Fatigue of metal matrix composites

One unidirectional and two laminated 6061-0 A-B composite plates were tested under various cyclic loading conditions. Three types of material response to cyclic loading were identified; No evidence of damage at relatively low cyclic loads, damage accumulation caused primarily by growth of long matrix cracks parallel to the fibers in off-axis layers at higher loads, and sudden localized failure of the fibers. Quantitative analysis of the results shows that the extent of internal damage, demonstrated by a reduction in axial elastic modulus, depends on the applied stress range and is independent of mean stress. The stress range at which damage first starts to appear coincides with the shakedown range of the laminate.

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Résumé On a testé sous des conditions de contrainte cyclique variable des plaques constituées d'une part par des alliages 6061-0 A-B unidirectionnels et d'autre part du même alliage composite bilaminé. On a identifié trois types de réponse du matériau aux contraintes cycliques, à savoir la non-évidence d'un dommage pour des cycles de charge à faible amplitude relative, une accumulation du dommage causé principalement par la croissance de longues fissures matricielles parallèles aux fibres dans les couches éloignées du plan médian à des contraintes plus élevées, et une fissure soudainement localisée des fibres. L'analyse quantitative des résultats montre que 1'extension du dommage interne telle qu'elle est dóntree par une réduction du module axial d'élasticité, dépend de l'amplitude des contraintes appliquées et est indéndante de la contrainte moyenne. L'amplitude de contrainte auquelle un dommage commence à apparaître coíncide avec l'amplitude de l'adaptation plastique du laminé telle qu'établie par le théorème de Melan.

     

Improved generative semisupervised learning based on finely grained component-conditional class labeling

We introduce new inductive, generative semisupervised mixtures with more finely grained class label generation mechanisms than in previous work. Our models combine advantages of semisupervised mixtures, which achieve label extrapolation over a component, and nearest-neighbor (NN)/nearest-prototype (NP) classification, which achieve accurate classification in the vicinity of labeled samples or prototypes. For our NN-based method, we propose a novel two-stage stochastic data generation, with all samples first generated using a standard finite mixture and then all class labels generated, conditioned on the samples and their components of origin. This mechanism entails an underlying Markov random field, specific to each mixture component or cluster. We invoke the pseudo-likelihood formulation, which forms the basis for an approximate generalized expectation-maximization model learning algorithm. Our NP-based model overcomes a problem with the NN-based model that manifests at very low labeled fractions. Both models are advantageous when within-component class proportions are not constant over the feature space region "owned by" a component. The practicality of this scenario is borne out by experiments on UC Irvine data sets, which demonstrate significant gains in classification accuracy over previous semisupervised mixtures and also overall gains, over KNN classification. Moreover, for very small labeled fractions, our methods overall outperform supervised linear and nonlinear kernel support vector machines.     

Self-calibrated,Multi-spectral Photometric Stereo for 3D Face Capture

This paper addresses the problem of obtaining 3d detailed reconstructions of human faces in real-time and with inexpensive hardware. We present an algorithm based on a monocular multi-spectral photometric-stereo setup. This system is known to capture high-detailed deforming 3d surfaces at high frame rates and without having to use any expensive hardware or synchronized light stage. However, the main challenge of such a setup is the calibration stage, which depends on the lights setup and how they interact with the specific material being captured, in this case, human faces. For this purpose we develop a self-calibration technique where the person being captured is asked to perform a rigid motion in front of the camera, maintaining a neutral expression. Rigidity constrains are then used to compute the head’s motion with a structure-from-motion algorithm. Once the motion is obtained, a multi-view stereo algorithm reconstructs a coarse 3d model of the face. This coarse model is then used to estimate the lighting parameters with a stratified approach: In the first step we use a RANSAC search to identify purely diffuse points on the face and to simultaneously estimate this diffuse reflectance model. In the second step we apply non-linear optimization to fit a non-Lambertian reflectance model to the outliers of the previous step. The calibration procedure is validated with synthetic and real data.     

Spectral efficiency of cognitive radio networks under interference constraint and QoS guarantees

We study the problem of maximizing spectral efficiency of cognitive radio network deployments subject to an interference constraint and under specific quality of service (QoS) guarantees. The interference constraint corresponds to the upper limit of the received power that can be tolerated at the licensed users’ due to transmissions from unlicensed users. The QoS guarantees stem from the requirements imposed by the applications running at the users’ terminals. A cross-layer design is adopted that maps the user’s requirements into delay related QoS guarantees at the data link layer and error probability QoS guarantees at the physical layer. The obtained numerical results provide important insights regarding the impact of the considered constraint and guarantees on the achievable spectral efficiency of cognitive radio networks.     

A state estimator including conventional and synchronized phasor measurements

This paper presents an effective weighted least square formulation for the solution of the state estimation problem, considering conventional as well as synchronized phasor measurements. The proposed algorithm is based on a reference-free formulation, using both rectangular and polar coordinates for branch current phasor measurements, and alleviates any numerical problems encountered during initialization stage of the state estimation algorithm. Analytical equations are provided for the conventional and the phasor measurements and their corresponding partial derivatives with respect to state variables. The proposed algorithm is tested with a seven bus system and is compared with the traditional state estimator. Simulation results show that the proposed algorithm improves the precision greatly and gets better behavior as compared with the traditional state estimator.     

Histology image analysis for carcinoma detection and grading

This paper presents an overview of the image analysis techniques in the domain of histopathology, specifically, for the objective of automated carcinoma detection and classification. As in other biomedical imaging areas such as radiology, many computer assisted diagnosis (CAD) systems have been implemented to aid histopathologists and clinicians in cancer diagnosis and research, which have been attempted to significantly reduce the labor and subjectivity of traditional manual intervention with histology images. The task of automated histology image analysis is usually not simple due to the unique characteristics of histology imaging, including the variability in image preparation techniques, clinical interpretation protocols, and the complex structures and very large size of the images themselves. In this paper we discuss those characteristics, provide relevant background information about slide preparation and interpretation, and review the application of digital image processing techniques to the field of histology image analysis. In particular, emphasis is given to state-of-the-art image segmentation methods for feature extraction and disease classification. Four major carcinomas of cervix, prostate, breast, and lung are selected to illustrate the functions and capabilities of existing CAD systems.     

Task-driven e-manufacturing resource configurable model

Manufacturing resource configuration (MRC) plays a very important role in an e-Manufacturing system. Higher requirements for optimal configuration under online resource visibility and traceability have led to two main challenges. One is that more features of manufacturing tasks affecting the optimization results should be taken into consideration when establishing the MRC mathematical model for a manufacturing cell. The other is that manufacturing information should be given equal attention as MRC to realize real-time visibility and traceability of the resulting manufacturing cells. This paper presents a comprehensive mathematical model which considers more practical features of manufacturing tasks (e.g. batch volume and alternative processing routes) for manufacturing cell formation. This model adopts a fuzzy clustering method to group the manufacturing tasks and machines. Moreover, it is enabled by a smart equipment model to realize the configurable model of real-time manufacturing information and corresponding visualization and tracing methods. A case study is given to demonstrate the proposed models and methods.     

An efficient generation method of embedded reinforcement in hexahedral elements for reinforced concrete simulations

In this paper, an automatic procedure for the generation of embedded steel reinforcement inside hexahedral finite elements is presented. The automatic mapping of the entire reinforcement network inside the concrete hexahedral finite elements is performed using the end-point coordinates of the rebar reinforcement macro-elements. By introducing a geometrical constraint, this procedure decreases significantly the computational effort for generating the input data of the embedded rebar elements in three-dimensional finite-element analysis, particularly when dealing with relatively large-scale reinforced concrete models. The computational robustness and efficiency of the proposed mesh generation method are demonstrated through numerical experiments.