947 resultados para ACCURATE DOCKING


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Orthopaedic fracture fixation implants are increasingly being designed using accurate 3D models of long bones based on computer tomography (CT). Unlike CT, magnetic resonance imaging (MRI) does not involve ionising radiation and is therefore a desirable alternative to CT. This study aims to quantify the accuracy of MRI-based 3D models compared to CT-based 3D models of long bones. The femora of five intact cadaver ovine limbs were scanned using a 1.5T MRI and a CT scanner. Image segmentation of CT and MRI data was performed using a multi-threshold segmentation method. Reference models were generated by digitising the bone surfaces free of soft tissue with a mechanical contact scanner. The MRI- and CT-derived models were validated against the reference models. The results demonstrated that the CT-based models contained an average error of 0.15mm while the MRI-based models contained an average error of 0.23mm. Statistical validation shows that there are no significant differences between 3D models based on CT and MRI data. These results indicate that the geometric accuracy of MRI based 3D models was comparable to that of CT-based models and therefore MRI is a potential alternative to CT for generation of 3D models with high geometric accuracy.

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Distributed Denial-of-Service (DDoS) attacks continue to be one of the most pernicious threats to the delivery of services over the Internet. Not only are DDoS attacks present in many guises, they are also continuously evolving as new vulnerabilities are exploited. Hence accurate detection of these attacks still remains a challenging problem and a necessity for ensuring high-end network security. An intrinsic challenge in addressing this problem is to effectively distinguish these Denial-of-Service attacks from similar looking Flash Events (FEs) created by legitimate clients. A considerable overlap between the general characteristics of FEs and DDoS attacks makes it difficult to precisely separate these two classes of Internet activity. In this paper we propose parameters which can be used to explicitly distinguish FEs from DDoS attacks and analyse two real-world publicly available datasets to validate our proposal. Our analysis shows that even though FEs appear very similar to DDoS attacks, there are several subtle dissimilarities which can be exploited to separate these two classes of events.

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Computational models for cardiomyocyte action potentials (AP) often make use of a large parameter set. This parameter set can contain some elements that are fitted to experimental data independently of any other element, some elements that are derived concurrently with other elements to match experimental data, and some elements that are derived purely from phenomenological fitting to produce the desired AP output. Furthermore, models can make use of several different data sets, not always derived for the same conditions or even the same species. It is consequently uncertain whether the parameter set for a given model is physiologically accurate. Furthermore, it is only recently that the possibility of degeneracy in parameter values in producing a given simulation output has started to be addressed. In this study, we examine the effects of varying two parameters (the L-type calcium current (I(CaL)) and the delayed rectifier potassium current (I(Ks))) in a computational model of a rabbit ventricular cardiomyocyte AP on both the membrane potential (V(m)) and calcium (Ca(2+)) transient. It will subsequently be determined if there is degeneracy in this model to these parameter values, which will have important implications on the stability of these models to cell-to-cell parameter variation, and also whether the current methodology for generating parameter values is flawed. The accuracy of AP duration (APD) as an indicator of AP shape will also be assessed.

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Endocytosis is the process by which cells internalise molecules including nutrient proteins from the extracellular media. In one form, macropinocytosis, the membrane at the cell surface ruffles and folds over to give rise to an internalised vesicle. Negatively charged phospholipids within the membrane called phosphoinositides then undergo a series of transformations that are critical for the correct trafficking of the vesicle within the cell, and which are often pirated by pathogens such as Salmonella. Advanced fluorescent video microscopy imaging now allows the detailed observation and quantification of these events in live cells over time. Here we use these observations as a basis for building differential equation models of the transformations. An initial investigation of these interactions was modelled with reaction rates proportional to the sum of the concentrations of the individual constituents. A first order linear system for the concentrations results. The structure of the system enables analytical expressions to be obtained and the problem becomes one of determining the reaction rates which generate the observed data plots. We present results with reaction rates which capture the general behaviour of the reactions so that we now have a complete mathematical model of phosphoinositide transformations that fits the experimental observations. Some excellent fits are obtained with modulated exponential functions; however, these are not solutions of the linear system. The question arises as to how the model may be modified to obtain a system whose solution provides a more accurate fit.

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This study aimed to explore resilience and wellbeing among a group of eight refugee women originating from several countries (mainly African) and living in Brisbane, most of whom were single mothers. To challenge mostly quantitative and gender-blind explorations of mental health concepts among refugee groups, the project sought an emic and contextual understanding of resilience and wellbeing. Established perspectives, while useful, tend to overlook the complexities of refugee mental health experiences and can neglect the dense nature of individual stories. The purpose of my study was to contest relatively simplistic narratives of mental health constructs that tend to dominate migrant and refugee studies and influence practice paradigms in the human services field. In this ethnographic exploration of mental health constructs conducted in 2008 and 2009, the use of in-depth interviews, participant observations, and visual ethnographic elements provided an opportunity for refugee women to tell their own stories. The participants’ unique narratives of pre- and post-migration experiences, shaped by specific gender, age, social, cultural and political aspects prevailing in their lives, yielded ‘thick’ ethnographic description (Geertz, 1973) of their social worlds. The findings explored in this study, namely language issues, the impact of community dynamics, and the single status of refugee women, clearly demonstrate that mental health constructs are fluid, multifaceted and complex in reality. In fact, language, community dynamics, and being a single mother, represented both opportunities and barriers in the lives of participants. In some contexts, these factors were conducive to resilience and wellbeing, while in other circumstances, these three elements acted as a hindrance to positive mental health outcomes. There are multiple dimensions to the findings, signifying that the social worlds of refugee women cannot be simplified using set definitions and neat notions of resilience and wellbeing. Instead, the intricacies and complexities embedded in the mundane of the everyday highlight novel conceptualisations of resilience and wellbeing. Based on the particular circumstances of single refugee mothers, whose experiences differ from that of married women, this thesis presents novel articulations of mental health constructs, as an alternative view to existing trends in the literature on refugee issues. Rich and multi-dimensional meanings associated with the socio-cultural determinants of mental health emerged in the process. This thesis’ findings highlight a significant gap in diasporic studies as well as simplistic assumptions about refugee women’s resettlement experiences. Single refugee women’s distinct issues are so complex and dense, that a contextual approach is critical to yield accurate depictions of their circumstances. It is therefore essential to understand refugee lived experiences within broader socio-political contexts to truly appreciate the depth of these narratives. In this manner, critical aspects salient to refugee journeys can inform different understandings of resilience, wellbeing and mental health, and shape contemporary policy and human service practice paradigms.

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Mechanical damages such as bruising, collision and impact during food processing stages diminish quality and quantity of productions as well as efficiency of operations. Studying mechanical characteristics of food materials will help to enhance current industrial practices. Mechanical properties of fruits and vegetables describe how these materials behave under loading in real industrial operations. Optimizing and designing more efficient equipments require accurate and precise information of tissue behaviours. FE modelling of food industrial processes is an effective method of studying interrelation of variables during mechanical operation. In this study, empirical investigation has been done on mechanical properties of pumpkin peel. The test was a part of FE modelling and simulation of mechanical peeling stage of tough skinned vegetables. The compression test has been conducted on Jap variety of pumpkin. Additionally, stress strain curve, bio-yield and toughness of pumpkin skin have been calculated. The required energy for reaching bio-yield point was 493.75, 507.71 and 451.71 N.mm for 1.25, 10 and 20 mm/min loading speed respectively. Average value of force in bio-yield point for pumpkin peel was 310 N.

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In this study, the delivery and portal imaging of one square-field and one conformal radiotherapy treatment was simulated using the Monte Carlo codes BEAMnrc and DOSXYZnrc. The treatment fields were delivered to a humanoid phantom from different angles by a 6 MV photon beam linear accelerator, with an amorphous-silicon electronic portal imaging device (a-Si EPID) used to provide images of the phantom generated by each field. The virtual phantom preparation code CTCombine was used to combine a computed-tomography-derived model of the irradiated phantom with a simple, rectilinear model of the a-Si EPID, at each beam angle used in the treatment. Comparison of the resulting experimental and simulated a-Si EPID images showed good agreement, within \[gamma](3%, 3 mm), indicating that this method may be useful in providing accurate Monte Carlo predictions of clinical a-Si EPID images, for use in the verification of complex radiotherapy treatments.

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Trees, shrubs and other vegetation are of continued importance to the environment and our daily life. They provide shade around our roads and houses, offer a habitat for birds and wildlife, and absorb air pollutants. However, vegetation touching power lines is a risk to public safety and the environment, and one of the main causes of power supply problems. Vegetation management, which includes tree trimming and vegetation control, is a significant cost component of the maintenance of electrical infrastructure. For example, Ergon Energy, the Australia’s largest geographic footprint energy distributor, currently spends over $80 million a year inspecting and managing vegetation that encroach on power line assets. Currently, most vegetation management programs for distribution systems are calendar-based ground patrol. However, calendar-based inspection by linesman is labour-intensive, time consuming and expensive. It also results in some zones being trimmed more frequently than needed and others not cut often enough. Moreover, it’s seldom practicable to measure all the plants around power line corridors by field methods. Remote sensing data captured from airborne sensors has great potential in assisting vegetation management in power line corridors. This thesis presented a comprehensive study on using spiking neural networks in a specific image analysis application: power line corridor monitoring. Theoretically, the thesis focuses on a biologically inspired spiking cortical model: pulse coupled neural network (PCNN). The original PCNN model was simplified in order to better analyze the pulse dynamics and control the performance. Some new and effective algorithms were developed based on the proposed spiking cortical model for object detection, image segmentation and invariant feature extraction. The developed algorithms were evaluated in a number of experiments using real image data collected from our flight trails. The experimental results demonstrated the effectiveness and advantages of spiking neural networks in image processing tasks. Operationally, the knowledge gained from this research project offers a good reference to our industry partner (i.e. Ergon Energy) and other energy utilities who wants to improve their vegetation management activities. The novel approaches described in this thesis showed the potential of using the cutting edge sensor technologies and intelligent computing techniques in improve power line corridor monitoring. The lessons learnt from this project are also expected to increase the confidence of energy companies to move from traditional vegetation management strategy to a more automated, accurate and cost-effective solution using aerial remote sensing techniques.

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In this paper, we describe a voting mechanism for accurate named entity (NE) translation in English–Chinese question answering (QA). This mechanism involves translations from three different sources: machine translation,online encyclopaedia, and web documents. The translation with the highest number of votes is selected. We evaluated this approach using test collection, topics and assessment results from the NTCIR-8 evaluation forum. This mechanism achieved 95% accuracy in NEs translation and 0.3756 MAP in English–Chinese cross-lingual information retrieval of QA.

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Continuous user authentication with keystroke dynamics uses characters sequences as features. Since users can type characters in any order, it is imperative to find character sequences (n-graphs) that are representative of user typing behavior. The contemporary feature selection approaches do not guarantee selecting frequently-typed features which may cause less accurate statistical user-representation. Furthermore, the selected features do not inherently reflect user typing behavior. We propose four statistical based feature selection techniques that mitigate limitations of existing approaches. The first technique selects the most frequently occurring features. The other three consider different user typing behaviors by selecting: n-graphs that are typed quickly; n-graphs that are typed with consistent time; and n-graphs that have large time variance among users. We use Gunetti’s keystroke dataset and k-means clustering algorithm for our experiments. The results show that among the proposed techniques, the most-frequent feature selection technique can effectively find user representative features. We further substantiate our results by comparing the most-frequent feature selection technique with three existing approaches (popular Italian words, common n-graphs, and least frequent ngraphs). We find that it performs better than the existing approaches after selecting a certain number of most-frequent n-graphs.

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Diabetic neuropathy is a significant clinical problem that currently has no effective therapy, and in advanced cases, leads to foot ulceration and lower limb amputation. The accurate detection, characterization and quantification of this condition are important in order to define at-risk patients, anticipate deterioration, monitor progression, and assess new therapies This review evaluates novel corneal methods of assessing diabetic neuropathy. Two new non-invasive corneal markers have emerged, and in cross-sectional studies have demonstrated their ability to stratify the severity of this disease. Corneal confocal microscopy allows quantification of corneal nerve parameters and non-contact corneal esthesiometry, the functional correlate of corneal structure, assesses the sensitivity of the cornea. Both these techniques are quick to perform, produce little or no discomfort for the patient, and are suitable for clinical settings. Each has advantages and disadvantages over traditional techniques for assessing diabetic neuropathy. Application of these new corneal markers for longitudinal evaluation of diabetic neuropathy has the potential to reduce dependence on more invasive, costly, and time-consuming assessments, such as skin biopsy.

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This paper outlines our literature review background, investigation and practical application utilizing a precise optical survey level and total station technology for a specialist industrial measurement application. The practical part of the project was to measure and check specific critical features of the Industrial JIG assembly table used by the Queensland University of Technology (QUT) Motorsport group. The JIG is used in constructing a new Formula SAE race-car frame each year and is used throughout the racing season to check the production frame for twists, bends and potential stresses. The industrial JIG table required two survey approaches, firstly determination of the overall flatness throughout its’ steel base surface. Secondly was the validation of verticality of the steel uprights used to support and hold the race-car frame in place during construction and checking alignment for key suspension components. In addition the investigation brings realisations that there are far more accurate, efficient and economical technologies to be harnessed in industrial metrology.

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The World Health Organization recommends that data on mortality in its member countries are collected utilising the Medical Certificate of Cause of Death published in the instruction volume of the ICD-10. However, investment in health information processes necessary to promote the use of this certificate and improve mortality information is lacking in many countries. An appeal for support to make improvements has been launched through the Health Metrics Network’s MOVE-IT strategy (Monitoring of Vital Events – Information Technology) [World Health Organization, 2011]. Despite this international spotlight on the need for capture of mortality data and in the use of the ICD-10 to code the data reported on such certificates, there is little cohesion in the way that certifiers of deaths receive instruction in how to complete the death certificate, which is the main source document for mortality statistics. Complete and accurate documentation of the immediate, underlying and contributory causes of death of the decedent on the death certificate is a requirement to produce standardised statistical information and to the ability to produce cause-specific mortality statistics that can be compared between populations and across time. This paper reports on a research project conducted to determine the efficacy and accessibility of the certification module of the WHO’s newly-developed web based training tool for coders and certifiers of deaths. Involving a population of medical students from the Fiji School of Medicine and a pre and post research design, the study entailed completion of death certificates based on vignettes before and after access to the training tool. The ability of the participants to complete the death certificates and analysis of the completeness and specificity of the ICD-10 coding of the reported causes of death were used to measure the effect of the students’ learning from the training tool. The quality of death certificate completion was assessed using a Quality Index before and after the participants accessed the training tool. In addition, the views of the participants about accessibility and use of the training tool were elicited using a supplementary questionnaire. The results of the study demonstrated improvement in the ability of the participants to complete death certificates completely and accurately according to best practice. The training tool was viewed very positively and its implementation in the curriculum for medical students was encouraged. Participants also recommended that interactive discussions to examine the certification exercises would be an advantage.

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Sustainable transport has become a necessity instead of an option, to address the problems of congestion and urban sprawl, whose effects include increased trip lengths and travel time. A more sustainable form of development, known as Transit Oriented Development (TOD) is presumed to offer sustainable travel choices with reduced need to travel to access daily destinations, by providing a mixture of land uses together with good quality of public transport service, infrastructure for walking and cycling. However, performance assessment of these developments with respect to travel characteristics of their inhabitants is required. This research proposes a five step methodology for evaluating the transport impacts of TODs. The steps for TOD evaluation include pre–TOD assessment, traffic and travel data collection, determination of traffic impacts, determination of travel impacts, and drawing outcomes. Typically, TODs are comprised of various land uses; hence have various types of users. Assessment of characteristics of all user groups is essential for obtaining an accurate picture of transport impacts. A case study TOD, Kelvin Grove Urban Village (KGUV), located 2km of north west of the Brisbane central business district in Australia was selected for implementing the proposed methodology and to evaluate the transport impacts of a TOD from an Australian perspective. The outcomes of this analysis indicated that KGUV generated 27 to 48 percent less traffic compared to standard published rates specified for homogeneous uses. Further, all user groups of KGUV used more sustainable modes of transport compared to regional and similarly located suburban users, with higher trip length for shopping and education trips. Although the results from this case study development support the transport claims of reduced traffic generation and sustainable travel choices by way of TODs, further investigation is required, considering different styles, scales and locations of TODs. The proposed methodology may be further refined by using results from new TODs and a framework for TOD evaluation may be developed.

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Metallic materials exposed to oxygen-enriched atmospheres – as commonly used in the medical, aerospace, aviation and numerous chemical processing industries – represent a significant fire hazard which must be addressed during design, maintenance and operation. Hence, accurate knowledge of metallic materials flammability is required. Reduced gravity (i.e. space-based) operations present additional unique concerns, where the absence of gravity must also be taken into account. The flammability of metallic materials has historically been quantified using three standardised test methods developed by NASA, ASTM and ISO. These tests typically involve the forceful (promoted) ignition of a test sample (typically a 3.2 mm diameter cylindrical rod) in pressurised oxygen. A test sample is defined as flammable when it undergoes burning that is independent of the ignition process utilised. In the standardised tests, this is indicated by the propagation of burning further than a defined amount, or „burn criterion.. The burn criterion in use at the onset of this project was arbitrarily selected, and did not accurately reflect the length a sample must burn in order to be burning independent of the ignition event and, in some cases, required complete consumption of the test sample for a metallic material to be considered flammable. It has been demonstrated that a) a metallic material.s propensity to support burning is altered by any increase in test sample temperature greater than ~250-300 oC and b) promoted ignition causes an increase in temperature of the test sample in the region closest to the igniter, a region referred to as the Heat Affected Zone (HAZ). If a test sample continues to burn past the HAZ (where the HAZ is defined as the region of the test sample above the igniter that undergoes an increase in temperature of greater than or equal to 250 oC by the end of the ignition event), it is burning independent of the igniter, and should be considered flammable. The extent of the HAZ, therefore, can be used to justify the selection of the burn criterion. A two dimensional mathematical model was developed in order to predict the extent of the HAZ created in a standard test sample by a typical igniter. The model was validated against previous theoretical and experimental work performed in collaboration with NASA, and then used to predict the extent of the HAZ for different metallic materials in several configurations. The extent of HAZ predicted varied significantly, ranging from ~2-27 mm depending on the test sample thermal properties and test conditions (i.e. pressure). The magnitude of the HAZ was found to increase with increasing thermal diffusivity, and decreasing pressure (due to slower ignition times). Based upon the findings of this work, a new burn criterion requiring 30 mm of the test sample to be consumed (from the top of the ignition promoter) was recommended and validated. This new burn criterion was subsequently included in the latest revision of the ASTM G124 and NASA 6001B international test standards that are used to evaluate metallic material flammability in oxygen. These revisions also have the added benefit of enabling the conduct of reduced gravity metallic material flammability testing in strict accordance with the ASTM G124 standard, allowing measurement and comparison of the relative flammability (i.e. Lowest Burn Pressure (LBP), Highest No-Burn Pressure (HNBP) and average Regression Rate of the Melting Interface(RRMI)) of metallic materials in normal and reduced gravity, as well as determination of the applicability of normal gravity test results to reduced gravity use environments. This is important, as currently most space-based applications will typically use normal gravity information in order to qualify systems and/or components for reduced gravity use. This is shown here to be non-conservative for metallic materials which are more flammable in reduced gravity. The flammability of two metallic materials, Inconel® 718 and 316 stainless steel (both commonly used to manufacture components for oxygen service in both terrestrial and space-based systems) was evaluated in normal and reduced gravity using the new ASTM G124-10 test standard. This allowed direct comparison of the flammability of the two metallic materials in normal gravity and reduced gravity respectively. The results of this work clearly show, for the first time, that metallic materials are more flammable in reduced gravity than in normal gravity when testing is conducted as described in the ASTM G124-10 test standard. This was shown to be the case in terms of both higher regression rates (i.e. faster consumption of the test sample – fuel), and burning at lower pressures in reduced gravity. Specifically, it was found that the LBP for 3.2 mm diameter Inconel® 718 and 316 stainless steel test samples decreased by 50% from 3.45 MPa (500 psia) in normal gravity to 1.72 MPa (250 psia) in reduced gravity for the Inconel® 718, and 25% from 3.45 MPa (500 psia) in normal gravity to 2.76 MPa (400 psia) in reduced gravity for the 316 stainless steel. The average RRMI increased by factors of 2.2 (27.2 mm/s in 2.24 MPa (325 psia) oxygen in reduced gravity compared to 12.8 mm/s in 4.48 MPa (650 psia) oxygen in normal gravity) for the Inconel® 718 and 1.6 (15.0 mm/s in 2.76 MPa (400 psia) oxygen in reduced gravity compared to 9.5 mm/s in 5.17 MPa (750 psia) oxygen in normal gravity) for the 316 stainless steel. Reasons for the increased flammability of metallic materials in reduced gravity compared to normal gravity are discussed, based upon the observations made during reduced gravity testing and previous work. Finally, the implications (for fire safety and engineering applications) of these results are presented and discussed, in particular, examining methods for mitigating the risk of a fire in reduced gravity.