Rapid computation of far-field statistics for random obstacle scattering

In this article, we consider the numerical approximation of far-field statistics for acoustic scattering problems in the case of random obstacles. In particular, we consider the computation of the expected far-field pattern and the expected scattered wave away from the scatterer as well as the computation of the corresponding variances. To that end, we introduce an artificial interface, which almost surely contains all realizations of the random scatterer. At this interface, we directly approximate the second order statistics, i.e., the expectation and the variance, of the Cauchy data by means of boundary integral equations. From these quantities, we are able to rapidly evaluate statistics of the scattered wave everywhere in the exterior domain, including the expectation and the variance of the far-field. By employing a low-rank approximation of the Cauchy data's two-point correlation function, we drastically reduce the cost of the computation of the scattered wave's variance. Numerical results are provided in order to demonstrate the feasibility of the proposed approach

Learning the LMP-Load Coupling From Data: A Support Vector Machine Based Approach

This paper investigates the fundamental coupling between loads and locational marginal prices (LMPs) in security-constrained economic dispatch (SCED). Theoretical analysis based on multi-parametric programming theory points out the unique one-to-one mapping between load and LMP vectors. Such one-to-one mapping is depicted by the concept of system pattern region (SPR) and identifying SPRs is the key to understanding the LMP-load coupling. Built upon the characteristics of SPRs, the SPR identification problem is modeled as a classification problem from a market participant's viewpoint, and a Support Vector Machine based data-driven approach is proposed. It is shown that even without the knowledge of system topology and parameters, the SPRs can be estimated by learning from historical load and price data. Visualization and illustration of the proposed data-driven approach are performed on a 3-bus system as well as the IEEE 118-bus system

The heart of political steering: the EU's areana of power as template for a governance typology

The literature on the so-called new modes of governance in the European Union focuses on steering instruments beyond hierarchy and coercion. While it has repeatedly been put into question how ‘new’ these instruments are, no systematic attention has been paid to the mutual dependency between policy types marked by the specific conflict lines and choice of governance tools. On the contrary, some attempts to classify modes of governance explicitly disregard policy typologies. The paper argues conversely that in order to arrive at a comprehensive mapping of modes of governance – ‘old’ and ‘new’ – the most promising doorway is indeed to start from the actor constellations characteristic for the different policy types. A review of the European Union’s policies and modes of governance illustrates how modes of governance are pre-defined by the structures between policy-makers and –takers innate to the policy types that dominate supranational policy-making

Large-Scale Rendering Using Shadowmaps

Shadow mapovanie je najpoužívanejšia metóda ktorá sa využíva v real-time 3D grafike na tvorbu tieňov v lokálnych osvetlovacích modeloch. Táto práca krok-za-krokom vysvetľuje proces vytvárania shadow máp. Porovnané su metódy výpočtu hĺbkovej odchylky ako aj filtrovacie metódy, a zároveň je odvodený výpočet normálovej odchýlky pre filtrovacie kernely s premennou veľkosťou. Taktiež popíšeme proces ako efektívne obaliť frustum kamery kaskádovým frustumom. Popri tom vysvetlíme ako využiť moderné OpenGL API na zníženie výkonnostných nedostatkov.Shadow mapping is the most widely used method in real-time 3D graphics for producing shadows in local light models. This thesis step-by-step explains the process of creating shadow maps. Depth biasing as well as filtering methods are analysed, then the calculation of normal offset bias for variable sized kernels is derived. We describe the process of efficiently fitting stable cascade frustums to view frustum. Also shown is how to use modern OpenGL to reduce performance overhead.

Real-time Shadows for Gigapixel Displacement Maps

Shadows portray helpful information in scenes. From a scientific visualization standpoint, they help to add data without unnecessary clutter. In video games they add realism and depth. In common graphics pipelines, due to the independent and parallel rendering of geometric primitives, shadows are difficult to achieve. Objects require knowledge of each other and therefore multiple renders are needed to collect the necessary data. The collection of this data comes with its own set of trade offs. Our research involves adding shadows into a lunar rendering framework developed by Dr. Robert Kooima. The NASA-collected data contains a multi-gigapixel displacement map describing the lunar topology. This map does not fit entirely into main memory and therefore out-of-core paging is utilized to achieve real-time speeds. Current shadow techniques do not attempt to generate occluder data on such a scale, and therefore we have developed a novel approach to fit this situation. By using a chain of pre-processing steps, we analyze the structure of the displacement map and calculate horizon lines at each vertex. This information is saved into several images and used to generate shadows in a single pass, maintaining real-time speeds. The algorithm is even capable of generating soft shadows without extra information or loss of speed. We compare our algorithm with common approaches in the field as well as two forms of ground truth; one from ray tracing and the other from the gigapixel lunar texture data, showing real shadows at the time it was collected