Power amplifiers (PAs) are important components of communication systems and are inherently nonlinear. When a non-constant modulus signal goes through a nonlinear PA, spectral regrowth (broadening) appears in the PA output, which in turn causes adjacent channel interference (ACI). Stringent limits on the ACI are imposed by regulatory bodies, and thus the extent of the PA nonlinearity must be controlled. PA linearization is often necessary to suppress spectral regrowth, contain adjacent channel interference, and reduce bit error rate (BER). This dissertation addresses the following aspects of power amplifier research: modeling, linearization, and spectral regrowth analysis. We explore the passband and baseband PA input/output relationships and show that they manifest differently when the PA exhibits long-term, short-term, or no memory effects. The so-called quasi-memoryless case is especially clarified. Four particular nonlinear models with memory are further investigated. We provide experimental results to support our analysis. The benefits of using the orthogonal polynomials as opposed to the conventional polynomials are explored, in the context of digital baseband PA modeling and predistorter design. A closed-form expression for the orthogonal polynomial basis is derived. We demonstrate the improvement in numerical stability associated with the use of orthogonal polynomials for predistortion. Spectral analysis can help to evaluate the suitability of a given PA for amplifying certain signals or to assist in predistortion linearization algorithm design. With the orthogonal polynomials that we derived, spectral analysis of the nonlinear PA becomes a straightforward task. We carry out nonlinear spectral analysis with digitally modulated signal as input. We demonstrate an analytical approach for evaluating the power spectra of filtered QPSK and OQPSK signals after nonlinear amplification. Many communications devices are nonlinear and have a peak power or peak amplitude constraint. In addition to possibly amplifying the useful signal, the nonlinearity also generates distortions. We focus on signal-to-noise-and-distortion ratio (SNDR) optimization within the family of amplitude limited memoryless nonlinearities. We obtain a link between the capacity of amplitude-limited nonlinear channels with Gaussian noise to the SNDR.

In an event of a radiological dispersion device (RDD) detonated by terrorists in a high population density area, the hospitals and other medical facilities will be overwhelmed by people who may or may not have been contaminated by radioactivity. Under such circumstances, it would be desirable to identify people who have inhaled radioactive particles and direct them immediately for further treatment. A portable 3 by 3 NaI detector, which is widely available at most universities, was studied as a tool to identify and calculate the activity of unknown radioisotopes for such an RDD event.

Electrical Muscle Stimulation (EMS) is used as a countermeasure in animal disuse studies that seek to determine which forms of exercise are most effective in mitigating the effects of disuse atrophy on bone and muscle. Although EMS has been used for many years in our lab and others, few researchers have been able to quantify the levels of strain on rat tibiae during EMS and far fewer have investigated the causal relationship between torque produced at the ankle and strain on the tibia. This thesis sought to investigate the relationship between ankle torque and tibial strain by using a combination of techniques, namely: (1) the addition of rosette strain gages, (2) improved synchronization between ankle torque and tibial strain recordings, and (3) spectral analysis between torque and strain waveforms. In previous work, few methods existed to align torque and strain recordings temporally, as those data were recorded on separate computers and synchronizing events were not captured. Attempting to create a torque-strain crossplot with unsynchronized data does not always yield valid results, so a method of reliably synchronizing those data is required. This thesis developed methods to capture simultaneous (synchronizing) events in both torque and strain recordings and then used those captured events to synchronize data between two computers. Following that synchronization, stiffness calculations were run on torque-strain crossplots to determine linear-model relationships between torque and strain for each method of synchronization. The results from those regressions were then used to determine if one or more synchronization techniques are superior to others, in terms of repeatability or precision. The results of these analyses have shown that using portions of the curves can dramatically increase computing speed while providing high levels of repeatability in synchronization measures. After synchronization techniques had been investigated, 3-element rosette data were used to calculate the principal strains on the surface of the tibiae, and the percentage of principal strains that are accounted for in the axial direction. Since the strain environment changes along the axis of the bone, the principal strain data were plotted versus the distance from proximal epiphysis to rosette gage, and statistical analysis was presented. After rosette data were analyzed, the torque and strain data pairs were fed into a signal processing suite for the purpose of transfer function calculation. Using the synchronization methods outlined above, two means of synchronization were compared in the transfer function program. Results for these analyses demonstrated that transfer functions are slightly dependent on synchronization methods, but that calculated gains do not differ between synchronization techniques. The specific shapes of the transfer functions highlight the relative attenuation/amplification of frequencies in torque and strain signals. Specifically, a range of frequencies, commonly called a band, between 24 and 32Hz is attenuated by the soft tissues and mechanical linkages in the lower leg of rats. This finding gives researchers looking to increase or decrease modeling stimulus to bone a new piece of information about the relative efficiency of EMS exercise. For example, EMS performed at 24-25Hz might produce less strain in the tibia than EMS at 22-23Hz, despite the 22-23Hz stimulation producing marginally less torque.

In this work, the CHANDRA ACIS-S3 data of the old classical nova RR Pic (1925) is presented. The source is detected with a count rate of 0.067 (+-0.002) c/s in the 0.3-5.0 keV energy range. The orbital period of the binary system in X-ray wavelengths is detected. X-ray spectrum of RR Pic can be represented by a composite model of bremsstrahlung with a photoelectric absorption, two absorption lines centered around 1.1-1.4 keV and 5 Gaussian emission lines centered at around 0.3-1.1 keV . The best t bremsstrahlung temperature derived from the model ranges from 0.99 to 1.60 keV and the unabsorbed X-ray flux is found to be 2.51 (+0.39 -1.21) erg/cm2/s in the 0.3-5.0 keV range.The absorption lines correspond to several transitions of Fe, Ne and Na. The emission lines correspond to various transitions of S, N, O, C, Ne and Fe / and observations with better spectral resolution are needed to determine the exact transitions. The source spectrum is better explained with photoionized plasma model rather than the cooling flow model. It has also been found that the neutral Hydrogen column density differs for orbital minimum and orbital maximum spectra with values 0.25 (+0.23 -0:18)*10^22 atoms/cm2 and 0.64 (+0.13 -0.14)*10^22 atoms/cm2 respectively at 3 sigma confidence level. The difference of neutral Hydrogen column density between the maximum and minimum phase spectra indicates existence of a warm absorbing region on the disc at the location of the impact zone.

This thesis brings statistical analyses techniques to bear on data derived from an extensive database of satellite launches and on-orbit anomalies and failures. The data collected is analyzed from two different perspectives and addresses, in two separate studies, two research objectives. The first study proposes to identify trends and cyclical patterns in the space industry, and to forecast the volume of launches for the next few years. Satellites have been rightfully described as the lifeblood of the entire space industry and the number of satellites ordered or launched per year is an important defining metric of the industry's level of activity. The structure of the space industry, its financial health and its workforce retention and development is dependent on the volume of satellites contracted. As such, trends and variability in this volume have significant strategic impact on the space industry. Over the past 40+ years, hundreds of satellites have been launched every year. Thus, an important data set is available for time series analysis and identification of trends and cycles in the various markets of the space industry. For the purpose of this first study, we collected data for over 6,000 satellites launched since 1960 on a yearly basis. We separated the satellites into three broad segments: 1) defense and intelligence satellites, 2) science satellites, and 3) commercial satellites. Several techniques are available for the analysis of time series data, both in the time domain and in the frequency domain. In this first study, we conducted spectral analysis of the time series for each of the three satellite populations and identified cycles contained in the data. In addition, once harmonic models were derived and fitted to the data, we built forecasting models of satellite launch volumes in the different market segments for the next few years. The potential implications of the results are discussed as a number of strategic matters for the space industry are contingent on the predictions or forecast of the volume of satellites contracted (the example of the U.S. auto industry is a solemn reminder of such possible strategic issues). The second study uses the previously collected launch data, confined to Earth-orbiting satellites launched between 1990 and 2008, and expanded with the failure information and retirement of each satellite to conduct a comparative analysis of satellite reliability in GEO, LEO, and MEO orbits. Reliability has long been recognized as an essential consideration in the design of space systems. However, there is limited statistical analysis of satellite reliability based on actual flight data. The objective of this second study is to conduct nonparametric satellite reliability analysis, with orbit type as a covariate, and to explore appropriate parametric fits (Weibull, lognormal, and mixture distributions). The results indicate for example that differences exist between the failure behaviors of satellites in different orbits, or that satellite infant mortality exists or dominates more clearly in a particular orbit type. The findings can be useful to satellite manufacturers as they would provide an empirical basis for reviewing and adjusting satellite testing and burn-in procedures.

The intra-continental movement of waterborne contaminants is governed by the distribution of solute load in the landscape along with the characteristics and distribution of the hydrological pathways that transport the solutes. An understanding of the processes affecting the transport and fate of the contaminants is crucial for assessments of solute concentrations and their environmental effect on downstream recipients. Elevated concentration of nutrients and the presence of anthropogenic substances, such as pharmaceutical residues, are two examples of the current problems related to hydrological transport. The overall objective of this thesis is to increase the mechanistic understanding of the governing hydrological transport processes and their links to geomorphological and biogeochemical retention and attenuation processes. Specifically, this study aims to quantify the processes governing the transport and fate of waterborne contaminants on the point, stream reach, and watershed scales by evaluating time series obtained from stream tracer tests and water quality monitoring data. The process quantification was achieved by deriving formal expressions for the key transport characteristics, such as the central temporal moments of a unit solute response function and the spectral scaling function for time series of solute responses, which attributes the solute response in the Laplace and Fourier domains to the governing processes and spatial regions within the watershed. The results demonstrate that in addition to the hydrological and biogeochemical processes, the distribution of the load in the landscape and the geomorphological properties in terms of the distribution of transport pathway distances have defined effects on the solute response. Furthermore, the spatial variability between and along the transport pathways significantly affect the solute response. The results indicate that environments with high retention and attenuation intensity, such as stream-reaches with pronounced hyporheic zones, may often dominate the solute flux in the watershed effluent, especially for reactive solutes. The mechanistic-based framework along with the evaluation methodologies presented within this study describes how the results can be generalized in terms of model parameters that reflect the hydrology, geomorphology and biogeochemistry in the studied area. This procedure is demonstrated by the parameterization of a compartment-in-series model for phosphorous transport. / <p>QC 20140826</p>

Wetlands are nominally characterized by, vegetation, presence of saturated soils and/or period and depth of standing water (inundation). Wetland hydroperiod, traditionally defined by the period or duration of inundation, is considered to control the ecological function and resultant plant community. This study seeks to redefine "hydroperiod" to incorporate both surface and subsurface water-level fluctuations, to identify predominant hydroperiod of different wetland types, and to find the range of the water-level fluctuations during the predominant hydroperiod durations. The motivation being that wetland ecological condition is controlled not just by the period of inundation but also by the proximity and depth to water-table and period of water-level fluctuation. To accomplish this, a frequency distribution analysis of water-table and stage levels in wetlands is performed. The conclusions of this study suggest a need to rethink current definitions and methodologies in determining hydroperiod. Redefining wetland hydroperiod taking into consideration depth to water-table, namely water-level periods and depths below ground surface, may also aid in the understanding of how fluctuations in water-levels in a wetland affect plant ecology.

Downhole seismic testing and seismic cone penetration testing (SCPT) have shown little change since the 1990’s, with essentially the same sensors, sources, test procedures and analytical methods being used. In these tests, the time differences of first-arrivals or other reference points early in the time-domain signals have been used to calculate shear and compression wave velocities in soil and rock layers. This time-domain method requires an operator to pick the first arrival or other reference point of each seismic wave in the time record. Picking these reference points correctly is critical in calculating wave velocities. However, picking these points in time records is time consuming and is not always easy because of low signal-to-noise ratios, especially in the case of shear waves which arrive later in the time record. To avoid picking reference points, a cross-correlation method is sometimes applied to determine travel times of the seismic waves, especially in traditional downhole testing. One benefit of the cross-correlation method is that it can be automated. The cross-correlation method is not, however, appropriate for evaluation other body wave characteristics such as wave dispersion and material damping. An alternate approach is to use frequency-domain analysis methods which are well suited for evaluating time changes between all types of waveforms measured at spatially different points. In addition, frequency-domain methods can be automated and attenuation measurements can also be performed. Examples of such testing procedures with Rayleigh-type surface waves in geotechnical earthquake engineering are the Spectral-Analysis-of-Surface-Waves (SASW) and Multi-Channel-Analysis-of-Surface-Waves (MASW) methods. In this research, an automated procedure for calculating body wave velocities that is based on frequency-domain analysis is presented. The basis for and an automated procedure to calculated body wave dispersion is also presented. Example results showing shear wave velocity and material damping measurements in the SCPT are presented. The objective of this study is to improve downhole seismic tests with boreholes, cone penetrometers or flat-plate dilatometers by developing a frequency-domain analysis method which overcomes many of the disadvantages of time-domain analyses. The frequency-domain method is called the Spectral-Analysis-of-Body-Waves (SABW) method. The SABW method does not require an operator to pick the first-arrival or other reference times. As a result, the shear wave velocities and wave dispersion can be calculated in real time using the interpretation method with an automatic calculation procedure, thus reducing human subjectivity. Also, the SABW method can be used to determine additional information from the dispersion curves such as the material damping ratio and an estimate of soil type based on the dispersion relationship. In this research, field SCPT measurements are presented as an example to illustrate the potential of the SABW method. Measurements with shear waves are highlighted because these measurements are most often required in geotechnical earthquake engineering studies. / text

Roughness is an important indicator of pavement riding comfort and safety. It is a condition indicator that should be carefully considered when evaluating primary pavements. At the same time, the use of roughness measurements plays a critical role in the pavement management system.There are many devices used for roughness evaluation. The major tools used for road roughness quantify are the road profilers. In the thesis research, in order to obtain useful pavement surface condition data for pavement evaluation, an inertial based pavement roughness measuring system was developed with the combination of modern sensor technology and computer technology. The research will focus on the development of new method to get the profile in order to improve the repeatability of the inertial based pavement roughness system, the hardware design and the software development which is used for data sampling and data analysis. Finally maximum entropy spectral analysis method was used to evalu ate the road profile spectrum.In order to get evaluate the accuracy and correction of the laser profiler system, different roughness devices (including Dipstick, direct type profiler and the laser profiler developed) were operated in the test sites. The research focused on several performance measures, such as repeatability (before and after new method analysis), impact of operating speed and sample interval, correlativity and etc. IRI from these devices were analyzed to evaluate the correlativity between these devices. Some regression models were developed in this research. Test results show that the new method can improve the repeatability of the profiler system. The laser profiler system has good repeatability and the operating speed and sample interval do not have a significant impact on the inertial based roughness measuring system. With the reliable results, the system is ready to be used in the field application within the speed and sample interval range. Through the spectrum an alysis, it shows that the spectrum has a qualitative relation with pavement roughness conditions.

A new approach (designed to lower computational complexity) to compression of finite binary data, based on the application of “exclusive-or” operation, is presented in the paper. The new concept of an identifying sequence, associated with a particular decomposition scheme, is introduced. A new heuristic algorithm for calculation of the identifying sequences has been developed. Two robust algorithms – for compressing and streaming the sequences (using a priori compiled decomposition tables), and for real time decoding of the compressed streams – were proposed and implemented. The experimental results confirmed that the developed approach gave a data compression effect on an ordinary computer system.