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Electrically Tuning Quasi-Bound States in the Continuum with Hybrid Graphene-Silicon Metasurfaces

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arXiv 2024年

作者： Cai, Ziqiang Zhang, Xianzhe Karnik, Tushar Sanjay Xu, Yihao Kim, Tae Yoon Hu, Juejun Liu, Yongmin Department of Electrical and Computer Engineering Northeastern University BostonMA02115 United States Department of Materials Science and Engineering Massachusetts Institute of Technology CambridgeMA02139 United States Department of Mechanical and Industrial Engineering Northeastern University BostonMA02115 United States

Metasurfaces have become one of the most prominent research topics in the field of optics owing to their unprecedented properties and novel applications on an ultrathin platform. By combining graphene with metasurfaces, electrical tunable functions can be achieved with fast tuning speed, large modulation depth and broad tuning range. However, the tuning efficiency of hybrid graphene metasurfaces within the short-wavelength infrared (SWIR) spectrum is typically low because of the small resonance wavelength shift in this wavelength range. In this work, through the integration of graphene and silicon metasurfaces that support quasi-bound states in the continuum (quasi-BIC), we experimentally demonstrate significant transmittance tuning even with less than 30 nm resonance wavelength shift thanks to the high quality-factor of quasi-BIC metasurfaces. The tunable transmittance spectrum was measured using Fourier Transform Infrared Spectroscopy (FTIR) with a modified reflective lens to improve the accuracy, and the electrical tuning was realized utilizing the "cut-and-stick" method of ion gel. At the wavelength of 3.0 µm, the measured change of transmittance ΔT = Tmax − Tmin and modulation depth ΔT/Tmax can reach 22.2% and 28.9%, respectively, under a small bias voltage ranging from -2 V to +2 V. To the best of our knowledge, this work is the first experimental demonstration of tunable graphene/quasi-BIC metasurfaces, which have potential applications in optical modulation, reconfigurable photonic devices, and optical communications. Copyright © 2024, The Authors. All rights reserved.

关键词： Graphene

Three-dimensional Morphological Reconstruction of Millimeter-Scale Soft Continuum Robots based on Dual-Stereo-Vision

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arXiv 2024年

作者： Ren, Tian-Ao Liu, Wenyan Zhang, Tao Zhao, Lei Ren, Hongliang Lai, Jiewen The Department of Mechanical Engineering Stanford University CA United States The CUHK Shenzhen Research Institute Shenzhen China The Department of Electronic Engineering The Chinese University of Hong Kong NT Shatin Hong Kong The College of Computer Science and Electronic Engineering Hunan University Changsha China

Continuum robots can be miniaturized to just a few millimeters in diameter. Among these, notched tubular continuum robots (NTCR) show great potential in many delicate applications. Existing works in robotic modeling focus on kinematics and dynamics but still face challenges in reproducing the robot’s morphology—a significant factor that can expand the research landscape of continuum robots, especially for those with asymmetric continuum structures. This paper proposes a dual stereo vision-based method for the three-dimensional morphological reconstruction of millimeter-scale NTCRs. The method employs two oppositely located stationary binocular cameras to capture the point cloud of the NTCR, then utilizes predefined geometry as a reference for the KD tree method to relocate the capture point clouds, resulting in a morphologically correct NTCR despite the low-quality raw point cloud collection. The method has been proved feasible for an NTCR with a 3.5 mm diameter, capturing 14 out of 16 notch features, with the measurements generally centered around the standard of 1.5 mm, demonstrating the capability of revealing morphological details. Our proposed method paves the way for 3D morphological reconstruction of millimeter-scale soft robots for further self-modeling study. Copyright © 2024, The Authors. All rights reserved.

关键词： Stereocenters

Honeypot based Intrusion Detection System for Cyber Physical System

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Honeypot based Intrusion Detection System for Cyber Physical...

Augmented Intelligence and Sustainable Systems (ICAISS), International Conference on

作者： G.Kingsle Edwin S.E. Vinodh Ewards G. Jaspher Willsie Kathrine G. Matthew Palmer A. Bertia S.J. Vijay Department of Computer science and engineering Karunya Institute of Technology and Sciences Coimbatore Department of Mechanical engineering Karunya Institute of Technology and Sciences Coimbatore

ISBN: (纸本)9781665489638

An intrusion detection system is a software programme or hardware that keeps an eye out for malicious activities or policy breaches on a network or in a system. Any intrusion activity or violation is often recorded centrally using a security information and event management system, alerted to an administrator, or both. Cyber physical systems link physical infrastructure and things to the internet and to one another by integrating sensing, computing, control, and networking into them. As a result, cyber assaults on the cyber-physical system can make the devices malfunction, and adequate intrusion detection is needed to protect the system. An essential tool for detecting network intrusion is a honeypot. Honeypots not only engage the attacker but also collect information that may be used to understand attacks and attackers on the network. As a result, the aim of the paper is to construct honeypot to catch attacks. Once an intrusion caused by the attacker is caught, the process of assaulting the system is stopped. The logs are also recorded so that network activity can be properly analysed.

关键词： Intrusion detection Cyber-physical systems Software Hardware Sensors Security Network intrusion

Towards End-to-End GPS Localization with Neural Pseudorange Correction

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arXiv 2024年

作者： Weng, Xu Ling, K.V. Liu, Haochen Cao, Kun The School of Electrical and Electronic Engineering Nanyang Technological University Singapore639798 Singapore The School of Mechanical and Aerospace Engineering Nanyang Technological University Singapore639798 Singapore The School of Electrical Engineering and Computer Science KTH Royal Institute of Technology StockholmSE-100 44 Sweden

Pseudorange errors are the root cause of localization inaccuracy in GPS. Previous data-driven methods regress and eliminate pseudorange errors using handcrafted intermediate labels. Unlike them, we propose an end-to-end GPS localization framework, E2E-PrNet, to train a neural network for pseudorange correction (PrNet) directly using the final task loss calculated with the ground truth of GPS receiver states. The gradients of the loss with respect to learnable parameters are backpropagated through a differentiable nonlinear least squares optimizer to PrNet. The feasibility is verified with GPS data collected by Android phones, showing that E2E-PrNet outperforms the state-of-the-art end-to-end GPS localization methods. © 2024, CC BY.

关键词： Global positioning system

Ano-SuPs: Multi-size anomaly detection for manufactured products by identifying suspected patches

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arXiv 2023年

作者： Xu, Hao Du, Juan Wang, Andi Chen, Ying-Cong Guangdong Guangzhou China Department of Mechanical and Aerospace Engineering The Hong Kong University of Science and Technology Hong Kong Department of Industrial and Systems Engineering College of Engineering University of Wisconsin-Madison Madison United States Guangdong Guangzhou China Department of Computer Science and Engineering The Hong Kong University of Science and Technology Hong Kong

Image-based systems have gained popularity owing to their capacity to provide rich manufacturing status information, low implementation costs, and high acquisition rates. However, the complexity of the image background and various anomaly patterns pose new challenges to existing matrix decomposition methods, which are inadequate for modeling requirements. Moreover, the uncertainty of the anomaly can cause anomaly contamination problems, making the designed model and method highly susceptible to external disturbances. To address these challenges, we propose a two-step strategy anomaly detection method that detects anomalies by identifying suspected patches (Ano-SuPs). Specifically, we propose to detect the patches with anomalies by reconstructing the input image twice: the first step is to obtain a set of normal patches by removing those suspected patches, and the second step is to use those normal patches to refine the identification of the patches with anomalies. To demonstrate its effectiveness, we evaluate the proposed method systematically through simulation experiments and case studies. We further identified the key parameters and designed steps that impact the model’s performance and efficiency. Copyright © 2023, The Authors. All rights reserved.

关键词： Anomaly detection

Thermal comparison of mono-facial and bi-facial photovoltaic cells considering the effect of TPT layer absorptivity

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International Journal of Thermofluids 2023年 18卷

作者： Radwan, Ali Mahmoud, Montaser Olabi, Abdul-Ghani Rezk, Ahmed Maghrabie, Hussein M Abdelkareem, Mohammad Ali Sustainable Energy & Power Systems Research Centre RISE University of Sharjah Sharjah P.O. Box 27272 United Arab Emirates Mechanical Power Engineering Department Faculty of Engineering Mansoura University Mansoura35516 Egypt Department of Engineering School of Mathematics Computer Science and Engineering City University of London London United Kingdom Mechanical Engineering and Design Aston University School of Engineering and Applied Science Birmingham Aston TriangleB4 7ET United Kingdom College of Engineering and Physical Science Aston University Birmingham B4 7ET United Kingdom Department of Mechanical Engineering Faculty of Engineering South Valley University Qena83521 Egypt Chemical Engineering Department Minia University Elminia Egypt

With the widespread utilization of solar photovoltaics (PV), it is becoming increasingly important to understand its performance using various configurations to harvest solar energy at the most suitable efficiency, specifically in hot climates. Therefore, this paper compares mono-facial and bi-facial PV cells under the high-temperature desert climate of Sharjah (United Arab Emirates). The optimally tilted and vertical east-west configurations were compared to evaluate the annual energy production for these scenarios. In addition, new parameter, the effect of the rear side layer absorptivity of the mono-facial PV cell, was investigated. The comparative study considered solar radiation, ambient temperature, wind speed, and albedo. The results showed that considering the effect of absorptivity achieves better performance predictions. However, the effect of the absorptivity did not exhibit a significant influence compared to the case with neglected backsheet absorptivity. As such, the PV cell temperature increased by 0.4 °C and 1.4 °C at an albedo of 0.2 and 0.7, considering the actual absorptivity value of 0.2. On the other hand, it is worth mentioning that improper designs result in considerable temperature rises as the absorptivity value increases. Under the investigated conditions and based on the yearlong comparison, the tilted bi-facial performed better than the vertical bi-facial;as the albedo increased from 0.2 to 0.7, the power gain ratio of the tilted bi-facial increased from 7.18% to 20.88% and that of vertical bi-facial from -19.4% to 12.65%. © 2023 The Author(s)

关键词： Solar energy

Off-Policy Reinforcement based on a Safe Model Eco-Driving Education for Fully-Automated, Connected Hybrid Vehicles 2

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Off-Policy Reinforcement based on a Safe Model Eco-Driving E...

2nd International Conference on Electronics and Renewable Systems, ICEARS 2023

作者： Pande, Soumitra S Neeraja, B. Kumar, K Kalyan Sathish, Singarapu Mounika, Lakkakula Patra, Jyoti Prasad Ericsson Global India Private Limited Karnataka Bangalore India Government Polytechnic Hyderabad Department of Electrical and Electronics Engineering Telangana India Department of Electrical and Electronics Engineering Andhra Pradesh Kadapa India Kg Reddy College of Engineering & Technology Mechanical Engineering Department Telangana India Sr University Lakkakula Mounika School of Computer Science and Artificial Intelligence Telangana Warangal India Outr Government of Odisha Mahalaxmi Vihar Techno Campus Electrical Odisha University of Technology and Research Odisha Ghatikia Bhubaneswar India

ISBN: (纸本)9798350346640

Eco-driving reduces gas use. Eco-driving improves driving behavior and fuel economy without hardware modifications. Eco-driving strategies exist. Speed control is difficult in many driving conditions. This research develops an eco-driving approach to reduce car emissions in a variety of scenarios. DRL has helped eco-driving reduce fuel usage and travel time. Data-driven reinforcement learning can improve autonomous electric car speed planning. Eco-driving strategy reinforcement learning prototype. Three enhancements are offered. Off-policy learning and physics-based models improve sample efficiency. Second, constraint fulfillment can be achieved without externally rewarding proper behavior during training. Third, deep generative techniques to mimic a safe set ensure the route is possible. The reinforcement learning method can optimize car speed based on highway gradient and vehicle distance. Reinforcement learning outperforms evolutionary algorithms nearly perfectly. © 2023 IEEE.

关键词： Reinforcement learning

Dynamic Battery Type Detection Using Neural Networks

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Dynamic Battery Type Detection Using Neural Networks

International Symposium on High Capacity Optical Networks and Enabling Technologies, HONET

作者： Hector K. Lopez Ali Zilouchian Amir Abtahi Department of Electrical Engineering & Computer Science Florida Atlantic University Boca Raton FL United States Department of Ocean and Mechanical Engineering Florida Atlantic University Boca Raton FL United States

Dynamically detecting battery chemistries, including LiFePO4, Ni-MH, and Lead Acid, is explored through extensive simulations. Utilizing discharge curves as training data, three neural network architectures-Single Hidden Layer, Double Hidden Layer, and Radial Basis Transfer Function-are employed for pattern recognition across diverse discharge profiles. The objective is to enable the identification of connected battery types and optimize charging control. This research holds significance in real-time Electric Vehicle (EV) charging optimization, offering the capability to discern various battery chemistries. Additionally, in Peer-to-Peer (P2P) energy markets, the dynamic contribution of batteries to the grid requires safe and efficient charging for interoperable systems. The findings presented in this study introduce adaptable systems, fostering innovation in sustainable energy practices.

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RecGS: Removing Water Caustic with Recurrent Gaussian Splatting

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arXiv 2024年

作者： Zhang, Tianyi Zhi, Weiming Huang, Kaining Mangelson, Joshua Barbalata, Corina Johnson-Roberson, Matthew Robotics Institute School of Computer Science Carnegie Mellon University PittsburghPA15213 United States Department of Mechanical & Industrial Engineering Louisiana State University Baton RougeLA70803 United States Department of Electrical and Computer Engineering Brigham Young University ProvoUT84602 United States

Water caustics are commonly observed in seafloor imaging data from shallow-water areas. Traditional methods that remove caustic patterns from images often rely on 2D filtering or pre-training on an annotated dataset, hindering the performance when generalizing to real-world seafloor data with 3D structures. In this paper, we present a novel method Recurrent Gaussian Splatting (RecGS), which takes advantage of today’s photorealistic 3D reconstruction technology, 3D Gaussian Splatting (3DGS), to separate caustics from seafloor imagery. With a sequence of images taken by an underwater robot, we build 3DGS recurrently and decompose the caustic with low-pass filtering in each iteration. In the experiments, we analyze and compare with different methods, including joint optimization, 2D filtering, and deep learning approaches. The results show that our proposed RecGS paradigm can effectively separate the caustic from the seafloor, improving the visual appearance, and can be potentially applied on more problems with inconsistent illumination. Our videos and code are released at https://***/proj/*** © 2024, CC BY.

关键词： Iterative methods