检索结果-内蒙古大学图书馆

48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Cerviño, Juan Ruiz, Luana Ribeiro, Alejandro University of Pennsylvania Department of Electrical and Systems Engineering Philadelphia United States Mit Computer Science & Artificial Intelligence Laboratory Cambridge United States

ISBN: (纸本)9781728163277

Graph Neural Networks (GNNs) rely on graph convolutions to exploit meaningful patterns in networked data. Based on matrix multiplications, convolutions incur in high computational costs leading to scalability limitations in practice. To overcome these limitations, proposed methods rely on training GNNs in smaller number of nodes, and then transferring the GNN to larger graphs. Even though these methods are able to bound the difference between the output of the GNN with different number of nodes, they do not provide guarantees against the optimal GNN on the very large graph. In this paper, we propose to learn GNNs on very large graphs by leveraging the limit object of a sequence of growing graphs, the graphon. We propose to grow the size of the graph as we train, and we show that our proposed methodology - learning by transference - converges to a neighborhood of a first order stationary point on the graphon data. A numerical experiment validates our proposed approach. © 2023 IEEE.

关键词： Graph Neural Networks Graphons

来源：评论

学校读者我要写书评

暂无评论

A Framework for Cyber-Secure Monitoring and Safe Operation of Solar PV Microgrids

A Framework for Cyber-Secure Monitoring and Safe Operation o...

引用

2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Kim, Jaewon Ilic, Marija Xie, Le Massachusetts Institute of Technology Laboratory for Information & Decision Systems CambridgeMA02139 United States Massachusetts Institute of Technology Department of Electrical Engineering and Computer Science CambridgeMA02139 United States Texas A&m University Department of Electrical & Computer Engineering College StationTX77843 United States

ISBN: (纸本)9798350376067

In this paper, we introduce a systematic design of an end-to-end cyber-secure monitoring and safe operation framework for solar photovoltaic (PV)-rich microgrids, by focusing on the use of on-line attack detector for defending against potential cyber-physical attacks and sensor measurement data processing for operational safety. The proposed approach is based on: 1) identifying component models using their input and output measurements;2) dynamic watermarking (DW) methodology for on-line cyber-attack detection and its timing;and 3) an adaptive event-driven safe shutdown procedure after attack detection. It is shown how these three components interactive steps jointly to ensure safe operation under both normal operational scenarios and compromised operational scenarios with some malicious sensors caused by cyber-attacks on solar PV microgrids. Through this on-line integration, the proposed framework dynamically adapts to varying solar irradiance, load demands, operating conditions, and potential cyber-physical attacks. This forms a cyber-physical system which can pro-actively detect and mitigate potential cyber-physical attacks on solar PV microgrids. We describe its proof-of-concept implementation using real-world industrial solar farm data provided by the CenterPoint Energy. This study contributes to enhancing the cyber-security and safe operation of solar PVrich power systems, offering a scalable solution to other types of emerging renewable-rich energy distribution systems. © 2024 IEEE.

关键词： Cyber attacks

来源：评论

学校读者我要写书评

暂无评论

GIRP: Energy-Efficient QoS-Oriented Microservice Resource Provisioning via Multi-Objective Multi-Task Reinforcement Learning

引用

IEEE Transactions on Mobile Computing 2025年第7期24卷 5793-5807页

作者： Yuan, Honggang Wang, Ting Fu, Min Shi, Yuanming East China Normal University MoE Engineering Research Center of Software/Hardware Co-design Technology and Application Shanghai Key Laboratory of Trustworthy Computing Shanghai200062 China National University of Singapore Department of Electrical and Computer Engineering 117583 Singapore ShanghaiTech University School of Information Science and Technology Shanghai201210 China

Microservice architecture has revolutionized web service development by facilitating loosely coupled and independently developable components distributed as containers or virtual machines. While existing studies emphasize end-to-end latency, this paper investigates energy-efficient quality-of-service (QoS)-oriented microservice provisioning, focusing on both QoS satisfaction and power consumption (PC) conservation. We propose the Green and Intelligent Resource Provision (GIRP) architecture, integrating a data-driven energy-latency-aware resource allocation and scheduling manager to balance latency and PC. To reconcile the trade-offs involved, a dual-objective optimization problem is formulated to minimize latency and energy use by selecting proper servers, allocating CPU cores, and determining service replicas. To address challenges with discrete variables, dual objectives, and implicit mappings, we leverage a model-free deep deterministic policy gradient-based reinforcement learning algorithm. Specifically, we develop a multi-task agent via the Multi-gate Mixture-of-Experts model to simultaneously make two separate actions regarding CPU core numbers and service replica numbers, followed by a single-task agent to determine service scheduling. Extensive experiments on the DeathStarBenchmark testbed validate GIRP's effectiveness, demonstrating approximately 52% resource savings and a 43% reduction in PC compared to leading methods like Sinan, Firm, and heuristic-based algorithms. These results highlight GIRP's capability to optimize microservice orchestration by balancing end-to-end latency and power efficiency. © 2025 IEEE. All rights reserved.

关键词： Quality of service

来源：评论

学校读者我要写书评

暂无评论

Neural Architecture Search for Image Dehazing

IEEE Transactions on Artificial Intelligence

引用

IEEE Transactions on Artificial Intelligence 2023年第5期4卷 1337-1347页

作者： Mandal, Murari Meedimale, Yashwanth Reddy Satish Kumar Reddy, M. Vipparthi, Santosh Kumar Kalinga Institute of Industrial Technology Deemed to Be University School of Computer Engineering Bhubaneswar751024 India Walmart Global Tech Hyderabad500081 India Texas A&m University Computer Science and Engineering Department College StationTX77843 United States Indian Institute of Technology Ropar Cvpr Laboratory at Department of Electrical Engineering Rupnagar140001 India

Manual design of deep networks require numerous trials and parameter tuning, resulting in inefficient utilization of time, energy, and resources. In this article, we present a neural architecture search (NAS) algorithm - AutoDehaze, to automatically discover effective neural network for single image dehazing. The proposed AutoDehaze algorithm is built on the gradient-based search strategy and hierarchical network-level optimization. We construct a set of search space layouts to reduce memory consumption, avoid the NAS collapse issue, and considerably accelerate the search speed. We propose four search spaces AutoDehaze B, AutoDehaze U1, AutoDehaze U2, and AutoDehaze L, which are inspired by the boat-shaped, U-shaped, and lateral connection-based designs. To the best of authors knowledge, this is a first attempt to present an NAS method for dehazing with a variety of network search strategies. We conduct a comprehensive set of experiments on Reside-Standard (SOTS), Reside-β (SOTS) and Reside-β (HSTS), D-Hazy, and HazeRD datasets. The architectures discovered by the proposed AutoDehaze quantitatively and qualitatively outperform the existing state-of-the-art approaches. The experiments also show that our models have considerably fewer parameters and runs at a faster inference speed in both CPU and GPU devices. © 2020 IEEE.

关键词： Network architecture

来源：评论

学校读者我要写书评

暂无评论

Digital Twins for Photorealistic Event-Based Structural Dynamics 41st

Digital Twins for Photorealistic Event-Based Structural Dyna...

引用

41st IMAC, A Conference and Exposition on Structural Dynamics, 2023

作者： Davis, Allison Walker, Edward Chen, Marcus Felipe, Moises Mascareñas, David Moreu, Fernando Cattaneo, Alessandro Department of Electrical Engineering and Computer Science College of Engineering and Applied Science University of Wyoming LaramieWY United States Department of Mechanical Engineering George R. Brown School of Engineering Rice University HoustonTX United States Department of Electrical and Computer Engineering College of Engineering University of Washington SeattleWA United States Los Alamos National Laboratory Los AlamosNM United States Department of Civil Construction and Environmental Engineering University of New Mexico AlbuquerqueNM United States

ISBN: (纸本)9783031349096

Digital twins are virtual representations of real-world structures that can be used for modeling and simulation. Because of digital twins’ ability to simulate complex structural behaviors, they also have potential for structural health monitoring (SHM) applications. Video-based SHM techniques are advantageous due to the lower installation/maintenance costs, analysis in high-spatial resolution, and its non-contact monitoring features. Both digital twins and video-based techniques hold particular interest in the fields of non-destructive evaluation, damage identification, and modal analysis. An effective use of these techniques for SHM applications still poses several challenges. Neural radiance fields (NeRFs) are an emerging and promising type of neural network that can render photorealistic novel views of a complex scene using a sparse data set of 2D images. Originally, NeRF was designed to capture static scenes, but recent work has extended its capability to capture dynamic scenes which has implications for medium and long-term SHM. However, to date, most NeRFs use frame-based images and videos as input data. Frame-based video monitoring approaches result in redundant information derived from the fact that, for structural dynamics monitoring, only a small number of active pixels record the actual dynamical changes in the structure, resulting in intensive computational loads for data processing and storage. A promising alternative is event-based imaging, which only records pixel-wise changes on the illumination of a scene. Event-based imaging creates a sparse set of data, while accurately capturing the dynamics. The work proposes a method to extract the dynamics of a structure using a generated digital twin. Using Unreal Engine 5, digital twins of rigid and non-rigid structures were generated. The digital twin model was then used along with an event-based camera simulator to generate event-based data. A frequency analysis framework was then developed to extract the

关键词： Cameras

来源：评论

学校读者我要写书评

暂无评论

A 2.2-3.6 GHz CMOS Reconfigurable Fourth-Order Bandpass Filter With Compact Size and High Selectivity Using Transformer-Type Resonators

引用

IEEE Transactions on Microwave Theory and Techniques 2023年第1期71卷 218-229页

作者： Li, Kun Liu, Bin Chi, Pei-Ling Wang, Yong Yang, Tao University of Electronic Science and Technology of China School of Electronic Science and Engineering Chengdu Sichuan610054 China National Chiao Tung University Department of Electrical and Computer Engineering Hsinchu300 Taiwan Nanhu Laboratory Research Center of Advanced Rf Chips and Systems Jiaxing Zhejiang314000 China

A compact reconfigurable CMOS bandpass filter (BPF) with high selectivity is proposed using transformer-type resonators in this article. The transformer-type resonator is constructed by a transformer loaded with parallel varactors for frequency tuning, and two varactors are then added across primary wind and secondary wind for coupling tuning. With the transformer-type structure, one resonator is formed inside another resonator, thus fully utilizing the chip area and resulting in a miniaturized structure. Magnetic and electrical couplings are formed within the transformer-type resonator and facilitate the bandwidth (BW) tuning. The quality factor (Q) of each resonator is improved by cross-coupled negative resistance structure. Meanwhile, two pairs of transformer-type resonators are placed side-by-side and naturally form a quadruplet structure;as a result, two transmission zeros (TZs) are introduced at each side of the passband thus significantly improving the selectivity and stopband rejection of the BPF. The proposed tunable on-chip BPF is manufactured by a commercial 55 nm bulk CMOS technology with a core area of 1.48 × 0.54 mm2. The filter center frequency (CF) can be tuned from 2.2 to 3.6 GHz, while the 3 dB fractional BW (FBW) can be tuned from 14% to 33%. The shape factor of the proposed filter is 1.4-1.9. © 1963-2012 IEEE.

关键词： Varactors

来源：评论

学校读者我要写书评

暂无评论

Hybridization of Wavelet Decomposition and Machine Learning for Brain Waves based Emotion Recognition 1

Hybridization of Wavelet Decomposition and Machine Learning ...

引用

1st International Conference in Advanced Innovation on Smart City, ICAISC 2023

作者： Ali, Mirna Qaisar, Saeed Mian Anurulafchar, Tamanna Effat University Electrical and Computer Engineering Department Jeddah22332 Saudi Arabia LINEACT Laboratory CESI Engineering School Villeurbanne69100 France Effat University Computer Science Department Jeddah22332 Saudi Arabia

ISBN: (纸本)9781665472753

Emotion recognition has sparked the interest of researchers from a variety of disciplines. Studies have demonstrated that brain signals may be utilized to characterize a wide range of emotional states. Electroencephalogram (EEG) measures the cerebral activity. Therefore, by exploiting the EEG signals the emotion states can be determined. In this study the EEG signals undergoes through filtering, segmentation, Wavelet Packet Decomposition (WPD), feature mining, and classification. The machine learning algorithms used for classifications are 'Decision Tree' (DT), 'Support Vector Machine' (SVM), and K-Nearest Neighbor' (K-NN) algorithms are used for categorization. Their performance is compared for automatically identifying the emotion state. It is determined that the best performer is SVM. It has attained 98.2% accuracy, 97.3% precision, 97.3% recall, 98.7% specificity, 97.3% F1, 97.3% kappa, and 99.3% AUC. © 2023 IEEE.

关键词： Emotion Recognition

来源：评论

学校读者我要写书评

暂无评论

Disentangling Spatio-Temporal Knowledge for Weakly Supervised Object Detection and Segmentation in Surgical Video

Disentangling Spatio-Temporal Knowledge for Weakly Supervise...

引用

2025 IEEE/CVF Winter Conference on Applications of computer Vision, WACV 2025

作者： Liao, Guiqiu Jogan, Matjaz Koushik, Sai Eaton, Eric Hashimoto, Daniel A. University of Pennsylvania Pcaso Laboratory Department of Surgery United States University of Pennsylvania Department of Electrical and Systems Engineering United States University of Pennsylvania Department of Computer and Information Science United States

ISBN: (纸本)9798331510831

Weakly supervised video object segmentation (WSVOS) enables the identification of segmentation maps without requiring extensive annotations of object masks, relying instead on coarse video labels indicating object presence. WSVOS in surgical videos is, however, more challenging due to the complex interaction of multiple transient objects, such as surgical tools moving in and out of the surgical field. In this scenario, state-of-the-art WSVOS methods struggle to learn accurate segmentation maps. We address this problem by introducing ViDeo Spatio-Temporal disentanglement Networks (VDST-Net), a framework to disentangle complex spatio-temporal object interactions using semi-decoupled knowledge distillation to predict high-quality class activation maps (CAMs). A teacher network is designed to help a temporal-reasoning student network resolve activation conflicts, as the student leverages temporal dependencies when specifics about object location and timing in the video are not provided. We demonstrate the efficacy of our framework on a challenging surgical video dataset where objects are, on average, present in less than 60% of annotated frames, and compare our method to state-of-the-art methods on surgical data and on a public dataset commonly used to benchmark WSVOS. Our method outperforms state-of-the-art techniques and generates accurate segmentation masks under video-level weak supervision. Our code is available at: https://***/PCASOlab/VDST-net. © 2025 IEEE.

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

High-fidelity model to predict heat transfer enhancement for liquid film boiling on uniform micro-structured wicking surfaces

引用

National science Review 2024年第6期11卷 93-95页

作者： Vishwanath Ganesan Mohammad Jalal Inanlu Nenad Miljkovic Department of Mechanical Science and Engineering University of Illinois Urbana-Champaign Department of Electrical and Computer Engineering University of Illinois Urbana-Champaign Materials Research Laboratory University of Illinois Urbana-Champaign International Institute for Carbon Neutral Energy Research (WPI-I2CNER) Kyushu University Institute for Sustainability Energy and Environment (iSEE)University of Illinois Urbana-Champaign

The field of thermal management in highpower electronic devices is a critical area of study, focusing on the efficient dissipation of heat to prevent device overheating and failure [1]. A key aspect of this field is understanding the dynamics of thin liquid film boiling, both on uniform and non-uniform micro-structured wicking surfaces, which can significantly enhance the heat transfer effectiveness[2].

关键词： structured predict micro liquid model boiling enhancement film heat high-fidelity

来源：评论

学校读者我要写书评

暂无评论

Screening-current-induced magnetic fields and strains in a compact REBCO coil in self field and background field

引用

Superconductivity 2024年第1期9卷 35-49页

作者： Yufan Yan Donghui Jiang Peng Song Jeonghwan Park Seungyong Hahn Yunfei Tan Timing Qu Department of Electrical and Computer Engineering Seoul National UniversitySeoul 08826Republic of Korea State Key Laboratory of Clean and Efficient Turbomachinery Power Equipment Department of Mechanical EngineeringTsinghua UniversityBeijing 100084China High Magnetic Field Laboratory Hefei Institutes of Physical ScienceChinese Academy of SciencesHefei 230031China Wuhan National High Magnetic Field Center Huazhong University of Science and TechnologyWuhan 430074China

REBa_(2)Cu_(3)O_(7−x)(REBCO)coated conductors,owing to its high tensile strength and current‐carrying ability in a background field,are widely regarded a promising candidate in high‐field *** the great potentials,recent studies have highlighted the challenges posed by screening currents,which are featured by a highly nonuniform current distribution in the superconducting *** this paper,we report a comprehensive study on the behaviors of screening currents in a compact REBCO coil,specifically the screeningcurrent‐induced magnetic fields and *** were carried out in the self‐generated magnetic field and a background field,*** the self‐field condition,the full hysteresis of the magnetic field was obtained by applying current sweeps with repeatedly reversed polarity,as the nominal center field reached 9.17 T with a maximum peak current of 350 *** a background field of 23.15 T,the insert coil generated a center field of 4.17 T with an applied current of 170 ***,a total center field of 32.58 T was achieved before *** the sequential model and the coupled model considering the perpendicular field modification due to conductor deformation are *** comparative study shows that,for this coil,the electromagnetic–mechanical coupling plays a trivial role in self‐field conditions up to 9 *** contrast,with a high axial field dominated by the background field,the coupling effect has a stronger influence on the predicted current and strain *** discussions regarding the role of background field on the strains in the insert suggest potential design strategies to maximize the total center field.

关键词： Electromagnetic-mechanical analysis High‐field insert coil REBCO coated conductor Screening‐current‐induced magnetic field Screening‐current‐induced stress

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：