The tetrahedral finite cell method: Higher‐order immersogeometric analysis on adaptive non‐boundary‐fitted meshes

The finite cell method (FCM) is an immersed domain finite element method that combines higher‐order non‐boundary‐fitted meshes, weak enforcement of Dirichlet boundary conditions, and adaptive quadrature based on recursive subdivision. Because of its ability to improve the geometric resolution of intersected elements, it can be characterized as an immersogeometric method. In this paper, we extend the FCM, so far only used with Cartesian hexahedral elements, to higher‐order non‐boundary‐fitted tetrahedral meshes, based on a reformulation of the octree‐based subdivision algorithm for tetrahedral elements. We show that the resulting TetFCM scheme is fully accurate in an immersogeometric sense, that is, the solution fields achieve optimal and exponential rates of convergence for h‐refinement and p‐refinement, if the immersed geometry is resolved with sufficient accuracy. TetFCM can leverage the natural ability of tetrahedral elements for local mesh refinement in three dimensions. Its suitability for problems with sharp gradients and highly localized features is illustrated by the immersogeometric phase‐field fracture analysis of a human femur bone. Copyright © 2016 John Wiley & Sons, Ltd.     

Polarization-Dependent Periodic Pulse Oscillation in a Diode-Laser-Pumped and Intracavity Frequency-Doubled Nd:YVO 4 Laser

We demonstrate that two cross-polarized longitudinal modes can have 50% higher conversion efficiency than two parallel-polarized longitudinal modes in a diode-laser-pumped and intracavity frequency-doubled Nd:YVO(4) laser when operated under periodic pulse oscillation. Through simulations of the rate equations for primary frequency intensities and gains, we also verify that this effect can be attributed to gain competition and complementary conversion coefficient between second-harmonic and sum-frequency generations.     

Single- and dual-ion-beam sputter deposition of titanium oxide films

The optical properties and the surface morphologies of single-ion-beam sputtering (SIBS) and dual-ion-beam sputtering (DIBS) depositions of titanium oxide films are investigated and compared. In the DIBS process, the ion-assisted deposition by the voltage of a low ion beam ranged from 50 to 300 V at a 0% and 44% oxygen percentage. Cosputtering with materials of Si, SiO(2) (fused silica), and Al is also utilized in SIBS to improve amorphous-structure film. For the low-absorption and surface-roughness film, the optimum deposition condition of DIBS and postdeposition baking temperature for SIBS and DIBS are essential to the process.     

Independent spanning trees vs. edge-disjoint spanning trees in locally twisted cubes

Fault-tolerant broadcasting and secure message distribution are important issues for numerous applications in networks. It is a common idea to design multiple spanning trees with a specific property in the underlying graph of a network to serve as a broadcasting scheme or a distribution protocol for receiving high levels of fault-tolerance and of security. A set of spanning trees in a graph is said to be edge-disjoint if these trees are rooted at the same node without sharing any common edge. Hsieh and Tu [S.-Y. Hsieh, C.-J. Tu, Constructing edge-disjoint spanning trees in locally twisted cubes, Theoretical Computer Science 410 (2009) 926-932] recently presented an algorithm for constructing n edge-disjoint spanning trees in an n-dimensional locally twisted cube. In this paper, we prove that indeed all spanning trees constructed by their algorithm are independent, i.e., any two spanning trees are rooted at the same node, say r, and for any other node v≠r, the two different paths from v to r, one path in each tree, are internally node-disjoint.     

Local contrast enhancement and adaptive feature extraction for illumination-invariant face recognition

Recognizing human faces in various lighting conditions is quite a difficult problem. The problem becomes more difficult when face images are taken in extremely high dynamic range scenes. Most of the automatic face recognition systems assume that images are taken under well-controlled illumination. The face segmentation as well as recognition becomes much simpler under such a constrained condition. However, illumination control is not feasible when a surveillance system is installed in any location at will. Without compensating for uneven illumination, it is impossible to get a satisfactory recognition rate. In this paper, we propose an integrated system that first compensates uneven illumination through local contrast enhancement. Then the enhanced images are fed into a robust face recognition system which adaptively selects the most important features among all candidate features and performs classification by support vector machines (SVMs). The dimension of feature space as well as the selected types of features is customized for each hyperplane. Three face image databases, namely Yale, Yale Group B, and Extended Yale Group B, are used to evaluate performance. The experimental result shows that the proposed recognition system give superior results compared to recently published literatures.     

A practical design of content protection for H.264/AVC compressed videos by selective encryption and fingerprinting

Digital Rights Management (DRM) of videos is an important issue nowadays. Considering that H.264/AVC videos will be widely used in various applications, we propose a practical design, which combines the methodologies of selective encryption and fingerprinting, for effective DRM of H.264/AVC streaming videos. A selective encryption scheme is first presented to scramble the video content by encrypting a small amount of data in the compressed bit-stream. The scrambled video is H.264-compliant to reduce the complexity of decoder since it can still be played without triggering errors in the decoding process. A fingerprinting scheme is then introduced to provide further protection. We extract a reasonable amount of data from the video and embed the watermark acting as the fingerprint of the video recipient. To acquire the high-quality video for viewing, the user has to decrypt the video obtained from a video server and then combine it with the watermarked data provided from a user information server. The resulting viewable video is thus fingerprinted to deter the user from illegally redistributing the content. Experimental results will demonstrate the feasibility of the proposed approach.     

The bending strip method for isogeometric analysis of Kirchhoff–Love shell structures comprised of multiple patches

In this paper we present an isogeometric formulation for rotation-free thin shell analysis of structures comprised of multiple patches. The structural patches are C¹- or higher-order continuous in the interior, and are joined with C⁰-continuity. The Kirchhoff–Love shell theory that relies on higher-order continuity of the basis functions is employed in the patch interior as presented in Kiendl et al. [36]. For the treatment of patch boundaries, a method is developed in which strips of fictitious material with unidirectional bending stiffness and zero membrane stiffness are added at patch interfaces. The direction of bending stiffness is chosen to be transverse to the patch interface. This choice leads to an approximate satisfaction of the appropriate kinematic constraints at patch interfaces without introducing additional stiffness to the shell structure. The attractive features of the method include simplicity of implementation and direct applicability to complex, multi-patch shell structures. The good performance of the bending strip method is demonstrated on a set of benchmark examples. Application to a wind turbine rotor subjected to realistic wind loads is also shown. Extension of the bending strip approach to the coupling of solids and shells is proposed and demonstrated numerically.     

Integrating independent component analysis and support vector machine for multivariate process monitoring

This study aims to develop an intelligent algorithm by integrating the independent component analysis (ICA) and support vector machine (SVM) for monitoring multivariate processes. For developing a successful SVM-based fault detector, the first step is feature extraction. In real industrial processes, process variables are rarely Gaussian distributed. Thus, this study proposes the application of ICA to extract the hidden information of a non-Gaussian process before conducting SVM. The proposed fault detector will be implemented via two simulated processes and a case study of the Tennessee Eastman process. Results demonstrate that the proposed method possesses superior fault detection when compared to conventional monitoring methods, including PCA, ICA, modified ICA, ICA–PCA and PCA–SVM.