959 resultados para Multiple routes planning
Resumo:
Predicting safety on roadways is standard practice for road safety professionals and has a corresponding extensive literature. The majority of safety prediction models are estimated using roadway segment and intersection (microscale) data, while more recently efforts have been undertaken to predict safety at the planning level (macroscale). Safety prediction models typically include roadway, operations, and exposure variables—factors known to affect safety in fundamental ways. Environmental variables, in particular variables attempting to capture the effect of rain on road safety, are difficult to obtain and have rarely been considered. In the few cases weather variables have been included, historical averages rather than actual weather conditions during which crashes are observed have been used. Without the inclusion of weather related variables researchers have had difficulty explaining regional differences in the safety performance of various entities (e.g. intersections, road segments, highways, etc.) As part of the NCHRP 8-44 research effort, researchers developed PLANSAFE, or planning level safety prediction models. These models make use of socio-economic, demographic, and roadway variables for predicting planning level safety. Accounting for regional differences - similar to the experience for microscale safety models - has been problematic during the development of planning level safety prediction models. More specifically, without weather related variables there is an insufficient set of variables for explaining safety differences across regions and states. Furthermore, omitted variable bias resulting from excluding these important variables may adversely impact the coefficients of included variables, thus contributing to difficulty in model interpretation and accuracy. This paper summarizes the results of an effort to include weather related variables, particularly various measures of rainfall, into accident frequency prediction and the prediction of the frequency of fatal and/or injury degree of severity crash models. The purpose of the study was to determine whether these variables do in fact improve overall goodness of fit of the models, whether these variables may explain some or all of observed regional differences, and identifying the estimated effects of rainfall on safety. The models are based on Traffic Analysis Zone level datasets from Michigan, and Pima and Maricopa Counties in Arizona. Numerous rain-related variables were found to be statistically significant, selected rain related variables improved the overall goodness of fit, and inclusion of these variables reduced the portion of the model explained by the constant in the base models without weather variables. Rain tends to diminish safety, as expected, in fairly complex ways, depending on rain frequency and intensity.
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A substantial body of research is focused on understanding the relationships between socio-demographics, land-use characteristics, and mode specific attributes on travel mode choice and time-use patterns. Residential and commercial densities, inter-mixing of land uses, and route directness in conjunction with transportation performance characteristics interact to influence accessibility to destinations as well as time spent traveling and engaging in activities. This study uniquely examines the activity durations undertaken for out-of-home subsistence; maintenance, and discretionary activities. Also examined are total tour durations (summing all activity categories within a tour). Cross-sectional activities are obtained from household activity travel survey data from the Atlanta Metropolitan Region. Time durations allocated to weekdays and weekends are compared. The censoring and endogeneity between activity categories and within individuals are captured using multiple equations Tobit models. The analysis and modeling reveal that land-use characteristics such as net residential density and the number of commercial parcels within a kilometer of a residence are associated with differences in weekday and weekend time-use allocations. Household type and structure are significant predictors across the three activity categories, but not for overall travel times. Tour characteristics such as time-of-day and primary travel mode of the tours also affect traveler's out-of-home activity-tour time-use patterns.
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At least two important transportation planning activities rely on planning-level crash prediction models. One is motivated by the Transportation Equity Act for the 21st Century, which requires departments of transportation and metropolitan planning organizations to consider safety explicitly in the transportation planning process. The second could arise from a need for state agencies to establish incentive programs to reduce injuries and save lives. Both applications require a forecast of safety for a future period. Planning-level crash prediction models for the Tucson, Arizona, metropolitan region are presented to demonstrate the feasibility of such models. Data were separated into fatal, injury, and property-damage crashes. To accommodate overdispersion in the data, negative binomial regression models were applied. To accommodate the simultaneity of fatality and injury crash outcomes, simultaneous estimation of the models was conducted. All models produce crash forecasts at the traffic analysis zone level. Statistically significant (p-values < 0.05) and theoretically meaningful variables for the fatal crash model included population density, persons 17 years old or younger as a percentage of the total population, and intersection density. Significant variables for the injury and property-damage crash models were population density, number of employees, intersections density, percentage of miles of principal arterial, percentage of miles of minor arterials, and percentage of miles of urban collectors. Among several conclusions it is suggested that planning-level safety models are feasible and may play a role in future planning activities. However, caution must be exercised with such models.
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The Intermodal Surface Transportation Efficiency Act (ISTEA) of 1991 mandated the consideration of safety in the regional transportation planning process. As part of National Cooperative Highway Research Program Project 8-44, "Incorporating Safety into the Transportation Planning Process," we conducted a telephone survey to assess safety-related activities and expertise at Governors Highway Safety Associations (GHSAs), and GHSA relationships with metropolitan planning organizations (MPOs) and state departments of transportation (DOTs). The survey results were combined with statewide crash data to enable exploratory modeling of the relationship between GHSA policies and programs and statewide safety. The modeling objective was to illuminate current hurdles to ISTEA implementation, so that appropriate institutional, analytical, and personnel improvements can be made. The study revealed that coordination of transportation safety across DOTs, MPOs, GHSAs, and departments of public safety is generally beneficial to the implementation of safety. In addition, better coordination is characterized by more positive and constructive attitudes toward incorporating safety into planning.
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Open access reforms to railway regulations allow multiple train operators to provide rail services on a common infrastructure. As railway operations are now independently managed by different stakeholders, conflicts in operations may arise, and there have been attempts to derive an effective access charge regime so that these conflicts may be resolved. One approach is by direct negotiation between the infrastructure manager and the train service providers. Despite the substantial literature on the topic, few consider the benefits of employing computer simulation as an evaluation tool for railway operational activities such as access pricing. This article proposes a multi-agent system (MAS) framework for the railway open market and demonstrates its feasibility by modelling the negotiation between an infrastructure provider and a train service operator. Empirical results show that the model is capable of resolving operational conflicts according to market demand.
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Background: The first sign of developing multiple sclerosis is a clinically isolated syndrome that resembles a multiple sclerosis relapse. Objective/methods: The objective was to review the clinical trials of two medicines in clinically isolated syndromes (interferon β and glatiramer acetate) to determine whether they prevent progression to definite multiple sclerosis. Results: In the BENEFIT trial, after 2 years, 45% of subjects in the placebo group developed clinically definite multiple sclerosis, and the rate was lower in the interferon β-1b group. Then all subjects were offered interferon β-1b, and the original interferon β-1b group became the early treatment group, and the placebo group became the delayed treatment group. After 5 years, the number of subjects with clinical definite multiple sclerosis remained lower in the early treatment than late treatment group. In the PreCISe trial, after 2 years, the time for 25% of the subjects to convert to definite multiple sclerosis was prolonged in the glatiramer group. Conclusions: Interferon β-1b and glatiramer acetate slow the progression of clinically isolated syndromes to definite multiple sclerosis. However, it is not known whether this early treatment slows the progression to the physical disabilities experienced in multiple sclerosis.
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Background: Most people with multiple sclerosis have the relapsing-remitting type. Objective/methods: The objective was to evaluate two clinical trials of fingolimod in relapsing multiple sclerosis. Results: FREEDOMS (FTY720 Research Evaluation Effects of Daily Oral therapy in Multiple Sclerosis), a Phase III placebo-controlled trial, showed that fingolimod (0.5 or 1.25 mg) reduced the relapse rate and disability in multiple sclerosis, compared to placebo. Fingolimod (0.5 or 1.25 mg) has been compared to interferon β-1a in a Phase III clinical trial (TRANSFORMS; Trial Assessing Injectable Interferon versus FTY720 Oral in Relapsing-Remitting Multiple Sclerosis) and shown to be more efficacious than interferon β-1a in reducing relapse rates. However, fingolimod did increase the risk of infections and skin cancers. Conclusions: Only the lower dose of fingolimod (0.5 mg), which possibly has less toxicity, should be considered for prevention of relapses in relapsing-remitting multiple sclerosis.
Resumo:
Most infrastructure project developments are complex in nature, particularly in the planning phase. During this stage, many vague alternatives are tabled - from the strategic to operational level. Human judgement and decision making are characterised by biases, errors and the use of heuristics. These factors are intangible and hard to measure because they are subjective and qualitative in nature. The problem with human judgement becomes more complex when a group of people are involved. The variety of different stakeholders may cause conflict due to differences in personal judgements. Hence, the available alternatives increase the complexities of the decision making process. Therefore, it is desirable to find ways of enhancing the efficiency of decision making to avoid misunderstandings and conflict within organisations. As a result, numerous attempts have been made to solve problems in this area by leveraging technologies such as decision support systems. However, most construction project management decision support systems only concentrate on model development and neglect fundamentals of computing such as requirement engineering, data communication, data management and human centred computing. Thus, decision support systems are complicated and are less efficient in supporting the decision making of project team members. It is desirable for decision support systems to be simpler, to provide a better collaborative platform, to allow for efficient data manipulation, and to adequately reflect user needs. In this chapter, a framework for a more desirable decision support system environment is presented. Some key issues related to decision support system implementation are also described.
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BLAST Atlas is a visual analysis system for comparative genomics that supports genome-wide gene characterisation, functional assignment and function-based browsing of one or more chromosomes. Inspired by applications such as the WorldWide Telescope, Bing Maps 3D and Google Earth, BLAST Atlas uses novel three-dimensional gene and function views that provide a highly interactive and intuitive way for scientists to navigate, query and compare gene annotations. The system can be used for gene identification and functional assignment or as a function-based multiple genome comparison tool which complements existing position based comparison and alignment viewers.
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The field of collaborative health planning faces significant challenges due to the lack of effective information, systems and the absence of a framework to make informed decisions. These challenges have been magnified by the rise of the healthy cities movement, consequently, there have been more frequent calls for localised, collaborative and evidence-driven decision-making. Some studies in the past have reported that the use of decision support systems (DSS) for planning healthy cities may lead to: increase collaboration between stakeholders and the general public, improve the accuracy and quality of the decision-making processes and improve the availability of data and information for health decision-makers. These links have not yet been fully tested and only a handful of studies have evaluated the impact of DSS on stakeholders, policy-makers and health planners. This study suggests a framework for developing healthy cities and introduces an online Geographic Information Systems (GIS)-based DSS for improving the collaborative health planning. It also presents preliminary findings of an ongoing case study conducted in the Logan-Beaudesert region of Queensland, Australia. These findings highlight the perceptions of decision-making prior to the implementation of the DSS intervention. Further, the findings help us to understand the potential role of the DSS to improve collaborative health planning practice.
Resumo:
The field of collaborative health planning faces significant challenges posed by the lack of effective information, systems and a framework to organise that information. Such a framework is critical in order to make accessible and informed decisions for planning healthy cities. The challenges have been exaggerated by the rise of the healthy cities movement, as a result of which, there have been more frequent calls for localised, collaborative and evidence-based decision-making. Some studies suggest that the use of ICT-based tools in health planning may lead to: increased collaboration between stakeholder sand the community; improve the accuracy and quality of the decision making process; and, improve the availability of data and information for health decision-makers as well as health service planners. Research has justified the use of decision support systems (DSS) in planning for healthy cities as these systems have been found to improve the planning process. DSS are information communication technology (ICT) tools including geographic information systems (GIS) that provide the mechanisms to help decision-makers and related stake holders assess complex problems and solve these in a meaningful way. Consequently, it is now more possible than ever before to make use of ICT-based tools in health planning. However, knowledge about the nature and use of DSS within collaborative health planning is relatively limited. In particular, little research has been conducted in terms of evaluating the impact of adopting these tools upon stakeholders, policy-makers and decision-makers within the health planning field. This paper presents an integrated method that has been developed to facilitate an informed decision-making process to assist in the health planning process. Specifically, the paper describes the participatory process that has been adopted to develop an online GIS-based DSS for health planners. The literature states that the overall aim of DSS is to improve the efficiency of the decisions made by stakeholders, optimising their overall performance and minimizing judgmental biases. For this reason, the paper examines the effectiveness and impact of an innovative online GIS-based DSS on health planners. The case study of the online DSS is set within a unique settings-based initiative designed to plan for and improve the health capacity of Logan-Beaudesert area, Australia. This unique setting-based initiative is named the Logan-Beaudesert Health Coalition (LBHC).The paper outlines the impact occurred by implementing the ICT-based DSS. In conclusion, the paper emphasizes upon the need for the proposed tool for enhancing health planning.
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Purpose: To provide recommendations for construction clients who design and implement financial incentive mechanisms (FIMs) on projects. ---------- Methodology: Four large Australian building projects commissioned by government clients under managing contractor contracts and completed between 2001 and 2005 were examined to explore the ‘drivers’ that promoted motivation toward financial incentive goals. The results were triangulated across data sources, projects and stakeholder types. ---------- Findings: FIM design should incorporate: 1. flexibility to modify goals and measurement procedures over time, 2. multiple goals covering different project areas, 3. distribution of rewards across all the key organizations contributing to team performance (e.g. potentially not just the contractor, but the subcontractors and consultants) and a reward amount sufficient to be valued by potential recipients. FIM benefits are maximized through the following complementary procurement initiatives: 4. equitable contract risk allocation, 5. early contractor involvement in design, 6. value-driven tender selection, 7. relationship workshops, and 8. future work opportunities.---------- Research Limitations: This paper provides practical recommendations to industry and hence does not emphasize theoretical aspects.---------- Practical Implications: The uptake of these recommendations is likely to increase the impact of FIMs on motivation and improve project and industry outcomes. Although the study focuses on government clients of building projects, all the recommendations would seem to apply equally to private-sector clients and to non-building projects.---------- Originality: In order to improve motivation and reward high performance, clients are increasingly using FIM in their construction contracts. Despite the rising use of financial incentives, there is a lack of comprehensive construction-specific knowledge available to help clients maximize outcomes. The study addresses this gap in the literature.
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Recent epidemiologic studies have suggested that ultraviolet radiation (UV) may protect against non-Hodgkin lymphoma (NHL), but few, if any, have assessed multiple indicators of ambient and personal UV exposure. Using the US Radiologic Technologists study, we examined the association between NHL and self-reported time outdoors in summer, as well as average year-round and seasonal ambient exposures based on satellite estimates for different age periods, and sun susceptibility in participants who had responded to two questionnaires (1994–1998, 2003–2005) and who were cancer-free as of the earlier questionnaire. Using unconditional logistic regression, we estimated the odds ratio (OR) and 95% confidence intervals for 64,103 participants with 137 NHL cases. Self-reported time outdoors in summer was unrelated to risk. Lower risk was somewhat related to higher average year-round and winter ambient exposure for the period closest in time, and prior to, diagnosis (ages 20–39). Relative to 1.0 for the lowest quartile of average year-round ambient UV, the estimated OR for successively higher quartiles was 0.68 (0.42–1.10); 0.82 (0.52–1.29); and 0.64 (0.40–1.03), p-trend = 0.06), for this age period. The lower NHL risk associated with higher year-round average and winter ambient UV provides modest additional support for a protective relationship between UV and NHL.
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Symmetric multi-processor (SMP) systems, or multiple-CPU servers, are suitable for implementing parallel algorithms because they employ dedicated communication devices to enhance the inter-processor communication bandwidth, so that a better performance can be obtained. However, the cost for a multiple-CPU server is high and therefore, the server is usually shared among many users. The work-load due to other users will certainly affect the performance of the parallel programs so it is desirable to derive a method to optimize parallel programs under different loading conditions. In this paper, we present a simple method, which can be applied in SPMD type parallel programs, to improve the speedup by controlling the number of threads within the programs.
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Background Delivering effective multiple health behavior interventions to large numbers of adults with chronic conditions via primary care settings is a public health priority. Purpose Within a 12-month, telephone-delivered diet and physical activity intervention with multiple behavioral outcomes, we examined the extent and co-variation of multiple health behavior change. Methods A cluster-randomized trial with 434 patients with type 2 diabetes or hypertension were recruited from 10 general practices, which were randomized to receive telephone counseling or usual care. Results Those receiving telephone counseling were significantly more likely than those in usual care to make greater reductions in multiple behaviors after adjusting for baseline risk behaviors (OR 2.42; 95%CI 1.43, 4.11). Controlling for baseline risk and group allocation, making changes to either physical activity, fat, vegetable, or fiber intake was associated with making significantly more improvements in other behaviors. Conclusions For patients with chronic conditions, telephone counseling can significantly improve multiple health behaviors, with behavioral changes tending to co-vary.