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CLEO: Science and Innovations in CLEO 2024, CLEO: S and I 2024 - Part of Conference on Lasers and Electro-Optics

作者： Uddin, Shiekh Zia Rivera, Nicholas Seyler, Devin Salamin, Yannick Sloan, Jamison Xu, Shutao Sander, Michelle Y. Soljačić, Marin Department of Physics Massachusetts Institute of Technology CambridgeMA02139 United States Research Laboratory of Electronics Massachusetts Institute of Technology CambridgeMA02139 United States Department of Physics Harvard University CambridgeMA02138 United States Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States Department of Electrical and Computer Engineering BU Photonics Center Boston University BostonMA02215 United States

We present a new fluctuation-dissipation relation that shows how quantum noise transforms under engineered nonlinear dissipation found in many important nonlinear optical devices and validate the theory with experimen... 详细信息

关键词： Quantum noise

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Recent Progress in Reinforcement Learning and Adaptive Dynamic Programming for Advanced Control Applications

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 18-36页

作者： Ding Wang Ning Gao Derong Liu Jinna Li Frank L.Lewis IEEE the Faculty of Information Technology Beijing Key Laboratory of Computational Intelligence and Intelligent SystemBeijing Laboratory of Smart Environmental Protectionand Beijing Institute of Artificial IntelligenceBeijing University of TechnologyBeijing 100124China the School of System Design and Intelligent Manufacturing Southern University of Science and TechnologyShenzhen 518055China the Department of Electrical and Computer Engineering University of Illinois at ChicagoChicago IL 60607 USA the School of Information and Control Engineering Liaoning Petrochemical UniversityFushun 113001China the UTA Research Institute the University of Texas at ArlingtonArlington TX 76118 USA

Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, ***, the research progress on adaptive critic control based on the event-triggered framework and under uncertain environment is discussed, respectively, where event-based design, robust stabilization, and game design are reviewed. Moreover, the extensions of ADP for addressing control problems under complex environment attract enormous attention. The ADP architecture is revisited under the perspective of data-driven and RL frameworks,showing how they promote ADP formulation ***, several typical control applications with respect to RL and ADP are summarized, particularly in the fields of wastewater treatment processes and power systems, followed by some general prospects for future research. Overall, the comprehensive survey on ADP and RL for advanced control applications has d emonstrated its remarkable potential within the artificial intelligence era. In addition, it also plays a vital role in promoting environmental protection and industrial intelligence.

关键词： Adaptive dynamic programming(ADP) advanced control complex environment data-driven control event-triggered design intelligent control neural networks nonlinear systems optimal control reinforcement learning(RL)

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Single-Phase and Two-Phase Liquid Immersion Cooling of Data Center Power Supply Units for Heat Capture 23

Single-Phase and Two-Phase Liquid Immersion Cooling of Data ...

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23rd IEEE Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems, ITherm 2024

作者： Qiu, Haoyun Kabirzadeh, Pouya Garimella, Vivek S. Bali, Arjit Gurusami, Keerthivasan Lee, Kang Joon Stillwell, Andrew Salamon, Todd Miljkovic, Nenad University of Illinois Urbana-Champaign Department of Mechanical Science and Engineering UrbanaIL United States University of Illinois Urbana-Champaign Department of Electrical and Computer Engineering UrbanaIL United States Optical Systems and Device Research Laboratory Nokia Bell Labs Murray HillNJ United States

ISBN: (纸本)9798350364330

Data center power supply units (PSU) have high power density due to the increasing power demand and their low profiles. Air cooling proves to be increasingly difficult in mitigating the hot spots, and it also consumes extra energy in fluid delivery, air conditioning, and rejection to the ambience. In this work, we redesign and modify the PSU cooling infrastructure and adopt quiescent immersion cooling. This design removes all active air-cooling elements and enables heat capture. The PSU used in the experiments is a 2 kW 80 Plus Platinum commercial unit (Bel PET2000-12-074RA). The cooling performance was characterized by tracking the steady-state case temperatures of the switching semiconductors. Flutec PP1 was used to study the cooling performance variations with respect to PSU load and capture temperature. Conventional fan-cooled PSU with heat sinks served as the benchmark. Experiments show that two-phase immersion cooling grants an overall enhancement of 4.4× over the original air-cooling approach at 40 °C heat capture. The results suggest that heat rejection from the dielectric fluid to the riding heatsink is the main bottleneck, and further reduction of the thermal resistance would allow heat capture at a temperature closer to the liquid boiling point. The PSU thermal management approach studied here can help lower data center power usage effectiveness (PUE) while increasing PSU power delivery density. © 2024 IEEE.

关键词： Dielectric liquids

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Contextual Hourglass Network for Semantic Segmentation of High Resolution Aerial Imagery 5

Contextual Hourglass Network for Semantic Segmentation of Hi...

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5th International Conference on Electronic Communication and Artificial Intelligence, ICECAI 2024

作者： Li, Panfeng Lin, Youzuo Schultz-Fellenz, Emily University of Michigan Department of Electrical and Computer Engineering Ann Arbor United States Geophysics Group Los Alamos National Laboratory Ann Arbor United States Geology and Geochemistry Research Team Los Alamos National Laboratory Los Alamos United States Los Alamos National Laboratory United States

ISBN: (纸本)9798350386943

Semantic segmentation for aerial imagery is a challenging and important problem in remotely sensed imagery analysis. In recent years, with the success of deep learning, various convolutional neural network (CNN) based models have been developed. However, due to the varying sizes of the objects and imbalanced class labels, it can be challenging to obtain accurate pixel-wise semantic segmentation results. To address those challenges, we develop a novel semantic segmentation method and call it Contextual Hourglass Network. In our method, in order to improve the robustness of the prediction, we design a new contextual hourglass module which incorporates attention mechanism on processed low-resolution featuremaps to exploit the contextual semantics. We further exploit the stacked encoder-decoder structure by connecting multiple contextual hourglass modules from end to end. This architecture can effectively extract rich multi-scale features and add more feedback loops for better learning contextual semantics through intermediate supervision. To demonstrate the efficacy of our semantic segmentation method, we test it on Potsdam and Vaihingen datasets. Through the comparisons to other baseline methods, our method yields the best results on overall performance. © 2024 IEEE.

关键词： Semantic Segmentation

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Focused Bidirectional Search Trees: A Bidirectional Optimal Fast Matching Method for Robot Path Planning

Focused Bidirectional Search Trees: A Bidirectional Optimal ...

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2023 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2023

作者： Li, Chenming Wang, Jiankun Meng, Max Q.-H. The Chinese University of Hong Kong Department of Electronic Engineering Hong Kong Hong Kong Southern University of Science and Technology Shenzhen Key Laboratory of Robotics Perception and Intelligence Department of Electronic and Electrical Engineering Shenzhen China Southern University of Science and Technology Jiaxing Research Institute Jiaxing China University of Alberta Department of Electrical and Computer Engineering Canada

ISBN: (纸本)9798350327182

Robot path planning in high-dimensional continuous space is of great significance in robotics. The conventional bidirectional fast marching method utilizes brute-force search to explore the space, which is computationally expensive. Though improving the planning efficiency, heuristic-based bidirectional fast marching search results in a suboptimal path under a predetermined number of random samples. To address these issues, we propose Focused Bidirectional Fast Marching Trees (FBFMT*), developing a novel vertex exploring sequence to constrain the forward and backward searches within the brute-force searched regions. It enables the search trees to meet in the middle of the solution path, which guarantees the optimality under the current set of samples and searches faster than the bidirectional brute-force strategy. Extensive simulations in different scenarios validate the superiority of the proposed method, showing that FBFMT∗ can speed up the planning process and find a better solution. We also extend the proposed method to general conditions so that the forward and backward searches of FBFMT∗ can meet at any portion of the path. FBFMT∗ reveals that the heuristic-based bidirectional fast marching search strategy can be a general and efficient technique for robot path planning in high-dimensional continuous spaces. © 2023 IEEE.

关键词： Robot programming

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Progressive Motion Boosting for Video Frame Interpolation

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IEEE Transactions on Multimedia 2023年 25卷 8076-8090页

作者： Xiao, Jing Xu, Kangmin Hu, Mengshun Liao, Liang Wang, Zheng Lin, Chia-Wen Wang, Mi Satoh, Shin'Ichi The School of Computer Science Wuhan University Wuhan430072 China The School of Computer Science and Engineering Nanyang Technological University Singapore639798 Singapore The Department of Electrical Engineering the Institute of Communications Engineering National Tsing Hua University Hsinchu30013 Taiwan The State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University Wuhan430072 China The Digital Content and Media Sciences Research Division National Institute of Informatics Tokyo101-8430 Japan

Video frame interpolation has made great progress in estimating advanced optical flow and synthesizing in-between frames sequentially. However, frame interpolation involving various resolutions and motions remains challenging due to limited or fixed pre-trained networks. Inspired by the success of the coarse-to-fine scheme for video frame interpolation, i.e., gradually interpolating frames of different resolutions, we propose a progressive boosting network (ProBoost-Net) based on a multi-scale framework to achieve flexible recurrent scales and then gradually optimize optical flow estimation and frame interpolation. Specifically, we designed a dense motion boosting (DMB) module to transfer features close to real motion to the decoded features from the later scales, which provides complementary information to refine the motion further. Furthermore, to ensure the accuracy of the estimated motion features at each scale, we propose a motion adaptive fusion (MAF) module that adaptively deals with motions with different receptive fields according to the motion conditions. Thanks to the framework’s flexible recurrent scales, we can customize the number of scales and make trade-offs between computation and quality depending on the application scenario. Extensive experiments with various datasets demonstrated the superiority of our proposed method over state-of-the-art approaches in various scenarios. © 2023 Institute of electrical and Electronics Engineers Inc.. All rights reserved.

关键词： Motion estimation

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An overview of recent progress in the development of flexible electrochromic devices

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Nano Materials Science 2023年第4期5卷 369-391页

作者： Bin Wang Wu Zhang Feifei Zhao William W.Yu Abdulhakem Y.Elezzabi Linhua Liu Haizeng Li Optics and Thermal Radiation Research Center Institute of Frontier&Interdisciplinary ScienceShandong UniversityQingdao266237China School of Chemistry&Chemical Engineering Shandong UniversityJinan250100China Ultrafast Optics and Nanophotonics Laboratory Department of Electrical and Computer EngineeringUniversity of AlbertaEdmontonAlbertaT6G 2V4Canada

Electrochromic materials are capable of reversibly switching their colors or optical properties through redox reactions under applied voltages,which have shown great potential applications including smart windows,nonemissive displays,optical filters,among *** the current rigid electrochromic devices have shown emerging interest and developed rapidly,many applications(e.g.,wearable/deformable optoelectronics)are blocked due to their inflexible ***,the adaption of rigid electrochromic devices to flexible ones is of particular interest for the new era of smart *** this review,the current state-of-the-art achievements of flexible electrochromic devices(FECDs)are highlighted,along with their design strategies and the choice of electrochromic *** recent research progress of FECDs is reviewed in detail,and the challenges and corresponding solutions for real-world applications of FECDs are ***,we summarize the basic fabrication strategies of FECDs and their potential *** addition,the development trend,the perspectives,and the outlook of FECDs are discussed at the end of this Review,which may provide recommendations and potential directions to advance the practical applications of FECDs.

关键词： Electrochromism Flexible electrochromic devices Optoelectronics Optical materials

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Probabilistic Device Scheduling for Over-the-Air Federated Learning 23

Probabilistic Device Scheduling for Over-the-Air Federated L...

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23rd IEEE International Conference on Communication Technology, ICCT 2023

作者： Sun, Yuchang Lin, Zehong Mao, Yuyi Jin, Shi Zhang, Jun The Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Hong Kong The Hong Kong Polytechnic University Department of Electrical and Electronic Engineering Hong Kong Southeast University National Mobile Communications Research Laboratory Nanjing210096 China

ISBN: (纸本)9798350325959

Federated learning (FL) is an emerging distributed training scheme where edge devices collaboratively train a model by uploading model updates instead of private data. To address the communication bottleneck, over-the-air (OTA) computation has been introduced to FL, which allows multiple edge devices to upload their gradient updates concurrently for aggregation. However, OTA computation is plagued by the communication error, which is critically affected by the device selection policy and impacts the performance of the output model. In this paper, we propose a probabilistic device selection scheme PO-FL, which effectively enhances the convergence performance of over-the-air FL. Specifically, each device is selected for OTA computation according to the predetermined probability, and its local update is scaled by this probability. By analyzing the convergence of PO-FL, we show that its convergence is determined by the device selection via the communication error and the variance of global update. Then, we propose a device selection algorithm that jointly considers the channel condition and gradient update importance of edge devices to optimize their selection probabilities. The experimental results on the MNIST dataset demonstrate that the proposed algorithm converges faster and learns better models than the baselines. © 2023 IEEE.

关键词： channel awareness device scheduling Federated learning (FL) gradient importance over-the-air computation (AirComp)

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High-Value Target Escort and Defense Scenario with Differential Subgame Cost 63

High-Value Target Escort and Defense Scenario with Different...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Judy, Rachael L. Fuchs, Zachariah E. Casbeer, David W. University of Cincinnati Department of Electrical Engineering and Computer Science CincinnatiOH United States Control Science Center of Excellence Air Force Research Laboratory 2210 8th St. WPAFBOH45433 United States

ISBN: (纸本)9798350316339

An Escort and Defense Scenario is presented in which a high-value Target maneuvers through a high-risk region while being escorted by a mobile, defensive agent. Along this trajectory, an Attacker may be launched from one of several possible launch locations. If a launch occurs, the three agents play out a Target-Attacker-Defender (TAD) differential game in which the Defender attempts to intercept the Attacker at maximal distance from the Target while the Attacker strives to maneuver as close as possible to the Target. Prior to launch, the Target and Defender strive to preposition themselves in advantageous positions to effectively respond to a potential threat while simultaneously moving towards a safety region. An augmented collocation-based direct optimal control method is developed to solve the escort problem by solving and utilizing the value of the TAD differential subgame at each collocation point while simultaneously optimizing the primary optimal control problem. © 2024 IEEE.

关键词： Optimal control systems

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Potential detection of Flavescence dorée in the vineyard using close-range hyperspectral imaging

Potential detection of Flavescence dorée in the vineyard us...

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2023 International Conference on electrical, computer, Communications and Mechatronics engineering, ICECCME 2023

作者： Barjaktarovic, Marko Santoni, Massimo Faralli, Michele Bertamini, Massimo Bruzzone, Lorenzo School of Electrical Engineering University of Belgrade Serbia Remote Sensing Laboratory University of Trento Italy Remote Sensing Laboratory Department of Information Engineering and Computer Science University of Trento Italy University of Trento Italy Research and Innovation Centre Fondazione Edmund Mach Italy

ISBN: (纸本)9798350322972

Grapevine is one of the most important crops cultivated across Europe. Climate factors and diseases constantly threaten its production. Recently, Flavescence dorée (FD), an incurable grapevine disease with the obligation to uproot each infected plant, has been widely spread in Europe. The symptoms of FD are visually expressed in the late summer. Currently, the adopted procedure consists in scouting for infected plants by trained experts, which is time-consuming and not frequent enough. As stress development causes subtle spectral changes before any visible symptoms appear, during the summer of 2022, hyperspectral and multispectral images were acquired in the two vineyards near Riva del Garda, Trentino, Italy. A classification accuracy between 90.2 % and 96.9 % in distinguishing between infected and healthy plants was obtained from the hyperspectral data. These findings justify further efforts to use an in-house developed, affordable multispectral camera, significantly reducing equipment cost and procedure complexity while mapping the relevant spectral channels. © 2023 IEEE.

关键词： Hyperspectral imaging

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