968 resultados para Nikitin, Ivan Savvich, 1824-1861


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There has been considerable research conducted over the last 20 years focused on predicting motor vehicle crashes on transportation facilities. The range of statistical models commonly applied includes binomial, Poisson, Poisson-gamma (or negative binomial), zero-inflated Poisson and negative binomial models (ZIP and ZINB), and multinomial probability models. Given the range of possible modeling approaches and the host of assumptions with each modeling approach, making an intelligent choice for modeling motor vehicle crash data is difficult. There is little discussion in the literature comparing different statistical modeling approaches, identifying which statistical models are most appropriate for modeling crash data, and providing a strong justification from basic crash principles. In the recent literature, it has been suggested that the motor vehicle crash process can successfully be modeled by assuming a dual-state data-generating process, which implies that entities (e.g., intersections, road segments, pedestrian crossings, etc.) exist in one of two states—perfectly safe and unsafe. As a result, the ZIP and ZINB are two models that have been applied to account for the preponderance of “excess” zeros frequently observed in crash count data. The objective of this study is to provide defensible guidance on how to appropriate model crash data. We first examine the motor vehicle crash process using theoretical principles and a basic understanding of the crash process. It is shown that the fundamental crash process follows a Bernoulli trial with unequal probability of independent events, also known as Poisson trials. We examine the evolution of statistical models as they apply to the motor vehicle crash process, and indicate how well they statistically approximate the crash process. We also present the theory behind dual-state process count models, and note why they have become popular for modeling crash data. A simulation experiment is then conducted to demonstrate how crash data give rise to “excess” zeros frequently observed in crash data. It is shown that the Poisson and other mixed probabilistic structures are approximations assumed for modeling the motor vehicle crash process. Furthermore, it is demonstrated that under certain (fairly common) circumstances excess zeros are observed—and that these circumstances arise from low exposure and/or inappropriate selection of time/space scales and not an underlying dual state process. In conclusion, carefully selecting the time/space scales for analysis, including an improved set of explanatory variables and/or unobserved heterogeneity effects in count regression models, or applying small-area statistical methods (observations with low exposure) represent the most defensible modeling approaches for datasets with a preponderance of zeros

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In recent years the development and use of crash prediction models for roadway safety analyses have received substantial attention. These models, also known as safety performance functions (SPFs), relate the expected crash frequency of roadway elements (intersections, road segments, on-ramps) to traffic volumes and other geometric and operational characteristics. A commonly practiced approach for applying intersection SPFs is to assume that crash types occur in fixed proportions (e.g., rear-end crashes make up 20% of crashes, angle crashes 35%, and so forth) and then apply these fixed proportions to crash totals to estimate crash frequencies by type. As demonstrated in this paper, such a practice makes questionable assumptions and results in considerable error in estimating crash proportions. Through the use of rudimentary SPFs based solely on the annual average daily traffic (AADT) of major and minor roads, the homogeneity-in-proportions assumption is shown not to hold across AADT, because crash proportions vary as a function of both major and minor road AADT. For example, with minor road AADT of 400 vehicles per day, the proportion of intersecting-direction crashes decreases from about 50% with 2,000 major road AADT to about 15% with 82,000 AADT. Same-direction crashes increase from about 15% to 55% for the same comparison. The homogeneity-in-proportions assumption should be abandoned, and crash type models should be used to predict crash frequency by crash type. SPFs that use additional geometric variables would only exacerbate the problem quantified here. Comparison of models for different crash types using additional geometric variables remains the subject of future research.

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The intent of this note is to succinctly articulate additional points that were not provided in the original paper (Lord et al., 2005) and to help clarify a collective reluctance to adopt zero-inflated (ZI) models for modeling highway safety data. A dialogue on this important issue, just one of many important safety modeling issues, is healthy discourse on the path towards improved safety modeling. This note first provides a summary of prior findings and conclusions of the original paper. It then presents two critical and relevant issues: the maximizing statistical fit fallacy and logic problems with the ZI model in highway safety modeling. Finally, we provide brief conclusions.

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In this paper, we present a microphone array beamforming approach to blind speech separation. Unlike previous beamforming approaches, our system does not require a-priori knowledge of the microphone placement and speaker location, making the system directly comparable other blind source separation methods which require no prior knowledge of recording conditions. Microphone location is automatically estimated using an assumed noise field model, and speaker locations are estimated using cross correlation based methods. The system is evaluated on the data provided for the PASCAL Speech Separation Challenge 2 (SSC2), achieving a word error rate of 58% on the evaluation set.

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Engineered tissue grafts, which mimic the spatial variations of cell density and extracellular matrix present in native tissues, could facilitate more efficient tissue regeneration and integration. We previously demonstrated that cells could be uniformly seeded throughout a 3D scaffold having a random pore architecture using a perfusion bioreactor2. In this work, we aimed to generate 3D constructs with defined cell distributions based on rapid prototyped scaffolds manufactured with a controlled gradient in porosity. Computational models were developed to assess the influence of fluid flow, associated with pore architecture and perfusion regime, on the resulting cell distribution.

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The mineral dussertite, a hydroxy-arsenate mineral of formula BaFe3+3(AsO4)2(OH)5, has been studied by Raman complimented with infrared spectroscopy. The spectra of three minerals from different origins were investigated and proved quite similar, although some minor differences were observed. In the Raman spectra of Czech dussertite, four bands are observed in the 800 to 950 cm-1 region. The bands are assigned as follows: the band at 902 cm-1 is assigned to the (AsO4)3- ν3 antisymmetric stretching mode, at 870 cm-1 to the (AsO4)3- ν1 symmetric stretching mode, and both at 859 cm-1 and 825 cm-1 to the As-OM2+/3+ stretching modes/and or hydroxyls bending modes. Raman bands at 372 and 409 cm-1 are attributed to the ν2 (AsO4)3- bending mode and the two bands at 429 and 474 cm-1 are assigned to the ν4 (AsO4)3- bending mode. An intense band at 3446 cm-1 in the infrared spectrum and a complex set of bands centred upon 3453 cm-1 in the Raman spectrum are attributed to the stretching vibrations of the hydrogen bonded (OH)- units and/or water units in the mineral structure. The broad infrared band at 3223 cm-1 is assigned to the vibrations of hydrogen bonded water molecules. Raman spectroscopy identified Raman bands attributable to (AsO4)3- and (AsO3OH)2- units.

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Research has established a close relationship between learning environments and learning outcomes (Department of Education and Early Childhood Development, Victoria, 2008; Woolner, Hall, Higgins, McCaughey & Wall, 2007) yet little is known about how students in Australian schools imagine the ways that their learning environments could be improved to enhance their engagement with the processes and content of education and children are rarely consulted on the issue of school design (Rudduck & Flutter, 2004). Currently, school and classroom designers give attention to operational matters of efficiency and economy, so that architecture for children’s education is largely conceived in terms of adult and professional needs (Halpin, 2007). This results in the construction of educational spaces that impose traditional teaching and learning methods, reducing the possibilities of imaginative pedagogical relationships. Education authorities may encourage new, student-centred pedagogical styles, such as collaborative learning, team-teaching and peer tutoring, but the spaces where such innovations are occurring do not always provide the features necessary to implement these styles. Heeding the views of children could result in the creation of spaces where more imaginative pedagogical relationships and student-centred pedagogical styles can be implemented. In this article, a research project conducted with children in nine Queensland primary schools to investigate their ideas of the ideal ‘school’ is discussed. Overwhelmingly, the students’ work emphasised that learning should be fun and that learning environments should be eco-friendly places where their imaginations can be engaged and where they learn from and in touch with reality. The children’s imagined schools echo ideas that have been promoted over many decades by progressive educators such as John Dewey (1897, in Provenzo, 2006) (“experiential learning”), AS Neill (in Cassebaum, 2003) (Summerhill school) and Ivan Illich (1970) (“deschooling”), with a vast majority of students suggesting that, wherever possible, learning should take place away from classrooms and in environments that support direct, hands-on learning.