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IEEE International Conference on Electro-Information Technology

作者： Lukas Klicker Alex Maliwat Joanna Findura Xinrui Yu Mikhail Gromov Jafar Saniie Department of Electrical and Computer Engineering Embedded Computing and Signal Processing (ECASP) Research Laboratory Illinois Institute of Technology Chicago IL USA

ISBN: (数字)9798350330649

ISBN: (纸本)9798350330656

InfaSafe emerges as a novel approach to infant health monitoring, uniquely positioned at the convergence of advanced artificial intelligence and edge computing. This system is designed not as a definitive solution but as an advanced platform for comprehensive data archiving, offering valuable insights into the complex and elusive nature of Sudden Unexpected Infant Death (SUID). InfaSafe utilizes AI algorithms for real-time pose estimation, breathing surveillance, and cry analysis, all within an edge computing framework that facilitates prompt and efficient data handling. This paper explores the development and capabilities of InfaSafe, underscoring its role in providing crucial, real-time insights and alerts for caregivers and its potential to contribute significantly to our understanding of neonatal health and SUID. The focus is on leveraging technological advancements to gather comprehensive data, which can be instrumental in shaping future research and interventions in neonatal care.

关键词： Temperature sensors Temperature measurement Pediatrics Temperature distribution Prototypes Real-time systems Thermal analysis

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A Feasibility Study on Novel View Synthesis of Underwater Structures using Neural Radiance Fields

A Feasibility Study on Novel View Synthesis of Underwater St...

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OCEANS

作者： Yuen Min Too Hari Vishnu Mandar Chitre Bharath Kalyan Luyuan Peng Rajat Mishra Acoustic Research Laboratory Tropical Marine Science Institute National University of Singapore Department of Electrical & Computer Engineering National University of Singapore

ISBN: (数字)9798350362077

ISBN: (纸本)9798350362084

We explore Neural Radiance Fields (NeRFs) for synthesizing novel views of underwater structures. This learning-based approach relies on a sparse set of camera views to model the 3D geometry of underwater structures and scenes. Real-world underwater scenes exhibit significant temporal variations, introducing challenges in maintaining visual consistency. We investigate three NeRF implementations: 1) nerfacto, which rep-resents the baseline; 2) nerfacto with transient embed dings and 3) nerfacto with a robust loss, which are designed to deal with scene inconsistencies. We evaluate these implementations using datasets collected in 1) a controlled environment and 2) a real underwater setting. The modified implementations consistently outperform the original nerfacto across both datasets. The performance im-provements are particularly pronounced in the dataset obtained from the real underwater setting where scene inconsistencies are more prevalent. This underscores the importance of robustifying NeRF implementations to ensure consistent performance in the challenging underwater environments.

关键词： Underwater structures Visualization Solid modeling Three-dimensional displays Oceans Neural radiance field Cameras

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High-Resolution Arrayed-Waveguide-Grating-Assisted Passive Integrated Optical Phased Array for 2-D Beam Steering

High-Resolution Arrayed-Waveguide-Grating-Assisted Passive I...

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Conference on Lasers and Electro-Optics (CLEO)

作者： Yuan Liu Chongxin Zhang Daniel M. DeSantis Diya Hu Thomas Meissner Andres Garcia Coleto Benjamin Mazur Jelena Notaros Jonathan Klamkin Electrical and Computer Engineering Department University of California Santa Barbara CA Research Laboratory of Electronics Massachusetts Institute of Technology Cambridge Massachusetts

ISBN: (纸本)9798350369311

A high-resolution 64-channel arrayed-waveguide-grating-assisted silicon- integrated optical phase array is demonstrated for 2-D beam steering. A field of view of $5^{\circ}\times 25^{\circ}$ with 0.3° vertical resolution is achieved over a wavelength range of 100 nm with a single optical input. Higher vertical resolution can be attained by utilizing all the inputs of the OPA.

关键词： Phased arrays Integrated optics Beam steering Lasers and electrooptics Laser beams Electro-optical waveguides Optical arrays

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Unsupervised Video Domain Adaptation with Masked Pre-Training and Collaborative Self-Training

Unsupervised Video Domain Adaptation with Masked Pre-Trainin...

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Conference on computer Vision and Pattern Recognition (CVPR)

作者： Arun Reddy William Paul Corban Rivera Ketul Shah Celso M. de Melo Rama Chellappa Johns Hopkins University Applied Physics Laboratory Department of Electrical & Computer Engineering Johns Hopkins University DEVCOM U.S. Army Research Laboratory

ISBN: (数字)9798350353006

ISBN: (纸本)9798350353013

In this work, we tackle the problem of unsupervised domain adaptation (UDA) for video action recognition. Our approach, which we call UNITE, uses an image teacher model to adapt a video student model to the target domain. UNITE first employs self-supervised pretraining to promote discriminative feature learning on target domain videos using a teacher-guided masked distillation objective. We then perform self-training on masked target data, using the video student model and image teacher model together to generate improved pseudolabels for unlabeled target videos. Our self-training process successfully leverages the strengths of both models to achieve strong transfer performance across domains. We evaluate our approach on multiple video domain adaptation benchmarks and observe significant improvements upon previously reported results.

关键词： Representation learning Adaptation models computer vision Computational modeling Collaboration Benchmark testing Data models

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Energy Consumption Prediction of a CNC Machining Process With Incomplete Data

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IEEE/CAA Journal of Automatica Sinica 2021年第5期8卷 987-1000页

作者： Jian Pan Congbo Li Ying Tang Wei Li Xiaoou Li the State Key Laboratory of Mechanical Transmission Chongqing UniversityChongqing 400044China the Department of Electrical and Computer Engineering Rowan UniversityGlassboroNJ 08028 USA the Computer Science Department The Research and Advanced Studies Centre of the National Polytechnic InstituteMexico City 07360Mexico

Energy consumption prediction of a CNC machining process is important for energy efficiency optimization *** improve the generalization abilities,more and more parameters are acquired for energy prediction *** the data collected from workshops may be incomplete because of misoperation,unstable network connections,and frequent transfers,*** work proposes a framework for energy modeling based on incomplete data to address this ***,some necessary preliminary operations are used for incomplete data ***,missing values are estimated to generate a new complete data set based on generative adversarial imputation nets(GAIN).Next,the gene expression programming(GEP)algorithm is utilized to train the energy model based on the generated data ***,we test the predictive accuracy of the obtained *** experiments are designed to investigate the performance of the proposed framework with different rates of missing *** results demonstrate that even when the missing data rate increases to 30%,the proposed framework can still make efficient predictions,with the corresponding RMSE and MAE 0.903 k J and 0.739 k J,respectively.

关键词： Energy consumption prediction incomplete data generative adversarial imputation nets(GAIN) gene expression programming(GEP)

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Optimal Linear Deception Attacks on Remote State Estimation with Constrained Alarm Rates: A Low-Dimensional Case 63

Optimal Linear Deception Attacks on Remote State Estimation ...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Shang, Jun Zhang, Hanwen Zhou, Jing Chen, Tongwen Tongji University Shanghai Research Institute for Intelligent Autonomous Systems National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Department of Control Science and Engineering Shanghai200092 China University of Science and Technology Beijing Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education School of Automation and Electrical Engineering Beijing100083 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 1H9 Canada

ISBN: (纸本)9798350316339

This study addresses linear attacks on remote state estimation within the context of a constrained alarm rate. Smart sensors, which are equipped with local Kalman filters, transmit innovations instead of raw measurements through a wireless communication network. This transmission is vulnerable to malicious data interception and manipulation by attackers. The aim of this research is to identify the optimal attack strategy that degrades the system performance while adhering to stealthiness constraints. A notable innovation of this paper is the direct association of the attack's stealthiness with the alarm rate, diverging from traditional approaches that rely on the covariance of the innovation or the Kullback-Leibler divergence, which are conventional metrics that have been extensively explored in previous studies. Our findings reveal that the optimal attack strategy exhibits some structural characteristics in systems of low dimensions. The performance of the proposed attack strategy is demonstrated through numerical examples. © 2024 IEEE.

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Statistical CSI-Based Transmission Design for RIS and DMA Assisted MIMO Communication System

Statistical CSI-Based Transmission Design for RIS and DMA As...

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2023 IEEE/CIC International Conference on Communications in China, ICCC 2023

作者： Huang, Xiaojun Zhang, Jun Han, Yu Xu, Kaizhe Jin, Shi Ma, Shaodan Nanjing University of Posts and Telecommunications Jiangsu Key Laboratory of Wireless Communications Nanjing210003 China Southeast University National Mobile Communications Research Laboratory Nanjing210096 China University of Macau State Key Laboratory of Internet of Things for Smart City Department of Electrical and Computer Engineering Macau Taipa China

ISBN: (纸本)9798350345384

This paper presents a hybrid reconfigurable intelligent surface (RIS) and dynamic metasurface antenna (DMA) assisted multiple-input multiple-output (MIMO) communication system, which is capable to realize massive MIMO technology with superior performance at low hardware implementation cost. We aim for maximizing the achievable ergodic rate of the system through jointly designing the transmit covariance matrix of user, the phase shift matrix of RIS, and the DMA weight matrix at BS only with statistical channel state information. Based on the derived closed-form asymptotic ergodic rate, we first obtain the optimal transmit covariance matrix under the power consumption constraint and specific absorption rate constraints. Then, we obtain a locally optimal phase shift matrix of RIS via the projected gradient ascent algorithm. Finally, we reconfigure the DMA weights by utilizing the optimal solution of the unconstrained DMA problem. Simulation results demonstrate that the proposed optimization algorithm outperforms the baseline. © 2023 IEEE.

关键词： Antennas

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Bright InAs/GaAs Quantum Dot Single Photon Emitters Embedded in Tapered Nanobeam Cavity

Bright InAs/GaAs Quantum Dot Single Photon Emitters Embedded...

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2024 Laser Science, LS 2024

作者： Biswas, Abhijit Rahaman, Mohammad Habibur Bracker, Allan S. Waks, Edo Institute for Research in Electronics and Applied Physics Joint Quantum Institute University of Maryland College ParkMD20742 United States Department of Electrical and Computer Engineering University of Maryland College ParkMD20740 United States Naval Research Laboratory 4555 Overlook Avenue SW WashingtonDC20375 United States

We report a nanobeam photonic crystal cavity coupled to charge tunable quantum dot for efficient spin-photon interface. We achieved coupling efficiency of ~32% and deterministically tuned the cavity resonance over ~9 ... 详细信息

关键词： Semiconductor quantum dots

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Personalized Multimedia Recommendation Systems Using Higher-Order Tensor Singular-Value-Decomposition

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IEEE Transactions on Broadcasting 2024年第1期70卷 148-160页

作者： Chang, Shih Yu Wu, Hsiao-Chun Yan, Kun Chen, Xinjia Huang, Scott Chih-Hao Wu, Yiyan San Jose State University Department of Applied Data Science San JoseCA95192 United States Louisiana State University School of Electrical Engineering and Computer Science Baton RougeLA70803 United States Yuan Ze University Innovation Center for AI Applications Chungli32003 Taiwan Guilin University of Electronic Technology Guangxi Key Laboratory of Wireless Wideband Communication and Signal Processing Department of Information and Telecommunication Guilin541004 China Northwestern State University Department of Engineering Technology NatchitochesLA71497 United States National Tsing Hua University Department of Electrical Engineering Hsinchu300 Taiwan Communications Research Centre Canada OttawaK2H 8S2 Canada

Because of rapid growth of multimedia data over the Internet, the infobesity has been emerging in recent years. Many recommender systems (RSs) have been proposed using a variety of techniques, including artificial intelligence, machine learning, statistical analysis, and data mining. Nowadays, E-commerce companies such as Amazon, eBay, Netflix, etc. have applied RSs conveniently to provide better customer services than before by enabling customized multimedia-content recommendations. It is well known that classical RSs are almost all based on the user-item attribute matrices. However, this two-fold user-item relationship should be extended to the emerging many-fold relationship among an arbitrary number of attribute groups so that the corresponding new RSs may lead to better performances. Therefore, in this paper, we introduce a novel personalized multimedia recommender system (PMRS) according to our proposed new parallel higher-order tensor singular-value-decomposition (PHOTSVD) algorithm. This PHOTSVD algorithm is capable of accommodating an arbitrary number of entities such as social-media channels, users, queries, webpages, etc. in a robust RS. Furthermore, we also investigate the cold start and data bias problems critical to RSs. Finally, we compare the performances of our proposed new PMRS and three other existing tensor-based RSs over realworld data with respect to the well-adopted metric, namely normalized root-mean-square error (NRMSE). Our proposed new PMRS greatly outperforms the other three existing tensor-based RSs in terms of NRMSE. © 1963-12012 IEEE.

关键词： Singular value decomposition

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Integrating Sustainability and Industry 4.0: A Framework for Sustainable Logistics 4.0

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Circular Economy and Sustainability 2025年 1-39页

作者： Di Nardo, Mario Gallab, Maryam Murino, Teresa Wu, Jing Pandey, Shatrudhan Facoltàdi Ingegneria Università Telematica Pegaso Rome 00186 Italy MIS-LISTD Laboratory Computer Science Department Mines-Rabat School (ENSMR) Rabat 10000 Morocco Department of Chemical Materials and Industrial Production Engineering University of Naples “Federico II” Naples Italy Department of Electrical and Photonics Engineering Technical University of Denmark Kgs. Lyngby 2800 Denmark Marwadi University Research Center Faculty of Management Studies Marwadi University Gujarat Rajkot 360003 India

As society becomes more aware of environmental and social issues, supply chain stakeholders increasingly consider these factors alongside efficiency, cost, and time. The logistics industry must adapt by integrating Industry 4.0 technologies and sustainability practices. Sustainable Logistics 4.0, though nascent, is gaining traction for enhancing sustainability through digital interventions. This study conducted a comprehensive literature review and bibliometric network analysis using data extracted from the Scopus and Google Scholar databases, covering the period from 2013 to 2023, focusing on the integration of sustainability, Industry 4.0, and logistics. Noting a gap in conceptual frameworks, the paper performs a SWOT analysis to identify key factors and proposes a framework for digitalizing sustainable logistics and addressing emerging challenges. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

关键词： Circular Economy Industry 4.0 Logistics Sustainability TBL

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