985 resultados para control engineering computing


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This research investigates how to obtain accurate and reliable positioning results with global navigation satellite systems (GNSS). The work provides a theoretical framework for reliability control in GNSS carrier phase ambiguity resolution, which is the key technique for precise GNSS positioning in centimetre levels. The proposed approach includes identification and exclusion procedures of unreliable solutions and hypothesis tests, allowing the reliability of solutions to be controlled in the aspects of mathematical models, integer estimation and ambiguity acceptance tests. Extensive experimental results with both simulation and observed data sets effectively demonstrate the reliability performance characteristics based on the proposed theoretical framework and procedures.

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The requirement of distributed computing of all-to-all comparison (ATAC) problems in heterogeneous systems is increasingly important in various domains. Though Hadoop-based solutions are widely used, they are inefficient for the ATAC pattern, which is fundamentally different from the MapReduce pattern for which Hadoop is designed. They exhibit poor data locality and unbalanced allocation of comparison tasks, particularly in heterogeneous systems. The results in massive data movement at runtime and ineffective utilization of computing resources, affecting the overall computing performance significantly. To address these problems, a scalable and efficient data and task distribution strategy is presented in this paper for processing large-scale ATAC problems in heterogeneous systems. It not only saves storage space but also achieves load balancing and good data locality for all comparison tasks. Experiments of bioinformatics examples show that about 89\% of the ideal performance capacity of the multiple machines have be achieved through using the approach presented in this paper.

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With the ever increasing amount of eHealth data available from various eHealth systems and sources, Health Big Data Analytics promises enticing benefits such as enabling the discovery of new treatment options and improved decision making. However, concerns over the privacy of information have hindered the aggregation of this information. To address these concerns, we propose the use of Information Accountability protocols to provide patients with the ability to decide how and when their data can be shared and aggregated for use in big data research. In this paper, we discuss the issues surrounding Health Big Data Analytics and propose a consent-based model to address privacy concerns to aid in achieving the promised benefits of Big Data in eHealth.

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Concerns over the security and privacy of patient information are one of the biggest hindrances to sharing health information and the wide adoption of eHealth systems. At present, there are competing requirements between healthcare consumers' (i.e. patients) requirements and healthcare professionals' (HCP) requirements. While consumers want control over their information, healthcare professionals want access to as much information as required in order to make well-informed decisions and provide quality care. In order to balance these requirements, the use of an Information Accountability Framework devised for eHealth systems has been proposed. In this paper, we take a step closer to the adoption of the Information Accountability protocols and demonstrate their functionality through an implementation in FluxMED, a customisable EHR system.

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This tutorial primarily focuses on the implementation of Information Accountability (IA) protocols defined in an Information Accountability Framework (IAF) in eHealth systems. Concerns over the security and privacy of patient information are one of the biggest hindrances to sharing health information and the wide adoption of eHealth systems. At present, there are competing requirements between healthcare consumers' (i.e. patients) requirements and healthcare professionals' (HCP) requirements. While consumers want control over their information, healthcare professionals want access to as much information as required in order to make well-informed decisions and provide quality care. This conflict is evident in the review of Australia's PCEHR system and in recent studies of patient control of access to their eHealth information. In order to balance these requirements, the use of an Information Accountability Framework devised for eHealth systems has been proposed. Through the use of IA protocols, so-called Accountable-eHealth systems (AeH) create an eHealth environment where health information is available to the right person at the right time without rigid barriers whilst empowering the consumers with information control and transparency. In this half-day tutorial, we will discuss and describe the technical challenges surrounding the implementation of the IAF protocols into existing eHealth systems and demonstrate their use. The functionality of the protocols and AeH systems will be demonstrated, and an example of the implementation of the IAF protocols into an existing eHealth system will be presented and discussed.

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Various morphologies of the vertically-aligned graphene flakes were fabricated on the nanoporous templates treated with metal ions in solutions, as well as coated with a thin gold layer and activated in the low-temperature Ar plasma. The thickness and level of structural defects in the graphene flakes could be effectively controlled by a proper selection of the pre-treatment method. We have also demonstrated that various combinations of the flake thickness and defect levels can be obtained, and the morphology and density of the graphene pattern can be effectively controlled. The result obtained could be of interest for various applications requiring fabrication of large graphene networks with controllable properties.

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We address the problem of the rangefinder-based avoidance of unforeseen static obstacles during a visual navigation task. We extend previous strategies which are efficient in most cases but remain still hampered by some drawbacks (e.g., risks of collisions or of local minima in some particular cases, etc.). The key idea is to complete the control strategy by adding a controller providing the robot some anticipative skills to guarantee non collision and by defining more general transition conditions to deal with local minima. Simulation results show the proposed strategy efficiency.

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Introduction and Aims: Holiday periods are potentially a time for increased substance use as social events and private parties are more common. Data on community illicit drug consumption during holiday periods are limited. Besides existing methods for determining drug use, such as population surveys, one emerging method is to measure illicit drugs and/or their metabolites in wastewater samples. This study examined the change in consumption of cannabis, methamphetamine, cocaine and 3,4- methylenedioxymethamphetamine in three different types of areas (an inland semi-rural area, a coastal urban area and a vacation island) with respect to holiday times. Design and Methods: Samples were collected at the inlet of the major wastewater treatment plant in each area during a key annual holiday (i.e. the summer holiday including Christmas and New Year) and control period. Illicit drug residues in the daily composited samples were measured by liquid chromatography coupled with tandem mass spectrometry. Results: Drug use varied substantially among the three areas within each monitoring period as well as between the holiday and control period within each area. Use consistently increased and peaked over New Year particularly for cocaine and 3,4-methylenedioxymethamphetamine whereas cannabis and methamphetamine were relatively less subjected to holiday times in all the areas. Discussion and Conclusions: Wastewater sampling and analysis provides higher spatio-temporal resolution than national surveys and supplements drug epidemiology studies originating primary in metropolitan locations. Such data is essential for policy makers to plan potential intervention strategies associated with these illicit substances in regional areas and other settings besides urban areas in the future.

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Experiments were carried out to verify the effectiveness of the excess water storage depth (EWSD) in reducing runoff losses of simetryn and thiobencarb from paddy fields upon appreciable rainfall events. A paddy plot having an EWSD of 2 cm was effective in controlling runoff with the herbicide losses of less than 1% of the applied herbicides. Meanwhile, a plot with 0-cm EWSD lost 18.1 and 3.7% of the applied mass of simetryn and thiobencarb, respectively. Therefore, an appropriate EWSD is essential during the recommended 7-day water holding period in order to completely hold the water inside the field in case of rainfall.

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The applicability of ELISA kits was evaluated as an alternative to monitor bensulfuron-methyl and simetryn behavior in paddy water under intermittent (Plot 1) and continuous (Plot 2) irrigation schemes. Simetryn concentrations in both plots decreased exponentially from the peak of the first day. However, the simetryn kit systematically underestimated by a factor of 0.79 as compared to the GC method. Bensulfuron-methyl concentrations exhibited similar dissipation kinetics in paddy water and the drainage water. The bensulfuron-methyl kit was capable of distinguishing spatial variations of concentrations in the paddy field. The ELISA kits clearly indicated differences in the loss of both herbicides between the two plots and therefore may be useful for evaluating the water management practice of pesticide runoff control in paddy fields.

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In this paper, we present a decentralized dynamic load scheduling/balancing algorithm called ELISA (Estimated Load Information Scheduling Algorithm) for general purpose distributed computing systems. ELISA uses estimated state information based upon periodic exchange of exact state information between neighbouring nodes to perform load scheduling. The primary objective of the algorithm is to cut down on the communication and load transfer overheads by minimizing the frequency of status exchange and by restricting the load transfer and status exchange within the buddy set of a processor. It is shown that the resulting algorithm performs almost as well as a perfect information algorithm and is superior to other load balancing schemes based on the random sharing and Ni-Hwang algorithms. A sensitivity analysis to study the effect of various design parameters on the effectiveness of load balancing is also carried out. Finally, the algorithm's performance is tested on large dimensional hypercubes in the presence of time-varying load arrival process and is shown to perform well in comparison to other algorithms. This makes ELISA a viable and implementable load balancing algorithm for use in general purpose distributed computing systems.

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A number of hurdles must be overcome in order to integrate unmanned aircraft into civilian airspace for routine operations. The ability of the aircraft to land safely in an emergency is essential to reduce the risk to people, infrastructure and aircraft. To date, few field-demonstrated systems have been presented that show online re-planning and repeatability from failure to touchdown. This paper presents the development of the Guidance, Navigation and Control (GNC) component of an Automated Emergency Landing System (AELS) intended to address this gap, suited to a variety of fixed-wing aircraft. Field-tested on both a fixed-wing UAV and Cessna 172R during repeated emergency landing experiments, a trochoid-based path planner computes feasible trajectories and a simplified control system executes the required manoeuvres to guide the aircraft towards touchdown on a predefined landing site. This is achieved in zero-thrust conditions with engine forced to idle to simulate failure. During an autonomous landing, the controller uses airspeed, inertial and GPS data to track motion and maintains essential flight parameters to guarantee flyability, while the planner monitors glide ratio and re-plans to ensure approach at correct altitude. Simulations show reliability of the system in a variety of wind conditions and its repeated ability to land within the boundary of a predefined landing site. Results from field-tests for the two aircraft demonstrate the effectiveness of the proposed GNC system in live operation. Results show that the system is capable of guiding the aircraft to close proximity of a predefined keyhole in nearly 100% of cases.

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Shared eHealth records systems offer promising benefits for improving healthcare through high availability of information and improved decision making; however, their uptake has been hindered by concerns over the privacy of patient information. To address these privacy concerns while balancing the requirements of healthcare professionals to have access to the information they need to provide appropriate care, the use of an Information Accountability Framework (IAF) has been proposed. For the IAF and so called Accountable-eHealth systems to become a reality, the framework must provide for a diverse range of users and use cases. The initial IAF model did not provide for more diverse use cases including the need for certain users to delegate access to another user in the system to act on their behalf while maintaining accountability. In this paper, we define the requirements for delegation of access in the IAF, how such access policies would be represented in the Framework, and implement and validate an expanded IAF model.

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Meaningful use of eHealth, as seen through four key lenses: Usability; Usefulness; Utility; and Safety, is achieved through Accountable-eHealth systems.

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Allowing consumers to designate preferred healthcare professionals; Accountable-eHealth systems create a transparent and accountable eHealth environment for better healthcare delivery.