Modelling word meaning using efficient tensor representations

Models of word meaning, built from a corpus of text, have demonstrated success in emulating human performance on a number of cognitive tasks. Many of these models use geometric representations of words to store semantic associations between words. Often word order information is not captured in these models. The lack of structural information used by these models has been raised as a weakness when performing cognitive tasks. This paper presents an efficient tensor based approach to modelling word meaning that builds on recent attempts to encode word order information, while providing flexible methods for extracting task specific semantic information.

The geometric modelling of social frames and contexts

How do humans respond to their social context? This question is becoming increasingly urgent in a society where democracy requires that the citizens of a country help to decide upon its policy directions, and yet those citizens frequently have very little knowledge of the complex issues that these policies seek to address. Frequently, we find that humans make their decisions more with reference to their social setting, than to the arguments of scientists, academics, and policy makers. It is broadly anticipated that the agent based modelling (ABM) of human behaviour will make it possible to treat such social effects, but we take the position here that a more sophisticated treatment of context will be required in many such models. While notions such as historical context (where the past history of an agent might affect its later actions) and situational context (where the agent will choose a different action in a different situation) abound in ABM scenarios, we will discuss a case of a potentially changing context, where social effects can have a strong influence upon the perceptions of a group of subjects. In particular, we shall discuss a recently reported case where a biased worm in an election debate led to significant distortions in the reports given by participants as to who won the debate (Davis et al 2011). Thus, participants in a different social context drew different conclusions about the perceived winner of the same debate, with associated significant differences among the two groups as to who they would vote for in the coming election. We extend this example to the problem of modelling the likely electoral responses of agents in the context of the climate change debate, and discuss the notion of interference between related questions that might be asked of an agent in a social simulation that was intended to simulate their likely responses. A modelling technology which could account for such strong social contextual effects would benefit regulatory bodies which need to navigate between multiple interests and concerns, and we shall present one viable avenue for constructing such a technology. A geometric approach will be presented, where the internal state of an agent is represented in a vector space, and their social context is naturally modelled as a set of basis states that are chosen with reference to the problem space.

Modelling and performance evaluation of the IEEE 802.11 DCF for real-time control

Popular wireless networks, such as IEEE 802.11/15/16, are not designed for real-time applications. Thus, supporting real-time quality of service (QoS) in wireless real-time control is challenging. This paper adopts the widely used IEEE 802.11, with the focus on its distributed coordination function (DCF), for soft-real-time control systems. The concept of the critical real-time traffic condition is introduced to characterize the marginal satisfaction of real-time requirements. Then, mathematical models are developed to describe the dynamics of DCF based real-time control networks with periodic traffic, a unique feature of control systems. Performance indices such as throughput and packet delay are evaluated using the developed models, particularly under the critical real-time traffic condition. Finally, the proposed modelling is applied to traffic rate control for cross-layer networked control system design.

Modelling contractor's and subcontractor's trust : a system dynamics approach

A general mistrust within the contactor and subcontractor companies has identified one of the significant barriers to derive benefits from true downstream supply chain integration. Using the general theory of trust in inter-organizational relations and conducting interviews, this research discusses factors that influence development of trust and cooperation in contractor– subcontractor relationships in construction projects. System dynamics is the simulation method is selected in this theory-building effort, based on qualitative data collected from two projects of a construction company in Thailand. Performance, permeability and system based trust are found to make significant contributions toward parties’ trust level. Three strategic policies such as best value contracting, management of subcontractors as internal team and semi project partnering approach are recommended to stimulate the trust factors as well as cooperative long term relationship.

A Popperian consilience : modelling mathematical knowledge and understanding

Goldin (2003) and McDonald, Yanchar, and Osguthorpe (2005) have called for mathematics learning theory that reconciles the chasm between ideologies, and which may advance mathematics teaching and learning practice. This paper discusses the theoretical underpinnings of a recently completed PhD study that draws upon Popper’s (1978) three-world model of knowledge as a lens through which to reconsider a variety of learning theories, including Piaget’s reflective abstraction. Based upon this consideration of theories, an alternative theoretical framework and complementary operational model was synthesised, the viability of which was demonstrated by its use to analyse the domain of early-number counting, addition and subtraction.

Development and validation of novel methods for microbial source tracking based on Escherichia coli as an indicator of water quality

Microbial pollution in water periodically affects human health in Australia, particularly in times of drought and flood. There is an increasing need for the control of waterborn microbial pathogens. Methods, allowing the determination of the origin of faecal contamination in water, are generally referred to as Microbial Source Tracking (MST). Various approaches have been evaluated as indicatorsof microbial pathogens in water samples, including detection of different microorganisms and various host-specific markers. However, until today there have been no universal MST methods that could reliably determine the source (human or animal) of faecal contamination. Therefore, the use of multiple approaches is frequently advised. MST is currently recognised as a research tool, rather than something to be included in routine practices. The main focus of this research was to develop novel and universally applicable methods to meet the demands for MST methods in routine testing of water samples. Escherichia coli was chosen initially as the object organism for our studies as, historically and globally, it is the standard indicator of microbial contamination in water. In this thesis, three approaches are described: single nucleotide polymorphism (SNP) genotyping, clustered regularly interspaced short palindromic repeats (CRISPR) screening using high resolution melt analysis (HRMA) methods and phage detection development based on CRISPR types. The advantage of the combination SNP genotyping and CRISPR genes has been discussed in this study. For the first time, a highly discriminatory single nucleotide polymorphism interrogation of E. coli population was applied to identify the host-specific cluster. Six human and one animal-specific SNP profile were revealed. SNP genotyping was successfully applied in the field investigations of the Coomera watershed, South-East Queensland, Australia. Four human profiles [11], [29], [32] and [45] and animal specific SNP profile [7] were detected in water. Two human-specific profiles [29] and [11] were found to be prevalent in the samples over a time period of years. The rainfall (24 and 72 hours), tide height and time, general land use (rural, suburban), seasons, distance from the river mouth and salinity show a lack of relashionship with the diversity of SNP profiles present in the Coomera watershed (p values > 0.05). Nevertheless, SNP genotyping method is able to identify and distinquish between human- and non-human specific E. coli isolates in water sources within one day. In some samples, only mixed profiles were detected. To further investigate host-specificity in these mixed profiles CRISPR screening protocol was developed, to be used on the set of E. coli, previously analysed for SNP profiles. CRISPR loci, which are the pattern of previous DNA coliphages attacks, were considered to be a promising tool for detecting host-specific markers in E. coli. Spacers in CRISPR loci could also reveal the dynamics of virulence in E. coli as well in other pathogens in water. Despite the fact that host-specificity was not observed in the set of E. coli analysed, CRISPR alleles were shown to be useful in detection of the geographical site of sources. HRMA allows determination of ‘different’ and ‘same’ CRISPR alleles and can be introduced in water monitoring as a cost-effective and rapid method. Overall, we show that the identified human specific SNP profiles [11], [29], [32] and [45] can be useful as marker genotypes globally for identification of human faecal contamination in water. Developed in the current study, the SNP typing approach can be used in water monitoring laboratories as an inexpensive, high-throughput and easy adapted protocol. The unique approach based on E. coli spacers for the search for unknown phage was developed to examine the host-specifity in phage sequences. Preliminary experiments on the recombinant plasmids showed the possibility of using this method for recovering phage sequences. Future studies will determine the host-specificity of DNA phage genotyping as soon as first reliable sequences can be acquired. No doubt, only implication of multiple approaches in MST will allow identification of the character of microbial contamination with higher confidence and readability.

Caregiving experience and its influencing factors : rural versus urban adult-child caregivers caring for parents with dementia in China

Background: It is predicted that China will have the largest number of cases of dementia in the world by 2025 (Ferri et al., 2005). Research has demonstrated that caring for family members with dementia can be a long-term, burdensome activity resulting in physical and emotional distress and impairment (Pinquart & Sorensen, 2003b). The establishment of family caregiver supportive services in China can be considered urgent; and the knowledge of the caregiving experience and related influencing factors is necessary to inform such services. Nevertheless, in the context of rapid demographic and socioeconomic change, the impact of caregiving for rural and urban Chinese adult-child caregivers may be different, and different needs in supportive services may therefore be expected. Objectives: The aims of this research were 1) to examine the potential differences existing in the caregiving experience between rural and urban adult-child caregivers caring for parents with dementia in China; and 2) to examine the potential differences existing in the influencing factors of the caregiving experience for rural as compared with urban adult-child caregivers caring for parents with dementia in China. Based on the literature review and Kramer.s (1997) caregiver adaptation model, six concepts and their relationships of caregiving experience were studied: severity of the care receivers. dementia, caregivers. appraisal of role strain and role gain, negative and positive well-being outcomes, and health related quality of life. Furthermore, four influencing factors (i.e., filial piety, social support, resilience, and personal mastery) were studied respectively. Methods: A cross-sectional, comparative design was used to achieve the aims of the study. A questionnaire, which was designed based on the literature review and on Kramer.s (1997) caregiver adaptation model, was completed by 401 adult-child caregivers caring for their parents with dementia from the mental health outpatient departments in five hospitals in the Yunnan province, P.R. China. Structural equation modelling (SEM) was employed as the main statistical technique for data analyses. Other statistical techniques (e.g., t-tests and Chi-Square tests) were also conducted to compare the demographic characteristics and the measured variables between rural and urban groups. Results: For the first research aim, the results indicated that urban adult-child caregivers in China experienced significantly greater strain and negative well-being outcomes than their rural peers; whereas, the difference on the appraisal of role gain and positive outcomes was nonsignificant between the two groups. The results also indicated that the amounts of severity of care receivers. dementia and caregivers. health related quality of life do not have the same meanings between the two groups. Thus, the levels of these two concepts were not comparable between the rural and urban groups in this study. Moreover, the results also demonstrated that the negative direct effect of gain on negative outcomes in urban caregivers was stronger than that in rural caregivers, suggesting that the urban caregivers tended to use appraisal of role gain to protect themselves from negative well-being outcomes to a greater extent. In addition, the unexplained variance in strain in the urban group was significantly more than that in the rural group, suggesting that there were other unmeasured variables besides the severity of care receivers. dementia which would predict strain in urban caregivers compared with their rural peers. For the second research aim, the results demonstrated that rural adult-child caregivers reported a significantly higher level of filial piety and more social support than their urban counterparts, although the two groups did not significantly differ on the levels of their resilience and personal mastery. Furthermore, although the mediation effects of these four influencing factors on both positive and negative aspects remained constant across rural and urban adult-child caregivers, urban caregivers tended to be more effective in using personal mastery to protect themselves from role strain than rural caregivers, which in turn protects them more from the negative well-being outcomes than was the case with their rural peers. Conclusions: The study extends the application of Kramer.s caregiving adaptation process model (Kramer, 1997) to a sample of adult-child caregivers in China by demonstrating that both positive and negative aspects of caregiving may impact on the caregiver.s health related quality of life, suggesting that both aspects should be targeted in supportive interventions for Chinese family caregivers. Moreover, by demonstrating partial mediation effects, the study provides four influencing factors (i.e., filial piety, social support, resilience, and personal mastery) as specific targets for clinical interventions. Furthermore, the study found evidence that urban adult-child caregivers had more negative but similar positive experience compared to their rural peers, suggesting that the establishment of supportive services for urban caregivers may be more urgent at present stage in China. Additionally, since urban caregivers tended to use appraisal of role gain and personal mastery to protect themselves from negative well-being outcomes than rural caregivers to a greater extend, interventions targeting utility of gain or/and personal mastery to decrease negative outcomes might be more effective in urban caregivers than in rural caregivers. On the other hand, as cultural expectations and expression of filial piety tend to be more traditional in rural areas, interventions targeting filial piety could be more effective among rural caregivers. Last but not least, as rural adult-child caregivers have more existing natural social support than their urban counterparts, mobilising existing natural social support resources may be more beneficial for rural caregivers, whereas, formal supports (e.g., counselling services, support groups and adult day care centres) should be enhanced for urban caregivers.

Quantification of particle emission characteristics and development of an emission model for use in transport microenvironments affected by traffic emissions

Vehicle emitted particles are of significant concern based on their potential to influence local air quality and human health. Transport microenvironments usually contain higher vehicle emission concentrations compared to other environments, and people spend a substantial amount of time in these microenvironments when commuting. Currently there is limited scientific knowledge on particle concentration, passenger exposure and the distribution of vehicle emissions in transport microenvironments, partially due to the fact that the instrumentation required to conduct such measurements is not available in many research centres. Information on passenger waiting time and location in such microenvironments has also not been investigated, which makes it difficult to evaluate a passenger’s spatial-temporal exposure to vehicle emissions. Furthermore, current emission models are incapable of rapidly predicting emission distribution, given the complexity of variations in emission rates that result from changes in driving conditions, as well as the time spent in driving condition within the transport microenvironment. In order to address these scientific gaps in knowledge, this work conducted, for the first time, a comprehensive statistical analysis of experimental data, along with multi-parameter assessment, exposure evaluation and comparison, and emission model development and application, in relation to traffic interrupted transport microenvironments. The work aimed to quantify and characterise particle emissions and human exposure in the transport microenvironments, with bus stations and a pedestrian crossing identified as suitable research locations representing a typical transport microenvironment. Firstly, two bus stations in Brisbane, Australia, with different designs, were selected to conduct measurements of particle number size distributions, particle number and PM2.5 concentrations during two different seasons. Simultaneous traffic and meteorological parameters were also monitored, aiming to quantify particle characteristics and investigate the impact of bus flow rate, station design and meteorological conditions on particle characteristics at stations. The results showed higher concentrations of PN20-30 at the station situated in an open area (open station), which is likely to be attributed to the lower average daily temperature compared to the station with a canyon structure (canyon station). During precipitation events, it was found that particle number concentration in the size range 25-250 nm decreased greatly, and that the average daily reduction in PM2.5 concentration on rainy days compared to fine days was 44.2 % and 22.6 % at the open and canyon station, respectively. The effect of ambient wind speeds on particle number concentrations was also examined, and no relationship was found between particle number concentration and wind speed for the entire measurement period. In addition, 33 pairs of average half-hourly PN7-3000 concentrations were calculated and identified at the two stations, during the same time of a day, and with the same ambient wind speeds and precipitation conditions. The results of a paired t-test showed that the average half-hourly PN7-3000 concentrations at the two stations were not significantly different at the 5% confidence level (t = 0.06, p = 0.96), which indicates that the different station designs were not a crucial factor for influencing PN7-3000 concentrations. A further assessment of passenger exposure to bus emissions on a platform was evaluated at another bus station in Brisbane, Australia. The sampling was conducted over seven weekdays to investigate spatial-temporal variations in size-fractionated particle number and PM2.5 concentrations, as well as human exposure on the platform. For the whole day, the average PN13-800 concentration was 1.3 x 104 and 1.0 x 104 particle/cm3 at the centre and end of the platform, respectively, of which PN50-100 accounted for the largest proportion to the total count. Furthermore, the contribution of exposure at the bus station to the overall daily exposure was assessed using two assumed scenarios of a school student and an office worker. It was found that, although the daily time fraction (the percentage of time spend at a location in a whole day) at the station was only 0.8 %, the daily exposure fractions (the percentage of exposures at a location accounting for the daily exposure) at the station were 2.7% and 2.8 % for exposure to PN13-800 and 2.7% and 3.5% for exposure to PM2.5 for the school student and the office worker, respectively. A new parameter, “exposure intensity” (the ratio of daily exposure fraction and the daily time fraction) was also defined and calculated at the station, with values of 3.3 and 3.4 for exposure to PN13-880, and 3.3 and 4.2 for exposure to PM2.5, for the school student and the office worker, respectively. In order to quantify the enhanced emissions at critical locations and define the emission distribution in further dispersion models for traffic interrupted transport microenvironments, a composite line source emission (CLSE) model was developed to specifically quantify exposure levels and describe the spatial variability of vehicle emissions in traffic interrupted microenvironments. This model took into account the complexity of vehicle movements in the queue, as well as different emission rates relevant to various driving conditions (cruise, decelerate, idle and accelerate), and it utilised multi-representative segments to capture the accurate emission distribution for real vehicle flow. This model does not only helped to quantify the enhanced emissions at critical locations, but it also helped to define the emission source distribution of the disrupted steady flow for further dispersion modelling. The model then was applied to estimate particle number emissions at a bidirectional bus station used by diesel and compressed natural gas fuelled buses. It was found that the acceleration distance was of critical importance when estimating particle number emission, since the highest emissions occurred in sections where most of the buses were accelerating and no significant increases were observed at locations where they idled. It was also shown that emissions at the front end of the platform were 43 times greater than at the rear of the platform. The CLSE model was also applied at a signalled pedestrian crossing, in order to assess increased particle number emissions from motor vehicles when forced to stop and accelerate from rest. The CLSE model was used to calculate the total emissions produced by a specific number and mix of light petrol cars and diesel passenger buses including 1 car travelling in 1 direction (/1 direction), 14 cars / 1 direction, 1 bus / 1 direction, 28 cars / 2 directions, 24 cars and 2 buses / 2 directions, and 20 cars and 4 buses / 2 directions. It was found that the total emissions produced during stopping on a red signal were significantly higher than when the traffic moved at a steady speed. Overall, total emissions due to the interruption of the traffic increased by a factor of 13, 11, 45, 11, 41, and 43 for the above 6 cases, respectively. In summary, this PhD thesis presents the results of a comprehensive study on particle number and mass concentration, together with particle size distribution, in a bus station transport microenvironment, influenced by bus flow rates, meteorological conditions and station design. Passenger spatial-temporal exposure to bus emitted particles was also assessed according to waiting time and location along the platform, as well as the contribution of exposure at the bus station to overall daily exposure. Due to the complexity of the interrupted traffic flow within the transport microenvironments, a unique CLSE model was also developed, which is capable of quantifying emission levels at critical locations within the transport microenvironment, for the purpose of evaluating passenger exposure and conducting simulations of vehicle emission dispersion. The application of the CLSE model at a pedestrian crossing also proved its applicability and simplicity for use in a real-world transport microenvironment.

Fat and thin adaptive HMM filters for vision based detection of moving targets

Computer vision is an attractive solution for uninhabited aerial vehicle (UAV) collision avoidance, due to the low weight, size and power requirements of hardware. A two-stage paradigm has emerged in the literature for detection and tracking of dim targets in images, comprising of spatial preprocessing, followed by temporal filtering. In this paper, we investigate a hidden Markov model (HMM) based temporal filtering approach. Specifically, we propose an adaptive HMM filter, in which the variance of model parameters is refined as the quality of the target estimate improves. Filters with high variance (fat filters) are used for target acquisition, and filters with low variance (thin filters) are used for target tracking. The adaptive filter is tested in simulation and with real data (video of a collision-course aircraft). Our test results demonstrate that our adaptive filtering approach has improved tracking performance, and provides an estimate of target heading not present in previous HMM filtering approaches.

The effectiveness of a short-term group music therapy intervention for young parents and their children

The quality of early life experiences are known to influence a child’s capacities for emotional, social, cognitive and physical competence throughout their life (Peterson, 1996; Zubrick et al., 2008). These early life experiences are directly affected by parenting and family environments. A lack of positive parenting has significant implications both for children, and the broader communities in which they live (Davies & Cummings, 1994; Dryfoos, 1990; Sanders, 1995). Young parents are known to be at risk of experiencing adverse circumstances that affect their ability to provide positive parenting to their children (Milan et al., 2004; Trad, 1995). There is a need to provide parenting support programs to young parents that offer opportunities for them to come together, support each other and learn ways to provide for their children’s developmental needs in a friendly, engaging and non-judgemental environment. This research project examines the effectiveness of a 10 week group music therapy program Sing & Grow as an early parenting intervention for 535 young parents. Sing & Grow is a national early parenting intervention program funded by the Australian Government and delivered by Playgroup Queensland. It is designed and delivered by Registered Music Therapists for families at risk of marginalisation with children aged from birth to three years. The aim of the program is to improve parenting skills and parent-child interactions, and increase social support networks through participation in a group that is strengths-based and structured in a way that lends itself to modelling, peer learning and facilitated learning. During the 10 weeks parents have opportunities to learn practical, hands-on ways to interact and play with their children that are conducive to positive parent-child relationships and ongoing child development. A range of interactive, nurturing, stimulating and developmental music activities provide the framework for parents to interact and play with their children. This research uses data collected through the Sing & Grow National Evaluation Study to examine outcomes for all participants aged 25 years and younger, who attended programs during the Sing & Grow pilot study and main study from mid-2005 to the end of 2007. The research examines the change from pre to post in self-reported parent behaviours, parent mental health and parent social support, and therapist observed parent-child interactions. A range of statistical analyses are used to address each Research Objective for the young parent population, and for subgroups within this population. Research Objective 1 explored the patterns of attendance in the Sing & Grow program for young parents, and for subgroups within this population. Results showed that levels of attendance were lower than expected and influenced by Indigenous status and source of family income. Patterns of attendance showed a decline over time and incomplete data rates were high which may indicate high dropout rates. Research Objective 2 explored perceived satisfaction, benefits and social support links made. Satisfaction levels with the program and staff were very high. Indigenous status was associated with lower levels of reported satisfaction with both the program and staff. Perceived benefits from participation in the program were very high. Employment status was associated with perceived benefits: parents who were not employed were more likely than employed parents to report that their understanding of child development had increased as a result of participation in the program. Social support connections were reported for participants with other professionals, services and parents. In particular, families were more likely to link up with playgroup staff and services. Those parents who attended six or more sessions were significantly more likely to attend a playgroup than those who attended five sessions or less. Social support connections were related to source of family income, level of education, Indigenous status and language background. Research Objective 3 investigated pre to post change on self-report parenting skills and parent mental health. Results indicated that participation in the Sing & Grow program was associated with improvements in parent mental health. No improvements were found for self-reported parenting skills. Research Objective 4 investigated pre to post change in therapist observation measures of parent-child interactions. Results indicated that participation in the Sing & Grow program was associated with large and significant improvements in parent sensitivity to, engagement with and acceptance of the child. There were significant interactions across time (pre to post) for the parent characteristics of Indigenous status, family income and level of education. Research Objective 5 explored the relationship between the number of sessions attended and extent of change on self-report outcomes and therapist observed outcomes, respectively. For each, an overall change score was devised to ascertain those parents who had made any positive changes over time. Results showed that there was no significant relationship between high attendance and positive change in either the self-report or therapist observed behavioural measures. A risk index was also constructed to test for a relationship between the risk status of the parent. Parents with the highest risk status were significantly more likely to attend six or more sessions than other parents, but risk status was not associated with any differences in parent reported outcomes or therapist observations. The results of this research study indicate that Sing & Grow is effective in improving outcomes for young parents’ mental health, parent-child interactions and social support connections. High attendance by families in the highest category for risk factors may indicate that the program is effective at engaging and retaining parents who are most at-risk and therefore traditionally hard to reach. Very high levels of satisfaction and perceived benefits support this. Further research is required to help confirm the promising evidence from the current study that a short term group music therapy program can support young parents and improve their parenting outcomes. In particular, this needs to address the more disappointing outcomes of the current research study to improve attendance and engagement of all young parents in the program and especially the needs of young Indigenous parents.

Closing the loop of design and analysis : Parametric modelling tools for early decision support

There is a growing need for parametric design software that communicates building performance feedback in early architectural exploration to support decision-making. This paper examines how the circuit of design and analysis process can be closed to provide active and concurrent feedback between architecture and services engineering domains. It presents the structure for an openly customisable design system that couples parametric modelling and energy analysis software to allow designers to assess the performance of early design iterations quickly. Finally, it discusses how user interactions with the system foster information exchanges that facilitate the sharing of design intelligence across disciplines.

Engineering-based modelling experiences in the elementary classroom

Introducing engineering-based model-eliciting experiences in the elementary curriculum is a new and increasingly important domain of research by mathematics, science, technology, and engineering educators. Recent research has raised questions about the context of engineering problems that are meaningful, engaging, and inspiring for young students. In the present study an environmental engineering activity was implemented in two classes of 11-year-old students in Cyprus. The problem required students to develop a procedure for selecting among alternative countries from which to buy water. Students created a range of models that adequately solved the problem although not all models took into account all of the data provided. The models varied in the number of problem factors taken into consideration and also in the different approaches adopted in dealing with the problem factors. At least two groups of students integrated into their models the environmental aspect of the problem (energy consumption, water pollution) and further refined their models. Results indicate that engineering model-eliciting activities can be introduced effectively into the elementary curriculum, providing rich opportunities for students to deal with engineering contexts and to apply their learning in mathematics and science to solving real-world engineering problems.

Individual user behaviour modelling for effective web recommendation

With the growth of the Web, E-commerce activities are also becoming popular. Product recommendation is an effective way of marketing a product to potential customers. Based on a user’s previous searches, most recommendation methods employ two dimensional models to find relevant items. Such items are then recommended to a user. Further too many irrelevant recommendations worsen the information overload problem for a user. This happens because such models based on vectors and matrices are unable to find the latent relationships that exist between users and searches. Identifying user behaviour is a complex process, and usually involves comparing searches made by him. In most of the cases traditional vector and matrix based methods are used to find prominent features as searched by a user. In this research we employ tensors to find relevant features as searched by users. Such relevant features are then used for making recommendations. Evaluation on real datasets show the effectiveness of such recommendations over vector and matrix based methods.

An additional step towards modelling the mechanical behaviour of sugar cane bagasse

A better understanding of the behaviour of prepared cane and bagasse, especially the ability to model the mechanical behaviour of bagasse as it is squeezed in a milling unit to extract juice, would help identify how to improve the current milling process; for example to reduce final bagasse moisture. Previous investigations have proven with certainty that juice flow through bagasse obeys Darcy’s permeability law, that the grip of the rough surface of the grooves on the bagasse can be represented by the Mohr- Coulomb failure criterion for soils, and that the internal mechanical behaviour of the bagasse can be represented by critical state behaviour similar to that of sand and clay. Current Finite Element Models (FEM) available in commercial software have adequate permeability models. However, commercial software does not contain an adequate mechanical model for bagasse. Progress has been made in the last ten years towards implementing a mechanical model for bagasse in finite element software code. This paper builds on that progress and carries out a further step towards obtaining an adequate material model. In particular, the prediction of volume change during shearing of normally consolidated final bagasse is addressed.