425 resultados para Improved line tracker


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Performance of urban transit systems may be quantified and assessed using transit capacity and productive capacity in planning, design and operational management activities. Bunker (4) defines important productive performance measures of an individual transit service and transit line, which are extended in this paper to quantify efficiency and operating fashion of transit services and lines. Comparison of a hypothetical bus line’s operation during a morning peak hour and daytime hour demonstrates the usefulness of productiveness efficiency and passenger transmission efficiency, passenger churn and average proportion line length traveled to the operator in understanding their services’ and lines’ productive performance, operating characteristics, and quality of service. Productiveness efficiency can flag potential pass-up activity under high load conditions, as well as ineffective resource deployment. Proportion line length traveled can directly measure operating fashion. These measures can be used to compare between lines/routes and, within a given line, various operating scenarios and time horizons to target improvements. The next research stage is investigating within-line variation using smart card passenger data and field observation of pass-ups. Insights will be used to further develop practical guidance to operators.

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Background Breastfeeding self-efficacy (BFSE) supports breastfeeding initiation and duration. Challenges to breastfeeding may undermine BFSE, but second-line strategies including nipple shields, syringe, cup, supply line and bottle feeding may support breastfeeding until challenges are resolved. The primary aim of this study was to examine BFSE in a sample of women using second-line strategies for feeding healthy term infants in the first week postpartum. Methods A retrospective self-report study was conducted using the Breastfeeding Self-Efficacy Scale - Short Form (BSES-SF), demographic and infant feeding questionnaires. Breastfeeding women who gave birth to a singleton healthy term infant at one private metropolitan birthing facility in Australia from November 2008 to February 2009 returned anonymous questionnaires by mail. Results A total of 128 (73 multiparous, 55 primiparous) women participated in the study. The mean BSES-SF score was 51.18 (Standard deviation, SD: 12.48). The median BSES-SF score was 53. Of women using a second-line strategy, 16 exceeded the median, and 42 were below. Analyses using Kruskal-Wallis tests confirmed this difference was statistically significant (H = 21.569, p = 0.001). The rate of second-line strategy use was 48%. The four most commonly used second-line strategies were: bottles with regular teats (77%); syringe feeding (44%); bottles with wide teats (34%); and nipple shields (27%). Seven key challenges were identified that contributed to the decision to use second-line strategies, including: nipple pain (40%); unsettled infant (40%); insufficient milk supply (37%); fatigue (37%); night nursery care (25%); infant weight loss > 10% (24%); and maternal birth associated pain (20%). Skin-to-skin contact at birth was commonly reported (93%). At seven days postpartum 124 women (97%) were continuing to breastfeed. Conclusions The high rate of use of second-line strategies identified in this study and high rate of breastfeeding at day seven despite lower BFSE indicate that such practices should not be overlooked by health professionals. The design of this study does not enable determination of cause-effect relationships to identify factors which contribute to use of second-line strategies. Nevertheless, the significantly lower BSES-SF score of women using a second-line strategy highlights this group of women have particular needs that require attention.

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A novel intelligent online demand management system is discussed in this chapter for peak load management in low voltage residential distribution networks based on the smart grid concept. The discussed system also regulates the network voltage, balances the power in three phases and coordinates the energy storage within the network. This method uses low cost controllers, with two-way communication interfaces, installed in costumers’ premises and at distribution transformers to manage the peak load while maximizing customer satisfaction. A multi-objective decision making process is proposed to select the load(s) to be delayed or controlled. The efficacy of the proposed control system is verified by a MATLAB-based simulation which includes detailed modeling of residential loads and the network.

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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.

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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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The first generation e-passport standard is proven to be insecure and prone to various attacks. To strengthen, the European Union (EU) has proposed an Extended Access Control (EAC) mechanism for e-passports that intends to provide better security in protecting biometric information of the e-passport bearer. But, our analysis shows, the EU proposal fails to address many security and privacy issues that are paramount in implementing a strong security mechanism. In this paper we propose an on-line authentication mechanism for electronic passports that addresses the weakness in existing implementations, of both The International Civil Aviation Organisation (ICAO) and EU. Our proposal utilises ICAO PKI implementation, thus requiring very little modifications to the existing infrastructure which is already well established.

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Sustainability is a key driver for decisions in the management and future development of organisations and industries. However, quantifying and comparing sustainability across the triple bottom line (TBL) of economy, environment and social impact, has been problematic. There is a need for a tool which can measure the complex interactions within and between the environmental, economic and social systems which affect the sustainability of an industry in a transparent, consistent and comparable way. The authors acknowledge that there are currently numerous ways in which sustainability is measured and multiple methodologies in how these measurement tools were designed. The purpose of this book is to showcase how Bayesian network modelling can be used to identify and measure environmental, economic and social sustainability variables and to understand their impact on and interaction with each other. This book introduces the Sustainability Scorecard, and describes it through a case study on sustainability of the Australian dairy industry. This study was conducted in collaboration with the Australian dairy industry.