Edge Strength Research Articles

48‐3: Edge Strength Measurement of Ultra‐Thin LCD Panels

The feasibility of using Corning's edge strength measurement system (ESMS) for ultra‐thin LCD panels has been demonstrated. Panels were used to validate the load‐to‐stress correlation: digital image correlation, finite element analysis and mirror radius measurement all showed good agreement, supporting the robustness of the strength measurement. The edge strength of panels was measured by both static and dynamic ESMS. Test results revealed that dynamic ESMS is advantaged over static in better capturing the relevant flaw population owing to its larger test area. Accurate edge strength measurement via ESMS coupled with selective fracture analysis on the weakest flaws will assist in improving the edge strength of ultra‐thin LCD panels

Quantifying the Reliability and Replicability of Psychopathology Network Characteristics

Pairwise Markov random field networks—including Gaussian graphical models (GGMs) and Ising models—have become the “state-of-the-art” method for psychopathology network analyses. Recent research has focused on the reliability and replicability of these networks. In the present study, we compared the existing suite of methods for maximizing and quantifying the stability and consistency of PMRF networks (i.e., lasso regularization, plus the bootnet and NetworkComparisonTest packages in R) with a set of metrics for directly comparing the detailed network characteristics interpreted in the literature (e.g., the presence, absence, sign, and strength of each individual edge). We compared GGMs of depression and anxiety symptoms in two waves of data from an observational study (n = 403) and reanalyzed four posttraumatic stress disorder GGMs from a recent study of network replicability. Taken on face value, the existing suite of methods indicated that overall the network edges were stable, interpretable, and consistent between networks, but the direct metrics of replication indicated that this was not the case (e.g., 39–49% of the edges in each network were unreplicated across the pairwise comparisons). We discuss reasons for these apparently contradictory results (e.g., relying on global summary statistics versus examining the detailed characteristics interpreted in the literature) and conclude that the limited reliability of the detailed characteristics of networks observed here is likely to be common in practice, but overlooked by current methods. Poor replicability underpins our concern surrounding the use of these methods, given that generalizable conclusions are fundamental to the utility of their results.

Toward "plug and play" prospective motion correction for MRI by combining observations of the time varying gradient and static vector fields.

The efficacy of a Wireless Radio frequency triggered Acquisition Device (WRAD) is evaluated for high frequency (50 Hz) prospective motion correction in a 3-dimensional spoiled gradient echo pulse sequence. The device measures the rate of change in the gradient vector fields (slew) using a 3-dimensional assembly of Printed Circuit Board (PCB) inductors and the direction of the static magnetic field using a 3-axis Hall effect magnetometer. The slew vector encoding is highly efficient, because the Maxwell-term position encoding is observable, allowing overconstrained pose measurement using 3 sinusoidal gradient pulses lasting 880 μs. Since small offsets in the magnetometer can introduce bias into the pose estimates, sensor/system biases are tracked using a lightweight Kalman filter. The only calibration required is determining a geometric scaling factor for the pickup coils, which is specific to the device and will therefore be valid in any scanner. The device was used to perform prospective motion correction in 3 subjects, resulting in an increase in Average Edge Strength (AES) for involuntary and deliberate motion. The WRAD is simple to set up and use, with well-defined measurement variance. This could enable "plug and play" prospective motion correction if pulse sequence independence is achieved.

Effects of cooling and lubrication conditions on tool wear in turning of Al/SiCp composite

Al/SiCp composites machining is considerably difficult, owing to the presence of hard particles that result in severe tool wear. The application of different cooling and lubrication methods can offer a favorable change in the tool used in machining of Al/SiCp composites. To study the effects of different cooling and lubrication conditions on the tool wear in the machining of Al/SiCp composites, turning experiments under dry, liquid nitrogen (LN2), minimum quantity lubrication (MQL), cutting oil (Oil), and emulsion environments were conducted, and the mechanisms of tool wear with respect to boundary wear, major flank wear, adhesive wear, and tool breakage were discussed. The results indicate that the MQL and LN2, which exhibit excellent flushing performance, could wash away the chips and SiC particles from the boundary zones of the minor flanks, thus reducing the boundary wear. However, the use of Oil and emulsion promoted the formation of an abrasive slurry that enhanced the three-body abrasion at the boundary zones. In addition, the MQL and LN2, which show excellent lubricating and cooling properties, promoted the reduction of the major flank wear. The formation of worn pits and built up edge(s) (BUE) on the rake faces confirmed the presence of adhesive wear in the turning of the Al/SiCp composite using polycrystalline diamond (PCD) tools, and the cooling effect of MQL and LN2 could not prevent the workpiece material from accumulating in the worn pits and giving rise to the BUE. When turning Al/SiCp composites under LN2 and Oil conditions, the tool breakage was accelerated. The application of LN2 increased the thermal impact and the scratch effect of the SiC particles on the tool faces, aggravating the tool breakage. The rapid tool breakage caused by Oil cutting could be attributed to the reduction of the cutting edge strength that bore the alternating load and thermal impact. Therefore, it is concluded that the use of MQL, which assists in reducing the boundary wear, tool breakage, and major flank wear, is suitable as the preferred cooling and lubrication mode in the turning of Al/SiCp composites.

Comparison of anterior capsulotomy techniques: continuous curvilinear capsulorhexis, femtosecond laser-assisted capsulotomy and selective laser capsulotomy

PurposeTo compare the anterior capsulotomy edge tear strength created by manual continuous curvilinear capsulorhexis (CCC), femtosecond laser-assisted capsulotomy (FLACS), and selective laser capsulotomy (SLC).SettingSingapore National Eye Centre, Singapore and Excel-Lens,...

A network approach to prioritizing susceptibility genes for genome-wide association studies.

The heritability of complex diseases including cancer is often attributed to multiple interacting genetic alterations. Such a non-linear, non-additive gene-gene interaction effect, that is, epistasis, renders univariable analysis methods ineffective for genome-wide association studies. In recent years, network science has seen increasing applications in modeling epistasis to characterize the complex relationships between a large number of genetic variations and the phenotypic outcome. In this study, by constructing a statistical epistasis network of colorectal cancer (CRC), we proposed to use multiple network measures to prioritize genes that influence the disease risk of CRC through synergistic interaction effects. We computed and analyzed several global and local properties of the large CRC epistasis network. We utilized topological properties of network vertices such as the edge strength, vertex centrality, and occurrence at different graphlets to identify genes that may be of potential biological relevance to CRC. We found 512 top-ranked single-nucleotide polymorphisms, among which COL22A1, RGS7, WWOX, and CELF2 were the four susceptibility genes prioritized by all described metrics as the most influential on CRC.

A Coarse-to-Fine Registration Strategy for Multi-Sensor Images with Large Resolution Differences

Automatic image registration for multi-sensors has always been an important task for remote sensing applications. However, registration for images with large resolution differences has not been fully considered. A coarse-to-fine registration strategy for images with large differences in resolution is presented. The strategy consists of three phases. First, the feature-base registration method is applied on the resampled sensed image and the reference image. Edge point features acquired from the edge strength map (ESM) of the images are used to pre-register two images quickly and robustly. Second, normalized mutual information-based registration is applied on the two images for more accurate transformation parameters. Third, the final transform parameters are acquired through direct registration between the original high- and low-resolution images. Ant colony optimization (ACO) for continuous domain is adopted to optimize the similarity metrics throughout the three phases. The proposed method has been tested on image pairs with different resolution ratios from different sensors, including satellite and aerial sensors. Control points (CPs) extracted from the images are used to calculate the registration accuracy of the proposed method and other state-of-the-art methods. The feature-based preregistration validation experiment shows that the proposed method effectively narrows the value range of registration parameters. The registration results indicate that the proposed method performs the best and achieves sub-pixel registration accuracy of images with resolution differences from 1 to 50 times.

A simple synthesis route for preparation and optical properties of PMMA-g-ZnO nanocomposites through surface-initiated radical polymerization

An effortless chemisorption access for the planning of nanocomposites containing a semiconductor ZnO nanoparticles and poly(methyl methacrylate) (PMMA) is demonstrated. First, thiol-functionalized ZnO (ZnO-SH) were prepared by a silanization reaction between ZnO nanoparticles and (3-mercaptopropyl) trimethoxysilane. Then, a reserved radical polymerization of methyl methacrylate in the attendance of Zinc oxide-thiol (ZnO-SH) and butyrolactam produced PMMA-g-ZnO nanocomposites. DSC were used to examine the weight decline of glass transition temperature of nanocomposites. The ocular characteristics of the nanocomposites were studied by Ultraviolet-visible (UV–vis) absorption spectroscopy and photoluminescence spectroscopy (PL). The results accentuate the role of the grafted PMMA polymer segments in augmenting the strength of dispersal and near-band edge (NBE) emission of ZnO nanoparticles.

Rearview Camera-Based Stixel Generation for Backing Crash Prevention

Backing crashes have become a serious problem, resulting in the United States announcing a rule requiring all vehicles to come equipped with rearview cameras. As a result of this situation, this paper proposes a method that detects obstacles behind a vehicle using a rearview camera with a fisheye lens. The proposed method represents obstacles by means of the Stixel World, and it consists of two stages: free space boundary detection and obstacle height estimation. In the first stage, obstacles are three-dimensionally reconstructed, and the 3D points are spatially interpolated and sequentially accumulated. An occupancy grid map is generated with depth and incidence angle axes to effectively handle a wide field-of-view situation. In the second stage, this method combines some complementary information to reliably estimate the obstacle height using spare 3D points. Three cost maps based on 3D points, color similarity, and edge strength are calculated and fused in height and incidence angle axes. The free space boundary and the obstacle height are estimated by finding the optimal paths in the occupancy grid map and the fused cost map, respectively. Finally, Stixels are generated by integrating the free space boundary and obstacle height. In the experiment, the proposed method was quantitatively evaluated and compared with the previous methods in various road, obstacle, and background conditions.

Effects of machine stiffness and cutting tool design on the surface quality and flexural strength of edge trimmed carbon fibre reinforced polymers

A 22 full factorial design of experiment is used to investigate the effects of two machining platforms (5-axis elevated gantry versus 6-axis articulated robotic system) and two cutting tool designs (burr versus herringbone) on surface metrics and flexural strength of a 14 ply T300 2 × 2 carbon fibre reinforced polymer.A range of areal metrics are considered to characterise the surface with Sal and Stdi best able to represent differences due to the choice of robotic system or overhead gantry. The robotic system produces coupons with flexural strengths up to 26% higher than the overhead gantry. The choice of tool has a less significant effect however machine-tool interactions do play a role in the flexural strength.Analysis using scanning electron microscopy shows that defects may be obscured by smeared matrix which may contribute to overall flexural strength differences.

Multiscale fusion of multimodal medical images using lifting scheme based biorthogonal wavelet transform

Medical image fusion has been used to improve useful and relevant information (e.g., precise localization of abnormalities) of multimodal medical images, such as computed tomography (CT), magnetic resonance imaging (MRI) and positron emission tomography (PET) images, and the information obtained from the fused images can then be utilized as an assistive tool for better diagnosis and treatment. In this work, we propose an algorithm for fusing multimodal medical images using lifting scheme-based biorthogonal wavelet transform. The multiscale fusion scheme is performed for the multimodal medical images in the wavelet domain at multiple scales by adopting either average or absolute maximum fusion rules. To verify the effectiveness of the proposed method, a series of visual and quantitative performance evaluations of the proposed method are compared with those of five representative wavelet-based fusion methods including contourlet transform (CLT), nonsubsampled CLT (NSCLT), lifting wavelet transform (LWT), multiwavelet transform (MWT), and stationary wavelet transform (SWT). For the quantitative performance evaluations, we adopted five metrics: fusion factor, fusion symmetry, entropy, standard deviation and edge strength. The experimental results demonstrated that the proposed method could yield better results than other wavelet transform-based fusion methods. Furthermore, from the additional comparison study of fusing noise-contaminated images, we could conclude that the proposed method is noise resilient in fusing images corrupted by Gaussian and speckle noise with varying variances.

Fatigue strength of thermal cut edges—influence of ISO 9013 quality groups

The use of high strength steels has gained importance due to the interest in effective light steel constructions. Besides the well-designed weld seams, free cutting edges gain technical and economic relevance as locations for potential fatigue cracks. In this investigation, fatigue tests were carried out on 8-mm- and 20-mm-thick samples with a minimum yield strength ranging from 355 to 960 MPa at a stress ratio of R = 0.1. The cutting methods used were oxygen, plasma, and laser cutting. The surface roughness, hardness profile, and residual stresses were measured to classify the specimens into quality groups according to ISO 9013. Most of the specimens are classified in the quality groups 2 and 3. A slight tendency can be seen that the fatigue strength decreases with an increasing roughness value. Increasing local hardness values at the cut edges also have a minor negative influence on the fatigue strength. No positive impact was observed for increasing tensile strength on the fatigue strength. With higher surface roughness values, larger notches exist, the crack initiation starts early, and the fatigue strength decreases.

Overlapping Community Detection Algorithm Based on Edge Strength

Communities represent an ubiquitous topological characteristic of complex networks, and discovering community structures is of fundamental importance. Conductance is a detection algorithm for weighted overlapping communities with high-accuracy division results; however, the relationship between the nodes and their neighbors is not considered in the selection of the initial community, which leads to unreasonable initial community selection and lower accuracy in discovering the real community structure of the network. In addition, the algorithm may miss nodes. Accordingly, the edge strength conductance algorithm (ESCA) is proposed, which resolves the issues of unreasonable initial community selection and missing nodes by using the concepts of edge strength and belonging degree. Experiments demonstrate that for both unweighted and weighted networks, ESCA does not miss nodes, and the detected communities are closer to the real network community structure compared with those obtained by Conductance and COPRA, the community overlap propagation algorithm.

SAR Image Segmentation Using Hierarchical Region Merging With Orientated Edge Strength Weighted Kuiper’s Distance

In this paper, a hierarchical region merging method is proposed for partitioning synthetic aperture radar (SAR) image into un-overlapping scene area, such as forest regions, urban regions, agricultural regions, and so on. The proposed method mainly consists of two steps: initial over-segmentation and hierarchical regions merging. The over-segmentation uses the watershed transform to the thresholded Bhattacharyya-coefficient-based edge strength map (BESM), and the hierarchical regions merging applies a new region merging cost weighted by a gradually increasing orientated edge strength penalty. There is a defect that the ratio-based edge detector widely used in homogeneous SAR image fails to distinguish the transitions between uniform and texture regions in high spatial resolution SAR image, and yields an initial over-segmentation result with some regions straddling multiple uniform or texture areas. To overcome this, the Bhattacharyya coefficient is used to replace the ratio-based edge detector for extracting the ESM of a SAR image by using a bi-rectangle-window configuration. Multi-scale windows are utilized to capture additional edge information. A new region merging cost is proposed based on the Kuiper’s distance, weighted by a new gradually increasing orientated edge strength penalty term. The hierarchical region merging criterion is obtained with the increasing of the strength of the edge penalty. The effectiveness of the proposed method is demonstrated by comparing it qualitatively and quantitatively with several state-of-the-art methods.

It’s not amalgam, it is white amalgam

IntroductionA new class of restorative GIC, named Zirconomer, with increased strength and durability has been developed. It shows strength of amalgam, so it is also called white amalgam. Inclusion of zirconia fillers reinforces the structural integrity of that material, imparts its outstanding posterior esthetics, completely eliminates mercury hazards, and also it is fluoride rich, especially in cases with high caries risk. It is an ideal requirement for restorative material it has a good color stability, a co-efficient of thermal expansion, biocompatibility similar to that of natural tooth, remarkable edge strength, excellent marginal seal, and the ability to adhere chemically to enamel and dentin. Glass ionomer cements are esthetically more pleasing than metallic restorations, on the contrary, their use in dentistry as a restorative material in stress-bearing areas is limited due to poor mechanical properties. New GIC formulations are being introduced every day with improved physical and mechanical properties. ObjectivesZirconomer compared to Amalgam restoration. Materials and methodsArticles found through Medline search; Pubmed, Scopus, Cochrane Library databases covering years starting from 2010 to 2018 were reviewed. Key search words “Zirconomer,” “zirconium oxide,” “non-metal restorations,” “ceramic oxides,” “veneering ceramic,” “zirconia reinforced glass ionomer cement,” “zirconiabased fixed dental prostheses” and silver amalgam were used. Both in-vivo and in-vitro studies into zirconia-based restoration behavior were included. ResultsZirconomer restorations are found to be best alternative now to both GICs with its other modifications as well as dental amalgam for teeth restorations. Some bacterial retention on final could be expected when used. ConclusionsZirconomer and its family restorations are recommended for restorations of deciduous or permanent teeth. Further in-vitro and in-vivo works are needed to confirm their remarkable behavior. Conflict of interestThe authors declared that there is no conflict of interest.

An Innovative Technique to Simplify and Improve Pattern Fabrication for Digital Somatoprosthesis

ABSTRACT Introduction Patterns for somatoprostheses are conventionally made of modeling wax. The rigidity, brittle nature, reduced edge strength, and susceptibility to distortion of this wax often leads to failure in achieving marginal thinning and desired aesthetics. Technique A technique for fabrication of digital somatoprosthetic wax patterns with thin accurate margin by incorporation of a vacuum-formed polyvinyl chloride (PVC) template is described. Results and Discussion The technique helps in overcoming limitations of an all-wax pattern and improves accuracy and aesthetics of outcomes. Conclusions Incorporation of a PVC template in a somatoprosthetic wax pattern is a valuable technique to achieve good aesthetics and accuracy with the prosthesis.

Blind Image Quality Evaluation of Stitched Image using Novel Hybrid Warping Technique

Image stitching is collection of sequential images captured at fixed camera center having considerable amount of overlap and produces aesthetically pleasing seamless panoramic view. But, practically it is very difficult to obtain clean and pristine stitched panoramic image of particular scene as such images are apparently distorted. In this paper, a novel Hybrid Warping technique is used that combine two global warps and one local warp and helps to refine image alignment stage. Our proposed method optimizes Homography Screening to rectify problem of perspective distortion and Edge Strength Similarity approach to quantify structural irregularities. The Blind Image Quality Evaluation models such as Blind Image Quality Index (BIQI), Blind/Reference-less Image Spatial QUality Evaluator (BRISQUE) and BLind Image Integrity Notator using DCT Statistics (BLIINDS-II) are employed to measure objective quality of stitched image. The experimental results showed that blind image quality score of proposed method is significantly better than latest existing methods.

Estimating network structure from unreliable measurements

Most empirical studies of networks assume that the network data we are given represent a complete and accurate picture of the nodes and edges in the system of interest, but in real-world situations this is rarely the case. More often the data only specify the network structure imperfectly -- like data in essentially every other area of empirical science, network data are prone to measurement error and noise. At the same time, the data may be richer than simple network measurements, incorporating multiple measurements, weights, lengths or strengths of edges, node or edge labels, or annotations of various kinds. Here we develop a general method for making estimates of network structure and properties using any form of network data, simple or complex, when the data are unreliable, and give example applications to a selection of social and biological networks.

Dynamic Functional Magnetic Resonance Imaging Connectivity Tensor Decomposition: A New Approach to Analyze and Interpret Dynamic Brain Connectivity.

There is a growing interest in using so-called dynamic functional connectivity, as the conventional static brain connectivity models are being questioned. Brain network analyses yield complex network data that are difficult to analyze and interpret. To deal with the complex structures, decomposition/factorization techniques that simplify the data are often used. For dynamic network analyses, data simplification is of even greater importance, as dynamic connectivity analyses result in a time series of complex networks. A new challenge that must be faced when using these decomposition/factorization techniques is how to interpret the resulting connectivity patterns. Connectivity patterns resulting from decomposition analyses are often visualized as networks in brain space, in the same way that pairwise correlation networks are visualized. This elevates the risk of conflating connections between nodes that represent correlations between nodes' time series with connections between nodes that result from decomposition analyses. Moreover, dynamic connectivity data may be represented with three-dimensional or four-dimensional (4D) tensors and decomposition results require unique interpretations. Thus, the primary goal of this article is to (1) address the issues that must be considered when interpreting the connectivity patterns from decomposition techniques and (2) show how the data structure and decomposition method interact to affect this interpretation. The outcome of our analyses is summarized as follows. (1) The edge strength in decomposition connectivity patterns represents complex relationships not pairwise interactions between the nodes. (2) The structure of the data significantly alters the connectivity patterns, for example, 4D data result in connectivity patterns with higher regional connections. (3) Orthogonal decomposition methods outperform in feature reduction applications, whereas nonorthogonal decomposition methods are better for mechanistic interpretation.

A customized nonlocal restoration schemes with adaptive strength of smoothening for magnetic resonance images

Nonlocal Means (NLM) filter is a nonlinear filter exclusively suitable for images comprising redundant patterns at spatially distinct locations, like Magnetic Resonance (MR) images. However, its performance heavily depends on the selection of one of its arbitrary operational parameters termed as smoothening strength (ξ). Improper selection of ξ may lead to over-blurring or partial denoising. An image adaptive algorithm, to determine the optimum value of ξ, meant for customizing the NLM for MR images is proposed. In the proposed scheme for initializing ξ, its value is increased in proportion to the standard deviation of noise σ^n, according to a linear model ξ=β σ^n. The optimum value of the arbitrary parameter β is identified through an iterative search, using a composite metric termed as Optimum Denoising Index (ODI), which objectively accounts for the noise suppression and edge preservation capability of the filter, as target function. Assuming the noise to be Gaussian distributed with zero mean, its standard deviation is computed using a ‘difference of Laplacian’ kernel. The techniques available in literature for the selection of β are (i) Coupe’s model with β derived out of minimum error sense, (ii) simple linear model ξ=βσ with empirically decided value β = 10 and global optimum of β modified locally in proportion to either (iii) local noise statistics or (iv) edge strength. ODI exhibited by the above techniques and the proposed iterative search are 0.3145 ± 0.0347, 0.2509 ± 0.0149, 0.1210 ± 0.0143, 0.1790 ± 0.0511 and 0.3678 ± 0.0022, respectively. Peak Signal to Noise Ratio (PSNR) between the denoised and the noise-free ground truth images exhibited by Kuwahara Filter, Total Variation (TV) Filter, Anisotropic Diffusion (AD) Filter, Bilateral Filter, SUSAN Filter and the proposed NLM Filter are 21.8739 ± 4.7310, 20.9596 ± 5.0518, 22.1553 ± 5.3369, 22.2142 ± 5.1275, 28.5628 ± 0.02 and 28.9967 ± 0.13, on 30 standard images. The iterative search is superior to methods available in literature with regard to the sharpness of the true morphological edges and smoothness of the homogenous regions in the denoised image. The proposed scheme of NLM is found to be superior to Kuwahara, TV, AD, Bilateral and SUSAN Filters.