Trust-based automated recommendation making

Recommender systems are one of the recent inventions to deal with ever growing information overload in relation to the selection of goods and services in a global economy. Collaborative Filtering (CF) is one of the most popular techniques in recommender systems. The CF recommends items to a target user based on the preferences of a set of similar users known as the neighbours, generated from a database made up of the preferences of past users. With sufficient background information of item ratings, its performance is promising enough but research shows that it performs very poorly in a cold start situation where there is not enough previous rating data. As an alternative to ratings, trust between the users could be used to choose the neighbour for recommendation making. Better recommendations can be achieved using an inferred trust network which mimics the real world "friend of a friend" recommendations. To extend the boundaries of the neighbour, an effective trust inference technique is required. This thesis proposes a trust interference technique called Directed Series Parallel Graph (DSPG) which performs better than other popular trust inference algorithms such as TidalTrust and MoleTrust. Another problem is that reliable explicit trust data is not always available. In real life, people trust "word of mouth" recommendations made by people with similar interests. This is often assumed in the recommender system. By conducting a survey, we can confirm that interest similarity has a positive relationship with trust and this can be used to generate a trust network for recommendation. In this research, we also propose a new method called SimTrust for developing trust networks based on user's interest similarity in the absence of explicit trust data. To identify the interest similarity, we use user's personalised tagging information. However, we are interested in what resources the user chooses to tag, rather than the text of the tag applied. The commonalities of the resources being tagged by the users can be used to form the neighbours used in the automated recommender system. Our experimental results show that our proposed tag-similarity based method outperforms the traditional collaborative filtering approach which usually uses rating data.

FPGA implementation of an evolutionary algorithm for autonomous unmanned aerial vehicle on-board path planning

In this paper, a hardware-based path planning architecture for unmanned aerial vehicle (UAV) adaptation is proposed. The architecture aims to provide UAVs with higher autonomy using an application specific evolutionary algorithm (EA) implemented entirely on a field programmable gate array (FPGA) chip. The physical attributes of an FPGA chip, being compact in size and low in power consumption, compliments it to be an ideal platform for UAV applications. The design, which is implemented entirely in hardware, consists of EA modules, population storage resources, and three-dimensional terrain information necessary to the path planning process, subject to constraints accounted for separately via UAV, environment and mission profiles. The architecture has been successfully synthesised for a target Xilinx Virtex-4 FPGA platform with 32% logic slices utilisation. Results obtained from case studies for a small UAV helicopter with environment derived from LIDAR (Light Detection and Ranging) data verify the effectiveness of the proposed FPGA-based path planner, and demonstrate convergence at rates above the typical 10 Hz update frequency of an autopilot system.

Neoproterozoic glacial deposits of the Kimberly Region and northwestern Northern Territory, Australia

Neoproterozoic glacigenic formations are preserved in the Kimberley region and northwestern Northern Territory of northern Australia. They are distributed in the west Kimberley adjacent to the northern margins of the King Leopold Orogen, the Mt Ramsay area at the junction of the King Leopold and Halls Creek Orogens, and the east Kimberley, adjacent to the eastern margin of the Halls Creek Orogen. Small outlier glacigenic deposits are preserved in the Litchfield Province, Northern Territory (Uniya Formation) and Georgina Basin, western Queensland (Little Burke Formation). Glacigenic strata comprise diamictite, conglomerate, sandstone and pebbly mudstone and characterize the Walsh, Landrigan and Fargoo/Moonlight Valley formations. Thin units of laminated dolomite sit conformably at the top of the Walsh, Landrigan and Moonlight Valley formations. Glacigenic units are also interbedded with the carbonate platform deposits of the Egan Formation and Boonall Dolomite. δ13C data are available for all carbonate units. There is no direct chronological constraint on these successions. Dispute over regional correlation of the Neoproterozoic succession has been largely resolved through biostratigraphic, chemostratigraphic and lithostratigraphic analysis. However, palaeomagnetic results from the Walsh Formation are inconsistent with sedimentologically based correlations. Two stratigraphically defined glaciations are preserved in northwestern Australia: the ‘Landrigan Glaciation’, characterized by southwest-directed continental ice-sheet movement and correlated with late Cryogenian glaciation elsewhere in Australia and the world; and, the ‘Egan Glaciation’, a more localized glaciation of the Ediacaran Period. Future research focus should include chronology, palaeomagnetic constraint and tectonostratigraphic controls on deposition.

Trust, reputation and the small firm : building online brand reputation for SMEs

Social media provides numerous opportunities for small businesses to promote their products and services, build brand communities and reach diverse market niches. An important factor in seizing these opportunities is developing trust and creating reputation among consumers. This qualitative study examines how a group of Australian small business managers utilize social media websites to connect to, communicate with and maintain their customer base. For the purpose of this paper we are using case studies of four companies physically based in Victoria, Australia. These businesses have a high presence in online consumer groups, being both active members of communities and representatives of their businesses. The duality of their role as participant and company representative imposes difficulties in creating reputation among community members. We have used in-depth interviews as a primary research method, additionally monitoring their activities on social media sites such as forums, social networking services, blogs and micro-blogs. We have identified practices helpful for developing trust, building reputation and create a brand image in online communities.

Optimal coordination of overcurrent relays in distribution systems with distributed generators based on differential evolution algorithm

Distributed generators (DGs) are defined as generators that are connected to a distribution network. The direction of the power flow and short-circuit current in a network could be changed compared with one without DGs. The conventional protective relay scheme does not meet the requirement in this emerging situation. As the number and capacity of DGs in the distribution network increase, the problem of coordinating protective relays becomes more challenging. Given this background, the protective relay coordination problem in distribution systems is investigated, with directional overcurrent relays taken as an example, and formulated as a mixed integer nonlinear programming problem. A mathematical model describing this problem is first developed, and the well-developed differential evolution algorithm is then used to solve it. Finally, a sample system is used to demonstrate the feasiblity and efficiency of the developed method.

A mask-based approach for the geometric calibration of thermal-infrared cameras

Accurate and efficient thermal-infrared (IR) camera calibration is important for advancing computer vision research within the thermal modality. This paper presents an approach for geometrically calibrating individual and multiple cameras in both the thermal and visible modalities. The proposed technique can be used to correct for lens distortion and to simultaneously reference both visible and thermal-IR cameras to a single coordinate frame. The most popular existing approach for the geometric calibration of thermal cameras uses a printed chessboard heated by a flood lamp and is comparatively inaccurate and difficult to execute. Additionally, software toolkits provided for calibration either are unsuitable for this task or require substantial manual intervention. A new geometric mask with high thermal contrast and not requiring a flood lamp is presented as an alternative calibration pattern. Calibration points on the pattern are then accurately located using a clustering-based algorithm which utilizes the maximally stable extremal region detector. This algorithm is integrated into an automatic end-to-end system for calibrating single or multiple cameras. The evaluation shows that using the proposed mask achieves a mean reprojection error up to 78% lower than that using a heated chessboard. The effectiveness of the approach is further demonstrated by using it to calibrate two multiple-camera multiple-modality setups. Source code and binaries for the developed software are provided on the project Web site.

A sequential Monte Carlo algorithm to incorporate model uncertainty in Bayesian sequential design

Here we present a sequential Monte Carlo (SMC) algorithm that can be used for any one-at-a-time Bayesian sequential design problem in the presence of model uncertainty where discrete data are encountered. Our focus is on adaptive design for model discrimination but the methodology is applicable if one has a different design objective such as parameter estimation or prediction. An SMC algorithm is run in parallel for each model and the algorithm relies on a convenient estimator of the evidence of each model which is essentially a function of importance sampling weights. Other methods for this task such as quadrature, often used in design, suffer from the curse of dimensionality. Approximating posterior model probabilities in this way allows us to use model discrimination utility functions derived from information theory that were previously difficult to compute except for conjugate models. A major benefit of the algorithm is that it requires very little problem specific tuning. We demonstrate the methodology on three applications, including discriminating between models for decline in motor neuron numbers in patients suffering from neurological diseases such as Motor Neuron disease.

Adaptive bilateral filtering using saliency map for deblocking low bit rate videos

This paper proposes a novel approach to video deblocking which performs perceptually adaptive bilateral filtering by considering color, intensity, and motion features in a holistic manner. The method is based on bilateral filter which is an effective smoothing filter that preserves edges. The bilateral filter parameters are adaptive and avoid over-blurring of texture regions and at the same time eliminate blocking artefacts in the smooth region and areas of slow motion content. This is achieved by using a saliency map to control the strength of the filter for each individual point in the image based on its perceptual importance. The experimental results demonstrate that the proposed algorithm is effective in deblocking highly compressed video sequences and to avoid over-blurring of edges and textures in salient regions of image.

Limestone and speleothem trace element geochemistry as tools for palaeoclimatic reconstruction, Mount Etna region, central-coastal Queensland

This study investigated potential palaeoclimate proxies provided by rare earth element (REE) geochemistry in speleothems and in clay mineralogy of cave sediments. Speleothem and sediment samples were collected from a series of cave fill deposits that occurred with rich vertebrate fossil assemblages in and around Mount Etna National Park, Rockhampton (central coastal Queensland). The fossil deposits range from Plio- Pleistocene to Holocene in age (based on uranium/thorium dating) and appear to represent depositional environments ranging from enclosed rainforest to semi-arid grasslands. Therefore, the Mount Etna cave deposits offer the perfect opportunity to test new palaeoclimate tools as they include deposits that span a known significant climate shift on the basis of independent faunal data. The first section of this study investigates the REE distribution of the host limestone to provide baseline geochemistry for subsequent speleothem investigations. The Devonian Mount Etna Beds were found to be more complex than previous literature had documented. The studied limestone massif is overturned, highly recrystallised in parts and consists of numerous allochthonous blocks with different spatial orientations. Despite the complex geologic history of the Mount Etna Beds, Devonian seawater-like REE patterns were recovered in some parts of the limestone and baseline geochemistry was determined for the bulk limestone for comparison with speleothem REE patterns. The second part of the study focused on REE distribution in the karst system and the palaeoclimatic implications of such records. It was found that REEs have a high affinity for calcite surfaces and that REE distributions in speleothems vary between growth bands much more than along growth bands, thus providing a temporal record that may relate to environmental changes. The morphology of different speleothems (i.e., stalactites, stalagmites, and flowstones) has little bearing on REE distributions provided they are not contaminated with particulate fines. Thus, baseline knowledge developed in the study suggested that speleothems were basically comparable for assessing palaeoclimatically controlled variations in REE distributions. Speleothems from rainforest and semi-arid phases were compared and it was found that there are definable differences in REE distribution that can be attributed to climate. In particular during semiarid phases, total REE concentration decreased, LREE became more depleted, Y/Ho increased, La anomalies were more positive and Ce anomalies were more negative. This may reflect more soil development during rainforest phases and more organic particles and colloids, which are known to transport REEs, in karst waters. However, on a finer temporal scale (i.e. growth bands) within speleothems from the same climate regime, no difference was seen. It is suggested that this may be due to inadequate time for soil development changes on the time frames represented by differences in growth band density. The third part of the study was a reconnaissance investigation focused on mineralogy of clay cave sediments, illite/kaolinite ratios in particular, and the potential palaeoclimatic implications of such records. Although the sample distribution was not optimal, the preliminary results suggest that the illite/kaolinite ratio increased during cold and dry intervals, consistent with decreased chemical weathering during those times. The study provides a basic framework for future studies at differing latitudes to further constrain the parameters of the proxy. The identification of such a proxy recorded in cave sediment has broad implications as clay ratios could potentially provide a basic local climate proxy in the absence of fossil faunas and speleothem material. This study suggests that REEs distributed in speleothems may provide information about water throughput and soil formation, thus providing a potential palaeoclimate proxy. It highlights the importance of understanding the host limestone geochemistry and broadens the distribution and potential number of cave field sites as palaeoclimate information no longer relies solely on the presence of fossil faunas and or speleothems. However, additional research is required to better understand the temporal scales required for the proxies to be recognised.

Improving trust and securing data accessibility for e-health decision making by using data encryption techniques

In the medical and healthcare arena, patients‟ data is not just their own personal history but also a valuable large dataset for finding solutions for diseases. While electronic medical records are becoming popular and are used in healthcare work places like hospitals, as well as insurance companies, and by major stakeholders such as physicians and their patients, the accessibility of such information should be dealt with in a way that preserves privacy and security. Thus, finding the best way to keep the data secure has become an important issue in the area of database security. Sensitive medical data should be encrypted in databases. There are many encryption/ decryption techniques and algorithms with regard to preserving privacy and security. Currently their performance is an important factor while the medical data is being managed in databases. Another important factor is that the stakeholders should decide more cost-effective ways to reduce the total cost of ownership. As an alternative, DAS (Data as Service) is a popular outsourcing model to satisfy the cost-effectiveness but it takes a consideration that the encryption/ decryption modules needs to be handled by trustworthy stakeholders. This research project is focusing on the query response times in a DAS model (AES-DAS) and analyses the comparison between the outsourcing model and the in-house model which incorporates Microsoft built-in encryption scheme in a SQL Server. This research project includes building a prototype of medical database schemas. There are 2 types of simulations to carry out the project. The first stage includes 6 databases in order to carry out simulations to measure the performance between plain-text, Microsoft built-in encryption and AES-DAS (Data as Service). Particularly, the AES-DAS incorporates implementations of symmetric key encryption such as AES (Advanced Encryption Standard) and a Bucket indexing processor using Bloom filter. The results are categorised such as character type, numeric type, range queries, range queries using Bucket Index and aggregate queries. The second stage takes the scalability test from 5K to 2560K records. The main result of these simulations is that particularly as an outsourcing model, AES-DAS using the Bucket index shows around 3.32 times faster than a normal AES-DAS under the 70 partitions and 10K record-sized databases. Retrieving Numeric typed data takes shorter time than Character typed data in AES-DAS. The aggregation query response time in AES-DAS is not as consistent as that in MS built-in encryption scheme. The scalability test shows that the DBMS reaches in a certain threshold; the query response time becomes rapidly slower. However, there is more to investigate in order to bring about other outcomes and to construct a secured EMR (Electronic Medical Record) more efficiently from these simulations.

A 2-h diagnostic protocol to assess patients with chest pain symptoms in the Asia-Pacific region (ASPECT): a prospective observational validation study

Background: Patients with chest pain contribute substantially to emergency department attendances, lengthy hospital stay, and inpatient admissions. A reliable, reproducible, and fast process to identify patients presenting with chest pain who have a low short-term risk of a major adverse cardiac event is needed to facilitate early discharge. We aimed to prospectively validate the safety of a predefined 2-h accelerated diagnostic protocol (ADP) to assess patients presenting to the emergency department with chest pain symptoms suggestive of acute coronary syndrome. Methods: This observational study was undertaken in 14 emergency departments in nine countries in the Asia-Pacific region, in patients aged 18 years and older with at least 5 min of chest pain. The ADP included use of a structured pre-test probability scoring method (Thrombolysis in Myocardial Infarction [TIMI] score), electrocardiograph, and point-of-care biomarker panel of troponin, creatine kinase MB, and myoglobin. The primary endpoint was major adverse cardiac events within 30 days after initial presentation (including initial hospital attendance). This trial is registered with the Australia-New Zealand Clinical Trials Registry, number ACTRN12609000283279. Findings: 3582 consecutive patients were recruited and completed 30-day follow-up. 421 (11•8%) patients had a major adverse cardiac event. The ADP classified 352 (9•8%) patients as low risk and potentially suitable for early discharge. A major adverse cardiac event occurred in three (0•9%) of these patients, giving the ADP a sensitivity of 99•3% (95% CI 97•9–99•8), a negative predictive value of 99•1% (97•3–99•8), and a specificity of 11•0% (10•0–12•2). Interpretation: This novel ADP identifies patients at very low risk of a short-term major adverse cardiac event who might be suitable for early discharge. Such an approach could be used to decrease the overall observation periods and admissions for chest pain. The components needed for the implementation of this strategy are widely available. The ADP has the potential to affect health-service delivery worldwide.

The role of organisational culture, trust and mechanisms in inter-project knowledge sharing

Knowledge has been recognised as a powerful yet intangible asset, which is difficult to manage. This is especially true in a project environment where there is the potential to repeat mistakes, rather than learn from previous experiences. The literature in the project management field has recognised the importance of knowledge sharing (KS) within and between projects. However, studies in that field focus primarily on KS mechanisms including lessons learned (LL) and post project reviews as the source of knowledge for future projects, and only some preliminary research has been carried out on the aspects of project management offices (PMOs) and organisational culture (OC) in KS. This study undertook to investigate KS behaviours in an inter-project context, with a particular emphasis on the role of trust, OC and a range of knowledge sharing mechanisms (KSM) in achieving successful inter-project knowledge sharing (I-PKS). An extensive literature search resulted in the development of an I-PKS Framework, which defined the scope of the research and shaped its initial design. The literature review indicated that existing research relating to the three factors of OC, trust and KSM remains inadequate in its ability to fully explain the role of these contextual factors. In particular, the literature review identified these areas of interest: (1) the conflicting answers to some of the major questions related to KSM, (2) the limited empirical research on the role of different trust dimensions, (3) limited empirical evidence of the role of OC in KS, and (4) the insufficient research on KS in an inter-project context. The resulting Framework comprised the three main factors including: OC, trust and KSM, demonstrating a more integrated view of KS in the inter-project context. Accordingly, the aim of this research was to examine the relationships between these three factors and KS by investigating behaviours related to KS from the project managers‘ (PMs‘) perspective. In order to achieve the aim, this research sought to answer the following research questions: 1. How does organisational culture influence inter-project knowledge sharing? 2. How does the existence of three forms of trust — (i) ability, (ii) benevolence and (iii) integrity — influence inter-project knowledge sharing? 3. How can different knowledge sharing mechanisms (relational, project management tools and process, and technology) improve inter-project knowledge sharing behaviours? 4. How do the relationships between these three factors of organisational culture, trust and knowledge sharing mechanisms improve inter-project knowledge sharing? a. What are the relationships between the factors? b. What is the best fit for given cases to ensure more effective inter-project knowledge sharing? Using multiple case studies, this research was designed to build propositions emerging from cross-case data analysis. The four cases were chosen on the basis of theoretical sampling. All cases were large project-based organisations (PBOs), with a strong matrix-type structure, as per the typology proposed by the Project Management Body of Knowledge (PMBoK) (2008). Data were collected from project management departments of the respective organisations. A range of analytical techniques were used to deal with the data including pattern matching logic and explanation building analysis, complemented by the use of NVivo for data coding and management. Propositions generated at the end of the analyses were further compared with the extant literature, and practical implications based on the data and literature were suggested in order to improve I-PKS. Findings from this research conclude that OC, trust, and KSM contribute to inter-project knowledge sharing, and suggest the existence of relationships between these factors. In view of that, this research identified the relationships between different trust dimensions, suggesting that integrity trust reinforces the relationship between ability trust and knowledge sharing. Furthermore, this research demonstrated that characteristics of culture and trust interact to reinforce preferences for mechanisms of knowledge sharing. This means that cultures that facilitate characteristics of Clan type are more likely to result in trusting relationships, hence are more likely to use organic sources of knowledge for both tacit and explicit knowledge exchange. In contrast, cultures that are empirically driven, based on control, efficiency, and measures (characteristics of Hierarchy and Market types) display tendency to develop trust primarily in ability of non-organic sources, and therefore use these sources to share mainly explicit knowledge. This thesis contributes to the project management literature by providing a more integrative view of I-PKS, bringing the factors of OC, trust and KSM into the picture. A further contribution is related to the use of collaborative tools as a substitute for static LL databases and as a facilitator for tacit KS between geographically dispersed projects. This research adds to the literature on OC by providing rich empirical evidence of the relationships between OC and the willingness to share knowledge, and by providing empirical evidence that OC has an effect on trust; in doing so this research extends the theoretical propositions outlined by previous research. This study also extends the research on trust by identifying the relationships between different trust dimensions, suggesting that integrity trust reinforces the relationship between ability trust and KS. Finally, this research provides some directions for future studies.

Anisotropy of articular cartilage reflects the ECM gradient architecture : Hough-Radon Transform Analysis

Tissue-specific extracellular matrix (ECM) is known to be an ideal bioscaffold to inspire the future of regenerative medicine. It holds the secret of how nature has developed such an organization of molecules into a unique functional complexity. This work exploited an innovative image processing algorithm and high resolution microscopy associated with mechanical analysis to establish a correlation between the gradient organization of cartiligous ECM and its anisotropic biomechanical response. This was hypothesized to be a reliable determinant that can elucidate how microarchitecture interrelates with biomechanical properties. Hough-Radon transform of the ECM cross-section images revealed its conformational variation from tangential interface down to subchondral region. As the orientation varied layer by layer, the anisotropic mechanical response deviated relatively. Although, results were in good agreement (Kendall's tau-b > 90%), there were evidences proposing that alignment of the fibrous network, specifically in middle zone, is not as random as it was previously thought.

A boundary preserving numerical algorithm for the Wright-Fisher model with mutation

The Wright-Fisher model is an Itô stochastic differential equation that was originally introduced to model genetic drift within finite populations and has recently been used as an approximation to ion channel dynamics within cardiac and neuronal cells. While analytic solutions to this equation remain within the interval [0,1], current numerical methods are unable to preserve such boundaries in the approximation. We present a new numerical method that guarantees approximations to a form of Wright-Fisher model, which includes mutation, remain within [0,1] for all time with probability one. Strong convergence of the method is proved and numerical experiments suggest that this new scheme converges with strong order 1/2. Extending this method to a multidimensional case, numerical tests suggest that the algorithm still converges strongly with order 1/2. Finally, numerical solutions obtained using this new method are compared to those obtained using the Euler-Maruyama method where the Wiener increment is resampled to ensure solutions remain within [0,1].

Clustering composite SaaS components in cloud computing using a grouping genetic algorithm

Recently, Software as a Service (SaaS) in Cloud computing, has become more and more significant among software users and providers. To offer a SaaS with flexible functions at a low cost, SaaS providers have focused on the decomposition of the SaaS functionalities, or known as composite SaaS. This approach has introduced new challenges in SaaS resource management in data centres. One of the challenges is managing the resources allocated to the composite SaaS. Due to the dynamic environment of a Cloud data centre, resources that have been initially allocated to SaaS components may be overloaded or wasted. As such, reconfiguration for the components’ placement is triggered to maintain the performance of the composite SaaS. However, existing approaches often ignore the communication or dependencies between SaaS components in their implementation. In a composite SaaS, it is important to include these elements, as they will directly affect the performance of the SaaS. This paper will propose a Grouping Genetic Algorithm (GGA) for multiple composite SaaS application component clustering in Cloud computing that will address this gap. To the best of our knowledge, this is the first attempt to handle multiple composite SaaS reconfiguration placement in a dynamic Cloud environment. The experimental results demonstrate the feasibility and the scalability of the GGA.