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arXiv 2025年

作者： Pei, Ziqian Wang, Jintao Zhang, Pingping Shi, Zheng Yang, Guanghua Ma, Shaodan State Key Laboratory of Internet of Things for Smart City The Department of Electrical and Computer Engineering University of Macau Macau999078 China School of Intelligent Systems Science and Engineering Jinan University Zhuhai519070 China

In this letter, we investigate a dynamic reconfigurable distributed antenna and reflection surface (RDARS)driven secure communication system, where the working mode of the RDARS can be flexibly configured. We aim to maximize the secrecy rate by jointly designing the active beamforming vectors, reflection coefficients, and the channel-aware mode selection matrix. To address the non-convex binary and cardinality constraints introduced by dynamic mode selection, we propose an efficient alternating optimization (AO) framework that employs penalty-based fractional programming (FP) and successive convex approximation (SCA) transformations. Simulation results demonstrate the potential of RDARS in enhancing the secrecy rate and show its superiority compared to existing reflection surface-based schemes. Copyright © 2025, The Authors. All rights reserved.

关键词： Secure communication

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Data-Driven Model for Photovoltaic Generation: Comparison with Physical Models Using a Microgrid in Puerto Rico

Data-Driven Model for Photovoltaic Generation: Comparison wi...

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IEEE General Meeting Power& Energy Society

作者： Marcos R. Pesante Colón Alberto I. Cruz Salamán Dylan Cruz Figueroa Aditya Sundararajan Maximiliano Ferrari Electrical and Computer Engineering Department University of Puerto Rico Mayagüez USA Grid Systems Architecture Group Oak Ridge National Laboratory Oak Ridge TN USA

ISBN: (数字)9798350381832

ISBN: (纸本)9798350381849

Photovoltaic (PV) generation is a critical component of microgrids, but its accurate modeling is challenging due to the complex and dynamic interactions between solar irradiance, temperature, and PV system installation. This paper develops a multilayer perceptron (MLP) model that inputs solar irradiance and temperature to estimate the PV generation, and it compares the proposed data-driven model’s performance to two well-known physical models: the single-diode model and the inverter model. The results demonstrate that all the models can reach high levels of accuracy. However, the MLP model outperforms the physical models on average by 4.5 to 6.6 percent in R squared scores and 220 to 290 Watts in RMSE scores, and it does not require physical system parameters. Moreover, the data-driven model can overcome the limitations of the lack of real-time PV generation data.

关键词： Temperature measurement Solar irradiance Photovoltaic systems Adaptation models Accuracy Voltage measurement Predictive models Multilayer perceptrons Data models Inverters

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Photorealistic Arm Robot Simulation for 3D Plant Reconstruction and Automatic Annotation using Unreal Engine 5

Photorealistic Arm Robot Simulation for 3D Plant Reconstruct...

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IEEE computer Society Conference on computer Vision and Pattern Recognition Workshops (CVPRW)

作者： Xingjian Li Jeremy Park Chris Reberg-Horton Steven Mirsky Edgar Lobaton Lirong Xiang Department of Biological and Agricultural Engineering North Carolina State University Department of Electrical and Computer Engineering North Carolina State University Department of Computer Science North Carolina State University Department of Crop and Soil Science North Carolina State University Sustainable Agricultural Systems Laboratory USDA-ARS

ISBN: (数字)9798350365474

ISBN: (纸本)9798350365481

Robotics paired with computer vision are widely used in precision agriculture. Simulations are critical for safety and performance estimation by verifying their routine in a virtual world before real-world testing and deployment. However, many simulators used in agricultural robots lack photorealism in their virtual worlds compared to the real world. We implemented Unreal Engine 5 (UE5) and the Robot Operating System (ROS) to develop a robot simulator tailored to agricultural tasks and synthetic data generation with RGB, segmentation, and depth images. We designed a method for assigning multiple segmentation labels within a single plant mesh. We experimented with a semi-spherical routine for two robot arms to perform 3D point cloud reconstruction across 10 plant assets. We showed our simulator produces much more accurate segmentation images and reconstruction compared to existing UE5 solutions. We extend our results with Neural Radiance Field (NeRF) reconstructions. The packaged simulator, UE5 project, and ROS package with the Python routine can be found at https://***/NCSU-BAE-ARLab/AgriRoboSimUE5.

关键词： Image segmentation computer vision Three-dimensional displays Computational modeling Neural radiance field Manipulators Image reconstruction

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Invertible Voice Conversion with parallel Data

Invertible Voice Conversion with Parallel Data

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Zexin Cai Ming Li Department of Electrical and Computer Engineering Duke University Durham NC USA Suzhou Municipal Key Laboratory of Multimodal Intelligent Systems Duke Kunshan University Kunshan PR China

This paper introduces an innovative deep learning framework for parallel voice conversion to mitigate inherent risks associated with such systems. Our approach focuses on developing an invertible model capable of countering potential spoofing threats. Specifically, we present a conversion model that allows for the retrieval of source voices, thereby facilitating the identification of the source speaker. This framework is constructed using a series of invertible modules composed of affine coupling layers to ensure the reversibility of the conversion process. We conduct comprehensive training and evaluation of the proposed framework using parallel training data. Our experimental results reveal that this approach achieves comparable performance to non-invertible systems in voice conversion tasks. Notably, the converted outputs can be seamlessly reverted to the original source inputs using the same parameters employed during the forwarding process. This advancement holds considerable promise for elevating the security and reliability of voice conversion.

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Wavelet Convolutional Neural Network for Low-Resolution Brain MRI Images

Wavelet Convolutional Neural Network for Low-Resolution Brai...

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IEEE International Symposium on Biomedical Imaging

作者： Soo Min Oh Yifan Li Jo Woon Chong Wireless Information and Network Sciences Laboratory Massachusetts Institute of Technology Cambridge MA USA Laboratory for Information and Decision Systems Massachusetts Institute of Technology Cambridge MA USA Department of Statistics Texas A&M University College Station TX USA Department of Electrical and Computer Engineering Texas Tech University Lubbock TX USA Department of Electrical and Computer Engineering Sungkyunkwan University Suwon Korea

ISBN: (数字)9798331520526

ISBN: (纸本)9798331520533

Low-resolution images inherently contain less information, making effective feature extraction more challenging and posing difficulties for training neural networks. However, if neural networks can be trained successfully on low-resolution images, this could significantly reduce memory storage requirements and computational costs. In this study, we address the limitations of low-resolution brain MRI images by enhancing the available information through wavelet transform techniques. Specifically, we leverage the high-frequency coefficients obtained from wavelet transforms and the Hurst exponent to improve feature representation and optimize model training for convolutional neural networks (CNN), which is referred to as the wavelet CNN (WCNN). We demonstrate that WCNN outperforms standard CNNs in multi-class classification tasks, distinguishing among four categories of brain MRI images such as normal, glioma, meningioma, and pituitary tumor images. This approach highlights the potential to achieve high classification accuracy even with low-resolution data, ultimately reducing the memory and computational resources required for data processing and model training.

关键词： Wavelet transforms Training Accuracy Magnetic resonance imaging Computational modeling Brain modeling Feature extraction Data models Convolutional neural networks Tumors

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Exploration of the Role of Cryptoprocessors in Advancing IoT Security

Exploration of the Role of Cryptoprocessors in Advancing IoT...

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International Conference on Distributed Computing in Sensor systems (DCOSS)

作者： Elena Kakoulli Eleftherios Zacharioudakis Department of Computer Science Intelligent Systems Laboratory Neapolis University Pafos Pafos Cyprus Electrical Engineering and Computer Engineering and Informatics Cyprus University of Technology Limassol Cyprus Igor Sikorsky Kyiv Polytechnic Institute National Technical University of Ukraine Kyiv Ukraine

ISBN: (数字)9798350369441

ISBN: (纸本)9798350369458

This paper presents a thorough exploration of Cryptoprocessors in the context of the Internet of Things (IoT). The focus is on hardware support, cryptographic processors, and energy-efficient designs to fortify the security of IoT ecosystems. Leveraging insights from recent research papers, the survey examines various aspects of Cryptoprocessor implementations, ranging from lightweight countermeasures to advanced lattice-based post-quantum cryptography. The proposed paper amalgamates findings from studies on hardware architectures, energy-efficient designs, and innovative cryptographic algorithms to provide a holistic overview of state-of-the-art advancements in IoT security. The synthesis of this survey’s exploration aims to contribute to the ongoing discourse on securing IoT devices through robust hardware-backed cryptographic solutions.

关键词： Surveys Industries Technological innovation Program processors Ecosystems Hardware Energy efficiency

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Fault Tolerant Control Allocation Scheme for LPV system

Fault Tolerant Control Allocation Scheme for LPV system

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Control Conference (ANZCC), Australian and New Zealand

作者： Salman Ijaz Ahmed Nasr Mirza Tariq Hamayun Key Laboratory of More Electric Aircraft Zhejiang Province and members of Control Systems laboratory University of Nottingham Ningbo China Department of Electrical and Computer Engineering COMSATS University Islamabad Lahore Campus Pakistan

This paper proposed a passive fault tolerant control (FTC) approach for the class of linear parameter-varying systems to deal with faults and failures in the actuator channel. The method provided in this study combines the robustness feature of integral sliding mode control (ISMC) and control allocation (CA) obtained through singular value decomposition of the input matrix. The purpose is to effectively handle faults and failures along the entire operating spectrum, which involves various scheduling parameters. This technique is effective because the same baseline controller, initially developed for a nominal system, can deal with a wide range of faults and failures without acquiring fault information. The performance of ISM-FTC is tested on a longitudinal model of aircraft system. Numerical simulations indicate no noticeable difference in tracking performance between nominal and faulty conditions.

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VersaSens: An Extendable Multimodal Platform for Next-Generation Edge-AI Wearables

IEEE Transactions on Circuits and Systems for Artificial Int...

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IEEE Transactions on Circuits and systems for Artificial Intelligence 2024年第1期1卷 83-96页

作者： Taraneh Aminosharieh Najafi José Angel Miranda Calero Jérôme Thevenot Benjamin Duc Stefano Albini Alireza Amirshahi Hossein Taji María José Belda Beneyto Antonio Affanni David Atienza Embedded Systems Laboratory (ESL) Institute of Electrical and Micro Engineering École Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland Polytechnic Department of Engineering and Architecture Udine Italy Computer Architecture and Automation Department Universidad Complutense de Madrid Madrid Spain

The transition of healthcare towards digitalization is closely related to the advancement of health-related technologies, including wearable sensors and edge computing. In this paper, we present VersaSens, a versatile and customizable platform concept and its real implementation as a tool to boost research in wearable sensors. The platform embodies the core attributes of the VersaSens concept: versatility, flexibility, and extendability across multiple aspects of hardware, software, and processing components. It features a modular design, consisting of sensor, processor, and co-processor modules, allowing for various configurations. To evaluate the efficiency of the platform, we tested three use cases: cough monitoring, heartbeat classification and epileptic seizure detection. In all cases, the results indicate that the platform effectively executes the applications, achieving low energy consumption. In particular, our findings indicates that the integration of a domain-specific edge-AI co-processor [i.e., HEEP ocrates (Machetti et al., 2024)] equipped with several hardware accelerators further improved the overall execution time and energy consumption of the system. These results demonstrate the potential of VersaSens to effectively support a diverse range of edge-AI applications and configurations, thereby providing a robust foundation for the research and development of novel smart wearable sensor systems.

关键词： Sensors Wearable devices Artificial intelligence Wearable sensors Medical services Intelligent sensors Monitoring

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An Optimal Bipolar MVDC Coaxial Power Cable Design for Envisaged All Electric Wide Body Aircraft

An Optimal Bipolar MVDC Coaxial Power Cable Design for Envis...

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Conference on electrical Insulation and Dielectric Phenomena, (CEIDP)

作者： Anoy Saha Arian Azizi Mona Ghassemi Department of Electrical and Computer Engineering Zero Emission Realization of Optimized Energy Systems (ZEROES) Laboratory The University of Texas at Dallas Richardson TX USA

Future generations of electrified aircraft, such as more electric aircraft (MEA) and all-electric aircraft (AEA), will require high-power-delivery and low-system-mass electric power systems (EPS). Designing aircraft cables confronts thermal challenges due to the limited heat transfer by convection at a cruising altitude of 12.2 km (18.8 kPa) for wide-body aircraft. These thermal challenges are exacerbated by implementing bipolar MVDC EPSs which are formed of two adjacent power cables, conventionally. In this regard, coaxial geometry for cables can be evaluated as a solution to this problem. In this paper, a coaxial MVDC power cable is, for the first time, designed with inner and outer conductors carrying the same ampacity of 1000 A when the voltage of the inner and outer conductors is −5 kV and +5 kV, respectively. This design compares the effectiveness of coaxial power cables to the conventional arrangement of bipolar MVDC cable systems. This study will analyze three case studies to determine if a coaxial geometry is better than a conventional arrangement for a bipolar MVDC cable system or not. According to the findings of this study, coaxial cable requires thicker insulation and more conductors to maintain the same maximum electric field norm within cable insulation and ampacity. As a result, coaxial cables result in a greater mass and cross-sectional area than standard bipolar cables. For the envisaged AEA, the investigation in this paper addresses questions about the performance of coaxial geometry for bipolar MVDC power cables.

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Hybrid Sub-Harmonic Synchronous Machines Using Series and parallel Consequent Permanent Magnet

Hybrid Sub-Harmonic Synchronous Machines Using Series and Pa...

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IEEE Energy Conversion Congress and Exposition, ECCE

作者： S M Sajjad Hossain Rafin Qasim Ali Osama A. Mohammed Dept. of Electrical and Computer Engineering Energy Systems Research Laboratory Florida International University Miami Florida USA Department of Electrical Engineering Sukkur IBA University Sukkur Pakistan

This paper presents novel sub-harmonic synchronous machines having series or parallel permanent magnet structures on rotors for better performance in terms of greater torque density. The stator of the machines has two sets of three-phase winding, where the additional winding is used to generate sub-harmonic magnetomotive force components for brushless operation. Similar to the stator, the rotor of them uses an additional winding to induce that sub-harmonic component. Rotor also uses a permanent magnet to improve machine performance in series or parallel hybrid structures having conventional or consequent pole permanent magnet structures. In this paper, 4 different rotors, 3 having hybrid excitation, are used and their performance is compared. To validate the performance, a 2D finite element analysis of 8 poles and 48 slots of sub-harmonic synchronous machines is carried out with different rotors. Finally, the wide-speed operation of the proposed machine is discussed.

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