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arXiv 2025年

作者： Nikolaidis, Panagiotis Mostafavi, Samie Gross, James Baras, John Department of Electrical and Computer Engineering The Institute for Systems Research University of Maryland United States School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden

Augmented reality applications are bitrate intensive, delay-sensitive, and computationally demanding. To support them, mobile edge computing systems need to carefully manage both their networking and computing resources. To this end, we present a proof of concept resource management scheme that adapts the bandwidth at the base station and the GPU frequency at the edge to efficiently fulfill roundtrip delay constrains. Resource adaptation is performed using a Multi-Armed Bandit algorithm that accounts for the monotonic relationship between allocated resources and performance. We evaluate our scheme by experimentation on an OpenAirInterface 5G testbed where the considered application is OpenRTiST. The results indicate that our resource management scheme can substantially reduce both bandwidth usage and power consumption while delivering high quality of service. Overall, this work demonstrates that intelligent resource control can potentially establish systems that are not only more efficient but also more sustainable. © 2025, CC BY.

关键词： Quality of service

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Temporal Sensitivity Analysis of Internal Temperature Informed Charging Algorithms and Rapid Thermal Management System for E-mobility

Temporal Sensitivity Analysis of Internal Temperature Inform...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Samanta, Akash Chetri, Chandan Karnehm, Dominic Neve, Antje Williamson, Sheldon Ontario Tech University Department of Electrical Computer and Software Engineering Oshawa Canada Bundeswehr University Munich Institute of Intelligent Distributed Systems Neubiberg Germany

ISBN: (纸本)9798350376067

The experimental studies presented in this paper reveal that existing thermal management systems (TMS) and temperature-informed charging algorithms exhibit a response time lag of at least 5.3 minutes due to their reliance on surface temperature measurements. The results indicate that changes in the internal thermal state of lithium-ion batteries (LIBs), induced by variations in charging currents, take an average of 2 minutes to manifest on the battery surface, particularly evident in cylindrical cells. Current thermal management systems for automotive battery packs solely rely on surface temperature measurements, neglecting the approximately 5.8°C temperature difference between the core and surface in TMS control. Consequently, changes in the battery's thermal state due to internal heat losses are not promptly detected by surface-mounted temperature sensors. This delayed response time accelerates battery degradation and increases the risk of thermal runaway events. In this study, temperature-informed fast charging algorithms, tested under various ambient conditions for LIBs, along with a comparative analysis, demonstrate that response time can be reduced by at least 2 minutes by considering internal temperature rather than relying solely on surface temperature measurements. Moreover, accounting for the temperature difference between the core and surface facilitates rapid TMS control and health-conscious fast charging, thereby mitigating the risk of thermal runaway events. © 2024 IEEE.

关键词： Surface measurement

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A GPS-Free Air Vehicle On-Board Positioning Mechanism Applying Feature Matching Technique 43

A GPS-Free Air Vehicle On-Board Positioning Mechanism Applyi...

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43rd AIAA DATC/IEEE Digital Avionics systems Conference, DASC 2024

作者： Hsieh, Chao-Yi Wang, Yu-Shun National Chung-Shan Institute of Science and Technology Aeronautical Systems Research Division Avionics and Electrical Engineering Department Taichung40722 Taiwan

ISBN: (纸本)9798350349610

In the contemporary era, Global Positioning System (GPS) technology has reached a high maturity, and its unparalleled convenience has led to the relegation of other technologies to secondary roles in navigation. However, the dependence of both military and civilian sectors on GPS increases the likelihood of GPS becoming a primary target in the event of conflicts. Anticipating potential loss of GPS functionality in future combat scenarios, there is a renewed emphasis on GPS-denied navigation. In this work, the authors propose replacing GPS with visual localization using image-based techniques such as offline map, image feature extraction, and image stitching to calculate location. The proposed image-based localization method is simulated and tested for its ability to handle rotation and scaling in real images. The simulation results indicate that this method performs good adaptability to the rotation and scaling of real images. In addition, considering the longer time required for offline map reading, an image localization optimization method is proposed to improve real-time performance. This method achieves real-time image localization functionality through the stitching of local maps. The simulation results show that after applying positioning optimization methods, the performance has improved 166 times compared to before. It is believed that this method can be practically applied in the development of GPS-denied positioning capabilities for unmanned aerial vehicles (UAV) or fighter jets, reducing operational risks and enhancing national defense security. © 2024 IEEE.

关键词： Global positioning system

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Vehicle Overtaking in a Bidirectional Mixed-Traffic Setting

Vehicle Overtaking in a Bidirectional Mixed-Traffic Setting

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2022 American Control Conference, ACC 2022

作者： Tariq, Faizan M. Suriyarachchi, Nilesh Mavridis, Christos Baras, John S. The Institute for Systems Research University of Maryland Electrical and Computer Engineering Department College ParkMD United States

ISBN: (数字)9781665451963

ISBN: (纸本)9781665451963

With the advent of autonomous vehicles on public roads imminent in the near future, special emphasis needs to be placed on addressing scenarios pertaining to mixed-traffic settings, comprised of human-driven and autonomous vehicles. In this paper, we address the problem of autonomous vehicle overtaking in a bidirectional mixed-traffic setting. We design a mixed-integer model predictive controller that maximizes the ego vehicle's velocity while prioritizing safety and accounting for driver comfort. The proposed approach: (i) operates in a limited sensing range while accounting for occlusion;(ii) is able to retract the overtake decision through a receding horizon approach;(iii) is robust to the variations in sensory input and driving behaviors of external agents due to behavior-dependent safety margins;and (iv) reduces to a mixed-integer optimization problem with linear constraints, yielding low computational complexity. We demonstrate the behavior of the proposed approach in a realistic traffic simulation environment. © 2022 American Automatic Control Council.

关键词： Autonomous vehicles

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An Entorhinal-Hippocampal Loop Model Based on Non-negative Sparse Coding

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Journal of The Institution of Engineers (India): Series B 2025年第1期106卷 113-127页

作者： Zhao, Kaixin Ren, Menghui College of Computer Science and Technology Henan Institute of Technology Xinxiang453003 China School of Electrical and Information Engineering Zhengzhou University Zhengzhou450001 China Manufacturing IoT Big Data Engineering Technology Research Center of Henan Province Xinxiang453003 China

In our study, we investigate how the brain maps environmental spaces into understandable maps through hippocampal place cells and entorhinal cortex grid cells. We uncover that the hippocampus and entorhinal cortex are not just directly connected but also engage in a sophisticated feedback loop crucial for spatial encoding during navigation. We developed an innovative network model based on this feedback mechanism, linking entorhinal inputs to hippocampal spatial encoding cells through a non-negative sparse coding, using grid cells and weak spatial cells as inputs. Our findings demonstrate that the model learns and adjusts the characteristics of spatial encoding cells, successfully learning the specific spatial selectivities of place cells even with inputs from cells carrying weaker spatial information. This highlights the critical role of feedback encoding in refining spatial representations, an indispensable component of the brain’s navigation system. Moreover, experiments comparing our model with others validate our model’s exceptional ability in generating precise spatial encodings, underscoring its superiority. This research not only deepens our understanding of the brain’s navigational mechanisms but also offers a robust computational framework for future neuroscience studies, emphasizing the intricate interplay between feedback loops and spatial encoding in the brain’s navigation system. © The Institution of Engineers (India) 2024.

关键词： Brain

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Selective Secondary Phase-Shift Control for High Gain in LLC Converters with Matrix Transformers

Selective Secondary Phase-Shift Control for High Gain in LLC...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Prakash, Pranav Raj Li, Qiang Virginia Polytechnic Institute and State University Center for Power Electronics Systems The Bradley Department of Electrical and Computer Engineering BlacksburgVA24061 United States

ISBN: (纸本)9798350376067

Many applications such as datacenters and electric vehicles require well-regulated isolated DC-DC power converters. However, these often require high voltage gains for a wide input voltage range or when the input supply is lost. Although resonant converters, especially LLC converters, are great candidates for such dc-dc converters, their performance at the nominal operating conditions must be sacrificed to enable the converter to reach high gain levels with the conventional frequency modulation. Matrix transformers are commonly employed to distribute the high output currents evenly among the different elemental transformers. This paper proposes a control method to utilize matrix transformers to achieve high gains while operating at the resonant frequency. One or more secondary rectifiers (SRs) can be phase-shifted with respect to the other SRs to create periods where the transformer windings are partially shorted, resulting in a precise boost to the resonant tank energy, and hence, the resonant tank gain. This technique is implemented on a 400 V/12 V LLC converter for datacenters that requires high transformer gains during the hold-up period. © 2024 IEEE.

关键词： Phase shift

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Automated and controlled patch generation for enhanced fixing of communication software vulnerabilities

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Intelligent and Converged Networks 2024年第3期5卷 222-236页

作者： Shuo Feng Shuai Yuan Zhitao Guan Xiaojiang Du School of Control and Computer Engineering North China Electric Power UniversityBeijing 100029China Department of Finance Operationsand Information SystemsBrock UniversitySt.Catharines L2S3A1Canada Department of Electrical and Computer Engineering Stevens Institute of TechnologyHobokenNJ 07030USA

Software is a crucial component in the communication systems,and its security is of paramount ***,it is susceptible to different types of attacks due to potential ***,significant time and effort is required to fix such *** propose an automated program repair method based on controlled text generation ***,we utilize a fine-tuned language model for patch generation and introduce a discriminator to evaluate the generation process,selecting results that contribute most to vulnerability ***,we perform static syntax analysis to expedite the patch verification *** effectiveness of the proposed approach is validated using QuixBugs and Defects4J datasets,demonstrating significant improvements in generating correct patches compared to other existing methods.

关键词： automatic program repair controlled text generation communication software security program language model

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Multi-Objective Transmission Expansion: An Offshore Wind Power Integration Case Study

IEEE Transactions on Energy Markets, Policy and Regulation

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IEEE Transactions on Energy Markets, Policy and Regulation 2024年第4期2卷 519-535页

作者： Khanal, Saroj Graf, Christoph Liang, Zhirui Dvorkin, Yury Unel, Burcin Johns Hopkins University Department of Electrical and Computer Engineering BaltimoreMD21218 United States New York University School of Law Institute for Policy Integrity New YorkNY10012 United States StanfordCA94305 United States Johns Hopkins University Departments of Electrical and Computer Engineering and Civil and Systems Engineering BaltimoreMD21218 United States

Despite ambitious offshore wind targets in the U.S. and globally, offshore grid planning guidance remains notably scarce, contrasting with well-established frameworks for onshore grids. This gap, alongside the increasing penetration of offshore wind and other clean-energy resources in onshore grids, highlights the urgent need for a coordinated planning framework. Our paper describes a multi-objective, multistage generation, storage and transmission expansion planning model to facilitate efficient and resilient large-scale adoption of offshore wind power. Recognizing regulatory emphasis and, in some cases, requirements to consider externalities, this model explicitly accounts for negative externalities: greenhouse gas emissions and local emission-induced air pollution. Utilizing an 8-zone ISO-NE test system and a 9-zone PJM test system, we explore grid expansion sensitivities such as impacts of optimizing Points of Interconnection (POIs) versus fixed POIs, negative externalities, and consideration of extreme operational scenarios. Our results indicate that accounting for negative externalities necessitates greater upfront investment in clean generation and storage (balanced by lower expected operational costs). Optimizing POIs could significantly reshape offshore topology or POIs, and lower total cost. Finally, accounting for extreme operational scenarios typically results in greater operational costs and sometimes may alter onshore line investment. © 2024 IEEE.

关键词： Investments

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FaceTopoNet: Facial Expression Recognition Using Face Topology Learning

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2023年第6期4卷 1526-1539页

作者： Kolahdouzi, Mojtaba Sepas-Moghaddam, Alireza Etemad, Ali Queen's University Department of Electrical and Computer Engineering and Ingenuity Labs Research Institute KingstonONK7L 3N6 Canada

Prior work has shown that the order in which different components of the face are learned using a sequential learner can play an important role in the performance of facial expression recognition systems. We propose FaceTopoNet, an end-to-end deep model for facial expression recognition, which is capable of learning an effective tree topology of the face. Our model then traverses the learned tree to generate a sequence, which is then used to form an embedding to feed a sequential learner. The devised model adopts one stream for learning structure and one stream for learning texture. The structure stream focuses on the positions of the facial landmarks, whereas the main focus of the texture stream is on the patches around the landmarks to learn textural information. We then fuse the outputs of the two streams by utilizing an effective attention-based fusion strategy. We perform extensive experiments on four large-scale in-the-wild facial expression datasets-namely AffectNet, FER2013, ExpW, and real-world affective face database-and one lab-controlled dataset (Cohn-Kanade) to evaluate our approach. FaceTopoNet achieves state-of-the-art performance on three of the five datasets and obtains competitive results on the other two datasets. We also perform rigorous ablation and sensitivity experiments to evaluate the impact of different components and parameters in our model. Finally, we perform robustness experiments and demonstrate that FaceTopoNet is more robust against occlusions in comparison to other leading methods in the area. © 2020 IEEE.

关键词： Face recognition

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Multiview Video-Based 3-D Hand Pose Estimation

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2023年第4期4卷 896-909页

作者： Khaleghi, Leyla Sepas-Moghaddam, Alireza Marshall, Joshua Etemad, Ali Queen's University Department of Electrical and Computer Engineering The Ingenuity Labs Research Institute KingstonONK7L 3N6 Canada

Hand pose estimation (HPE) can be used for a variety of human-computer interaction applications, such as gesture-based control for physical or virtual/augmented reality devices. Recent works have shown that videos or multiview images carry rich information regarding the hand, allowing for the development of more robust HPE systems. In this article, we present the multiview video-based three-dimensional (3-D) hand (MuViHand) dataset, consisting of multiview videos of the hand along with ground-truth 3-D pose labels. Our dataset includes more than 402 000 synthetic hand images available in 4560 videos. The videos have been simultaneously captured from six different angles with complex backgrounds and random levels of dynamic lighting. The data has been captured from ten distinct animated subjects using 12 cameras in a semicircle topology where six tracking cameras only focus on the hand and the other six fixed cameras capture the entire body. Next, we implement MuViHandNet, a neural pipeline consisting of image encoders for obtaining visual embeddings of the hand, recurrent learners to learn both temporal and angular sequential information, and graph networks with U-Net architectures to estimate the final 3-D pose information. We perform extensive experiments and show the challenging nature of this new dataset as well as the effectiveness of our proposed method. Ablation studies show the added value of each component in MuViHandNet, as well as the benefit of having temporal and sequential information in the dataset. © 2020 IEEE.

关键词： Cameras

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