572 resultados para multiple objective programming


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Scientists need to transfer semantically similar queries across multiple heterogeneous linked datasets. These queries may require data from different locations and the results are not simple to combine due to differences between datasets. A query model was developed to make it simple to distribute queries across different datasets using RDF as the result format. The query model, based on the concept of publicly recognised namespaces for parts of each scientific dataset, was implemented with a configuration that includes a large number of current biological and chemical datasets. The configuration is flexible, providing the ability to transparently use both private and public datasets in any query. A prototype implementation of the model was used to resolve queries for the Bio2RDF website, including both Bio2RDF datasets and other datasets that do not follow the Bio2RDF URI conventions.

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Background A number of studies have found associations between dysbindin (DTNBP1) polymorphisms and schizophrenia. Recently we identified a DTNBP1 SNP (rs9370822) that is strongly associated with schizophrenia. Individuals diagnosed with schizophrenia were nearly three times as likely to carry the CC genotype compared to the AA genotype. Methods To investigate the importance of this SNP in the function of DTNBP1, a number of psychiatric conditions including addictive behaviours and anxiety disorders were analysed for association with rs9370822. Results The DTNBP1 polymorphism was significantly associated with post-traumatic stress disorder (PTSD) as well as nicotine and opiate dependence but not alcohol dependence. Individuals suffering PTSD were more than three times as likely to carry the CC genotype compared to the AA genotype. Individuals with nicotine or opiate dependence were more than twice as likely to carry the CC genotype compared to the AA genotype. Conclusions This study provides further support for the importance of DTNBP1 in psychiatric conditions and suggests that there is a common underlying molecular defect involving DTNBP1 that contributes to the development of several anxiety and addictive disorders that are generally recognised as separate clinical conditions. These disorders may actually be different expressions of a single metabolic pathway perturbation. As our participant numbers are limited our observations should be viewed with caution until they are independently replicated.

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Automobiles have deeply impacted the way in which we travel but they have also contributed to many deaths and injury due to crashes. A number of reasons for these crashes have been pointed out by researchers. Inexperience has been identified as a contributing factor to road crashes. Driver’s driving abilities also play a vital role in judging the road environment and reacting in-time to avoid any possible collision. Therefore driver’s perceptual and motor skills remain the key factors impacting on road safety. Our failure to understand what is really important for learners, in terms of competent driving, is one of the many challenges for building better training programs. Driver training is one of the interventions aimed at decreasing the number of crashes that involve young drivers. Currently, there is a need to develop comprehensive driver evaluation system that benefits from the advances in Driver Assistance Systems. A multidisciplinary approach is necessary to explain how driving abilities evolves with on-road driving experience. To our knowledge, driver assistance systems have never been comprehensively used in a driver training context to assess the safety aspect of driving. The aim and novelty of this thesis is to develop and evaluate an Intelligent Driver Training System (IDTS) as an automated assessment tool that will help drivers and their trainers to comprehensively view complex driving manoeuvres and potentially provide effective feedback by post processing the data recorded during driving. This system is designed to help driver trainers to accurately evaluate driver performance and has the potential to provide valuable feedback to the drivers. Since driving is dependent on fuzzy inputs from the driver (i.e. approximate distance calculation from the other vehicles, approximate assumption of the other vehicle speed), it is necessary that the evaluation system is based on criteria and rules that handles uncertain and fuzzy characteristics of the driving tasks. Therefore, the proposed IDTS utilizes fuzzy set theory for the assessment of driver performance. The proposed research program focuses on integrating the multi-sensory information acquired from the vehicle, driver and environment to assess driving competencies. After information acquisition, the current research focuses on automated segmentation of the selected manoeuvres from the driving scenario. This leads to the creation of a model that determines a “competency” criterion through the driving performance protocol used by driver trainers (i.e. expert knowledge) to assess drivers. This is achieved by comprehensively evaluating and assessing the data stream acquired from multiple in-vehicle sensors using fuzzy rules and classifying the driving manoeuvres (i.e. overtake, lane change, T-crossing and turn) between low and high competency. The fuzzy rules use parameters such as following distance, gaze depth and scan area, distance with respect to lanes and excessive acceleration or braking during the manoeuvres to assess competency. These rules that identify driving competency were initially designed with the help of expert’s knowledge (i.e. driver trainers). In-order to fine tune these rules and the parameters that define these rules, a driving experiment was conducted to identify the empirical differences between novice and experienced drivers. The results from the driving experiment indicated that significant differences existed between novice and experienced driver, in terms of their gaze pattern and duration, speed, stop time at the T-crossing, lane keeping and the time spent in lanes while performing the selected manoeuvres. These differences were used to refine the fuzzy membership functions and rules that govern the assessments of the driving tasks. Next, this research focused on providing an integrated visual assessment interface to both driver trainers and their trainees. By providing a rich set of interactive graphical interfaces, displaying information about the driving tasks, Intelligent Driver Training System (IDTS) visualisation module has the potential to give empirical feedback to its users. Lastly, the validation of the IDTS system’s assessment was conducted by comparing IDTS objective assessments, for the driving experiment, with the subjective assessments of the driver trainers for particular manoeuvres. Results show that not only IDTS was able to match the subjective assessments made by driver trainers during the driving experiment but also identified some additional driving manoeuvres performed in low competency that were not identified by the driver trainers due to increased mental workload of trainers when assessing multiple variables that constitute driving. The validation of IDTS emphasized the need for an automated assessment tool that can segment the manoeuvres from the driving scenario, further investigate the variables within that manoeuvre to determine the manoeuvre’s competency and provide integrated visualisation regarding the manoeuvre to its users (i.e. trainers and trainees). Through analysis and validation it was shown that IDTS is a useful assistance tool for driver trainers to empirically assess and potentially provide feedback regarding the manoeuvres undertaken by the drivers.

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Reliable infrastructure assets impact significantly on quality of life and provide a stable foundation for economic growth and competitiveness. Decisions about the way assets are managed are of utmost importance in achieving this. Timely renewal of infrastructure assets supports reliability and maximum utilisation of infrastructure and enables business and community to grow and prosper. This research initially examined a framework for asset management decisions and then focused on asset renewal optimisation and renewal engineering optimisation in depth. This study had four primary objectives. The first was to develop a new Asset Management Decision Framework (AMDF) for identifying and classifying asset management decisions. The AMDF was developed by applying multi-criteria decision theory, classical management theory and life cycle management. The AMDF is an original and innovative contribution to asset management in that: · it is the first framework to provide guidance for developing asset management decision criteria based on fundamental business objectives; · it is the first framework to provide a decision context identification and analysis process for asset management decisions; and · it is the only comprehensive listing of asset management decision types developed from first principles. The second objective of this research was to develop a novel multi-attribute Asset Renewal Decision Model (ARDM) that takes account of financial, customer service, health and safety, environmental and socio-economic objectives. The unique feature of this ARDM is that it is the only model to optimise timing of asset renewal with respect to fundamental business objectives. The third objective of this research was to develop a novel Renewal Engineering Decision Model (REDM) that uses multiple criteria to determine the optimal timing for renewal engineering. The unique features of this model are that: · it is a novel extension to existing real options valuation models in that it uses overall utility rather than present value of cash flows to model engineering value; and · it is the only REDM that optimises timing of renewal engineering with respect to fundamental business objectives; The final objective was to develop and validate an Asset Renewal Engineering Philosophy (AREP) consisting of three principles of asset renewal engineering. The principles were validated using a novel application of real options theory. The AREP is the only renewal engineering philosophy in existence. The original contributions of this research are expected to enrich the body of knowledge in asset management through effectively addressing the need for an asset management decision framework, asset renewal and renewal engineering optimisation based on fundamental business objectives and a novel renewal engineering philosophy.

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Ureaplasma species are the bacteria most frequently isolated from human amniotic fluid in asymptomatic pregnancies and placental infections. Ureaplasma parvum serovars 3 and 6 are the most prevalent serovars isolated from men and women. We hypothesized that the effects on the fetus and chorioamnion of chronic ureaplasma infection in amniotic fluid are dependent on the serovar, dose, and variation of the ureaplasma multiple banded antigen (MBA) and mba gene. We injected high- or low dose U. parvum serovar 3, serovar 6, or vehicle intra-amniotically into pregnant ewes at 55 days of gestation (term = 150 days) and examined the chorioamnion, amniotic fluid, and fetal lung tissue of animals delivered by cesarean section at 125 days of gestation. Variation of the multiple banded antigen/mba generated by serovar 3 and serovar 6 ureaplasmas in vivo were compared by PCR assay and Western blot. Ureaplasma inoculums demonstrated only one (serovar 3) or two (serovar 6) MBA variants in vitro, but numerous antigenic variants were generated in vivo: serovar 6 passage 1 amniotic fluid cultures contained more MBA size variants than serovar 3 (P = 0.005),and ureaplasma titers were inversely related to the number of variants (P = 0.025). The severity of chorioamnionitis varied between animals. Low numbers of mba size variants (five or fewer) within amniotic fluid were associated with severe inflammation, whereas the chorioamnion from animals with nine or more mba variants showed little or no inflammation. These differences in chorioamnion inflammation may explain why not all women with in utero Ureaplasma spp. experience adverse pregnancy outcomes.

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Complex surveillance problems are common in biosecurity, such as prioritizing detection among multiple invasive species, specifying risk over a heterogeneous landscape, combining multiple sources of surveillance data, designing for specified power to detect, resource management, and collateral effects on the environment. Moreover, when designing for multiple target species, inherent biological differences among species result in different ecological models underpinning the individual surveillance systems for each. Species are likely to have different habitat requirements, different introduction mechanisms and locations, require different methods of detection, have different levels of detectability, and vary in rates of movement and spread. Often there is a further challenge of a lack of knowledge, literature, or data, for any number of the above problems. Even so, governments and industry need to proceed with surveillance programs which aim to detect incursions in order to meet environmental, social and political requirements. We present an approach taken to meet these challenges in one comprehensive and statistically powerful surveillance design for non-indigenous terrestrial vertebrates on Barrow Island, a high conservation nature reserve off the Western Australian coast. Here, the possibility of incursions is increased due to construction and expanding industry on the island. The design, which includes mammals, amphibians and reptiles, provides a complete surveillance program for most potential terrestrial vertebrate invaders. Individual surveillance systems were developed for various potential invaders, and then integrated into an overall surveillance system which meets the above challenges using a statistical model and expert elicitation. We discuss the ecological basis for the design, the flexibility of the surveillance scheme, how it meets the above challenges, design limitations, and how it can be updated as data are collected as a basis for adaptive management.

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Tangible programming elements offer the dynamic and programmable properties of a computer without the complexity introduced by the keyboard, mouse and screen. This paper explores the extent to which programming skills are used by children during interactions with a set of tangible programming elements: the Electronic Blocks. An evaluation of the Electronic Blocks indicates that children become heavily engaged with the blocks, and learn simple programming with a minimum of adult support.

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Introduction. Surgical treatment of scoliosis is assessed in the spine clinic by the surgeon making numerous measurements on X-Rays as well as the rib hump. But it is important to understand which of these measures correlate with self-reported improvements in patients’ quality of life following surgery. The objective of this study was to examine the relationship between patient satisfaction after thoracoscopic (keyhole) anterior scoliosis surgery and standard deformity correction measures using the Scoliosis Research Society (SRS) adolescent questionnaire. Methods. A series of 100 consecutive adolescent idiopathic scoliosis patients received a single anterior rod via a keyhole approach at the Mater Children’s Hospital, Brisbane. Patients completed SRS outcomes questionnaires before surgery and again at 24 months after surgery. Multiple regression and t-tests were used to investigate the relationship between SRS scores and deformity correction achieved after surgery. Results. There were 94 females and 6 males with a mean age of 16.1 years. The mean Cobb angle improved from 52º pre-operatively to 21º for the instrumented levels post-operatively (59% correction) and the mean rib hump improved from 16º to 8º (51% correction). The mean total SRS score for the cohort was 99.4/120 which indicated a high level of satisfaction with the results of their scoliosis surgery. None of the deformity related parameters in the multiple regressions were significant. However, the twenty patients with the smallest Cobb angles after surgery reported significantly higher SRS scores than the twenty patients with the largest Cobb angles after surgery, but there was no difference on the basis of rib hump correction. Discussion. Patients undergoing thoracoscopic (keyhole) anterior scoliosis correction report good SRS scores which are comparable to those in previous studies. We suggest that the absence of any statistically significant difference in SRS scores between patients with and without rod or screw complications is because these complications are not associated with any clinically significant loss of correction in our patient group. The Cobb angle after surgery was the only significant predictor of patient satisfaction when comparing subgroups of patients with the largest and smallest Cobb angles after surgery.

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This paper reports on the development of a tool that generates randomised, non-multiple choice assessment within the BlackBoard Learning Management System interface. An accepted weakness of multiple-choice assessment is that it cannot elicit learning outcomes from upper levels of Biggs’ SOLO taxonomy. However, written assessment items require extensive resources for marking, and are susceptible to copying as well as marking inconsistencies for large classes. This project developed an assessment tool which is valid, reliable and sustainable and that addresses the issues identified above. The tool provides each student with an assignment assessing the same learning outcomes, but containing different questions, with responses in the form of words or numbers. Practice questions are available, enabling students to obtain feedback on their approach before submitting their assignment. Thus, the tool incorporates automatic marking (essential for large classes), randomised tasks to each student (reducing copying), the capacity to give credit for working (feedback on the application of theory), and the capacity to target higher order learning outcomes by requiring students to derive their answers rather than choosing them. Results and feedback from students are presented, along with technical implementation details.

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The proportion of functional sequence in the human genome is currently a subject of debate. The most widely accepted figure is that approximately 5% is under purifying selection. In Drosophila, estimates are an order of magnitude higher, though this corresponds to a similar quantity of sequence. These estimates depend on the difference between the distribution of genomewide evolutionary rates and that observed in a subset of sequences presumed to be neutrally evolving. Motivated by the widening gap between these estimates and experimental evidence of genome function, especially in mammals, we developed a sensitive technique for evaluating such distributions and found that they are much more complex than previously apparent. We found strong evidence for at least nine well-resolved evolutionary rate classes in an alignment of four Drosophila species and at least seven classes in an alignment of four mammals, including human. We also identified at least three rate classes in human ancestral repeats. By positing that the largest of these ancestral repeat classes is neutrally evolving, we estimate that the proportion of nonneutrally evolving sequence is 30% of human ancestral repeats and 45% of the aligned portion of the genome. However, we also question whether any of the classes represent neutrally evolving sequences and argue that a plausible alternative is that they reflect variable structure-function constraints operating throughout the genomes of complex organisms.