Data-driven decision making has become more popular in today’s businesses including logistics and vehicle routing. Leveraging historical data, companies can achieve goals such as customer satisfaction management, scalable and efficient operation, and higher overall revenue. In the management of customer satisfaction, logistics companies use consistent assignment of their drivers to customers over time. Creating this consistency takes time and depends on the history experienced between the company and the customer. While pursuing this goal, companies trade off the cost of capacity with consistency because demand is unknown on a daily basis. We propose concepts and methods that enable a parcel delivery company to balance the trade-off between cost and customer satisfaction. We use clustering methods that use cumulative historical service data to generate better consistency using the information entropy measure. Parcel delivery companies route many vehicles to serve customer requests on a daily basis. While clustering was important to the development of early routing algorithms, modern solution methods rely on metaheuristics, which are not easily deployable and often do not have open source code bases. We propose a two-stage, shape-based clustering approach that efficiently obtains a clustering of delivery request locations. Our solution technique is based on creating clusters that form certain shapes with respect to the depot. We obtain a routing solution by ordering all locations in every cluster separately. Our results are competitive with a state-of-the-art vehicle routing solver in terms of quality. Moreover, the results show that the algorithm is more scalable and is robust to problem parameters in terms of runtime. Fish trawling can be considered as a vehicle routing problem where the main objective is to maximize the amount of fish (revenue) facing uncertainty on catch. This uncertainty creates an embedded prediction problem before deciding where to harvest. Using previous catch data to train prediction models, we solve the routing problem a fish trawler faces using dynamically updated routing decisions allowing for spatiotemporal correlation in the random catch. We investigate the relationship between the quality of predictions and the quality of revenue generated as a result.

This thesis analyzes the wireless propagation modeling of a 2.6 GHz band channel around the Tampa Bay area. Different empirical models are compared against measured data, and an adapted model, specific for the Tampa Bay area, is presented that builds on the accuracy of existing models. The effects of the propagation characteristics along bridges are also discussed, and a two-slope model is presented. The proposed models are based on a simple linear regression method, and statistical tests are evaluated for reliability thereof. The analysis also investigates the statistical properties of shadowing effects imposed on the wireless channel. The spatial correlation properties of shadowing effects are investigated in detail, and an extension of existing correlation models for shadowing effects is suggested where the correlation properties are studied in different distance ranges rather than the whole service coverage area.

This thesis investigates the design and the analysis of acoustic signal processing algorithms in reverberant rooms. Reverberation poses a major challenge to acoustic signal processing problems. It degrades speech intelligibility and causes many acoustic algorithms that process sound to perform poorly. Current solutions to the reverberation problem frequently only work in lightly reverberant environments. There is need to improve the reverberant performance of acoustic algorithms.¶ The approach of this thesis is to explore how the intrinsic properties of reverberation can be exploited to improve acoustic signal processing algorithms. A general approach to soundfield modelling using statistical room acoustics is applied to analyze the reverberant performance of several acoustic algorithms. A model of the underlying structure of reverberation is incorporated to create a new method of soundfield reproduction.¶ Several outcomes resulting from this approach are: (i) a study of how more sound capture with directional microphones and beamformers can improve the robustness of acoustic equalization, (ii) an assessment of the extent to which source tracking can improve accuracy of source localization, (iii) a new method of soundfield reproduction for reverberant rooms, based upon a parametrization of the acoustic transfer function and (iv) a study of beamforming to directional sources, specifically exploiting the directionality of human speech.¶ The approach to soundfield modelling has permitted a study of algorithm performance on important parameters of the room acoustics and the algorithm design. The performance of acoustic equalization and source tracking have been found to depend not only on the levels of reverberation but also on the correlation of pressure between points in reverberant soundfields. This correlation can be increased by sound capture with directional capture devices. Work on soundfield reproduction has shown that, though reverberation significantly degrades the performance of conventional techniques, by accounting for the reverberation it is possible to design reproduction methods that function well in reverberant environments.

Multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) technology has been used widely in many wireless communication systems. Signals will be distorted when they are transmitted in wireless channels. For the reason that wireless channel is time or location variant, we have to estimate the channel impulse response and use the channel state information to compensate the channel distortion. In order to estimate the state of the channel, let the known training symbols put in front of the data symbols and use training symbols to estimate channel response. A typical channel estimate for MIMO OFDM systems is treated as spatially uncorrelated. However in many realistic scenarios, the channel tends to be spatially correlated. Indeed, we have no prior knowledge of the channel spatial correlation. So consider the spatial correlation, the channel can estimate accurately. And it is important that how to combine spatial correlation and channel estimation to reduce the estimation error. In the paper we propose a iterative channel spatial correlation and channel estimation algorithm. At first, channel spatial correlation estimation is obtained by synchronize symbols. The receiver uses the estimated channel to help the detection/decision of data symbol. And then the channel estimation treats the detected signals as known data to perform a next stage channel estimation iteratively. By utilizing the iterative channel estimation and signal detection process we can reduce the estimation error caused by channel spatial correlation estimation. The accuracy of the channel estimation can be improved by increasing the number of iteration process. Simulation results demonstrate the iterative spatial correlation and channel estimation algorithm can provide better mean-square-error performance.

This thesis focuses on the design of field experiments with blocks to study treatment effects for a number of treatments. Small field plots are available but located in several blocks and each plot is assigned to a treatment in the experiment. Due to spatial correlation among the plots, the allocation of the treatments to plots has influence on the analysis of the treatment effects. When the spatial correlation is known, optimal allocations (designs) of the treatments to plots have been studied in the literature. However, the spatial correlation is usually unknown in practice, so we propose a robust criterion to study optimal designs of the treatments to plots. Neighbourhoods of correlation structures are introduced and a modified generalized least squares estimator is discussed. A simulated annealing algorithm is implemented to compute optimal/robust designs. Various results are obtained for different experimental settings. Some theoretical results are also proved in the thesis. / Graduate

Medições em túnel de vento e em escala real têm mostrado que as pressões do vento natural não estão totalmente correlacionadas espacialmente. O uso da Decomposição Ortogonal Própria (DOP) permite a obtenção dos desvios padrões das respostas da estrutura a partir da matriz de coeficientes de correlação espacial das pressões do vento nos diferentes pontos de tomadas em túnel. O método indicado pela NBR6123 - Forças devido ao vento em edificações supõe um vento de rajada totalmente correlacionado espacialmente dentro das dimensões da edificação. O objetivo deste trabalho é comparar a resposta estrutural obtida pelos métodos da Decomposição Ortogonal Própria (MDOP) e da NBR6123. Para tal foi escolhida uma estrutura tipo treliça espacial em arco semicircular com 53,00 m de largura, 26,50m de flecha e 92,80m de comprimento. A escolha da estrutura tipo treliça espacial tem o motivo de este tipo de estrutura possuir uma continuidade estrutural capaz de difundir o desvio padrão devido às pressões em uma tomada em uma extremidade da construção para uma resposta em um elemento estrutural na outra extremidade. Foi construído um modelo em escala reduzida para realização de ensaios no túnel de vento do Laboratório de Aerodinâmica das Construções (LAC) da Universidade Federal do Rio Grande do Sul - UFRGS. A partir daí empregou-se o MDOP para a obtenção da resposta estrutural e comparou-se com a resposta obtida pelo método da NBR6123. Os resultados demonstram que os distintos padrões de escoamento em torno do modelo resultam em um carregamento com níveis também distintos de correlação e que o MDOP é uma poderosa ferramenta de análise, permitindo um projeto mais seguro e otimizado da estrutura. / Both wind tunnel and real scale measurements have been indicating that the natural wind pressures are not entirely correlated spatially. The use of the Proper Orthogonal Decomposition (POD) allows the acquisition of the structural responses standard deviations from the wind pressures spatial correlation coefficients matrix on the various measurement points in a tunnel. The method shown by the "NBR6123 - Forças devido ao vento em edificações", on the other hand, assumes a gust of wind entirely correlated spatially. The objective of this study was to compare the structural response obtained by the proper orthogonal decomposition methods (POD) with that obtained by the NBR6123 methods. In order to do that, a spatial truss-type structure in semicircular arch was chosen, with a 53,00 m width, a 26,50 m arrow and a 92,80 m length. The choice for a spatial truss structure was made because it has a structural continuity capable of spreading the pressure's standard deviation from a given measurement point on one extremity of the construction, to a response in a structural element on the other extremity. A reduced scale model was built in the Laboratório de Aerodinâmica das Construções (LAC) from the Universidade Federal do Rio Grande do Sul - UFGRS -, in order to perform the tests. Then, the POD\ was employed to obtain the structural responses, which were compared to those obtained employing the NBR6123. The results show that the distinct flow patterns around the model result in a load with also distinct levels of correlation. In conclusion, the POD is a powerful analysis tool that allows a safer and optimized structural design.

Massive multiple-input multiple-output is a promising technique for the next generation of wireless communication systems which addresses most of the critical challenges associated with concurrent relaying systems, such as digital signal processing complexity, long processing delay, and low latency wireless communications. However, the deployment of conventional fully digital beamforming methods, dedicates one radio frequency (RF) chain to each antenna, is not viable enough due to the high fabrication/implementation cost and power consumption. In this thesis, we envision to address this critical issue by reducing the number of RF chains in a viable analog/digital configuration paradigm which is usually referred to hybrid structure. From another viewpoint, the development of fifth generation enabling technologies brings new challenges to the design of power amplifiers (PAs). In particular, there is a strong demand for low-cost, nonlinear PAs which, however, introduce nonlinear distortions. On the other hand, contemporary expensive PAs show great power efficiency in their nonlinear region. Inspired by this trade-off between nonlinearity distortions and efficiency, finding an optimal operating point is highly desirable, and this is the second key contribution of this thesis.

Medições em túnel de vento e em escala real têm mostrado que as pressões do vento natural não estão totalmente correlacionadas espacialmente. O uso da Decomposição Ortogonal Própria (DOP) permite a obtenção dos desvios padrões das respostas da estrutura a partir da matriz de coeficientes de correlação espacial das pressões do vento nos diferentes pontos de tomadas em túnel. O método indicado pela NBR6123 - Forças devido ao vento em edificações supõe um vento de rajada totalmente correlacionado espacialmente dentro das dimensões da edificação. O objetivo deste trabalho é comparar a resposta estrutural obtida pelos métodos da Decomposição Ortogonal Própria (MDOP) e da NBR6123. Para tal foi escolhida uma estrutura tipo treliça espacial em arco semicircular com 53,00 m de largura, 26,50m de flecha e 92,80m de comprimento. A escolha da estrutura tipo treliça espacial tem o motivo de este tipo de estrutura possuir uma continuidade estrutural capaz de difundir o desvio padrão devido às pressões em uma tomada em uma extremidade da construção para uma resposta em um elemento estrutural na outra extremidade. Foi construído um modelo em escala reduzida para realização de ensaios no túnel de vento do Laboratório de Aerodinâmica das Construções (LAC) da Universidade Federal do Rio Grande do Sul - UFRGS. A partir daí empregou-se o MDOP para a obtenção da resposta estrutural e comparou-se com a resposta obtida pelo método da NBR6123. Os resultados demonstram que os distintos padrões de escoamento em torno do modelo resultam em um carregamento com níveis também distintos de correlação e que o MDOP é uma poderosa ferramenta de análise, permitindo um projeto mais seguro e otimizado da estrutura. / Both wind tunnel and real scale measurements have been indicating that the natural wind pressures are not entirely correlated spatially. The use of the Proper Orthogonal Decomposition (POD) allows the acquisition of the structural responses standard deviations from the wind pressures spatial correlation coefficients matrix on the various measurement points in a tunnel. The method shown by the "NBR6123 - Forças devido ao vento em edificações", on the other hand, assumes a gust of wind entirely correlated spatially. The objective of this study was to compare the structural response obtained by the proper orthogonal decomposition methods (POD) with that obtained by the NBR6123 methods. In order to do that, a spatial truss-type structure in semicircular arch was chosen, with a 53,00 m width, a 26,50 m arrow and a 92,80 m length. The choice for a spatial truss structure was made because it has a structural continuity capable of spreading the pressure's standard deviation from a given measurement point on one extremity of the construction, to a response in a structural element on the other extremity. A reduced scale model was built in the Laboratório de Aerodinâmica das Construções (LAC) from the Universidade Federal do Rio Grande do Sul - UFGRS -, in order to perform the tests. Then, the POD\ was employed to obtain the structural responses, which were compared to those obtained employing the NBR6123. The results show that the distinct flow patterns around the model result in a load with also distinct levels of correlation. In conclusion, the POD is a powerful analysis tool that allows a safer and optimized structural design.

Made available in DSpace on 2015-05-07T14:49:36Z (GMT). No. of bitstreams: 1 arquivototal.pdf: 10226116 bytes, checksum: 00c57b6430d40332cb7d0f99dc974a3e (MD5) Previous issue date: 2014-04-29 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Given the complexity of the phenomenon of degradation/desertification in semi-arid northeast it becomes increasingly necessary intensification of studies in which the process, showing its size and the impacts of human activities on the landscape areas in the region. Therefore, several studies have used methods that make use of geotechnology and indicators for analysis of this phenomenon, considering mitigation actions and understanding of the same .Thus, the present study was to scope the spatio- temporal analysis of the degradation / desertification in Taperoá River Basin, through the integration of the physical environmental and socioeconomic indicators, with the support of geotechnology. As a methodological approach to analyze the evolution of the socioeconomic indicators were used the data of the last three demographic and agricultural census , checking the status of improvement or worsening of each indicator in full or partially municipalities in the basin. For physical environmental indicators techniques of digital image processing and GIS were used. Finally maps the evolution of each group of indicators are generated and made the spatial correlation between the levels of desertification. As a result of the levels of desertification was identified that 49.15% of the total area in basin are on average level; 36.81 % at low level and 11.08% at a high level; pointing to a recovery process of vegetation in the region over the past twenty years. The spatial correlation with the social and economic indicators was considered indirect, due to the influence of external factors such as public politics. Have the spatial correlation with agriculture indicators presented more directly, since they reflect the intensity of land use. There is a strong spatial correlation between the levels of rainfall, the topography of the region and the state of vegetation cover and therefore, the levels of desertification. / Diante da complexidade do fenômeno da degradação/desertificação no semiárido brasileiro, torna-se cada vez mais necessário a intensificação de estudos em áreas susceptíveis ao processo, que mostrem sua dimensão e os impactos das atividades humanas sobre a paisagem nessa região. Nesse sentido, diversos estudos vêm utilizando metodologias que fazem uso das geotecnologias e de indicadores para análise desse fenômeno, tendo em vista ações de mitigação e de entendimento do mesmo. Deste modo, o presente trabalho teve como escopo a análise espaço-temporal do processo de degradação/desertificação na Bacia Hidrográfica do Rio Taperoá-Pb, através da integração de indicadores físico-ambientais e socioeconômicos, com apoio das geotecnologias. Para análise da evolução dos indicadores socioeconômicos, foram utilizados dados dos três últimos censos demográficos e agropecuários, verificando a situação de melhora ou piora de cada indicador nos municípios inseridos, total ou parcialmente, na bacia. Para gerar os indicadores físico-ambientais foram utilizadas técnicas de processamento digital de imagens e de geoprocessamento. Por fim, foram gerados mapas da evolução de cada grupo de indicadores e feita a correlação espacial com o mapa dos níveis de desertificação. Como resultado dos níveis de desertificação foi identificado que 49,15% da área total da bacia estão em nível médio, 36,81% em nível baixo e 11,08% em nível alto, o que aponta para um processo de recuperação da cobertura vegetal na região nos últimos vinte anos. A correlação com os indicadores sociais e econômicos foi feita de forma indireta, devido à influência de fatores externos, como as políticas públicas. Já a correlação com os indicadores agropecuários foi feita de forma mais direta, visto que estes refletem a intensidade do uso das terras. Também foi verificada uma forte correlação espacial entre os níveis de precipitação, a topografia da região e a situação da cobertura vegetal e, portanto, com os níveis de desertificação.

Made available in DSpace on 2015-05-08T14:44:50Z (GMT). No. of bitstreams: 1 Arquivototal.pdf: 1070265 bytes, checksum: 41d67c357b7266afb5172394d3c6dfd2 (MD5) Previous issue date: 2012-09-28 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / This study aims to characterize the levels and patterns of concentration of industrial activity in the state of Rio Grande do Norte in the period between 2000 and 2010. For this there will be the calculation of the indices of spatial correlation Global Moran's I and local (LISA) defined by Anselin (1995) between the territorial subdivisions of the state - microregions. It was identified that the state only has clusters of positive spatial correlation in the manufacturing industry and the sectors of capital, labor and natural resource intensive. It was also observed that the resource sector is less concentrated in both years considered polar and that all sectors have experienced decentralization of industrial activities except for the labor-intensive sector, which takes the place of more concentrated industry in 2010, this place occupied by the capital-intensive sector in 2000. In the estimation of the model say that the influence of the variables defined in the theory of growth was observed that the small amount of micro state not allowed to obtain a model very consistent. This suggested the estimation of models considering the variables individually, allowing better understand the influence that the wages paid to the worker, the average size of establishments, the distances of the micro and the capital share in manufacturing employment that each state has in the micro affect growth of such participation, indicating the agglomeration tendencies. The results are consistent with the arguments presented in the New Economic Geography and the empirical studies that have been done to test them. / O presente trabalho busca caracterizar os níveis e padrões de concentração da atividade industrial no estado do Rio Grande do Norte no período compreendido entre os anos 2000 e o ano 2010. Para isso será realizado o cálculo dos índices de correlação espacial I de Moran Global e local (LISA) definidos por Anselin (1995) entre as subdivisões territoriais do estado microrregiões. Foi identificado que o estado só apresenta aglomerados de correlação espacial positiva na indústria de transformação e nos setores de capital, trabalho e recursos naturais intensivos. Também foi observado que o setor de recursos naturais é o menos concentrado em ambos os anos polares considerados e que todos os setores sofreram desconcentração das atividades industriais com exceção do setor de trabalho intensivo, que ocupa o lugar de setor mais concentrado em 2010, lugar esse ocupado pelo setor de capital intensivo no ano 2000. Na estimação do modelo que descreve a influência das variáveis definidas na teoria sobre o crescimento foi observado que a quantidade pequena de microrregiões do estado não permitiu a obtenção de um modelo muito consistente. Isso sugeriu a estimação de modelos considerando as variáveis individualmente, o que permitiu entender melhor a influência que o salário pago ao trabalhador, o tamanho médio dos estabelecimentos, a distâncias das microrregiões à capital e a participação no emprego industrial que cada microrregião tem no estado afetam o crescimento dessa participação, indicando tendências à aglomeração. Os resultados são coerentes com os argumentos apresentados na Nova Geografia Econômica e com os trabalhos empíricos que vêm sendo feitos para testá-los.