216 resultados para improved SVM
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The poor nutritional status of Aboriginal Australians is a serious and complex public health concern. We describe an unusually successful health and nutrition project initiated by the people of Minjilang, which was developed, implemented and evaluated with the community. Apparent community dietary intake, assessed by the ‘store-turnover’ method, and biochemical, anthropometric and haematological indicators of health and nutritional status were measured before intervention and at three-monthly intervals during the intervention year. Following intervention, there was a significant decrease in dietary intake of sugar and saturated fat, an increase in micronutrient density, corresponding improvements in biochemical indices (for example, a 12 per cent decrease in mean serum cholesterol, increases in serum and red cell folate, serum vitamin B6 and plasma ascorbic acid), decrease in mean systolic and diastolic blood pressures, a normalisation of body mass index, and a normalisation of haematologic indices. The success of this project demonstrates that Aboriginal communities can bring about improvements in their generally poor nutritional status, and that the store-turnover method provides a valid, inexpensive and noninvasive method for evaluating the resultant changes in community diet. Although the project was undoubtedly effective in the short term, further work is in progress to assess individual strategies with respect to sustainability, cost-effectiveness and generalisability.
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This paper introduces an improved line tracker using IMU and vision data for visual servoing tasks. We utilize an Image Jacobian which describes motion of a line feature to corresponding camera movements. These camera motions are estimated using an IMU. We demonstrate impacts of the proposed method in challenging environments: maximum angular rate ~160 0/s, acceleration ~6m /s2 and in cluttered outdoor scenes. Simulation and quantitative tracking performance comparison with the Visual Servoing Platform (ViSP) are also presented.
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The geographic location of cloud data storage centres is an important issue for many organisations and individuals due to various regulations that require data and operations to reside in specific geographic locations. Thus, cloud users may want to be sure that their stored data have not been relocated into unknown geographic regions that may compromise the security of their stored data. Albeshri et al. (2012) combined proof of storage (POS) protocols with distance-bounding protocols to address this problem. However, their scheme involves unnecessary delay when utilising typical POS schemes due to computational overhead at the server side. The aim of this paper is to improve the basic GeoProof protocol by reducing the computation overhead at the server side. We show how this can maintain the same level of security while achieving more accurate geographic assurance.
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The detection and correction of defects remains among the most time consuming and expensive aspects of software development. Extensive automated testing and code inspections may mitigate their effect, but some code fragments are necessarily more likely to be faulty than others, and automated identification of fault prone modules helps to focus testing and inspections, thus limiting wasted effort and potentially improving detection rates. However, software metrics data is often extremely noisy, with enormous imbalances in the size of the positive and negative classes. In this work, we present a new approach to predictive modelling of fault proneness in software modules, introducing a new feature representation to overcome some of these issues. This rank sum representation offers improved or at worst comparable performance to earlier approaches for standard data sets, and readily allows the user to choose an appropriate trade-off between precision and recall to optimise inspection effort to suit different testing environments. The method is evaluated using the NASA Metrics Data Program (MDP) data sets, and performance is compared with existing studies based on the Support Vector Machine (SVM) and Naïve Bayes (NB) Classifiers, and with our own comprehensive evaluation of these methods.
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INTRODUCTION Health disparity between urban and rural regions in Australia is well-documented. In the Wheatbelt catchments of Western Australia there is higher incidence and rate of avoidable hospitalisation for chronic diseases. Structured care approach to chronic illnesses is not new but the focus has been on single disease state. A recent ARC Discovery Project on general practice nurse-led chronic disease management of diabetes, hypertension and stable ischaemic heart disease reported improved communication and better medical administration.[1] In our study we investigated the sustainability of such a multi-morbidities general practice –led collaborative model of care in rural Australia. METHODS A QUAN(qual) design was utilised. Eight pairs of rural general practices were matched. Inclusion criteria used were >18 years and capable of giving informed consent, at least one identified risk factor or diagnosed with chronic conditions. Patients were excluded if deemed medically unsuitable. A comprehensive care plan was formulated by the respective general practice nurse in consultation with the treating General Practitioner (GP) and patient based on the individual’s readiness to change, and was informed by available local resource. A case management approach was utilised. Shediaz-Rizkallah and Lee’s conceptual framework on sustainability informed our evaluation.[2] Our primary outcome on measures of sustainability was reduction in avoidable hospitalisation. Secondary outcomes were patients and practitioners acceptance and satisfaction, and changes to pre-determined interim clinical and process outcomes. RESULTS The qualitative interviews highlighted the community preference for a ‘sustainable’ local hospital in addition to general practice. Costs, ease of access, low prioritisation of self chronic care, workforce turnover and perception of losing another local resource if underutilised influenced the respondents’ decision to present at local hospital for avoidable chronic diseases regardless. CONCLUSIONS Despite the pragmatic nature of rural general practice in Australia, the sustainability of chronic multi-morbidities management in general practice require efficient integration of primary-secondary health care and consideration of other social determinants of health. What this study adds: What is already known on this subject: Structured approach to chronic disease management is not new and has been shown to be effective for reducing hospitalisation. However, the focus has been on single disease state. What does this study add: Sustainability of collaborative model of multi-morbidities care require better primary-secondary integration and consideration of social determinants of health.
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Sugar cane is a major source of food and fuel worldwide. Biotechnology has the potential to improve economically-important traits in sugar cane as well as diversify sugar cane beyond traditional applications such as sucrose production. High levels of transgene expression are key to the success of improving crops through biotechnology. Here we describe new molecular tools that both expand and improve gene expression capabilities in sugar cane. We have identified promoters that can be used to drive high levels of gene expression in the leaf and stem of transgenic sugar cane. One of these promoters, derived from the Cestrum yellow leaf curling virus, drives levels of constitutive transgene expression that are significantly higher than those achieved by the historical benchmark maize polyubiquitin-1 (Zm-Ubi1) promoter. A second promoter, the maize phosphonenolpyruvate carboxylate promoter, was found to be a strong, leaf-preferred promoter that enables levels of expression comparable to Zm-Ubi1 in this organ. Transgene expression was increased approximately 50-fold by gene modification, which included optimising the codon usage of the coding sequence to better suit sugar cane. We also describe a novel dual transcriptional enhancer that increased gene expression from different promoters, boosting expression from Zm-Ubi1 over eightfold. These molecular tools will be extremely valuable for the improvement of sugar cane through biotechnology.
An improved chemically inducible gene switch that functions in the monocotyledonous plant sugar cane
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Chemically inducible gene switches can provide precise control over gene expression, enabling more specific analyses of gene function and expanding the plant biotechnology toolkit beyond traditional constitutive expression systems. The alc gene expression system is one of the most promising chemically inducible gene switches in plants because of its potential in both fundamental research and commercial biotechnology applications. However, there are no published reports demonstrating that this versatile gene switch is functional in transgenic monocotyledonous plants, which include some of the most important agricultural crops. We found that the original alc gene switch was ineffective in the monocotyledonous plant sugar cane, and describe a modified alc system that is functional in this globally significant crop. A promoter consisting of tandem copies of the ethanol receptor inverted repeat binding site, in combination with a minimal promoter sequence, was sufficient to give enhanced sensitivity and significantly higher levels of ethanol inducible gene expression. A longer CaMV 35S minimal promoter than was used in the original alc gene switch also substantially improved ethanol inducibility. Treating the roots with ethanol effectively induced the modified alc system in sugar cane leaves and stem, while an aerial spray was relatively ineffective. The extension of this chemically inducible gene expression system to sugar cane opens the door to new opportunities for basic research and crop biotechnology.
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Spatially-explicit modelling of grassland classes is important to site-specific planning for improving grassland and environmental management over large areas. In this study, a climate-based grassland classification model, the Comprehensive and Sequential Classification System (CSCS) was integrated with spatially interpolated climate data to classify grassland in Gansu province, China. The study area is characterized by complex topographic features imposed by plateaus, high mountains, basins and deserts. To improve the quality of the interpolated climate data and the quality of the spatial classification over this complex topography, three linear regression methods, namely an analytic method based on multiple regression and residues (AMMRR), a modification of the AMMRR method through adding the effect of slope and aspect to the interpolation analysis (M-AMMRR) and a method which replaces the IDW approach for residue interpolation in M-AMMRR with an ordinary kriging approach (I-AMMRR), for interpolating climate variables were evaluated. The interpolation outcomes from the best interpolation method were then used in the CSCS model to classify the grassland in the study area. Climate variables interpolated included the annual cumulative temperature and annual total precipitation. The results indicated that the AMMRR and M-AMMRR methods generated acceptable climate surfaces but the best model fit and cross validation result were achieved by the I-AMMRR method. Twenty-six grassland classes were classified for the study area. The four grassland vegetation classes that covered more than half of the total study area were "cool temperate-arid temperate zonal semi-desert", "cool temperate-humid forest steppe and deciduous broad-leaved forest", "temperate-extra-arid temperate zonal desert", and "frigid per-humid rain tundra and alpine meadow". The vegetation classification map generated in this study provides spatial information on the locations and extents of the different grassland classes. This information can be used to facilitate government agencies' decision-making in land-use planning and environmental management, and for vegetation and biodiversity conservation. The information can also be used to assist land managers in the estimation of safe carrying capacities which will help to prevent overgrazing and land degradation.
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Current federal government policy initiatives in Aboriginal education and social welfare reform are based on assumptions about the relationship between increased attendance and increased student performance on standardized tests. There are empirical assumptions underlying these policy interventions and their accompanying public debates. Our aim here is to empirically explore the relationships between patterns of student attendance and patterns of student achievement in schools with significant cohorts of Aboriginal and/or Torres Strait Islander students at the school level. Based on an analysis of the publicly available data reported on the ‘MySchool’ website, we find that reforms and policies around attendance have not and are unlikely to generate patterns of improved achievement. Questions about the rationale and rhetoric of government policy focused at the school level as opposed to the need to focus on pedagogy and curriculum are discussed.
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A total of 1,625 tornadoes occurred in the United States in 2011, resulting in economic losses that exceeded $25 billion. Two tornado outbreaks stand out because they caused more than half of those losses. The tornadoes that cut through Tuscaloosa, Alabama, on April 27 and Joplin, Missouri, on May 22 were responsible for a combined 223 fatalities and more than 13,000 damaged buildings in the two cities. Although the economic losses associated with tornado damage are well documented, the writers argue that the overall impact should encompass longer term, broader considerations such as the social disruption and psychological effects that impact communities. This paper examines observations by tornado damage assessment teams led by the first author in these two medium-sized cities and suggests that the evolution of building codes and past approaches to construction have led to conditions that made this extent of damage possible. The authors outline a multidisciplinary path forward that incorporates engineering research and social and economic studies into a new design paradigm leading to building code changes and social practices that will improve resistance and mitigate future losses at a community level from tornadoes.
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An increasing number of countries are faced with an aging population increasingly needing healthcare services. For any e-health information system, the need for increased trust by such clients with potentially little knowledge of any security scheme involved is paramount. In addition notable scalability of any system has become a critical aspect of system design, development and ongoing management. Meanwhile cryptographic systems provide the security provisions needed for confidentiality, authentication, integrity and non-repudiation. Cryptographic key management, however, must be secure, yet efficient and effective in developing an attitude of trust in system users. Digital certificate-based Public Key Infrastructure has long been the technology of choice or availability for information security/assurance; however, there appears to be a notable lack of successful implementations and deployments globally. Moreover, recent issues with associated Certificate Authority security have damaged trust in these schemes. This paper proposes the adoption of a centralised public key registry structure, a non-certificate based scheme, for large scale e-health information systems. The proposed structure removes complex certificate management, revocation and a complex certificate validation structure while maintaining overall system security. Moreover, the registry concept may be easier for both healthcare professionals and patients to understand and trust.
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Increasing the importance and use of infrastructures such as bridges, demands more effective structural health monitoring (SHM) systems. SHM has well addressed the damage detection issues through several methods such as modal strain energy (MSE). Many of the available MSE methods either have been validated for limited type of structures such as beams or their performance is not satisfactory. Therefore, it requires a further improvement and validation of them for different types of structures. In this study, an MSE method was mathematically improved to precisely quantify the structural damage at an early stage of formation. Initially, the MSE equation was accurately formulated considering the damaged stiffness and then it was used for derivation of a more accurate sensitivity matrix. Verification of the improved method was done through two plane structures: a steel truss bridge and a concrete frame bridge models that demonstrate the framework of a short- and medium-span of bridge samples. Two damage scenarios including single- and multiple-damage were considered to occur in each structure. Then, for each structure, both intact and damaged, modal analysis was performed using STRAND7. Effects of up to 5 per cent noise were also comprised. The simulated mode shapes and natural frequencies derived were then imported to a MATLAB code. The results indicate that the improved method converges fast and performs well in agreement with numerical assumptions with few computational cycles. In presence of some noise level, it performs quite well too. The findings of this study can be numerically extended to 2D infrastructures particularly short- and medium-span bridges to detect the damage and quantify it more accurately. The method is capable of providing a proper SHM that facilitates timely maintenance of bridges to minimise the possible loss of lives and properties.
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Efforts to improve the performance of commercial buildings have often focused on encouraging green design, construction and building operation; however, the business case is not very compelling if considering the energy cost savings alone. In recent years green building has been driven by a sense that it will improve the productivity of occupants, something with even greater economic returns than energy savings. Reducing energy demand in commercial buildings in a way that encourages greater productivity is not yet well understood as it involves a set of complex and interdependent factors. This project investigates these factors and focuses on the performance of and interaction between: green design elements, indoor environment quality, tenant/ leasing agreements and culture, occupant experience, and building management practices.
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Dragon stream cipher is one of the focus ciphers which have reached Phase 2 of the eSTREAMproject. In this paper, we present a new method of building a linear distinguisher for Dragon. The distinguisher is constructed by exploiting the biases of two S-boxes and the modular addition which are basic components of the nonlinear function F. The bias of the distinguisher is estimated to be around 2−75.32 which is better than the bias of the distinguisher presented by Englund and Maximov. We have shown that Dragon is distinguishable from a random cipher by using around 2150.6 keystream words and 259 memory. In addition, we present a very efficient algorithm for computing the bias of linear approximation of modular addition.
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Background Large segmental defects in bone do not heal well and present clinical challenges. This study investigated modulation of the mechanical environment as a means of improving bone healing in the presence of bone morphogenetic protein (BMP)-2. Although the influence of mechanical forces on the healing of fractures is well established, no previous studies, to our knowledge, have described their influence on the healing of large segmental defects. We hypothesized that bone-healing would be improved by initial, low-stiffness fixation of the defect, followed by high-stiffness fixation during the healing process. We call this reverse dynamization. Methods A rat model of a critical-sized femoral defect was used. External fixators were constructed to provide different degrees of stiffness and, importantly, the ability to change stiffness during the healing process in vivo. Healing of the critical-sized defects was initiated by the implantation of 11 mg of recombinant human BMP (rhBMP)-2 on a collagen sponge. Groups of rats receiving BMP-2 were allowed to heal with low, medium, and high-stiffness fixators, as well as under conditions of reverse dynamization, in which the stiffness was changed from low to high at two weeks. Healing was assessed at eight weeks with use of radiographs, histological analysis, microcomputed tomography, dual x-ray absorptiometry, and mechanical testing. Results Under constant stiffness, the low-stiffness fixator produced the best healing after eight weeks. However, reverse dynamization provided considerable improvement, resulting in a marked acceleration of the healing process by all of the criteria of this study. The histological data suggest that this was the result of intramembranous, rather than endochondral, ossification. Conclusions Reverse dynamization accelerated healing in the presence of BMP-2 in the rat femur and is worthy of further investigation as a means of improving the healing of large segmental bone defects. Clinical Relevance These data provide the basis of a novel, simple, and inexpensive way to improve the healing of critical-sized defects in long bones. Reverse dynamization may also be applicable to other circumstances in which bonehealing is problematic.