Carbon Dioxide concentration in Earth’s atmosphere is currently at 417 Parts permillion (ppm) and keep rising. Historic CO2 levels and historic temperature levels hasbeen cycling over the past 800,000 years. To study the trend of CO2 and temperatureover past 800,00 years, one needs to find out the relation between historic CO2 andhistoric temperature levels. In this project, we will perform different tasks to identify thetrend influencer between CO2 and temperature. Cross correlation technique is used tofind out the relation between two random signals. Temperature and CO2 data areconsidered as two random signals. Re-sampling by Interpolation techniques are imposedon both CO2 and temperature data for the change of sampling rate. Short time crosscorrelation technique is employed on the CO2 and temperature data over the differenttime windows to find out the time lag. Time lag refers to how far the signals are offset.

<p><p>Benchmarking of DSP kernel algorithms was conducted in the thesis on a DSP processor for teaching in the course TESA26 in the department of Electrical Engineering. It includes benchmarking on cycle count and memory usage. The goal of the thesis is to evaluate the quality of a single MAC DSP instruction set and provide suggestions for further improvement in instruction set architecture accordingly. The scope of the thesis is limited to benchmark the processor only based on assembly coding. The quality check of compiler is not included. The method of the benchmarking was proposed by BDTI, Berkeley Design Technology Incorporations, which is the general methodology used in world wide DSP industry.</p><p>Proposals on assembly instruction set improvements include the enhancement of FFT and DCT. The cycle cost of the new FFT benchmark based on the proposal was XX% lower, showing that the proposal was right and qualified. Results also show that the proposal promotes the cycle cost score for matrix computing, especially matrix multiplication. The benchmark results were compared with general scores of single MAC DSP processors offered by BDTI.</p></p>

Benchmarking of DSP kernel algorithms was conducted in the thesis on a DSP processor for teaching in the course TESA26 in the department of Electrical Engineering. It includes benchmarking on cycle count and memory usage. The goal of the thesis is to evaluate the quality of a single MAC DSP instruction set and provide suggestions for further improvement in instruction set architecture accordingly. The scope of the thesis is limited to benchmark the processor only based on assembly coding. The quality check of compiler is not included. The method of the benchmarking was proposed by BDTI, Berkeley Design Technology Incorporations, which is the general methodology used in world wide DSP industry. Proposals on assembly instruction set improvements include the enhancement of FFT and DCT. The cycle cost of the new FFT benchmark based on the proposal was XX% lower, showing that the proposal was right and qualified. Results also show that the proposal promotes the cycle cost score for matrix computing, especially matrix multiplication. The benchmark results were compared with general scores of single MAC DSP processors offered by BDTI.

This thesis proposes a novel approach for finding tables in text files containing a mixture of unstructured and structured text. Tables may be arbitrarily complex because the data in the tables may themselves be tables and because the grouping of data elements displayed in a table may be very complex. Although investigators have proposed competence models to explain the structure of tables, there are no computationally feasible performance models for detecting and parsing general structures in real data. Our emphasis is placed on the investigation of a new statistical procedure for detecting basic tables in plain text documents. The main task here is defining and testing this theory in the context of the Odessa Digital Library. / Master of Science

We introduced nested search methods to design (n, k) block codes for arbitrary channels by optimizing an appropriate metric spectrum in each iteration. For a given k, the methods start with a good high rate code, say k/(k + 1), and successively design lower rate codes up to rate k/2^k corresponding to a Hadamard code. Using a full search for small binary codes we found that optimal or near-optimal codes of increasing length can be obtained in a nested manner by utilizing Hadamard matrix columns. The codes can be linear if the Hadamard matrix is linear and non-linear otherwise. The design methodology was extended to the generic complex codes by utilizing columns of newly derived or existing unitary codes. The inherent nested nature of the codes make them ideal for progressive transmission. Extensive comparisons to metric bounds and to previously designed codes show the optimality or near-optimality of the new codes, designed for the fading and the additive white Gaussian noise channel (AWGN). It was also shown that linear codes can be optimal or at least meeting the metric bounds; one example is the systematic pilot-based code of rate k/(k + 1) which was proved to meet the lower bound on the maximum cross-correlation. Further, the method was generalized such that good codes for arbitrary channels can be designed given the corresponding metric or the pairwise error probability. In synchronous multiple-access schemes it is common to use unitary block codes to transmit the multiple users’ information, especially in the downlink. In this work we suggest the use of newly designed non-unitary block codes, resulting in increased throughput e&#64259;ciency, while the performance is shown not to be substantially sacri&#64257;ced. The non-unitary codes are again developed through suitable nested searches. In addition, new multiple-access codes are introduced that optimize certain criteria, such as the sum-rate capacity. Finally, the introduction of the asymptotically optimum convolutional codes for a given constraint length, reduces dramatically the search size for good convolutional codes of a certain asymptotic performance, and the consequences to coded code-division multiple access (CDMA) system design are highlighted.

Made available in DSpace on 2017-05-12T14:47:10Z (GMT). No. of bitstreams: 1 Ademir Natal Correa.pdf: 1505539 bytes, checksum: fd8e294f5766bf4043789d75eba28f1f (MD5) Previous issue date: 2007-07-16 / The objective of this study was to assess the relationship among soil physical attributes and their influences on wheat yield. For this purpose an estimating method, called State-Space Model or dynamic linear regression model, was used and compared to simple and multiple regression models of classical statistics. Experimental data were obtained at a Rhodic Ferralsol, originated from UNIOESTE Agricultural Engineering Experimental Nucleus Cascavel Campus, in an area where wheat was grown. In this area, 3 equally spaced transects, with 97 sampling points, 3.0 meters away from each other, were delimited. The State-Space approach was used to assess wheat yield estimate on position i, influenced by wheat yield, bulk density, soil compaction degree and soil resistance to penetration on position i-1 in different combination between data series of these variables. Applying the State-Space approach, all the response variables presented significant correlation with the dependent variable: soil resistance to penetration was the attribute with the best correlation, presenting R2 coefficient equal to 0.849. The other attributes had R2 coefficient of around 0.800. Comparing to conventional static models, soil resistance to penetration attribute had R2 coefficient equal to 0.102. The other attributes had R2 coefficient equal or less than 0.087, in conventional regression. Utilizing the State-Space approach, the two combinations that indicated the best results were: 1) between wheat yield and soil resistance to penetration that showed the best estimate to wheat yield with R2 coefficient equal to 0.849, while the same combination in conventional regression presented R2 equal to 0.102; 2) between wheat yield, soil compaction degree and soil resistance to penetration, with R2 coefficient equal to 0.836, while the same combination in classical regression presented R2 equal to 0.217. Thus, it is possible to show the advantage of the State-Space approach in relation to other more conventional regression methods for estimating and forecasting in soil-plant system relationship. / Este trabalho foi realizado com o objetivo de estudar o relacionamento entre os atributos físicos do solo e a influência destes na produtividade de trigo. Para isso, utilizou-se o método de estimação chamado de Modelo de Espaço de Estados ou modelo de regressão linear dinâmico, comparando-o aos modelos de regressão simples e múltipla da estatística clássica. Os dados experimentais foram obtidos em um Latossolo Vermelho-Escuro pertencente ao Núcleo Experimental de Engenharia Agrícola da Universidade Estadual do Oeste do Paraná Campus de Cascavel, em uma área cultivada com trigo. Foram demarcadas 3 transeções com 97 pontos de amostragem espaçados de 3 m entre si. A abordagem de Espaço de Estados foi usada para avaliar a estimativa da produtividade do trigo na posição i, influenciada por medidas da produtividade do trigo, da densidade do solo, do grau de compactação do solo e da resistência do solo à penetração na posição i-1, em diferentes combinações entre as séries de dados dessas variáveis. Com a aplicação da abordagem de Espaço de Estados, todas as variáveis explicativas utilizadas apresentaram correlação significativa com a variável dependente: a resistência do solo à penetração foi o atributo com a melhor correlação, apresentando o coeficiente de ajuste R2 igual a 0,849. Os demais atributos tiveram os coeficientes R2 em torno de 0,800. Comparando-se com os modelos estáticos convencionais, o atributo resistência do solo à penetração teve o coeficiente de ajuste R2 igual a 0,102 e os demais atributos tiveram os seus coeficientes R2 abaixo de 0,087, na regressão convencional. Utilizando a metodologia de Espaço de Estados, as duas combinações que indicaram os melhores resultados foram a combinação entre produtividade do trigo e resistência do solo à penetração, que apresentou a melhor estimativa para produtividade do trigo, com coeficiente R2 igual a 0,849. A mesma combinação na regressão convencional resultou em R2 igual a 0,102. A segunda melhor combinação ocorreu entre os atributos: produtividade do trigo, grau de compactação do solo e resistência do solo à penetração, com R2 igual a 0,836, sendo que a mesma combinação na regressão clássica teve o coeficiente R2 igual a 0,217. Com isso é possível mostrar-se a vantagem da abordagem de Espaço de Estados em relação a outros métodos de estimativa e previsão para o relacionamento no sistema solo-planta.

Made available in DSpace on 2017-07-10T19:23:56Z (GMT). No. of bitstreams: 1 Ademir Natal Correa.pdf: 1505539 bytes, checksum: fd8e294f5766bf4043789d75eba28f1f (MD5) Previous issue date: 2007-07-16 / The objective of this study was to assess the relationship among soil physical attributes and their influences on wheat yield. For this purpose an estimating method, called State-Space Model or dynamic linear regression model, was used and compared to simple and multiple regression models of classical statistics. Experimental data were obtained at a Rhodic Ferralsol, originated from UNIOESTE Agricultural Engineering Experimental Nucleus Cascavel Campus, in an area where wheat was grown. In this area, 3 equally spaced transects, with 97 sampling points, 3.0 meters away from each other, were delimited. The State-Space approach was used to assess wheat yield estimate on position i, influenced by wheat yield, bulk density, soil compaction degree and soil resistance to penetration on position i-1 in different combination between data series of these variables. Applying the State-Space approach, all the response variables presented significant correlation with the dependent variable: soil resistance to penetration was the attribute with the best correlation, presenting R2 coefficient equal to 0.849. The other attributes had R2 coefficient of around 0.800. Comparing to conventional static models, soil resistance to penetration attribute had R2 coefficient equal to 0.102. The other attributes had R2 coefficient equal or less than 0.087, in conventional regression. Utilizing the State-Space approach, the two combinations that indicated the best results were: 1) between wheat yield and soil resistance to penetration that showed the best estimate to wheat yield with R2 coefficient equal to 0.849, while the same combination in conventional regression presented R2 equal to 0.102; 2) between wheat yield, soil compaction degree and soil resistance to penetration, with R2 coefficient equal to 0.836, while the same combination in classical regression presented R2 equal to 0.217. Thus, it is possible to show the advantage of the State-Space approach in relation to other more conventional regression methods for estimating and forecasting in soil-plant system relationship. / Este trabalho foi realizado com o objetivo de estudar o relacionamento entre os atributos físicos do solo e a influência destes na produtividade de trigo. Para isso, utilizou-se o método de estimação chamado de Modelo de Espaço de Estados ou modelo de regressão linear dinâmico, comparando-o aos modelos de regressão simples e múltipla da estatística clássica. Os dados experimentais foram obtidos em um Latossolo Vermelho-Escuro pertencente ao Núcleo Experimental de Engenharia Agrícola da Universidade Estadual do Oeste do Paraná Campus de Cascavel, em uma área cultivada com trigo. Foram demarcadas 3 transeções com 97 pontos de amostragem espaçados de 3 m entre si. A abordagem de Espaço de Estados foi usada para avaliar a estimativa da produtividade do trigo na posição i, influenciada por medidas da produtividade do trigo, da densidade do solo, do grau de compactação do solo e da resistência do solo à penetração na posição i-1, em diferentes combinações entre as séries de dados dessas variáveis. Com a aplicação da abordagem de Espaço de Estados, todas as variáveis explicativas utilizadas apresentaram correlação significativa com a variável dependente: a resistência do solo à penetração foi o atributo com a melhor correlação, apresentando o coeficiente de ajuste R2 igual a 0,849. Os demais atributos tiveram os coeficientes R2 em torno de 0,800. Comparando-se com os modelos estáticos convencionais, o atributo resistência do solo à penetração teve o coeficiente de ajuste R2 igual a 0,102 e os demais atributos tiveram os seus coeficientes R2 abaixo de 0,087, na regressão convencional. Utilizando a metodologia de Espaço de Estados, as duas combinações que indicaram os melhores resultados foram a combinação entre produtividade do trigo e resistência do solo à penetração, que apresentou a melhor estimativa para produtividade do trigo, com coeficiente R2 igual a 0,849. A mesma combinação na regressão convencional resultou em R2 igual a 0,102. A segunda melhor combinação ocorreu entre os atributos: produtividade do trigo, grau de compactação do solo e resistência do solo à penetração, com R2 igual a 0,836, sendo que a mesma combinação na regressão clássica teve o coeficiente R2 igual a 0,217. Com isso é possível mostrar-se a vantagem da abordagem de Espaço de Estados em relação a outros métodos de estimativa e previsão para o relacionamento no sistema solo-planta.

Made available in DSpace on 2017-07-10T19:24:46Z (GMT). No. of bitstreams: 1 Marcio Paulo de Oliveira.pdf: 1960743 bytes, checksum: 7438fe00d388d47b01b27d6cfdf2e229 (MD5) Previous issue date: 2010-02-04 / The knowledge about soil and plant attributes is important for the improvement of agricultural management. Intense tillage activities may induce not only alterations in the soil attributes but also decrease in productivity. Studies directed to the soil and plant spatial variability identification and the relations amid these variables are tools for agriculture, with the potential to increase productivity. The data set for this study was sampled in a Rhodic Acrudox soil, at a farmland that has been being cultivated for over five years under no-tillage system, with soybean and wheat in crop succession. At 252 m long transect, 84 points were demarcated, with 3 m of spacing between each of them. The relations between soybean productivity and soil water content, micro, macro and total porosity, soil density and soil resistance to penetration at 0,0-0,10 m and 0,10-0,20 m deep layers, were evaluated, as well as the respective variabilities. The relations between soybean productivity and soil attributes were determined using simple and cross correlations, followed by the state space models determinations, compared to linear and multiple regression models. The results have shown that the soybean productivity and soil mechanical resistance variables presented not only autocorrelation structure but also crosscorrelation structure. The state space models, relating to the soybean productivity at a point i, with the same attribute at point i-1, at the two layers, were more efficient than the equivalent models in simple and multiple regression. With geoestatistics, the spatial dependence structure was determined with envelopes and models for the semivariograms, allowing identification and classification of the spatial dependence for the variables under study. The thematic maps were obtained with simple kriging and indicated the soil attributes behavior, related to the soybean productivity. / O conhecimento do comportamento dos atributos do solo e da planta é importante para a melhoria das práticas agrícolas. A intensa atividade de cultivo pode provocar modificações dos atributos do solo e reduzir a produtividade de uma cultura em determinada região. Os estudos que visam identificar a variabilidade espacial dos atributos do solo e da planta e a relação entre esses atributos surgem como um recurso para a agricultura, podendo ser utilizados para realização de um manejo adequado dos recursos disponíveis, ampliando a produtividade e preservando o meioambiente. Os dados para a realização deste estudo foram obtidos em um Latossolo Vermelho distroférrico, em uma área cultivada há mais de cinco anos com alternância entre as culturas de soja e trigo, com o sistema de plantio direto. Em uma transeção de 252 m de comprimento foram demarcados 84 elementos amostrais, espaçados de 3 m entre si. As relações da produtividade da soja com os seguintes atributos físicos e hídricos do solo: teor de água no solo, microporosidade, macroporosidade e porosidade total do solo, densidade do solo e resistência mecânica do solo à penetração, nas camadas 0,0-0,10 m e 0,10-0,20 m, foram avaliadas bem como a variabilidade espacial desses atributos. A relação entre a produtividade da soja e os atributos do solo foi determinada através das correlações simples e cruzada entre os elementos amostrais de cada atributo, seguida da estimação dos modelos em espaço de estados, comparados aos modelos equivalentes em regressão linear múltipla. Os resultados mostraram que as variáveis produtividade da soja e resistência do solo a penetração apresentaram estrutura de autocorrelação e de correlação cruzada entre si. Os modelos estimados em espaço de estados, relacionando a produtividade da soja em um ponto i com a produtividade da soja e resistência do solo a penetração nas duas camadas no ponto i -1 mostraram-se mais eficientes do que os modelos equivalentes estimados em regressão linear simples e múltipla. Por meio da geoestatística, a estrutura de dependência espacial foi avaliada por meio dos envelopes e modelos para os semivariogramas experimentais, permitindo identificar e classificar a dependência espacial das variáveis em estudo. Os mapas temáticos foram obtidos por meio de interpolação por krigagem ordinária e indicaram o comportamento dos atributos do solo ligadas a produtividade da soja.

Made available in DSpace on 2017-05-12T14:48:09Z (GMT). No. of bitstreams: 1 Marcio Paulo de Oliveira.pdf: 1960743 bytes, checksum: 7438fe00d388d47b01b27d6cfdf2e229 (MD5) Previous issue date: 2010-02-04 / The knowledge about soil and plant attributes is important for the improvement of agricultural management. Intense tillage activities may induce not only alterations in the soil attributes but also decrease in productivity. Studies directed to the soil and plant spatial variability identification and the relations amid these variables are tools for agriculture, with the potential to increase productivity. The data set for this study was sampled in a Rhodic Acrudox soil, at a farmland that has been being cultivated for over five years under no-tillage system, with soybean and wheat in crop succession. At 252 m long transect, 84 points were demarcated, with 3 m of spacing between each of them. The relations between soybean productivity and soil water content, micro, macro and total porosity, soil density and soil resistance to penetration at 0,0-0,10 m and 0,10-0,20 m deep layers, were evaluated, as well as the respective variabilities. The relations between soybean productivity and soil attributes were determined using simple and cross correlations, followed by the state space models determinations, compared to linear and multiple regression models. The results have shown that the soybean productivity and soil mechanical resistance variables presented not only autocorrelation structure but also crosscorrelation structure. The state space models, relating to the soybean productivity at a point i, with the same attribute at point i-1, at the two layers, were more efficient than the equivalent models in simple and multiple regression. With geoestatistics, the spatial dependence structure was determined with envelopes and models for the semivariograms, allowing identification and classification of the spatial dependence for the variables under study. The thematic maps were obtained with simple kriging and indicated the soil attributes behavior, related to the soybean productivity. / O conhecimento do comportamento dos atributos do solo e da planta é importante para a melhoria das práticas agrícolas. A intensa atividade de cultivo pode provocar modificações dos atributos do solo e reduzir a produtividade de uma cultura em determinada região. Os estudos que visam identificar a variabilidade espacial dos atributos do solo e da planta e a relação entre esses atributos surgem como um recurso para a agricultura, podendo ser utilizados para realização de um manejo adequado dos recursos disponíveis, ampliando a produtividade e preservando o meioambiente. Os dados para a realização deste estudo foram obtidos em um Latossolo Vermelho distroférrico, em uma área cultivada há mais de cinco anos com alternância entre as culturas de soja e trigo, com o sistema de plantio direto. Em uma transeção de 252 m de comprimento foram demarcados 84 elementos amostrais, espaçados de 3 m entre si. As relações da produtividade da soja com os seguintes atributos físicos e hídricos do solo: teor de água no solo, microporosidade, macroporosidade e porosidade total do solo, densidade do solo e resistência mecânica do solo à penetração, nas camadas 0,0-0,10 m e 0,10-0,20 m, foram avaliadas bem como a variabilidade espacial desses atributos. A relação entre a produtividade da soja e os atributos do solo foi determinada através das correlações simples e cruzada entre os elementos amostrais de cada atributo, seguida da estimação dos modelos em espaço de estados, comparados aos modelos equivalentes em regressão linear múltipla. Os resultados mostraram que as variáveis produtividade da soja e resistência do solo a penetração apresentaram estrutura de autocorrelação e de correlação cruzada entre si. Os modelos estimados em espaço de estados, relacionando a produtividade da soja em um ponto i com a produtividade da soja e resistência do solo a penetração nas duas camadas no ponto i -1 mostraram-se mais eficientes do que os modelos equivalentes estimados em regressão linear simples e múltipla. Por meio da geoestatística, a estrutura de dependência espacial foi avaliada por meio dos envelopes e modelos para os semivariogramas experimentais, permitindo identificar e classificar a dependência espacial das variáveis em estudo. Os mapas temáticos foram obtidos por meio de interpolação por krigagem ordinária e indicaram o comportamento dos atributos do solo ligadas a produtividade da soja.

Divers radars sont développés pour des besoins d’aide à la conduite automobile de sécurité mais aussi de confort. Ils ont pour but de détecter la présence d’obstacles routiers afin d’éviter d’éventuelles collisions. La demande actuelle en termes de capteurs radars pour l’automobile connaît une croissance importante et les technologies employées doivent garantir de bonnes performances dans un environnement dégradé par les signaux interférents des autres utilisateurs. Dans cette thèse, nous nous intéressons au développement d’un système radar performant en tout lieu et en particulier dans un contexte multi-utilisateurs. A ce propos, nous proposons de nouvelles formes d’ondes qui se basent sur la combinaison des codes fréquentiels de Costas et d’autres techniques de compression d’impulsion en exploitant les signaux de Costas modifiés. La conception adoptée permet, grâce à la diversité introduite, de synthétiser un nombre important de formes d’ondes. Nous avons, ensuite, exploité deux approches d’estimation des paramètres des cibles. La première, plutôt classique, se base sur le traitement Doppler dans un train d’impulsions cohérent. La deuxième, récente dans le domaine automobile, se base sur la technique dite de « Compressed Sensing ». Une adaptation de ces algorithmes pour les signaux proposés a été discutée dans des environnements bruités et multi-cibles. L’ensemble de ces travaux contribue à explorer de nouvelles formes d’ondes, autres que celles utilisées dans les radars actuels et à proposer un traitement innovant en réception, adapté aux radars en général et à l’automobile en particulier. / Several driver assistance radars are developed for security and comfort requirements. Their goal is among others to detect the presence of obstacles for collision avoidance. The current demand in terms of automotive radar sensors experience a significant growth and the technologies being employed must ensure good performances especially in an environment degraded by interfering signals of other users. In this thesis, we are interested in developing a radar system which is effective in all situations especially in a multi-user context. For this purpose, we propose novel radar waveforms based on the combination of frequency hopping Costas codes and other pulse compression techniques, using modified Costas signals. The design approach allows to synthesize a significant number of waveforms, thanks to the high diversity introduced. Afterwards, we have exploited two estimation of target parameters approaches. The first one, quite classic, is based on Doppler processing in a coherent pulse train. The second one, recent in the automotive field , is based on the Compressed sensing techniques. An adaptation of these algorithms to proposed signals is discussed in noisy and multi-target environments. All these works contribute in one hand to explore novel radar waveforms, complement to those currently used in automotive radars and in another hand to propose an innovative processing at the receiver level, suited to radar applications in general and automotive ones in particular.