Multi-scale analysis of connectivity for image retrieval

Previously, we proposed the concept of connectivity to obtain discriminating shape descriptors. In this paper, we use connectivity to obtain superior distance histograms for multi-scale images. Experiments are performed to evaluate the distance histograms, based on connectivity, for shape-based retrieval of multi-scale images. Item S8 within the MPEG-7 still images content set is used for performing experiments. Experimental results show that the proposed method enhances retrieval performance significantly.

Development of the multi-scale analysis model to simulate strain localization occurring during material processing

Abstract A detailed description of possibilities given by the developed Cellular Automata—Finite Element (CAFE) multi scale model for prediction of the initiation and propagation of micro shear bands and shear bands in metallic materials subjected to plastic deformation is presented in the work. Particular emphasis in defining the criterion for initiation of micro shear and shear bands, as well as in defining the transition rules for the cellular automata, is put on accounting for the physical aspects of these phenomena occurring in two different scales in the material. The proposed approach led to the creation of the real multi scale model of strain localization phenomena. This model predicts material behavior in various thermo-mechanical processes. Selected examples of applications of the developed model to simulations of metal forming processes, which involve strain localization, are presented in the work. An approach based on the Smoothed Particle Hydrodynamic, which allows to overcome difficulties with remeshing in the traditional CAFE method, is a subject of this work as well. In the developed model remeshing becomes possible and difficulties limiting application of the CAFE method to simple deformation processes are solved. Obtained results of numerical simulaA detailed description of possibilities given by the developed Cellular Automata—Finite Element (CAFE) multi scale model for prediction of the initiation and propagation of micro shear bands and shear bands in metallic materials subjected to plastic deformation is presented in the work. Particular emphasis in defining the criterion for initiation of micro shear and shear bands, as well as in defining the transition rules for the cellular automata, is put on accounting for the physical aspects of these phenomena occurring in two different scales in the material. The proposed approach led to the creation of the real multi scale model of strain localization phenomena. This model predicts material behavior in various thermo-mechanical processes. Selected examples of applications of the developed model to simulations of metal forming processes, which involve strain localization, are presented in the work. An approach based on the Smoothed Particle Hydrodynamic, which allows to overcome difficulties with remeshing in the traditional CAFE method, is a subject of this work as well. In the developed model remeshing becomes possible and difficulties limiting application of the CAFE method to simple deformation processes are solved. Obtained results of numerical simulations are compared with the experimental results of cold rolling process to show good predicative capabilities of the developed model.tions are compared with the experimental results of cold rolling process to show good predicative capabilities of the developed model.

Multi-scale simulation using a hybrid mass-spring system and finite element model

Ply-scale finite element (FE) models are widely used to predict the performance of a composite structure based on material properties of individual plies. When simulating damage, these models neglect microscopic fracture processes which may have a significant effect on how a crack progresses within and between plies of a multidirectional laminate. To overcome this resolution limitation a multi-scale modelling technique is employed to simulate the effect micro-scale damage events have on the macro-scale response of a structure. The current paper discusses the development and validation of a hybrid mass-spring system and finite element modelling technique for multi-scale analysis. The model developed here is limited to elastic deformations; however, it is the first key step towards an efficient multi-scale damage model well suited to simulation of fracture in fibre reinforced composite materials. Various load cases have been simulated using the model developed here which show excellent accuracy compared to analytical and FE results. Future work is discussed, including extension of the model to incorporate damage modelling.

Sparse representation with multi-manifold analysis for texture classification from few training images

Texture classification is one of the most important tasks in computer vision field and it has been extensively investigated in the last several decades. Previous texture classification methods mainly used the template matching based methods such as Support Vector Machine and k-Nearest-Neighbour for classification. Given enough training images the state-of-the-art texture classification methods could achieve very high classification accuracies on some benchmark databases. However, when the number of training images is limited, which usually happens in real-world applications because of the high cost of obtaining labelled data, the classification accuracies of those state-of-the-art methods would deteriorate due to the overfitting effect. In this paper we aim to develop a novel framework that could correctly classify textural images with only a small number of training images. By taking into account the repetition and sparsity property of textures we propose a sparse representation based multi-manifold analysis framework for texture classification from few training images. A set of new training samples are generated from each training image by a scale and spatial pyramid, and then the training samples belonging to each class are modelled by a manifold based on sparse representation. We learn a dictionary of sparse representation and a projection matrix for each class and classify the test images based on the projected reconstruction errors. The framework provides a more compact model than the template matching based texture classification methods, and mitigates the overfitting effect. Experimental results show that the proposed method could achieve reasonably high generalization capability even with as few as 3 training images, and significantly outperforms the state-of-the-art texture classification approaches on three benchmark datasets. © 2014 Elsevier B.V. All rights reserved.

Reliability and validity of the Alberta context tool (ACT) with professional nurses: Findings from a multi-study analysis

Although organizational context is central to evidence-based practice, underdeveloped measurement hindersitsassessment. The Alberta Context Tool, comprised of 59 items that tap10 modifiable contextual concepts, was developed to address this gap. The purpose of this study to examine the reliability and validity of scores obtained when the Alberta Context Tool is completed by professional nurses across different healthcare settings. Five separate studies (N = 2361 nurses across different care settings) comprised the study sample. Reliability and validity were assessed. Cronbach's alpha exceeded 0.70 for9/10 Alberta Context Tool concepts. Item-total correlations exceeded acceptable standards for 56/59items. Confirmatory Factor Analysescoordinated acceptably with the Alberta Context Tool's proposed latent structure. The mean values for each Alberta Context Tool concept increased from low to high levels of research utilization(as hypothesized) further supporting its validity. This study provides robust evidence forreliability and validity of scores obtained with the Alberta Context Tool when administered to professional nurses.

Multi-scale rheological model for discontinuous phenomena in materials under deformation conditions

A study of possibilities given by the developed Cellular Automata–Finite Element (CAFE) multi-scale model for prediction of the initiation and propagation of micro-shear bands and shear bands in metallic materials subjected to plastic deformation is described in the paper. Particular emphasis in defining the criterion for initiation of micro-shear and shear bands, as well as in defining the transition rules for the cellular automata, is put on accounting for the physical aspects of those phenomena occurring in two different scales in the material. The proposed approach led to the creation of the real multi-scale model of strain localization. This model predicts material behavior in various thermo-mechanical processes. Selected examples of applications of the developed model to simulations of metal forming processes, which involve strain localization, are presented in the paper. An approach based on the Smoothed Particle Hydrodynamic, which allows to overcome difficulties with remeshing in the traditional CAFE method, is presented in the paper as well. In this approach remeshing becomes possible and mesh distortion, which limits application of the CAFE method to simple deformation processes, is eliminated.

Comparison of the strain distribution obtained from multi scale and conventional approaches to modelling extrusion

An investigation of the application of a multi scale CAFE model to prediction of the strain localization phenomena in industrial processes, such as extrusion, is presented in this work. Extrusion involves the formation of a strong strain localization zone, which influences the final product microstructure and may lead to a coarse grain layer close to the surface. Modelling of the shape of this zone and prediction of the strain magnitude will allow computer aided design of the extrusion process and optimisation of the technological parameters with respect to the microstructure and properties of the products. Thus, the particular objective of this work is comparison of the FE and CAFE predictions of strain localization in the shear zone area in extrusion. Advantages and disadvantages of the developed CAFE model are also discussed on the basis of the simulation results.

Depth estimation using multi-wavelet analysis based stereo vision approach

The problem of dimensional defects in aluminum die- casting is widespread throughout the foundry industry and their detection is of paramount importance in maintaining product quality. Due to the unpredictable factory environment and metallic, with highly reflective, nature of aluminum die-castings, it is extremely hard to estimate true dimensionality of the die-casting, autonomously. In this work, we propose a novel robust 3D reconstruction algorithm capable of reconstructing dimensionally accurate 3D depth models of the aluminum die-castings. The developed system is very simple and cost effective as it consists of only a stereo cameras pair and a simple fluorescent light. The developed system is capable of estimating surface depths within the tolerance of 1.5 mm. Moreover, the system is invariant to illuminative variations and orientation of the objects in the input image space, which makes the developed system highly robust. Due to its hardware simplicity and robustness, it can be implemented in different factory environments without a significant change in the setup.

Multi-scale modelling of DP590 steel

Dual Phase (DP) steel one of the Advanced High Strength Steels (AHSS) has a two phase microstructure where soft and hard phase acts together to offer a high strength composite effect. The high strength, however, must be balanced with ductility so that complex parts and designs can be manufactured from AHSS sheets. However, during forming certain grades of DP steel a sudden crack can occur without any intimation of necking. Thus, due to this abnormal forming behaviour, is difficult to accurately predict because most classical modelling approaches are not designed for such micro-structurally heterogeneous materials. These modelling approaches are generally based on an average representation of the material behaviour in a continuum mechanics formulation. This works for materials that are homogenous, or at least could be assumed to be homogenous at scales lower than the naked eye can see. However, for a material like AHSS, the microstructure plays a significant role in dictating the mechanical behaviour at the macro-scale. This paper studies the multi-scale modelling ofDP590 steel. It is found that the sufficient accuracy can be achieved from multi-scale modelling while comparing with the experiments.