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arXiv 2025年

作者： Majhor, Casey D. Bos, Jeremy P. Robust Autonomous Systems Laboratory Department of Electrical and Computer Engineering Michigan Technological University HoughtonMI49931 United States

We present a multifractal artificial terrain generation method that uses the 3D Weierstrass-Mandelbrot function to control roughness. By varying the fractal dimension used in terrain generation across three different values, we generate 60 unique off-road terrains. We use gradient maps to categorize the roughness of each terrain, consisting of low-, semi-, and high-roughness areas. To test how the fractal dimension affects the difficulty of vehicle traversals, we measure the success rates, vertical accelerations, pitch and roll rates, and traversal times of an autonomous ground vehicle traversing 20 randomized straight-line paths in each terrain. As we increase the fractal dimension from 2.3 to 2.45 and from 2.45 to 2.6, we find that the median area of low-roughness terrain decreases 13.8% and 7.16%, the median area of semi-rough terrain increases 11.7% and 5.63%, and the median area of high-roughness terrain increases 1.54% and 3.33%, all respectively. We find that the median success rate of the vehicle decreases 22.5% and 25% as the fractal dimension increases from 2.3 to 2.45 and from 2.45 to 2.6, respectively. Successful traversal results show that the median root-mean-squared vertical accelerations, median root-mean-squared pitch and roll rates, and median traversal times all increase with the fractal dimension. © 2025, CC BY.

关键词： Off road vehicles

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Average Coverage Probability for Base-Station-to-UAV Communications Over 6G Multiple Access Wireless Networks

Average Coverage Probability for Base-Station-to-UAV Communi...

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IEEE International Symposium on Information Theory

作者： Xi Zhang Qixuan Zhu H. Vincent Poor Department of Electrical and Computer Engineering Networking and Information Systems Laboratory Texas A&#x0026 M University TX USA Department of Electrical and Computer Engineering Princeton University Princeton USA

ISBN: (数字)9781665421591

ISBN: (纸本)9781665421607

While the fifth generation (5G) of wireless networks is currently being rolled out, wireless networks still need further development to meet the requirements of dramatically increasing numbers of users and new applications and the resulting traffic expected in the coming decade and beyond. The sixth generation (6G) of wireless networks is envisioned to respond to this by providing services with massive access, ultra-reliability, low latency, intelligence, and security while maximizing the spectral/energy/cost efficiency. Unmanned aerial vehicles (UAVs) have attracted considerable research attention due to their mobility and ability to line-of-sight (LoS) coverage in areas that suffer from low channel quality. However, how to characterize a UAV’s coverage area is a challenging problem and has not been thoroughly studied. To address this issue, in this paper we investigate the coverage performance of base station (BS) to UAV communications with a number of interfering mobile users. We first establish a Nakagami-m fading channel model for BS-toUAV wireless communications. Then, we derive a closed-form expression for the UAV’s average coverage probability under the scenario of interfering mobile users. Finally, numerical results confirm our derived analytical results and evaluate the UAV’s performance under different scenarios that anticipate 6G wireless networking models.

关键词： 6G mobile communication Fading channels Base stations Closed-form solutions Wireless networks Probability Autonomous aerial vehicles

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Grid Services Demonstration Using Service-Oriented DERMS

Grid Services Demonstration Using Service-Oriented DERMS

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Grid Edge Technologies Conference & Exposition (Grid Edge), IEEE PES

作者： Midrar Adham Sean J. Keene Tylor Slay Jaime T. Kolln Robert B. Bass Department of Electrical & Computer Engineering Portland State University Portland OR Distributed Systems Pacific Northwest National Laboratory Richland WA

ISBN: (数字)9798350352528

ISBN: (纸本)9798350352535

This work demonstrates four grid service use cases using a service-oriented DER Management System within an Energy Grid of Things network. Imposed by a set of rules referred to as the Energy Service Interface, the DER Management System uses IEEE 2030.5 as its primary communication protocol. To simulate the efforts of Grid Operators, Grid Service Providers, and consumers to provide grid services, a co-simulation environment that leverages the GridAPPS-D simulation platform was developed. The results show that a service-oriented DER Management System provides a means of achieving reliable and impactful grid services while protecting customers' privacy and ensuring their agency over their Distributed Energy Resources.

关键词： Privacy Protocols Real-time systems Distributed power generation Servers Reliability Information exchange

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Van der Waals integration inch-scale 2D MoSe_(2) layers on Si for highly-sensitive broadband photodetection and imaging

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Nano Research 2023年第8期16卷 11422-11429页

作者： Yupiao Wu Shuo-En Wu Jinjin Hei Longhui Zeng Pei Lin Zhifeng Shi Qingming Chen Xinjian Li Xuechao Yu Di Wu School of Physics and Microelectronics and Key Laboratory of Material PhysicsZhengzhou UniversityZhengzhou 450052China Department of Electrical and Computer Engineering University of California San DiegoLa JollaCA 92093USA School of Microelectronics Science and Technology Sun Yat-Sen UniversityZhuhai 519082China Key Laboratory of Multifunctional Nanomaterials and Smart Systems Suzhou Institute of Nano-Tech and Nano-BionicsChinese Academy of SciencesSuzhou 215123China

As one of the most promising materials for two-dimensional transition metal chalcogenides(2D TMDs),molybdenum diselenide(MoSe_(2))has great potential in photodetectors due to its excellent properties like tunable bandgap,high carrier mobility,and excellent air *** 2D MoSe_(2)-based photodetectors have been reported to exhibit admired performance,the large-area 2D MoSe_(2)layers are difficult to be achieved via conventional synthesis methods,which severely impedes its future ***,we present the controllable growth of large-area 2D MoSe_(2)layers over 3.5-inch with excellent homogeneity by a simple post-selenization ***,a high-quality n-MoSe_(2)/p-Si van der Waals(vdW)heterojunction device is in-situ fabricated by directly growing 2D n-MoSe_(2)layers on the patterned p-Si substrate,which shows a self-driven broadband photoresponse ranging from ultraviolet to mid-wave infrared with an impressive responsivity of 720.5 mA·W^(−1),a high specific detectivity of 10^(13) Jones,and a fast response time to follow nanosecond pulsed optical *** addition,thanks to the inch-level 2D MoSe_(2)layers,a 4×4 integrated heterojunction device array is achieved,which has demonstrated good uniformity and satisfying imaging *** large-area 2D MoSe_(2)layer and its heterojunction device array have great promise for high-performance photodetection and imaging applications in integrated optoelectronic systems.

关键词： molybdenum diselenide large-area synthesis broadband photodetector integrated device array van der Waals(vdW)heterojunction

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Trajectory Tracking of Tractor-Trailer Wheeled Mobile Robots via Dynamic Feedback Linearization in Forward and Backward Motion 10

Trajectory Tracking of Tractor-Trailer Wheeled Mobile Robots...

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10th International Conference on Control, Instrumentation and Automation, ICCIA 2024

作者： Olyai, Mohammad Alipour, Khalil Tarvirdizadeh, Bahram Sorouri, Majid Ghamari, Mohammad Laboratory Department of Mechatronics Eng School of Intelligent Systems Engineering College of Interdisciplinary Science and Technology Tehran Iran Maynooth University Maynooth Department of Electronic Engineering Co. Kildare Ireland Islamic Azad University Science and Research Branch Department of Computer and Mechatronics Engineering Tehran Iran California Polytechnic State University Electrical Engineering Department San Luis ObispoCA93407 United States

ISBN: (纸本)9798331509972

One type of wheeled mobile robot widely used in public transportation and for carrying high payloads is the tractor-Trailer wheeled robots (TTWRs). This study considers a differentially-driven tractor under pure rolling conditions, which is subject to nonholonomic constraints. Controlling a TTWR in both backward and forward motion is challenging due to inherent instability. To address this issue and achieve trajectory tracking control for these systems, this paper employs dynamic feedback linearization (DFL) to overcome the limitations of static feedback linearization (SFL). The system's response will be examined under various trajectories and initial conditions for both forward and backward motion. © 2024 IEEE.

关键词： Tractors (truck)

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ChatBCI: A P300 Speller BCI Leveraging Large Language Models for Improved Sentence Composition in Realistic Scenarios

arXiv

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arXiv 2024年

作者： Hong, Jiazhen Wang, Weinan Najafizadeh, Laleh Integrated Systems and NeuroImaging Laboratory Department of Electrical and Computer Engineering Rutgers University PiscatawayNJ08854 United States

P300 speller brain computer interfaces (BCIs) allow users to compose sentences by selecting target keys on a graphical user interface (GUI) through the detection of P300 component in their electroencephalogram (EEG) signals following visual stimuli. Most existing P300 speller BCIs require users to spell all or the first few initial letters of the intended word, letter by letter. Consequently, a large number of keystrokes are required to write a sentence, which can be time consuming, increasing user’s cognitive load and fatigue. Therefore, there is a need for more efficient and user-friendly methods for faster, and practical sentence composition. In this work, we introduce ChatBCI, a P300 speller BCI that leverages the zero-shot learning capabilities of large language models (LLMs) to suggest words from user-spelled initial letters or predict the subsequent word(s), reducing keystrokes and accelerating sentence composition. ChatBCI retrieves word suggestions through remote queries to the GPT-3.5 API. A new GUI, displaying GPT-3.5 word suggestions as extra keys is designed. Stepwise linear discriminant analysis (SWLDA) is used for the P300 classification. Seven subjects completed two online spelling tasks: 1) copy-spelling a self-composed sentence using ChatBCI, and 2) improvising a sentence using ChatBCI’s word suggestions. Results demonstrate that in Task 1, on average, ChatBCI outperforms letter-by-letter BCI spellers, reducing time and keystrokes by 62.14% and 53.22%, respectively, and increasing information transfer rate by 198.96%. In Task 2, ChatBCI achieves 80.68% keystroke savings and a record 8.53 characters/min for typing speed. Overall, ChatBCI by employing remote LLM queries enhances sentence composition in realistic scenarios, significantly outperforming traditional spellers without requiring local model training or storage. ChatBCI’s (multi-) word predictions, combined with its new GUI, pave the way for developing next-generation speller BCIs that are e

关键词： Electroencephalography

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A Tube-Based Reinforcement Learning Approach for Optimal Motion Planning in Unknown Workspaces

A Tube-Based Reinforcement Learning Approach for Optimal Mot...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Panagiotis Rousseas Charalampos P. Bechlioulis Kostas J. Kyriakopoulos School of Mechanical Engineering Control Systems Laboratory National Technical University of Athens Greece Department of Electrical and Computer Engineering University of Patras

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

In this work, a tube-based nearly optimal solution to motion planning in unknown workspaces is presented. The advantages of reactive motion planning are combined with a Policy Iteration Reinforcement Learning scheme to yield a novel solution for unknown workspaces that inherits provable safety, convergence and optimality. Moreover, in simply-connected workspaces, our method is proven to asymptotically provide the globally optimal path. Our method is compared against a provably asymptotically optimal RRT ⋆ method, as well as a relevant reactive method and provides satisfactory performance, closely matching or outperforming the former.

关键词： Reinforcement learning Planning Safety Robotics and automation Convergence

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BitMoD: Bit-serial Mixture-of-Datatype LLM Acceleration

arXiv

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arXiv 2024年

作者： Chen, Yuzong AbouElhamayed, Ahmed F. Dai, Xilai Wang, Yang Andronic, Marta Constantinides, George A. Abdelfattah, Mohamed S. Computer Systems Lab Cornell University United States Systems and Networking Research Group Microsoft Research United States Department of Electrical and Electronic Engineering Imperial College London United Kingdom

Large language models (LLMs) have demonstrated remarkable performance across various machine learning tasks. Yet the substantial memory footprint of LLMs significantly hinders their deployment. In this paper, we improve the accessibility of LLMs through BitMoD1, an algorithm-hardware co-design solution that enables efficient LLM acceleration at low weight precision. On the algorithm side, BitMoD introduces fine-grained data type adaptation that uses a different numerical data type to quantize a group of (e.g., 128) weights. Through the careful design of these new data types, BitMoD is able to quantize LLM weights to very low precision (e.g., 4 bits and 3 bits) while maintaining high accuracy. On the hardware side, BitMoD employs a bit-serial processing element to easily support multiple numerical precisions and data types;our hardware design includes two key innovations: First, it employs a unified representation to process different weight data types, thus reducing the hardware cost. Second, it adopts a bit-serial dequantization unit to rescale the per-group partial sum with minimal hardware overhead. Our evaluation on six representative LLMs demonstrates that BitMoD significantly outperforms state-of-the-art LLM quantization and acceleration methods. For discriminative tasks, BitMoD can quantize LLM weights to 4-bit with © 2024, CC BY-NC-ND.

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Advances in magnetic-assisted triboelectric nanogenerators:structures,materials and self-sensing systems

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International Journal of Extreme Manufacturing 2024年第5期6卷 162-188页

作者： Pengfan Wu Chenxi Zhao Endian Cui Shiwei Xu Tao Liu Fayang Wang Chengkuo Lee Xiaojing Mu Key Laboratory of Optoelectronic Technology&Systems Ministry of Education International R&D Center of Micro-Nano Systems and New Materials TechnologyChongqing UniversityChongqing 400044People’s Republic of China Department of Electrical and Computer Engineering National University of SingaporeSingaporeSingapore

Triboelectric nanogenerators(TENG),renowned for their remarkable capability to harness weak mechanical energy from the environment,have gained considerable attention owing to their cost-effectiveness,high output,and *** review provides a unique perspective by conducting a comprehensive and in-depth analysis of magnetically assisted TENGs that encompass structures,materials,and self-powered sensing *** systematically summarize the diverse functions of the magnetic assistance for TENGs,including system stiffness,components of the hybrid electromagnetic-triboelectric generator,transmission,and interaction *** the material domain,we review the incorporation of magnetic nano-composites materials,along with ferrofluid-based TENG and microstructure verification,which have also been summarized based on existing ***,we delve into the research progress on physical quantity sensing and human-machine interface in magnetic-assisted *** analysis highlights that magnetic assistance extends beyond the repulsive and suction forces under a magnetic field,thereby playing multifaceted roles in improving the output performance and environmental adaptability of the ***,we present the prevailing challenges and offer insights into the future trajectory of the magnetic-assisted TENGs development.

关键词： triboelectric nanogenerator magnetic assistance tuning structure controlled material preparation self-powered system

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An Efficient Medical Image Deep Fusion Model Based on Convolutional Neural Networks

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computers, Materials & Continua 2023年第2期74卷 2905-2925页

作者： Walid El-Shafai Noha A.El-Hag Ahmed Sedik Ghada Elbanby Fathi E.Abd El-Samie Naglaa F.Soliman Hussah Nasser AlEisa Mohammed E.Abdel Samea Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Higher Institute of Commercial Science Management Information SystemsEl-Mahala El-KobraEgypt Department of the Robotics and Intelligent Machines Faculty of Artificial IntelligenceKafrelsheikh UniversityKafr El-SheikhEgypt Department of Industrial Electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia Medical Imaging and Interventional Radiology National Liver InstituteMenoufia UniversityEgypt

Medical image fusion is considered the best method for obtaining one image with rich details for efficient medical diagnosis and *** learning provides a high performance for several medical image analysis *** paper proposes a deep learning model for the medical image fusion *** model depends on Convolutional Neural Network(CNN).The basic idea of the proposed model is to extract features from both CT and MR ***,an additional process is executed on the extracted *** that,the fused feature map is reconstructed to obtain the resulting fused ***,the quality of the resulting fused image is enhanced by various enhancement techniques such as Histogram Matching(HM),Histogram Equalization(HE),fuzzy technique,fuzzy type,and Contrast Limited Histogram Equalization(CLAHE).The performance of the proposed fusion-based CNN model is measured by various metrics of the fusion and enhancement *** realistic datasets of different modalities and diseases are tested and ***,real datasets are tested in the simulation analysis.

关键词： Image fusion CNN deep learning feature extraction evaluation metrics medical diagnosis

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