889 resultados para Case Study Analysis
Resumo:
The aim of this dissertation is to show the power of contrastive analysis in successfully predicting the errors a language learner will make by means of a concrete case study. First, there is a description of what language transfer is and why it is important in the matter of second language acquisition. Second, a brief explanation of the history and development of contrastive analysis will be offered. Third, the focus of the thesis will move to an analysis of errors usually made by language learners. To conclude, the dissertation will focus on the concrete case study of a Russian learner of English: after an analysis of the errors the student is likely to make, a recorded conversation will be examined.
Resumo:
A combinatorial protocol (CP) is introduced here to interface it with the multiple linear regression (MLR) for variable selection. The efficiency of CP-MLR is primarily based on the restriction of entry of correlated variables to the model development stage. It has been used for the analysis of Selwood et al data set [16], and the obtained models are compared with those reported from GFA [8] and MUSEUM [9] approaches. For this data set CP-MLR could identify three highly independent models (27, 28 and 31) with Q2 value in the range of 0.632-0.518. Also, these models are divergent and unique. Even though, the present study does not share any models with GFA [8], and MUSEUM [9] results, there are several descriptors common to all these studies, including the present one. Also a simulation is carried out on the same data set to explain the model formation in CP-MLR. The results demonstrate that the proposed method should be able to offer solutions to data sets with 50 to 60 descriptors in reasonable time frame. By carefully selecting the inter-parameter correlation cutoff values in CP-MLR one can identify divergent models and handle data sets larger than the present one without involving excessive computer time.
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Detrital provenance analyses in orogenic settings, in which sediments are collected at the outlet of a catchment, have become an important tool to estimate how erosion varies in space and time. Here we present how Raman Spectroscopy on Carbonaceous Material (RSCM) can be used for provenance analysis. RSCM provides an estimate of the peak temperature (RSCM-T) experienced during metamorphism. We show that we can infer modern erosion patterns in a catchment by combining new measurements on detrital sands with previously acquired bedrock data. We focus on the Whataroa catchment in the Southern Alps of New Zealand and exploit the metamorphic gradient that runs parallel to the main drainage direction. To account for potential sampling biases, we also quantify abrasion properties using flume experiments and measure the total organic carbon content in the bedrock that produced the collected sands. Finally, we integrate these parameters into a mass-conservative model. Our results first demonstrate that RSCM-T can be used for detrital studies. Second, we find that spatial variations in tracer concentration and erosion have a first-order control on the RSCM-T distributions, even though our flume experiments reveal that weak lithologies produce substantially more fine particles than do more durable lithologies. This result implies that sand specimens are good proxies for mapping spatial variations in erosion when the bedrock concentration of the target mineral is quantified. The modeling suggests that highest present-day erosion rates (in Whataroa catchment) are not situated at the range front but around 10 km into the mountain belt.
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BACKGROUND Limitations in the primary studies constitute one important factor to be considered in the grading of recommendations assessment, development, and evaluation (GRADE) system of rating quality of evidence. However, in the network meta-analysis (NMA), such evaluation poses a special challenge because each network estimate receives different amounts of contributions from various studies via direct as well as indirect routes and because some biases have directions whose repercussion in the network can be complicated. FINDINGS In this report we use the NMA of maintenance pharmacotherapy of bipolar disorder (17 interventions, 33 studies) and demonstrate how to quantitatively evaluate the impact of study limitations using netweight, a STATA command for NMA. For each network estimate, the percentage of contributions from direct comparisons at high, moderate or low risk of bias were quantified, respectively. This method has proven flexible enough to accommodate complex biases with direction, such as the one due to the enrichment design seen in some trials of bipolar maintenance pharmacotherapy. CONCLUSIONS Using netweight, therefore, we can evaluate in a transparent and quantitative manner how study limitations of individual studies in the NMA impact on the quality of evidence of each network estimate, even when such limitations have clear directions.
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Objective: The present study offers a novel methodological contribution to the study of the configuration and dynamics of research groups, through a comparative perspective of the projects funded (inputs) and publication co-authorships (output). Method: A combination of bibliometric techniques and social network analysis was applied to a case study: the Departmento de Bibliotecología (DHUBI), Universidad Nacional de La Plata, Argentina, for the period 2000-2009. The results were interpreted statistically and staff members of the department, were interviewed. Results: The method makes it possible to distinguish groups, identify their members and reflect group make-up through an analytical strategy that involves the categorization of actors and the interdisciplinary and national or international projection of the networks that they configure. The integration of these two aspects (input and output) at different points in time over the analyzed period leads to inferences about group profiles and the roles of actors. Conclusions: The methodology presented is conducive to micro-level interpretations in a given area of study, regarding individual researchers or research groups. Because the comparative input-output analysis broadens the base of information and makes it possible to follow up, over time, individual and group trends, it may prove very useful for the management, promotion and evaluation of science
Resumo:
Objective: The present study offers a novel methodological contribution to the study of the configuration and dynamics of research groups, through a comparative perspective of the projects funded (inputs) and publication co-authorships (output). Method: A combination of bibliometric techniques and social network analysis was applied to a case study: the Departmento de Bibliotecología (DHUBI), Universidad Nacional de La Plata, Argentina, for the period 2000-2009. The results were interpreted statistically and staff members of the department, were interviewed. Results: The method makes it possible to distinguish groups, identify their members and reflect group make-up through an analytical strategy that involves the categorization of actors and the interdisciplinary and national or international projection of the networks that they configure. The integration of these two aspects (input and output) at different points in time over the analyzed period leads to inferences about group profiles and the roles of actors. Conclusions: The methodology presented is conducive to micro-level interpretations in a given area of study, regarding individual researchers or research groups. Because the comparative input-output analysis broadens the base of information and makes it possible to follow up, over time, individual and group trends, it may prove very useful for the management, promotion and evaluation of science
Resumo:
Objective: The present study offers a novel methodological contribution to the study of the configuration and dynamics of research groups, through a comparative perspective of the projects funded (inputs) and publication co-authorships (output). Method: A combination of bibliometric techniques and social network analysis was applied to a case study: the Departmento de Bibliotecología (DHUBI), Universidad Nacional de La Plata, Argentina, for the period 2000-2009. The results were interpreted statistically and staff members of the department, were interviewed. Results: The method makes it possible to distinguish groups, identify their members and reflect group make-up through an analytical strategy that involves the categorization of actors and the interdisciplinary and national or international projection of the networks that they configure. The integration of these two aspects (input and output) at different points in time over the analyzed period leads to inferences about group profiles and the roles of actors. Conclusions: The methodology presented is conducive to micro-level interpretations in a given area of study, regarding individual researchers or research groups. Because the comparative input-output analysis broadens the base of information and makes it possible to follow up, over time, individual and group trends, it may prove very useful for the management, promotion and evaluation of science
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Economic backwardness often influences the growth of firms in developing countries. In this paper, we investigate the growth conditions and paths available for latecomers competing with first movers. Employing the concepts of boundaries of the firm and the disadvantage of backwardness, we present a case study of China's mobile handset industry and proceed to develop a simple model. We find that although significant disadvantage does not allow latecomers to grow, there are possibilities for changing the conditions of growth if latecomers can utilize outside resources and/or indigenous advantages.
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The direct application of existing models for seed germination may often be inadequate in the context of ecology and forestry germination experiments. This is because basic model assumptions are violated and variables available to forest managers are rarely used. In this paper, we present a method which addresses the aforementioned shortcomings. The approach is illustrated through a case study of Pinus pinea L. Our findings will also shed light on the role of germination in the general failure of natural regeneration in managed forests of this species. The presented technique consists of a mixed regression model based on survival analysis. Climate and stand covariates were tested. Data for fitting the model were gathered from a 5-year germination experiment in a mature, managed P. pinea stand in the Northern Plateau of Spain in which two different stand densities can be found. The model predictions proved to be unbiased and highly accurate when compared with the training data. Germination in P. pinea was controlled through thermal variables at stand level. At microsite level, low densities negatively affected the probability of germination. A time-lag in the response was also detected. Overall, the proposed technique provides a reliable alternative to germination modelling in ecology/forestry studies by using accessible/ suitable variables. The P. pinea case study highlights the importance of producing unbiased predictions. In this species, the occurrence and timing of germination suggest a very different regeneration strategy from that understood by forest managers until now, which may explain the high failure rate of natural regeneration in managed stands. In addition, these findings provide valuable information for the management of P. pinea under climate-change conditions.
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In 2005 the Directorate General for Industrial Development and Technological Innovation of the Canary Islands proceeded to carry out a project to measure the behavioral skills of various government agencies and companies in the Canary Islands in order to prepare a White Paper to assess the most effective measures for the stimulation of innovation in this autonomous community and to facilitate the objectives of public subsidies. This paper shows a portion of the work performed comparing the activity oriented towards innovation and the one aimed at sustaining the status quo of the organizations in the sample.
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The paper focuses on the analysis of radial-gated spillways, which is carried out by the solution of a numerical model based on the finite element method (FEM). The Oliana Dam is considered as a case study and the discharge capacity is predicted both by the application of a level-set-based free-surface solver and by the use of traditional empirical formulations. The results of the analysis are then used for training an artificial neural network to allow real-time predictions of the discharge in any situation of energy head and gate opening within the operation range of the reservoir. The comparison of the results obtained with the different methods shows that numerical models such as the FEM can be useful as a predictive tool for the analysis of the hydraulic performance of radial-gated spillways.
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In this work the failure analysis carried out in III-V concentrator multijunction solar cells after a temperature accelerated life test is presented. All the failures appeared have been catastrophic since all the solar cells turned into low shunt resistances. A case study in failure analysis based on characterization by optical microscope, SEM, EDX, EQE and XPS is presented in this paper, revealing metal deterioration in the bus bar and fingers as well as cracks in the semiconductor structure beneath or next to the bus bar. In fact, in regions far from the bus bar the semiconductor structure seems not to be damaged. SEM images have dismissed the presence of metal spikes inside the solar cell structure. Therefore, we think that for these particular solar cells, failures appear mainly as a consequence of a deficient electrolytic growth of the front metallization which also results in failures in the semiconductor structure close to the bus bars.
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The present paper provides an insight into the food value chain of three specific sectors (fruit and vegetables, poultry and rice) in the Dominican Republic. The Glocal methodology used for the study combines a global view with local conditions and thus it can be applied to food markets. Each of these food chains is analyzed by following traditional industrial organization theory, based on structure, conduct and performance. Regarding the specific case of the Dominican Republic, different sources of information are used to analyze the weaknesses of the studied chains, including direct interviews. The food value chains of fruit and vegetables, poultry and rice in the Dominican Republic show a lack of structure and they are undergoing changes; however, they also have great opportunities to improve efficiency by making some changes.
Resumo:
Acknowledgements We thank Andrew Spink (Noldus Information Technology) and the Blogging Birds team members Peter Kindness and Abdul Adeniyi for their valuable contributions to this paper. John Fryxell, Chris Thaxter and Arjun Amar provided valuable comments on an earlier version. The study was part of the Digital Conservation project of dot.rural, the University of Aberdeen’s Digital Economy Research Hub, funded by RCUK (grant reference EP/G066051/1).
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A twenty-year period of severe land subsidence evolution in the Alto Guadalentín Basin (southeast Spain) is monitored using multi-sensor SAR images, processed by advanced differential interferometric synthetic aperture radar (DInSAR) techniques. The SAR images used in this study consist of four datasets acquired by ERS-1/2, ENVISAT, ALOS and COSMO-SkyMed satellites between 1992 and 2012. The integration of ground surface displacement maps retrieved for different time periods allows us to quantify up to 2.50 m of cumulated displacements that occurred between 1992 and 2012 in the Alto Guadalentín Basin. DInSAR results were locally compared with global positioning system (GPS) data available for two continuous stations located in the study area, demonstrating the high consistency of local vertical motion measurements between the two different surveying techniques. An average absolute error of 4.6 ± 4 mm for the ALOS data and of 4.8 ± 3.5 mm for the COSMO-SkyMed data confirmed the reliability of the analysis. The spatial analysis of DInSAR ground surface displacement reveals a direct correlation with the thickness of the compressible alluvial deposits. Detected ground subsidence in the past 20 years is most likely a consequence of a 100–200 m groundwater level drop that has persisted since the 1970s due to the overexploitation of the Alto Guadalentín aquifer system. The negative gradient of the pore pressure is responsible for the extremely slow consolidation of a very thick (> 100 m) layer of fine-grained silt and clay layers with low vertical hydraulic permeability (approximately 50 mm/h) wherein the maximum settlement has still not been reached.