Thus far, a plethora of analysis on genome-wide gene expression microarray experiments on the cell cycle have been reported. Time series data from these experiments include gene expression profiles that might be periodically expressed. However, the numbers and actual genes that are periodically expressed have not been reported with consistency, analysis on similar experiments reports disparate numbers of genes that are periodically expressed with scant overlap. This work ultimately compares the performance of five spectral estimation schemes in their ability to recover periodically expressed genes profiles. Lomb-Scargle (LS), Capon, Missing-Data Amplitude and Phase Estimation (MAPES), Real Value Iterative Adaptive Approach (RIAA) and Lomb-Scargle Periodogram Regression (LSPR) are rigorously studied and pitted against each other in various simulated testing conditions. Results obtained using synthetic and microarray data reveals that RIAA is an efficient and robust method for the detection of periodically expressed genes in short time series data that might be characterized with noisy and irregularly sampled data points.

Made available in DSpace on 2014-12-17T14:56:03Z (GMT). No. of bitstreams: 1 LuizPSM_DISSERT.pdf: 2597772 bytes, checksum: 2a89626ca2223935451ac8cbba3ad340 (MD5) Previous issue date: 2012-02-24 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior / Digital signal processing (DSP) aims to extract specific information from digital signals. Digital signals are, by definition, physical quantities represented by a sequence of discrete values and from these sequences it is possible to extract and analyze the desired information. The unevenly sampled data can not be properly analyzed using standard techniques of digital signal processing. This work aimed to adapt a technique of DSP, the multiresolution analysis, to analyze unevenly smapled data, to aid the studies in the CoRoT laboratory at UFRN. The process is based on re-indexing the wavelet transform to handle unevenly sampled data properly. The was efective presenting satisfactory results / O processamento digital de sinais (PDS) tem como objetivo a extra??o de informa??es espec?ficas a partir de sinais armazenados digitalmente. Os sinais digitais s?o, por defini??o, grandezas f?sicas representadas por uma sequ?ncia de valores discretos e ? a partir dessas sequ?ncias de valores que ? poss?vel extrair e analisar as informa??es desejadas. Os sinais digitais n?o regularmente espa?ados n?o s?o corretamente analisados utilizando as t?cnicas padr?es do processamento digital de sinais. Neste trabalho teve-se o objetivo de adequar uma t?cnica de PDS, a an?lise multiresolu??o, para analisar sinais n?o regularmente espa?ados, visando auxiliar as pesquisas realizadas no laborat?rio CoRoT na UFRN. O trabalho desenvolvido consiste em uma reindexa??o da transformada Wavelet para tratar os dados n?o regularmente espa?ados de maneira adequada. O m?todo mostrou-se efetivo, apresentando resultados satisfat?rios

Thesis (Doctor of Engineering in Electrical Engineering)--Cape Peninsula University of Technology, 2017. / Remote sensing provides a way of frequently observing broad land surfaces. The availability of various earth observation data and their potential exploitation in a wide range of socioeconomic applications stimulated the rapid development of remote sensing technology. Much of the research and most of the publications dealing with remote sensing in the solar spectral domain focus on analysing and interpreting the spectral, spatial and temporal signatures of the observed areas. However, the angular signatures of the reflectance field, known as surface anisotropy, also merit attention. The current research took an exploratory approach to the land surface anisotropy described by the RPV model parameters derived from the MISR-HR processing system (denoted as MISR-HR anisotropy data or MISR-HR RPV data), over a period of 14+ years, for three typical terrestrial surfaces in the Western Cape Province of South Africa: a semi-desert area, a wheat field and a vineyard area. The objectives of this study were to explore (1) to what extent spectral and directional signatures of the MISR-HR RPV data may vary in time and space over the different targets (landscapes), and (2) whether the observed variations in anisotropy might be useful in classifying different land surfaces or as a supplementary method to the traditional land cover classification method. The objectives were achieved by exploring the statistics of the MISR-HR RPV data in each spectral band over the different land surfaces, as well as seasonality and trend in these data. The MISR-HR RPV products were affected by outliers and missing values, both of which influenced the statistics, seasonality and trend of the examined time series. This research proposes a new outlier detection method, based on the cost function derived from the RPV model inversion process. Removed outliers and missing values leave gaps in a MISR-HR RPV time series; to avoid introducing extra biases in the statistics of the anisotropy data, this research kept the gaps and relied on gap-resilient trend and seasonality detection methods, such as the Mann-Kendal trend detection and Lomb-Scargle periodogram methods. The exploration of the statistics of the anisotropy data showed that RPV parameter rho exhibited distinctive over the different study sites; NIR band parameter k exhibits prominent high values for the vineyard area; red band parameter Theta data are not that distinctive over different study sites; variance is important in describing all three RPV parameters. The explorations on trends also demonstrated interesting findings: the downward trend in green band parameter rho data for the semi-desert and vineyard areas; and the upward trend in blue band parameters k and Theta data for all the three study sites. The investigation on seasonality showed that all the RPV parameters had seasonal variations which differed over spectral bands and land covers; the results confirmed expectations in previous literature that parameter varies regularly along the observation time, and also revealed seasonal variations in the parameter rho and Theta data. The explorations on the statistics and seasonality of the MISR-HR anisotropy data show that these data are potentially useful for classifying different landscapes. Finally, the classification results demonstrated that both red band parameter rho data and NIR band parameter k data could successfully separate the three different land surfaces in this research, which fulfilled the second primary objective of this study. This research also demonstrated a classification method using multiple RPV parameters as the classification signatures to discriminate different terrestrial surfaces; significant separation results were obtained by this method.

The theory of stellar evolution and stellar structure relies on the observation of stars in di erent phases of their evolutionary cycle. The relation between observations and theory can be strengthened by obtaining observational data of a large sample of stars in a particular evolutionary phase. The search for Cephei stars, as conducted in this study, can contribute to the sample of known Cephei stars, where these interesting stars are massive non-supergiant early B-type stars, displaying pulsating behaviour which is not well understood. Stars tend to form in clusters where it can therefore be expected that young massive stars can be found in open clusters. For this reason two young southern open clusters were observed in order to search for B-type pulsating stars. The region of NGC 6204 and Hogg 22 was observed over a period of thirteen nights in Johnson B, V and I bands. NGC 6204 is believed to be the oldest cluster of the two at a distance of 0.8 kpc while the much younger Hogg 22 is more distant at 2.8 kpc. These two open clusters are located 6 arcminutes apart which made it possible to observe them simultaneously with a 12.8 12.8 arcminute eld of view. The observations were done with the newly installed 1600 telescope of the North-West University, South Africa. In order to do a variability search, periodic stars need to be identi ed from the cluster data, where a typical data set may contain thousands of scienti c images. In addition to the main motivation for this study, a pipeline was created in order to automate the photometry and data reduction processes. A Lomb-Scargle transform was applied to the stellar light curves in order to identify periodic sources. 354 signi cantly periodic stars were identi ed from the 3182 observed stars. Amongst them, two new possible Cephei stars were found together with a possible slowly pulsating B star (SPB), and numerous eclipsing binary systems. By using photometry of this region obtained by Forbes & Short (1996), instrumental magnitudes were transformed to a standard system in order to compare photometry results. From the constructed colour magnitude diagram of the two clusters, it could be seen that some stars, indicated by Forbes & Short (1996) to be cluster members, were in fact eld stars belonging to neither cluster. The reduction and photometry pipeline was implemented successfully on the data set, which also highlighted the importance of instrumentation and correct data analysis procedures. Possible improvements were identi ed in order to overcome di culties experienced during this study. / Thesis (MSc (Space Physics))--North-West University, Potchefstroom Campus, 2013

The theory of stellar evolution and stellar structure relies on the observation of stars in di erent phases of their evolutionary cycle. The relation between observations and theory can be strengthened by obtaining observational data of a large sample of stars in a particular evolutionary phase. The search for Cephei stars, as conducted in this study, can contribute to the sample of known Cephei stars, where these interesting stars are massive non-supergiant early B-type stars, displaying pulsating behaviour which is not well understood. Stars tend to form in clusters where it can therefore be expected that young massive stars can be found in open clusters. For this reason two young southern open clusters were observed in order to search for B-type pulsating stars. The region of NGC 6204 and Hogg 22 was observed over a period of thirteen nights in Johnson B, V and I bands. NGC 6204 is believed to be the oldest cluster of the two at a distance of 0.8 kpc while the much younger Hogg 22 is more distant at 2.8 kpc. These two open clusters are located 6 arcminutes apart which made it possible to observe them simultaneously with a 12.8 12.8 arcminute eld of view. The observations were done with the newly installed 1600 telescope of the North-West University, South Africa. In order to do a variability search, periodic stars need to be identi ed from the cluster data, where a typical data set may contain thousands of scienti c images. In addition to the main motivation for this study, a pipeline was created in order to automate the photometry and data reduction processes. A Lomb-Scargle transform was applied to the stellar light curves in order to identify periodic sources. 354 signi cantly periodic stars were identi ed from the 3182 observed stars. Amongst them, two new possible Cephei stars were found together with a possible slowly pulsating B star (SPB), and numerous eclipsing binary systems. By using photometry of this region obtained by Forbes & Short (1996), instrumental magnitudes were transformed to a standard system in order to compare photometry results. From the constructed colour magnitude diagram of the two clusters, it could be seen that some stars, indicated by Forbes & Short (1996) to be cluster members, were in fact eld stars belonging to neither cluster. The reduction and photometry pipeline was implemented successfully on the data set, which also highlighted the importance of instrumentation and correct data analysis procedures. Possible improvements were identi ed in order to overcome di culties experienced during this study. / Thesis (MSc (Space Physics))--North-West University, Potchefstroom Campus, 2013