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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Yin, Heyuan Yang, Jingxiang Liu, Jia Xiao, Liang School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210094 China Key Laboratory of Analysis of Mathematical Theory and Modeling of Complex Systems Ministry of Industry and Information Technology China

ISBN: (纸本)9798350368741

Effectively reconstructing 3D hyperspectral images (HSIs) from 2D measurements presents a significant challenge in Coded Aperture Snapshot Spectral Imaging (CASSI) systems. While recent transformers exhibit potential in HSI reconstruction, they often suffer from inadequate exploration of multi-scale spatial-spectral self-similarity, leading to mean effects and information loss. Additionally, these methods struggle with insufficient modeling of the degradation inherent in the compressive imaging process. To address these issues, we propose a novel Mask-guided Multi-scale Spatial-Spectral Transformer (MMSST). Specifically, we introduce a Degradation Aware Mask Attention (DAMA) module to incorporate degradation information of the compressive imaging process. Furthermore, MMSST leverages Local-Regional SpAtial attention (LRSA) and Global-Regional SpEctral attention (GRSE) to effectively exploit multi-scale self-similarity across spatial and spectral dimensions. Extensive experimental results demonstrate the effectiveness of our MMSST. © 2025 IEEE.

关键词： hyperspectral reconstruction Snapshot Compressive Imaging spatial-spectral transformer

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Resilient Operation of DC Standalone Microgrids: Experimental Validation of Hybrid RNN-PI Control for Pulse Load Management

Resilient Operation of DC Standalone Microgrids: Experimenta...

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IEEE Green Technologies Conference (IEEE-Green)

作者： Ahmed Aghmadi Osama A. Mohammed Department of Electrical and Computer Engineering Energy Systems Research Laboratory Florida International University Miami FL USA

ISBN: (数字)9798331520182

ISBN: (纸本)9798331520199

Effective energy storage system (ESS) management is critical for enhancing the performance of standalone DC microgrids, particularly when integrating renewable energy sources such as photovoltaic (PV) or wind systems. This research describes a new hybrid control technique to improve DC microgrid operations' efficiency and resiliency, especially when handling critical loads. This research presents a hybrid closed-loop control technique that uses Recurrent Neural Networks (RNNs) and Proportional-Integral (PI) controllers to address the complex issues of dynamic load situations and transient disturbances. The RNN evaluates voltage errors to generate accurate reference currents, which the PI controllers then adjust to improve the performance of the bidirectional converter. Unlike standard PI-PI controls, our hybrid approach is particularly effective at regulating pulsed power loads (PPLs) and enhancing system response to transitory situations. The experimental results show that the RNN-PI control scheme significantly improves voltage regulation and transient responsiveness, exceeding conventional performance and resilience techniques. This approach provides a convincing solution for enhancing microgrid systems' stability and efficiency in various real-world applications.

关键词： Renewable energy sources Recurrent neural networks PI control Voltage fluctuations Microgrids Robustness Voltage control Transient analysis Standards Resilience

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Temporal Up-Sampling for Asynchronous Events

Temporal Up-Sampling for Asynchronous Events

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2022 IEEE International Conference on Multimedia and Expo, ICME 2022

作者： Xiang, Xijie Zhu, Lin Li, Jianing Tian, Yonghong Huang, Tiejun Shanghai Jiao Tong University Department of Electrical and Computer Engineering China School of Computer Science Peking University China Peng Cheng National Laboratory China

ISBN: (数字)9781665485630

ISBN: (纸本)9781665485630

The event camera is a novel bio-inspired vision sensor. When the brightness change exceeds the preset threshold, the sensor generates events asynchronously. The number of valid events directly affects the performance of event-based tasks, such as reconstruction, detection, and recognition. However, when in low-brightness or slow-moving scenes, events are often sparse and accompanied by noise, which poses challenges for event-based tasks. To solve these challenges, we propose an event temporal up-sampling algorithm 11Code: https://***/XIJIE-XIANG/Event-Temporal-Up-sampling to generate more effective and reliable events. The main idea of our algorithm is to generate up-sampling events on the event motion trajectory. First, we estimate the event motion trajectory by contrast maximization algorithm and then up-sampling the events by temporal point processes. Experimental results show that up-sampling events can provide more effective information and improve the performance of downstream tasks, such as improving the quality of reconstructed images and increasing the accuracy of object detection. © 2022 IEEE.

关键词： Cameras

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Enhancing Fault Detection in Stochastic Environments Using Interval-Valued KPCA: A Cement Rotary Kiln Case Study

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IEEE Access 2025年 13卷 102951-102963页

作者： Abdelhalim Louifi Abdelmalek Kouadri Mohamed-Faouzi Harkat Abderazak Bensmail Majdi Mansouri Signals and Systems Laboratory Institute of Electrical and Electronics Engineering University M’Hamed Bougara of Boumerdes Boumerdes Algeria Systems and Advanced Material Laboratory Badji Mokhtar–Annaba University Annaba Algeria Department of Electrical and Computer Engineering College of Engineering Sultan Qaboos University Muscat Oman

Fault detection in industrial processes is challenging due to significant data uncertainty, which complicates the accurate modeling of interval-valued data and the quantification of errors necessary for reliable detection. Existing approaches, such as kernel principal component analysis (KPCA), struggle with these challenges because they rely on single-valued data representations and are unable to effectively handle interval-based variability. To address these limitations, this paper introduces the interval-valued model KPCA (IV-KPCA), which extends KPCA by redefining similarity measures and kernel functions to accommodate interval-valued uncertainty. IV-KPCA preserves the interval structure throughout the modeling process, enhancing robustness to dynamic uncertainties and improving fault detection in complex nonlinear systems. Within this framework, fault detection statistics ( $T^{2}$ , Q, and $\Phi $ ) are developed to enable precise error quantification. The proposed method is validated on a cement rotary kiln process, a highly stochastic industrial system characterized by significant uncertainties. Experimental results demonstrate that IV-KPCA reduces false alarms, missed detections, and detection delays by over 100%, 90%, and 95%, respectively, compared to traditional methods. These findings underscore the potential of IV-KPCA in enhancing fault detection performance in complex, uncertain environments.

关键词： Fault detection Uncertainty Kernel Principal component analysis Data models Monitoring Computational modeling Accuracy Kilns Cement industry

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Scaling Distributed Collaboration in Mixed Reality

Scaling Distributed Collaboration in Mixed Reality

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2025 CHI Conference on Human Factors in Computing systems, CHI EA 2025

作者： Genay, Adélaïde Syiem, Brandon Victor Wong, Emily Feuchtner, Tiare Knibbe, Jarrod Grønbæk, Jens Emil Sloth Velloso, Eduardo School of Computer Science University of Sydney SydneyNSW Australia School of Computing and Information Systems The University of Melbourne MelbourneVIC Australia HCI Group University of Konstanz Konstanz Germany Department of Computer Science Aarhus University Aarhus Denmark School of Electrical Engineering and Computer Science The University of Queensland St. LuciaQLD Australia

ISBN: (纸本)9798400713958

Distributed collaboration in Mixed Reality (MR) promises to revolutionise how people connect across different physical environments, offering experiences akin to face-to-face interactions. However, previous work has mostly focused on enabling this vision in overly simplified settings such as with only two users interacting in identical distributed environments. Scaling current systems to work with large groups and for common real-life scenarios is a persistent challenge that requires addressing multiple tensions. We identified six challenges: 1) supporting locally congruent actions from heterogeneous remote spaces, 2) communicating accurate user behaviours through virtual representation instead of physical bodies, 3) facilitating organic group interactions within limited physical space, 4) maintaining conversational dynamics even in asynchronous exchanges, 5) providing equal access to physical objects for all participants, and 6) enabling efficient task switching within a complex ecology of applications, devices, and accessibility needs. This workshop aims to gather researchers and practitioners to explore actionable strategies for resolving these challenges. Through a mix of presentations, hands-on activities, and group discussions, participants will generate new ideas and develop a research agenda to articulate the future of MR collaboration systems. The workshop outcomes will include a list of concrete next steps for the community to bring distributed MR collaboration at scale. © 2025 Copyright held by the owner/author(s).

关键词： Grid computing

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Classifying Bicycle Infrastructure Using On-Bike Street-Level Images

Classifying Bicycle Infrastructure Using On-Bike Street-Leve...

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International Conference on Intelligent Transportation

作者： Kal Backman Ben Beck Dana Kulić Department of Electrical and Computer Systems Engineering School of Public Health and Preventive Medicine Monash University

ISBN: (数字)9798331505929

ISBN: (纸本)9798331505936

While cycling offers an attractive option for sus-tainable transportation, many potential cyclists are discouraged from taking up cycling due to the lack of suitable and safe infrastructure. Efficiently mapping cycling infrastructure across entire cities is necessary to advance our understanding of how to provide connected networks of high-quality infrastructure. Therefore we propose a system capable of classifying available cycling infrastructure from on-bike smartphone camera data. The system receives an image sequence as input, temporally analyzing the sequence to account for sparsity of signage. The model outputs cycling infrastructure class labels defined by a hi-erarchical classification system. Data is collected via participant cyclists covering 7,006Km across the Greater Melbourne region that is automatically labeled via a GPS and OpenStreetMap database matching algorithm. The proposed model achieved an accuracy of 95.38%, an increase in performance of 7.55% compared to the non-temporal model. The model demonstrated robustness to extreme absence of image features where the model lost only 6.6% in accuracy after 90% of images being replaced with blank images. This work is the first to classify cycling infrastructure using only street-level imagery collected from bike-mounted mobile phone cameras, while demonstrating robustness to feature sparsity via long temporal sequence analysis.

关键词： Accuracy Databases Bicycles Feature extraction Cameras Robustness Vectors Image sequences Data mining Global Positioning System

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Impact of Gale Weather Events on Wind Power Generation 1

Impact of Gale Weather Events on Wind Power Generation

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2024 1st International Conference on Smart Grids and Power systems, ICSGPS 2024

作者： Zhang, Yuanhe Yang, Ming Wang, Bo Li, Menglin Yu, Yixiao School of Computer Science and Engineering Shandong University Shandong province Jinan China State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems China Electric Power Research Institute Beijing China

Due to the influence of global warming, extreme wind weather occurs frequently, especially in extreme weather such as typhoons and cold waves, problems such as wind turbine shutdown, cutting out, and sudden changes in power generation power will occur, which brings great challenges to wind power forecast and safe and stable operation of the power grid. At present, the research and analysis of strong wind weather mostly stay at the single fan level, and the causes of abnormal changes in wind power output are mostly analyzed from the physical level. However, with the large-scale access of wind power to the power grid, the impact of extreme weather on power grid operation is becoming more and more significant, and it is particularly important to study the impact of strong wind weather events on wind power cluster output. This paper summarizes various types of wind power generation weather events, then screens key meteorological factors affecting power generation under different wind weather conditions based on Gaussian search and grey correlation weighting, and finally analyzes the meteorological impact on the actual operation of wind farm stations and clusters under typhoons and cold waves respectively, aiming at the problem of huge deviations in wind power forecast caused by wind. The next research direction and suggestions are put forward. © 2024 Published under licence by IOP Publishing Ltd.

关键词： Wind power

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AILS-NTUA at SemEval-2024 Task 6: Efficient model tuning for hallucination detection and analysis

arXiv

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arXiv 2024年

作者： Griogoriadou, Natalia Lymperaiou, Maria Filandrianos, Giorgos Stamou, Giorgos School of Electrical and Computer Engineering AILS Laboratory National Technical University of Athens Greece

In this paper, we present our team's submissions for SemEval-2024 Task-6 - SHROOM, a Shared-task on Hallucinations and Related Observable Overgeneration Mistakes. The participants were asked to perform binary classification to identify cases of fluent overgeneration hallucinations. Our experimentation included fine-tuning a pre-trained model on hallucination detection and a Natural Language Inference (NLI) model. The most successful strategy involved creating an ensemble of these models, resulting in accuracy rates of 77.8% and 79.9% on model-agnostic and model-aware datasets respectively, outperforming the organizers' baseline and achieving notable results when contrasted with the top-performing results in the competition, which reported accuracies of 84.7% and 81.3% correspondingly. © 2024, CC BY.

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Interview with light-wave architect Jelena Vuckovic

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Advanced Photonics 2024年第4期6卷 9-13页

作者： Mengjie Yu Jelena Vuckovic University of Southern California Viterbi School of EngineeringDepartment of Electrical and Computer EngineeringLos AngelesCaliforniaUnited States Stanford University the National Academy of Sciences the Nanoscale and Quantum Photonics Lab in the Ginzton Laboratory

Mengjie Yu:Hello,*** interview is organized by the journal Advanced *** today we're really honored and privileged to have Professor Jelena Vuckovic from Stanford University here with us.I'm from University of ... 详细信息

关键词： wave interview light

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Towards Seamless Wireless Link Connection 23

Towards Seamless Wireless Link Connection

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21st Annual International Conference on Mobile systems, Applications and Services, MobiSys 2023

作者： Chen, Lili Yu, Bozhong Ren, Ju Gummeson, Jeremy Zhang, Yaoxue Department of Computer Science and Technology BNRist Tsinghua University China School of Information Science and Technology Northwest University United States Department of Electrical and Computer Engineering University of Massachusetts Amherst United States Zhongguancun Laboratory Beijing China

ISBN: (纸本)9798400701108

Sub-6GHz and mmWave complement each other in the next generation of wireless communications for wide coverage and high capacity. However, there is still a gap between current network technology and seamless connection in indoor environments due to the inevitable occlusions that particularly affect higher frequency bands like Wi-Fi 5GHz and mmWave. To overcome this gap, economical tunable metasurfaces offer a promising solution by redirecting the beam direction of incoming waves to bypass blockages. However, existing metasurface technologies focus on a single frequency band and lack a theoretical framework to guide surface design for multiple desired bands, limiting their potential for diverse *** work attempts to provide a general method for cross-band metasurface design, extend wireless link coverage by using a new metasurface prototype called CrossFlit, which can maximize the link quality with efficient aperture usage and low cost. We addressed a series of challenges to enable CrossFlit to independently control the wireless communication links across multiple frequency bands;our proof of concept implementation is for Wi-Fi 5 GHz and mmWave bands. We integrate a fast beam-scanning algorithm into an end-to-end system that actuates the metasurface to optimize links in realtime. Empirical evaluation demonstrates that CrossFlit can enhance multiple wireless links simultaneously, providing 10 dB and 15 dB power improvements for Wi-Fi and mmWave links, respectively. CrossFlit achieves less than 4° beam mismatch even in challenging mobile scenarios. © 2023 Owner/Author(s)

关键词： Wi-Fi

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