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With urbanisation continuing to encroach upon flood plains, the constant replacement of permeable land with impermeable surfaces and with the changes in global climate, the need for improved flood modelling is ever more apparent. A wide range of methods exist that simulate surface flow; most commonly in one-dimensional (1D) or twodimensional (2D), and more recently on smaller scales in three-dimensional (3D) models. In urban flood modelling, 2D models are often the preferred choice as they can simulate surface flow more accurately than their 1D model counterparts; they are, however, more computationally demanding and thereby usually require greater simulation time. With the vast amount of information used in flood modelling, generalisation techniques are often employed to reduce the computational load within a simulation. The objective of this thesis is to improve 2D flood modelling in urban environments by introducing a new and novel approach of representing fine scale building features within coarse grids. This is achieved by creating an automated approach that data-mines key features such as buildings and represents their effects numerically within a multiple layer grid format. This new approach is tested in comparison to two other, already established generalising techniques which are single layer based. The effectiveness of each model is assessed by its ability to accurately represent surface flow at different grid resolutions and how each copes with varying building orientations and distributions within the test datasets. The performance of each generalising approach is determined therefore by its accuracy in relation to the fine scale model and the difference in the computational time required complete the simulation. Finally the multilayered methodology is applied to a real case scenario to test its applicability further. Overall it revealed, as predicted, that the multilayered approach enables far greater accuracies at routing surface flow within coarse grids whilst still greatly reducing computational time. As a further benefit in urban flood modelling, this thesis shows that using a multilayered data format it is possible to simulate the influence of features that have a grid resolution finer than the initial terrain topology data, thus enabling, for example, the routing of surface water through alleyways between buildings that have a width less than one meter.

Orientador: Glauco de Souza Rolim / Resumo: Precipitação, em pequenas escalas de tempo, é um fenômeno associado a altos níveis de incerteza e variabilidade. Dada a sua natureza, técnicas tradicionais de previsão são dispendiosas e exigentes em termos computacionais. Este trabalho apresenta um modelo para prever a ocorrência de chuvas em curtos intervalos de tempo por Redes Neurais Artificiais (RNAs) em períodos acumulados de 3 a 7 dias para cada estação climática, mitigando a necessidade de predizer o seu volume. Com essa premissa pretende-se reduzir a variância, aumentar a tendência dos dados diminuindo a responsabilidade do algoritmo que atua como um filtro para modelos quantitativos, removendo ocorrências subsequentes de valores de zero(ausência) de precipitação, o que influencia e reduz seu desempenho. O modelo foi desenvolvido com séries temporais de 10 regiões agricolamente relevantes no Brasil, esses locais são os que apresentam as séries temporais mais longas disponíveis e são mais deficientes em previsões climáticas precisas, com 60 anos de temperatura média diária do ar e precipitação acumulada. foram utilizados para estimar a evapotranspiração potencial e o balanço hídrico; estas foram as variáveis ​​utilizadas como entrada para as RNAs. A precisão média para todos os períodos acumulados foi de 78% no verão, 71% no inverno 62% na primavera e 56% no outono, foi identificado que o efeito da continentalidade, o efeito da altitude e o volume da precipitação normal , tem um impacto direto na precisão das RNAs. Os... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: Precipitation, in short periods of time, is a phenomenon associated with high levels of uncertainty and variability. Given its nature, traditional forecasting techniques are expensive and computationally demanding. This paper presents a model to forecast the occurrence of rainfall in short ranges of time by Artificial Neural Networks(ANNs) in accumulated periods from 3 to 7 days for each climatic season, mitigating the necessity of predicting its amount. With this premise it is intended to reduce the variance, rise the bias of data and lower the responsibility of the model acting as a filter for quantitative models by removing subsequent occurrences of zeros values of rainfall which leads to bias the and reduces its performance. The model were developed with time series from 10 agriculturally relevant regions in Brazil, these places are the ones with the longest available weather time series and and more deficient in accurate climate predictions, it was available 60 years of daily mean air temperature and accumulated precipitation which were used to estimate the potential evapotranspiration and water balance; these were the variables used as inputs for the ANNs models. The mean accuracy of the model for all the accumulated periods were 78% on summer, 71% on winter 62% on spring and 56% on autumn, it was identified that the effect of continentality, the effect of altitude and the volume of normal precipitation, have a direct impact on the accuracy of the ANNs. The models have ... (Complete abstract click electronic access below) / Mestre

Interdisciplinary Research (IDR) has received a lot of attention from academics, policy-makers, and decision-makers alike. RCUK invests £3 billion in research grants each year (RCUK 2017); half of the grants are provided to investigators who hail from different departments. There is mounting awareness of the challenges facing IDR, and a large body of literature trying to establish how IDR can be analysed (Davidson 2015, Yegros-Yegros, Rafols et al. 2015). Of these, the majority have been qualitative studies and it has been noticed that there is a distinct lack of quantitative studies that can be used to identify how to enable IDR. The literature shows that many of the barriers to IDR can be classified as either cultural or administrative (Katz and Martin 1997, Cummings and Kiesler 2005, Rafols 2007, Wagner, Roessner et al. 2011), neither of which are easily changed over a short period of time. The perspective taken in this research is that change can be affected by enabling the individuals who conduct IDR. Herein lies the main challenge; how can these future leaders of IDR be identified so that they can be properly supported. No existing datasets were deemed suitable for the purpose, and a new dataset was created to analyse IDR. To isolate dynamics within an organisation, hard boundaries were drawn around research-organisations. The University of Bath journal co-authorship dataset 2000-2017 was determined to be suitable for this purpose. From this dataset a co-authorship network was created. To analyse this, established models from literature were adapted and used to identify differences in disciplinary and interdisciplinary archetypes. This was done through a correlational study. No statistically significant differences between such author archetypes were found. It was therefore concluded that an alternative approach was necessary. By adapting the networks framework to account for different types of links between edges, a multilayer perspective was adopted. This resulted in a rank-3 tensor, node-aligned framework being proposed, allowing disciplines to be represented in the network. By using this framework to construct the University of Bath multiplex co-authorship network, an exemplar structure was established through use of a series of proposed structural metrics. A growth model was proposed and successfully recreated the structure and thereby uncovered mechanics affecting real-world multiplex networks. This highlighted the importance of node entities and the layer closeness centrality. This implies that it is very difficult to carry over benefits across disciplines, and that some disciplines are better suited to share and adapt knowledge than others. The growth model also allowed an analytical expression for the rate of change of disciplinary degree, thereby providing a model for who is most likely to enable and sustain IDR.

In this study, the tansparent conductive oxide (TCO) multilayer film AZO/Ag-Ti/AZO was fabricated with Ag-Ti alloy as conducting layer and AZO as anti-reflective material. The metal alloy was deposited by DC magnetron sputtering, and the AZO film deposition was performed by spin-coating technique and dried at suitable temperature. The thicknesses of Ag-Ti and AZO thin films were varied to fabricate AZO/Ag-Ti/AZO multilayer films. The microstructures of the multilayer films were observed by SEM and AFM. Sheet resistance was measured by using four-point probe. Optical transmittance was measured in the visible range by uv-vis spectrophotometer. The results show that as the top of AZO thickness is 50 nm, intermediate Ag-Ti metal laminated to 9 nm, and the bottom of the AZO is 35 nm, the transmittance of multilayer film AZO/Ag-Ti/AZO can reach 78.92%, and the sheet resistance is 1.86£[/¡¼. When thermal annealing process was carried out to the bottom AZO film, the worse characteristics of the transmittance and resistance of the performed multilayer film were resulted.

The tensile behavior of the monolithic amorphous ZrCu and crystalline Cu thin films and the ZrCu/Cu multilayered thin films, coated on polyimide (PI) substrates in different layer thicknesses has been investigated. The scanning electron microscope (SEM) morphology of the as-deposited thin film is composed of sphere domains. Between the domains, stress concentration is induced. The cracks perpendicular to the loading direction would propagate along the domains. The constituent component examined by energy dispersive X-ray spectrometer (EDS) shows that the average composition (in atomic percent) amorphous thin film is Zr46.78Cu53.22, closed to the designed Zr50Cu50 goal. The X-ray diffraction (XRD) results show that the multilayered specimens are composed of both amorphous ZrCu and nanocrystalline Cu crystal structure. As the monolayer thickness become lower, the normalized peak height and grain sizes of Cu become lower. To obtain the mechanical properties of the coated films, deducting the contribution of substrates is used in this study. The tensile Young¡¦s moduli of monolithic amorphous ZrCu and nanocrystalline Cu thin films are close to the results extracted from micro-compression. Based on the current tensile results for the moduli of multilayered thin films, the obtained mechanical data are demonstrated to be reliable and are consistent with the theoretical values predicted by Rule of Mixture. As the thickness decreases from 100 nm down to 10 nm, the tensile Young¡¦s moduli do not vary much. On the other hand, the maximum tensile stress shows strong variation, being highest for the layer thickness of 25 nm. The deformed surface morphologies characterized by scanning electron microscopy also exhibit a similar trend. The optimum tensile properties of the monolithic and multilayered thin film combinations are examined and discussed in this thesis.

In this study, the AZO thin films were deposited with various manufacturing conditions, such as working pressure of oxygen and substrate temperature, by e-beam evaporation. The microstructure of the AZO film was observed by SEM and AFM. Sheet resistance was measured using four-point probe method. Optical transmittance was measured in the visible range by UV spectrophotometer. Finally, AZO transparent film was used as a substitute for ITO to fabricate the radiation-resistant glasses. The optimum parameters for depositing AZO films are glass substrates of 80¢J and working pressure of 1¡Ñ10-4 Torr. The film resistance is 9.2¡Ñ10-4 £[-cm with a film thickness of 60 nm. The refractive index was measured to be 2.05 at a wavelength of 510 nm. The optical transmittance of the prepared films was above 83 % in the visible range. The manufacturing conditions for depositing AZO multilayer coatings are working pressure of 5.0¡Ñ10-5 Torr, ion gun working pressure of 6.0¡Ñ10-5 Torr, voltage of 6.2 V, oxygen gas flow rate of 36 sccm and glass substrates of 80¢J. The optical transmittance of the glass was above 94 % in the visible range.

ITC/USA 2014 Conference Proceedings / The Fiftieth Annual International Telemetering Conference and Technical Exhibition / October 20-23, 2014 / Town and Country Resort & Convention Center, San Diego, CA / This paper presents an effective multi-layer background modeling method to detect moving objects by exploiting the advantage of novel distinctive features and hierarchical structure of the Codebook (CB) model. In the block-based structure, the mean-color feature within a block often does not contain sufficient texture information, causing incorrect classification especially in large block size layers. Thus, the Binary Ordered Dithering (BOD) feature becomes an important supplement to the mean RGB feature In summary, the uniqueness of this approach is the incorporation of the halftoning scheme with the codebook model for superior performance over the existing methods.

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