Dynamics of Tectonic Plates

We suggest a model that describes a mutual dynamic of tectonic plates. The dynamic is a sort of stick-slip one which is modeled by a Markov random process. The process defines a microlevel of the dynamic. A macrolevel is obtained by a scaling limit which leads to a system of integro-differential equations which determines a kind of mean field systems. Conditions when Gutenberg-Richter empirical law are presented on the mean field level. These conditions are rather universal and do not depend on features of resistant forces.Comment: 3 figure

Approximation of quantum control correction scheme using deep neural networks

We study the functional relationship between quantum control pulses in the idealized case and the pulses in the presence of an unwanted drift. We show that a class of artificial neural networks called LSTM is able to model this functional relationship with high efficiency, and hence the correction scheme required to counterbalance the effect of the drift. Our solution allows studying the mapping from quantum control pulses to system dynamics and then analysing the robustness of the latter against local variations in the control profile.Comment: 6 pages, 3 figures, Python code available upon request. arXiv admin note: text overlap with arXiv:1803.0516

A Time Series Analysis: Exploring the Link between Human Activity and Blood Glucose Fluctuation

In this thesis, time series models are developed to explore the correlates of blood glucose (BG) fluctuation of diabetic patients. In particular, it is investigated whether certain human activities and lifestyle events (e.g. food and medication consumption, physical activity, travel and social interaction) influence BG, and if so, how. A unique dataset is utilized consisting of 40 diabetic patients who participated in a 3-day study involving continuous monitoring of blood glucose (BG) at five minute intervals, combined with measures for sugar; carbohydrate; calorie and insulin intake; physical activity; distance from home; time spent traveling via public transit and private automobile; and time spent with other people, dining and shopping. Using a dynamic regression model fitted with autoregressive integrated moving average (ARIMA) components, the influence of independent predictive variables on BG levels is quantified, while at the same time the impact of unknown factors is defined by an error term. Models were developed for individuals with overall findings demonstrating the potential for continuous monitoring of diabetic (DM) patients who are trying to control their BG. Model results produced significant BG predicting variables that include food consumption, exogenous insulin administration and physical activity

Investigation of Techniques for Inventorying Forested Regions. Volume 1: Reflectance Modeling and Empirical Multispectral Analysis of Forest Canopy Components

The author has identified the following significant results. Effects of vegetation density on overall canopy reflectance differed dramatically, depending on spectral band, base material, and vegetation type. For example, reflectance changes caused by variations in vegetation density were hardly apparant for a simulated burned surface in LANDSAT band 5, while large changes occurred in band 7. When increasing densities of tree overstory were placed over understories, intermediate to dense overstories effectively masked the understories and dominated the spectral signatures. Dramatic changes in reflectance occurred for canopies placed on a number of varying topographic positions. Such changes were seen to result in the spectral overlap of some nonforested with densely forested situations