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IEEE Conference on Vehicular Technology (VTC)

作者： Maria Cecilia Luna Alvarado Carlos Rafael Nogueira Da Silva Nidhi Simmons Paschalis C. Sofotasios Simon L. Cotton Michel Daoud Yacoub Wireless Technology Laboratory School of Electrical and Computer Engineering University of Campinas Campinas Brazil Department of Electrical Engineering Federal University of Triângulo Mineiro Uberaba Brazil Centre for Wireless Innovation (CWI) The Queen’s University of Belfast Belfast UK Department of Computer and Information Engineering C2PS and 6G Center Khalifa University Abu Dhabi UAE

ISBN: (数字)9798331517786

ISBN: (纸本)9798331517793

Reconfigurable Intelligent Surfaces (RISs) are considered a key candidate technology for next-generation 6G wireless systems, promising to extend network coverage, enhance spectral efficiency, and effectively mitigate interference. RISs will achieve this by controlling the propagation environment, enabled by carefully altering the reflective properties of their elements. In this context, this work presents a general framework for deriving the exact probability density function (PDF) and higher-order moments of the signal-to-ratio (SNR) in a RIS system, considering the direct transmission and RIS-assisted links from source to destination. Recognizing the analytical challenges associated with obtaining exact statistics for RIS-assisted systems, which persist in both common and more generalized fading models, the proposed contribution is realized with the aid of the suitable α-µ fading model. To that end, we derive accurate approximations for the κ-µ and the extended η-µ distributions, which constitute effective and versatile multipath fading models. Based on this, the achieved results are virtually indistinguishable from those obtained through simulations for various environmental settings. This renders the proposed framework a valuable tool for evaluating the performance of RIS systems, particularly in terms of the corresponding average symbol error rate (ASER). Tractable closed-form asymptotic expressions are also derived and utilized to provide a deeper understanding of the system’s behavior.

关键词： Fading channels Wireless communication Analytical models Vehicular and wireless technologies Symbols Reconfigurable intelligent surfaces Probability density function Diversity methods Encoding Signal to noise ratio

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BORPIC++: A Body-of-Revolution Particle-in-Cell Algorithm with Radial Perfectly Matched Layers and Dual Polarizations

BORPIC++: A Body-of-Revolution Particle-in-Cell Algorithm wi...

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USNC-URSI Radio Science Meeting (Joint with AP-S Symposium)

作者： Dong-Yeop Na Fernando L. Teixeira Yuri A. Omelchenko Hongbin Kim Department of Electrical Engineering Pohang University of Science and Technology Pohang Gyeongsangbuk-do South Korea ElectroScience Laboratory and Department of Electrical and Computer Engineering The Ohio State University Columbus OH USA Trinum Research Inc. San Diego CA USA

ISBN: (数字)9789463968119

ISBN: (纸本)9798350359497

Plasma turbulence, arising from nonlinear interactions in charged plasma, occurs in various environments such as astrophysical and ionospheric plasmas. Extreme space weather events pose risks to space assets, especially regarding radiation belt flux enhancements affecting satellites. “Radiation belt remediation” schemes, including heavy ion beam injection, aim to scatter energetic electrons. 3D particle-in-cell (PIC) simulations model these interactions, but their computational demands are significant. To address this, we propose an innovative axisymmetric full PIC unstructured mesh simulation model, particularly beneficial for plasmas with cylindrical symmetry, enabling higher resolution and longer simulations. A novel irregular-mesh-based electromagnetic particle-in-cell algorithm has been developed for fully kinetic plasma simulations involving in the body-of-revolution geometries. Leveraging the cylindrical symmetry, we utilize a field rescaling and a coordinate mapping based on transformation optics to convert the original 3D Maxwell's equations in a cylindrical coordinate system into the equivalent 2D one in the meridian plane. We exploit the discrete exterior calculus for the consistent discretization of various Maxwell dynamical variables on irregular meshes. As a result, exact charge conservation is attained on a discrete mesh from first principles. We model dual polarizations accounting for all possible motions of charged particles. A cylindrical perfectly matched layer is implemented in the radial direction to enable the simulation of open space problems while avoiding spurious interactions between reflected waves and charged particles can be avoided. As a numerical application of the BORPIC++ algorithm, we simulate the the ion beam deflection caused by a magnetic dipole positioned on an insulating plate. This simulation corresponds to small-scale laboratory experiments mimicking lunar magnetic anomalies caused by interactions with the solar wind. Specifi

关键词： Solid modeling Magnetic flux Three-dimensional displays Ionizing radiation Computational modeling Space radiation Mathematical models

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Semantic Communication for Cooperative Perception with HARQ

Semantic Communication for Cooperative Perception with HARQ

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IEEE Workshop on Machine Learning for Signal Processing

作者： Yucheng Sheng Hao Ye Le Liang Shi Jin National Mobile Communications Research Laboratory Southeast University Nanjing China Department of Electrical and Computer Engineering University of California Santa Cruz USA Purple Mountain Laboratories Nanjing China

ISBN: (数字)9798350372250

ISBN: (纸本)9798350372267

Cooperative perception, offering a wider field of view than standalone perception, is becoming increasingly crucial in autonomous driving. This advanced perception is enabled through vehicle-to-vehicle (V2V) communication, allowing connected automated vehicles (CAVs) to exchange sensor data, such as LiDAR point clouds, thereby enhancing the collective understanding of the environment. In this paper, we leverage an importance map to distill critical semantic information, introducing a cooperative perception semantic communication framework that employs intermediate fusion. Furthermore, recognizing the necessity for reliable transmission, especially in low SNR scenarios, we introduce a novel semantic error detection method that is integrated within our semantic communication framework in the spirit of hybrid automatic repeated request (HARQ). Simulation results show that our model surpasses traditional separate source-channel coding methods in perception performance. Additionally, in terms of throughput, our proposed HARQ schemes demonstrate superior efficiency compared to conventional coding approaches.

关键词： Point cloud compression Wireless communication Wireless sensor networks Laser radar Simulation Vehicular ad hoc networks Signal processing Throughput Encoding Signal to noise ratio

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An Improved Model for Sap Flow Prediction Based on Linear Trend Decomposition 19th

An Improved Model for Sap Flow Prediction Based on Linear Tr...

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19th EAI International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness, QShine 2023

作者： Li, Bo Li, Yane Feng, Hailin Wu, Bin Zhu, Qiang Weng, Xiang Ruan, Yaoping College of Mathematics and Computer Science Zhejiang A&F University 666 Wusu Street Hangzhou311300 China Key Laboratory of Forestry Intelligent Monitoring and Information Technology of Zhejiang Province Hangzhou311300 China China Key Laboratory of State Forestry and Grassland Administration on Forestry Sensing Technology and Intelligent Equipment Hangzhou311300 China College of Optical Mechanical and Electrical Engineering Zhejiang A&F University Hangzhou311300 China

ISBN: (纸本)9783031651229

Tree transpiration plays an important role in environmental change, which mainly assessed by sap flow. It is great significance to predict sap flow accurately for estimation of water consumption, management of water resource and making of sustainable development strategy for geohydrological balance under climate change. In this study, an improved prediction model was built with Dilnear algorithm using historical environment factors to assess short-term sap flow. Specifically, a public dataset including 17568 records was used. One record have one sap flow value and 9 environment factors which measured from January 1, 2016 to December 31, 2016 at 30 min interval in Canada for Tsuga canadensis (L.) Carriere. After data processed with missing value padding and normalization, seven factors was extracted with fusion of Pearson correlation and Grey correlation method. Then, sap flow prediction model was established with Dlinear algorithm. For comparison and analysis, five other deep learning networks of CNN, GRU, LSTM, Transformer and Informer were used to built sap flow prediction model respectively. Results shown that Dlinear based model has better performance than other models established in this paper. The coefficient of determination (R2), the Mean Absolute Error (MSE) and the Mean Square Error (MAE) achieved 0.9568, 0.0282 and 0.0017 for Dlinear based model. R2 of Dlinear based model is of 20.37%, 14.9% and 21.93% higher than CNN, GRU and LSTM based model respectively. In addition, we also analyzed length of look-back window and prediction window. Results shown that when length of look-back window was set as 720, Dlinear based model has better performance with R2 of 0.9568, which higher of 2.62%, 7.75%, 18.95% and 35.46% than length of 336, 192, 96, and 48. When the prediction window length was set as 96, Dlinear based model has higher of R2 and smaller of MSE and MAE than length of 240, 336 and 720. At the same time, we compared performance of models established wit

关键词： Prediction models

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Model-Free Dynamic Control of a 3-DoF Delta Parallel Robot for Pick-and-Place Application based on Deep Reinforcement Learning

Model-Free Dynamic Control of a 3-DoF Delta Parallel Robot f...

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RSI/ISM International Conference on Robotics and Mechatronics (ICROM)

作者： Hasan Jalali Saba Samadi Ahmad Kalhor Mehdi Tale Masouleh Human and Robot Interaction Laboratory School of Electrical and Computer Engineering University of Tehran Tehran Iran Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran

ISBN: (纸本)9781665454537

This article investigates the performance of the Delta robot using model-free controller. Since it is difficult to obtain an accurate dynamic model of the robot and identification methods are complex and challenging. Therefore, in this article, a new approach is presented which checks the performance of the Delta robot in pick-and-place operation using model-free dynamic controllers. For the purposes of this paper, Deep Reinforcement Learning (DRL) and also the Deep Deterministic Policy Gradient (DDPG) network is used. The DDPG algorithm is implemented for the first time on the Delta robot, and according to the obtained results, it reveals that it can provide a favorable approach for the pick-and-place operation. In this method, based on the science of DRL, a reward function based on the pick-and-place operation is also defined, which gives negative reward (punishment) or a positive reward according to the way the robot performs. It is noteworthy that according to the obtained results, it is possible to generalize other points for the pick-and-place operation. It should be noted that the robot was able to learn the target after a long episode and its graph converged after approximately 18,000 episodes.

关键词： Training Deep learning Parallel robots Actuators Mechatronics Heuristic algorithms Reinforcement learning

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Secure Wireless-Powered zeRIS Communications

arXiv

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arXiv 2025年

作者： Chen, Jingyu Cao, Kunrui Diamantoulakis, Panagiotis D. Lv, Lu Yang, Liang Chi, Haolian Ding, Haiyang School of Information and Communications National University of Defense Technology Wuhan430035 China Department of Electrical and Computer Engineering Aristotle University of Thessaloniki Thessaloniki54124 Greece State Key Laboratory of Integrated Services Networks Xidian University Xi’an710071 China College of Computer Science and Electronic Engineering Hunan University Changsha410082 China

This paper introduces the concept of wireless-powered zero-energy reconfigurable intelligent surface (zeRIS), and investigates a wireless-powered zeRIS aided communication system in terms of security, reliability and energy efficiency. In particular, we propose three new wireless-powered zeRIS modes: 1) in mode-I, N reconfigurable reflecting elements are adjusted to the optimal phase shift design of information user to maximize the reliability of the system;2) in mode-II, N reconfigurable reflecting elements are adjusted to the optimal phase shift design of cooperative jamming user to maximize the security of the system;3) in mode-III, N1 and N2 (N1+N2 = N) reconfigurable reflecting elements are respectively adjusted to the optimal phase shift designs of information user and cooperative jamming user to balance the reliability and security of the system. Then, we propose three new metrics, i.e., joint outage probability (JOP), joint intercept probability (JIP), and secrecy energy efficiency (SEE), and analyze their closed-form expressions in three modes, respectively. The results show that under high transmission power, all the diversity gains of three modes are 1, and the JOPs of mode-I, mode-II and mode-III are improved by increasing the number of zeRIS elements, which are related to N2, N, and N12, respectively. In addition, mode-I achieves the best JOP, while mode-II achieves the best JIP among three modes. We exploit two security-reliability trade-off (SRT) metrics, i.e., JOP versus JIP, and normalized joint intercept and outage probability (JIOP), to reveal the SRT performance of the proposed three modes. It is obtained that mode-II outperforms the other two modes in the JOP versus JIP, while mode-III and mode-II achieve the best performance of normalized JIOP at low and high transmission power, respectively. © 2025, CC BY.

关键词： Outages

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Reconstructing Richtmyer-Meshkov instabilities from noisy radiographs using low dimensional features and attention-based neural networks

arXiv

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arXiv 2024年

作者： Serino, Daniel A. Klasky, Marc L. Nadiga, Balasubramanya T. Xu, Xiaojian Wilcox, Trevor Los Alamos National Laboratory Los AlamosNM87545 United States Dept. of Electrical and Computer Engineering University of Michigan Ann ArborMI48109 United States

A trained attention-based transformer network can robustly recover the complex topologies given by the Richtmyer-Meshkoff instability from a sequence of hydrodynamic features derived from radiographic images corrupted with blur, scatter, and noise. This approach is demonstrated on ICF-like double shell hydrodynamic simulations. The key component of this network is a transformer encoder that acts on a sequence of features extracted from noisy radiographs. This encoder includes numerous self-attention layers that act to learn temporal dependencies in the input sequences and increase the expressiveness of the model. This approach is demonstrated to exhibit an excellent ability to accurately recover the Richtmyer-Meshkov instability growth rates, even despite the gas-metal interface being greatly obscured by radiographic noise. © 2024, CC BY.

关键词： Mesh generation

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Unidirectional scattering with spatial homogeneity using photonic time disorder

arXiv

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arXiv 2022年

作者： Kim, Jungmin Lee, Dayeong Yu, Sunkyu Park, Namkyoo Photonic Systems Laboratory Department of Electrical and Computer Engineering Seoul National University Seoul08826 Korea Republic of Intelligent Wave Systems Laboratory Department of Electrical and Computer Engineering Seoul National University Seoul08826 Korea Republic of

The temporal degree of freedom in photonics has been a recent research hotspot due to its analogy with spatial axes, causality, and open-system characteristics. In particular, the temporal analogues of photonic crystals have stimulated the design of momentum gaps and their extension to topological and non-Hermitian photonics. Although recent studies have also revealed the effect of broken discrete time-translational symmetry in view of the temporal analogy of spatial Anderson localization, the broad intermediate regime between time order and time uncorrelated disorder has not been examined. Here we investigate the inverse design of photonic time disorder to achieve optical functionalities in spatially homogeneous platforms. By developing the structure factor and order metric using causal Green’s functions for the domain of time disorder, we demonstrate engineered time scatterer, which provides unidirectional scattering with controlled scattering amplitudes. We also reveal that the order-to-disorder transition in the time domain allows for the manipulation of scattering bandwidths, which inspires resonance-free temporal colour filtering. Our work will pave the way for advancing optical functionalities without spatial patterning. © 2022, CC BY.

关键词： Degrees of freedom (mechanics)

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CNN-Based Emotional Stress Classification using Smart Learning Dataset 15

CNN-Based Emotional Stress Classification using Smart Learni...

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2022 IEEE Congress on Cybermatics: 15th IEEE International Conferences on Internet of Things, iThings 2022, 18th IEEE International Conferences on Green Computing and Communications, GreenCom 2022, 2022 IEEE International Conference on Cyber, Physical and Social Computing, CPSCom 2022 and 8th IEEE International Conference on Smart Data, SmartData 2022

作者： Andreas, Andreou Mavromoustakis, Constandinos X. Song, Houbing Batalla, Jordi Mongay Department of Computer Science University of Nicosia University of Nicosia Research Foundation Nicosia Cyprus Security and Optimization for Networked Globe Laboratory Department of Electrical Engineering and Computer Science Embry-Riddle Aeronautical University Daytona Beach FL32114-3900 United States Warsaw University of Technology National Institute of Telecommunications Warsaw Poland

ISBN: (数字)9781665454179

ISBN: (纸本)9781665454179

Smart learning analytics aims to support researchers investigating mental health by improving the interpretation of the datasets acquired from physiological biomarkers. The key enabler for emotional stress classification are Machine Learning (ML) methods in conjunction with Online Transfer Learning (OTL). The knowledge of high-level characteristics at the top layers is obtained through an optimized Convolutional Neural Network (CNN)-based on emotional stress datasets. Nevertheless, the lack of performance in a real-time environment and the temporal patterns of data acquisition complications and their interpretation motivated us to contribute by tackling these concerns. Therefore, we propose an innovative procedure based on the aforementioned orientation through our research work. Considering mining data streams with concept drifts, we enable the ensemble classifiers. For evaluation, we compare the proposed classification, the LIBrary for Large LINEAR classification (LIBLINEAR) and the Deep Belief Network with Transfer Learning (DBNTL) model. Furthermore, we utilized a multimodal dataset of physical and biological characteristics obtained by fifteen individuals during a lab study. Finally, our framework based on the extracted results has presented more accuracy in classifying an individual's sense of stress. Hence, the proposed method achieves higher efficiency than the state-of-the-art models. © 2022 IEEE.

关键词： Classification (of information)

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Very High Frequency Stability of Single-Crystal Silicon Thermal-Piezoresistive Resonators with Phase-Locked Loop

Very High Frequency Stability of Single-Crystal Silicon Ther...

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International Conference on Solid State Sensors and Actuators (TRANSDUCERS)

作者： Connor A. Watkins Jaesung Lee Jonathan P. McCandless Harris J. Hall Philip X.-L. Feng Electrical & Computer Engineering University of Florida Gainesville FL USA Air Force Research Laboratory Wright-Patterson AFB OH USA Electrical Engineering Case Western Reserve University Cleveland OH USA

This paper reports on a single-crystal silicon (Si) thermal-piezoresistive resonator (TPR) achieving very high frequency stability in phase-locked loop (PLL) measurements. A pair of resonators operating in a balanced-bridge configuration is presented, with one device being driven at resonance and the other used to null the background response. The resonance frequency of the single TPR is collected over 40 hours with closed-loop tracking by PLL and yields Allan deviation σ A ≈ 2.66ppb for an averaging time τ ≈ 4.95 seconds, which is the lowest reported value among all Si TPRs studied to date. This result is significant as it suggests that such TPRs can potentially achieve frequency stabilities comparable to, or better than, existing state-of-the-art resonators used in oscillator circuits, with significantly reduced external thermal control requirements and power demands.

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