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arXiv 2022年

作者： Kabir, Md Faiyaz Mia, Md Borhan Ahmed, Ishtiaque Jaidye, Nafiz Ahmed, Syed Z. Kim, Sangsik Department of Electrical and Computer Engineering Texas Tech University LubbockTX79409 United States Department of Physics and Astronomy Texas Tech University LubbockTX79409 United States School of Electrical Engineering Korea Advanced Institute of Science and Technology Daejeon34141 Korea Republic of

Electromagnetic coupling via exponentially decaying evanescent field or radiative wave is a primary characteristic of light, allowing optical signal/power transfer but limiting integration density in a photonic circuit. A leaky mode combines both evanescent field and radiative wave, causing stronger coupling and thus not ideal for dense integration. Here we show that a leaky mode with anisotropic perturbation rather can achieve completely zero crosstalk realized by subwavelength grating (SWG) metamaterials. The oscillating fields in the SWGs enable coupling coefficients in each direction to counteract each other, resulting in completely zero crosstalk. We experimentally demonstrate such an extraordinarily low coupling between closely spaced identical leaky SWG waveguides, suppressing the crosstalk by ≈40 dB compared to conventional strip waveguides, corresponding to ≈100 times longer coupling length. This leaky-SWG suppresses the crosstalk of transverse–magnetic (TM) mode, which is challenging due to its low confinement, and marks a novel approach in electromagnetic coupling applicable to other spectral regimes and generic devices. Copyright © 2022, The Authors. All rights reserved.

关键词： Crosstalk

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Enhanced Labeling Technique for Reddit Text and Fine-Tuned Longformer Models for Classifying Depression Severity in English and Luganda

Enhanced Labeling Technique for Reddit Text and Fine-Tuned L...

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International Conference on Information and Communication Technology Convergence (ICTC)

作者： Richard Kimera Daniela N. Rim Joseph Kirabira Ubong Godwin Udomah Heeyoul Choi Department of Advanced Convergence Handong Global University Pohang South Korea School of Computer Science and Electrical Engineering Handong Global University Pohang South Korea Department of Psychiatry Busitema University (Faculty of Health Sciences) Mbale Uganda Department of Psychiatry University of Uyo Teaching Hospital Uyo Akwa Ibom Nigeria

Depression is a global burden and one of the most challenging mental health conditions to control. Using the BDI questionnaire, experts can detect its severity early, administer appropriate medication to patients, and impede its progression. Owing to the fear of potential stigmatization, many patients turn to social media platforms such as Reddit for advice and assistance at various stages of their journey. This research extracts text from Reddit to facilitate the diagnostic process, employs a proposed labelling approach to categorize the text, and subsequently fine-tunes the Longformer model. The model’s performance is compared against the baseline models, including Naive Bayes, Random Forest, Support Vector Machines, and Gradient Boosting. Our findings reveal that the Longformer model outperforms the baseline models in both English (48%) and Luganda (45%) languages on a custom-made dataset.

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Current and future directions in network biology

arXiv

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arXiv 2023年

作者： Zitnik, Marinka Li, Michelle M. Wells, Aydin Glass, Kimberly Gysi, Deisy Morselli Krishnan, Arjun Murali, T.M. Radivojac, Predrag Roy, Sushmita Baudot, Anaïs Bozdag, Serdar Chen, Danny Z. Cowen, Lenore Devkota, Kapil Gitter, Anthony Gosline, Sara Gu, Pengfei Guzzi, Pietro H. Huang, Heng Jiang, Meng Kesimoglu, Ziynet Nesibe Koyuturk, Mehmet Ma, Jian Pico, Alexander R. Pržulj, Nataša Przytycka, Teresa M. Raphael, Benjamin J. Ritz, Anna Sharan, Roded Shen, Yang Singh, Mona Slonim, Donna K. Tong, Hanghang Yang, Xinan Holly Yoon, Byung-Jun Yu, Haiyuan Milenković, Tijana Department of Biomedical Informatics Harvard University United States Department of Computer Science and Engineering University of Notre Dame United States Lucy Family Institute for Data and Society University of Notre Dame United States Eck Institute for Global Health University of Notre Dame United States Channing Division of Network Medicine Brigham and Women’s Hospital Harvard Medical School United States Department of Statistics Federal University of Paraná Brazil Department of Physics Northeastern University United States Department of Biomedical Informatics University of Colorado United States Department of Computer Science Virginia Tech United States Khoury College of Computer Sciences Northeastern University United States Department of Biostatistics and Medical Informatics University of Wisconsin-Madison United States Wisconsin Institute for Discovery United States Aix Marseille Université INSERM MMG Marseille France Department of Computer Science and Engineering University of North Texas United States Department of Mathematics University of North Texas United States Department of Computer Science Tufts University United States Morgridge Institute for Research United States Pacific Northwest National Laboratory United States Department of Medical and Surgical Sciences University Magna Graecia of Catanzaro Italy Department of Computer Science University of Maryland College Park United States National Center of Biotechnology Information National Library of Medicine National Institutes of Health Department of Computer and Data Sciences Case Western Reserve University United States Computational Biology Department School of Computer Science Carnegie Mellon University United States Institute of Data Science and Biotechnology Gladstone Institutes Department of Computer Science University College London United Kingdom ICREA Catalan Institution for Research and Advanced Studies Spain Department of Computer Science Princeton University United States Departmen

Network biology is an interdisciplinary field bridging computational and biological sciences that has proved pivotal in advancing the understanding of cellular functions and diseases across biological systems and scales. Although the field has been around for two decades, it remains nascent. It has witnessed rapid evolution, accompanied by emerging challenges. These challenges stem from various factors, notably the growing complexity and volume of data together with the increased diversity of data types describing different tiers of biological organization. We discuss prevailing research directions in network biology and highlight areas of inference and comparison of biological networks, multimodal data integration and heterogeneous networks, higher-order network analysis, machine learning on networks, and network-based personalized medicine. Following the overview of recent breakthroughs across these five areas, we offer a perspective on the future directions of network biology. Additionally, we offer insights into scientific communities, educational initiatives, and the importance of fostering diversity within the field. This paper establishes a roadmap for an immediate and long-term vision for network biology. © 2023, CC BY.

关键词： Machine learning

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Overview of Ancillary Services in the Nigerian Power Sector 2

Overview of Ancillary Services in the Nigerian Power Sector

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2nd International Conference on Multidisciplinary engineering and Applied science, ICMEAS 2023

作者： Saka, Bemdoo Hussein, Suleiman U. Ishola, Biliaminu A. Mohammed, Yekini S. Hembe, Nanen D. Mustapha, Umar M. Thomas, Sadiq Nile University of Nigeria Dept. of Electrical/Electronics Eng. Abuja Nigeria Centre for Satellite Tech. Development Nat. Space Research and Dev. Agency Abuja Nigeria National Control Center Transmission Company of Nigeria Osogbo Abuja Nigeria Federal Polytechnic Nasarawa Dept. of Electrical/Electronics Eng. Nasarawa Nigeria Nasarawa State University Department of Geography Nasarawa Nigeria Advanced UAV Laboratory Nat. Space Research and Dev. Agency Abuja Nigeria Nile University of Nigeria Dept. of Computer Engineering Abuja Nigeria

ISBN: (纸本)9798350358834

An overview of the ancillary services in the Nigerian power sector is provided in this work. These services are essential in the power system because they are additional services required by the grid during critical times to enable the power grid to operate in a stable, safe, and reliable manner. The ancillary services provided as stipulated in the Grid Code are black start, frequency control, operating reserves, and voltage control. The System Operator procures the relevant ancillary service depending on the requirement of the grid at a particular time. The paper further presents some ways of improving the viability of ancillary services for the energy grid of Nigeria. These include making incentives more attractive for suppliers of ancillary services, utilizing more hydroelectric power plants for generation and load balancing, integrating distributed generation to provide support to the reactive power, and making necessary investments in the grid. © 2023 IEEE.

关键词： Hydroelectric power plants

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Semi-Federated Learning: Convergence Analysis and Optimization of A Hybrid Learning Framework

arXiv

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arXiv 2023年

作者： Zheng, Jingheng Ni, Wanli Tian, Hui Gündüz, Deniz Quek, Tony Q.S. Han, Zhu The State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing100876 China The Department of Electrical and Electronic Engineering Imperial College London LondonSW7 2AZ United Kingdom Modena41100 Italy The Singapore University of Technology and Design 487372 Singapore The Department of Electronic Engineering Kyung Hee University Yongin17104 Korea Republic of The Department of Electrical and Computer Engineering University of Houston HoustonTX77004 United States The Department of Computer Science and Engineering Kyung Hee University Seoul446-701 Korea Republic of

Under the organization of the base station (BS), wireless federated learning (FL) enables collaborative model training among multiple devices. However, the BS is merely responsible for aggregating local updates during the training process, which incurs a waste of the computational resource at the BS. To tackle this issue, we propose a semi-federated learning (SemiFL) paradigm to leverage the computing capabilities of both the BS and devices for a hybrid implementation of centralized learning (CL) and FL. Specifically, each device sends both local gradients and data samples to the BS for training a shared global model. To improve communication efficiency over the same time-frequency resources, we integrate over-the-air computation for aggregation and non-orthogonal multiple access for transmission by designing a novel transceiver structure. To gain deep insights, we conduct convergence analysis by deriving a closed-form optimality gap for SemiFL and extend the result to two extra cases. In the first case, the BS uses all accumulated data samples to calculate the CL gradient, while a decreasing learning rate is adopted in the second case. Our analytical results capture the destructive effect of wireless communication and show that both FL and CL are special cases of SemiFL. Then, we formulate a non-convex problem to reduce the optimality gap by jointly optimizing the transmit power and receive beamformers. Accordingly, we propose a two-stage algorithm to solve this intractable problem, in which we provide the closed-form solutions to the beamformers. Extensive simulation results on two real-world datasets corroborate our theoretical analysis, and show that the proposed SemiFL outperforms conventional FL and achieves 3.2% accuracy gain on the MNIST dataset compared to state-of-the-art benchmarks. Copyright © 2023, The Authors. All rights reserved.

关键词： Efficiency

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Darlington pair of quantum thermal transistors

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Physical Review B 2021年第4期104卷 045405-045405页

作者： Ravi T. Wijesekara Sarath D. Gunapala Malin Premaratne Advanced Computing and Simulation Laboratory(AχL) Department of Electrical and Computer Systems Engineering Monash University Clayton Victoria 3800 Australia Jet Propulsion Laboratory California Institute of Technology Pasadena California 91109 USA

Recent progress in manipulating individual quantum systems has led to the development of quantum thermal transistors, which control the thermal conductivity between two of its terminals according to an input signal on its third terminal. With several models for individual thermal transistors already developed, the next natural step is to investigate how multiple thermal transistors can interconnect to build useful composite devices. In electronics literature, the Darlington pair is a two-transistor configuration commonly used to construct electronic amplifiers with higher gain than is possible with a single transistor. We create the electronic Darlington pair's thermal equivalent using two individual thermal transistors in a similar configuration. Unlike previously studied models, multitransistor configurations like this contain internal transistor interconnections whose temperatures cannot be biased externally but are determined by the individual transistors' internal dynamics. We refine previous models to incorporate these transistor-transistor interactions and introduce an intermediate thermal bath to facilitate the thermal energy exchange between the Darlington pair transistors. We investigate temperature-based and optical field-based control strategies of the Darlington pair in terms of both steady-state and transient thermal flow characteristics through numerical simulations. Under both control strategies, the thermal Darlington pair's steady-state performance exhibits superior thermal amplification, sensitivity, and thermodynamic efficiency than an equivalent single thermal transistor. Our results closely mirror those expected from the corresponding electronic Darlington pair. Hence, we envision that we may readily adapt the intermediate bath formalism we developed in this work to translate a wide variety of useful electronic multitransistor configurations to their thermal equivalents.

关键词： Thermal properties Nanostructures Transistors

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Coherent Acoustic Phonons in Bi2Se3 Ultrathin Films Probed by Femtosecond, Optical Pump-Probe Spectroscopy

Coherent Acoustic Phonons in Bi2Se3 Ultrathin Films Probed b...

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CLEO: Fundamental science, CLEO:FS 2024 - Part of Conference on Lasers and Electro-Optics, CLEO 2024

作者： Cheng, Jing Niherysh, Kiryl A. Francis, Peter Chakraborty, Debamitra Lombardi, Floriana Erts, Donats Prischepa, Serghej L. Laszcz, Adam Komissarov, Ivan V. Sobolewski, Roman Materials Science Graduate Program University of Rochester RochesterNY14627 United States Laboratory for Laser Energetics University of Rochester RochesterNY14623-1299 United States Department of Microtechnology and Nanoscience Chalmers University of Technology Gothenburg Sweden Institute of Chemical Physics University of Latvia Riga Latvia Department of Electrical and Computer Engineering University of Rochester RochesterNY14627 United States Dipartimento di Fisica "E.R. Caianiello" Università degli Studi di Salerno Sa FiscianoI-84084 Italy Lukasiewicz Research Network Institute of Microelectronics and Photonics WarszawaPL-02668 Poland

ISBN: (纸本)9781957171395

The dynamics of coherent acoustic phonons in the Bi2Se3 layered crystal system are investigated. The findings reveal that the frequency evolution of breathing modes with the number of the material quintuple layers and the dispersion relation both can be explained by a modified chain model with a nonuniform coupling force. © Optica Publishing Group 2024, © 2024 The Author(s)

关键词： Ultrathin films

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Recent advances in optical dynamic metaholography

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Opto-Electronic Advances 2021年第11期4卷 27-45页

作者： Hui Gao Xuhao Fan Wei Xiong Minghui Hong Wuhan National Laboratory for Optoelectronics School of Optical and Electronic InformationHuazhong University of Science and TechnologyWuhan 430074China Department of Electrical and Computer Engineering National University of SingaporeEngineering Drive 3Singapore 117576Singapore

Holography,with the capability of recording and reconstructing wavefronts of light,has emerged as an ideal approach for future deep-immersive naked-eye ***,the shortcomings(e.g.,small field of view,twin imaging,multiple or-ders of diffraction)of traditional dynamic holographic devices bring many challenges to their practical ***,planar artificial materials composed of subwavelength unit cells,have shown great potential in light field manipulation,which is useful for overcoming these ***,we review recent progress in the field of dynamic metasurface holography,from realization methods to design strategies,mainly including typical research works on dy-namic meta-holography based on tunable metasurfaces and multiplexed *** applications of dynam-ic meta-holography have been found in 3D display,optical storage,optical encryption,and optical information pro-cessing,which may accelerate the development of light field manipulation and micro/nanofabrication with higher dimen-sions.A number of potential applications and possible development paths are also discussed at the end.

关键词： metasurface dynamic meta-holography tunable meta-holography multiplexed meta-holography

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Tensor Decomposition Based Relaxed Linear Regression for Hyperspectral Image Classification

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IEEE Transactions on Geoscience and Remote Sensing 2025年 63卷

作者： Deng, Yang-Jun Zhang, Lv-Wei Ren, Longfei Zhu, Xinghui Li, Heng-Chao Du, Qian Hunan Agricultural University College of Information and Intelligence Changsha410128 China Chinese Academy of Sciences Key Laboratory of Computational Optical Imaging Technology Aerospace Information Research Institute Beijing100094 China Southwest Jiaotong University School of Information Science and Technology Chengdu611756 China Mississippi State University Department of Electrical and Computer Engineering StarkvilleMS39762 United States

Linear regression and its variants have achieved considerable success in image classification. However, those methods still encounter two challenges when dealing with hyperspectral image (HSI) classification. On the one hand, the existing ones focus on mining the relationship between the label space and original data space during the classifier training, which is generally sensitive to noise corruptions. On the other hand, transforming the training samples into a strict binary label matrix makes the generalization ability of the classifier limited. To address these challenges, this paper constructs a novel integrative model called tensor decomposition-based relaxed linear regression (TDRLR) for HSI classification. Firstly, the model adopts tensor canonical polyadic (CP) decomposition to learn two dictionaries from spatial and spectral directions respectively, which can help to generate a double dictionary representation for HSI data. Then, the linear regression classifier is integrated to learn a transformation that reveals the mapping relation between the double dictionary representation and label space rather than the original data for enhancing robustness. Meanwhile, a more flexible way, label relaxation, is employed to enlarge the margins between different classes. More importantly, the learned double dictionary representation and classifier can be fine-tuned in tandem to enhance performance through the designed alternate iterative jointly learning algorithm. Experiments conducted on four real-world HSI datasets demonstrate that the proposed method achieves significant improvements in classification performance with a small size training set, when compared with state-of-the-art HSI classification methods. © 1980-2012 IEEE.

关键词： Linear transformations

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Secure state estimation over Markov wireless communication channels

Secure state estimation over Markov wireless communication c...

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IEEE Conference on Decision and Control

作者： Anastasia Impicciatore Anastasios Tsiamis Yuriy Zacchia Lun Alessandro D’Innocenzo George J. Pappas Department of Information Engineering Computer Science and Mathematics University of L’Aquila L’Aquila Italy Automatic Control Laboratory ETH Zürich Department of Electrical and Systems Engineering University of Pennsylvania Philadelphia PA United States

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

This note studies state estimation in wireless networked control systems with secrecy against eavesdropping. Specifically, a sensor transmits a system state information to the estimator over a legitimate user link, and an eavesdropper overhears these data over its link independent of the user link. Each connection may be affected by packet losses and is modeled by a finite-state Markov channel (FSMC), an abstraction widely used to design wireless communication systems. This paper presents a novel concept of optimal mean square expected secrecy over FSMCs and delineates the design of a secrecy parameter requiring the user mean square estimation error (MSE) to be bounded and eavesdropper MSE unbounded. We illustrate the developed results on an example of an inverted pendulum on a cart whose parameters are estimated remotely over a wireless link exposed to an eavesdropper.

关键词： Wireless communication Wireless sensor networks Estimation error Networked control systems Channel estimation Packet loss Markov processes

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