Electronic imaging technologies are faced with the challenge of power consumption when transmitting large amounts of image data from the acquisition imager to the display or processing devices. This is especially a concern for portable applications, and becomes more prominent in increasingly high-resolution, high-frame rate imagers. Therefore, new sampling techniques are needed to minimize transmitted data, while maximizing the conveyed image information. <br /><br /> From this point of view, two approaches have been proposed and implemented in this thesis: <ol> <li> A system-level approach, in which the classical 1D row sampling CMOS imager is modified to a 2D ring sampling pyramidal architecture, using the same standard three transistor (3T) active pixel sensor (APS). </li> <li> A device-level approach, in which the classical orthogonal architecture has been preserved while altering the APS device structure, to design an expandable multiresolution image sensor. </li> </ol> A new scanning scheme has been suggested for the pyramidal image sensor, resulting in an intrascene foveated dynamic range (FDR) similar in profile to that of the human eye. In this scheme, the inner rings of the imager have a higher dynamic range than the outer rings. The pyramidal imager transmits the sampled image through 8 parallel output channels, allowing higher frame rates. The human eye is known to have less sensitivity to oblique contrast. Using this fact on the typical oblique distribution of fixed pattern noise, we demonstrate lower perception of this noise than the orthogonal FPN distribution of classical CMOS imagers. <br /><br /> The multiresolution image sensor principle is based on averaging regions of low interest from frame-sampled image kernels. One pixel is read from each kernel while keeping pixels in the region of interest at their high resolution. This significantly reduces the transferred data and increases the frame rate. Such architecture allows for programmability and expandability of multiresolution imaging applications.

Electronic imaging technologies are faced with the challenge of power consumption when transmitting large amounts of image data from the acquisition imager to the display or processing devices. This is especially a concern for portable applications, and becomes more prominent in increasingly high-resolution, high-frame rate imagers. Therefore, new sampling techniques are needed to minimize transmitted data, while maximizing the conveyed image information. <br /><br /> From this point of view, two approaches have been proposed and implemented in this thesis: <ol> <li> A system-level approach, in which the classical 1D row sampling CMOS imager is modified to a 2D ring sampling pyramidal architecture, using the same standard three transistor (3T) active pixel sensor (APS). </li> <li> A device-level approach, in which the classical orthogonal architecture has been preserved while altering the APS device structure, to design an expandable multiresolution image sensor. </li> </ol> A new scanning scheme has been suggested for the pyramidal image sensor, resulting in an intrascene foveated dynamic range (FDR) similar in profile to that of the human eye. In this scheme, the inner rings of the imager have a higher dynamic range than the outer rings. The pyramidal imager transmits the sampled image through 8 parallel output channels, allowing higher frame rates. The human eye is known to have less sensitivity to oblique contrast. Using this fact on the typical oblique distribution of fixed pattern noise, we demonstrate lower perception of this noise than the orthogonal FPN distribution of classical CMOS imagers. <br /><br /> The multiresolution image sensor principle is based on averaging regions of low interest from frame-sampled image kernels. One pixel is read from each kernel while keeping pixels in the region of interest at their high resolution. This significantly reduces the transferred data and increases the frame rate. Such architecture allows for programmability and expandability of multiresolution imaging applications.

As software and hardware systems grow more complex and we begin to rely more on their correctness and reliability, it becomes exceedingly important to formally verify certain properties of these systems. If done na&iuml;vely, verifying a system can easily require exponentially more work than running it, in order to account for all possible executions. However, there are often symmetries or other properties of a system that can be exploited to reduce the amount of necessary work. In this thesis, we present a number of approaches that do this in the context of the CSP model checker FDR. CSP is named for Communicating Sequential Processes, or parallel combinations of state machines with synchronised communications. In the FDR model, the component processes are typically converted to explicit state machines while their parallel combination is evaluated lazily during model checking. Our contributions are motivated by this model but applicable to other models as well. We first address the scalability of the component machines by proposing a lazy compiler for a subset of CSP_M selected to model parameterised state machines. This is a typical case where the state space explosion can make model checking impractical, since the size of the state space is exponential in the number and size of the parameters. A lazy approach to evaluating these systems allows only the reachable subset of the state space to be explored. As an example, in studying security protocols, it is common to model an intruder parameterised by knowledge of each of a list of facts; even a relatively small 100 facts results in an intractable 2¹⁰⁰ states, but the rest of the system can ensure that only a small number of these states are reachable. Next, we address the scalability of the overall combination by presenting novel algorithms for bisimulation reduction with respect to strong bisimulation, divergence- respecting delay bisimulation, and divergence-respecting weak bisimulation. Since a parallel composition is related to the Cartesian product of its components, performing a relatively time-consuming bisimulation reduction on the components can reduce its size significantly; an efficient bisimulation algorithm is therefore very desirable. This thesis is motivated by practical implementations, and we discuss an implementation of each of the proposed algorithms in FDR. We thoroughly evaluate their performance and demonstrate their effectiveness.

Neste trabalho apresenta-se uma revisão da metodologia de experimentos de microarray relativas a sua instalação e análise estatística dos dados obtidos. A seguir, aplica-se essa metodologia na análise de dados de expressão gênica em citros, gerados por um experimento de macroarray, utilizando modelos lineares de efeitos fixos considerando a inclusão ou não de diferentes efeitos e considerando ajustes de modelos para cada gene separadamente e para todos os genes simultaneamente. Os experimentos de macroarray são similares aos experimentos de microarray, porém utilizam um menor número de genes. Em geral, são utilizados devido a restrições econômicas. Devido ao fato de terem sido utilizados poucos arrays no experimento analisado neste trabalho foi utilizada uma abordagem bayesiana empírica que utiliza estimativas de variância mais estáveis e que leva em consideração a correlação entre as repetições do gene dentro do array. Também foi utilizado um método de análise não paramétrico para contornar o problema da falta de normalidade para alguns genes. Os resultados obtidos em cada um dos métodos de análise descritos foram então comparados. / This paper presents a review of the methodology of microarray experiments for its installation and statistical analysis of data obtained. Then this methodology is applied in data analysis of gene expression in citrus, generated by a macroarray experiment, using linear models with fixed effects considering the inclusion or exclusion of different effects and considering adjustments of models for each gene separately and for all genes simultaneously. The macroarray experiments are similar to the microarray experiments, but use a smaller number of genes. In general, are used due to economic restrictions. Because they have been used a few arrays in the experiment analyzed in this study it was used a empirical Bayes approach that uses estimates of variance more stable and that takes into account the correlation among replicates of the gene within array. A non parametric analysis method was also used to outline the problem of the non normality for some genes. The results obtained in each of the described methods of analysis were then compared.

Reuse of reclaimed asphalt pavement (RAP) in the full-depth recycling (FDR) process is a cost-effective and environmentally responsible method of asphalt pavement reconstruction. Although FDR has been used for several years in some locations, the effect of RAP on the mechanical properties of recycled base materials has not been well documented. The purpose of this research was to investigate the influence of RAP on the mechanical properties of recycled base materials typical of northern Utah. Two sources of RAP, two sources of base, and RAP contents of 0, 25, 50, 75, and 100 percent were utilized in a full-factorial experimental design with three replicates of each unique combination. Testing procedures consisted of material classifications, compaction tests, and evaluations of strength, stiffness, and moisture susceptibility of each material blend. The California bearing ratio (CBR) test was used to measure strength, the free-free resonant column test was used to measure stiffness, and the tube suction test (TST) was used to measure moisture susceptibility. Once all the testing was completed, a fixed effects analysis of variance (ANOVA) was performed on each of the test results, or dependent variables. The independent variables were RAP content, RAP type, and base type, together with all their interactions. Results of the ANOVA were used to quantify the effects of RAP on the mechanical properties of the base materials. The data indicate that CBR values decrease as RAP content increases, with the greatest percentage reduction occurring with the addition of 25 percent RAP. For stiffness testing at the optimum moisture content determined for each blend, the general trend was a decrease in stiffness from 0 percent RAP to 25 percent RAP, followed by a steady increase in stiffness as the RAP content was increased from 25 to 100 percent. Following a 72-hr drying period at 140ºF, however, the general trend reversed; an increase in stiffness occurred as the RAP content was increased from 0 to 25 percent, and a steady decrease in stiffness was observed for RAP contents above 25 percent. The TST data suggest that additions of 25 and 50 percent RAP actually increase the moisture susceptibility of the recycled material compared to the neat base, although the blended material tested in this study was classified as non-moisture-susceptible when the RAP content was 75 percent or higher. Because of the marked impact of RAP content on the mechanical properties of recycled base materials, engineers should accurately determine asphalt layer thicknesses prior to pavement reconstruction and carefully determine the optimum blending depth for each project. While asphalt milling or base overlays may be required in some locations to avoid excessively high RAP contents, reduced blending depths may be warranted in other areas to prevent the use of low RAP contents. In summary, while the use of RAP in the FDR process is environmentally responsible and offers potentially significant cost savings, thicker pavement base layers, base stabilization, or both may be required in many instances to ensure adequate long-term pavement performance.

The Frequency Disturbance Recorder (FDR) is a specialized data acquisition device designed to monitor fluctuations in the overall power system. The device is designed such that it can be attached by way of a standard wall power outlet to the power system. These devices then transmit their calculated frequency data through the public internet to a centralized data management and storage server. By distributing a number of these identical systems throughout the three major North American power systems, Virginia Tech has created a Frequency Monitoring Network (FNET). The FNET is composed of these distributed FDRs as well as an Information Management Server (IMS). Since frequency information can be used in many areas of power system analysis, operation and control, there are a great number of end uses for the information provided by the FNET system. The data provides researchers and other users with the information to make frequency analyses and comparisons for the overall power system. Prior to the end of 2004, the FNET system was made a reality, and a number of FDRs were placed strategically throughout the United States. The purpose of this thesis is to present the elements of a new generation of FDR hardware design. These elements will enable the design to be more flexible and to lower reliance on some vendor specific components. Additionally, these enhancements will offload most of the computational processing required of the system to a commodity PC rather than an embedded system solution that is costly in both development time and financial cost. These goals will be accomplished by using a Field Programmable Gate Array (FPGA), a commodity off-the-shelf personal computer, and a new overall system design. / Master of Science

Recent large-scale blackouts revealed that power systems around the world are far from the stability and reliability requirement as they suppose to be. The post-event analysis clarifies that one major reason of the interconnection blackout is lack of wide area information. Frequency dynamics is one of the most important parameters of an electrical power system. In order to understand power system dynamics effectively, accurately measured wide-area frequency is needed. The idea of building an Internet based real-time GPS synchronized wide area Frequency Monitoring Network (FNET) was proposed to provide the imperative dynamic information for the large-scale power grids and the implementation of FNET has made the synchronized observations of the entire US power network possible for the first time. The FNET system consists of Frequency Disturbance Recorders (FDR), which work as the sensor devices to measure the real-time frequency at 110V single-phase power outlets, and an Information Management System (IMS) to work as a central server to process the frequency data. The device comparison between FDR and commercial PMU (Phasor Measurement Unit) demonstrate the advantage of FNET. The web visualization tools make the frequency data available for the authorized users to browse through Internet. The research work addresses some preliminary observations and analyses with the field-measured frequency information from FNET. The original algorithms based on the frequency response characteristic are designed to process event detection, localization and unbalanced power estimation during frequency disturbances. The analysis of historical cases illustrate that these algorithms can be employed in real-time level to provide early alarm of abnormal frequency change to the system operator. The further application is to develop an adaptive under frequency load shedding scheme with the processed information feed in to prevent further frequency decline in power systems after disturbances causing dangerous imbalance between the load and generation. / Ph. D.

Frequency dynamics is one of the most important signals of a power system, and it is an indicator of imbalance between generation and load in the system. The Internet-based real-time GPS-synchronized wide-area Frequency Monitoring Network (FNET) was proposed to provide imperative frequency dynamics information for a variety of system-wide monitoring, analysis and control applications. The implementation of FNET has for the first time made the synchronized observation of the entire U.S. power network possible with very little cost. The FNET is comprised of many Frequency Disturbance Recorders (FDR) geographically dispersed throughout the U.S. and an Information Management System (IMS), currently located at Virginia Tech. The FDR works as a sensor, which performs local measurements and transmits calculations of frequency, voltage magnitude and voltage angle to the remote servers via the Internet. Compared with its commercial counterpart Phasor Measurement Unit (PMU), FDR provides less expensive version for networked high-resolution real-time synchronized. The improved single phase algorithm in the FDRs made it possible to measure at 110V level which is much more challenging than PMUs due to the noise involved at this level. This research work presents the challenges and issues of both software and hardware design for the novel measurement device FDR, which is one of the devices with the highest dynamic precision for power system frequency measurement. The DFT-based Phasor Angle Analysis algorithm has been improved to make sure the high-resolution measuring FDRs are installed at residential voltage outlets, instead of substation high-voltage inputs. An embedded 12-channel timing GPS receiver has been integrated to provide an accurate timing synchronization signal, UTC time stamp, and unit location. This research work also addresses the harmonics, voltage swing and other noise components' impacts on the measurement results, and the optimized design of filters and a coherent sampling scheme to reduce or eliminate those impacts. The verification test results show that the frequency measurement accuracy of the FDR is within +/-0.0005Hz, and the time synchronization error is within +/-500ns with suitable GPS antenna installation. The preliminary research results show the measurement accuracy and real-time performance of the FDR are satisfactory for a variety of FNET applications, such as disturbance identification and event location triangulation. / Ph. D.

This thesis investigates the application of In-Situ Recycling and provides guidelines for localities to aid in the selection of recycling methods, as well as documents a local government's experience with Cold In-Place Recycling. The recycling methods discussed in this study include Cold In-Place Recycling (CIR), Hot In-Place Recycling (HIR), and Full Depth Reclamation (FDR). These methods are performed onsite and in-place in a continuous process of milling, mixing, and placement. The In-Situ Recycling guidelines include suggestions based on: traffic characteristics, existing road condition, distress types, road access, local climate, road geometry, and other road characteristics. The guidelines are based on information from sources including NCHRP Synthesis 421, American Recycling and Reclamation Association (ARRA), FHWA, and state agencies with recycling experience. This study also resulted in documenting obstacles that localities may face when in-situ recycling, as well as the impact of limited experience with recycling. The study also evaluated the construction of Cold In-Place Recycled pavement sections in Christiansburg, VA, using Falling Weight Deflectometer (FWD) and Ground Penetrating Radar (GPR). Additionally, using the FWD and GPR data, alternate recycled designs were proposed in addition to a cost comparison to a conventional design. / Master of Science

L’énergie éolienne, l’une des énergies renouvelables les plus compétitives, est considérée comme une solution qui remédie aux inconvénients de l’énergie fossile. Pour une meilleure gestion et exploitation de cette énergie, des prévisions de sa production s’avèrent nécessaires. Les méthodes de prévisions utilisées dans la littérature permettent uniquement une prévision de la moyenne annuelle de cette production. Certains travaux récents proposent l’utilisation du Théorème Central Limite (TCL), sous des hypothèses non classiques, pour l’estimation de la production annuelle moyenne de l’énergie éolienne ainsi que sa variance pour une seule turbine. Nous proposons dans cette thèse une extension de ces travaux à un parc éolien par relaxation de l’hypothèse de stationnarité la vitesse du vent et la production d’énergie, en supposant que ces dernières sont saisonnières. Sous cette hypothèse la qualité de la prévision annuelle s’améliore considérablement. Nous proposons aussi de prévoir la production d’énergie éolienne au cours des quatre saisons de l’année. L’utilisation du modèle fractal, nous permet de trouver une division ”naturelle” de la série de la vitesse du vent afin d’affiner l’estimation de la production éolienne en détectant les points de ruptures. Dans les deux derniers chapitres, nous donnons des outils statistiques de la détection des points de ruptures et d’estimation des modèles fractals. / The wind energy, one of the most competitive renewable energies, is considered as a solution which remedies the inconveniences of the fossil energy. For a better management and an exploitation of this energy, forecasts of its production turn out to be necessary. The methods of forecasts used in the literature allow only a forecast of the annual mean of this production. Certain recent works propose the use of the Central Limit Theorem (CLT), under not classic hypotheses, for the estimation of the mean annual production of the wind energy as well as its variance for a single turbine. We propose in this thesis, an extension of these works in a wind farm by relaxation of the hypothesis of stationarity the wind speed and the power production, supposing that the latter are seasonal. Under this hypothesis the quality of the annual forecast improves considerably. We also suggest planning the wind power production during four seasons of the year. The use of the fractal model, allows us to find a "natural" division of the series of the wind speed to refine the estimation of the wind production by detecting abrupt change points. Statistical tools of the change points detection and the estimation of fractal models are presented in the last two chapters.