961 resultados para Linear Models in Temporal Series


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Author: Heather K. Smith Title: Small Town America Under the “Lights:” Contemporary Images of Rural America in the Series Friday Night Lights Advisor: Rodney Buxton Degree Date: August 2015 ABSTRACT What is Small Town America? The answer to this varies based on a person’s experiences. This is not always from real-world exposure, but often vicariously through television. For some, television is the only opportunity to create a perception for such areas. For others, television could reinforce or sway their perceptions of Small Town America. Therefore, a comprehension of the identity for Small Town America broadcasted through the small screen is important. This research utilized the theory of semiotics to analyze cinematography and mise-en-scene in the opening credits of Friday Night Lights to unearth the themes and overarching ideology for Small Town America conveyed by the series. A modern depiction of rural America that played on considered “traditional values” arose. Unexpectedly, the research also unveiled the inability for an “authentic” or cohesive identity for Small Town America, or any person, location or group for that matter, to exist.

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Although deterministic models of the evolution of mass tourism coastal resorts predict an almost inevitable decline over time, theoretical frameworks of the evolution and restructuring policies of mature destinations should be revised to reflect the complex and dynamic way in which these destinations evolve and interact with the tourism market and global socio-economic environment. The present study examines Benidorm because its urban and tourism model and large-scale tourism supply and demand make it one of the most unique destinations on the Mediterranean coast. The investigation reveals the need to adopt theories and models that are not purely deterministic. The dialectic interplay between external factors and the internal factors inherent in this destination simultaneously reveals a complex and diverse stage of maturity and the ability of destinations to create their own future.

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A fast, simple and environmentally friendly ultrasound-assisted dispersive liquid-liquid microextraction (USA-DLLME) procedure has been developed to preconcentrate eight cyclic and linear siloxanes from wastewater samples prior to quantification by gas chromatography-mass spectrometry (GC-MS). A two-stage multivariate optimization approach has been developed employing a Plackett-Burman design for screening and selecting the significant factors involved in the USA-DLLME procedure, which was later optimized by means of a circumscribed central composite design. The optimum conditions were: extractant solvent volume, 13 µL; solvent type, chlorobenzene; sample volume, 13 mL; centrifugation speed, 2300 rpm; centrifugation time, 5 min; and sonication time, 2 min. Under the optimized experimental conditions the method gave levels of repeatability with coefficients of variation between 10 and 24% (n=7). Limits of detection were between 0.002 and 1.4 µg L−1. Calculated calibration curves gave high levels of linearity with correlation coefficient values between 0.991 and 0.9997. Finally, the proposed method was applied for the analysis of wastewater samples. Relative recovery values ranged between 71–116% showing that the matrix had a negligible effect upon extraction. To our knowledge, this is the first time that combines LLME and GC-MS for the analysis of methylsiloxanes in wastewater samples.

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With advances in the synthesis and design of chemical processes there is an increasing need for more complex mathematical models with which to screen the alternatives that constitute accurate and reliable process models. Despite the wide availability of sophisticated tools for simulation, optimization and synthesis of chemical processes, the user is frequently interested in using the ‘best available model’. However, in practice, these models are usually little more than a black box with a rigid input–output structure. In this paper we propose to tackle all these models using generalized disjunctive programming to capture the numerical characteristics of each model (in equation form, modular, noisy, etc.) and to deal with each of them according to their individual characteristics. The result is a hybrid modular–equation based approach that allows synthesizing complex processes using different models in a robust and reliable way. The capabilities of the proposed approach are discussed with a case study: the design of a utility system power plant that has been decomposed into its constitutive elements, each treated differently numerically. And finally, numerical results and conclusions are presented.

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Reviews of the sport psychology literature have identified a number of models of athlete development in sport (Alfermann & Stambulova, 2007; Durand-Bush &Salmela, 2001). However, minimal research has investigated the origins of knowledge from which each model was developed. The purpose of this study was to systematically examine the influential texts responsible for providing the basis of athlete development models in sport. A citation path analysis of the sport psychology literature was used to generate a knowledge development path of seven athlete development models in sport. The analysis identified influential texts and authors in the conceptualization of athlete development. The popula-tion of 229 texts (articles, books, book chapters) was selected in two phases. Phase1 texts were articles citing seven articles depicting models of athlete development(n  75). Phase 2 included texts cited three or more times by Phase 1 articles (n  154). The analysis revealed how the scholarship of Benjamin Bloom (1985) has been integrated into the field of sport psychology, and how two articles appearing in 1993 and 2003 helped shape present conceptualizations of athlete development