- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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[IEEE 2019 IEEE Sustainable Power and Energy Conference (iSPEC) - Beijing, China (2019.11.21-2019.11.23)] 2019 IEEE Sustainable Power and Energy Conference (iSPEC) - The Probabilistic Assessment of Outgoing Transformer Operation Risk Considering the Correlation Between Wind Power and Photovoltaic
摘要： Rough set proposed by Pawlak in 1982 is an important tool to process uncertain information. As an extended model of rough set, an approximation set model of rough set was proposed and proved to be feasible to establish an approximation target set with existing knowledge base. However, there still is a lack of effective methods for knowledge acquisition based on the approximation set model. In this paper, related methods of attribute reduction based on approximation set model of rough set are discussed in algebraic view and information view, respectively. First, a distribution reduction method on the basic of discernibility matrix according to approximation set is proposed and discussed in algebraic view. Furthermore, an algorithm of attribute reduction based on conditional information entropy of approximation set model is presented in information view. Finally, many experimental results show that the proposed algorithm could acquire more effective knowledge from uncertain information system compared with other algorithms based on classical rough set theory.
关键词： attribute reduction,approximation set,information view,algebra view,Rough set
更新于2025-09-19 17:13:59
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Interplay between electronic and structural transitions in VO <sub/>2</sub> revealed by ellipsometry
摘要： Temperature-dependent spectroscopic ellipsometry measurements, combined with AFM investigations, have been performed to reveal the interplay between the structural and electronic phase transitions during the insulator-to-metal transition in VO2 thin films with different thicknesses. A comprehensive analysis of the macroscopic optical response in the framework of an anisotropic Bruggeman effective medium approximation yields the hysteretic shape evolution of the metallic inclusions and the changes in film roughness due to the structural transitions during a temperature cycle. The authors show that the structural modifications in the material across the transition affect the metallic cluster shape in the vicinity of the percolation threshold, leading to an altered absorption by the localized plasmon resonances. The structural changes are supported by AFM measurements and can be explained by the particular strain present in different films.
关键词： VO2,AFM,localized plasmon resonances,spectroscopic ellipsometry,Bruggeman effective medium approximation,insulator-to-metal transition
更新于2025-09-19 17:13:59
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[IEEE 2019 Photonics & Electromagnetics Research Symposium - Fall (PIERS - Fall) - Xiamen, China (2019.12.17-2019.12.20)] 2019 Photonics & Electromagnetics Research Symposium - Fall (PIERS - Fall) - Class F-C Power Amplifier with 2nd Harmonic Control at the Input
摘要： Currently, self-healing is one of the most important functions in the smart grid. Meanwhile, fault detection, isolation, and restoration of feeder automation systems dominate the self-healing function in power distribution systems. The steps of the aforementioned function depend on the fault ?ag status of the feeder terminal unit. The conditions for setting this ?ag are judged by the feeder terminal unit overcurrent detecting curve. This paper found an ef?cient approach to calculate this curve via a half-interval method. Versatile application software with the curve plotting capability was also developed and deployed on the web server of the information-management department of Taiwan Power Company and is running successfully.
关键词： piecewise linear approximation,power distribution protection,IEEE standards,fault currents,Computer aided analysis
更新于2025-09-19 17:13:59
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[IEEE 2019 7th International Japan-Africa Conference on Electronics, Communications, and Computations, (JAC-ECC) - Alexandria, Egypt (2019.12.15-2019.12.16)] 2019 7th International Japan-Africa Conference on Electronics, Communications, and Computations, (JAC-ECC) - Synthesis and Characterization of Neodymium Oxide Doped Phosphate Glass Matrix for Solar Cell Application
摘要： In this paper, we consider the down-link dynamic resource allocation in multi-cell virtualized wireless networks (VWNs) to support the users of different service providers (slices) within a specific region by a set of base stations (BSs) through orthogonal frequency division multiple access (OFDMA). In particular, we develop a joint BS assignment, sub-carrier, and power allocation algorithm to maximize the network sum rate, while satisfying the minimum required rate of each slice. Under the assumption that each user at each transmission instance can connect to no more than one BS, we introduce the user-association factor to represent the joint sub-carrier and BS assignment as the optimization variable vector in the problem formulation. Sub-carrier reuse is allowed in different cells, but not within one cell. As the proposed optimization problem is inherently non-convex and NP-hard, by applying the successive convex approximation (SCA) and complementary geometric programming (CGP), we develop an efficient two-step iterative approach with low computational complexity to solve the proposed problem. For a given problem, Step 1 derives the optimum user-association and subsequently, and for an obtained user-association, Step 2 finds the optimum power allocation. Simulation results demonstrate that the proposed iterative algorithm outperforms the traditional approach in which each user is assigned to the BS with the largest average value of signal strength, and then, joint sub-carrier and power allocation is obtained for the assigned users of each cell. Simulation results reveal a coverage improvement, offered by the proposed approach, of 57% and 71% for uniform and non-uniform users distribution, respectively, leading to higher spectrum efficiency for VWN.
关键词： joint user association and resource allocation,virtualized wireless networks,successive convex approximation,Complementary geometric programming
更新于2025-09-19 17:13:59
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[IEEE 2019 3rd International Conference on Recent Developments in Control, Automation & Power Engineering (RDCAPE) - NOIDA, India (2019.10.10-2019.10.11)] 2019 3rd International Conference on Recent Developments in Control, Automation & Power Engineering (RDCAPE) - Impact of Solar Photovoltaic Penetration In Distribution Network
摘要： In this paper, we consider the down-link dynamic resource allocation in multi-cell virtualized wireless networks (VWNs) to support the users of different service providers (slices) within a specific region by a set of base stations (BSs) through orthogonal frequency division multiple access (OFDMA). In particular, we develop a joint BS assignment, sub-carrier, and power allocation algorithm to maximize the network sum rate, while satisfying the minimum required rate of each slice. Under the assumption that each user at each transmission instance can connect to no more than one BS, we introduce the user-association factor to represent the joint sub-carrier and BS assignment as the optimization variable vector in the problem formulation. Sub-carrier reuse is allowed in different cells, but not within one cell. As the proposed optimization problem is inherently non-convex and NP-hard, by applying the successive convex approximation (SCA) and complementary geometric programming (CGP), we develop an efficient two-step iterative approach with low computational complexity to solve the proposed problem. For a given problem, Step 1 derives the optimum user-association and subsequently, and for an obtained user-association, Step 2 finds the optimum power allocation. Simulation results demonstrate that the proposed iterative algorithm outperforms the traditional approach in which each user is assigned to the BS with the largest average value of signal strength, and then, joint sub-carrier and power allocation is obtained for the assigned users of each cell. Simulation results reveal a coverage improvement, offered by the proposed approach, of 57% and 71% for uniform and non-uniform users distribution, respectively, leading to higher spectrum efficiency for VWN.
关键词： joint user association and resource allocation,successive convex approximation,virtualized wireless networks,Complementary geometric programming
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 IEEE 58th Conference on Decision and Control (CDC) - Nice, France (2019.12.11-2019.12.13)] 2019 IEEE 58th Conference on Decision and Control (CDC) - Robust Population Transfer for Coupled Spin Ensembles
摘要： Finely manipulating a large population of interacting nuclear spins is an extremely challenging problem arising in wide-ranging applications in quantum science and technology. Prominent examples include the design of robust excitation and inversion pulses for nuclear magnetic resonance spectroscopy and imaging, coordination of spin networks for coherence transfer, and control of superposition and entanglement for quantum computation. In this paper, by integrating the technique of small angle approximation with non-harmonic Fourier analysis, we establish a systematic method to construct robust pulse sequences that neutralize the effect of coupling variations in a spin network. In addition, we explore an alternating optimization procedure for tailoring the constructed pulses to satisfy practical design criteria. We also provide numerical examples to demonstrate the efficacy of the proposed methodology.
关键词： non-harmonic Fourier analysis,small angle approximation,robust pulse sequences,spin ensembles,quantum control
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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Laser-induced incandescence on metal nanoparticles: validity of the Rayleigh approximation
摘要： Time-resolved laser-induced incandescence (TiRe-LII) is increasingly being used to characterize non-carbonaceous nanoparticles. However, there exist several measured phenomena, particularly on metal nanoparticles, that cannot be explained using traditional models. This paper shows that some of these phenomena may be due to errors caused by the Rayleigh approximation of Mie theory, which is a standard approach for modeling the spectral absorption of carbonaceous nanoparticles but is generally invalid for metal nanoparticles. Other measurement phenomena can be explained by combining Mie theory with a polydisperse particle size distribution or by considering the change in the refractive index as the nanoparticles melt. Also, the effect of the nanoparticle charge on optical properties is investigated and is found to have a negligible effect on the TiRe-LII model.
关键词： Mie theory,Polydisperse particle size distribution,Metal nanoparticles,Refractive index,Nanoparticle charge,Rayleigh approximation,Laser-induced incandescence
更新于2025-09-19 17:13:59
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[IEEE 2019 Days on Diffraction (DD) - St. Petersburg, Russia (2019.6.3-2019.6.7)] 2019 Days on Diffraction (DD) - Novel types of mode dispersion of optical vortices in twisted optical fibers
摘要： Nonlocal self-similarity of images has attracted considerable interest in the field of image processing and has led to several state-of-the-art image denoising algorithms, such as block matching and 3-D, principal component analysis with local pixel grouping, patch-based locally optimal wiener, and spatially adaptive iterative singular-value thresholding. In this paper, we propose a computationally simple denoising algorithm using the nonlocal self-similarity and the low-rank approximation (LRA). The proposed method consists of three basic steps. First, our method classifies similar image patches by the block-matching technique to form the similar patch groups, which results in the similar patch groups to be low rank. Next, each group of similar patches is factorized by singular value decomposition (SVD) and estimated by taking only a few largest singular values and corresponding singular vectors. Finally, an initial denoised image is generated by aggregating all processed patches. For low-rank matrices, SVD can provide the optimal energy compaction in the least square sense. The proposed method exploits the optimal energy compaction property of SVD to lead an LRA of similar patch groups. Unlike other SVD-based methods, the LRA in SVD domain avoids learning the local basis for representing image patches, which usually is computationally expensive. The experimental results demonstrate that the proposed method can effectively reduce noise and be competitive with the current state-of-the-art denoising algorithms in terms of both quantitative metrics and subjective visual quality.
关键词： patch grouping,Back projection,low-rank approximation (LRA),singular value decomposition (SVD),image denoising,self-similarity
更新于2025-09-19 17:13:59