997 resultados para Exhaust Systems.
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Mathematics has been perceived as the core area of learning in most educational systems around the world including Sri Lanka. Unfortunately, it is clearly visible that a majority of Sri Lankan students are failing in their basic mathematics when the recent grade five scholarship examination and ordinary level exam marks are analysed. According to Department of Examinations Sri Lanka , on average, over 88 percent of the students are failing in the grade 5 scholarship examinations where mathematics plays a huge role while about 50 percent of the students fail in there ordinary level mathematics examination. Poor or lack of basic mathematics skills has been identified as the root cause.
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Distributed systems are widely used for solving large-scale and data-intensive computing problems, including all-to-all comparison (ATAC) problems. However, when used for ATAC problems, existing computational frameworks such as Hadoop focus on load balancing for allocating comparison tasks, without careful consideration of data distribution and storage usage. While Hadoop-based solutions provide users with simplicity of implementation, their inherent MapReduce computing pattern does not match the ATAC pattern. This leads to load imbalances and poor data locality when Hadoop's data distribution strategy is used for ATAC problems. Here we present a data distribution strategy which considers data locality, load balancing and storage savings for ATAC computing problems in homogeneous distributed systems. A simulated annealing algorithm is developed for data distribution and task scheduling. Experimental results show a significant performance improvement for our approach over Hadoop-based solutions.
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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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Background At Queensland University of Technology (QUT), the Bachelor of Radiation Therapy course evaluation has previously suffered from low online survey participation rates. A communal instantaneous feedback event using an audience response system (ARS) was evaluated as a potential solution to this problem. The aims of the project were to determine the extent to which this feedback event could be facilitated by ARS technology and to evaluate the impact the technology made on student satisfaction and engagement. Methods Students were invited to a timetabled session to provide feedback on individual study units and the course overall. They provided quantitative Likert-style responses to prompts for each unit and the course using an ARS as well as anonymous typed qualitative comments. Data collection was performed live so students were able to view collective class responses. This prompted further discussion and enabled a prospective action plan to be developed. To inform future ARS use, students were asked for their opinions on the feedback method. Results Despite technological difficulties, student evaluation indicated that all responders enjoyed the session and the opportunity to view the combined responses. All students felt that useful feedback was generated and that this method should be used in the future. The student attendance and response rates were high, and it was clear that the session had led to the development of some insightful qualitative feedback comments. Conclusions: An ARS contributed well to the collection of course feedback in a communal and interactive environment. Students found it enjoyable to use, and it helped to stimulate useful qualitative comments
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While enhanced cybersecurity options, mainly based around cryptographic functions, are needed overall speed and performance of a healthcare network may take priority in many circumstances. As such the overall security and performance metrics of those cryptographic functions in their embedded context needs to be understood. Understanding those metrics has been the main aim of this research activity. This research reports on an implementation of one network security technology, Internet Protocol Security (IPSec), to assess security performance. This research simulates sensitive healthcare information being transferred over networks, and then measures data delivery times with selected security parameters for various communication scenarios on Linux-based and Windows-based systems. Based on our test results, this research has revealed a number of network security metrics that need to be considered when designing and managing network security for healthcare-specific or non-healthcare-specific systems from security, performance and manageability perspectives. This research proposes practical recommendations based on the test results for the effective selection of network security controls to achieve an appropriate balance between network security and performance
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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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Provision of network infrastructure to meet rising network peak demand is increasing the cost of electricity. Addressing this demand is a major imperative for Australian electricity agencies. The network peak demand model reported in this paper provides a quantified decision support tool and a means of understanding the key influences and impacts on network peak demand. An investigation of the system factors impacting residential consumers’ peak demand for electricity was undertaken in Queensland, Australia. Technical factors, such as the customers’ location, housing construction and appliances, were combined with social factors, such as household demographics, culture, trust and knowledge, and Change Management Options (CMOs) such as tariffs, price,managed supply, etc., in a conceptual ‘map’ of the system. A Bayesian network was used to quantify the model and provide insights into the major influential factors and their interactions. The model was also used to examine the reduction in network peak demand with different market-based and government interventions in various customer locations of interest and investigate the relative importance of instituting programs that build trust and knowledge through well designed customer-industry engagement activities. The Bayesian network was implemented via a spreadsheet with a tick box interface. The model combined available data from industry-specific and public sources with relevant expert opinion. The results revealed that the most effective intervention strategies involve combining particular CMOs with associated education and engagement activities. The model demonstrated the importance of designing interventions that take into account the interactions of the various elements of the socio-technical system. The options that provided the greatest impact on peak demand were Off-Peak Tariffs and Managed Supply and increases in the price of electricity. The impact in peak demand reduction differed for each of the locations and highlighted that household numbers, demographics as well as the different climates were significant factors. It presented possible network peak demand reductions which would delay any upgrade of networks, resulting in savings for Queensland utilities and ultimately for households. The use of this systems approach using Bayesian networks to assist the management of peak demand in different modelled locations in Queensland provided insights about the most important elements in the system and the intervention strategies that could be tailored to the targeted customer segments.
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This research used design science research methods to develop, instantiate, implement, and measure the acceptance of a novel software artefact. The primary purpose of this software artefact was to enhance data collection, improve its quality and enable its capture in classroom environments without distracting from the teaching activity. The artefact set is an iOS app, with supporting web services and technologies designed in response to teacher and pastoral care needs. System analysis and design used Enterprise Architecture methods. The novel component of the iOS app implemented proximity detection to identify the student through their iPad and automatically link to that student's data. The use of this novel software artefact and web services was trialled in a school setting, measuring user acceptance and system utility. This integrated system was shown to improve the accuracy, consistency, completeness and timeliness of captured data and the utility of the input and reporting systems.
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China has a massive population of children with disabilities. To address the special needs of these children, special/inclusive education in China has developed dramatically since the early 1980s onwards. This Special Issue puts together seven empirical studies emerging from the Chinese societies. These studies analyse inclusive discourses embedded in the education policy documents; scrutinise professional competence of inclusive education teachers; evaluate inclusive education practices in physical education, mathematics education, and job-related social skills education provided to students with disabilities; debate the required in-class support for inclusive education teachers; and discuss the social attitudes towards people with disabilities. The foci, methods and theories vary across the seven studies, while their aims converge. These studies are seeking best possible approaches and best available resources that facilitate inclusion. Knowledge built and lessons learned from these studies will provide implications for future inclusive education practices in China and beyond.
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The world has experienced a large increase in the amount of available data. Therefore, it requires better and more specialized tools for data storage and retrieval and information privacy. Recently Electronic Health Record (EHR) Systems have emerged to fulfill this need in health systems. They play an important role in medicine by granting access to information that can be used in medical diagnosis. Traditional systems have a focus on the storage and retrieval of this information, usually leaving issues related to privacy in the background. Doctors and patients may have different objectives when using an EHR system: patients try to restrict sensible information in their medical records to avoid misuse information while doctors want to see as much information as possible to ensure a correct diagnosis. One solution to this dilemma is the Accountable e-Health model, an access protocol model based in the Information Accountability Protocol. In this model patients are warned when doctors access their restricted data. They also enable a non-restrictive access for authenticated doctors. In this work we use FluxMED, an EHR system, and augment it with aspects of the Information Accountability Protocol to address these issues. The Implementation of the Information Accountability Framework (IAF) in FluxMED provides ways for both patients and physicians to have their privacy and access needs achieved. Issues related to storage and data security are secured by FluxMED, which contains mechanisms to ensure security and data integrity. The effort required to develop a platform for the management of medical information is mitigated by the FluxMED's workflow-based architecture: the system is flexible enough to allow the type and amount of information being altered without the need to change in your source code.
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Contemporary food systems promote the consumption of highly processed foods of limited nutrition, contributing to overweight and obesity, diet-related disease and significant financial burden on healthcare systems. In part, this has resulted from highly successful design, development and marketing strategies for processed foods. The successful application of such strategies to healthy food options, and the services and business plans that accompany them, could assist in enhancing health and alleviating burden on health care systems. Product designers have long been aware of the importance of intertwining emotional experiences with new products. However, a lack of theoretical precision exists for applying emotional design beyond food products, to the food systems, services and business models that drive them. This article explores emotional design within the context of food and food systems and proposes a new concept – Emotional Food Design (EFD), through which emotional design is integrated across levels of a food system. EFD complements the dominating deductive view of food systems research with an abductive iterative design approach contextualized within the creation of new food products, services and business models and their associated emotional attachments. This paper concludes by outlining what EFD can offer to reorient food systems to successfully promote healthy eating.
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This review is focused on the impact of chemometrics for resolving data sets collected from investigations of the interactions of small molecules with biopolymers. These samples have been analyzed with various instrumental techniques, such as fluorescence, ultraviolet–visible spectroscopy, and voltammetry. The impact of two powerful and demonstrably useful multivariate methods for resolution of complex data—multivariate curve resolution–alternating least squares (MCR–ALS) and parallel factor analysis (PARAFAC)—is highlighted through analysis of applications involving the interactions of small molecules with the biopolymers, serum albumin, and deoxyribonucleic acid. The outcomes illustrated that significant information extracted by the chemometric methods was unattainable by simple, univariate data analysis. In addition, although the techniques used to collect data were confined to ultraviolet–visible spectroscopy, fluorescence spectroscopy, circular dichroism, and voltammetry, data profiles produced by other techniques may also be processed. Topics considered including binding sites and modes, cooperative and competitive small molecule binding, kinetics, and thermodynamics of ligand binding, and the folding and unfolding of biopolymers. Applications of the MCR–ALS and PARAFAC methods reviewed were primarily published between 2008 and 2013.
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为研究风电并网对互联系统低频振荡的影响,基于完整的双馈风电机组模型,定性分析了两区域互联系统在风电机组并网前后阻尼特性的变化情况.从双馈风电机组并网输送距离、并网容量、互联系统联络线传送功率、是否加装电力系统稳定器等多个方面,多角度分析了风电场并网对互联系统小干扰稳定及低频振荡特性的影响.之后,以两个包括两个区域的电力系统为例,进行了系统的计算分析和比较.结果表明,有双馈风电机组接入的互联电力系统,在不同运行模式下,双馈风电机组的并网输送距离、出力水平、联络线传送功率对低频振荡模式的影响在趋势和程度上均有显著差异,这样在对风电场进行入网规划、设计和运行时就需要综合考虑这些因素的影响.
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RFID is an important technology that can be used to create the ubiquitous society. But an RFID system uses open radio frequency signal to transfer information and this leads to pose many serious threats to its privacy and security. In general, the computing and storage resources in an RFID tag are very limited and this makes it difficult to solve its secure and private problems, especially for low-cost RFID tags. In order to ensure the security and privacy of low-cost RFID systems we propose a lightweight authentication protocol based on Hash function. This protocol can ensure forward security and prevent information leakage, location tracing, eavesdropping, replay attack and spoofing. This protocol completes the strong authentication of the reader to the tag by twice authenticating and it only transfers part information of the encrypted tag’s identifier for each session so it is difficult for an adversary to intercept the whole identifier of a tag. This protocol is simple and it takes less computing and storage resources, it is very suitable to some low-cost RFID systems.
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With new national targets for patient flow in public hospitals designed to increase efficiencies in patient care and resource use, better knowledge of events affecting length of stay will support improved bed management and scheduling of procedures. This paper presents a case study involving the integration of material from each of three databases in operation at one tertiary hospital and demonstrates it is possible to follow patient journeys from admission to discharge. What is known about this topic? At present, patient data at one Queensland tertiary hospital are assembled in three information systems: (1) the Hospital Based Corporate Information System (HBCIS), which tracks patients from in-patient admission to discharge; (2) the Emergency Department Information System (EDIS) containing patient data from presentation to departure from the emergency department; and (3) Operation Room Management Information System (ORMIS), which records surgical operations. What does this paper add? This paper describes how a new enquiry tool may be used to link the three hospital information systems for studying the hospital journey through different wards and/or operating theatres for both individual and groups of patients. What are the implications for practitioners? An understanding of the patients’ journeys provides better insight into patient flow and provides the tool for research relating to access block, as well as optimising the use of physical and human resources.