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30th IEEE Real-Time and Embedded Technology and Applications Symposium, RTAS 2024

作者： Hamid Miji, Md Kausar Liu, Mengyu Akowuah, Francis E Kong, Fanxin The South Dakota School of Mines and Technology Department of Electrical Engineering and Computer Science Rapid CitySD United States University of Notre Dame Department of Computer Science and Engineering South BendIN United States

ISBN: (纸本)9798350358414

Industries are embracing information technology and constructing more robust machines known as Cyber-Physical Systems(CPS) to automate processes. CPSs are envisioned to be pervasive, coordinating, and integrating computation, sensing, actuation, and physical processes. CPSs have various applications in life-critical scenarios, where their performance and reliability can have direct impacts on human safety and well-being. However, CPSs are vulnerable to malicious attacks, and researchers have developed detectors to identify such attacks in different contexts. Surprisingly, little work has been done to detect attacks on the actuators of CPS. Furthermore, actuators face a high risk of optimal hidden attacks designed by powerful attackers, which can push them into an unsafe state without detection. To the best of our knowledge, no such attacks on actuators have been developed yet. In this paper, we design an optimal hidden attack for actuators and evaluate its effectiveness. First, we develop a mathematical model for actuators and then create a linear program for convex optimization. Second, we solve the optimization problem and simulate the optimal attack. © 2024 IEEE.

关键词： Cyber Physical System

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Renewable Distributed Generation for Smart Highway Lighting 11

Renewable Distributed Generation for Smart Highway Lighting

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11th International Conference on Reliability, Infocom Technologies and Optimization, ICRITO 2024

作者： Channi, Harpreet Kaur Handa, Kanika Bhullar, Manpreet Sandhu, Ramandeep Kaur, Harpreet Singh, Parminder Vishal Chandigarh University Department of Electrical Engineering Mohali India Ct University Department of Computer Science and Engineering India School of Computer Science and Engineering Lovely Professional University India School of Computer Science and Engineering Lovely Professional University Punjab Jalandhar India Lovely Professional University Department of Cse Punjab Jalandhar India

ISBN: (纸本)9798350350357

Renewable energy generation is encouraging nowadays due to increasing demand day by day. At the commercial level, renewable energy generation is already in use. In this project, renewable energy generation is used on highways for lighting purposes. These energies are already wasted on highways by constructively using them, it can convert traditional highways into smart highways. The project consists combination of three energies, i.e. solar, wind, and piezoelectric energy. Many projects are already running on the highway in which individual energy or a combination of two energy is used for the generation. Still, with this project, three hybrid energy generation systems will be explained for the lighting on the highways. Initially, this system can cost more, but in the long term, it benefits more as well. This off-grid system can also further extend to supply back to the grid if satisfy the current usage on the highway. © 2024 IEEE.

关键词： Solar energy

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Maximizing Profit of the Service Providers through Efficient Content Placement and Retrieval in an IoT-enabled Edge-Cloud Platform 18

Maximizing Profit of the Service Providers through Efficient...

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18th IEEE International Conference on Advanced Networks and Telecommunications Systems, ANTS 2024

作者： Gandhi, Preet Mahanta, Abhishriya Ghose, Manojit Sahu, Aryabartta Indian Institute of Technology Department of Computer Science and Engineering Guwahati India Indian Institute of Technology School of Computing and Electrical Engineering Mandi India Indian Institute of Information Technology Department of Computer Science and Engineering Guwahati India

ISBN: (纸本)9798350391725

In today's 5G era, the amount of data generated by the Internet of Things (IoT) devices is enormous. Data is processed and stored in the cloud under a traditional cloud computing architecture, and real-time processing and retrieval of these data is time-consuming. Therefore, an edge-cloud framework comes in handy where the content generated is placed on the edge nodes of the network, and it can reach the endusers in a time-bound manner. A majority of the previous research works on content placement under the edge-cloud architecture primarily aimed at improving the latency of the system. However, the approach proposed in this paper aims to maximize the profit of the service provider by effectively placing the content in a hierarchically organized edge-cloud network. We propose two strategies and compare them with random and greedy approaches for both synthetic and real data sets. The experimental results demonstrate the effectiveness of the proposed strategies, and the profit of the service providers increases by 38.81% (maximum) and 10.51% (on average) for the synthetic dataset and by 65.74% (maximum) and 22.83% (on average) for the real-world dataset when compared with the greedy approach. © 2024 IEEE.

关键词： Cloud platforms

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DSTER: A Dual-Stream Transformer-based Emotion Recognition Model through Keystrokes Dynamics 18

DSTER: A Dual-Stream Transformer-based Emotion Recognition M...

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18th IEEE International Joint Conference on Biometrics, IJCB 2024

作者： Chen, Frank Rao, Shruti Tiwari, Brijesh Phoha, Vir V. Syracuse University Syracuse Department of Electrical Engineering and Computer Science New York13210 United States

ISBN: (纸本)9798350364132

Emotion Recognition is a critical research area for enhancing human-computer interaction. Keystroke dynamics, a behavioral biometric capturing typing patterns, offers a non-intrusive, user-friendly method for recognizing emotions. We propose a Dual-Stream Transformer-based Emotion Recognition (DSTER) model, which leverages keystroke dynamics to determine emotional states. The DSTER model features a dual-stream architecture that separately extracts temporal-over-channel and channel-over-temporal information. Each stream employs multi-head self-attention mechanisms, Long-Short Term Memory (LSTM), and Convolutional Neural Network (CNN) layers, along with dense vector embeddings of keycode data, to improve the extraction of temporal and contextual information from typing sequences. To the best of our knowledge, the DSTER model is the first to integrate transformer architecture with keystroke dynamics for emotion recognition. Our experiments on a widely-used fixed-text dataset demonstrate that the DSTER model significantly outperforms the three most recent baseline models, achieving average F1 scores up to 0.989 and an average accuracy increase of up to 66.04%. Unlike the significant performance variations reported in baseline models, the DSTER model maintains consistent and robust performance across all five tested emotional states. Further analysis shows that the model performs better with longer window lengths and greater overlaps. © 2024 IEEE.

关键词： Convolutional neural networks

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Excitonic Single- and Two-Photon Photoluminescence Excitations in Bilayer GaN/AlN Nanowires

Excitonic Single- and Two-Photon Photoluminescence Excitatio...

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2024 Conference on Lasers and Electro-Optics, CLEO 2024

作者： Cui, Liangqing Wu, You Wu, Yuanpeng Mi, Zetian Kira, Mackillo Norris, Theodore B. Department of Electrical Engineering and Computer Science University of Michigan Ann ArborMI48109 United States

The energy difference between the 1s and 2p exciton states of bilayer GaN/AlN is measured and computed by comparing excitonic resonances in photoluminescence excitation spectra following single- versus two-photon abso... 详细信息

ISBN: (纸本)9781957171395

关键词： Photoluminescence

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Enhanced Cross Z-Complementary Set and Its Application in Generalized Spatial Modulation

IEEE Open Journal of the Communications Society

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IEEE Open Journal of the Communications Society 2024年 5卷 4674-4690页

作者： Huang, Zhen-Ming Pai, Cheng-Yu Liu, Zilong Chen, Chao-Yu Institute of Computer and Communication Engineering National Cheng Kung University Tainan701 Taiwan National Cheng Kung University Department of Engineering Science Tainan701 Taiwan National Cheng Kung University Department of Electrical Engineering Tainan701 Taiwan University of Essex School of Computer Science and Electronic Engineering ColchesterCO4 3SQ United Kingdom

Generalized spatial modulation (GSM) is a novel multiple-antenna technique offering flexibility among spectral efficiency, energy efficiency, and the cost of RF chains. In this paper, a novel class of sequence sets, called enhanced cross Z-complementary set (E-CZCS), is proposed for efficient and feasible training sequence design in broadband GSM systems. Specifically, an E-CZCS consists of multiple CZCSs possessing front-end and tail-end zero-correlation zones (ZCZs), whereby any two distinct CZCSs have a tail-end ZCZ when a novel type of cross-channel aperiodic correlation sums is considered. The theoretical upper bound on the ZCZ width is first derived, upon which E-CZCSs with maximum ZCZ width and flexible parameters are constructed. For optimal channel estimation over frequency-selective channels, we introduce and evaluate a novel GSM training framework employing the proposed E-CZCSs. Numerical results demonstrate that the proposed E-CZCS-based training can achieve the minimum channel estimation mean square error (MSE) and outperform other classes of sequences. © 2020 IEEE.

关键词： Mean square error

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Fair-Over-Time Distributed Energy Resource Coordination 60

Fair-Over-Time Distributed Energy Resource Coordination

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60th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2024

作者： Moring, Hannah Farrell, Xavier Mathieu, Johanna L. University of Michigan Department of Electrical Engineering and Computer Science Ann ArborMI48109 United States

ISBN: (纸本)9798331541033

There are numerous strategies to coordinate distributed energy resources (DERs) to provide a variety of services to the power grid. DER coordination can affect resources and participants unequally, for example, by excessively degrading or curtailing particular DERs more than others. However, few DER coordination strategies explicitly take into account fairness, equity, or justice. In this paper, we explore fairness metrics and their applicability to the DER coordination problem. In particular, we investigate metrics from machine learning to identify metrics that could be incorporated into DER coordination problems and we summarize fairness metrics that have been used in the power systems literature. A key challenge is that most existing fairness metrics are static - ensuring fairness at a point in time. DER coordination problems are inherently dynamic and we often care about fairness over time, not at each time. The machine learning literature offers some ways to think about fairness over time and, more generally, how to incorporate fairness into dynamic power systems problems. We use a specific DER coordination problem - the problem of computing dynamic operating envelopes - to demonstrate how incorporation of a fair-over-time metric changes DER coordination solutions, and highlight the trade-offs that arise. © 2024 IEEE.

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Dynamic Outcome Prediction of an NBA Match 18

Dynamic Outcome Prediction of an NBA Match

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18th International Conference on Ubiquitous Information Management and Communication, IMCOM 2024

作者： Kandhway, Kundan Indian Institute of Science Education and Research Department of Electrical Engineering and Computer Science Madhya Pradesh Bhopal462066 India

ISBN: (纸本)9798350331011

In this paper we formulate the problem of predicting the outcome (winner) of an ongoing National Basketball Association (NBA) match as a supervised machine learning problem. In this approach, as the match progresses, the outcome prediction dynamically adapts to the current match situation which does not happen in static prediction problems. Dynamic outcome prediction of the match seems to have received less attention in the literature than static predictions. We compute the features used in the classification problem based on the most up-to-date match situation till that point in time. A total of 32 features are used. We present results for all the regular season matches of the 2022-23 NBA season. Dynamic prediction accuracy varies from about 62% at the beginning of the match to about 78% at the beginning of the final quarter of the match. We also evaluate feature importance in this classification problem. © 2024 IEEE.

关键词： Forecasting

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Dynamical phase-field model of cavity electromagnonic systems

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npj Computational Materials 2024年第1期10卷 1263-1273页

作者： Shihao Zhuang Yujie Zhu Changchun Zhong Liang Jiang Xufeng Zhang Jia-Mian Hu Department of Materials Science and Engineering University of Wisconsin-MadisonMadisonWI53706USA Pritzker School of Molecular Engineering The University of ChicagoChicagoIL60637USA Department of Electrical and Computer Engineering Northeastern UniversityBostonMA02115USA Department of Physics Northeastern UniversityBostonMA02115USA

Cavity electromagnonic system,which simultaneously consists of cavities for photons,magnons(quanta of spin waves),and acoustic phonons,provides an exciting platform to achieve coherent energy transduction among different physical systems down to single quantum *** we report a dynamical phase-field model that allows simulating the coupled dynamics of the electromagnetic waves,magnetization,and strain in 3D multiphase *** examples of application,we computationally demonstrate the excitation of hybrid magnon-photon modes(magnon polaritons),Floquet-induced magnonic Aulter-Townes splitting,dynamical energy exchange(Rabi oscillation)and relative phase control(Ramsey interference)between the two magnon polariton *** simulation results are consistent with analytical calculations based on Floquet Hamiltonian *** are also performed to design a cavity electro-magno-mechanical system that enables the triple phononmagnon-photon resonance,where the resonant excitation of a chiral,fundamental(n=1)transverse acoustic phonon mode by magnon polaritons is *** the capability to predict coupling strength,dissipation rates,and temporal evolution of photon/magnon/phonon mode profiles using fundamental materials parameters as the inputs,the present dynamical phase-fieldmodel represents a valuable computational tool to guide the fabrication of the cavity electromagnonic system and the design of operating conditions for applications in quantum sensing,transduction,and communication.

关键词： theory phonon phase

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Manufacturing High-Q Silicon Nitride Photonic Chips via Silicon Hardmask Etching

Manufacturing High-Q Silicon Nitride Photonic Chips via Sili...

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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： Liu, Shuai Zhang, Yuheng Zhang, Zheshen Department of Electrical Engineering and Computer Science University of Michigan Ann ArborMI48109 United States

We present a robust process for fabricating high-Q, dispersion-engineered Si3N4 photonic chips using amorphous silicon hardmask etching with PECVD SiO2 cladding, achieving an intrinsic quality factor up to ∼ 17.5×106 and an average intrinsic quality factor of ∼ 13×106. We anticipate a further reduction in propagation loss through LPCVD SiO2 cladding. © Optica Publishing Group 2024

关键词： Silicon nitride

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