985 resultados para Background Traffic Modeling
Resumo:
Standards for the construction of full-depth patching in portland cement concrete pavement usually require replacement of all deteriorated based materials with crushed stone, up to the bottom of the existing pavement layer. In an effort to reduce the time of patch construction and costs, the Iowa Department of Transportation and the Department of Civil, Construction and Environmental Engineering at Iowa State University studied the use of extra concrete depth as an option for base construction. This report compares the impact of additional concrete patching material depth on rate of strength gain, potential for early opening to traffic, patching costs, and long-term patch performance. This report also compares those characteristics in terms of early setting and standard concrete mixes. The results have the potential to change the method of Portland cement concrete pavement patch construction in Iowa.
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Building a personalized model to describe the drug concentration inside the human body for each patient is highly important to the clinical practice and demanding to the modeling tools. Instead of using traditional explicit methods, in this paper we propose a machine learning approach to describe the relation between the drug concentration and patients' features. Machine learning has been largely applied to analyze data in various domains, but it is still new to personalized medicine, especially dose individualization. We focus mainly on the prediction of the drug concentrations as well as the analysis of different features' influence. Models are built based on Support Vector Machine and the prediction results are compared with the traditional analytical models.
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The paper presents a competence-based instructional design system and a way to provide a personalization of navigation in the course content. The navigation aid tool builds on the competence graph and the student model, which includes the elements of uncertainty in the assessment of students. An individualized navigation graph is constructed for each student, suggesting the competences the student is more prepared to study. We use fuzzy set theory for dealing with uncertainty. The marks of the assessment tests are transformed into linguistic terms and used for assigning values to linguistic variables. For each competence, the level of difficulty and the level of knowing its prerequisites are calculated based on the assessment marks. Using these linguistic variables and approximate reasoning (fuzzy IF-THEN rules), a crisp category is assigned to each competence regarding its level of recommendation.
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Nuclear receptors are a major component of signal transduction in animals. They mediate the regulatory activities of many hormones, nutrients and metabolites on the homeostasis and physiology of cells and tissues. It is of high interest to model the corresponding regulatory networks. While molecular and cell biology studies of individual promoters have provided important mechanistic insight, a more complex picture is emerging from genome-wide studies. The regulatory circuitry of nuclear receptor regulated gene expression networks, and their response to cellular signaling, appear highly dynamic, and involve long as well as short range chromatin interactions. We review how progress in understanding the kinetics and regulation of cofactor recruitment, and the development of new genomic methods, provide opportunities but also a major challenge for modeling nuclear receptor mediated regulatory networks.
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It is commonly regarded that the overuse of traffic control devices desensitizes drivers and leads to disrespect, especially for low-volume secondary roads with limited enforcement. The maintenance of traffic signs is also a tort liability concern, exacerbated by unnecessary signs. The Federal Highway Administration’s (FHWA) Manual on Uniform Traffic Control Devices (MUTCD) and the Institute of Transportation Engineer’s (ITE) Traffic Control Devices Handbook provide guidance for the implementation of STOP signs based on expected compliance with right-of-way rules, provision of through traffic flow, context (proximity to other controlled intersections), speed, sight distance, and crash history. The approach(es) to stop is left to engineering judgment and is usually dependent on traffic volume or functional class/continuity of system. Although presently being considered by the National Committee on Traffic Control Devices, traffic volume itself is not given as a criterion for implementation in the MUTCD. STOP signs have been installed at many locations for various reasons which no longer (or perhaps never) met engineering needs. If in fact the presence of STOP signs does not increase safety, removal should be considered. To date, however, no guidance exists for the removal of STOP signs at two-way stop-controlled intersections. The scope of this research is ultra-low-volume (< 150 daily entering vehicles) unpaved intersections in rural agricultural areas of Iowa, where each of the 99 counties may have as many as 300 or more STOP sign pairs. Overall safety performance is examined as a function of a county excessive use factor, developed specifically for this study and based on various volume ranges and terrain as a proxy for sight distance. Four conclusions are supported: (1) there is no statistical difference in the safety performance of ultra-low-volume stop-controlled and uncontrolled intersections for all drivers or for younger and older drivers (although interestingly, older drivers are underrepresented at both types of intersections); (2) compliance with stop control (as indicated by crash performance) does not appear to be affected by the use or excessive use of STOP signs, even when adjusted for volume and a sight distance proxy; (3) crash performance does not appear to be improved by the liberal use of stop control; (4) safety performance of uncontrolled intersections appears to decline relative to stop-controlled intersections above about 150 daily entering vehicles. Subject to adequate sight distance, traffic professionals may wish to consider removal of control below this threshold. The report concludes with a section on methods and legal considerations for safe removal of stop control.
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PURPOSE: Aerodynamic drag plays an important role in performance for athletes practicing sports that involve high-velocity motions. In giant slalom, the skier is continuously changing his/her body posture, and this affects the energy dissipated in aerodynamic drag. It is therefore important to quantify this energy to understand the dynamic behavior of the skier. The aims of this study were to model the aerodynamic drag of alpine skiers in giant slalom simulated conditions and to apply these models in a field experiment to estimate energy dissipated through aerodynamic drag. METHODS: The aerodynamic characteristics of 15 recreational male and female skiers were measured in a wind tunnel while holding nine different skiing-specific postures. The drag and the frontal area were recorded simultaneously for each posture. Four generalized and two individualized models of the drag coefficient were built, using different sets of parameters. These models were subsequently applied in a field study designed to compare the aerodynamic energy losses between a dynamic and a compact skiing technique. RESULTS: The generalized models estimated aerodynamic drag with an accuracy of between 11.00% and 14.28%, and the individualized models estimated aerodynamic drag with an accuracy between 4.52% and 5.30%. The individualized model used for the field study showed that using a dynamic technique led to 10% more aerodynamic drag energy loss than using a compact technique. DISCUSSION: The individualized models were capable of discriminating different techniques performed by advanced skiers and seemed more accurate than the generalized models. The models presented here offer a simple yet accurate method to estimate the aerodynamic drag acting upon alpine skiers while rapidly moving through the range of positions typical to turning technique.
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The past four decades have witnessed an explosive growth in the field of networkbased facility location modeling. This is not at all surprising since location policy is one of the most profitable areas of applied systems analysis in regional science and ample theoretical and applied challenges are offered. Location-allocation models seek the location of facilities and/or services (e.g., schools, hospitals, and warehouses) so as to optimize one or several objectives generally related to the efficiency of the system or to the allocation of resources. This paper concerns the location of facilities or services in discrete space or networks, that are related to the public sector, such as emergency services (ambulances, fire stations, and police units), school systems and postal facilities. The paper is structured as follows: first, we will focus on public facility location models that use some type of coverage criterion, with special emphasis in emergency services. The second section will examine models based on the P-Median problem and some of the issues faced by planners when implementing this formulation in real world locational decisions. Finally, the last section will examine new trends in public sector facility location modeling.
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The Office of Transportation Data, in cooperation with the Federal Highway Administration, prepares this biennial traffic report. This report is used by federal, state, and local governmental agencies in determining highway needs, construction priorities, route location and environmental impact studies, and the application of appropriate design standards. The general public uses this information in determining the amount of traffic that passes a given area as they make their development plans and propose land use changes. The above reflects only a few of the many technical uses for this data.
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We implemented Biot-type porous wave equations in a pseudo-spectral numerical modeling algorithm for the simulation of Stoneley waves in porous media. Fourier and Chebyshev methods are used to compute the spatial derivatives along the horizontal and vertical directions, respectively. To prevent from overly short time steps due to the small grid spacing at the top and bottom of the model as a consequence of the Chebyshev operator, the mesh is stretched in the vertical direction. As a large benefit, the Chebyshev operator allows for an explicit treatment of interfaces. Boundary conditions can be implemented with a characteristics approach. The characteristic variables are evaluated at zero viscosity. We use this approach to model seismic wave propagation at the interface between a fluid and a porous medium. Each medium is represented by a different mesh and the two meshes are connected through the above described characteristics domain-decomposition method. We show an experiment for sealed pore boundary conditions, where we first compare the numerical solution to an analytical solution. We then show the influence of heterogeneity and viscosity of the pore fluid on the propagation of the Stoneley wave and surface waves in general.
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This paper presents a review of methodology for semi-supervised modeling with kernel methods, when the manifold assumption is guaranteed to be satisfied. It concerns environmental data modeling on natural manifolds, such as complex topographies of the mountainous regions, where environmental processes are highly influenced by the relief. These relations, possibly regionalized and nonlinear, can be modeled from data with machine learning using the digital elevation models in semi-supervised kernel methods. The range of the tools and methodological issues discussed in the study includes feature selection and semisupervised Support Vector algorithms. The real case study devoted to data-driven modeling of meteorological fields illustrates the discussed approach.
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OBJECTIVE To describe the scientific knowledge produced about trauma in the elderly caused by traffic accidents in healthcare area studies. METHODS Integrative review of studies from 2003 to 2013 searched in LILACS, SciELO, PubMed and CINHAL databases. We used combination of the descriptors injuries, wounds and accidents, in English, Portuguese and Spanish languages. RESULTS 32 studies were selected. In the thematic analysis, three categories emerged: epidemiological data from traffic accidents involving elderly; traffic accidents with elderly pedestrians; and trauma care in the elderly. We observed increased incidence of trauma in most countries and pedestrians represented a large part of the victims. Among these, the elderly are the most vulnerable group. CONCLUSION Studies showed that trauma care in the elderly need protocols and professionals with training in gerontology specialized in trauma care services.
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The methodology for generating a homology model of the T1 TCR-PbCS-K(d) class I major histocompatibility complex (MHC) class I complex is presented. The resulting model provides a qualitative explanation of the effect of over 50 different mutations in the region of the complementarity determining region (CDR) loops of the T cell receptor (TCR), the peptide and the MHC's alpha(1)/alpha(2) helices. The peptide is modified by an azido benzoic acid photoreactive group, which is part of the epitope recognized by the TCR. The construction of the model makes use of closely related homologs (the A6 TCR-Tax-HLA A2 complex, the 2C TCR, the 14.3.d TCR Vbeta chain, the 1934.4 TCR Valpha chain, and the H-2 K(b)-ovalbumine peptide), ab initio sampling of CDR loops conformations and experimental data to select from the set of possibilities. The model shows a complex arrangement of the CDR3alpha, CDR1beta, CDR2beta and CDR3beta loops that leads to the highly specific recognition of the photoreactive group. The protocol can be applied systematically to a series of related sequences, permitting the analysis at the structural level of the large TCR repertoire specific for a given peptide-MHC complex.