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Antennas and Propagation & USNC/URSI National Radio Science Meeting

作者： Jongwoo Jeong Leung Tsang Zhenming Huang Haokui Xu Andreas Colliander Department of Electrical Engineering and Computer Science University of Michigan Jet Propulsion Laboratory California Institute of Technology

ISBN: (数字)9798350369908

ISBN: (纸本)9798350369915

We perform full-wave simulations of propagation of L-band microwave signals in forested areas to study forest effects on microwave remote sensing, wireless communications, and hidden object detection. Initially, full-wave simulations of forests were limited to eight-meter-tall trees. With the aid of computational enhancement by a fast hybrid method (FHM) solving Maxwell's equations, a height of trees extends to 13 m followed by 17 m. The FHM applies to 91 trees of a height of 17 m, where the volumetric space in the simulation domain is equivalent to 133 wavelengths by 133 wavelengths and 80 wavelengths. We will continue to investigate the effects of tapering and bifurcated trunks, as well as the presence of leaves, on microwave remote sensing. We illustrate the spatial distribution of electric fields under forests. Computational efficiency of the FHM is also discussed. The results indicate that L-band microwave signals can penetrate through forests, enabling the detection of soil and objects below, and GPS signals can be successfully received by receivers beneath forested areas.

关键词： Computational modeling Forestry Vegetation Microwave communication Soil Microwave theory and techniques Mathematical models

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Mixture of Prompt Experts for Natural Language Inference

Mixture of Prompt Experts for Natural Language Inference

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Canadian Conference on electrical and computer engineering (CCECE)

作者： Zi’ou Zheng Xiaodan Zhu Department of Electrical and Computer Engineering Ingenuity Labs Research Institute Queen’s University Kingston Canada

ISBN: (数字)9798350371628

ISBN: (纸本)9798350371635

Reasoning is a central problem in artificial intelligence (AI). Natural language inference (NLI) is a fundamental task that aims to discern the logical relationship between two natural language sentences. Such a capability underlies many real-life applications. One challenge of NLI is that it involves different reasoning requirements and linguistic phenomena. Recently, deep prompt tuning has achieved performance comparable to full-scale fine-tuning. These trained prompts can fit subtasks or data regimes with only a small number of parameters to avoid overfitting. However, one prompt is not adequate for fitting various data regimes. In this paper, we aim to leverage the benefits of deep prompt tuning to craft a more adaptable model for complex natural language inference problems. We propose a novel parameter-efficient approach, named Mixture of Prompt Experts (MOPE), designed to learn various prompts, addressing the inadequacy of one single prompt for tasks comprising multiple sub-tasks with various distributions. This novel approach integrates the mixture of experts with parameter-efficient prompt tuning. Our experimental results show that MOPE achieves better performance on the natural language inference tasks compared to the baseline models.

关键词： Adaptation models Natural languages Fitting Data visualization Performance gain Linguistics Natural language processing

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Analysis of Brain Excitability After Transcranial Direct Current Stimulation and Brain-computer Interface Based on Motor Imagery on a Post-stroke Patient 9th

Analysis of Brain Excitability After Transcranial Direct Cu...

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9th Latin American Congress on Biomedical engineering, CLAIB 2022 and 28th Brazilian Congress on Biomedical engineering, CBEB 2022

作者： Silva, Leticia Lima, Jéssica Schreider, Sheila Delisle-Rodriguez, Denis Krishnan, Sridhar Bastos-Filho, Teodiano Postgraduate Program in Electrical Engineering Universidade Federal do Espirito Santo Vitoria Brazil Postgraduate Program in Biotechnology Universidade Federal do Espirito Santo Vitoria Brazil Edmond and Lily Safra International Institute of Neurosciences Instituto Santos Dumont Macaiba Brazil Department of Electrical Computer and Biomedical Engineering Toronto Metropolitan University Toronto Canada

ISBN: (纸本)9783031494062

Stroke is a neurological syndrome that may cause severe cognitive and motor impairments for survival. Alternative rehabilitation techniques have been developed to recover lower-limb movements and gait of post-stroke patients, such as Motor Imagery (MI)-based Brain-computer Interfaces (BCIs), Virtual Reality (VR), and robotic devices. Transcranial Direct Current Stimulation (tDCS) is a non-invasive technique to stimulate the brain and modulate cortical excitability. This study aims to analyze the short-term effects of tDCS compared to sham stimulation before a lower-limb MI-BCI pedaling training (through a robotic monocycle) task in a patient with subacute stroke. We studied a post-stroke patient with 2 months of ischemic stroke and right hemiparesis who was submitted to the following tasks: active pedaling, sham tDCS and MI-BCI, and tDCS and MI-BCI. We evaluated the relative power around the foot area (Cz electrode), and a significant (p-value © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Brain computer interface

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Evaluating the Role of Secure Shell (SSH) in Securing Wireless Networks 3

Evaluating the Role of Secure Shell (SSH) in Securing Wirele...

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3rd International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Jangid, Satish Kumar Saini, Rajat Kumar, Ritesh Devaraj Verma, C. Mahalakshmi, V. Vivekananda Global University Department of Electrical Engineering Jaipur India Chitkara University Institute of Engineering and Technology Chitkara University Centre of Interdisciplinary Research in Business and Technology Punjab India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Faculty of Engineering and Technology Department of Computer Science and Engineering Karnataka Ramnagar562112 India Prince Shri Venkateshwara Padmavathy Engineering College Department of Electrical and Electronics Engineering Chennai127 India

ISBN: (纸本)9798350319125

Cozy Shell (SSH) is an essential device for securing wireless networks. SSH is a cozy protocol that provides relaxed authentication, records confidentiality, and integrity for Wi-Fi networks. It can permit a more cozy transmission of statistics, provide admission to manipulating, and deliver customers better information on how their records are getting used. This abstract evaluates relaxed Shell (SSH) for securing wireless networks. The evaluation of SSH specializes in the strengths and weaknesses of the protocol and appears into how nicely it could provide ease of authentication, facts confidentiality, and integrity. The assessment also looks into SSH's role in shielding Wi-Fi networks from potential threats, such as guy-in-the-center assaults, packet sniffers, eavesdropping, and other network safety challenges. Additionally, the assessment shows how SSH can offer an extra comfy interface for controlling consumer access and modifying wireless networks. Sooner or later, the evaluation looks into the challenges of deploying SSH in secure wireless networks and a way to make sure its security and compatibility. The summary concludes that SSH can play an essential role in promoting cozy wireless networks and guarding consumer information. © 2023 IEEE.

关键词： challenges concludes controlling evaluation weaknesses

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Information Structures in AC/DC Grids

Information Structures in AC/DC Grids

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IEEE Conference on Decision and Control

作者： Josh Taylor Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark New Jersey United States

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

The converters in an AC/DC grid form actuated boundaries between the AC and DC subgrids. In both simple linear and balanced dq-frame models, the states on either side of these boundaries are coupled only by control inputs. In this paper, we show how this topological property imparts all AC/DC grids with poset-causal information structures. A practical benefit is that certain decentralized control problems that are hard in general are tractable for poset-causal systems. We also show that special cases like multi-terminal DC grids can have coordinated and leader-follower information structures.

关键词： Decentralized control Bidirectional control Power system stability Controllability Stability analysis Power electronics Voltage control Observability Frequency control

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THE IMPACT OF MODEL SIZE ON CATASTROPHIC FORGETTING IN ONLINE CONTINUAL LEARNING

arXiv

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arXiv 2024年

作者： Lee, Eunhae Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States

This study investigates the impact of model size on Online Continual Learning performance, with a focus on catastrophic forgetting. Employing ResNet architectures of varying sizes, the research examines how network depth and width affect model performance in class-incremental learning using the SplitCIFAR-10 dataset. Key findings reveal that larger models do not guarantee better Continual Learning performance;in fact, they often struggle more in adapting to new tasks, particularly in online settings. These results challenge the notion that larger models inherently mitigate catastrophic forgetting, highlighting the nuanced relationship between model size and Continual Learning efficacy. This study contributes to a deeper understanding of model scalability and its practical implications in Continual Learning scenarios. © 2024, CC BY.

关键词： Learning systems

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Cross-Layer Optimized HARQ Protocol for Underwater Acoustic Wireless Sensor Networks Using Stochastic Network Calculus

Cross-Layer Optimized HARQ Protocol for Underwater Acoustic ...

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Emerging Research in Computational Science (ICERCS), International Conference on

作者： Sivajayaprakash A Rajeev Sukumaran Kumar C Department of Computer Science and Engineering SRM Institute of Science and Technology Kattankulathur India Department of Electrical and Electronics Engineering Karpagam College of Engineering Coimbatore India

ISBN: (数字)9798331534967

ISBN: (纸本)9798331534974

UAWSNs face challenges such as long propagation delays, limited bandwidth, and varying channel conditions. To solve these problems, we developed a new protocol called Multi- Hop Cross-Layer Optimized Hybrid Automatic Repeat Request (CLO-HARQ) suitable for UAWSNs. This protocol automatically changes the retransmission strategy and error correction redundancy based on real-time feedback from the physical and network layers. A unique feature of this protocol is the inclusion of environmental factors such as water salinity and temperature in the decision-making process. Also, using Stochastic Network Calculus (SNC), stochastic traffic characteristics predict single-hop and multi-hop communication delay (delay), energy usage (energy usage), and throughput. In the performance evaluation of CLO-HARQ, it has been shown to provide significant improvement in efficiency, throughput, and delay over existing HARQ methods. It is well-suited for long-term underwater monitoring and is a sustainable solution for energy-constrained sensor networks.

关键词： Cross layer design Wireless sensor networks Protocols Temperature Salinity (geophysical) Spread spectrum communication Throughput Calculus Delays Underwater acoustics

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Non-impulsive Contact-Implicit Motion Planning for Morpho-functional Loco-manipulation

Non-impulsive Contact-Implicit Motion Planning for Morpho-fu...

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IEEE/ASME (AIM) International Conference on Advanced Intelligent Mechatronics

作者： Adarsh Salagame Kruthika Gangaraju Harin Kumar Nallaguntla Bibek Gupta Eric Sihite Gunar Schirner Alireza Ramezani Department of Electrical and Computer Engineering Northeastern University Boston MA California Institute of Technology Pasadena CA

ISBN: (数字)9798350355369

ISBN: (纸本)9798350355376

Object manipulation has been extensively studied in the context of fixed base and mobile manipulators. However, the overactuated locomotion modality employed by snake robots allows for a unique blend of object manipulation through locomotion, referred to as loco-manipulation. The following work presents an optimization approach to solving the loco-manipulation problem based on non-impulsive implicit contact path planning for our snake robot COBRA. We present the mathematical framework and show high fidelity simulation results for fixed-shape lateral rolling trajectories that demonstrate the object manipulation.

关键词： Mechatronics Simulation Snake robots Manipulators Trajectory Planning Optimization

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Human gesture recognition in degraded environments with multi-dimensional integral imaging: An Overview [Invited]

Human gesture recognition in degraded environments with mult...

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3D Image Acquisition and Display: Technology, Perception and Applications, 3D 2024 - Part of Optica Imaging Congress

作者： Javidi, Bahram Krishnan, Gokul Pla, Filiberto Department of Electrical and Computer Engineering University of Connecticut StorrsCT06269 United States Institute of New Imaging Technologies Universitat Jaume I Campus Riu Sec s/n Castelló de la Plana12071 Spain

In this work, we present an overview of human gesture recognition in degraded environments with multi-dimensional integral imaging. It is shown that for human gesture recognition in degraded environments such as low light, and occlusion, we can gain substantial improvements in performance over conventional imaging. © 2024 The Author(s).

关键词： Gesture recognition

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An Interdisciplinary Framework for Systematic Innovation: A Case Study on Nature-Inspired Imaging Solutions

An Interdisciplinary Framework for Systematic Innovation: A ...

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2024 IEEE International Conference on Imaging Systems and Techniques, IST 2024

作者： Douard, Nicolas Samet, Ahmed Cavallucci, Denis Giakos, George National Institute of Applied Sciences University of Strasbourg 24 Bd de la Victoire Strasbourg67000 France Manhattan University Department of Electrical and Computer Engineering 3825 Corlear Ave New YorkNY10463 United States

ISBN: (纸本)9798350378214

This research presents a novel interdisciplinary framework designed to uncover connections across diverse knowledge domains through advanced semantic modeling techniques. A case study focused on nature-inspired imaging solutions illustrates the potential of the framework. Innovation often emerges at the intersection of various scientific fields. However, manually identifying these intersections within the vast scientific literature is impractical. By exploring how biological principles can inspire the development of advanced imaging technologies, such as image sensors for rapid motion tracking, we underscore the critical role of interdisciplinary research in the promotion of technological innovation. Our framework systematically identifies and analyzes cross-domain connections, showcasing the potential of automated bioinspired approaches to drive innovation from the early stages. This research highlights how semantic modeling can bridge gaps between disparate fields, facilitating the discovery of novel insights, and fostering a more integrated approach to academic research. By automating the process of identifying relevant intersections within extensive literature, our framework not only enhances research efficiency, but also broadens the scope for innovative solutions. Ultimately, this work underscores the value of interdisciplinary collaboration and the transformative potential of bioinspired methodologies in the advancement of technology. The findings presented offer an actionable roadmap for leveraging semantic modeling to accelerate the pace of innovation in various domains. © 2024 IEEE.

关键词： bioinspired innovation imaging technologies interdisciplinary research semantic modeling technological innovation

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