Different Kinds Of Textures Research Articles

Implications of the Dark-LMA solution for neutrino mass matrices

In this work we have re-investigated two different kinds of texture zero ansatz of the low energy neutrino mass matrix in view of the Dark-Large-Mixing-Angle (DLMA) solution of the solar neutrino problem which can arise in the presence of non-standard interactions. In particular we revisit the cases of (i) one zero mass matrices when the lowest neutrino mass is zero and (ii) one zero texture with a vanishing minor. In our study we find that for most of the cases, the texture zero conditions which are allowed for the LMA solution, are also allowed for the DLMA solution. However, we found two textures belonging to the case of one zero texture with a vanishing minor where LMA solution does not give a viable solution whereas DLMA solution does. We analyze all the possible texture zero cases belonging to these two kinds of texture zero structures in detail and present correlations between different parameters. We also present the predictions for the effective neutrino mass governing neutrino-less double beta decay for the allowed textures.

4. Exercises for Piano and their Role in the Pedagogical Activity of Vitalii Sechkin

Abstract In the article, the author analyses the role of technical exercises used in his pedagogical activity by Vitaly Sechkin, remarkable pianist and professor, Honoured Artist of Ukraine. He paid particular attention to the development of the technical skills of his students, for which he used various exercises and virtuoso etudes. A detailed characteristic is made of the particularities of C.-L. Hanon’s and J. Brahms’s sets of exercises, which pursue similar objectives - the development of finger speed, the freedom to execute different kinds of texture, assimilation of tonalities. The professor’s favourite exercises and his methodical recommendations are mentioned as well.

A robust weakly supervised learning of deep Conv-Nets for surface defect inspection

Automatic defect detection is a challenging task owing to the complex textured background with non-uniform intensity distribution, weak differences between defects and background, diversity of defect types, and high cost of annotated samples. In order to solve these challenges, this paper proposes a novel end-to-end defect classification and segmentation framework based on weakly supervised learning of a convolutional neural network (CNN) with attention architecture. Firstly, a novel end-to-end CNN architecture integrating the robust classifier and spatial attention module is proposed to enhance defect feature representation ability, which significantly improves the classification accuracy. Secondly, a new spatial attention class activation map (SA-CAM) is proposed to improve segmentation adaptability by generating more accurate heatmap. Moreover, for different surface texture, SA-CAM can significantly suppress the background’s inference and highlight defect area. Finally, the proposed weakly supervised learning framework is trained using only global image labels and devoted to two main visual recognition tasks: defect samples classification and area segmentation. At the same time, it is robust to complex backgrounds. Results of the experiments verify the generalization of the proposed method on three distinct datasets with different kinds of textures and backgrounds. In the classification tasks, the proposed method improves accuracy by 0.66–25.50%. In the segmentation tasks, the proposed method improves accuracy by 5.49–7.07%.

Unsupervised color texture segmentation based on multi-scale region-level Markov random field models

In the field of color texture segmentation, region-level Markov random field model (RMRF) has become a focal problem because of its efficiency in modeling the large-range spatial constraints. However, the RMRF defined on a single scale cannot describe the un-stationary essence of the image, which highly limits its robustness. Hence, by combining wavelet transformation and the RMRF model, we present a multi-scale RMRF (MsRMRF) model in wavelet domainin this paper. In the Bayesian framework, the proposed model seamlessly integrates the multi-scale information stemmed from both the original image and the region-level spatial constraints. Therefore, the new model can accurately describe the characteristics of different kinds of texture. Based on MsRMRF, an unsupervised segmentation algorithm is designed for segmenting color texture images. Both synthetic color texture images and remote sensing images are employed in the comparative experiments, and the experimental results show that the proposed method can obtain more accurate segmentation results than the competitors.

Automatic texture exemplar extraction based on global and local textureness measures

Texture synthesis is widely used for modeling the appearance of virtual objects. However, traditional texture synthesis techniques emphasize creation of optimal target textures, and pay insufficient attention to choice of suitable input texture exemplars. Currently, obtaining texture exemplars from natural images is a labor intensive task for the artists, requiring careful photography and significant postprocessing. In this paper, we present an automatic texture exemplar extraction method based on global and local textureness measures. To improve the efficiency of dominant texture identification, we first perform Poisson disk sampling to randomly and uniformly crop patches from a natural image. For global textureness assessment, we use a GIST descriptor to distinguish textured patches from non-textured patches, in conjunction with SVM prediction. To identify real texture exemplars consisting solely of the dominant texture, we further measure the local textureness of a patch by extracting and matching the local structure (using binary Gabor pattern (BGP)) and dominant color features (using color histograms) between a patch and its sub-regions. Finally, we obtain optimal texture exemplars by scoring and ranking extracted patches using these global and local textureness measures. We evaluate our method on a variety of images with different kinds of textures. A convincing visual comparison with textures manually selected by an artist and a statistical study demonstrate its effectiveness.

Influence of Different Micro-Imprints to Fatigue Life of Components

Abstract To improve tribological properties of components, different kinds of textures are added to their surfaces. Although the added imprints or craters are only few tens of micrometers wide and a few micrometers deep, they form an initial crack from which a fatigue crack may propagate. In this article, a numerical approach for calculating the fatigue life of a body with present micro-imprints with standard finite-element software will be presented. The objective is to show how the imprint shape and its manufacturing process influences the fatigue life. The considered specimens are round bodies that were made from Boehler K890 microclean cold-working steel. Three shapes of the imprints are studied: the imprints produced by a Vickers pyramid and a Rockwell cone and a half-spherical crater void produced by a laser device. The flat-surface round body served as a reference. The imprint shape and its manufacturing process is also considered. For this reason, a simulation of impression of Vickers and Rockwell indenters is simulated first, which is followed by a numerical fatigue-life prediction. In this manner, the residual stresses from the imprinting process are considered during the fatigue-life prediction. For the laser-induced craters and the reference body, only the fatigue life is numerically predicted. Because the material inhomogeneities are much smaller than the geometrical ones, the calculated fatigue lives for different texturing represent the fatigue-life reduction caused by the applied textures. To validate the presented numerical approach, the calculated fatigue lives are compared to the experimentally determined.

$\mathcal {H}$ Distribution for Multilook Polarimetric SAR Data

Polarimetric synthetic aperture radar (PolSAR) is an advanced imaging radar system, for which the acquired data provide not only the information of each channel but also the correlation between channels. To fully utilize and accurately model the multilook PolSAR data, a novel compound distribution, named the $\mathcal {H}$ distribution, is proposed based on the generalized Fisher distribution ( $\text{G}\mathcal {F}\text{D}$ ). Specifically, the $\text{G}\mathcal {F}\text{D}$ introduces a power parameter to the ordinary Fisher distribution. With one more free parameter, the $\text{G}\mathcal {F}\text{D}$ is flexible and versatile enough to characterize different kinds of texture. Then, by assuming the generalized-Fisher-distributed texture and the Wishart-distributed speckle, the $\mathcal {H}$ distribution is derived, whose closed-form expression is obtained with the help of Fox’s H-function. As such, the $\mathcal {H}$ distribution has a compact form and is conveniently applied to practical problems, such as modeling and classification of PolSAR data. The effectiveness of this method is tested by modeling the multilook PolSAR data and performing image classification. The experimental results demonstrate that the $\mathcal {H}$ distribution is a flexible and effective way to model multilook PolSAR data.

Nanotribological Properties of Nanotextured Ni-Co Coating Surface Measured with AFM Colloidal Probe Technique

Surface-texturing is a useful method of modifying surface frictional performance. A simple, novel, easily-controlled method was used to fabricate different kinds of textures on an Ni-Co coating surface. The nanotribological properties were characterised by atomic force microscope (AFM) with a colloidal probe. The results showed that, compared to the original Ni-Co coating surface, the nanotextured surface can adjust the surface friction forces. The half-elliptic patterns have better tribological properties than hemispherical patterns. Therefore, both laser energy and laser scanning speed will influence the friction performances of Ni-Co coating surfaces.

Effect of ion-beam surface modification technology on the variation of surface texture

Ion-beam surface bombardment modification technology is successfully used to manufacture different kinds of nano-textures on the surface of silicon substrate. Relationship between the morphology and arrangement patterns of nano-textures and the bombarding parameters is studied. Results show that the ion-beam bombardment has a significant impact on surface morphology. Different kinds of textures on silicon substrate can be formed according to the variation of bombardment time. The nanodot array texture is observed on the surface of silicon substrate when the duration of argon ion-beam bombardment is 15 minutes. Simultaneously, the tetrahedral amorphous carbon film is deposited on the silicon substrates that have different kinds of nano-texture. The microstructure of ta-C film deposited on unprocessed and nano-textured silicon substrate is analyzed by X-ray photoelectron spectroscopy. Results indicate that the content of sp3 bonds decreases with increasing bombardment time, and thereafter keeps a steady value. The ta-C films deposited on the nanodot-textured substrate shows the lowest sp3 fraction. It is also observed by friction and wear test that the wear time is enhanced from 10 to 70 min. The tribological properties is highly improved when the coating is deposited on the nano-textured substrate.

Optimization of reparative osteogenesis with using of calcium phosphate osteoplastic materials (literature review)

The analysis of domestic and foreign scientific sources on the possibilities of calcium phosphate osteoplastic materials for optimization of the reparative osteogenesis was done. It was found that different kinds of texture and geometric shapes of calcium phosphate osteoplastic materials make it possible to fill the defects of various configurations. Impregnation of granules, blocks and cylinders with hydrophilic surface with sterile physiological saline, autologous blood, blood products, bone marrow cells provide such texture of the material which might be easily modeled with a scalpel according to the shape of the defect, and thus it is useful in the surgical field. Synthetic nature of calcium phosphate materials ensures their safety in clinical practice, preventing the risk of infections, the occurrence of immune and genetic incompatibility, rejection reaction, suppuration, and allergic reactions. Xenografs of bovine bones also demonstrate safety concerning allergic reactions, bovine spongiform encephalopathy and other infections because of deproteinisation and high temperature processing (above 800 ºC) in time of their producing. Above all calcium-phosphate osteoplastic materials have osteoconductive, osteostimulative and secondary osteoinductive features, and impregnation of some implants with antibiotic allows to create on the site of implantation anti-bacterial and anti-inflammatory effects. Osteocondution caused by macro-, micropores and rough structure of osteoplastic materials, osteostimulation caused by their ability to adsorb growth factors on their surface and calcium ions from implants, and the secondary osteoinduction caused by bone morphogenetic proteins which absorb from tissue environment of the bone defect and blood on their surface or comprise to the implant. It was found that calcium phosphate osteoplastic materials are able to optimize angiogenesis, adhesion, proliferation of osteogenic cells and their differentiation into osteoblasts in the area of the defect and, consequently, newly development of bone tissue directly on the surface and in the cavities of the implant. It was shown that initially granulation tissue with blood vessels or osteoid, and after that trabecular mesh of woven bone tissue with a gradual formation of mature lamellar bone to be formed. Due to the phenomenon of precipitation and association with newly formed bone tissue of dissolved crystals of implanted calcium phosphate materials and activity of osteoblasts it is subjected to mineralization and remodeling resulting in the formation of bone tissue with architectonics which according to the law of Julius Wolff meets concrete functional load acting on bone. Simultaneously with bone formation due to the activity of osteoclasts and macrophages calcium phosphate osteoplastic materials are subjected to gradual resorption with speed ranging from some months to 11 years. The latter depends on many factors among which there are physical and chemical characteristics of material, size and structure of pores, geometrical shape, architectonics of the surface, impregnating substances before implantation, technical nuances of producing as well as type of bone which it implanted in. Different expressiveness of the above mentioned properties of implants must be considered in case of application in each clinical situation.

Texture analysis and classification using shortest paths in graphs

Texture is a very important attribute in the field of computer vision. This work proposes a novel texture analysis method which is based on graph theory. Basically, we convert the pixels of an image into vertices of an undirected weighted graph and explore the shortest paths between pairs of pixels in different scales and orientations of the image. This procedure is applied to Brodatz’s textures and UIUC texture dataset in order to evaluate its capacity of discriminating different kinds of textures. The best classification results using the standard parameters of the method are 98.50%,67.30% and 88.00% of success rate (percentage of samples correctly classified) for Brodatz’s textures, UIUC textures (image size of 200×200 pixels), and original UIUC textures (image size of 640×480 pixels), respectively. These results prove that the proposed approach is an efficient tool for texture analysis, once they are superior to the results achieved by traditional and novel texture descriptors presented in literature.

Processing Routes Toward Textured Polycrystals in Ferromagnetic Shape Memory Alloys

AbstractNi–Mn–Ga single crystals can produce large strain in moderate magnetic fields. It is the scope of this article to demonstrate, that also polycrystalline materials can show strain in a magnetic field, so called MFIS (magnetic field‐induced strain). In order to design functional polycrystalline materials the interactions of twin boundaries and grain boundaries have to be understood. Therefore, different ways of introducing a texture into Ni–Mn–Ga polycrystals are presented. The different kinds of texture and the consequences for the corresponding materials are discussed. Moreover, thermal, magnetic, and/or mechanical training concepts are presented and their working principle is explained. Several possibilities of evaluating the MFIS capability of the resulting samples are displayed. Finally methods of increasing the strain further are discussed.

Unsupervised detection and localization of structural textures using projection profiles

The main goal of existing approaches for structural texture analysis has been the identification of repeating texture primitives and their placement patterns in images containing a single type of texture. We describe a novel unsupervised method for simultaneous detection and localization of multiple structural texture areas along with estimates of their orientations and scales in real images. First, multi-scale isotropic filters are used to enhance the potential texton locations. Then, regularity of the textons is quantified in terms of the periodicity of projection profiles of filter responses within sliding windows at multiple orientations. Next, a regularity index is computed for each pixel as the maximum regularity score together with its orientation and scale. Finally, thresholding of this regularity index produces accurate localization of structural textures in images containing different kinds of textures as well as non-textured areas. Experiments using three different data sets show the effectiveness of the proposed method in complex scenes.

Underwater Sustainability of the “Cassie” State of Wetting

A rough hydrophobic surface when immersed in water can result in a "Cassie" state of wetting in which the water is in contact with both the solid surface and the entrapped air. The sustainability of the entrapped air on such surfaces is important for underwater applications such as reduction of flow resistance in microchannels and drag reduction of submerged bodies such as hydrofoils. We utilize an optical technique based on total internal reflection of light at the water-air interface to quantify the spatial distribution of trapped air on such a surface and its variation with immersion time. With this technique, we evaluate the sustainability of the Cassie state on hydrophobic surfaces with four different kinds of textures. The textures studied are regular arrays of pillars, ridges, and holes that were created in silicon by a wet etching technique, and also a texture of random craters that was obtained through electrodischarge machining of aluminum. These surfaces were rendered hydrophobic with a self-assembled layer of fluorooctyl trichlorosilane. Depending on the texture, the size and shape of the trapped air pockets were found to vary. However, irrespective of the texture, both the size and the number of air pockets were found to decrease with time gradually and eventually disappear, suggesting that the sustainability of the "Cassie" state is finite for all the microstructures studied. This is possibly due to diffusion of air from the trapped air pockets into the water. The time scale for disappearance of air pockets was found to depend on the kind of microstructure and the hydrostatic pressure at the water-air interface. For the surface with a regular array of pillars, the air pockets were found to be in the form of a thin layer perched on top of the pillars with a large lateral extent compared to the spacing between pillars. For other surfaces studied, the air pockets are smaller and are of the same order as the characteristic length scale of the texture. Measurements for the surface with holes indicate that the time for air-pocket disappearance reduces as the hydrostatic pressure is increased.

Effect of the cooling speed through Tc on the formation of textures in superfluid 3He-A

The cw-NMR measurements have been performed for superfluid 3He A-phase in a single cylinder with 115 μm inner radius. We observed two peaks in NMR spectra, the main peak and the satellite peak. The satellite peak is attributed to textures which are induced by the flow due to temperature gradient by controlling the cooling speed of samples from normal fluid state to superfluid A-phase. We have observed that the satellite peak height of NMR spectrum increases continuously as the cooling speed increases. The number of possible texture types is restricted for our cylindrical cell, since the radius of the cell is about ten times larger than the dipole coherence length ξd ∼ 10 μm. Therefore, it is unlikely that the continuous change of NMR spectrum is attributed to the different kinds of textures. We discuss that these results are due to textural domain structure along cylindrical axis.

Model of Frequency Analysis in the Visual Cortex and the Shape from Texture Problem

This paper addresses the question: at the level of cortical cells present in the primary area V1, is the information sufficient to extract the local perspective from the texture? Starting from a model of complex cells in visual area V1, we propose a biologically plausible algorithm for frequency analysis applied to the shape from texture problem. First, specific log-normal filters are designed in replacement of the classical Gabor filters because of their theoretical properties and of their biological plausibility. These filters are separable in frequency and orientation and they better sample the image spectrum which makes them appropriate for any pattern analysis technique. A method to estimate the local frequency in the image, which discards the need to choose the best local scale, is designed. Based on this frequency analysis model, a local decomposition of the image into patches leads to the estimation of the local frequency variation which is used to solve the problem of recovering the shape from the texture. From the analytical relation between the local frequency and the geometrical parameters, under perspective projection, it is possible to recover the orientation and the shape of the original image. The accuracy of the method is evaluated and discussed on different kind of textures, both regular and irregular, with planar and curved surfaces and also on natural scenes and psychophysical stimuli. It compares favorably to the best existing methods, with in addition, a low computational cost. The biological plausibility of the model is finally discussed.

Different kind of textures of Yukawa coupling matrices in the two Higgs doublet model type III

The quark mass matrices ansatze proposed by Fritzsch, Du–Xing and Fukuyama–Nishiura in the framework of the general two Higgs doublet model are studied. The corresponding Yukawa matrices in the flavor basis in the various cases considered are discussed. The corresponding Cabibbo–Kobayashi–Maskawa matrix elements are computed in all cases and compared with their experimental values. The complex phases of the ansatze are taken into account, and the CP violating phase δ is computed. Finally, in order to observe the influence of the various kinds of texture of the Yukawa coupling matrices considered, some issues in the phenomenology of the two body decays of the top quark, the lightest Higgs boson and the charged Higgs boson are discussed.

Neuronal response to texture- and contrast-defined boundaries in early visual cortex

Natural scenes contain a variety of visual cues that facilitate boundary perception (e.g., luminance, contrast, and texture). Here we explore whether single neurons in early visual cortex can process both contrast and texture cues. We recorded neural responses in cat A18 to both illusory contours formed by abutting gratings (ICs, texture-defined) and contrast-modulated gratings (CMs, contrast-defined). We found that if a neuron responded to one of the two stimuli, it also responded to the other. These neurons signaled similar contour orientation, spatial frequency, and movement direction of the two stimuli. A given neuron also exhibited similar selectivity for spatial frequency of the fine, stationary grating components (carriers) of the stimuli. These results suggest that the cue-invariance of early cortical neurons extends to different kinds of texture or contrast cues, and might arise from a common nonlinear mechanism.

X-ray diffraction investigations of adherent and free standing TiN coatings deposited by magnetron sputtering

TiN coatings deposited on steel substrates at different biases and temperatures, and with different nitrogen contents, were studied by conventional X-ray powder diffractometry. The diffraction peaks were separated by profile fitting. In adherent films different kinds of texture and a large anisotropy of lattice parameters ( a(hhh) < a( h00) < a( hh0)) were detected. In corresponding free-standing films lower average values of lattice parameters were found and their anisotropy decreased considerably. The microstrain determined from X-ray line broadening remained unchanged, which proves its inelastic nature owing to the lattice defects.

Textures in induced morphology crystal aggregates of CaCO3: Sheaf of wheat morphologies

Three different kinds of textures have been found in induced crystal aggregates of CaCO 3 sheaf of wheat morphologies, grown in silica gel at pH = 10. One of them showing concentric banding can be explained by a simple aggregation model of stacked rhombohedra along its c axis. The second does not present concentric banding and is formed by fibers with 3 m symmetry. Finally, the third has a more complicated fiber design with periodical units arranged in a helical pattern, which has not been explained by any simple model of CaCO 3 crystal aggregation. The morphogenetical role of the silicated matrix must be particularly important in this last case.