- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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Method for Processing and Analysis of the Images of a Network of Thermal Fatigue Cracks on the Surfaces of Rollers of Continuous Casting Machines
摘要： We propose an algorithm for the analysis of thermal fatigue cracks on the surfaces of rollers of continuous casting machines that does not require adaptation to images of various types and individual choice of parameters. For this purpose, the images are analyzed for a sufficiently large subset of the sets of values of the parameters. The result of this classification is regarded as a fuzzy set with a membership function of each element equal to the number of sets of parameters responsible for the detection of this element as a component of the frame of the damage grid.
关键词： image processing,thermal fatigue cracks,self-focusing,fuzzy sets,classification
更新于2025-09-23 15:21:21
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[IEEE 2018 International Conference on Recent Innovations in Electrical, Electronics & Communication Engineering (ICRIEECE) - Bhubaneswar, India (2018.7.27-2018.7.28)] 2018 International Conference on Recent Innovations in Electrical, Electronics & Communication Engineering (ICRIEECE) - Fault Monitoring System for Photovoltaic Modules in Solar Panels using LabVIEW
摘要： Understanding relationships between sets is an important analysis task that has received widespread attention in the visualization community. The major challenge in this context is the combinatorial explosion of the number of set intersections if the number of sets exceeds a trivial threshold. In this paper we introduce UpSet, a novel visualization technique for the quantitative analysis of sets, their intersections, and aggregates of intersections. UpSet is focused on creating task-driven aggregates, communicating the size and properties of aggregates and intersections, and a duality between the visualization of the elements in a dataset and their set membership. UpSet visualizes set intersections in a matrix layout and introduces aggregates based on groupings and queries. The matrix layout enables the effective representation of associated data, such as the number of elements in the aggregates and intersections, as well as additional summary statistics derived from subset or element attributes. Sorting according to various measures enables a task-driven analysis of relevant intersections and aggregates. The elements represented in the sets and their associated attributes are visualized in a separate view. Queries based on containment in specific intersections, aggregates or driven by attribute filters are propagated between both views. We also introduce several advanced visual encodings and interaction methods to overcome the problems of varying scales and to address scalability. UpSet is web-based and open source. We demonstrate its general utility in multiple use cases from various domains.
关键词： set visualization,set relationships,multidimensional data,sets intersections,set attributes,Sets
更新于2025-09-23 15:19:57
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[IEEE OCEANS 2018 MTS/IEEE Charleston - Charleston, SC, USA (2018.10.22-2018.10.25)] OCEANS 2018 MTS/IEEE Charleston - Geometric Distortion Correction for the Underwater Images
摘要： Non-metric cameras have been widely used in applications of obtaining geometric information of the underwater objects using either digital photogrammetric approaches or computer vision algorithms. All the underwater images exhibit significant geometric distortions caused by lens distortions and light refraction in underwater imaging, which must be geometrically corrected. In this paper, a geometric distortion correction method for the underwater images is proposed, which uses the sets of distortion parameters obtained through the iterative camera calibration to determine the position relationship between the original images and the final corrected images, and then the gray values of the final corrected images are directly resampled from the original images. The GoPro Hero 5 Black calibration results show that the final accuracies are close to 0 pixel after three iterations; all the final distortion parameters calculated with the iterative calibration method are decreased after several iterations and can be ignored. By contrast, the original image was corrected well with the three sets of distortion parameters calculated with the iterative calibration method. An example shows that the successful generation of point clouds illustrates the effectiveness of the geometric correction. The proposed correcting method provides a technique not only to greatly reduce the distortion through applying a series of distortion parameters but also preserve the image quality through a smart resampling way.
关键词： sets of distortion parameters,once resampling,iterative camera calibration,underwater images,geometric correction
更新于2025-09-19 17:15:36
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[IEEE 2019 Antennas Design and Measurement International Conference (ADMInC) - St. Petersburg, Russia (2019.10.16-2019.10.18)] 2019 Antennas Design and Measurement International Conference (ADMInC) - Experimental Study of the Amplitude-Frequency Characteristics of a Waveguide Filter with a Resonant Waveguide-Slot Membrane at Subcritical Waveguide Frequencies
摘要： Understanding relationships between sets is an important analysis task that has received widespread attention in the visualization community. The major challenge in this context is the combinatorial explosion of the number of set intersections if the number of sets exceeds a trivial threshold. In this paper we introduce UpSet, a novel visualization technique for the quantitative analysis of sets, their intersections, and aggregates of intersections. UpSet is focused on creating task-driven aggregates, communicating the size and properties of aggregates and intersections, and a duality between the visualization of the elements in a dataset and their set membership. UpSet visualizes set intersections in a matrix layout and introduces aggregates based on groupings and queries. The matrix layout enables the effective representation of associated data, such as the number of elements in the aggregates and intersections, as well as additional summary statistics derived from subset or element attributes. Sorting according to various measures enables a task-driven analysis of relevant intersections and aggregates. The elements represented in the sets and their associated attributes are visualized in a separate view. Queries based on containment in specific intersections, aggregates or driven by attribute filters are propagated between both views. We also introduce several advanced visual encodings and interaction methods to overcome the problems of varying scales and to address scalability. UpSet is web-based and open source. We demonstrate its general utility in multiple use cases from various domains.
关键词： set visualization,set relationships,multidimensional data,sets intersections,set attributes,Sets
更新于2025-09-19 17:13:59
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[IEEE 2019 25th International Workshop on Thermal Investigations of ICs and Systems (THERMINIC) - Lecco, Italy (2019.9.25-2019.9.27)] 2019 25th International Workshop on Thermal Investigations of ICs and Systems (THERMINIC) - Modeling of Temperature Distribution Induced by Thermo-Mechanical Deformation of High-Power AlInGaN LED Arrays
摘要： When the amount of labeled data are limited, semi-supervised learning can improve the learner’s performance by also using the often easily available unlabeled data. In particular, a popular approach requires the learned function to be smooth on the underlying data manifold. By approximating this manifold as a weighted graph, such graph-based techniques can often achieve state-of-the-art performance. However, their high time and space complexities make them less attractive on large data sets. In this paper, we propose to scale up graph-based semisupervised learning using a set of sparse prototypes derived from the data. These prototypes serve as a small set of data representatives, which can be used to approximate the graph-based regularizer and to control model complexity. Consequently, both training and testing become much more ef?cient. Moreover, when the Gaussian kernel is used to de?ne the graph af?nity, a simple and principled method to select the prototypes can be obtained. Experiments on a number of real-world data sets demonstrate encouraging performance and scaling properties of the proposed approach. It also compares favorably with models learned via (cid:2)1-regularization at the same level of model sparsity. These results demonstrate the ef?cacy of the proposed approach in producing highly parsimonious and accurate models for semisupervised learning.
关键词： semisupervised learning,low-rank approximation,Graph-based methods,large data sets,manifold regularization
更新于2025-09-19 17:13:59
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[IEEE 2019 9th International Conference on Recent Advances in Space Technologies (RAST) - Istanbul, Turkey (2019.6.11-2019.6.14)] 2019 9th International Conference on Recent Advances in Space Technologies (RAST) - Radiation Analysis of HR Electro-Optical Satellite
摘要： When the amount of labeled data are limited, semi-supervised learning can improve the learner’s performance by also using the often easily available unlabeled data. In particular, a popular approach requires the learned function to be smooth on the underlying data manifold. By approximating this manifold as a weighted graph, such graph-based techniques can often achieve state-of-the-art performance. However, their high time and space complexities make them less attractive on large data sets. In this paper, we propose to scale up graph-based semisupervised learning using a set of sparse prototypes derived from the data. These prototypes serve as a small set of data representatives, which can be used to approximate the graph-based regularizer and to control model complexity. Consequently, both training and testing become much more ef?cient. Moreover, when the Gaussian kernel is used to de?ne the graph af?nity, a simple and principled method to select the prototypes can be obtained. Experiments on a number of real-world data sets demonstrate encouraging performance and scaling properties of the proposed approach. It also compares favorably with models learned via (cid:2)1-regularization at the same level of model sparsity. These results demonstrate the ef?cacy of the proposed approach in producing highly parsimonious and accurate models for semisupervised learning.
关键词： large data sets,semisupervised learning,Graph-based methods,manifold regularization,low-rank approximation
更新于2025-09-19 17:13:59
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A Multi-Attribute Decision Making Process with Immediate Probabilistic Interactive Averaging Aggregation Operators of T-Spherical Fuzzy Sets and Its Application in the Selection of Solar Cells
摘要： The objective of this paper is to present new interactive averaging aggregation operators by assigning associate probabilities for T-spherical fuzzy sets (T-SFSs). T-SFS is a generalization of several existing theories such as intuitionistic fuzzy sets and picture fuzzy sets to handle imprecise information. Under such an environment, we developed a series of averaging interactive aggregation operators under the features that each element is represented with T-spherical fuzzy numbers. Various properties of the proposed operators are also investigated. Further, to rank the different T-SFSs, we exhibit the new score functions and state their some properties. To demonstrate the presented algorithm, a decision-making process algorithm is presented with T-SFS features. To save non-renewable resources and to the protect environment, the use of renewable resources is important. Solar energy is one of the best renewable energy resources and is also environment-friendly and thus the selection of solar cells is typically a multi-attribute decision-making problem. Therefore, the applicability of the developed algorithm is demonstrated with a numerical example in the selection of the solar cells and comparison of their performance with the several existing approaches.
关键词： t-spherical fuzzy sets,aggregation operators,multi-attribute decision making,interactive aggregation operators
更新于2025-09-12 10:27:22
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Probing Basis Set Requirements for Calculating Core Ionization and Core Excitation Spectroscopy by the ΔSCF Approach
摘要： We investigate the basis set requirements for calculating properties corresponding to removing core electrons by the ΔSCF approach using Hartree-Fock and density functional theory. Standard contracted basis sets are shown to produce large errors and the improved performance of core-augmented basis sets is traced to the fact that the core-augmenting functions effectively creates an auxiliary set of uncontracted function in the core region. We propose two specific basis sets of double and triple zeta quality based on exponent interpolation of the polarization consistent basis sets, denoted pcX-1 and pcX-2, that display significantly lower basis set errors compared to other alternatives. These are suitable for both non-relativistic and relativistic calculations of the Douglas-Kroll-Hess type, with typical basis set errors of 0.1 and 0.01 eV, respectively, and they can be used in a mixed basis set approach with only a minor degradation in performance. The versions augmented with diffuse functions (aug-pcX-1 and aug-pcX-2) are shown to perform better than other alternatives for X-ray absorption spectroscopy. When used in connection with range-separated hybrid density functional methods and relativistic corrections, the pcX-n basis sets can in favorable cases reproduce experimental results to within a few tenths of an eV.
关键词： basis sets,Hartree-Fock,density functional theory,ΔSCF approach,core ionization,core excitation spectroscopy
更新于2025-09-10 09:29:36
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Improved Image Fusion of Colored and Grayscale Medical Images Based on Intuitionistic Fuzzy Sets
摘要： Image fusion is the process of combining the properties of two images into one single image that will show the features of both the images. There are various methods available in the literature to fuse the images. In this paper, an intuitionistic fuzzy logic-based image fusion approach has been implemented for medical images that firstly suppresses the noise and enhances the input images, and merges them efficiently in Hue-Saturation-Intensity domain. Here, enhancement is included because these input images are not always well contrasted and may contain some noise due to the inherent properties of the modalities used for capturing the images. The intuitionistic fuzzy sets are incorporated to handle uncertainties that are often due to vagueness and ambiguity. The results certify that this method significantly improves the output fused image than the image obtained by existing technique both visually and metrically.
关键词： fuzzy histogram equalization,Image fusion,contrast enhancement,intuitionistic fuzzy sets
更新于2025-09-10 09:29:36
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[IEEE 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) - Atlanta, GA (2017.10.21-2017.10.28)] 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) - Spatially-variant Strength for Anatomical Priors in PET Reconstruction
摘要： This study explores the use of a spatially-variant penalty strength, proposed initially for quadratic penalties, in penalized image reconstruction using anatomical information. We have used the recently proposed Parallel Level Sets (PLS) anatomical prior as it has shown promising results in the literature. It was incorporated into the previously proposed preconditioned algorithm (L-BFGS-B-PC) for achieving both good image quality and fast convergence rate. A 2-dimensional (2D) disc phantom with a hot spot at the center and a 3D XCAT thorax phantom with lesions inserted in different slices are used to study how surrounding activity and lesion location affect both the visual appearance and quantitative consistency, respectively. Anatomical information is provided and assumed to be well-aligned with the corresponding activity images. For the XCAT phantom, the inserted lesions are either present or absent in the anatomical images to investigate the influence of the anatomical penalty. The reconstructed images for both phantoms with and without applying the spatially-variant penalty strength are compared. Preliminary results demonstrate that applying the spatially-variant penalization with an anatomical prior can reduce the dependence of local contrast on background activity and lesion location. Further work to explore the potential benefit in clinical imaging is warranted.
关键词： spatially-variant penalty strength,penalized image reconstruction,L-BFGS-B-PC,Parallel Level Sets,anatomical prior
更新于2025-09-09 09:28:46