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Double-Blockchain Assisted Secure and Anonymous Data Aggregation for Fog-Enabled Smart Grid

engineering 2022年第1期8卷 159-169页

作者： Siguang Chen Li Yang Chuanxin Zhao Vijayakumar Varadarajan Kun Wang Jiangsu Key Lab of Broadband Wireless Communication and Internet of Things Nanjing University of Posts and TelecommunicationsNanjing 210003China Jiangsu Engineering Research Center of Communication and Network Technology Nanjing University of Posts and TelecommunicationsNanjing 210003China Anhui Provincial Key Laboratory of Network and Information Security Anhui Normal UniversityWuhu 241000China School of Computer Science and Engineering Vellore Institute of TechnologyChennai 600127India Department of Electrical and Computer Engineering University of CaliforniaLos AngelesCA 90095USA

As a future energy system,the smart grid is designed to improve the efficiency of traditional power systems while providing more stable and reliable ***,this efficient and reliable service relies on collecting and analyzing users’electricity consumption data frequently,which induces various security and privacy *** address these challenges,we propose a double-blockchain assisted secure and anonymous data aggregation scheme for fog-enabled smart grid named ***,we design a three-tier architecture-based data aggregation framework by integrating fog computing and the blockchain,which provides strong support for achieving efficient and secure data collection in smart ***,we develop a secure and anonymous data aggregation mechanism with low computational overhead by jointly leveraging the Paillier encryption,batch aggregation signature and anonymous *** particular,the system achieves fine-grained data aggregation and provides effective support for power dispatching and price adjustment by the designed double-blockchain and two-level data ***,the superiority of the proposed scheme is illustrated by a series of security and computation cost analyses.

关键词： Blockchain Fog computing Homomorphic encryption Smart grid Anonymity

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DiffSenseNet: Integrating Hierarchical Features and Angular Diffusion for Remote Sensing Object Detection

DiffSenseNet: Integrating Hierarchical Features and Angular ...

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International Symposium on Parallel and Distributed Processing with Applications, ISPA

作者： Songwen Pei Hongli Ma Xinyun Qiu Libo Huang Key Laboratory of Fire Detection and Early Warning Technology of Shanghai Emergency Management Bureau School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai China School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai China National University of Defense Technology Changsha China

ISBN: (数字)9798331509712

ISBN: (纸本)9798331509729

Object detection in remote sensing images is a significant and challenging task. The detection performance is difficult to further improve due to the wide variation in object scale and unpredictable orientations. However, traditional methods typically rely on Region Proposal Networks (RPN) with fixed anchor boxes, which makes it difficult to locate objects of multi-scale and multi-orientation. In this paper, we propose DiffSenseNet, a detection network that integrates Hierarchical Feature Fusion (HFF) and Angular Diffusion Augmentation (ADA). The HFF architecture integrates both bottom-up and top-down pathways to effectively merge features at different scales. The ADA strategy introduces directional information into noisy boxes by adding Gaussian noise to the ground truth boxes. On the DOTA and HRSC2016 datasets, DiffSenseNet achieves the accuracy of 75.89% and 86.24% mAP, respectively. Comprehensive experiments show that DiffSenseNet achieves relatively superior performance compared to previous state-of-the-art jobs.

关键词： Distributed processing Accuracy Gaussian noise Object detection Feature extraction Proposals Noise measurement Remote sensing

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MEMS-based twisted bilayer flat optics for multidimensional optical modulation and hyperimaging

MEMS-based twisted bilayer flat optics for multidimensional ...

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2024 Frontiers in Optics, FiO 2024

作者： Tang, Haoning Lou, Beicheng Du, Fan Gao, Guangqi Zhang, Mingjie Ni, Xueqi Yacoby, Amir Cao, Yuan Fan, Shanhui Mazur, Eric School of Engineering and Applied Sciences Harvard University CambridgeMA02138 United States Department of Electrical Engineering and Computer Science University of California at Berkeley BerkeleyCA94720 United States National Institute for Materials Science Namiki 1-1 Ibaraki Tsukuba305-0044 Japan Department of Applied Physics Ginzton Laboratory Stanford University StanfordCA94305 United States

Our MEMS-based twistoptics device enables precise control of interlayer gaps and twist angles in photonic crystals, achieving high-accuracy, multidimensional light manipulation with significant potential in reconfigur... 详细信息

关键词： Nanophotonics

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Silicon Micro-Disk Resonator Crossbar Array for High-Speed and High-Density Photonic Convolution Processing

arXiv

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arXiv 2025年

作者： Huang, Long Yao, Jianping Microwave Photonics Research Laboratory School of Electrical Engineering and Computer Science University of Ottawa OttawaONK1N 6N5 Canada

Advanced artificial intelligence (AI) algorithms, particularly those based on artificial neural networks, have garnered significant attention for their potential applications in areas such as image recognition and natural language processing. Notably, neural networks make heavy use of matrix-vector multiplication (MVM) operations, causing substantial computing burden on existing electronic computing systems. Optical computing has attracted considerable attention that can perform optical-domain MVM at an ultra-high speed. In this paper, we introduce a novel silicon photonic micro-disk resonator (MDR) crossbar signal processor designed to support matrix-vector multiplication (MVM) with both high processing speed and enhanced computational density. The key innovation of the proposed MDR crossbar processor is the placement of two MDRs at each crosspoint, enabling simultaneous routing and weighting functions. This design effectively doubles the computational density, improving overall performance. We fabricate a silicon photonic MDR crossbar processor, which is employed to perform convolutional tasks in a convolutional neural network (CNN). The experimental results demonstrate that the photonic processor achieves a classification accuracy of 96% on the MNIST dataset. Additionally, it is capable of scaling to a computational speed of up to 160 tera-operations per second (TOPS) and a computational density as high as 25.6 TOPS/mm2. Our approach holds significant promise for enabling highly efficient, scalable on-chip optical computing, with broad potential applications in AI and beyond. © 2025, CC BY-NC-ND.

关键词： Silicon photonics

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An on-chip platform for multi-degree-of-freedom control of two-dimensional quantum and nonlinear materials

An on-chip platform for multi-degree-of-freedom control of t...

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CLEO: science and Innovations in CLEO 2024, CLEO: S and I 2024 - Part of Conference on Lasers and Electro-Optics

作者： Tang, Haoning Wang, Yiting Ni, Xueqi Watanabe, Kenji Taniguchi, Takashi Fan, Shanhui Mazur, Eric Yacoby, Amir Cao, Yuan School of Engineering and Applied Sciences Harvard University CambridgeMA02138 United States Department of Electrical Engineering and Computer Science University of California at Berkeley BerkeleyCA94720 United States National Institute for Materials Science Namiki 1-1 Ibaraki Tsukuba305-0044 Japan Department of Applied Physics Ginzton Laboratory Stanford University StanfordCA94305 United States

We introduce the first on-chip, microelectromechanical system for the in situ tuning of twisted 2D materials, enabling tunable interfacial properties, synthetic topological singularities, and adjustable-polarization l... 详细信息

关键词： Degrees of freedom (mechanics)

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Impact Assessment of NILM Methods for an Enhanced Observability of Low Voltage Distribution Networks 8

Impact Assessment of NILM Methods for an Enhanced Observabil...

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8th IEEE International Smart Cities Conference, ISC2 2022

作者： Moreno Jaramillo, Andres F Lopez-Lorente, Javier Brogan, Paul Laverty, David Del Rincon, Jesus Martinez Foley, Aoife School of Electronics Electrical Engineering and Computer Science Queen's University Belfast Belfast United Kingdom Pv Technology Laboratory Foss Research Centre for Sustainable Energy University of Cyprus Department of Electrical and Computer Engineering Nicosia Cyprus Applications Strategist Phasora Ltd Belfast United Kingdom School of Mechanical and Aerospace Engineering Queen's University Belfast Belfast United Kingdom

ISBN: (数字)9781665485616

ISBN: (纸本)9781665485616

The migration to low-carbon technologies in secondary (low-voltage) distribution networks relies on high integration of distributed energy resources (DER), including distributed generation and low-carbon loads. The electrification of power and transport sectors has led to an increased deployment of solar photovoltaic systems and electric vehicles causing unconventional dynamics in distribution networks. Thus, distribution network operators are facing new technical challenges such as reverse power flow, higher load peaks, and power quality issues. This has attracted research interest to investigate the implementation of innovative techniques such as non-intrusive load monitoring (NILM) methods. These techniques contribute to an enhanced and scalable monitoring of DER in electrical networks. Current literature based NILM models have achieved significantly high performance for both electromobility and photovoltaic systems, which makes them eligible for deployment from a technical standpoint. However, a critical analysis of the considerations for a feasible implementation of these methodologies has not been covered. Thus, this work studies the techno-economic implications for the large-scale implementation of NILM methods at the customer level and low voltage side of distribution transformers. While a substantial investment is associated with a better monitored low voltage distribution network, there are multiple benefits related to technical, economic, social, and environmental aspects. © 2022 IEEE.

关键词： Electric power transmission networks

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Surface-patterned chalcogenide glasses with high-aspect-ratio microstructures for long-wave infrared metalenses

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Opto-Electronic science 2024年第10期3卷 1-13页

作者： Zhaofeng Gu Yixiao Gao Kongsi Zhou Junyang Ge Chen Xu Lei Xu Mohsen Rahmani Ran Jiang Yimin Chen Zijun Liu Chenjie Gu Yaoguang Ma Jianrong Qiu Xiang Shen Laboratory of Infrared Materials and Devices Research Institute of Advanced TechnologiesNingbo UniversityNingbo 315211China Zhejiang Key Laboratory of Advanced Optical Functional Materials and Devices Ningbo 315211China Advanced Optics&Photonics Laboratory Department of EngineeringSchool of Science and TechnologyNottingham Trent UniversityNottingham NG118NSUnited Kingdom Faculty of Electrical Engineering and Computer Science Ningbo UniversityNingbo 315211China State Key Laboratory of Extreme Photonics and Instrumentation College of Optical Science and EngineeringInternational ResearchCenter for Advanced PhotonicsZhejiang UniversityHangzhou 310027China Ningbo Institute of Oceanography Ningbo 315832China

Multidimensional-engineering chalcogenide glasses is widely explored to construct various infrared photonic devices,with their surface as a key dimension for wavefront ***,we demonstrate direct patterning high-aspect-ratio microstructures on the surface of chalcogenide glasses offers an efficient and robust method to manipulate longwave infrared *** chalcogenide glass being considered soft in terms of its mechanical properties,we successfully fabricate high-aspect-ratio micropillars with a height of 8μm using optimized deep etching process,and we demonstrate a 2-mm-diameter all-chalcogenide metalens with a numerical aperture of 0.45 on the surface of a 1.5-mm-thick As2Se3 *** the exceptional longwave infrared(LWIR)transparency and moderate refractive index of As2Se3 glass,the all-chalcogenide metalens produces a focal spot size of~1.39λ0 with a focusing efficiency of 47%at the wavelength of 9.78μm,while also exhibiting high-resolution imaging *** work provides a promising route to realize easy-to-fabricate,mass-producible planar infrared optics for compact,light-weight LWIR imaging systems.

关键词： chalcogenide glasses long wave infrared metalens

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Differential Evolution for Optimizing Parameter Estimation in Practical D2D Channels

Differential Evolution for Optimizing Parameter Estimation i...

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IEEE Conference on Wireless Communications and Networking

作者： Samuel B. Ferreira Gomes Nidhi Simmons Michel Daoud Yacoub Paschalis C. Sofotasios Simon L. Cotton Wireless Technology Laboratory School of Electrical and Computer Engineering University of Campinas Campinas Brazil Centre for Wireless Innovation School of Electronics Electrical Engineering and Computer Science Queen's University Belfast Belfast UK Department of Computer and Communication Engineering C2PS and 6G Center Khalifa University Abu Dhabi UAE Department of Electrical Engineering Tampere University Tampere Finland

ISBN: (数字)9798350303582

ISBN: (纸本)9798350303599

Inspired by the theory of natural evolution, Differential Evolution (DE) functions constitute an optimization tool in the field of evolutionary algorithms. Here, we propose employing DE to estimate physically acceptable fading parameters in device-to-device (D2D) communication channels. We examine four real-world D2D propagation channel measurements obtained under various conditions: indoor, outdoor, line-of-sight (LOS), and non-LOS. Four popular fading models, $\kappa-\mu, \eta-\mu, \kappa-\mu$ /inverse gamma, and $\eta-\mu$ /inverse gamma are used to characterize these links. Two fitness functions, Kullback-Leibler divergence (KLD) and mean squared error (MSE), are utilized for evaluation. We also compare the DE with another evolutionary algorithm, namely the genetic algorithm (GA). Notably, our results demonstrate that while both algorithms deliver excellent estimation performances, DE emerges as significantly faster and more robust compared to GA. Regarding fitness performances, the algorithm, when paired with KLD, outperforms the pairing with MSE, as assessed through the minimization of the Akaike information criterion.

关键词： Fading channels Parameter estimation Metaheuristics Estimation Channel estimation Line-of-sight propagation Evolutionary computation

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3-D Near-Field Localization by Jointly Exploiting Spatial and Temporal Information Based on a Nonuniform Cross Array

3-D Near-Field Localization by Jointly Exploiting Spatial an...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Zelong Yi Hua Chen Zhiwei Jiang Wei Liu Qing Wang Gang Wang Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo China Zhejiang Key Laboratory of Mobile Network Application Technology Ningbo China School of Electronic Engineering and Computer Science Queen Mary University of London London UK School of Electronic Informatin Engineering Tianjin University Tianjin China

In this paper, an underdetermined three-dimensional (3-D) near-field source localization method is proposed, based on a two-dimensional (2-D) symmetric nonuniform cross array. Firstly, the fourth-order cumulant of the near-field observations with multiple delay lags is exploited to construct virtual far-field pseudo-observations, leading to increased degrees of freedom (DOF); then, 2-D angles of the nearfield sources are jointly estimated by employing the recently proposed sparse and parametric approach (SPA) and Vandermonde decomposition technique, eliminating the need for parameter discretization. To estimate the range term, the one-dimensional (1-D) MUSIC algorithm is applied by resorting to the conjugate symmetry property of the signal's autocorrelation function. Numerical results are provided to demonstrate the superiority of our method.

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Active twistoptics: on-chip multidimensional dynamic control for data hypercube reconstruction

Active twistoptics: on-chip multidimensional dynamic control...

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2024 Conference on Lasers and Electro-Optics, CLEO 2024

Our MEMS-integrated twistoptics device enables precise control of interlayer gaps and twist angles in photonic crystals, achieving high-accuracy, multidimensional light manipulation with significant potential in recon... 详细信息

ISBN: (纸本)9781957171395

关键词： Nanophotonics

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