Texture Direction Research Articles

Intelligent decision support system for cardiovascular risk prediction using hybrid loss deep joint segmentation and optimized deep learning

Cardiovascular disease (CVD) represents an emerging death reason worldwide. CVD is based on the capability to discover the high-risk individuals before designing overt events. An effective technique for CVD risk prediction is developed using retinal fundus images. Initially, the retinal fundus images are subjected to pre-processing using grayscale conversion. The optic disc is detected with binarization and circle fixing. Then, the blood vessel segmentation uses deep joint segmentation, wherein dice coefficient and binary cross-entropy are integrated. After that, the feature extraction is done for mining convenient features that include several statistical features. Meanwhile, features like Local Directional Texture Pattern (LDTP) and Local Gabor Binary Pattern (LGBP) are mined from the inputted image. Then, the cardiovascular risk prediction is made by a Deep neuro-fuzzy network (DNFN), such that the risks are classified into normal and hypertensive. Finally, the DNFN is trained using the developed Fractional Calculus-Horse Herd Optimization Algorithm (FCHOA), which is devised by combining Fractional Calculus (FC) and the Horse Herd Optimization algorithm (HOA). The proposed FCHOA-based DNFN offered enhanced efficiency with the highest accuracy, sensitivity and specificity of 91.6, 92.3 and 91.9%.

Infrared and visible image fusion for ship targets based on scale‐aware feature decomposition

Infrared (IR) and visible (VI) image fusion play an important role in improving the sea scene perception and ship target detection. Although there have been many studies on image fusion considering the sea scene characteristics, there has still been no adequate extraction method for detailed information of a ship target in a sea scene. To overcome this shortcoming, this paper proposes a fusion method based on a scale-aware feature decomposition, which can accurately extract features of a ship target at different scales. First, a hybrid feature decomposition method based on the scale-aware structure-preserving filter and Gaussian filter is designed. The proposed method separated source images into region, structure, and texture layers, and thus achieved a finer-scale division than traditional multiscale decomposition methods in the sea-clutter background. Then, further decomposition of the texture layer was performed by the shearlet transform to obtain the directional texture feature. According to the characteristics of each layer, different strategies were adopted for the fusion, and the weighting factor was used to obtain the final fusion result. Experimental results indicated that the proposed method could achieve better subjective and objective results than current state-of-the-art methods. This method introduces a scale-aware edge preserving filter to improve the ability of detail extraction and is suitable for image fusion of ship targets.

The effect of hot rolling process on macro-texture and high-temperature mechanical properties of AZ31B alloy modified by Ca and Ce

This study examines the high-temperature tensile properties of AZ31 and AZ31-1.0Ca-0.2Ce alloys in different rolling directions. Tensile test results at 250 °C showed that the ductility of AZ31-1.0Ca-0.2Ce alloy increased threefold in the 90° perpendicular direction to rolling direction. Moreover, both strength and elongation values of AZ31-1.0Ca-0.2Ce alloy were higher than those of AZ31. Macro-texture measurements revealed that AZ31 and AZ31-1.0Ca-0.2Ce alloys showed strong and weakened basal texture in the rolling direction, respectively. The combined effect of secondary phases and texture weakening increased the high-temperature ductility (49%) of AZ31-1.0Ca-0.2Ce. In the rolling direction, yield (YS) and ultimate tensile strength of AZ31-1.0Ca-0.2Ce were obtained as 115 and 121 MPa, respectively. These values were higher than AZ31 alloy due to the stronger texture of the non-basal planes. The fracture surface of AZ31 samples proved that the rough and crack-dominated surface led to brittle fracture formation. However, fine-sized dimples resulted in a ductile fracture in AZ31-1.0Ca-0.2Ce samples.

Image Enhancement of Maritime Infrared Targets Based on Scene Discrimination.

Infrared image enhancement technology can effectively improve the image quality and enhance the saliency of the target and is a critical component in the marine target search and tracking system. However, the imaging quality of maritime infrared images is easily affected by weather and sea conditions and has low contrast defects and weak target contour information. At the same time, the target is disturbed by different intensities of sea clutter, so the characteristics of the target are also different, which cannot be processed by a single algorithm. Aiming at these problems, the relationship between the directional texture features of the target and the roughness of the sea surface is deeply analyzed. According to the texture roughness of the waves, the image scene is adaptively divided into calm sea surface and rough sea surface. At the same time, through the Gabor filter at a specific frequency and the gradient-based target feature extraction operator proposed in this paper, the clutter suppression and feature fusion strategies are set, and the target feature image of multi-scale fusion in two types of scenes are obtained, which is used as a guide image for guided filtering. The original image is decomposed into a target and a background layer to extract the target features and avoid image distortion. The blurred background around the target contour is extracted by Gaussian filtering based on the potential target region, and the edge blur caused by the heat conduction of the target is eliminated. Finally, an enhanced image is obtained by fusing the target and background layers with appropriate weights. The experimental results show that, compared with the current image enhancement method, the method proposed in this paper can improve the clarity and contrast of images, enhance the detectability of targets in distress, remove sea surface clutter while retaining the natural environment features in the background, and provide more information for target detection and continuous tracking in maritime search and rescue.

Understanding the impact of texture on the micromechanical anisotropy of laser powder bed fused Inconel 718

The manufacturability of metallic alloys using laser-based additive manufacturing methods such as laser powder bed fusion has substantially improved within the last decade. However, local melting and solidification cause hierarchically structured and crystallographically textured microstructures possessing large residual stress. Such microstructures are not only the origin of mechanical anisotropy but also pose metrological challenges for the diffraction-based residual stress determination. Here we demonstrate the influence of the build orientation and the texture on the microstructure and consequently the mechanical anisotropy of as-built Inconel 718. For this purpose, we manufactured specimens with [001]/[011]-, [001]- and [011]/[overline{1} {text{11}}]-type textures along their loading direction. In addition to changes in the Young’s moduli, the differences in the crystallographic textures result in variations of the yield and ultimate tensile strengths. With this in mind, we studied the anisotropy on the micromechanical scale by subjecting the specimens to tensile loads along the different texture directions during in situ neutron diffraction experiments. In this context, the response of multiple lattice planes up to a tensile strain of 10% displayed differences in the load partitioning and the residual strain accumulation for the specimen with [011]/[overline{1} {text{11}}]-type texture. However, the relative behavior of the specimens possessing an [001]/[011]- and [001]-type texture remained qualitatively similar. The consequences on the metrology of residual stress determination methods are discussed.

Sampling optimization for 3D surface measurement. Part II: Sampling interval optimization based on cumulative power spectral density analysis

Sampling interval is a key sampling parameter in 3D surface measurement, which affects uncertainty and time of measurement. This study aimed to optimize the sampling interval of 3D isotropic and anisotropic surfaces based on cumulative power spectral density (PSD) analysis for the comparability of 3D surface measurement meanwhile ensuring the measurement efficiency. Twenty-four surfaces with expected height distribution and spatial distribution were generated based on Fast Fourier Transform (FFT) and autocorrelation length function. The effects of sampling interval on surface texture parameters and cumulative PSD of isotropic and anisotropic surfaces were investigated under the conditions of redundant, appropriate and distorted sampling intervals, respectively. The results show 3D texture parameters were insensitive to sampling interval, but cumulative PSD significantly depends on sampling interval. Therefore, based on the cumulative PSD analysis, the optimal sampling intervals for isotropic and anisotropic surfaces with different mean surface height ranges were given. It also indicates that the optimal sampling intervals parallel to the texture direction were higher 10–20 times than that perpendicular to texture direction for anisotropic surfaces. In addition, to verify the validity of the recommended sampling intervals, three actual surfaces were machined using different abrasive grit burs and were measured using a non-contact confocal profiler with the optimal sampling intervals recommended. They demonstrate that the recommended optimal sampling intervals could be used as the sampling parameter selection guidance for 3D surface measurement and characterization.

Texture analysis of the microstructure of internal curing concrete based on image recognition technology

Mechanical properties of internal curing concrete are greatly affected by its physical properties such as water content, cementing material content, porosity, and saturation. At the micro- level, such impact is finally reflected in the surface texture of its materials. In this study, the image recognition technology was used to find that the internal curing concrete samples have significant micromorphology and texture features. A texture parameter–strength model was established based on the relationship between Tamura texture parameters, gray level co-occurrence matrix (GLCM) texture parameters, and the mechanical strength. Due to the sensitivity of material properties and parameters, in terms of Tamura texture characteristics, coarseness, regularity and directionality are effective parameters for predicting the compressive strength of internally curing concrete. In terms of the GLCM texture, energy, correlation, entropy, and contrast are effective parameters to predict the compressive strength of the internal curing concrete. Correlations between each texture parameter and compressive strength follow different laws.

A Superior High-Strength Dilute Mg-Bi-Ca Extrusion Alloy with a Bimodal Microstructure

Improving the mechanical properties of Mg alloys is of great significance for their wide application. A micro-alloyed Mg-1.45Bi-0.79Ca alloy (in wt.%) exhibiting a high tensile yield strength of 394 ± 5 MPa and a moderate elongation of 6.6 ± 0.6% was fabricated by single pass extrusion. The superior high strength is mainly attributed to the synergy effects of ultra-fine dynamic recrystallized grains; numerous Mg2Ca, Mg3Bi2, and Mg2Bi2Ca nano-precipitates; residual dislocations; sub-grain boundaries; as well as strong <10-10> fibre texture in the extrusion direction.

EFFECTS OF POINT GRINDING SURFACE TEXTURE ON CONTACT AND WEAR CHARACTERISTICS UNDER DRY SLIDING CONDITION

The main objective of this work is to study the effects of surface texture direction on contact and wear characteristics of point grinding parts under dry sliding contact. This study provided a method to obtain the surface with good contact characteristics and wear resistance under certain working conditions. The point grinding surface texture model, the contour support length model considering surface texture, and the fractal contact model of the cylindrical surface were built. The measuring experiment was carried out using TR300 roughness shape measuring instrument and the tribological experiment was carried out using HSR-2M high-speed reciprocating friction and wear tester. The results showed that the surface texture direction had an effect on the contour support length ratio, the contact and wear characteristics of parts. When the surface texture direction angle was 30∘, the average friction coefficient was the smallest, the supporting performance and wear resistance of parts were the best; for surfaces with 30∘ and 60∘ texture, the fluctuation of the friction coefficients was smaller, the wear uniformity was better; when the load was small, the abrasion loss of point grinding parts will decrease with increase in the direction angle of surface texture. The results can help to choose appropriate processing method and machining parameters to obtain appropriate surface.

Laser hexagonal texture on surface of Ti6Al4V for the improvement of fluid spreadability and tribological properties

The joint capsule removal after artificial joint replacement surgery have led to improper lubrication, causing the pair to wear out quickly and reducing the joint lifespan. In this paper, laser processing and chemical corrosion were used to prepare a hexagonal convex texture on the surface of titanium alloy (Ti6Al4V). After etching and laser polishing, SEM images indicated the presence of secondary micro-nano textures in the grooves around the hexagonal texture, and the formation of anatase oxides on the surface, resulting in an increase of the surface energy and a very small contact angle (CA). The surfaces’ CA increases with the texture ratio, and the surface is super-hydrophilic when the texture ratio is less than 0.84. Furthermore, the effect of texture parameters and directions are studied by using UHMWPE and Ti6Al4V as friction pairs and simulated body fluid as lubricant. The COF is 0.068 with 0.84 area ratio, which is 51.4% lower than the original surface. The wear rate of UHMWPE on the textured surface decreases by 74.5% after two hours of tribological testing. In addition, high speed camera images and calculation results proved that creating grooves can promote fluid distribution on the textured surface. The surface texture on titanium alloy results in a significant COF and wear reduction, extending the service life of artificial joints.

The Relationship Of The Land Physical Characteristic To The Productivity Of Potato (Solanum Tuberosum L.) At Karo Regency

The research aims to determine the relationship’s of the lands’s physical characteristic (temperature, soil texture, soil moisture, slope, and planting direction) to the productivity of potato (Solanum tuberosum L.) at Karo Regency. The research was started from June 2021 to August 2021. This research was conducted using a survey method at 5 sub-districts (Berastagi, Merdeka, Kabanjahe, Tigapanah, Simpangempat) at Karo Regency using Stratified random sampling with potato productivity (low-high productivity) as consideration. The results showed that the physical characteristic of land (temperature, soil texture, soil moisture, slope, and planting direction) simultaneously affected potato productivity, 51% of potato productivity were affected by the characteristics of the land. Partially: temperature, slope, and soil moisture affect the potato productivity. Temperature and slope were positively correlated with potato productivity.

Recognition of Protein Network for Bioinformatics Knowledge Analysis Using Support Vector Machine.

Protein is the material foundation of living things, and it directly takes part in and runs the process of living things itself. Predicting protein complexes helps us understand the structure and function of complexes, and it is an important foundation for studying how cells work. Genome-wide protein interaction (PPI) data is growing as high-throughput experiments become more common. The aim of this research is that it provides a dual-tree complex wavelet transform which is used to find out about the structure of proteins. It also identifies the secondary structure of protein network. Many computer-based methods for predicting protein complexes have also been developed in the field. Identifying the secondary structure of a protein is very important when you are studying protein characteristics and properties. This is how the protein sequence is added to the distance matrix. The scope of this research is that it can confidently predict certain protein complexes rapidly, which compensates for shortcomings in biological research. The three-dimensional coordinates of C atom are used to do this. According to the texture information in the distance matrix, the matrix is broken down into four levels by the double-tree complex wavelet transform because it has four levels. The subband energy and standard deviation in different directions are taken, and then, the two-dimensional feature vector is used to show the secondary structure features of the protein in a way that is easy to understand. Then, the KNN and SVM classifiers are used to classify the features that were found. Experiments show that a new feature called a dual-tree complex wavelet can improve the texture granularity and directionality of the traditional feature extraction method, which is called secondary structure.

Phonon-assisted phase separation in strongly correlated systems

We relate the phase separation observed in many crystals with pronounced electron correlations to the regions of negative electron compressibility (NEC). They were found in several models describing strong electron correlations. At low temperatures, these regions arise near chemical potentials corresponding to the change of the ground state in the site Hamiltonian. The NEC leads to the separation of the system into electron-rich and electron-poor domains. The energy released in the course of this separation is absorbed by phonons. Another role of phonons is to give a definite form — stripes or checkerboards — to lattice distortions and domains of different electron concentrations. The shape, direction and periodicity of such textures are determined by wavevectors of lattice distortions, which most strongly scatter electrons.

Deformation mechanisms of selective laser melted 316L austenitic stainless steel in high temperature low cycle fatigue

To investigate the low cycle fatigue (LCF) properties of SLM (Selective laser melting) 316L at 550 °C high temperature, a series of LCF tests at different strain amplitudes is conducted on SLM 316L and traditional 316L. In contrast to the cyclic hardening behavior of traditional 316L, SLM 316L is shown to have a stable cyclic softening behavior and higher fatigue life due to its higher strength (yield strength is 1.9 times of traditional 316L). The coarsening of cellular sub-structure, evolution of geometrically necessary dislocations (GND) and texture direction contribute to the cyclic softening behavior of SLM 316L. Fractographic observations illustrate that strain amplitude has a significant influence on initiation and propagation of transgranular fatigue cracks, and lack-of-fusion defects near the surface are key initiation sites of fatigue cracks. Additionally, the life prediction method of the non-Masing model is suitable for SLM 316L.

Three-Dimensional Nanoscale Morphological Surface Analysis of Polymeric Particles Containing Allium sativum Essential Oil.

Biodegradable particles were developed using poly-ε-caprolactone and gelatin carriers containing different concentrations of Allium sativum essential oil (EO) (360 µg/mL, 420 µg/mL, and 460 µg/mL). Atomic force microscopy was useful to evaluate the particles’ surface based on morphological parameters. The particles’ size varied from 150 nm to 300 nm. The diameter was related to the increase of the particles’ height as a function of the EO concentration, influencing the roughness of the surface core values (from 20 to 30 nm) and surface irregularity. The spatial parameters Str (texture aspect ratio) and Std (texture direction) revealed low spatial frequency components. The hybrid parameters Sdq (root mean square gradient) and Sdr (interfacial area ratio) also increased as a function of the EO concentration, revealing fewer flat particles. On the other hand, the functional parameters (inverse areal material ratio and peak extreme height) suggested differences in surface irregularities. Higher concentrations of EO resulted in greater microtexture asperity on the particles’ surface, as well as sharper peaks. The nanoscale morphological surface analysis allowed the determination of the most appropriate concentration of encapsulated EO, influencing statistical surface parameters.

Low-pressure CVD of (Tix,W1-x)Ny from WF6, TiCl4 and NH3

In this work chemical vapour deposited (CVD) coatings of (Tix,W1-x)Ny from TiCl4, WF6, NH3 and Ar were investigated. This coating material has previously been deposited using other vacuum techniques but no publication has so far demonstrated CVD of (Tix,W1-x)Ny. The studied (Tix,W1-x)Ny coatings had a metallic molar ratio (Ti:W) close to 2:1 and 1:1, and were slightly over-stoichiometric with regard to N. The coatings appeared homogeneous and crystallised in a rock salt structure on an α-Al2O3 substrate. The cell parameter varied between 4.16 and 4.23 Å as a function of the deposition conditions, ranging from a pure TiNx to a pure WNx coating. The texture in the normal direction was 〈100〉 for the TiNx and (Tix,W1-x)Ny coatings and 〈111〉 for WNx. Electron backscattered diffraction (EBSD) results showed that a strong correlation to the substrate existed but random in-plane orientation was also present. The microstructure showed columnar grains with well defined facets growing. Adding a mixture of TiCl4 and WF6 to produce (Tix,W1-x)Ny did increase the grain size significantly when compared to the case when only one metal precursor was present. The down-stream thickness profile, using only WF6 and NH3, displayed mass transport control behaviour, with the coating thickness converging to zero within the deposition zone. Using only TiCl4 on the other hand showed a uniform deposition profile, the signs of a surface kinetics controlled process.

Adaptive Despeckling and Heart Disease Diagnosis by Echocardiogram using Optimized Deep Learning Model

ABSTRACT Echocardiography is a significant diagnostic tool intended to interpret and identify different categories of heart diseases. The classification of heart condition by utilising the CAD on echocardiogram is an essential and primary step, which should be performed in a precise manner. This process aims to achieve a strong differentiation among abnormal and normal heart conditions through machine learning algorithms. As the heart disease diagnosis using echocardiography is still a complex process, it can be adopted with different deep learning approaches for identification. For solving these issues, this paper develops a novel heart disease diagnosis using echocardiogram images and video frames. As speckle noise is the main problem in echocardiogram images, noise reduction is the initial phase of the process. This is performed by the adaptive speckle-noise reduction technique. Then, the hybrid pattern extraction is adopted using two well-performing techniques termed local binary pattern and local directional texture pattern. This extracted hybrid pattern is subjected to the optimised Convolutional Neural Network (CNN). Here, optimised CNN is accomplished by the distance-based cat swarm optimisation for enhancing the diagnosis accuracy of heart disease. Finally, the proposed work shows the efficiency of the developed echocardiogram-based CAD heart disease diagnosis system by conducting the experiments.

Enhancing mechanical properties of metallic materials by architecting gradient structures

Here, two types of gradient structures (GS), i.e. gradient dislocation structure (GDS) and gradient grain structure (GGS) are successfully constructed . Results indicate that the relationship between the strength and ductility of the samples with GDS and GGS is referred to as an inverse linear rule, which is in stark contrast to and superior to the banana-shaped strength-ductility trade-off dilemma in monolithic materials. In low-strength (σy ∼400–550 MPa) range, plausible strength-ductility-toughness synergies can be achieved by both the GDS and GGS, however, in high-strength (σy ∼550–750 MPa) range, much better strength-ductility-toughness combinations are presented by the GGS than those by the GDS. For the GGS, the formation of strong 〈110〉 fibre texture in the tensile direction is beneficial for enhancing the high strength-ductility-toughness synergy.

On the preferred orientation in Ti1–x Al x N and Ti1–x–y Al x Si y N thin films

Abstract The influence of the deposition geometry and the chemical composition on the form and degree of the preferred orientation of crystallites was investigated in TiN, Ti1–x Al x N, and Ti1–x–y Al x Si y N thin films deposited by cathodic arc evaporation. The deposition geometry was varied by changing the angle between the cathodes and the substrates. The chemical composition of the thin films was modified by the choice of the cathodic materials. In TiN thin films, the crystallites were preferentially oriented with the {111} direction perpendicular to the sample surface, independent of the deposition geometry. Besides, a well-pronounced in-plane texture was observed. Co-deposition of Ti, Al, and Si in nitrogen atmosphere stimulated inclination of the texture direction towards the sample surface, which can be described as a change of the texture direction related to the sample surface perpendicular direction, and reduced the amount of the in-plane texture in the coatings (the preferred orientation of crystallites in the plane of the coating).

Microstructure and properties of β-TCP / Zn - 1Mg composites processed by hot extrusion combination of multi-pass ECAP

To further improve the comprehensive service performance of Zn, hot extrusion combined multi-pass equal channel angular pressing route were applied to process Zn-1(wt%)Mg alloy and 1(vol%)β-TCP/Zn-1Mg composites. As-cast cylinders specimens with a diameter of 60 mm were finally processed to the ECAP-processed specimens with the dimensions of 15 mm × 15 mm × 120 mm. The evolution and corresponding mechanism of the microstructure, mechanical properties, corrosion behavior, and biocompatibility of 1β-TCP/Zn-1Mg composites and Zn-1Mg components were systematically investigated. As a result, compared with Zn-1Mg alloy, the grain refinement effect of ECAP was enhanced in the 1β-TCP/Zn-1Mg composites with exact the same ECAP conditions. Among all the experimental specimens, the minimum average grain size of 3.0 ± 0.3 µm was achieved in 1β-TCP/Zn-1Mg composites processed by 8 ECAP passes. With the increase of ECAP processing times, the texture strength increased, and the texture direction changed to be (0 0 0 1) base plane parallel to TD-axis. Consequently, the 1β-TCP/Zn-1Mg composites after 8 passes of the ECAP process exhibited the highest compressive yield strength (CYS) of 288.05 ± 6.87 MPa and an elongation greater than 50%. Moreover, these composites also showed a moderate degradation rate of 0.04496 mm·y−1 in the simulated body fluid solution. The in vitro cytotoxicity and cytocompatibility evaluation revealed that both ECAP-processed Zn-1Mg alloy and 1β-TCP/Zn-1Mg composites showed non-cytotoxicity to MC3T3-E1 cells, and the addition of β-TCP could improve the biocompatibility of the experimental materials. Above all, the combination of hot extrusion and ECAP should be a useful route to obtain biodegradable Zn-based materials with excellent comprehensive service performance as orthopedic implants. The 1β-TCP/Zn-1Mg composites, which were processed by hot extrusion and subsequent 8 passes ECAP, exhibited the highest CYS, moderate degradation rate, and good biocompatibility, should be a promising candidate for the application of bone repair and bone replacement.