Detection and classification of non-stationary signals using sparse representations in adaptive dictionaries

Automatic classification of non-stationary radio frequency (RF) signals is of particular interest in persistent surveillance and remote sensing applications. Such signals are often acquired in noisy, cluttered environments, and may be characterized by complex or unknown analytical models, making feature extraction and classification difficult. This thesis proposes an adaptive classification approach for poorly characterized targets and backgrounds based on sparse representations in non-analytical dictionaries learned from data. Conventional analytical orthogonal dictionaries, e.g., Short Time Fourier and Wavelet Transforms, can be suboptimal for classification of non-stationary signals, as they provide a rigid tiling of the time-frequency space, and are not specifically designed for a particular signal class. They generally do not lead to sparse decompositions (i.e., with very few non-zero coefficients), and use in classification requires separate feature selection algorithms. Pursuit-type decompositions in analytical overcomplete (non-orthogonal) dictionaries yield sparse representations, by design, and work well for signals that are similar to the dictionary elements. The pursuit search, however, has a high computational cost, and the method can perform poorly in the presence of realistic noise and clutter. One such overcomplete analytical dictionary method is also analyzed in this thesis for comparative purposes. The main thrust of the thesis is learning discriminative RF dictionaries directly from data, without relying on analytical constraints or additional knowledge about the signal characteristics. A pursuit search is used over the learned dictionaries to generate sparse classification features in order to identify time windows that contain a target pulse. Two state-of-the-art dictionary learning methods are compared, the K-SVD algorithm and Hebbian learning, in terms of their classification performance as a function of dictionary training parameters. Additionally, a novel hybrid dictionary algorithm is introduced, demonstrating better performance and higher robustness to noise. The issue of dictionary dimensionality is explored and this thesis demonstrates that undercomplete learned dictionaries are suitable for non-stationary RF classification. Results on simulated data sets with varying background clutter and noise levels are presented. Lastly, unsupervised classification with undercomplete learned dictionaries is also demonstrated in satellite imagery analysis

Performance of alumina-supported Pt catalysts in an electron-beam-sustained CO2 laser amplifier

The performance of an alumina-supported Pt catalyst system used to maintain the gas purity in an electron-beam-sustained (636) isotope CO2 laser amplifier has been tested. The system characteristics using the two-zone, parallel flow reactor were determined for both continuous- and end-of-day reactor operation using on-line mass spectrometric sampling. The laser amplifier was run with an energy loading of typically 110 J-l/atm and an electron-beam current of 4 mA/sq cm. With these conditions and a pulse repetition frequency of 10 Hz for up to 10,000 shots, increases on the order of 100 ppm O2 were observed with the purifier on and 150 ppm with it off. The 1/e time recovery time was found to be approximately 75 minutes

Neuroendocrinology and resistance training in adult males

An understanding of the neuroendocrine system will assist the Strength and Conditioning coach in the design of progressive strength training programmes by allowing them to manipulate acute training variables according to hormone release profiles. For muscle hypertrophy, training programmes should utilise 3 sets of 10 repetitions at 10RM loads, with short rest periods of no longer than 1 minute. This will ensure the accumulation and maintenance of lactate and hydrogen ions, to which anabolic hormone release is correlated. For strength adaptations without concomitant muscle hypertrophy, the training load and the length of rest periods should be increased, (>85% 1RM and >2mins respectively), and body parts should be rotated (e.g. upper body to lower body or agonist to antagonist). Finally, catabolic hormones and neurohormones significantly affect training adaptations. Therefore the strength and conditioning coach should be cognisant of the specific exercise programming and psychological interventions that manipulate their release

The rings of n-dimensional polytopes

Points of an orbit of a finite Coxeter group G, generated by n reflections starting from a single seed point, are considered as vertices of a polytope (G-polytope) centered at the origin of a real n-dimensional Euclidean space. A general efficient method is recalled for the geometric description of G- polytopes, their faces of all dimensions and their adjacencies. Products and symmetrized powers of G-polytopes are introduced and their decomposition into the sums of G-polytopes is described. Several invariants of G-polytopes are found, namely the analogs of Dynkin indices of degrees 2 and 4, anomaly numbers and congruence classes of the polytopes. The definitions apply to crystallographic and non-crystallographic Coxeter groups. Examples and applications are shown.Comment: 24 page

Six types of E−E-functions of the Lie groups O(5) and G(2)

New families of $E$-functions are described in the context of the compact simple Lie groups O(5) and G(2). These functions of two real variables generalize the common exponential functions and for each group, only one family is currently found in the literature. All the families are fully characterized, their most important properties are described, namely their continuous and discrete orthogonalities and decompositions of their products.Comment: 25 pages, 13 figure

The relationship between isometric mid-thigh pull force-time characteristics and swing performance in high-level youth golfers

The production of vertical ground reaction force has been suggested to relate directly to club head speed (CHS) in golfers, providing a rationale for the implementation of strength and conditioning to enhance performance. The aim of the study was to determine the relationship between isometric mid-thigh pull (IMTP) force-time characteristics and measures of swing performance (CHS and Carry) in high-level youth golfers. Thirteen high-level youth golfers selected for their National Squad performed IMTP and swing testing using a TrackMan launch monitor across two testing sessions. Results revealed significant correlations between IMTP Peak Force (PF) and 6-iron Carry (r=0.91, p<0.001), Driver Carry (r=0.91, p<0.001), 6-iron CHS (r=0.89, p<0.001) and Driver CHS (r=0.88, p<0.001). All other variables showed trivial to large non-significant correlations. Findings support the use of the IMTP as a testing tool in high-level youth golfers and emphasise the importance of strength training within this population

Associations between indoor temperature, self-rated health and socioeconomic position in a cross-sectional study of adults in England

Objective: Excess winter deaths are a major public health concern in England and Wales, with an average of 20 000 deaths per year since 2010. Feeling cold at home during winter is associated with reporting poor general health; cold and damp homes have greater prevalence in lower socioeconomic groups. Overheating in the summer also has adverse health consequences. This study evaluates the association between indoor temperature and general health and the extent to which this is affected by socioeconomic and household factors. / Design: Cross-sectional study. / Setting: England. / Participants: Secondary data of 74 736 individuals living in England that took part in the Health Survey for England (HSE) between 2003 and 2014. The HSE is an annual household survey which uses multilevel stratification to select a new, nationally representative sample each year. The study sample comprised adults who had a nurse visit; the analytical sample was adults who had observations for indoor temperature and self-rated health. / Results: Using both logistic and linear regression models to examine indoor temperature and health status, adjusting for socioeconomic and housing factors, the study found an association between poor health and higher indoor temperatures. Each one degree increase in indoor temperature was associated with a 1.4% (95% CI 0.5% to 2.3%) increase in the odds of poor health. After adjusting for income, education, employment type, household size and home ownership, the OR of poor health for each degree temperature rise increased by 19%, to a 1.7% (95% CI 0.7% to 2.6%) increase in odds of poor health with each degree temperature rise. / Conclusion: People with worse self-reported health had higher indoor temperatures after adjusting for household factors. People with worse health may have chosen to maintain warmer environments or been advised to. However, other latent factors, such as housing type and energy performance could have an effect

Associations between indoor temperature, self-rated health and socioeconomic position in a cross-sectional study of adults in England

Objective: Excess winter deaths are a major public health concern in England and Wales, with an average of 20 000 deaths per year since 2010. Feeling cold at home during winter is associated with reporting poor general health; cold and damp homes have greater prevalence in lower socioeconomic groups. Overheating in the summer also has adverse health consequences. This study evaluates the association between indoor temperature and general health and the extent to which this is affected by socioeconomic and household factors. / Design: Cross-sectional study. / Setting: England. / Participants: Secondary data of 74 736 individuals living in England that took part in the Health Survey for England (HSE) between 2003 and 2014. The HSE is an annual household survey which uses multilevel stratification to select a new, nationally representative sample each year. The study sample comprised adults who had a nurse visit; the analytical sample was adults who had observations for indoor temperature and self-rated health. / Results: Using both logistic and linear regression models to examine indoor temperature and health status, adjusting for socioeconomic and housing factors, the study found an association between poor health and higher indoor temperatures. Each one degree increase in indoor temperature was associated with a 1.4% (95% CI 0.5% to 2.3%) increase in the odds of poor health. After adjusting for income, education, employment type, household size and home ownership, the OR of poor health for each degree temperature rise increased by 19%, to a 1.7% (95% CI 0.7% to 2.6%) increase in odds of poor health with each degree temperature rise. / Conclusion: People with worse self-reported health had higher indoor temperatures after adjusting for household factors. People with worse health may have chosen to maintain warmer environments or been advised to. However, other latent factors, such as housing type and energy performance could have an effect