970 resultados para variance ration method


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The modal strain energy method, which depends on the vibration characteristics of the structure, has been reasonably successful in identifying and localising damage in the structure. However, existing strain energy methods require the first few modes to be measured to provide meaningful damage detection. Use of individual modes with existing strain energy methods may indicate false alarms or may not detect the damage at or near the nodal points. This paper proposes a new modal strain energy based damage index which can detect and localize the damage using any one of the modes measured and illustrates its application for beam structures. It becomes evident that the proposed strain energy based damage index also has potential for damage quantification.

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The literature was reviewed and analyzed to determine the feasibility of using a combination of acid hydrolysis and CO2-C release during long-term incubation to determine soil organic carbon (SOC) pool sizes and mean residence times (MRTs). Analysis of 1100 data points showed the SOC remaining after hydrolysis with 6 M HCI ranged from 30 to 80% of the total SOC depending on soil type, depth, texture, and management. Nonhydrolyzable carbon (NHC) in conventional till soils represented 48% of SOC; no-till averaged 56%, forest 55%, and grassland 56%. Carbon dates showed an average of 1200 yr greater MRT for the NHC fraction than total SOC. Longterm incubation, involving measurement of CO2 evolution and curve fitting, measured active and slow pools. Active-pool C comprised 2 to 8% of the SOC with MRTs of days to months; the slow pool comprised 45 to 65% of the SOC and had MRTs of 10 to 80 yr. Comparison of field C-14 and (13) C data with hydrolysis-incubation data showed a high correlation between independent techniques across soil types and experiments. There were large differences in MRTs depending on the length of the experiment. Insertion of hydrolysis-incubation derived estimates of active (C-a), slow (C-s), and resistant Pools (C-r) into the DAYCENT model provided estimates of daily field CO2 evolution rates. These were well correlated with field CO2 measurements. Although not without some interpretation problems, acid hydrolysis-laboratory incubation is useful for determining SOC pools and fluxes especially when used in combination with associated measurements.

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Grassland management affects soil organic carbon (SOC) storage and can be used to mitigate greenhouse gas emissions. However, for a country to assess emission reductions due to grassland management, there must be an inventory method for estimating the change in SOC storage. The Intergovernmental Panel on Climate Change (IPCC) has developed a simple carbon accounting approach for this purpose, and here we derive new grassland management factors that represent the effect of changing management on carbon storage for this method. Our literature search identified 49 studies dealing with effects of management practices that either degraded or improved conditions relative to nominally managed grasslands. On average, degradation reduced SOC storage to 95% +/- 0.06 and 97% +/- 0.05 of carbon stored under nominal conditions in temperate and tropical regions, respectively. In contrast, improving grasslands with a single management activity enhanced SOC storage by 14% 0.06 and 17% +/- 0.05 in temperate and tropical regions, respectively, and with an additional improvement(s), storage increased by another 11% +/- 0.04. We applied the newly derived factor coefficients to analyze C sequestration potential for managed grasslands in the U.S., and found that over a 20-year period changing management could sequester from 5 to 142 Tg C yr(-1) or 0.1 to 0.9 Mg C ha(-1) yr(-1), depending on the level of change. This analysis provides revised factor coefficients for the IPCC method that can be used to estimate impacts of management; it also provides a methodological framework for countries to derive factor coefficients specific to conditions in their region.

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Fractional Fokker-Planck equations (FFPEs) have gained much interest recently for describing transport dynamics in complex systems that are governed by anomalous diffusion and nonexponential relaxation patterns. However, effective numerical methods and analytic techniques for the FFPE are still in their embryonic state. In this paper, we consider a class of time-space fractional Fokker-Planck equations with a nonlinear source term (TSFFPE-NST), which involve the Caputo time fractional derivative (CTFD) of order α ∈ (0, 1) and the symmetric Riesz space fractional derivative (RSFD) of order μ ∈ (1, 2). Approximating the CTFD and RSFD using the L1-algorithm and shifted Grunwald method, respectively, a computationally effective numerical method is presented to solve the TSFFPE-NST. The stability and convergence of the proposed numerical method are investigated. Finally, numerical experiments are carried out to support the theoretical claims.

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Statistical modeling of traffic crashes has been of interest to researchers for decades. Over the most recent decade many crash models have accounted for extra-variation in crash counts—variation over and above that accounted for by the Poisson density. The extra-variation – or dispersion – is theorized to capture unaccounted for variation in crashes across sites. The majority of studies have assumed fixed dispersion parameters in over-dispersed crash models—tantamount to assuming that unaccounted for variation is proportional to the expected crash count. Miaou and Lord [Miaou, S.P., Lord, D., 2003. Modeling traffic crash-flow relationships for intersections: dispersion parameter, functional form, and Bayes versus empirical Bayes methods. Transport. Res. Rec. 1840, 31–40] challenged the fixed dispersion parameter assumption, and examined various dispersion parameter relationships when modeling urban signalized intersection accidents in Toronto. They suggested that further work is needed to determine the appropriateness of the findings for rural as well as other intersection types, to corroborate their findings, and to explore alternative dispersion functions. This study builds upon the work of Miaou and Lord, with exploration of additional dispersion functions, the use of an independent data set, and presents an opportunity to corroborate their findings. Data from Georgia are used in this study. A Bayesian modeling approach with non-informative priors is adopted, using sampling-based estimation via Markov Chain Monte Carlo (MCMC) and the Gibbs sampler. A total of eight model specifications were developed; four of them employed traffic flows as explanatory factors in mean structure while the remainder of them included geometric factors in addition to major and minor road traffic flows. The models were compared and contrasted using the significance of coefficients, standard deviance, chi-square goodness-of-fit, and deviance information criteria (DIC) statistics. The findings indicate that the modeling of the dispersion parameter, which essentially explains the extra-variance structure, depends greatly on how the mean structure is modeled. In the presence of a well-defined mean function, the extra-variance structure generally becomes insignificant, i.e. the variance structure is a simple function of the mean. It appears that extra-variation is a function of covariates when the mean structure (expected crash count) is poorly specified and suffers from omitted variables. In contrast, when sufficient explanatory variables are used to model the mean (expected crash count), extra-Poisson variation is not significantly related to these variables. If these results are generalizable, they suggest that model specification may be improved by testing extra-variation functions for significance. They also suggest that known influences of expected crash counts are likely to be different than factors that might help to explain unaccounted for variation in crashes across sites

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This paper outlines a method of constructing narratives about an individual’s self-efficacy. Self-efficacy is defined as “people’s judgments of their capabilities to organise and execute courses of action required to attain designated types of performances” (Bandura, 1986, p. 391), and as such represents a useful construct for thinking about personal agency. Social cognitive theory provides the theoretical framework for understanding the sources of self-efficacy, that is, the elements that contribute to a sense of self-efficacy. The narrative approach adopted offers an alternative to traditional, positivist psychology, characterised by a preoccupation with measuring psychological constructs (like self-efficacy) by means of questionnaires and scales. It is argued that these instruments yield scores which are somewhat removed from the lived experience of the person—respondent or subject—associated with the score. The method involves a cyclical and iterative process using qualitative interviews to collect data from participants – four mature aged university students. The method builds on a three-interview procedure designed for life history research (Dolbeare & Schuman, cited in Seidman, 1998). This is achieved by introducing reflective homework tasks, as well as written data generated by research participants, as they are guided in reflecting on those experiences (including behaviours, cognitions and emotions) that constitute a sense of self-efficacy, in narrative and by narrative. The method illustrates how narrative analysis is used “to produce stories as the outcome of the research” (Polkinghorne, 1995, p.15), with detail and depth contributing to an appreciation of the ‘lived experience’ of the participants. The method is highly collaborative, with narratives co-constructed by researcher and research participants. The research outcomes suggest an enhanced understanding of self-efficacy contributes to motivation, application of effort and persistence in overcoming difficulties. The paper concludes with an evaluation of the research process by the students who participated in the author’s doctoral study.

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In rural low-voltage networks, distribution lines are usually highly resistive. When many distributed generators are connected to such lines, power sharing among them is difficult when using conventional droop control, as the real and reactive power have strong coupling with each other. A high droop gain can alleviate this problem but may lead the system to instability. To overcome4 this, two droop control methods are proposed for accurate load sharing with frequency droop controller. The first method considers no communication among the distributed generators and regulates the output voltage and frequency, ensuring acceptable load sharing. The droop equations are modified with a transformation matrix based on the line R/X ration for this purpose. The second proposed method, with minimal low bandwidth communication, modifies the reference frequency of the distributed generators based on the active and reactive power flow in the lines connected to the points of common coupling. The performance of these two proposed controllers is compared with that of a controller, which includes an expensive high bandwidth communication system through time-domain simulation of a test system. The magnitude of errors in power sharing between these three droop control schemes are evaluated and tabulated.

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Aim: This paper is a report of a study conducted to determine the effectiveness of a community case management collaborative education intervention in terms of satisfaction, learning and performance among public health nurses. Background: Previous evaluation studies of case management continuing professional education often failed to demonstrate effectiveness across a range of outcomes and had methodological weaknesses such as small convenience samples and lack of control groups. Method: A cluster randomised controlled trial was conducted between September 2005 and February 2006. Ten health centre clusters (5 control, 5 intervention) recruited 163 public health nurses in Taiwan to the trial. After pre-tests for baseline measurements, public health nurses in intervention centres received an educational intervention of four half-day workshops. Post-tests for both groups were conducted after the intervention. Two-way repeated measures analysis of variance was performed to evaluate the effect of the intervention on target outcomes. Results: A total of 161 participants completed the pre- and post-intervention measurements. This was almost a 99% response rate. Results revealed that 97% of those in the experimental group were satisfied with the programme. There were statistically significant differences between the two groups in knowledge (p = 0.001), confidence in case management skills (p = 0.001), preparedness for case manager role activities (p = 0.001), self-reported frequency in using skills (p = 0.001), and role activities (p = 0.004). Conclusion: Collaboration between academic and clinical nurses is an effective strategy to prepare nurses for rapidly-changing roles.

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Proper application of sunscreen is essential as an effective public health strategy for skin cancer prevention. Insufficient application is common among sunbathers, results in decreased sun protection and may therefore lead to increased UV damage of the skin. However, no objective measure of sunscreen application thickness (SAT) is currently available for field-based use. We present a method to detect SAT on human skin for determining the amount of sunscreen applied and thus enabling comparisons to manufacturer recommendations. Using a skin swabbing method and subsequent spectrophotometric analysis, we were able to determine SAT on human skin. A swabbing method was used to derive SAT on skin (in mg sunscreen per cm2 of skin area) through the concentration–absorption relationship of sunscreen determined in laboratory experiments. Analysis differentiated SATs between 0.25 and 4 mg cm−2 and showed a small but significant decrease in concentration over time postapplication. A field study was performed, in which the heterogeneity of sunscreen application could be investigated. The proposed method is a low cost, noninvasive method for the determination of SAT on skin and it can be used as a valid tool in field- and population-based studies.

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Extensive groundwater withdrawal has resulted in a severe seawater intrusion problem in the Gooburrum aquifers at Bundaberg, Queensland, Australia. Better management strategies can be implemented by understanding the seawater intrusion processes in those aquifers. To study the seawater intrusion process in the region, a two-dimensional density-dependent, saturated and unsaturated flow and transport computational model is used. The model consists of a coupled system of two non-linear partial differential equations. The first equation describes the flow of a variable-density fluid, and the second equation describes the transport of dissolved salt. A two-dimensional control volume finite element model is developed for simulating the seawater intrusion into the heterogeneous aquifer system at Gooburrum. The simulation results provide a realistic mechanism by which to study the convoluted transport phenomena evolving in this complex heterogeneous coastal aquifer.

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This study investigates the application of local search methods on the railway junction traffic conflict-resolution problem, with the objective of attaining a quick and reasonable solution. A procedure based on local search relies on finding a better solution than the current one by a search in the neighbourhood of the current one. The structure of neighbourhood is therefore very important to an efficient local search procedure. In this paper, the formulation of the structure of the solution, which is the right-of-way sequence assignment, is first described. Two new neighbourhood definitions are then proposed and the performance of the corresponding local search procedures is evaluated by simulation. It has been shown that they provide similar results but they can be used to handle different traffic conditions and system requirements.

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There is a need for educational frameworks for computer ethics education. This discussion paper presents an approach to developing students’ moral sensitivity, an awareness of morally relevant issues, in project-based learning (PjBL). The proposed approach is based on a study of IT professionals’ levels of awareness of ethics. These levels are labelled My world, The corporate world, A shared world, The client’s world and The wider world. We give recommendations for how instructors may stimulate students’ thinking with the levels and how the levels may be taken into account in managing a project course and in an IS department. Limitations of the recommendations are assessed and issues for discussion are raised.

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There is a renaissance of interest in public service motivation in public management research. Moynnihan and Pandey (2007) assert that public service motivation (PSM) has significant practical relevance as it deals with the relationship between motivation and the public interest. There is a need to explore employee needs generated by public service motivation in order to attract and retain a high calibre cadre of public servants (Gabris & Simo, 1995). Such exploration is particularly important beyond the American context which has dominated the literature to date (Taylor, 2007; Vandenabeele, Scheepers, & Hondeghem, 2006; Vandenabeele & Van de Walle, 2008).

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The problem of delays in the construction industry is a global phenomenon and the construction industry in Brunei Darussalam is no exception. The goal of all parties involved in construction projects – owners, contractors, engineers and consultants in either the public or private sector is to successfully complete the project on schedule, within planned budget, with the highest quality and in the safest manner. Construction projects are frequently influenced by either success factors that help project parties reach their goal as planned, or delay factors that stifle or postpone project completion. The purpose of this research is to identify success and delay factors which can help project parties reach their intended goals with greater efficiency. This research extracted seven of the most important success factors according to the literature and seven of the most important delay factors identified by project parties, and then examined correlations between them to determine which were the most influential in preventing project delays. This research uses a comprehensive literature review to design and conduct a survey to investigate success and delay factors and then obtain a consensus of expert opinion using the Delphi methodology to rank the most needed critical success factors for Brunei construction projects. A specific survey was distributed to owners, contractors and engineers to examine the most critical delay factors. A general survey was distributed to examine the correlation between the identified delay factors and the seven most important critical success factors selected. A consensus of expert opinion using the Delphi methodology was used to rank the most needed critical success factors for Brunei building construction. Data was collected and evaluated by statistical methods to identify the most significant causes of delay and to measure the strength and direction of the relationship between critical success factors and delay factors in order to examine project parties’ evaluation of projects’ critical success and delay factors, and to evaluate the influence of critical success factors on critical delay factors. A relative importance index has been used to determine the relative importance of the various causes of delays. A one and two-way analysis of variance (ANOVA) has been used to examine how the group or groups evaluated the influence of the critical success factors in avoiding or preventing each of the delay factors, and which success factors were perceived as most influential in avoiding or preventing critical delay factors. Finally the Delphi method, using consensus from an expert panel, was employed to identify the seven most critical success factors used to avoid the delay factors, and thereby improve project performance.