Precision weak gravitational lensing experiments require measurements of galaxy shapes accurate to <1 part in 1000. We investigate measurement biases, noted by Voigt & Bridle and Melchior et al., ...that are common to shape measurement methodologies that rely upon fitting elliptical-isophote galaxy models to observed data. The first bias arises when the true galaxy shapes do not match the models being fit. We show that this ‘underfitting bias’ is due, at root, to these methods' attempts to use information at high spatial frequencies that have been destroyed by the convolution with the point spread function (PSF) and/or by sampling. We propose a new shape-measurement technique that is explicitly confined to observable regions of k-space. A second bias arises for galaxies whose ellipticity varies with radius. For most shape-measurement methods, such galaxies are subject to ‘ellipticity gradient bias’. We show how to reduce such biases by factors of 20–100 within the new shape-measurement method. The resulting shear estimator has multiplicative errors <1 part in 103 for high signal-to-noise ratio images, even for highly asymmetric galaxies. Without any training or recalibration, the new method obtains Q= 3000 in the GREAT08 Challenge of blind shear reconstruction on low-noise galaxies, several times better than any previous method.
•Camera silhouette measurement system is suitable for inspecting heavy forgings.•System accuracy is not critically influenced by the industrial environment.•The subpixel edge detection method helps ...achieve a better accuracy.•Weighted contour filtering using edge quality measures supresses edge disturbances.
In this study, a new passive camera system for heavy cylindrical forging measurement, based on silhouettes in images, is developed. New methods for making such a system more resistant to the negative effects of the industrial environment have been proposed. This includes weighted edge filtering based on complementary information about the edge quality in an image. The recorded measurement median errors were ±0.12 mm and ±0.14 mm. Moreover, the 95% confidence intervals were ±0.5 mm and ±1 mm for the forging axis and diameter measurements, respectively. Both results were achieved in a measurement volume of 6 × 6 × 2 m during the measurement of glowing hot forgings in industrial conditions. The results surpass those of the state-of-the-art method, mainly in the case of axis straightness measurement, by approximately 50%. The measurement is fast, and it provides feedback about the axis straightness for its subsequent correction.
We present a method for planar shape detection and regularization from raw point sets. The geometric modelling and processing of man‐made environments from measurement data often relies upon robust ...detection of planar primitive shapes. In addition, the detection and reinforcement of regularities between planar parts is a means to increase resilience to missing or defect‐laden data as well as to reduce the complexity of models and algorithms down the modelling pipeline. The main novelty behind our method is to perform detection and regularization in tandem. We first sample a sparse set of seeds uniformly on the input point set, and then perform in parallel shape detection through region growing, interleaved with regularization through detection and reinforcement of regular relationships (coplanar, parallel and orthogonal). In addition to addressing the end goal of regularization, such reinforcement also improves data fitting and provides guidance for clustering small parts into larger planar parts. We evaluate our approach against a wide range of inputs and under four criteria: geometric fidelity, coverage, regularity and running times. Our approach compares well with available implementations such as the efficient random sample consensus–based approach proposed by Schnabel and co‐authors in 2007.
We present a method for planar shape detection and regularization from raw point sets. The geometric modelling and processing of man‐made environments from measurement data often relies upon robust detection of planar primitive shapes. In addition, the detection and reinforcement of regularities between planar parts is a means to increase resilience to missing or defect‐laden data as well as to reduce the complexity of models and algorithms down the modelling pipeline. The main novelty behind our method is to perform detection and regularization in tandem. We first sample a sparse set of seeds uniformly on the input point set, and then perform in parallel shape detection through region growing, interleaved with regularization through detection and reinforcement of regular relationships (coplanar, parallel and orthogonal).
The significance of the acceleration zone is expressed when designing a straight pipeline that follows either the feeding point or a bend in a pneumatic conveying system. It is an effective and ...reliable system that takes into account the acceleration zone in the design process. The current paper presents a thorough experimental investigation of particle velocity profile at the acceleration region obtained from 3-in, 2-in and 1-in horizontal dilute phase pneumatic conveying systems with various operating conditions and conveyed materials. The velocity was obtained by using a high speed camera combined with image processing. Investigation of the statistical velocity distribution resulted in a new correlation for the particle velocity profile throughout the acceleration zone and the acceleration length in the range of the tested operating conditions.
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•Evaluation of the acceleration length is crucial when designing a system.•The velocity profile of the particles is needed for various reasons.•A correlation is given in order to evaluate the acceleration length.•A correlation is given for the velocity profile in the acceleration region.•A correlation is given for the velocities statistical distribution in the acceleration zone.
•Multi-scale images speed up method as well as ensure enough and detailed image information.•Low-resolution image contains more edge information with less background noise.•The change law of gray ...projection curve reflect the location information of intrusion target.•Dynamic candidate region can get rid of most useless information in the image.•Background difference method helps to extract intrusion target by the high-resolution image.
This paper focuses on image characteristics of railway monitoring scenes, and proposed a multi-scale image and dynamic candidate region-based automatic detection of foreign targets intruding the railway perimeter. The algorithm first constructs a multi-scale image set for each frame, then obtains a dynamic candidate region of the intrusion target according to the law of gray projection curve variation for the low-resolution image. The foreground image, containing the intrusion target, is obtained using the background differential method for the high-resolution image, then the intruding target is identified before fusion of the results from the two methods. Three railway surveillance videos are used to validate the algorithm comparing with other methods, currently used in the railway scene. Overall, the proposed algorithm guarantees high-accuracy real-time detection of intruding targets, while requiring little computational resources, which is able to achieve 89.3% Precision and 0.028 s/frame with CPU. This technology can reduce the workload of manual inspections, and improve the detection accuracy through the improvement of the model can also reduce the manual review work caused by false alarms.
In the past, information technology was frequently considered a waste from Lean manufacturing perspective. Though the business landscape evolves and competition from low-cost nations grows, new ...models must be created that provides a competitive edge by combining the Lean paradigm with Industry 4.0 technical advancements. This paper aims to contribute to this field by assessing the supporting function of a Machine-based Identification system (MBID) via Optical Character Recognition (OCR) in Lean manufacturing paradigm. The objective of this paper is to also explore the use of MBID to enable a competitive manufacturing process in a Lean 4.0 environment. Furthermore, a MBID via OCR model is proposed to extract the printed identification number of packages from images captured by a fixed camera in an industrial environment. The method considers different digital image processing techniques to deal with the significant lighting and printing variation observed, followed by a segmentation process that extracts and aligns the characters. The proposed system utilized an approach to treating lighting variations in images, covering low contrast, distorted, darker, and brighter images. Experiments were carried out on a data set consisting of 200 images and achieved an overall detection accuracy of 95% with a very low Character Error Rate (CER) value of 0.0041, clearly supporting the validity and effectiveness of the proposed method.
Detecting the dependency between integration test cases plays a vital role in the area of software test optimization. Classifying test cases into two main classes – dependent and independent – can be ...employed for several test optimization purposes such as parallel test execution, test automation, test case selection and prioritization, and test suite reduction. This task can be seen as an imbalanced classification problem due to the test cases’ distribution. Often the number of dependent and independent test cases is uneven, which is related to the testing level, testing environment and complexity of the system under test. In this study, we propose a novel methodology that consists of two main steps. Firstly, by using natural language processing we analyze the test cases’ specifications and turn them into a numeric vector. Secondly, by using the obtained data vectors, we classify each test case into a dependent or an independent class. We carry out a supervised learning approach using different methods for handling imbalanced datasets. The feasibility and possible generalization of the proposed methodology is evaluated in two industrial projects at Bombardier Transportation, Sweden, which indicates promising results.
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•In a manual testing procedure, all testing artifacts are written in a natural text, employing natural language processing techniques might provide highly useful information for test optimization purposes.•The ratio of dependent and independent test cases might suffer from an imbalanced distribution due to the testing level and complexity of the system under test.•Doc2Vec proves to be a good tool when transforming the manual test cases into feature vectors.•IFROWANN performs well when splitting dependent and independent test cases as an imbalance learning algorithm.
This paper proposes an original approach for the statistical analysis of longitudinal shape data. The proposed method allows the characterization of typical growth patterns and subject-specific shape ...changes in repeated time-series observations of several subjects. This can be seen as the extension of usual longitudinal statistics of scalar measurements to high-dimensional shape or image data. The method is based on the estimation of continuous subject-specific growth trajectories and the comparison of such temporal shape changes across subjects. Differences between growth trajectories are decomposed into morphological deformations, which account for shape changes independent of the time, and time warps, which account for different rates of shape changes over time. Given a longitudinal shape data set, we estimate a mean growth scenario representative of the population, and the variations of this scenario both in terms of shape changes and in terms of change in growth speed. Then, intrinsic statistics are derived in the space of spatiotemporal deformations, which characterize the typical variations in shape and in growth speed within the studied population. They can be used to detect systematic developmental delays across subjects. In the context of neuroscience, we apply this method to analyze the differences in the growth of the hippocampus in children diagnosed with autism, developmental delays and in controls. Result suggest that group differences may be better characterized by a different speed of maturation rather than shape differences at a given age. In the context of anthropology, we assess the differences in the typical growth of the endocranium between chimpanzees and bonobos. We take advantage of this study to show the robustness of the method with respect to change of parameters and perturbation of the age estimates.
Tackling the questions that systems designers care about, this book brings queueing theory decisively back to computer science. The book is written with computer scientists and engineers in mind and ...is full of examples from computer systems, as well as manufacturing and operations research. Fun and readable, the book is highly approachable, even for undergraduates, while still being thoroughly rigorous and also covering a much wider span of topics than many queueing books. Readers benefit from a lively mix of motivation and intuition, with illustrations, examples and more than 300 exercises – all while acquiring the skills needed to model, analyze and design large-scale systems with good performance and low cost. The exercises are an important feature, teaching research-level counterintuitive lessons in the design of computer systems. The goal is to train readers not only to customize existing analyses but also to invent their own.
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