971 resultados para 1770-1840


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ResumenEl artículo estudia el tamaño y ubicación de la población indígena de la zona denominada Gran Talamanca, que incluye todo el sur de Costa Rica, entre 1840 y 1927. En el período estudiado, la población indígena se mantuvo en cerca de tres mil personas. Su ubicación en general cambió poco, pero se vio afectada por corrientes migratorias, tanto de indígenas como de no indígenasAbstractThe article analyzes the extent and location between 1840 and 1927 of the indigenous population in the area known as Gran Talamanca, which comprises the entire southern region of Costa Rica. In the period under study, the indigenous population kept a steady figure of close to three thousand individuals. In general, their location experienced very slight changes, influenced by migratory flows, both of indigenous and non-indigenous people.

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Resumen La autora destaca la complejidad de las relaciones entre los actores locales y los agentes de las potencias externas, sus modos de cooperación, sometimiento y resistencia bajo diversos contextos sociales, asi como los resultados imprevistos o paradójicos de las intervenciones foráneas en la construcción de la idea nacional de Nicaragua Abstract The autor highlights the complexity of relations between local actor and the agents of foreing powers ; their modes of cooperation, submission, and resistance under diverse social contexts; and resistance under diverse social contexts; and the unexpected or paradoxical results of foreign interventions in the construction of the national idea of Nicaragua

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Resumen Examina la relación entre la elite de Santiago de Guatemala y el cabildo de esa ciudad entre 1700 y 1770. Abstract This essay examines  the relations between the elite of Santiago de Guatemala and the cabildo (municipal council) of that city between 1700 and 1770.

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Occupational stress has been a concern for human resource managers in light of research investigating the work stressor-employee adjustment relationship. This research has consistently demonstrated many negative effects between stressors in the workplace and employee adjustment. A considerable amount of literature also describes potential moderators of this relationship. Subjective fit with organizational culture has been established as a significant predictor of employee job-related attitudes; however, research has neglected investigation of the potential moderating effect of subjective fit in the work stressor-employee adjustment process. It was predicted that perceptions of subjective fit with the organization’s values and goals would mitigate the negative effect of work stressors on employee adjustment in an employee sample from three organizations (N ¼ 256). Hierarchical multiple regression analyses revealed support for the stress-buffering effects of high subjective fit in the prediction of physical symptoms, job satisfaction, and intentions to leave. The theoretical and practical implications of the results are discussed.

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A national-level safety analysis tool is needed to complement existing analytical tools for assessment of the safety impacts of roadway design alternatives. FHWA has sponsored the development of the Interactive Highway Safety Design Model (IHSDM), which is roadway design and redesign software that estimates the safety effects of alternative designs. Considering the importance of IHSDM in shaping the future of safety-related transportation investment decisions, FHWA justifiably sponsored research with the sole intent of independently validating some of the statistical models and algorithms in IHSDM. Statistical model validation aims to accomplish many important tasks, including (a) assessment of the logical defensibility of proposed models, (b) assessment of the transferability of models over future time periods and across different geographic locations, and (c) identification of areas in which future model improvements should be made. These three activities are reported for five proposed types of rural intersection crash prediction models. The internal validation of the model revealed that the crash models potentially suffer from omitted variables that affect safety, site selection and countermeasure selection bias, poorly measured and surrogate variables, and misspecification of model functional forms. The external validation indicated the inability of models to perform on par with model estimation performance. Recommendations for improving the state of the practice from this research include the systematic conduct of carefully designed before-and-after studies, improvements in data standardization and collection practices, and the development of analytical methods to combine the results of before-and-after studies with cross-sectional studies in a meaningful and useful way.

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One major gap in transportation system safety management is the ability to assess the safety ramifications of design changes for both new road projects and modifications to existing roads. To fulfill this need, FHWA and its many partners are developing a safety forecasting tool, the Interactive Highway Safety Design Model (IHSDM). The tool will be used by roadway design engineers, safety analysts, and planners throughout the United States. As such, the statistical models embedded in IHSDM will need to be able to forecast safety impacts under a wide range of roadway configurations and environmental conditions for a wide range of driver populations and will need to be able to capture elements of driving risk across states. One of the IHSDM algorithms developed by FHWA and its contractors is for forecasting accidents on rural road segments and rural intersections. The methodological approach is to use predictive models for specific base conditions, with traffic volume information as the sole explanatory variable for crashes, and then to apply regional or state calibration factors and accident modification factors (AMFs) to estimate the impact on accidents of geometric characteristics that differ from the base model conditions. In the majority of past approaches, AMFs are derived from parameter estimates associated with the explanatory variables. A recent study for FHWA used a multistate database to examine in detail the use of the algorithm with the base model-AMF approach and explored alternative base model forms as well as the use of full models that included nontraffic-related variables and other approaches to estimate AMFs. That research effort is reported. The results support the IHSDM methodology.

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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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Successful construction project managers often stress the importance of team working, relationship management, project environment and senior management commitment as being key determinants of project success. However, it is generally accepted that the construction industry has stronger preference for displaying distrust rather than emancipating the full benefits of cooperation. In the research domain, the impact of culture and organisation on project performance is becoming an increasingly important topic for the establishment of a sound relational approach to projects. Relational procurement strategies emphasise the importance of sustainable relationships. However, the efficacy of relational contracting is, so far, unproven. This study examines the organisational factors that facilitates sustainable relationship between project organisations and hence, lead to long-term business success. Initial findings captured from a survey undertaken with construction contracting organisations in Australia, where the perceptions of professional personnel and supply chain relationships are reported in this paper. A four-level project performance effectiveness model developed in this research is also presented.

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This paper presents a fault diagnosis method based on adaptive neuro-fuzzy inference system (ANFIS) in combination with decision trees. Classification and regression tree (CART) which is one of the decision tree methods is used as a feature selection procedure to select pertinent features from data set. The crisp rules obtained from the decision tree are then converted to fuzzy if-then rules that are employed to identify the structure of ANFIS classifier. The hybrid of back-propagation and least squares algorithm are utilized to tune the parameters of the membership functions. In order to evaluate the proposed algorithm, the data sets obtained from vibration signals and current signals of the induction motors are used. The results indicate that the CART–ANFIS model has potential for fault diagnosis of induction motors.

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We consider the problem of binary classification where the classifier can, for a particular cost, choose not to classify an observation. Just as in the conventional classification problem, minimization of the sample average of the cost is a difficult optimization problem. As an alternative, we propose the optimization of a certain convex loss function φ, analogous to the hinge loss used in support vector machines (SVMs). Its convexity ensures that the sample average of this surrogate loss can be efficiently minimized. We study its statistical properties. We show that minimizing the expected surrogate loss—the φ-risk—also minimizes the risk. We also study the rate at which the φ-risk approaches its minimum value. We show that fast rates are possible when the conditional probability P(Y=1|X) is unlikely to be close to certain critical values.

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In face of the increasing concern on global warming and climate change, the interests in the utilization of solar energy for building operation are also rapidly growing. In this paper, the importance of using renewable energy in building operations is first discussed. The potential use of solar energy is then reviewed. Possible applications of solar energy in building operation are also discussed, including the use of solar energy in the forms of daylighting, hot water heating, space heating and cooling and building-integrated photovoltaics. Finally, the research activities in the utilization of solar energy for space cooling at QUT are highlighted.

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Biological validation of new radiotherapy modalities is essential to understand their therapeutic potential. Antiprotons have been proposed for cancer therapy due to enhanced dose deposition provided by antiproton-nucleon annihilation. We assessed cellular DNA damage and relative biological effectiveness (RBE) of a clinically relevant antiproton beam. Despite a modest LET (~19 keV/μm), antiproton spread out Bragg peak (SOBP) irradiation caused significant residual γ-H2AX foci compared to X-ray, proton and antiproton plateau irradiation. RBE of ~1.48 in the SOBP and ~1 in the plateau were measured and used for a qualitative effective dose curve comparison with proton and carbon-ions. Foci in the antiproton SOBP were larger and more structured compared to X-rays, protons and carbon-ions. This is likely due to overlapping particle tracks near the annihilation vertex, creating spatially correlated DNA lesions. No biological effects were observed at 28–42 mm away from the primary beam suggesting minimal risk from long-range secondary particles.