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arXiv 2021年

作者： Ghojogh, Benyamin Ghodsi, Ali Karray, Fakhri Crowley, Mark Department of Electrical and Computer Engineering Machine Learning Laboratory University of Waterloo WaterlooON Canada Department of Statistics and Actuarial Science David R. Cheriton School of Computer Science Data Analytics Laboratory University of Waterloo WaterlooON Canada Department of Electrical and Computer Engineering Centre for Pattern Analysis and Machine Intelligence University of Waterloo WaterlooON Canada

This is a tutorial and survey paper on Boltzmann Machine (BM), Restricted Boltzmann Machine (RBM), and Deep Belief Network (DBN). We start with the required background on probabilistic graphical models, Markov random field, Gibbs sampling, statistical physics, Ising model, and the Hopfield network. Then, we introduce the structures of BM and RBM. The conditional distributions of visible and hidden variables, Gibbs sampling in RBM for generating variables, training BM and RBM by maximum likelihood estimation, and contrastive divergence are explained. Then, we discuss different possible discrete and continuous distributions for the variables. We introduce conditional RBM and how it is trained. Finally, we explain deep belief network as a stack of RBM models. This paper on Boltzmann machines can be useful in various fields including data science, statistics, neural computation, and statistical physics. Copyright © 2021, The Authors. All rights reserved.

关键词： Statistical Physics

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Resistance Distances in Simplicial Networks

arXiv

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arXiv 2022年

作者： Zhu, Mingzhe Xu, Wanyue Zhang, Zhongzhi Kan, Haibin Chen, Guanrong Shanghai Key Laboratory of Intelligent Information Processing Shanghai Engineering Research Institute of Blockchain School of Computer Science Fudan University Shanghai200433 China Department of Electrical Engineering City University of Hong Kong Hong Kong

It is well known that in many real networks, such as brain networks and scientific collaboration networks, there exist higher-order nonpairwise relations among nodes, i.e., interactions between among than two nodes at a time. This simplicial structure can be described by simplicial complexes and has an important effect on topological and dynamical properties of networks involving such group interactions. In this paper, we study analytically resistance distances in iteratively growing networks with higher-order interactions characterized by the simplicial structure that is controlled by a parameter q. We derive exact formulas for interesting quantities about resistance distances, including Kirchhoff index, additive degree-Kirchhoff index, multiplicative degree-Kirchhoff index, as well as average resistance distance, which have found applications in various areas elsewhere. We show that the average resistance distance tends to a q-dependent constant, indicating the impact of simplicial organization on the structural robustness measured by average resistance distance. Copyright © 2022, The Authors. All rights reserved.

关键词： Complex networks

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All-silicon quantum light source by embedding a single color center in a nanophotonic cavity

All-silicon quantum light source by embedding a single color...

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IEEE Photonics Conference (IPC)

作者： W. Qarony W. Redjem Y. Zhiyenbayev V. Ivanov C. Papapanos W. Liu K. Jhuria Z. Y. Al Balushi S. Dhuey A. Schwartzberg L. Z. Tan T. Schenkel B. Kanté Department of Electrical Engineering and Computer Sciences University of California Berkeley California USA Molecular Foundry Lawrence Berkeley National Laboratory Berkeley California USA Accelerator Technology and Applied Physics Division Lawrence Berkeley National Laboratory Berkeley California USA Department of Materials Science and Engineering University of California Berkeley Berkeley CA USA Materials Sciences Division Lawrence Berkeley National Laboratory Berkeley California USA

We present the first all-silicon quantum light source by integrating a silicon-based single color center within a silicon nanophotonic cavity. This approach results in a remarkable 30-fold increase in luminescence and an 8-fold emission acceleration, enabling scalable quantum technologies for communication, sensing, imaging, and computing.

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Beam Scanning for Integrated Sensing and Communication in IRS-aided mmWave Systems

Beam Scanning for Integrated Sensing and Communication in IR...

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IEEE Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

作者： Renwang Li Xiaodan Shao Shu Sun Meixia Tao Rui Zhang Department of Electronic Engineering Shanghai Jiao Tong University Shanghai China Shanghai Key Laboratory of Digital Media Processing and Transmission Shanghai Jiao Tong University Shanghai China School of Science and Engineering Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Shenzhen China Department of Electrical and Computer Engineering National University of Singapore Singapore

This paper investigates an intelligent reflecting surface (IRS) aided millimeter-wave integrated sensing and communication (ISAC) system. Specifically, based on the passive beam scanning in the downlink, the IRS finds the optimal beam for reflecting the signals from the base station to a communication user. Meanwhile, the IRS estimates the angle of a nearby target based on its echo signal received by the sensing elements mounted on the IRS (i.e., semi-passive IRS). We propose an ISAC protocol for achieving the above objective via simultaneous (beam) training and sensing (STAS). Then, we derive the achievable rate of the communication user and the Cramer-Rao bound (CRB) of the angle estimation for the sensing target in closed-form. The achievable rate and CRB exhibit different performance against the duration of beam scanning. Specifically, the average achievable rate initially rises and subsequently declines, while the CRB monotonically decreases. Consequently, the duration of beam scanning should be carefully selected to balance communication and sensing performance. Simulation results have verified our analytical findings and shown that, thanks to the efficient use of downlink beam scanning signal for simultaneous communication and target sensing, the STAS protocol outperforms the benchmark protocol with orthogonal beam training and sensing.

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FLaaS6G: Federated Learning as a Service in 6G Using Distributed Data Management architecture

FLaaS6G: Federated Learning as a Service in 6G Using Distrib...

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GLOBECOM 2022 - 2022 IEEE Global Communications Conference

作者： Wenxuan Ye Xueli Ant Xueqiang Yan Mohammad Hamad Sebastian Steinhorst Department of Electrical and Computer Engineering Technical University of Munich Advanced Wireless Technology Laboratory Munich Research Center Huawei Technologies Duesseldorf GmbH Wireless Technology Lab 2012 Laboratories Huawei Technologies Co. Ltd

ISBN: (纸本)9781665435413

AI/ML is envisioned to play an essential role in 6G mobile communication systems. The privacy-preserving capabil-ities of Federated Learning (FL) make it promising in vertical applications; however, the central server-based system and lack of trusted data management limit its widespread use. To effectively support FL as a service from a network architecture perspective, this work provides a comprehensive design including three key features: First, the network architecture enables transparent and traceable data management based on Distributed Ledger Technology (DLT) platform, and realizes distributed and off-chain data storage by adopting Distributed Data Storage Entity (DDSE). Second, the central aggregator of an FL service is decoupled from the data management scheme mentioned above, and is decentralized through smart contracts for aggregator selection among a set of aggregator candidates, with the selected aggregator subsequently responsible for client selection and model aggregation. Third, a completed set of procedures for FL services operations is defined. A simulation system is developed to verify the feasibility of the proposed architecture and to study the impact of introducing the data management mechanisms on the overall performance overhead. The results show that the impact is related to the FL settings, with a worst-case time overhead of 15% observed in selected test cases, i.e., 15% of the total time spent on the interactions with the DLT platform and DDSE.

关键词： 6G mobile communication Distributed ledger Federated learning Smart contracts Memory Distributed databases Network architecture

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A Buoyant Bio-Solar Cell Array with Long-Lasting High-Power Output: Energy Harvesting from Aquatic Environments

A Buoyant Bio-Solar Cell Array with Long-Lasting High-Power ...

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Micro and Nanotechnology for Power Generation and Energy Conversion Applications (PowerMEMS)

作者： Anwar Elhadad Maryam Rezaie Seokheun Choi Department of Electrical & Computer Engineering Bioelectronics & Microsystems Laboratory State University of New York (SUNY) at Binghamton New York USA SUNY Center for Research in Advanced Sensing Technologies & Environmental Sustainability New York Binghamton USA

ISBN: (纸本)9781665493079

Miniaturized bio-solar cells have emerged as a potential sustainable power source for the Internet of Things (IoT) applications deployed in unattended, difficult-to-reach aquatic environments such as oceans, rivers, and lakes. Here, we create a scalable, high-power, long-lasting, and buoyant bio-solar cell stack that integrates significantly improved miniature bio-solar cells in an array. Each cell incorporates a symbiotic microbial consortium consisting of Synechocystis sp. PCC6803 and Bacillus subtilis. While Synechocystis sp. generates electricity through its photosynthetic and respiratory activities, it produces an organic fuel through its photosynthesis, which sustains B. subtilis in the consortium. Each cell was able to generate a sustainable maximum power density of ~70 μWcm −2 .

关键词： Wireless communication Symbiosis Wireless sensor networks Power system measurements Oceans Rivers Internet of Things

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Joint Optimization of Transmit Power and Trajectory for UAV-Enabled Data Collection With Dynamic Constraints

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IEEE Transactions on Communications 2025年

作者： Zhang, Hongyun Li, Bin Rong, Yue Zeng, Yong Zhang, Rui School of Aeronautics and Astronautics Sichuan University Sichuan Chengdu610065 China The School of Electrical Engineering Computing and Mathematical Sciences Curtin University GPO Box U1987 PerthWA6845 Australia National Mobile Communications Research Laboratory Southeast University Jiangsu Nanjing210096 China The Purple Mountain Laboratories Nanjing211111 China School of Science and Engineering Shenzhen Research Institute of Big Data The Chinese University of Hon g Kong Guangdong Shenzhen518172 China The Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore

The unmanned aerial vehicle (UAV)-enabled data collection system with a rotary-wing UAV and multiple ground nodes (GNs) is investigated in this paper. The average transmission data rate is maximized through the coordinated optimization of the GNs’ transmit power and the UAV’s trajectory. In particular, the UAV dynamic constraints and physical constraints are imposed. The UAV dynamics, which are governed by a group of differential equations, are usually ignored in existing works. As a consequence, the planned trajectory cannot be fully tracked by the controller in real world applications, which could lead to severe performance degradation. Thus, a control-based method is devised to address this issue. Specifically, by adopting the state-space model from control theory, the data collection problem is established as a dynamic optimization problem subject to state constraints, in which both of the decision variables and constraints are infinite-dimensional in nature. The key idea of the solution method is to convert the infinite-dimensional dynamic program into a finite-dimensional static nonlinear problem. This is achieved by deriving the required gradients of the dynamic optimization problem based on the control parametrization scheme and an exact penalty function method. The effectiveness and superiority of the proposed design are validated via numerical experiments. © 1972-2012 IEEE.

关键词： State space methods

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Comparative Study of Nonlinear Black-Box Modeling for Power Electronics Converters

Comparative Study of Nonlinear Black-Box Modeling for Power ...

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IEEE Energy Conversion Congress and Exposition, ECCE

作者： Liang Qiao Yaosuo Xue Yonghao Gui Wei Du Fei Fred Wang Department of Electrical Engineering and Computer Science The University of Tennessee Knoxville Knoxville USA Electrification and Energy Infrastructures Division Oak Ridge National Laboratory Oak Ridge USA Electricity Infrastructure and Buildings Division Pacific Northwest National Laboratory Richland USA The University of Tennessee Knoxville Knoxville USA Oak Ridge National Laboratory Knoxville USA

With the increasing penetration level of renewable sources and power electronics loads in modern power systems, accurate and computationally efficient models are needed. Black-box model (BBM) could be a useful method in such systems. However, not very extensive research efforts have been made for power electronics BBM so far, and existing works mostly focus on steady-state operation, neglecting the important transient behaviors such as load transients, voltage transients, and faults. This paper presents a comparative study of three commonly used nonlinear BBM approaches for transient behaviors of power electronics converters. Comparison methods are proposed, and the evaluations are conducted under different transients using a grid-connected single-phase photovoltaic inverter. The findings of this study provide valuable references for further feasibility investigations on implementing BBMs in large-scale power electronics-rich power systems.

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Agent-based Simulation Evaluation of CBD Tolling: A Case Study from New York City

arXiv

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arXiv 2024年

作者： Liang, Qingnan Yao, Ruili Zhang, Ruixuan Chen, Zhibin Wu, Guoyuan The Department of Civil and Urban Engineering New York University New York United States Key Laboratory of Urban Design and Urban Science NYU Shanghai Shanghai China The Department of Electrical and Computer Engineering University of California Riverside RiversideCA United States Shanghai Frontiers Science Center of Artificial Intelligence and Deep Learning NYU Shanghai Shanghai China The Center of Environmental Research and Technology University of California Riverside RiversideCA United States

Congestion tollings have been widely developed and adopted as an effective tool to mitigate urban traffic congestion and enhance transportation system sustainability. Nevertheless, these tolling schemes are often tailored on a city-by-city or even area-by-area basis, and the cost of conducting field experiments often makes the design and evaluation process challenging. In this work, we leverage MATSim, a simulation platform that provides microscopic behaviors at the agent level, to evaluate performance on tolling schemes. Specifically, we conduct a case study of the Manhattan Central Business District (CBD) in New York City (NYC) using a fine-granularity traffic network model in the large-scale agent behavior setting. The flexibility of MATSim enables the implementation of a customized tolling policy proposed yet not deployed by the NYC agency while providing detailed interpretations. The quantitative and qualitative results indicate that the tested tolling program can regulate the personal vehicle volume in the CBD area and encourage the usage of public transportation, which proves to be a practical move towards sustainable transportation systems. More importantly, our work demonstrates that agent-based simulation helps better understand the travel pattern change subject to tollings in dense and complex urban environments, and it has the potential to facilitate efficient decision-making for the devotion to sustainable traffic management. Copyright © 2024, The Authors. All rights reserved.

关键词： Simulation platform

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A Novel Fault Section Identification Method for Smart

SSRN

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SSRN 2023年

作者： Wang, Tao Cheng, Liang Liu, Wei Wang, Peng Pérez-Jiménez, Mario J. Key Laboratory of Fluid and Power Machinery Ministry of Education Xihua University 610039 China School of Electrical Engineering and Electronic Information Xihua University Chengdu610039 China School of Electrical and Electronic Engineering Nanyang Technological University 639798 Singapore Department of Computer Science and Artificial Intelligence University of Sevilla Avda. Reina Mercedes s/n 41012 Spain

This paper deals with the fault section identification problem for smart electrical substations considering information tampering, which involves the information fusion of multiple types of fault alarm data including remote measurements, action information of protection devices and temporal information. The developed methodology should be used after the occurrence of failures with definitive disconnections of protection devices and before the beginning of power supply restoration. It consists of three modules, namely find suspicious fault sections, evaluate the uncertain degree of remote measurements and identify fault sections. Concretely, a fuzzy C-means algorithm is employed to find suspicious fault sections in module 1. In module 2, an amplitude sequence point constraint and a time sequence point constraint are designed to calculate point membership matrices, which are used to compute the gregarious coefficient of voltages for each suspicious section, so as to evaluate the uncertain degree of its remote measurements. To improve the fault tolerance and diagnostic accuracy of proposed method, in module 3, a multi-pulse spiking neural P system and its multi-pulse matrix reasoning algorithm are designed to comprehensively fuse the multi-source fault alarm data. Case studies on the realistic 110kV and 500kV substations demonstrate the feasibility and effectiveness of the proposed method. © 2023, The Authors. All rights reserved.

关键词： Fault tolerance

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