990 resultados para Use of ICT


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The removal of toxic anions has been achieved using hydrotalcite via two methods: (1) coprecipitation and (2) thermal activation. Hydrotalcite formed via the coprecipitation method, using solutions containing arsenate and vanadate up to pH 10, are able to remove more than 95% of the toxic anions (0.2 M) from solution. The removal of toxic anions in solutions with a pH of >10 reduces the removal uptake percentage to 75%. Raman spectroscopy observed multiple A1 stretching modes of V−O and As−O at 930 and 810 cm−1, assigned to vanadate and arsenate, respectively. Analysis of the intensity and position of the A1 stretching modes helped to identify the vanadate and arsenate specie intercalated into the hydrotalcite structure. It has been determined that 3:1 hydrotalcite structure predominantly intercalate anions into the interlayer region, while the 2:1 and 4:1 hydrotalcite structures shows a large portion of anions being removed from solution by adsorption processes. Treatment of carbonate solutions (0.2 M) containing arsenate and vanadate (0.2 M) three times with thermally activated hydrotalcite has been shown to remove 76% and 81% of the toxic anions, respectively. Thermally activated hydrotalcite with a Mg:Al ratio of 2:1, 3:1, and 4:1 have all been shown to remove 95% of arsenate and vanadate (25 ppm). At increased concentrations of arsenate and vanadate, the removal uptake percentage decreased significantly, except for the 4:1 thermally activated hydrotalcite. Thermally activated Bayer hydrotalcite has also been shown to be highly effective in the removal of arsenate and vanadate. The thermal activation of the solid residue component (red mud) removes 30% of anions from solution (100 ppm of both anions), while seawater-neutralized red mud removes 70%. The formation of hydrotalcite during the seawater neutralization process removes anions via two mechanisms, rather than one observed for thermally activated red mud.

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The Georgia Institute of Technology is currently performing research that will result in the development and deployment of three instrumentation packages that allow for automated capture of personal travel-related data for a given time period (up to 10 days). These three packages include: A handheld electronic travel diary (ETD) with Global Positioning System (GPS) capabilities to capture trip information for all modes of travel; A comprehensive electronic travel monitoring system (CETMS), which includes an ETD, a rugged laptop computer, a GPS receiver and antenna, and an onboard engine monitoring system, to capture all trip and vehicle information; and a passive GPS receiver, antenna, and data logger to capture vehicle trips only.

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In this paper we propose a new method for utilising phase information by complementing it with traditional magnitude-only spectral subtraction speech enhancement through Complex Spectrum Subtraction (CSS). The proposed approach has the following advantages over traditional magnitude-only spectral subtraction: (a) it introduces complementary information to the enhancement algorithm; (b) it reduces the total number of algorithmic parameters, and; (c) is designed for improving clean speech magnitude spectra and is therefore suitable for both automatic speech recognition (ASR) and speech perception applications. Oracle-based ASR experiments verify this approach, showing an average of 20% relative word accuracy improvements when accurate estimates of the phase spectrum are available. Based on sinusoidal analysis and assuming stationarity between observations (which is shown to be better approximated as the frame rate is increased), this paper also proposes a novel method for acquiring the phase information called Phase Estimation via Delay Projection (PEDEP). Further oracle ASR experiments validate the potential for the proposed PEDEP technique in ideal conditions. Realistic implementation of CSS with PEDEP shows performance comparable to state of the art spectral subtraction techniques in a range of 15-20 dB signal-to-noise ratio environments. These results clearly demonstrate the potential for using phase spectra in spectral subtractive enhancement applications, and at the same time highlight the need for deriving more accurate phase estimates in a wider range of noise conditions.

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This project discusses a component of the research study conducted to provide construction organizations with a generic benchmarking framework to assess their extent of information communication technology (ICT) adoption for building project management processes. It defines benchmarking and discusses objectives of the required benchmarking framework and development of the framework. The study focuses on ICT adoption by small and medium enterprises (SMEs) in the construction industry and with respect to SMEs it is important to understand processes, their indicators, and measures in the local context. Structure of the suggested benchmarking framework has been derived after extensive literature survey and a questionnaire survey conducted in the Indian construction industry. The suggested benchmarking process is an iterative process divided into four stages. It can be implemented at organization and industry levels for rating the construction organizations for ICT adoption and performance measurement. The framework has a generic structure and can be generalized and applied for other countries with due considerations.

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Expert panels have been used extensively in the development of the "Highway Safety Manual" to extract research information from highway safety experts. While the panels have been used to recommend agendas for new and continuing research, their primary role has been to develop accident modification factors—quantitative relationships between highway safety and various highway safety treatments. Because the expert panels derive quantitative information in a “qualitative” environment and because their findings can have significant impacts on highway safety investment decisions, the expert panel process should be described and critiqued. This paper is the first known written description and critique of the expert panel process and is intended to serve professionals wishing to conduct such panels.

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A novel application of the popular web instruction architecture Blackboard Academic Suite® is described. The method was applied to a large number of students to assess quantitatively the accuracy of each student’s laboratory skills. The method provided immediate feedback to students on their personal skill level, replaced labour-intensive scrutiny of laboratory skills by teaching staff and identified immediately those students requiring further individual assistance in mastering the skill under evaluation. The method can be used for both formative and summative assessment. When used formatively, the assessment can be repeated by the student without penalty until the skill is mastered. When used for summative assessment, the method can save the teacher much time and effort in assessing laboratory skills of vital importance to students in the real world.

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Background For CAM to feature prominently in health care decision-making there is a need to expand the evidence-base and to further incorporate economic evaluation into research priorities. In a world of scarce health care resources and an emphasis on efficiency and clinical efficacy, CAM, as indeed do all other treatments, requires rigorous evaluation to be considered in budget decision-making. Methods Economic evaluation provides the tools to measure the costs and health consequences of CAM interventions and thereby inform decision making. This article offers CAM researchers an introductory framework for understanding, undertaking and disseminating economic evaluation. The types of economic evaluation available for the study of CAM are discussed, and decision modelling is introduced as a method for economic evaluation with much potential for use in CAM. Two types of decision models are introduced, decision trees and Markov models, along with a worked example of how each method is used to examine costs and health consequences. This is followed by a discussion of how this information is used by decision makers. Conclusions Undoubtedly, economic evaluation methods form an important part of health care decision making. Without formal training it can seem a daunting task to consider economic evaluation, however, multidisciplinary teams provide an opportunity for health economists, CAM practitioners and other interested researchers, to work together to further develop the economic evaluation of CAM.