Ethics, Privacy and Data Collection: A Complex Intersection

The technology around us enables incredible abilities such as high-resolution video calls and the ability to stay connected with everyone we care about through social media. This technology also comes with a hidden cost in the form of data collection. This work explores what privacy means and how users understand what data social media companies collect and monetize. This thesis also proposes a more ethical business model that addresses privacy concerns from an individual perspective

The Technicolor Higgs in the Light of LHC Data

We consider scenarios in which the 125 GeV resonance observed at the Large Hadron Collider is a Technicolor (TC) isosinglet scalar, the TC Higgs. By comparison with quantum chromodynamics, we argue that the couplings of the TC Higgs to the massive weak bosons are very close to the Standard Model (SM) values. The couplings to photons and gluons are model-dependent, but close to the SM values in several TC theories. The couplings of the TC Higgs to SM fermions are due to interactions beyond TC, such as Extended Technicolor: if such interactions successfully generate mass for the SM fermions, we argue that the couplings of the latter to the TC Higgs are also SM-like. We suggest a generic parameterization of the TC Higgs interactions with SM particles that accommodates a large class of TC models, and we perform a fit of these parameters to the Higgs LHC data. The fit reveals regions of parameter space where the form factors are of order unity and consistent with data at the 95% CL, in agreement with expectations in TC theories. This indicates that the discovered Higgs boson is consistent with the TC Higgs hypothesis for several TC theories.Comment: 26 pages, 8 figure

Prediction of progression in idiopathic pulmonary fibrosis using CT scans atbaseline: A quantum particle swarm optimization - Random forest approach

Idiopathic pulmonary fibrosis (IPF) is a fatal lung disease characterized by an unpredictable progressive declinein lung function. Natural history of IPF is unknown and the prediction of disease progression at the time ofdiagnosis is notoriously difficult. High resolution computed tomography (HRCT) has been used for the diagnosisof IPF, but not generally for monitoring purpose. The objective of this work is to develop a novel predictivemodel for the radiological progression pattern at voxel-wise level using only baseline HRCT scans. Mainly, thereare two challenges: (a) obtaining a data set of features for region of interest (ROI) on baseline HRCT scans andtheir follow-up status; and (b) simultaneously selecting important features from high-dimensional space, andoptimizing the prediction performance. We resolved the first challenge by implementing a study design andhaving an expert radiologist contour ROIs at baseline scans, depending on its progression status in follow-upvisits. For the second challenge, we integrated the feature selection with prediction by developing an algorithmusing a wrapper method that combines quantum particle swarm optimization to select a small number of featureswith random forest to classify early patterns of progression. We applied our proposed algorithm to analyzeanonymized HRCT images from 50 IPF subjects from a multi-center clinical trial. We showed that it yields aparsimonious model with 81.8% sensitivity, 82.2% specificity and an overall accuracy rate of 82.1% at the ROIlevel. These results are superior to other popular feature selections and classification methods, in that ourmethod produces higher accuracy in prediction of progression and more balanced sensitivity and specificity witha smaller number of selected features. Our work is the first approach to show that it is possible to use onlybaseline HRCT scans to predict progressive ROIs at 6 months to 1year follow-ups using artificial intelligence

Global-scale wreath-building dynamos in stellar convection zones

When stars like our Sun are young they rotate rapidly and are very magnetically active. We explore dynamo action in rapidly rotating suns with the 3-D MHD anelastic spherical harmonic (ASH) code. The magnetic fields built in these dynamos are organized on global-scales into wreath-like structures that span the convection zone. Wreath-building dynamos can undergo quasi-cyclic reversals of polarity and such behavior is common in the parameter space we have been able to explore. These dynamos do not appear to require tachoclines to achieve their spatial or temporal organization. Wreath-building dynamos are present to some degree at all rotation rates, but are most evident in the more rapidly rotating simulations.Comment: 8 pages, 4 figures. To appear in IAU 271: "Astrophysical Dynamics: from Stars to Galaxies

Discriminative learning of local image descriptors

In this paper, we explore methods for learning local image descriptors from training data. We describe a set of building blocks for constructing descriptors which can be combined together and jointly optimized so as to minimize the error of a nearest-neighbor classifier. We consider both linear and nonlinear transforms with dimensionality reduction, and make use of discriminant learning techniques such as Linear Discriminant Analysis (LDA) and Powell minimization to solve for the parameters. Using these techniques, we obtain descriptors that exceed state-of-the-art performance with low dimensionality. In addition to new experiments and recommendations for descriptor learning, we are also making available a new and realistic ground truth data set based on multiview stereo data

BSM Physics: What the Higgs Can Tell Us

This discovery of the Higgs boson last year has created new possibilities for testing candidate theories for explaining physics beyond the Standard Model. Here we explain the ways in which new physics can leave its marks in the experimental Higgs data, and how we can use the data to constrain and compare different models. In this proceedings paper we use two models, Minimal Universal Extra Dimensions and the 4D Composite Higgs model, as examples to demonstrate the technique.Comment: V2 corrected typo in author name. Submitted to the proceedings of the 41st ITEP Winter School, Mosco