Probabilistic facial feature extraction using joint distribution of location and texture information

In this work, we propose a method which can extract critical points on a face using both location and texture information. This new approach can automatically learn feature information from training data. It finds the best facial feature locations by maximizing the joint distribution of location and texture parameters. We first introduce an independence assumption. Then, we improve upon this model by assuming dependence of location parameters but independence of texture parameters.We model combined location parameters with a multivariate Gaussian for computational reasons. The texture parameters are modeled with a Gaussian mixture model. It is shown that the new method outperforms active appearance models for the same experimental setup

Faces as a "Model Category" for Visual Object Recognition

Visual recognition is an important ability that is central to many everyday tasks such as reading, navigation and social interaction, and is therefore actively studied in neuroscience, cognitive psychology and artificial intelligence. There exist thousands of object categories, all of which pose similar challenges to biological and artificial visual systems: accurate recognition under varying location, scale, view angle, illumination and clutter. In many areas of science, important discoveries have been made using "model organisms" such as fruit flies, mice and macaques. For the thousands of object categories, the important and well-studied category of faces could potentially serve as a "model category" upon which efforts are focused, and from which fundamental insights are drawn. However, it has been hotly debated whether faces are processed by the brain in a manner fundamentally different from other categories. Here we show that "neural tuning size" -- a single parameter in a computational model of object processing -- is able to account for important face-specific phenomena. Thus, surprisingly, "face-like" processing is explainable by physiological mechanisms that differ only quantitatively from "object-like" processing. Our computational proof-of-principle provides specific neural tuning properties that correspond to the so-far qualitative and controversial notion of "holistic" face processing. Overall, faces may be a viable model category. Since faces are highly amenable to complementary experimental techniques like functional MRI, electrophysiology, electroencephalography and transcranial magnetic stimulation, this further raises the odds that the algorithms and neural circuits underlying visual recognition may first be solved for faces. With faces serving as a model category, the great scientific challenge of understanding and reverse-engineering general visual recognition can be greatly accelerated

Intake ground vortex characteristics

The development of ground vortices when an intake operates in close proximity to the ground has been studied computationally for several configurations including front and rear quarter approaching flows as well as tailwind arrangements. The investigations have been conducted at model scale using a generic intake geometry. Reynolds Averaged Navier–Stokes calculations have been used and an initial validation of the computational model has been carried out against experimental data. The computational method has subsequently been applied to configurations that are difficult to test experimentally by including tailwind and rear quarter flows. The results, along with those from a previous compatible study of headwind and pure cross-wind configurations, have been used to assess the ground vortex behaviour under a broad range of velocity ratios and approaching wind angles. The characteristics provide insights on the influence of the size and strength of ground vortices on the overall quality of the flow ingested by the intake

Prediction of transient head on seepage path using Boundary Fitted Coordinate (BFC) system

One of the main causes of levee failure is seepage through levee. This seepage can cause weakening in the levee structure, which in turn can cause sudden levee failure or overtopping of the levee due to levee depression. The purpose of this study is to determine the transient head on the seepage path due to changing water level during flood period. Transient seepage problems are very important as critical condition can occur during this time rather than during steady state condition. Seepage path through a levee can be predicted using the Boundary Fitted Coordinate (BFC) system method. The physical coordinate system is transformed into computational curvilinear coordinate system by using this method. One advantage of using this method is the grid generated can fit itself into the boundary of the system. The model developed is tested on a steady state rectangular dam for verification by comparing it with the analytical solutions. The model is then implemented on an unsteady state problem to determine the location of free surface and seepage face for several time steps until steady state is reached

A Library for Wall-Modelled Large-Eddy Simulation Based on OpenFOAM Technology

This work presents a feature-rich open-source library for wall-modelled large-eddy simulation (WMLES), which is a turbulence modelling approach that reduces the computational cost of traditional (wall-resolved) LES by introducing special treatment of the inner region of turbulent boundary layers (TBLs). The library is based on OpenFOAM and enhances the general-purpose LES solvers provided by this software with state-of-the-art wall modelling capability. In particular, the included wall models belong to the class of wall-stress models that account for the under-resolved turbulent structures by predicting and enforcing the correct local value of the wall shear stress. A review of this approach is given, followed by a detailed description of the library, discussing its functionality and extensible design. The included wall-stress models are presented, based on both algebraic and ordinary differential equations. To demonstrate the capabilities of the library, it was used for WMLES of turbulent channel flow and the flow over a backward-facing step (BFS). For each flow, a systematic simulation campaign was performed, in order to find a combination of numerical schemes, grid resolution and wall model type that would yield a good predictive accuracy for both the mean velocity field in the outer layer of the TBLs and the mean wall shear stress. The best result was achieved using a mildly dissipative second-order accurate scheme for the convective fluxes applied on an isotropic grid with 27000 cells per $\delta^3$-cube, where $\delta$ is the thickness of the TBL or the half-height of the channel. An algebraic model based on Spalding's law of the wall was found to perform well for both flows. On the other hand, the tested more complicated models, which incorporate the pressure gradient in the wall shear stress prediction, led to less accurate results

Linear and non-linear dynamic analyses of sandwich panels with face sheet-tocore debonding

А survey of recent developments in the dynamic analysis of sandwich panels with face sheet-to-core debonding is presented. The finite element method within the ABAQUSTM code is utilized. The emphasis is directed to the procedures used to elaborate linear and non-linear models and to predict dynamic response of the sandwich panels. Recently developed models are presented, which can be applied for structural health monitoring algorithms of real-scale sandwich panels. First, various popular theories of intact sandwich panels are briefly mentioned and a model is proposed to effectively analyse the modal dynamics of debonded and damaged (due to impact) sandwich panels. The influence of debonding size, form and location, and number of such damage on the modal characteristics of sandwich panels are shown. For nonlinear analysis, models based on implicit and explicit time integration schemes are presented and dynamic response gained with those models are discussed. Finally, questions related to debonding progression at the face sheet-core interface when dynamic loading continues with time are briefly highlighted