Using the Sharp Operator for edge detection and nonlinear diffusion

In this paper we investigate the use of the sharp function known from functional analysis in image processing. The sharp function gives a measure of the variations of a function and can be used as an edge detector. We extend the classical notion of the sharp function for measuring anisotropic behaviour and give a fast anisotropic edge detection variant inspired by the sharp function. We show that these edge detection results are useful to steer isotropic and anisotropic nonlinear diffusion filters for image enhancement

Application of general semi-infinite Programming to Lapidary Cutting Problems

We consider a volume maximization problem arising in gemstone cutting industry. The problem is formulated as a general semi-infinite program (GSIP) and solved using an interiorpoint method developed by Stein. It is shown, that the convexity assumption needed for the convergence of the algorithm can be satisfied by appropriate modelling. Clustering techniques are used to reduce the number of container constraints, which is necessary to make the subproblems practically tractable. An iterative process consisting of GSIP optimization and adaptive refinement steps is then employed to obtain an optimal solution which is also feasible for the original problem. Some numerical results based on realworld data are also presented

Air Force Institute of Technology Research Report 2014

This report summarizes the research activities of the Air Force Institute of Technology’s Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems Engineering and Management, Operational Sciences, Mathematics, Statistics and Engineering Physics

Forecasting Solar Flares Using Magnetogram-based Predictors and Machine Learning

We propose a forecasting approach for solar flares based on data from Solar Cycle 24, taken by the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory (SDO) mission. In particular, we use the Spaceweather HMI Active Region Patches (SHARP) product that facilitates cut-out magnetograms of solar active regions (AR) in the Sun in near-realtime (NRT), taken over a five-year interval (2012 – 2016). Our approach utilizes a set of thirteen predictors, which are not included in the SHARP metadata, extracted from line-of-sight and vector photospheric magnetograms. We exploit several Machine Learning (ML) and Conventional Statistics techniques to predict flares of peak magnitude >M1 and >C1, within a 24 h forecast window. The ML methods used are multi-layer perceptrons (MLP), support vector machines (SVM) and random forests (RF). We conclude that random forests could be the prediction technique of choice for our sample, with the second best method being multi-layer perceptrons, subject to an entropy objective function. A Monte Carlo simulation showed that the best performing method gives accuracy ACC=0.93(0.00), true skill statistic TSS=0.74(0.02) and Heidke skill score HSS=0.49(0.01) for >M1 flare prediction with probability threshold 15% and ACC=0.84(0.00), TSS=0.60(0.01) and HSS=0.59(0.01) for >C1 flare prediction with probability threshold 35%

Air Force Institute of Technology Research Report 1997

This report summarizes the research activities of the Air Force Institute of Technology\u27s Graduate School of Engineering and the Graduate School of Logistics and Acquisition Management. It describes research interests and faculty expertise; list student theses/dissertations; identifies research sponsors and contributions; and outlines the procedure for contacting either school

Aeronautical engineering: A continuing bibliography with indexes (supplement 292)

This bibliography lists 675 reports, articles, and other documents recently introduced into the NASA scientific and technical information system database. Subject coverage includes the following: design, construction and testing of aircraft and aircraft engines; aircraft components, equipment, and systems; ground support systems; and theoretical and applied aspects of aerodynamics and general fluid dynamics

Numerical simulation of the three-dimensional flow at the confluence of the Sava and Danube Rivers

In this paper, the confluence hydrodynamics at the mouth of the Sava and Danube Rivers in the city of Belgrade is analysed by means of the three-dimensional numerical model. The confluence offers excellent possibilities for such investigation as the two morphological features typical for a river confluence are present: bed elevation discordance at the entrance to the confluence and the scour hole in the post-confluence channel. The results are discussed in terms of the secondary flow pattern. Since the non-defomble bed is assumed, the nature of the river bed - flow interaction is analysed in terms of a non-dimensional bed shear stress and a re-suspension number distributions for different flow conditions in the confluence

Solar Power System Plaing & Design

Photovoltaic (PV) and concentrated solar power (CSP) systems for the conversion of solar energy into electricity are technologically robust, scalable, and geographically dispersed, and they possess enormous potential as sustainable energy sources. Systematic planning and design considering various factors and constraints are necessary for the successful deployment of PV and CSP systems. This book on solar power system planning and design includes 14 publications from esteemed research groups worldwide. The research and review papers in this Special Issue fall within the following broad categories: resource assessments, site evaluations, system design, performance assessments, and feasibility studies

Robust computational intelligence techniques for visual information processing

The third part is exclusively dedicated to the super-resolution of Magnetic Resonance Images. In one of these works, an algorithm based on the random shifting technique is developed. Besides, we studied noise removal and resolution enhancement simultaneously. To end, the cost function of deep networks has been modified by different combinations of norms in order to improve their training. Finally, the general conclusions of the research are presented and discussed, as well as the possible future research lines that are able to make use of the results obtained in this Ph.D. thesis.This Ph.D. thesis is about image processing by computational intelligence techniques. Firstly, a general overview of this book is carried out, where the motivation, the hypothesis, the objectives, and the methodology employed are described. The use and analysis of different mathematical norms will be our goal. After that, state of the art focused on the applications of the image processing proposals is presented. In addition, the fundamentals of the image modalities, with particular attention to magnetic resonance, and the learning techniques used in this research, mainly based on neural networks, are summarized. To end up, the mathematical framework on which this work is based on, ₚ-norms, is defined. Three different parts associated with image processing techniques follow. The first non-introductory part of this book collects the developments which are about image segmentation. Two of them are applications for video surveillance tasks and try to model the background of a scenario using a specific camera. The other work is centered on the medical field, where the goal of segmenting diabetic wounds of a very heterogeneous dataset is addressed. The second part is focused on the optimization and implementation of new models for curve and surface fitting in two and three dimensions, respectively. The first work presents a parabola fitting algorithm based on the measurement of the distances of the interior and exterior points to the focus and the directrix. The second work changes to an ellipse shape, and it ensembles the information of multiple fitting methods. Last, the ellipsoid problem is addressed in a similar way to the parabola