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This paper examines the empirical effect of corporate Income tax on GDP growth rate using historical data from 1951-2010 for Sweden. Economic theory postulates that corporate tax rates should significantly negatively affect GPD growth rate. Some past empirical works on cross-country panel data also supports this significantly negative correlation between growth rate and corporate tax. However, empirical works using country specific time-series data show deviations and contradictions to this conventional wisdom. Using time series data, I find that corporate income tax rates have no significant effect on Swedish economic growth.

A digital watermark is a message robustly hidden within another digitized signal such as an image, a piece of music, a video, etc. . The principal applications of this technology are copyright protection and document fingerprinting. The robustness of watermarking algorithms against common geometrical deformations has drawn the attention of many researchers in the last ten years. Such distortions can result from usual processing of the media and/or malicious manipulations. As an example, a major concern for digital cinema industry is the illicit copy of movies with video cameras taking place in movie theaters. In this scenario, severe geometric distortions can jeopardize the retrieval of the watermark message from the illicit copies. The limitations and weaknesses of the previously proposed solutions to fight these distortions are presented. We developed a generalized construction method for periodic pseudo-random patterns. Based on these patterns, we designed a spread spectrum watermarking scheme with enhanced security properties. We investigated the detection probability and the interaction between exhaustive search and informed coding strategies. Finally, a scheme for the detection of a periodic structure and for the inversion of affine distortions was presented. We showed that the choice of the periodic repetition size involves a trade-off between robustness and secrecy. Thereafter, we studied the security flaw caused by the lack of secrecy in pilot-registration approaches. We proposed an innovative hiding scheme to remedy this issue. Our solution involves the extraction of robust local references from the content of the cover signal. Using this content normalized interpretation, we showed how one can design robust secret binary mask and modulate pilot signals in watermarking schemes. The efficiency of the approach is demonstrated on pilots derived from periodic structures. We also addressed the assessment of the degradation introduced by a geometrical distortion. We assume that a global rigid transform does not impair the perceptual value of an image and we propose a new criterion based on a local analysis of the geometrical deformations.

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The expansion of the universe is currently accelerating, as first inferred by Efstathiou et al. (1990), Ostriker & Steinhardt (1995) and directly determined by Riess et al. (1998) and Perlmutter et al. (1999). Current constraints are consistent with a time independent equation-of-state of w = -1, which is to be expected when a constant vacuum energy density dominates. But the Quantum Field Theory prediction for the magnitude of this vacuum energy is very much larger than that inferred (Weinberg, 1989; Koksma & Prokopec, 2011). It is entirely possible that the cause of the expansion has an alternative explanation, with both the inclusion of a quantum scalar field and modified gravity theories able to reproduce an expansion history close to, but potentially deviating from, that of a cosmological constant and cold dark matter. In this work I investigate the consistency of the VIMOS Public Extragalactic Redshift Survey (VIPERS) v7 census of the galaxy distribution at z = 0:8 with the expansion history and linear growth rate predicted by General Relativity (GR) when a Planck Collaboration et al. (2016) fiducial cosmology is assumed. To do so, I measure the optimally weighted redshift-space power spectrum (Feldman et al., 1994), which is anisotropic due to the coherent infall of galaxies towards overdensities and outflow from voids (Kaiser, 1987). The magnitude of this anisotropy can distinguish between modified theories of gravity as the convergence (divergence) rate of the velocity field depends on the effective strength of gravity on cosmological scales (Guzzo et al., 2008). This motivates measuring the linear growth rate rather than the background expansion, which is indistinguishable for a number of modified gravity theories. In Chapter 6 I place constraints of fσ8(0:76) = 0:44 ± 0:04; fσ8(1:05) = 0:28 ± 0:08; with the completed VIPERS v7 survey; the combination remains consistent with General Relativity at 95% confidence. The dependence of the errors on the assumed priors will be investigated in future work. Further anisotropy is introduced by the Alcock-Paczynski effect - a distortion of the observed power spectrum due to the assumption of a fiducial cosmology differing from the true one. These two sources of anisotropy may be separated based on their distinct scale and angular dependence with sufficiently precise measurements. Doing so degrades the constraints: fσ8(0:76) = 0:31 ± 0:10; fσ8(1:05) = -0:04 ± 0:26; but allows for the background expansion (FAP ≡ (1 + z)DAH=c) to be simultaneously constrained. Galaxy redshift surveys may then directly compare both the background expansion and linear growth rate to the GR predictions I find the VIPERS v7 joint-posterior on (fσ8; FAP ) shows no compelling deviation from the GR expectation although the sizeable errors reduce the significance of this conclusion. In Chapter 4 I describe and outline corrections for the VIPERS spectroscopic selection, which enable these constraints to be made. The VIPERS selection strategy is (projected) density dependent and may potentially bias measures of galaxy clustering. Throughout this work I present numerous tests of possible systematic biases, which are performed with the aid of realistic VIPERS mock catalogues. These also allow for accurate statistical error estimates to be made { by incorporating the sample variance due to both the finite volume and finite number density. Chapter 5 details the development and testing of a new, rapid approach for the forward modelling of the power spectrum multipole moments obtained from a survey with an involved angular mask. An investigation of the necessary corrections for the VIPERS PDR-1 angular mask is recorded. This includes an original derivation for the integral constraint correction for a smoothed, joint-field estimate of ¯n(z) and a description of how the mask should be accounted for in light of the Alcock- Paczynski effect. Chapter 7 investigates the inclusion of a simple local overdensity transform: 'clipping' prior to the redshift-space distortions (RSD) analysis. This tackles the root cause of non-linearity and potentially extends the validity of perturbation theory. Moreover, this marked clustering statistic potentially amplifies signatures of modified gravity and, as a density-weighted two-point statistic, includes information not available to the power spectrum. I show that a linear real-space power spectrum with a Kaiser factor and a Lorentzian damping yields a significant bias without clipping, but that this may be removed with a sufficiently strict transform; similar behaviour is observed for the VIPERS v7 dataset. Estimates of fσ8 for different thresholds are highly correlated due to the overlapping volume, but the bias for insufficient clipping can be calibrated and the correlation obtained using mock catalogues. A maximum likelihood value for the combined constraint of a number of thresholds is shown to achieve a ' 16% decrease in statistical error relative to the most precise single-threshold estimate. The results are encouraging to date but represent a work in progress; the final analysis will be submitted to Astronomy & Astrophysics as Wilson et al. (2016). In addition to this, an original extension of the prediction for a clipped Gaussian field to a clipped lognormal field is presented. The results of tests of this model with a real-space cube populated according to the halo occupation distribution model are also provided.

abstract: Information forensics and security have come a long way in just a few years thanks to the recent advances in biometric recognition. The main challenge remains a proper design of a biometric modality that can be resilient to unconstrained conditions, such as quality distortions. This work presents a solution to face and ear recognition under unconstrained visual variations, with a main focus on recognition in the presence of blur, occlusion and additive noise distortions. First, the dissertation addresses the problem of scene variations in the presence of blur, occlusion and additive noise distortions resulting from capture, processing and transmission. Despite their excellent performance, ’deep’ methods are susceptible to visual distortions, which significantly reduce their performance. Sparse representations, on the other hand, have shown huge potential capabilities in handling problems, such as occlusion and corruption. In this work, an augmented SRC (ASRC) framework is presented to improve the performance of the Spare Representation Classifier (SRC) in the presence of blur, additive noise and block occlusion, while preserving its robustness to scene dependent variations. Different feature types are considered in the performance evaluation including image raw pixels, HoG and deep learning VGG-Face. The proposed ASRC framework is shown to outperform the conventional SRC in terms of recognition accuracy, in addition to other existing sparse-based methods and blur invariant methods at medium to high levels of distortion, when particularly used with discriminative features. In order to assess the quality of features in improving both the sparsity of the representation and the classification accuracy, a feature sparse coding and classification index (FSCCI) is proposed and used for feature ranking and selection within both the SRC and ASRC frameworks. The second part of the dissertation presents a method for unconstrained ear recognition using deep learning features. The unconstrained ear recognition is performed using transfer learning with deep neural networks (DNNs) as a feature extractor followed by a shallow classifier. Data augmentation is used to improve the recognition performance by augmenting the training dataset with image transformations. The recognition performance of the feature extraction models is compared with an ensemble of fine-tuned networks. The results show that, in the case where long training time is not desirable or a large amount of data is not available, the features from pre-trained DNNs can be used with a shallow classifier to give a comparable recognition accuracy to the fine-tuned networks. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2018

Scholars have connected cognitive distortions to adolescents’ externalizing behaviors. Other scholars have offered that higher levels of cognitive autonomy, which develops during adolescence, may be a protective factor for problem behaviors in adolescence. To date, no studies have explored how these two cognitive processes function and potentially interact to predict adolescent problem behaviors. This study’s purpose was to see if cognitive autonomy affected the relationship between cognitive distortions and externalizing behaviors in a clinical population of adolescents. Past research has suggested that cognitive distortions are greater and more prevalent in clinical populations. Because of this, the processes of cognitive autonomy could be affected by cognitive distortions (that can form prior to adolescence), and worsen the relationship between cognitive distortions and externalizing behaviors. This study analyzed 146 adolescents, from a residential treatment facility. Hierarchical multiple regression analyses were used to examine if links between cognitive distortions, cognitive autonomy, and externalizing behaviors existed, and to determine if elements of cognitive autonomy affected the relationship between cognitive distortions and externalizing behaviors. As expected, analyses showed that cognitive distortions and externalizing behaviors were related. Additionally, results indicated that aspects of cognitive autonomy were protective of externalizing behaviors. Results did not reveal that cognitive autonomy affected the relationship between cognitive distortions and externalizing behaviors. Discussion highlights potential reasons and alternative explanations for the results that were inconsistent with expectations. Limitations and future directions also are discussed.

This thesis focuses on the interplay of the spin-orbit coupling, the electronic correlations and the bandwidth energy scales, along with the lattice distortions seen in perovskite iridates. In particular, we study the magnetic phases in these materials and the insulator to metal transition that occurs as the dimensionality of the system is changed. Motivated by the novel magnetic phases seen in the Sr2IrO4 system, we study the band structures of three materials in the Sr(n+1)Ir(n)O(3n+1) Ruddlesden-Popper series by use of a tight-binding model. From the effect of spin-orbit coupling, we see that the relevant bands near the Fermi energy are indeed made of effective J=1/2 states. This spin-orbit separation of the bands creates effectively smaller bandwidth which can then be split via magnetic ordering driven by electronic correlations. By the use of a self-consistent mean-field theory, we derive the ordering for each of the three materials studied and show that the nature of the magnetic ordering is highly dependent on the lattice structure. The ordering in the bilayer Sr3Ir2O7, which has been a topic of debate in recent experimental studies, is understood within the current approach to be a collinear antiferromagnetic order, in agreement with the latest results. Given that the iridate systems have large spin-orbit coupling, and that the topic of topological insulators has become a very popular subject of research, we discuss the proximity of the perovskite iridates to topological insulators. Since the SrIrO3 material displays a semimetal structure with nodal dispersion near the Fermi level, we looked at an extra term in the Hamiltonian that could lift the nodal lines and turn the system into an insulator. Further studies of the parity eigenvalues of the bands at each time reversal invariant momentum point confirms that for a range of this extra term, a topological phase can be achieved. A discussion on material realization of such a phase is also given where we suggest that a Sr2IrRhO6 superstructure might be a good candidate to achieve this state.

This thesis focuses on the interplay of the spin-orbit coupling, the electronic correlations and the bandwidth energy scales, along with the lattice distortions seen in perovskite iridates. In particular, we study the magnetic phases in these materials and the insulator to metal transition that occurs as the dimensionality of the system is changed. Motivated by the novel magnetic phases seen in the Sr2IrO4 system, we study the band structures of three materials in the Sr(n+1)Ir(n)O(3n+1) Ruddlesden-Popper series by use of a tight-binding model. From the effect of spin-orbit coupling, we see that the relevant bands near the Fermi energy are indeed made of effective J=1/2 states. This spin-orbit separation of the bands creates effectively smaller bandwidth which can then be split via magnetic ordering driven by electronic correlations. By the use of a self-consistent mean-field theory, we derive the ordering for each of the three materials studied and show that the nature of the magnetic ordering is highly dependent on the lattice structure. The ordering in the bilayer Sr3Ir2O7, which has been a topic of debate in recent experimental studies, is understood within the current approach to be a collinear antiferromagnetic order, in agreement with the latest results. Given that the iridate systems have large spin-orbit coupling, and that the topic of topological insulators has become a very popular subject of research, we discuss the proximity of the perovskite iridates to topological insulators. Since the SrIrO3 material displays a semimetal structure with nodal dispersion near the Fermi level, we looked at an extra term in the Hamiltonian that could lift the nodal lines and turn the system into an insulator. Further studies of the parity eigenvalues of the bands at each time reversal invariant momentum point confirms that for a range of this extra term, a topological phase can be achieved. A discussion on material realization of such a phase is also given where we suggest that a Sr2IrRhO6 superstructure might be a good candidate to achieve this state.