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We address the problems of causal structure inference from conditional independence facts when latent confounders are admitted. The conditions that allow one to identify latent confounders and fully or partially recognize causal links are described. The updated implicative rules for orienting edges under confounding are suggested. We propose several new rules that are able to reveal bows and confounded causal edges. The rules rely on facts of absence of certain authentic edges (edge absence may be implied by Verma constraint or given in input as a priori requirement). [ABSTRACT FROM AUTHOR]

We address the problems of causal structure reconstruction given conditional independence facts when latent confounders are allowed. We examine the conditions that allow one to partially or fully identify authentic causal links and latent confounders. The updated implicative rules for orienting edges under confounding are suggested. As demonstrated, it is possible to construct the new rules, which can reveal confounded causal edges and bows. The rules rely on facts of the absence of certain authentic edges (such facts may be justified by non-independence constraints, like Verma constraint, or subject-based requirements). [ABSTRACT FROM AUTHOR]

Detecting changes in multisource heterogeneous images is a great challenge for unsupervised change detection methods. Image-translation-based methods, which transform two images to be homogeneous for comparison, have become a mainstream approach. However, most of them primarily rely on information from unchanged regions, resulting in networks that cannot fully capture the connection between two heterogeneous representations. Moreover, the lack of a priori information and sufficient training data makes the training vulnerable to the interference of changed pixels. In this paper, we propose an edge-oriented generative adversarial network (EO-GAN) for change detection that indirectly translates images using edge information, which serves as a core and stable link between heterogeneous representations. The EO-GAN is composed of an edge extraction network and a reconstructive network. During the training process, we ensure that the edges extracted from heterogeneous images are as similar as possible through supplemented data based on superpixel segmentation. Experimental results on both heterogeneous and homogeneous datasets demonstrate the effectiveness of our proposed method. [ABSTRACT FROM AUTHOR]

Context: Habitat edges are integral features of conservation corridors and can influence corridor function and effectiveness. Edge orientation is linked to corridor design and can shape edge responses by changing habitat conditions along edges as well as contrast between conserved habitats and transformed areas. Objectives: We assess whether corridor orientation affects butterfly assemblages in conservation corridors. To do this, we investigate how edge orientation influences butterfly diversity and abundance along forestry plantation edges, and compare this to another important design variable, corridor width. Methods: Butterflies were recorded along the sunny austral north- and shady austral south-orientated edges in grassland conservation corridors that dissect forestry plantations, as well as corridor interior sites. Species richness, abundance and similarity to interior sites were modelled using local habitat variables (ambient temperature, floral resources, and time of day), as well as corridor design variables (corridor width, orientation and an estimate of edge contrast influenced by orientation). Results: Both edge orientation and corridor width were important for butterfly diversity along corridor edges. Wider corridors enhanced overall species richness and promoted similarity between edge and interior habitats. Concurrently, grassland specialist species preferred the sunnier edges (i.e., north facing in the southern hemisphere) while forest- specialists showed a preference for the shadier edges (south facing edges). Edge orientation influenced resident butterflies more strongly than transient butterflies and influenced specialists more strongly than generalists. Conclusions: Corridor orientation and width are complementary design variables for butterfly conservation. Wide corridors at a variety of orientations benefit different subsets of the butterfly assemblage, and the whole corridor (including both edges) is important to consider in conservation planning to capture all biodiversity. [ABSTRACT FROM AUTHOR]

1. Geographical orientation affects the magnitude of microclimatic edge effects, mainly by altering the exposure to solar radiation. There is considerable evidence available concerning the influence of microclimatic edge effects on organisms at the population level, although little is known about effects at the community level, and variations with edge geographical orientation have barely been addressed. The present study investigated the influence of microclimatic conditions at the forest interior and edges with different geographical orientation on plant–leafminer–parasitoid food webs in the fragmented Chaco Serrano forest located in Central Argentina. 2. Microclimatic variables were measured in three locations: interior, north, and south‐facing edges of six forest fragments. In each location, plant resource availability was assessed and mined leaves were collected to investigate plant–leafminer–parasitoid communities by rearing leafminer and parasitoid adults. 3. The results obtained revealed changes in the specific composition of plant, leafminer and parasitoid communities among locations, although they failed to detect location influences on most variables linked to abundance (except for leafminers), richness or food web structure. Leafminer abundance was negatively related to temperature, whereas their richness was related, also negatively, to moisture. Instead, parasitoids were favoured by higher temperatures and light levels, stronger winds, and lower humidity. 4. The results of the present study indicate that the effects of microclimatic conditions may depend on the trophic level considered. Moreover, the findings suggest that possible trade‐offs between direct and indirect effects (such as plant quality, floral resources, etc.) of microclimatic conditions could influence plant and insect responses to location. [ABSTRACT FROM AUTHOR]

The perfect image retrieval and retrieval time are the two major challenges in CBIR systems. To improve the retrieval accuracy, the whole database is searched based on many image characteristics such as color, shape, texture and edge information which leads to more time consumption. This paper presents a new fuzzy based CBIR method, which utilizes colour, shape and texture attributes of the image. Fuzzy rule based system is developed by combining color, shape, and texture feature for enhanced image recovery. In this approach, DWT is used to pull out the texture characteristics and the region based moment invariant is utilized to pull out the shape features of an image. Color similarity and texture attributes are extorted using customized Color Difference Histogram (CDH). The performance evaluation based on precision and BEP measures reveals the superiority of the proposed method over renowned obtainable approaches. [ABSTRACT FROM AUTHOR]

Abstract Silicene nanoribbon is a one-dimensional structure of monolayer silicon atoms that its energy gap depends on the edge shape and the width of the ribbon. In this paper, we design a Silicene nanoribbon field effect transistor (SiNRFET) based on different ribbon widths and then we compare this structure with a graphene nanoribbon field effect transistor (GNRFET). For this purpose, we study the effect of the parameters such as ribbon length and the number of atoms along the ribbon width. Moreover, we investigate effect of the perpendicular electric field on the I on /I off and transfer characteristics of both structures and compare the performance of these transistors. Finally, we derive the output characteristics of SiNRFET and GNRFET as a function of gate voltage and compare them together. The method that we use in this research is the transfer matrix. The electron wave functions are derived in each region of both transistors in order to obtain the current. [ABSTRACT FROM AUTHOR]

Abstract Purpose To propose and evaluate a new calibrationless parallel imaging method aimed at further improving the reconstruction accuracy of the accelerated multi-channel MR images. Method We introduce a new calibrationless parallel imaging method. On top of exploiting joint sparsity cross channels of the target image to be reconstructed, it incorporates similar priors on the grey-level intensity and edge orientation, which both come from a high-spatial resolution reference image that can be easily obtained in many clinical MRI scenarios. The mixed l 2 - l 1 norm is used to enforce joint sparsity and a multi-scale gradient operator is applied to extract fine edges from the reference image. Additionally, this optimization problem can be solved via a non-linear conjugate gradient algorithm with line search in this work. Results The proposed method is compared with the existing state-of-the-art auto-calibration and calibrationless parallel imaging techniques. The experiments on different in-vivo brain MR datasets show that the proposed method has the superior performance in terms of both artifact suppression and detail preservation. Conclusion The reference guided calibrationless parallel imaging method can significantly improve the performance of joint reconstruction of target channel images. Even when the reduction factor is high, it can keep edge structures well. [ABSTRACT FROM AUTHOR]

We study an edge coloring problem in multigraphs, in which each node incurs a cost equal to the number of appearances of the most frequent color among those received by its incident edges. We seek an edge coloring with a given number w of colors, that minimizes the total cost incurred by the nodes of the multigraph. We consider a class of approximation algorithms for this problem, which are based on orienting the edges of the multigraph, then grouping appropriately the incoming and outgoing edges at each node so as to construct a bipartite multigraph of maximum degree w , and finally obtaining a proper edge coloring of this bipartite multigraph. As shown by Nomikos et al. (2001), simply choosing an arbitrary edge orientation in the first step yields a 2-approximation algorithm. We investigate whether this approximation ratio can be improved by a more careful choice of the edge orientation in the first step. We prove that, assuming a worst-case bipartite edge coloring, this is not possible in the asymptotic sense, as there exists a family of instances in which any orientation gives a solution with cost at least 2 − Θ ( 1 w ) times the optimal. On the positive side, we show how to produce an orientation which results in a solution with cost within a factor of 2 − 1 2 w of the optimal, thus yielding an approximation ratio strictly better than 2. This improvement is important in view of the fact that this graph-theoretic problem models, among others, wavelength assignment to communication requests in multifiber optical star networks. In this context, the parameter w corresponds to the number of available wavelengths per fiber, which is limited in practice due to technological constraints. [ABSTRACT FROM AUTHOR]

This paper presents a robust lane detection technique for roads on hilly terrain. The target of this paper is to utilize image processing strategies to recognize lane lines on structured mountain roads with the help of improved Hough transform. Vision-based approach is used as it performs well in a wide assortment of circumstances by abstracting valuable information contrasted with other sensors. The proposed strategy processes the live video stream, which is a progression of pictures, and concentrates on the position of lane markings in the wake of sending the edges through different channels and legitimate thresholding. The algorithm is tuned for Indian mountainous curved and paved roads. A technique of computation is utilized to discard the disturbing lines other than the credible lane lines and show just the required prevailing lane lines. This technique will consequently discover two lane lines that are nearest to the vehicle in a picture as right on time as could reasonably be expected. Various video sequences on hilly terrain are tested to verify the effectiveness of our method, and it has shown good performance with a detection accuracy of 91.89%. [ABSTRACT FROM AUTHOR]

This work demonstrates a method to directly determine edge orientations of three-fold symmetric two-dimensional crystals in real space, without resolving the edge structure. In an annular dark-field scanning transmission electron microscope, the orientation of an edge is derived from the overall edge direction recorded at a low magnification and the crystal orientation revealed by atomic resolution, element-contrast imaging at a high magnification. By applying this method, the edge orientation of equilateral triangle-shaped hexagonal boron nitride (h-BN) crystals grown by chemical vapor deposition on Cu is experimentally determined for the first time. The experimentally determined nitrogen-terminated zigzag edges validate the kinetic theory of h-BN crystal growth, which is a useful case study of the growth of 2D crystals lacking inversion symmetry. [ABSTRACT FROM AUTHOR]

For improving the speed of object detection,this paper proposed an object detection method by using edge. First,it computed the edge magnitude and orientation for every pixel in the image, located the edge position according to magnitude, and divided the edges into different groups according to edge position and orientation. Second, it voted for candidate bounding box by computing the similarity among edge groups. Finally, it calculated the voting scores of each candidate bounding box among multi-scale sliding windows, filterd the bounding boxes according to their scores, combined them according to their overlap ratio, distinguished an object according the number of combined bounding boxes, and obtained each object's bounding box in the image. Experimental results show that, comparing with main methods based on bounding box, this method has the higher computation efficiency, and the recall ratio and precision are high. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel hierarchical framework that combines motion and feature information to implement infrared-visible video registration on nearly planar scenes. In contrast to previous approaches, which involve the direct use of feature matching to find the global homography, the framework adds coarse registration based on the motion vectors of targets to estimate scale and rotation prior to matching. In precise registration based on keypoint matching, the scale and rotation are used in re-location to eliminate their impact on targets and keypoints. To strictly match the keypoints, first, we improve the quality of keypoint matching by using normalized location descriptors and descriptors generated by the histogram of edge orientation. Second, we remove most mismatches by counting the matching directions of correspondences. We tested our framework on a public dataset, where our proposed framework outperformed two recently-proposed state-of-the-art global registration methods in almost all tested videos. [ABSTRACT FROM AUTHOR]

The availability and affordability of handheld smart devices have made life easier by enabling us to do work on the go. Their widespread use brings with it concerns relating to data security and privacy. The rising demand to secure private and highly confidential data found on smart devices has motivated researchers to devise means for ensuring privacy and security at all times. This kind of continuous user authentication scheme would add an additional layer of much needed security to smart devices. In this context, touch screen interactions have recently been studied as an effective modality to perform active user authentication on mobile devices. In this paper, a visual analysis based active authentication framework has been presented. Considering the touch screen as a canvas, interaction trace maps are constructed as a result of user interactions within various applications. The user touch gestures are captured and represented as drawing strokes on the canvas. The behavioral and physiological characteristics of users are modeled as signatures by combining texture and shape features from the interaction trace maps. A two-step mechanism with support vector machines exploit this signature to perform active user authentication. Experiments conducted with various datasets show that the proposed framework compares favorably with other state-of-the-art methods. [ABSTRACT FROM AUTHOR]