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Frontiers in Education (FIE) Conference

作者： Sujan Ghimire Muhtasim Alam Chowdhury Ryan Tsang Richard Yarnell Emma Heckert Jaeden Carpenter Yu-Zheng Lin Muntasir Mamun Ronald F. DeMara Setareh Rafatirad Pratik Satam Soheil Salehi Department of Systems and Industrial Engineering University of Arizona Tucson AZ Department of Electrical and Computer Engineering University of Arizona Tucson AZ Department of Electrical and Computer Engineering University of California Davis Davis CA Department of Electrical and Computer Engineering University of Central Florida Orlando FL Department of Computer Science University of California Davis Davis CA

ISBN: (数字)9798350351507

ISBN: (纸本)9798350363067

This research-to-practice paper presents a novel pedagogical tool for hardware cybersecurity education and workforce development. The growing importance of hardware security has made it essential for individuals and organizations to understand hardware security principles and best practices. However, the current educational curriculum falls short of fulfilling these emerging demands due to the rapidly changing hardware security landscape and limited opportunities for hands-on training. To address these challenges, we propose and have developed the Interactive Hardware and Cybersecurity (I-HaC) Educational Framework, a pedagogical educational framework that supplements existing courses by leveraging generative AI for individualized instruction related to hardware and cybersecurity, data mining, and applied Machine Learning (ML), as well as data visualization to enhance cybersecurity education and workforce development. The framework is designed to be utilized by graduate and undergraduate electrical and computer engineering (ECE) and computer science (CS) students for a comprehensive introduction to cybersecurity exploits and countermeasures in an interactive manner with hands-on components. Using I-HaC, we have developed tailored lab components for a diverse range of students and intend to release I-HaC as open-source for the benefit of the ECE and CS education community.

关键词： Training Generative AI Databases Hardware security Data visualization Organizations Machine learning Ontologies computer security Protection

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Highly Sensitive Refractive Index Sensing Based on Microwave-Photonic Hybrid Optical Fiber Interferometers

Highly Sensitive Refractive Index Sensing Based on Microwave...

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Frontiers in Optics + Laser science 2023, FiO, LS 203: Part of Frontiers in Optics + Laser science 2023

作者： Zhu, Chen Huang, Jie Research Center for Optical Fiber Sensing Zhejiang Laboratory Hangzhou311100 China Department of Electrical and Computer Engineering Missouri University of Science and Technology RollaMO65409 United States

A simple yet new sensing method for measurements of refractive index based on microwave-photonic hybrid optical fiber interferometers (optically coherent and incoherent) is proposed and experimentally demonstrated. &#... 详细信息

ISBN: (纸本)9781957171296

关键词： Fabry Perot interferometers Fiber optic couplers Index measurements Long period fiber gratings Optical fibers Tilted fiber Bragg gratings

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Employing the Vernier Effect for Sensitivity Enhancement in a Distributed Optical Fiber Sensor

Employing the Vernier Effect for Sensitivity Enhancement in ...

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

Distributed optical fiber sensing based on microwave photonics with significantly improved and tunable sensitivity enabled by the distributed Vernier effect is demonstrated. © Optica Publishing Group 2023.

ISBN: (纸本)9781957171258

关键词： Optical fibers

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Leidenfrost droplet billiard balls

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Physical Review Fluids 2024年第11期9卷 L111601-L111601页

作者： Yukai Lin Canjun Zhao Fuqiang Chu Xiaomin Wu Nenad Miljkovic Key Laboratory for Thermal Science and Power Engineering of Ministry of Education Department of Energy and Power Engineering Tsinghua University Beijing 100084 China School of Energy and Environmental Engineering University of Science and Technology Beijing Beijing 100083 China Department of Mechanical Science and Engineering University of Illinois at Urbana-Champaign Urbana Illinois 61801 USA Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign Urbana Illinois 61801 USA Materials Research Laboratory University of Illinois at Urbana-Champaign Urbana Illinois 61801 USA Institute for Sustainability Energy and Environment (iSEE) University of Illinois Urbana Illinois USA International Institute for Carbon Neutral Energy Research (WPI-I2CNER) Kyushu University 744 Moto-oka Nishi-ku Fukuoka 819-0395 Japan

We report the observation of two identical Leidenfrost droplets rebounding from each other after a head-on collision on a hot surface, resembling billiard ball collision. The observed phenomenon contradicts the established understanding that predicts the coalescence of two colliding Leidenfrost droplets. The collision dynamics of the Leidenfrost droplets is investigated using pressure and energy balance analysis at the macroscale, and a molecular interaction analysis at the nanoscale. The results suggest that droplet properties and the temperature of the hot surface determine the state of the gas film between the colliding droplets. Droplets with lower surface tension form thicker gas films, while lower surface temperatures mitigate the interaction of vapor molecules within the gas film, both facilitating droplet rebound after their collision. The discovered Leidenfrost droplet phenomenon is highly controllable, and has potential for a variety of applications, such as the selective chemical synthesis as explored in this work.

关键词： Drop & bubble phenomena Heat transfer Multiphase flows Surface & interfacial phenomena

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Limitations of nearest-neighbor quantum networks

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Physical Review A 2022年第1期106卷 L010401-L010401页

作者： F. Hahn A. Dahlberg J. Eisert A. Pappa Dahlem Center for Complex Quantum Systems Freie Universität Berlin 14195 Berlin Germany Department of Electrical Engineering and Computer Science Technische Universität Berlin 10587 Berlin Germany QuTech TU Delft 2628CJ Delft The Netherlands Fraunhofer Heinrich Hertz Institute 10587 Berlin Germany Department of Electrical Engineering and Computer Science Technische Universität Berlin 10587 Berlin Germany Fraunhofer Institute for Open Communication Systems-FOKUS 10589 Berlin Germany

Quantum communication research has in recent years shifted to include multipartite networks for which questions of quantum network routing naturally emerge. To understand the potential for multipartite routing, we focus on the most promising architectures for future quantum networks—those connecting nodes close to each other. Nearest-neighbor networks, such as rings, lines, and grids, have been studied under different communication scenarios to facilitate the sharing of quantum resources especially in the presence of bottlenecks. We analyze the potential of nearest-neighbor entangling gate quantum networks and identify some serious limitations by demonstrating that rings and lines cannot overcome common bottleneck communication problems.

关键词： Entanglement manipulation Quantum communication Quantum entanglement Quantum information theory Quantum networks Quantum repeaters

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Mixture of Gradient: A Unified Enhancing Approach for Deep Learning-Based Wireless Network Optimization

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IEEE Internet of Things Journal 2025年第13期12卷 25487-25499页

作者： Cheng, Nan Ma, Longfei Dai, Yanpeng Wang, Xiucheng Li, Qihao Quan, Wei Liang, Hui Dongguan University of Technology School of Electrical Engineering and Intelligentization Dongguan523808 China Xidian University State Key Laboratory of ISN and School of Telecommunications Engineering Xi’an710071 China Dalian Maritime University School of Information Science and Technology Dalian116026 China Jilin University College of Communication Engineering Jilin Changchun130021 China Beijing Jiaotong University School of Electronic and Information Engineering Beijing100044 China Peng Cheng Laboratory Shenzhen518000 China University of Waterloo Department of Electrical and Computer Engineering WaterlooN2L 3G1 Canada

Deep learning plays increasingly important role in future wireless network management and optimization. Existing training methods such as label-based supervised learning and label-free learning have inherent limitations. The performance of supervised learning is limited by labels, while label-free training methods require extensive exploration. To address these limitations, this paper proposes a novel mixture of gradients (MoG) method, which integrates gradients from different sources within the training process in order to improve the convergence performance of neural networks (NNs). Particularly, MoG is a modular, plug-and-play solution requiring no structural modifications to existing NNs. Its implementation necessitates only minor modifications to the loss function, where the label-based supervised loss is combined with a label-free loss through weighted summation. The label-free loss can be either unsupervised loss or reinforcement learning loss. This flexibility allows seamless integration into nearly all NN-based methods, making it applicable to a wide range of wireless optimization problems with minimal implementation cost. Extensive simulations across multiple classic wireless scenarios demonstrate that MoG can significantly enhance the performance of NN decision-making, leading to higher transmission rates. © 2014 IEEE.

关键词： Self-supervised learning

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Redundant Weighted Clustered Scheme with Dynamic Weights Adjustment for Damaged S-UAV

Redundant Weighted Clustered Scheme with Dynamic Weights Adj...

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IEEE International Conference on Communications (ICC)

作者： Grace Khayat Constandinos X Mavromoustakis Andreas Pitsillides Jordi Mongay Batalla Evangelos K. Markakis Department of Computer Science Mobile Systems Laboratory (MoSys Lab) University of Nicosia Nicosia Cyprus Department of Computer Science University of Cyprus Cyprus Department of Electrical & Electronic Engineering Science University of Johannesburg (Visiting Professor) Warsaw University of Technology Warsaw Poland Department of Electrical and Computer Engineering Hellenic Mediteranean University Estavromenos Heraklion Greece

ISBN: (数字)9781728190549

ISBN: (纸本)9781728190556

Swarm of UAVs (S-UAVs) is the term used to describe an unplanned gathering of un-manned aerial vehicles (UAVs) that collaborate to complete predefined missions. Any UAV has a risk of being damaged in crisis situations like fire. Clustering is one of the most often used routing algorithms in S-UAVs. The clustering scheme divides the UAVs into clusters, with a cluster head (CH) and cluster members (CM) in each cluster. The CH plays a critical role within inter-cluster communication, and because of this, its selection is an ongoing area of study. A clustered weighted scheme with redundancy and dynamic weight adjustment is proposed in this paper. The selection of the principal CH, redundant CHs, and CMs is based on a weighted formula composed of distance, speed, and rewarding index. Whenever the primary CH is damaged, the redundant CH takes its place immediately. After the first clustering process, the proposed scheme dynamically and autonomously adjusts the weights to optimize the UAV role selection. According to the outcomes of the carried-out simulation, this is a promising scheme that reduces data loss in a crisis-case scenario and optimizes the time delay through the dynamic adjustments of the weights.

关键词： Delay effects Redundancy Clustering algorithms Routing Autonomous aerial vehicles Indexes Vehicle dynamics

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Accelerating Deep Neural Networks with a Low-Cost Lossless Compression

Accelerating Deep Neural Networks with a Low-Cost Lossless C...

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2025 International Conference on Electronics, Information, and Communication, ICEIC 2025

作者： Kim, Seongwook Byeon, Gwangeun Lee, Seungeui Bae, Youngseok Hong, Seokin Sungkyunkwan University Department of Electrical and Computer Engineering Suwon Korea Republic of Advanced R&D Center Hanwha Systems Co. Ltd. Korea Republic of Agency for Defense Development Emerging Science and Technology Directorate Korea Republic of

ISBN: (纸本)9798331510756

Since deep learning inference involves a significant amount of computations, there have been a lot of efforts to accelerate the inference process by eliminating ineffectual compu-tations. As a solution to this problem, several sparsity-aware deep learning accelerators have been proposed. These accelerators perform the inference on compressed data (filters and feature maps) and dynamically remove the ineffectual multiplications with zero operands. For efficiently handling the compressed data on the accelerators, a simple and effective compression scheme, which encodes the whole data with its nonzero values and their positions, is necessary. However, prior approaches have several shortcomings, such as low compression efficiency and high complexity in compression and decompression hardware. This paper proposes a low-cost compression scheme that can be applied to sparsity-aware deep-learning accelerators. The compression scheme synergistically combines two low-cost compression schemes: Zero-Value Compression (ZVC) and Base-Delta-Immediate Compression (BDI). Our experimental evaluation shows that the proposed compression scheme achieves an average compression ratio of 2.26, resulting in 2.33x performance improvement, © 2025 IEEE.

关键词： Data handling

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Energy Management System for Photovoltaic-Battery-Fuel Cell using Arduino Board and Matlab Simulink

Energy Management System for Photovoltaic-Battery-Fuel Cell ...

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2022 IEEE Delhi Section Conference, DELCON 2022

作者： Barhoumi, El Manaa Zghaibeh, Manaf Okonkwo, Paul C. Hasan, Najam Ul Farhani, Slah Bacha, Faouzi College of Engineering Dhofar University Electrical and Computer Engineering Department Salalah Oman College of Engineering Dhofar University Mechanical and Mechatronic Engineering Department Salalah Oman Insat University of Carthage Laboratory of Computer and Industrial Systems Tunis Tunisia Ensit University of Tunis Department of Electrical Engineering Tunis Tunisia

ISBN: (纸本)9781665458832

This paper presents the design and implementation of an energy management system (EMS) for a renewable energy system using Matlab Simulink and Arduino Mega. The proposed renewable energy system is composed of an electrolyzer, a battery, photovoltaic modules, and fuel cells. The developed energy management is implemented on the Arduino board to control the connection of the different components to the load based on the load power consumption, the battery's charge state, and the energy produced by the photovoltaic modules. The energy management system inputs include the information on the amount of energy produced by the photovoltaic modules, the power used by the load, and the battery's charge state. When the produced energy exceeds the energy used by the load and the batteries are fully charged, the system allows the electrolyzer to connect to the photovoltaic modules to produce the hydrogen. Our proposed system is based on low cost technology that intends to extend the life of the batteries and enhance the efficiency of the renewable energy system by the production and using the hydrogen. The obtained experimental results show the effectiveness of the EMS in controlling the connection of the different components. © 2022 IEEE.

关键词： Energy management systems

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LIMIT THEOREMS FOR β-LAGUERRE AND β-JACOBI ENSEMBLES

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Acta Mathematica Scientia 2022年第5期42卷 2025-2039页

作者： Naqi HUANG Yutao MA Faculty of Electrical Engineering Mathematics and Computer ScienceDelft University of TechnologyMekelweg 42628 CD DelftThe Netherlands School of Mathematical Sciences&Laboratory of Mathematics and Complea Systems of Ministry of Education Beijing Normal UniversityBeijing 100875China

We use tridiagonal models to study the limiting behavior of β-Laguerre and β-Jacobi ensembles,focusing on the limiting behavior of the extremal eigenvalues and the central limit theorem for the two *** the central limit theorem of β-Laguerre ensembles,we follow the idea in[1]while giving a modified version for the generalized *** we use the total variation distance between the two sorts of ensembles to obtain the limiting behavior of β-Jacobi ensembles.

关键词： beta-ensembles largest and smallest eigenvalues central limit theorem total variationdistance

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