Demonstration of Software Agents Prototype System : [AIMM] Agents for Improving Maintenance Management

This report presents the demonstration of software agents prototype system for improving maintenance management [AIMM] including: • Developing and implementing a user focused approach for mining the maintenance data of buildings. This report presents the demonstration of software agents prototype system for improving maintenance management [AIMM] including: • Developing and implementing a user focused approach for mining the maintenance data of buildings. • Refining the development of a multi agent system for data mining in virtual environments (Active Worlds) by developing and implementing a filtering agent on the results obtained from applying data mining techniques on the maintenance data. • Integrating the filtering agent within the multi agents system in an interactive networked multi-user 3D virtual environment. • Populating maintenance data and discovering new rules of knowledge.

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.

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.

A decision support system for sustainable urban development : the integrated land use and transportation indexing model

The broad definition of sustainable development at the early stage of its introduction has caused confusion and hesitation among local authorities and planning professionals. The main difficulties are experience in employing loosely-defined principles of sustainable development in setting policies and goals. The question of how this theory/rhetoric-practice gap could be filled will be the theme of this study. One of the widely employed sustainability accounting approaches by governmental organisations, triple bottom line, and applicability of this approach to sustainable urban development policies will be examined. When incorporating triple bottom line considerations with the environmental impact assessment techniques, the framework of GIS-based decision support system that helps decision-makers in selecting policy option according to the economic, environmental and social impacts will be introduced. In order to embrace sustainable urban development policy considerations, the relationship between urban form, travel pattern and socio-economic attributes should be clarified. This clarification associated with other input decision support systems will picture the holistic state of the urban settings in terms of sustainability. In this study, grid-based indexing methodology will be employed to visualise the degree of compatibility of selected scenarios with the designated sustainable urban future. In addition, this tool will provide valuable knowledge about the spatial dimension of the sustainable development. It will also give fine details about the possible impacts of urban development proposals by employing disaggregated spatial data analysis (e.g. land-use, transportation, urban services, population density, pollution, etc.). The visualisation capacity of this tool will help decision makers and other stakeholders compare and select alternative of future urban developments.

Recommending best answer in a collaborative question answering system

The World Wide Web has become a medium for people to share information. People use Web-based collaborative tools such as question answering (QA) portals, blogs/forums, email and instant messaging to acquire information and to form online-based communities. In an online QA portal, a user asks a question and other users can provide answers based on their knowledge, with the question usually being answered by many users. It can become overwhelming and/or time/resource consuming for a user to read all of the answers provided for a given question. Thus, there exists a need for a mechanism to rank the provided answers so users can focus on only reading good quality answers. The majority of online QA systems use user feedback to rank users’ answers and the user who asked the question can decide on the best answer. Other users who didn’t participate in answering the question can also vote to determine the best answer. However, ranking the best answer via this collaborative method is time consuming and requires an ongoing continuous involvement of users to provide the needed feedback. The objective of this research is to discover a way to recommend the best answer as part of a ranked list of answers for a posted question automatically, without the need for user feedback. The proposed approach combines both a non-content-based reputation method and a content-based method to solve the problem of recommending the best answer to the user who posted the question. The non-content method assigns a score to each user which reflects the users’ reputation level in using the QA portal system. Each user is assigned two types of non-content-based reputations cores: a local reputation score and a global reputation score. The local reputation score plays an important role in deciding the reputation level of a user for the category in which the question is asked. The global reputation score indicates the prestige of a user across all of the categories in the QA system. Due to the possibility of user cheating, such as awarding the best answer to a friend regardless of the answer quality, a content-based method for determining the quality of a given answer is proposed, alongside the non-content-based reputation method. Answers for a question from different users are compared with an ideal (or expert) answer using traditional Information Retrieval and Natural Language Processing techniques. Each answer provided for a question is assigned a content score according to how well it matched the ideal answer. To evaluate the performance of the proposed methods, each recommended best answer is compared with the best answer determined by one of the most popular link analysis methods, Hyperlink-Induced Topic Search (HITS). The proposed methods are able to yield high accuracy, as shown by correlation scores: Kendall correlation and Spearman correlation. The reputation method outperforms the HITS method in terms of recommending the best answer. The inclusion of the reputation score with the content score improves the overall performance, which is measured through the use of Top-n match scores.

Developing authentic achievement for disengaged young people using an electronic portfolio system

Credentials are a salient form of cultural capital and if a student’s learning and productions are not assessed, they are invisible in current social systems of education and employment. In this field, invisible equals non-existent. This paper arises from the context of an alternative education institution where conventional educational assessment techniques currently fail to recognise the creativity and skills of a cohort of marginalised young people. In order to facilitate a new assessment model an electronic portfolio system (EPS) is being developed and trialled to capture evidence of students’ learning and their productions. In so doing a dynamic system of arranging, exhibiting, exploiting and disseminating assessment data in the form of coherent, meaningful and valuable reports will be maintained. The paper investigates the notion of assessing development of creative thinking and skills through the means of a computerised system that operates in an area described as the efield. A model of the efield is delineated and is explained as a zone existing within the internet where free users exploit the cloud and cultivate social and cultural capital. Drawing largely on sociocultural theory and Bourdieu’s concepts of field, habitus and capitals, the article positions the efield as a potentially productive instrument in assessment for learning practices. An important aspect of the dynamics of this instrument is the recognition of teachers as learners. This is seen as an integral factor in the sociocultural approach to assessment for learning practices that will be deployed with the EPS. What actually takes place is argued to be assessment for learning as a field of exchange. The model produced in this research is aimed at delivering visibility and recognition through an engaging instrument that will enhance the prospects of marginalised young people and shift the paradigm for assessment in a creative world.

The efficacy of an augmented virtual reality system to alleviate pain in children undergoing burns dressing changes : a randomised controlled trial

In children, the pain and anxiety associated with acute burn dressing changes can be severe, with drug treatment alone frequently proving to be inadequate. Virtual reality (VR) systems have been successfully trialled in limited numbers of adult and paediatric burn patients. Augmented reality (AR) differs from VR in that it overlays virtual images onto the physical world, instead of creating a complete virtual world. This prospective randomised controlled trial investigated the use of AR as an adjunct to analgesia and sedation in children with acute burns. Forty-two children (30 male and 12 female), with an age range of 3–14 years (median age 9 years) and a total burn surface area ranging from 1 to 16% were randomised into a treatment (AR) arm and a control (basic cognitive therapy) arm after administration of analgesia and/or sedation. Pain scores, pulse rates (PR), respiratory rates (RR) and oxygen saturations (SaO2) were recorded pre-procedurally, at 10 min intervals and post-procedurally. Parents were also asked to grade their child's overall pain score for the dressing change. Mean pain scores were significantly lower (p = 0.0060) in the AR group compared to the control group, as were parental pain assessment scores (p = 0.015). Respiratory and pulse rates showed significant changes over time within groups, however, these were not significantly different between the two study groups. Oxygen saturation did not differ significantly over time or between the two study groups. This trial shows that augmented reality is a useful adjunct to pharmacological analgesia.

From conceptual process models to running systems: A holistic approach for the configuration of enterprise system processes

This paper proposes a method which aims at increasing the efficiency of enterprise system implementations. First, we argue that existing process modeling languages that feature different degrees of abstraction for different user groups exist and are used for different purposes which makes it necessary to integrate them. We describe how to do this using the meta models of the involved languages. Second, we argue that an integrated process model based on the integrated meta model needs to be configurable and elaborate on the enabling mechanisms. We introduce a business example using SAP modeling techniques to illustrate the proposed method.

Groundwater Visualisation System (GVS): a software framework for developing low-end, scalable and robust software for 3D visualisation and animation of groundwater conceptual models

Effective management of groundwater requires stakeholders to have a realistic conceptual understanding of the groundwater systems and hydrological processes.However, groundwater data can be complex, confusing and often difficult for people to comprehend..A powerful way to communicate understanding of groundwater processes, complex subsurface geology and their relationships is through the use of visualisation techniques to create 3D conceptual groundwater models. In addition, the ability to animate, interrogate and interact with 3D models can encourage a higher level of understanding than static images alone. While there are increasing numbers of software tools available for developing and visualising groundwater conceptual models, these packages are often very expensive and are not readily accessible to majority people due to complexity. .The Groundwater Visualisation System (GVS) is a software framework that can be used to develop groundwater visualisation tools aimed specifically at non-technical computer users and those who are not groundwater domain experts. A primary aim of GVS is to provide management support for agencies, and enhancecommunity understanding.

The encapsulation of gold nanoparticles using RAFT, ATRP and miniemulsion polymerisation techniques

The investigation into the encapsulation of gold nanoparticles (AuNPs) by poly(methyl methacrylate) (PMMA) was undertaken. This was performed by three polymerisation techniques including: grafting PMMA synthesised by reversible addition-fragmentation chain transfer (RAFT) polymerisation to AuNPs, grafting PMMA synthesised by atom transfer radical polymerisation (ATRP) from the surface of functionalised AuNPs and by encapsulation of AuNPs within PMMA latexes produced through photo-initiated oil-in-water (o/w) miniemulsion polymerisation. The grafting of RAFT PMMA to AuNPs was performed by the addition of the RAFT functionalised PMMA to citrate stabilised AuNPs. This was conducted with a range of PMMA of varying molecular weight distribution (MWD) as either the dithioester or thiol end-group functionalities. The RAFT PMMA polymers were characterised by gel permeation chromatography (GPC), ultraviolet-visible (UV-vis), Fourier transform infrared-attenuated total reflectance (FTIR-ATR), Fourier transform Raman (FT-Raman) and proton nuclear magnetic resonance (1H NMR) spectroscopies. The attachment of PMMA to AuNPs showed a tendency for AuNPs to associate with the PMMA structures formed, though significant aggregation occurred. Interestingly, thiol functionalised end-group PMMA showed very little aggregation of AuNPs. The spherical polymer-AuNP structures did not vary in size with variations in PMMA MWD. The PMMA-AuNP structures were characterised using scanning electron microscopy (SEM), transition electron microscopy (TEM), energy dispersive X-ray analysis (EDAX) and UV-vis spectroscopy. The surface confined ATRP grafting of PMMA from initiator functionalised AuNPs was polymerised in both homogeneous and heterogeneous media. 11,11’- dithiobis[1-(2-bromo-2-methylpropionyloxy)undecane] (DSBr) was used as the surface-confined initiator and was synthesised in a three step procedure from mercaptoundecanol (MUD). All compounds were characterised by 1H NMR, FTIR-ATR and Raman spectroscopies. The grafting in homogeneous media resulted in amorphous PMMA with significant AuNP aggregation. Individually grafted AuNPs were difficult to separate and characterise, though SEM, TEM, EDAX and UV-vis spectroscopy was used. The heterogeneous polymerisation did not produce grafted AuNPs as characterised by SEM and EDAX. The encapsulation of AuNPs within PMMA latexes through the process of photoinitiated miniemulsion polymerisation was successfully achieved. Initially, photoinitiated miniemulsion polymerisation was conducted as a viable low temperature method of miniemulsion initiation. This proved successful producing a stable PMMA with good conversion efficiency and narrow particle size distribution (PSD). This is the first report of such a system. The photo-initiated technique was further optimised and AuNPs were included into the miniemulsion. AuNP encapsulation was very effective, producing reproducible AuNP encapsulated PMMA latexes. Again, this is the first reported case of this. The latexes were characterised by TEM, SEM, GPC, gravimetric analysis and dynamic light scattering (DLS).

Improving automatic speaker verification using SVM techniques

Automatic recognition of people is an active field of research with important forensic and security applications. In these applications, it is not always possible for the subject to be in close proximity to the system. Voice represents a human behavioural trait which can be used to recognise people in such situations. Automatic Speaker Verification (ASV) is the process of verifying a persons identity through the analysis of their speech and enables recognition of a subject at a distance over a telephone channel { wired or wireless. A significant amount of research has focussed on the application of Gaussian mixture model (GMM) techniques to speaker verification systems providing state-of-the-art performance. GMM's are a type of generative classifier trained to model the probability distribution of the features used to represent a speaker. Recently introduced to the field of ASV research is the support vector machine (SVM). An SVM is a discriminative classifier requiring examples from both positive and negative classes to train a speaker model. The SVM is based on margin maximisation whereby a hyperplane attempts to separate classes in a high dimensional space. SVMs applied to the task of speaker verification have shown high potential, particularly when used to complement current GMM-based techniques in hybrid systems. This work aims to improve the performance of ASV systems using novel and innovative SVM-based techniques. Research was divided into three main themes: session variability compensation for SVMs; unsupervised model adaptation; and impostor dataset selection. The first theme investigated the differences between the GMM and SVM domains for the modelling of session variability | an aspect crucial for robust speaker verification. Techniques developed to improve the robustness of GMMbased classification were shown to bring about similar benefits to discriminative SVM classification through their integration in the hybrid GMM mean supervector SVM classifier. Further, the domains for the modelling of session variation were contrasted to find a number of common factors, however, the SVM-domain consistently provided marginally better session variation compensation. Minimal complementary information was found between the techniques due to the similarities in how they achieved their objectives. The second theme saw the proposal of a novel model for the purpose of session variation compensation in ASV systems. Continuous progressive model adaptation attempts to improve speaker models by retraining them after exploiting all encountered test utterances during normal use of the system. The introduction of the weight-based factor analysis model provided significant performance improvements of over 60% in an unsupervised scenario. SVM-based classification was then integrated into the progressive system providing further benefits in performance over the GMM counterpart. Analysis demonstrated that SVMs also hold several beneficial characteristics to the task of unsupervised model adaptation prompting further research in the area. In pursuing the final theme, an innovative background dataset selection technique was developed. This technique selects the most appropriate subset of examples from a large and diverse set of candidate impostor observations for use as the SVM background by exploiting the SVM training process. This selection was performed on a per-observation basis so as to overcome the shortcoming of the traditional heuristic-based approach to dataset selection. Results demonstrate the approach to provide performance improvements over both the use of the complete candidate dataset and the best heuristically-selected dataset whilst being only a fraction of the size. The refined dataset was also shown to generalise well to unseen corpora and be highly applicable to the selection of impostor cohorts required in alternate techniques for speaker verification.

UAS mission path planning system (MPPS) using hybrid-game coupled to multi-objective optimiser

This paper presents the application of advanced optimization techniques to unmanned aerial system mission path planning system (MPPS) using multi-objective evolutionary algorithms (MOEAs). Two types of multi-objective optimizers are compared; the MOEA nondominated sorting genetic algorithm II and a hybrid-game strategy are implemented to produce a set of optimal collision-free trajectories in a three-dimensional environment. The resulting trajectories on a three-dimensional terrain are collision-free and are represented by using Bézier spline curves from start position to target and then target to start position or different positions with altitude constraints. The efficiency of the two optimization methods is compared in terms of computational cost and design quality. Numerical results show the benefits of adding a hybrid-game strategy to a MOEA and for a MPPS.