122 resultados para Multi-criteria analysis


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Three-dimensional wagon train models have been developed for the crashworthiness analysis using multi-body dynamics approach. The contributions of the train size (number of wagon) to the frontal crash forces can be identified through the simulations. The effects of crash energy management (CEM) design and crash speed on train crashworthiness are examined. The CEM design can significantly improve the train crashworthiness and the consequential vehicle stability performance - reducing derailment risks.

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Time-varying bispectra, computed using a classical sliding window short-time Fourier approach, are analyzed for scalp EEG potentials evoked by an auditory stimulus and new observations are presented. A single, short duration tone is presented from the left or the right, direction unknown to the test subject. The subject responds by moving the eyes to the direction of the sound. EEG epochs sampled at 200 Hz for repeated trials are processed between -70 ms and +1200 ms with reference to the stimulus. It is observed that for an ensemble of correctly recognized cases, the best matching timevarying bispectra at (8 Hz, 8Hz) are for PZ-FZ channels and this is also largely the case for grand averages but not for power spectra at 8 Hz. Out of 11 subjects, the only exception for time-varying bispectral match was a subject with family history of Alzheimer’s disease and the difference was in bicoherence, not biphase.

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Data mining techniques extract repeated and useful patterns from a large data set that in turn are utilized to predict the outcome of future events. The main purpose of the research presented in this paper is to investigate data mining strategies and develop an efficient framework for multi-attribute project information analysis to predict the performance of construction projects. The research team first reviewed existing data mining algorithms, applied them to systematically analyze a large project data set collected by the survey, and finally proposed a data-mining-based decision support framework for project performance prediction. To evaluate the potential of the framework, a case study was conducted using data collected from 139 capital projects and analyzed the relationship between use of information technology and project cost performance. The study results showed that the proposed framework has potential to promote fast, easy to use, interpretable, and accurate project data analysis.

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Theoretical foundations of higher order spectral analysis are revisited to examine the use of time-varying bicoherence on non-stationary signals using a classical short-time Fourier approach. A methodology is developed to apply this to evoked EEG responses where a stimulus-locked time reference is available. Short-time windowed ensembles of the response at the same offset from the reference are considered as ergodic cyclostationary processes within a non-stationary random process. Bicoherence can be estimated reliably with known levels at which it is significantly different from zero and can be tracked as a function of offset from the stimulus. When this methodology is applied to multi-channel EEG, it is possible to obtain information about phase synchronization at different regions of the brain as the neural response develops. The methodology is applied to analyze evoked EEG response to flash visual stimulii to the left and right eye separately. The EEG electrode array is segmented based on bicoherence evolution with time using the mean absolute difference as a measure of dissimilarity. Segment maps confirm the importance of the occipital region in visual processing and demonstrate a link between the frontal and occipital regions during the response. Maps are constructed using bicoherence at bifrequencies that include the alpha band frequency of 8Hz as well as 4 and 20Hz. Differences are observed between responses from the left eye and the right eye, and also between subjects. The methodology shows potential as a neurological functional imaging technique that can be further developed for diagnosis and monitoring using scalp EEG which is less invasive and less expensive than magnetic resonance imaging.

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Bactrocera dorsalis sensu stricto, B. papayae, B. philippinensis and B. carambolae are serious pest fruit fly species of the B. dorsalis complex that predominantly occur in south-east Asia and the Pacific. Identifying molecular diagnostics has proven problematic for these four taxa, a situation that cofounds biosecurity and quarantine efforts and which may be the result of at least some of these taxa representing the same biological species. We therefore conducted a phylogenetic study of these four species (and closely related outgroup taxa) based on the individuals collected from a wide geographic range; sequencing six loci (cox1, nad4-3′, CAD, period, ITS1, ITS2) for approximately 20 individuals from each of 16 sample sites. Data were analysed within maximum likelihood and Bayesian phylogenetic frameworks for individual loci and concatenated data sets for which we applied multiple monophyly and species delimitation tests. Species monophyly was measured by clade support, posterior probability or bootstrap resampling for Bayesian and likelihood analyses respectively, Rosenberg's reciprocal monophyly measure, P(AB), Rodrigo's (P(RD)) and the genealogical sorting index, gsi. We specifically tested whether there was phylogenetic support for the four 'ingroup' pest species using a data set of multiple individuals sampled from a number of populations. Based on our combined data set, Bactrocera carambolae emerges as a distinct monophyletic clade, whereas B. dorsalis s.s., B. papayae and B. philippinensis are unresolved. These data add to the growing body of evidence that B. dorsalis s.s., B. papayae and B. philippinensis are the same biological species, which poses consequences for quarantine, trade and pest management.

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High-speed broadband internet access is widely recognised as a catalyst to social and economic development. However, the provision of broadband Internet services with the existing solutions to rural population, scattered over an extensive geographical area, remains both an economic and technical challenge. As a feasible solution, the Commonwealth Scientific and Industrial Research Organization (CSIRO) proposed a highly spectrally efficient, innovative and cost-effective fixed wireless broadband access technology, which uses analogue TV frequency spectrum and Multi-User MIMO (MUMIMO) technology with Orthogonal-Frequency-Division-Multiplexing (OFDM). MIMO systems have emerged as a promising solution for the increasing demand of higher data rates, better quality of service, and higher network capacity. However, the performance of MIMO systems can be significantly affected by different types of propagation environments e.g., indoor, outdoor urban, or outdoor rural and operating frequencies. For instance, large spectral efficiencies associated with MIMO systems, which assume a rich scattering environment in urban environments, may not be valid for all propagation environments, such as outdoor rural environments, due to the presence of less scatterer densities. Since this is the first time a MU-MIMO-OFDM fixed broadband wireless access solution is deployed in a rural environment, questions from both theoretical and practical standpoints arise; For example, what capacity gains are available for the proposed solution under realistic rural propagation conditions?. Currently, no comprehensive channel measurement and capacity analysis results are available for MU-MIMO-OFDM fixed broadband wireless access systems which employ large scale multiple antennas at the Access Point (AP) and analogue TV frequency spectrum in rural environments. Moreover, according to the literature, no deterministic MU-MIMO channel models exist that define rural wireless channels by accounting for terrain effects. This thesis fills the aforementioned knowledge gaps with channel measurements, channel modeling and comprehensive capacity analysis for MU-MIMO-OFDM fixed wireless broadband access systems in rural environments. For the first time, channel measurements were conducted in a rural farmland near Smithton, Tasmania using CSIRO's broadband wireless access solution. A novel deterministic MU-MIMO-OFDM channel model, which can be used for accurate performance prediction of rural MUMIMO channels with dominant Line-of-Sight (LoS) paths, was developed under this research. Results show that the proposed solution can achieve 43.7 bits/s/Hz at a Signal-to- Noise Ratio (SNR) of 20 dB in rural environments. Based on channel measurement results, this thesis verifies that the deterministic channel model accurately predicts channel capacity in rural environments with a Root Mean Square (RMS) error of 0.18 bits/s/Hz. Moreover, this study presents a comprehensive capacity analysis of rural MU-MIMOOFDM channels using experimental, simulated and theoretical models. Based on the validated deterministic model, further investigations on channel capacity and the eects of capacity variation, with different user distribution angles (θ) around the AP, were analysed. For instance, when SNR = 20dB, the capacity increases from 15.5 bits/s/Hz to 43.7 bits/s/Hz as θ increases from 10° to 360°. Strategies to mitigate these capacity degradation effects are also presented by employing a suitable user grouping method. Outcomes of this thesis have already been used by CSIRO scientists to determine optimum user distribution angles around the AP, and are of great significance for researchers and MU-MUMO-OFDM system developers to understand the advantages and potential capacity gains of MU-MIMO systems in rural environments. Also, results of this study are useful to further improve the performance of MU-MIMO-OFDM systems in rural environments. Ultimately, this knowledge contribution will be useful in delivering efficient, cost-effective high-speed wireless broadband systems that are tailor-made for rural environments, thus, improving the quality of life and economic prosperity of rural populations.

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Studies on quantitative fit analysis of precontoured fracture fixation plates emerged within the last few years and therefore, there is a wide research gap in this area. Quantitative fit assessment facilitates the measure of the gap between a fracture fixation plate and the underlying bone, and specifies the required plate fit criteria. For clinically meaningful fit assessment outcome, it is necessary to establish the appropriate criteria and parameter. The present paper studies this subject and recommends using multiple fit criteria and the maximum distance between the plate and underlying bone as fit parameter for clinically relevant outcome. We also propose the development of a software tool for automatic plate positioning and fit assessment for the purpose of implant design validation and optimization in an effort to provide better fitting implant that can assist proper fracture healing. The fundamental specifications of the software are discussed.

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Most commentators understand that contemporary social, economic and environmental challenges require quality governance from global to local scales. While public scrutiny of governance has increased in recent years, the literature on frameworks and methods for analysis in complex, poly-centric and multi-thematic governance systems remains fragmented; displaying many disciplinary or sectoral biases. This paper establishes a stronger theory-based foundation for the analysis of complex governance systems. It also develops a clear analytical framework applicable across a vast array of differing governance themes, domains and scales (GSA). The key methodological steps and evaluative criteria for the GSA framework are determined and practical guidance for its application in reform is provided.

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The ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Consortium was set up to analyze brain measures and genotypes from multiple sites across the world to improve the power to detect genetic variants that influence the brain. Diffusion tensor imaging (DTI) yields quantitative measures sensitive to brain development and degeneration, and some common genetic variants may be associated with white matter integrity or connectivity. DTI measures, such as the fractional anisotropy (FA) of water diffusion, may be useful for identifying genetic variants that influence brain microstructure. However, genome-wide association studies (GWAS) require large populations to obtain sufficient power to detect and replicate significant effects, motivating a multi-site consortium effort. As part of an ENIGMA-DTI working group, we analyzed high-resolution FA images from multiple imaging sites across North America, Australia, and Europe, to address the challenge of harmonizing imaging data collected at multiple sites. Four hundred images of healthy adults aged 18-85 from four sites were used to create a template and corresponding skeletonized FA image as a common reference space. Using twin and pedigree samples of different ethnicities, we used our common template to evaluate the heritability of tract-derived FA measures. We show that our template is reliable for integrating multiple datasets by combining results through meta-analysis and unifying the data through exploratory mega-analyses. Our results may help prioritize regions of the FA map that are consistently influenced by additive genetic factors for future genetic discovery studies. Protocols and templates are publicly available at (http://enigma.loni.ucla.edu/ongoing/dti-working-group/).

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This research investigated the use of DNA fingerprinting to characterise the bacteria Streptococcus pneumoniae or pneumococcus, and hence gain insight into the development of new vaccines or antibiotics. Different bacterial DNA fingerprinting methods were studied, and a novel method was developed and validated, which characterises different cell coatings that pneumococci produce. This method was used to study the epidemiology of pneumococci in Queensland before and after the introduction of the current pneumococcal vaccine. This study demonstrated that pneumococcal disease is highly prevalent in children under four years, that the bacteria can `switch' its cell coating to evade the vaccine, and that some DNA fingerprinting methods are more discriminatory than others. This has an impact on understanding which strains are more prone to cause invasive disease. Evidence of the excellent research findings have been published in high impact internationally refereed journals.

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Stress analysis within carotid plaques based on in vivo MR imaging has shown to be useful for the identification of vulnerable atheroma. This study is to investigate whether magnetic resonance imaging (MRI) based-biomechanical stress analysis of carotid plaques can differentiate acute symptomatic and asymptomatic patients. 54 asymptomatic and 45 acute symptomatic patients underwent in vivo multi-contrast MRI of the carotid arteries. Plaque geometry used for finite element analysis was derived from in vivo MR images at the site of maximum and minimum plaque burden. In total 198 slices were used for the computational simulations. A pre shrink technique was used to refine the simulation. Maximum principle stress at the vulnerable plaque sites (i.e. critical stress) was extracted for the selected slices and a comparison was performed between the two groups. Critical stress at the site of maximum plaque burden is significantly higher in acute symptomatic patients as compared to asymptomatic patients [median: 198.0kPa (inter quartile range (IQR) = (119.8 - 359.0) vs. 138.4kPa (83.8, 242.6), p=0.04]. No significant difference was found at the minimum plaque burden site between the two groups [196.7kPa (133.3- 282.7) vs. 182.4kPa (117.2 - 310. 6), p=0.82). Stress analysis at the site of maximal plaque burden can be effectively used for differentiating acute symptomatic carotid plaques from asymptomatic plaques. This maybe potentially used for development of biomechanical risk stratification criteria based on plaque burden in future studies.

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Atherosclerotic plaque rupture has been extensively considered as the leading cause of death in the world. It is believed that high stress within plaque can be an important factor which can trigger the rupture of the plaque. High resolution multi-spectral magnetic resonance imaging (MRI) has allowed the plaque components (arterial wall, lipids, and fibrous cap) to be visualized in vivo [1]. The patient specific finite element model can be generated from the image data to perform stress analysis and provide critical information on understanding plaque rupture mechanisms [2]. The present work is to apply the procedure to a total of 14 patients (S1 ∼ S14), to study the stress distributions on carotid artery plaque reconstructed from multi-spectral magnetic resonance images, and the possible relationships between stress and plaque burdens.