Local adjacency information is incorporated to disambiguate places which otherwise would appear to be the same. Experiments in an indoor environment show that the proposed technique is capable of dealing with perceptual aliasing using visual observations only and successfully performs topological SLAM.

Review of strengthening techniques using externally bonded fiber reinforced polymer composites

This report reviews the selection, design, and installation of fiber reinforced polymer systems for strengthening of reinforced concrete or pre-stressed concrete bridges and other structures. The report is prepared based on the knowledge gained from worldwide experimental research, analytical work, and field applications of FRP systems used to strengthen concrete structures. Information on material properties, design and installation methods of FRP systems used as external reinforcement are presented. This information can be used to select an FRP system for increasing the strength and stiffness of reinforced concrete beams or the ductility of columns, and other applications. Based on the available research, the design considerations and concepts are covered in this report. In the next stage of the project, these will be further developed as design tools. It is important to note, however, that the design concepts proposed in literature have not in many cases been thoroughly developed and proven. Therefore, a considerable amount of research work will be required prior to development of the design concepts into practical design tools, which is a major goal of the current research project. The durability and long-term performance of FRP materials has been the subject of much research, which still are on going. Long-term field data are not currently available, and it is still difficult to accurately predict the life of FRP strengthening systems. The report briefly addresses environmental degradation and long-term durability issues as well. A general overview of using FRP bars as primary reinforcement of concrete structures is presented in Chapter 8. In Chapter 9, a summary of strengthening techniques identified as part of this initial stage of the research project and the issues which require careful consideration prior to practical implementation of these identified techniques are presented.

Preliminary report on data mining techniques for life prediction

This project is an extension of a previous CRC project (220-059-B) which developed a program for life prediction of gutters in Queensland schools. A number of sources of information on service life of metallic building components were formed into databases linked to a Case-Based Reasoning Engine which extracted relevant cases from each source. In the initial software, no attempt was made to choose between the results offered or construct a case for retention in the casebase. In this phase of the project, alternative data mining techniques will be explored and evaluated. A process for selecting a unique service life prediction for each query will also be investigated. This report summarises the initial evaluation of several data mining techniques.

Enhancing students' self-concepts and related constructs: A critical longitudinal analysis capitalising on and combining promising enhancement techniques for educational settings

Enhancing children's self-concepts is widely accepted as a critical educational outcome of schooling and is postulated as a mediating variable that facilitates the attainment of other desired outcomes such as improved academic achievement. Despite considerable advances in self-concept research, there has been limited progress in devising teacher-administered enhancement interventions. This is unfortunate as teachers are crucial change agents during important developmental periods when self-concept is formed. The primary aim of the present investigation is to build on the promising features of previous self-concept enhancement studies by: (a) combining two exciting research directions developed by Burnett and Craven to develop a potentially powerful cognitive-based intervention; (b) incorporating recent developments in theory and measurement to ensure that the multidimensionality of self-concept is accounted for in the research design; (c) fully investigating the effects of a potentially strong cognitive intervention on reading, mathematics, school and learning self-concepts by using a large sample size and a sophisticated research design; (d) evaluating the effects of the intervention on affective and cognitive subcomponents of reading, mathematics, school and learning self-concepts over time to test for differential effects of the intervention; (e) modifying and extending current procedures to maximise the successful implementation of a teacher-mediated intervention in a naturalistic setting by incorporating sophisticated teacher training as suggested by Hattie (1992) and including an assessment of the efficacy of implementation; and (f) examining the durability of effects associated with the intervention.

Listening to nature : techniques for large-scale monitoring of ecosystems using acoustics

Climate change and human activity are subjecting the environment to unprecedented rates of change. Monitoring these changes is an immense task that demands new levels of automated monitoring and analysis. We propose the use of acoustics as a proxy for the time consuming auditing of fauna, especially for determining the presence/absence of species. Acoustic monitoring is deceptively simple; seemingly all that is required is a sound recorder. However there are many major challenges if acoustics are to be used for large scale monitoring of ecosystems. Key issues are scalability and automation. This paper discusses our approach to this important research problem. Our work is being undertaken in collaboration with ecologists interested both in identifying particular species and in general ecosystem health.

Structural health monitoring of bridges using acoustic emission technology and signal processing techniques

Structural health monitoring (SHM) is the term applied to the procedure of monitoring a structure’s performance, assessing its condition and carrying out appropriate retrofitting so that it performs reliably, safely and efficiently. Bridges form an important part of a nation’s infrastructure. They deteriorate due to age and changing load patterns and hence early detection of damage helps in prolonging the lives and preventing catastrophic failures. Monitoring of bridges has been traditionally done by means of visual inspection. With recent developments in sensor technology and availability of advanced computing resources, newer techniques have emerged for SHM. Acoustic emission (AE) is one such technology that is attracting attention of engineers and researchers all around the world. This paper discusses the use of AE technology in health monitoring of bridge structures, with a special focus on analysis of recorded data. AE waves are stress waves generated by mechanical deformation of material and can be recorded by means of sensors attached to the surface of the structure. Analysis of the AE signals provides vital information regarding the nature of the source of emission. Signal processing of the AE waveform data can be carried out in several ways and is predominantly based on time and frequency domains. Short time Fourier transform and wavelet analysis have proved to be superior alternatives to traditional frequency based analysis in extracting information from recorded waveform. Some of the preliminary results of the application of these analysis tools in signal processing of recorded AE data will be presented in this paper.

Cough-generated aerosols of Pseudomonas aeruginosa and other Gram Negative Bacteria from cystic fibrosis patients.

Background: Pseudomonas aeruginosa is the most common bacterial pathogen in cystic fibrosis (CF) patients. Current infection control guidelines aim to prevent transmission via contact and respiratory droplet routes and do not consider the possibility of airborne transmission. We hypothesized that with coughing, CF subjects produce viable, respirable bacterial aerosols. Methods: Cross-sectional study of 15 children and 13 adults with CF, 26 chronically infected with P. aeruginosa. A cough aerosol sampling system enabled fractioning of respiratory particles of different size, and culture of viable Gram negative non-fermentative bacteria. We collected cough aerosols during 5 minutes voluntary coughing and during a sputum induction procedure when tolerated. Standardized quantitative culture and genotyping techniques were used. Results: P. aeruginosa was isolated in cough aerosols of 25 (89%) subjects of whom 22 produced sputum samples. P. aeruginosa from sputum and paired cough aerosols were indistinguishable by molecular typing. In 4 cases the same genotype was isolated from ambient room air. Approximately 70% of viable aerosols collected during voluntary coughing were of particles ≤ 3.3 microns aerodynamic diameter. P. aeruginosa, Burkholderia cenocepacia Stenotrophomonas maltophilia and Achromobacter xylosoxidans were cultivated from respiratory particles in this size range. Positive room air samples were associated with high total counts in cough aerosols (P=0.003). The magnitude of cough aerosols were associated with higher FEV1 (r=0.45, P=0.02) and higher quantitative sputum culture results (r=0.58, P=0.008). Conclusion: During coughing, CF patients produce viable aerosols of P. aeruginosa and other Gram negative bacteria of respirable size range, suggesting the potential for airborne transmission.

Intrusion detection techniques in wireless local area networks

This research investigates wireless intrusion detection techniques for detecting attacks on IEEE 802.11i Robust Secure Networks (RSNs). Despite using a variety of comprehensive preventative security measures, the RSNs remain vulnerable to a number of attacks. Failure of preventative measures to address all RSN vulnerabilities dictates the need for a comprehensive monitoring capability to detect all attacks on RSNs and also to proactively address potential security vulnerabilities by detecting security policy violations in the WLAN. This research proposes novel wireless intrusion detection techniques to address these monitoring requirements and also studies correlation of the generated alarms across wireless intrusion detection system (WIDS) sensors and the detection techniques themselves for greater reliability and robustness. The specific outcomes of this research are: A comprehensive review of the outstanding vulnerabilities and attacks in IEEE 802.11i RSNs. A comprehensive review of the wireless intrusion detection techniques currently available for detecting attacks on RSNs. Identification of the drawbacks and limitations of the currently available wireless intrusion detection techniques in detecting attacks on RSNs. Development of three novel wireless intrusion detection techniques for detecting RSN attacks and security policy violations in RSNs. Development of algorithms for each novel intrusion detection technique to correlate alarms across distributed sensors of a WIDS. Development of an algorithm for automatic attack scenario detection using cross detection technique correlation. Development of an algorithm to automatically assign priority to the detected attack scenario using cross detection technique correlation.

Techniques for inserting additional trains into existing timetables

In this paper techniques for scheduling additional train services (SATS) are considered as is train scheduling involving general time window constraints, fixed operations, maintenance activities and periods of section unavailability. The SATS problem is important because additional services must often be given access to the railway and subsequently integrated into current timetables. The SATS problem therefore considers the competition for railway infrastructure between new services and existing services belonging to the same or different operators. The SATS problem is characterised as a hybrid job shop scheduling problem with time window constraints. To solve this problem constructive algorithm and metaheuristic scheduling techniques that operate upon a disjunctive graph model of train operations are utilised. From numerical investigations the proposed framework and associated techniques are tested and shown to be effective.