Investigating Machine Learning Techniques for Gesture Recognition with Low-Cost Capacitive Sensing Arrays

Machine learning has proven to be an effective tool for forming models to make predictions based on sample data. Supervised learning, a subset of machine learning, can be used to map input data to output labels based on pre-existing paired data. Datasets for machine learning can be created from many different sources and vary in complexity, with popular datasets including the MNIST handwritten dataset and CIFAR10 image dataset. The focus of this thesis is to test and validate multiple machine learning models for accurately classifying gestures performed on a low-cost capacitive sensing array. Multiple neural networks are trained using gesture datasets obtained from the capacitance board. In this paper, I train and compare different machine learning models on recognizing gesture datasets. Learning hyperparameters are also adjusted for results. Two datasets are used for the training: one containing simple gestures and another containing more complicated gestures. Accuracy and loss for the models are calculated and compared to determine which models excel at recognizing performed gestures

Theory of interstellar medium diagnostics

The theoretical interpretation of observed interplanetary resonance luminescence patterns is used as one of the must promising methods to determine the state of the local interstellar medium (LISM). However, these methods lead to discrepant results that would be hard to understand in the framework of any physical LISM scenario. Assuming that the observational data are reliable, two possibilities which could help to resolve these discrepancies are discussed: (1) the current modeling of resonance luminescence patterns is unsatisfactory and has to be improved, and (2) the extrapolated interstellar parameters are not indicative of the unperturbed LISM state, but rather designate an intermediate state attained in the outer regions of the solar system. It is shown that a quantitative treatment of the neutral gas-plasma interaction effects in the interface between the heliospheric and the interstellar plasmas is of major importance for the correct understanding of the whole complex

Stationary field-aligned MHD flows at astropauses and in astrotails. Principles of a counterflow configuration between a stellar wind and its interstellar medium wind

A stellar wind passing through the reverse shock is deflected into the astrospheric tail and leaves the stellar system either as a sub-Alfvenic or as a super-Alfvenic tail flow. An example is our own heliosphere and its heliotail. We present an analytical method of calculating stationary, incompressible, and field-aligned plasma flows in the astrotail of a star. We present a recipe for constructing an astrosphere with the help of only a few parameters, like the inner Alfven Mach number and the outer Alfven Mach number, the magnetic field strength within and outside the stellar wind cavity, and the distribution of singular points of the magnetic field within these flows. Within the framework of a one-fluid approximation, it is possible to obtain solutions of the MHD equations for stationary flows from corresponding static MHD equilibria, by using noncanonical mappings of the canonical variables. The canonical variables are the Euler potentials of the magnetic field of magnetohydrostatic equilibria. Thus we start from static equilibria determined by the distribution of magnetic neutral points, and assume that the Alfven Mach number for the corresponding stationary equilibria is finite. The topological structure determines the geometrical structure of the interstellar gas - stellar wind interface. Additional boundary conditions like the outer magnetic field and the jump of the magnetic field across the astropause allow determination of the noncanonical transformations. This delivers the strength of the magnetic field at every point in the astrotail region beyond the reverse shock. The mathematical technique for describing such a scenario is applied to astrospheres in general, but is also relevant for the heliosphere. It shows the restrictions of the outer and the inner magnetic field strength in comparison with the corresponding Alfven Mach numbers in the case of subalfvenic flows.Comment: 19 pages, 17 figures, accepted for publication in A&

Television program avoidance and personality

Recent communication research indicates that approach and avoidance constitute two separate yet co-existing processes during media exposure. While many studies address TV approach behavior, little is known about TV avoidance behavior. Furthermore, personality has yet to be linked to avoidance behavior. This study analyzes the influence of personality on TV program avoidance. Data show that the "Big Five" personality characteristics (Neuroticism, Extraversion, Openness, Conscientiousness, Agreeableness) and Risk and Fight Willingness influence program avoidance, albeit to varying degrees. While the specific correlations are discussed in the paper, the results generally reveal that the combination of personality and avoidance has added value in terms of understanding of TV using behavior compared to the frequently analyzed link between personality and approach. For nearly all personality characteristics, data show that the avoidance perspective is more than the inversion of the approach perspective. The findings are discussed with reference to gratification and selectivity research

When does lumpy factor adjustment matter for aggregate dynamics?

We analyze the dynamic e¤ects of lumpy factor adjustments at the firm level onto the aggregate economy. We find that distinguishing between capital and labour as lumpy factors within the production function result in very dfferent dynamics for aggregate output, investment and labour in an otherwise standard real business cycle model. Lumpy capital leaves the RBC mainly unchanged, while lumpy labour allows for persistence and an inner propagation within the model in form of hump-shaped impulse repsonses. In addition, when modeling lumpy adjustments on both investment and labour, the aggregate effects are even stronger. We investigate the mechanisms underlying these results and identify the elasticity of factor supply as the most important element in accounting for these differences. JEL Classification: E32, E22, E24business cycles, Elasticity of, Lumpy investment, Lumpy labor adjustment

Hospitals, Managed Care, and the Charity Caseload in California

Many observers have blamed HMOs for increasing financial pressures on private hospitals and causing them to cut back on the provision of charity care. We examine this issue using data on all hospital discharges in California between 1988 and 1996. We find that public hospitals in counties with higher HMO penetration do take on a larger share of the county's charity caseload. However, these public hospitals also take on larger shares of most other types of patients. At the hospital level, we find little evidence that either for-profit or non-profit private hospitals respond to HMO penetration by turning away uninsured and Medicaid patients. On the contrary, in the for-profit sector higher HMO penetration is linked to reductions in the share of privately insured patients in the caseload, and corresponding increases in the share of Medicare patients and Medicaid births. Since HMO penetration reduces the price paid by privately insured patients they may be less attractive to for-profit hospitals relative to the publicly insured.

Individual Determinants of Work Attendance: Evidence on the Role of Personality

We investigate the influence of personality as measured by the Big Five personality scale on absenteeism using representative data for Germany. In particular, the 2005 wave of the German Socio-Economic Panel provides detailed information on socio-economic background characteristics along with a Big Five personality scale. Estimates of a Logit model and of count data regression are used to analyze an empirical model based on the theory of hedonic labour market outcomes. These estimates allow us to test hypotheses on the influence of the Big Five personality traits on work attendance. We find clear negative correlations between the probability to be absent and Conscientiousness as well as Agreeableness. We find a strong positive impact of Neuroticism on work attendance decisions in general and clues for a positive impact of Extraversion among men. When looking at the length of absence occurrences the personality dimensions of Neuroticism and Agreeableness are found to significantly influence male absenteeism. Implications of our results are discussed.absenteeism, Five Factor Model, personality, count data model