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CLEO: Fundamental science, CLEO:FS 2024 - Part of Conference on Lasers and Electro-Optics, CLEO 2024

作者： Xiong, Zhongfei Wu, Fan O. Liu, Yang Jiang, Jian-Hua Christodoulides, Demetrios N. Chen, Yuntian School of Optical and Electronic Information Huazhong University of Science and Technology Wuhan430074 China School of Applied and Engineering Physics Cornell University IthacaNY14853 United States Ming Hsieh Department of Electrical and Computer School of Physical Science and Technology Soochow University Suzhou215006 China Suzhou Institute for Advanced Research University of Science and Technology of China Suzhou215123 China Department of Electrical Engineering University of Southern California Los AngelesCA90089 United States Wuhan National Laboratory of Optoelectronics Huazhong University of Science and Technology Wuhan430074 China

While conventional cooling schemes solely depend on temperature differences, here we demonstrate that in photonics configurations, amplified cooling can be achieved by judiciously manipulating Onsager coefficients thr... 详细信息

ISBN: (纸本)9781957171395

关键词： Photonics

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High-Resolution Detection of Stratospheric Aerosols in CALIPSO Atmospheric Lidar Data Facilitated by the CALIOP-Density-Dimension Algorithm

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IEEE Transactions on Geoscience and Remote Sensing 2025年

作者： Herzfeld, Ute C. Trantow, Thomas Vaughan, Mark Palm, Stephen Opfer, Camden Rodriguez, Eric University of Colorado GeomathematicsRemote Sensing and Cryospheric Sciences Laboratory Department of Electrical Energy and Computer Engineering Department of Computer Science Colorado Boulder80309-0425 United States University of Colorado Geomathematics Remote Sensing and Cryospheric Sciences Laboratory Department of Electrical Energy and Computer Engineering BoulderCO80309-0425 United States Lidar Science Branch NASA Langley Research Center Science Directorate HamptonVA United States Mesoscale Atmosphere Processes Laboratory NASA Goddard Space Flight Center GreenbeltMD United States

The objective of this paper is to demonstrate a new capability to detect faint stratospheric aerosols in atmospheric lidar data from NASA’s Cloud-Aerosol Lidar Infrared Pathfinder Satellite Observations (CALIPSO) Mission (12 June 2006 30 June 2023) at high resolution. Faint aerosols from wildfires, distant volcanic eruptions, and Asian and Saharan dust storms play important roles in the Earth-Atmosphere system, as they provide essential air quality and pollution, airline safety, climate radiative forcing, monitoring of fires and volcanic eruptions, environmental safety, and weather forecasting. Tenuous aerosols are recorded in the CALIOP atmospheric lidar data from the CALIPSO mission, but especially extremely faint stratospheric aerosol layers often escape detection and classification partly or entirely in the current CALIOP data analysis scheme. To solve this problem, we introduce a new algorithm for detection and height determination of atmospheric layers, the Density-Dimension Algorithm for CALIOP data analysis (CALIOP-DDA). The DDA is an auto-adaptive algorithm that builds on concepts from artificial intelligence and spatial statistics. Core steps are calculation of a density field and application of a threshold function for signal-noise separation. Stratospheric aerosol detection is aided by the tropopause split concept. The CALIOP-DDA facilitates detection of extremely faint stratospheric aerosols from various sources, including distant wildfires and volcanic eruptions, in night-time and day-time CALIOP data, even in presence of complex types of other cloud and aerosol layers across a large range of optical thicknesses, while retaining the full 334m along-track, 30m height resolution, without creating false positives. CALIOP-DDA results are evaluated by comparison to layer heights derived from airborne validation experiments, conducted using the Cloud Physics Lidar (CPL). In conclusion, the CALIOP-DDA holds promise as the algorithmic basis for a future improv

关键词： Air quality

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

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

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Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic systems (ITHERM)

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

ISBN: (数字)9798350364330

ISBN: (纸本)9798350364347

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.

关键词： Power system measurements Cooling Density measurement Thermal resistance Thermomechanical processes Immersion cooling Switches Thermal management Resistance heating Data center power

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Streamflow Prediction in the Mekong River Basin Using Deep Neural Networks

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IEEE Access 2023年 11卷 97930-97943页

作者： Nguyen, Thi-Thu-Ha Vu, Duc-Quang Mai, Son T. Dang, Thanh Duc National Taiwan University Department of Bioenvironmental Systems Engineering Taipei10617 Taiwan National Central University Department of Computer Science and Information System Taoyuan320317 Taiwan Thai Nguyen University of Education Thai Nguyen250000 Viet Nam Queen's University Belfast School of Electronics Electrical Engineering and Computer Science BelfastBT7 1NN United Kingdom Institute for Computational Science and Artificial Intelligence Van Lang University Laboratory of Environmental Sciences and Climate Change Ho Chi Minh City70000 Viet Nam Van Lang University Faculty of Environment Ho Chi Minh City70000 Viet Nam

In recent years, the Mekong River Basin (MRB), one of the largest river basins in Southeast Asia, has experienced severe impacts from extreme droughts and floods. Streamflow forecasting has become crucial for effective risk management strategies in the region. However, this task presents significant challenges due to rapid climate changes and the presence of numerous newly constructed upstream dams, which disrupt the natural flow. In this paper, we develop multiple deep learning models (incl. Multi-Layer Perceptron (MLP), Convolutional Neural Network (CNN), Long short-term Memory (LSTM), and Transformer) to predict streamflow with different lead time forecasts based on observed meteorological variables and climatic indices (i.e., discharge, water level, precipitation, and temperature) from 1979 to 2019. The results indicate that LSTM obtains high performance for streamflow prediction in both dry and wet seasons while Transformer is not recommended for long-term prediction, especially in the dry season. The proposed deep learning models capture well the fluctuation of river flow in the MRB during the period of high-dam development, especially LSTM (NSE ≥ 0.8). The models' performances are enhanced with the adding of temperature for short-term prediction while precipitation was the most sensitive variable for long-term one. Such proposed models are essential for government agencies to plan mitigation and adaptation strategies at different periods, which can range from days to years. © 2013 IEEE.

关键词： Floods

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Robust Wireless Power Transfer by Self-Oscillating Controlled Inverter and Circular Pads

Robust Wireless Power Transfer by Self-Oscillating Controlle...

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electrical Machines and Drives (ICEMD), International Conference on

作者： Alireza Eikani Mohammad Amirkhani Hossein Jafari Sadegh Vaez-Zadeh Mojtaba Mirsalim Davood Arab Khaburi Advanced Motion Systems Research Lab School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Department of Electrical Engineering Electrical Machines and Transformers Research Laboratory (EMTRL) Amirkabir University of Technology (Tehran Polytechnic) Tehran Iran Department of Electrical Engineering Iran University of Science and Technology Tehran Iran

Inductive wireless power transfer (WPT) faces significant challenges in achieving high efficiency and stable output power for charging mobile devices like EVs. Using circular pads (CP) as the transmitter (Tx) and receiver (Rx) and a self-oscillating controlled inverter, this paper demonstrates a robust WPT system that maintains high constant transfer efficiency and output power in a defined region regardless of coupling coefficient variations without communication between Tx and Rx or control circuits for the receiver side. In contrast to couplers with non-identical Tx and Rx pads and multiple decoupled coils in the Rx pad, the compact CP-CP magnetic coupler with a single identical coil on the Tx and Rx is more robust at a wider transfer distance (air gap) and lateral and rotational misalignment between the Tx and Rx. The proposed 1-kW robust WPT system with up to a 20 cm air gap between the Tx and Rx and up to 12 cm lateral misalignment in all directions at a 15 cm air gap and all degrees of rotational misalignment can tolerate coupling variations and achieve constant output power with 93% constant transfer efficiency.

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Self-polarized RGB device realized by semipolar micro-LEDs and perovskite-in-polymer films for backlight applications

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Opto-Electronic Advances 2024年第3期7卷 35-49页

作者： Tingwei Lu Yue Lin Tianqi Zhang Yue Huang Xiaotong Fan Shouqiang Lai Yijun Lu Hao-Chung Kuo Zhong Chen Tingzhu Wu Rong Zhang School of Electronic Science and Engineering Fujian Engineering Research Center for Solid-State LightingXiamen UniversityXiamen 361005China Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province(IKKEM) Xiamen 361005China Department of Photonics and Graduate Institute of Electro-Optical Engineering College of Electrical and Computer EngineeringYang Ming Chiao Tung UniversityHsinchu 30010China Semiconductor Research Center Hon Hai Research InstituteTaipei 11492China.

In backlighting systems for liquid crystal displays,conventional red,green,and blue(RGB)light sources that lack polarization properties can result in a significant optical loss of up to 50%when passing through a *** address this inefficiency and optimize energy utilization,this study presents a high-performance device designed for RGB polarized *** device employs an array of semipolar blueμLEDs with inherent polarization capabilities,coupled with mechanically stretched films of green-emitting CsPbBr3 nanorods and red-emitting CsPbI3-Cs4PbI6 hybrid *** CsPbBr3 nanorods in the polymer film offer intrinsic polarization emission,while the aligned-wire structures formed by the stable CsPbI3-Cs4PbI6 hybrid nanocrystals contribute to substantial anisotropic emissions,due to their high dielectric *** resulting device achieved RGB polarization degrees of 0.26,0.48,and 0.38,respectively,and exhibited a broad color gamut,reaching 137.2%of the NTSC standard and 102.5%of the Rec.2020 *** compared to a device utilizing c-plane LEDs for excitation,the current approach increased the intensity of light transmitted through the polarizer by 73.6%.This novel fabrication approach for polarized devices containing RGB components holds considerable promise for advancing next-generation display technologies.

关键词： halide perovskite light-emitting-diodes polarized emission nanocrystals stability

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A Cooperative Co-Evolution Algorithm with Variable-Importance Grouping for Large-Scale Optimization 13

A Cooperative Co-Evolution Algorithm with Variable-Importanc...

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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Li, Yongfeng Zhang, Yuze Ma, Lijia Ji, Junkai Liu, Dugang Leung, Victor C. M. Li, Jianqiang Shenzhen University National Engineering Laboratory for Big Data System Computing Technology Shenzhen518060 China Guangdong Laboratory of Artificial Intelligence and Digital Economy Shenzhen518123 China College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China Artificial Intelligence Research Institute Shenzhen MSU-BIT University Shenzhen518172 China The University of British Columbia Department of Electrical and Computer Engineering VancouverV6T 1Z4 Canada

ISBN: (纸本)9798350308365

Cooperative co-evolution (CC) is a promising direction in solving large-scale multiobjective optimization problems (LMOPs). However, most existing methods of grouping decision variables face some difficulties when searching in the huge search space. Specifically, the methods of grouping decision variables can be classified into two types, i.e., high-consumption grouping methods and non-consumption grouping methods. On the one hand, the former ones divide the decision variables into different groups based on the correlation analysis between variables, which consume much evaluation. This way may lead to premature convergence within limited computational resources. On the other hand, the later ones allocate the decision variables into sub-groups based on some metrics, e.g., order and size, which consume no evaluation while may cause the search fall into local optima. To alleviate the above issues, this paper proposes a CC-based algorithm with a variable-importance grouping (VIG) method, called VICCA. Firstly, the decision variables are classified into several subgroups according to their importance quantified by a meta-gene construction method. Secondly, a CC strategy is designed to simultaneously optimize all subgroups of decision variables formed by VIG using the differential evolution operator, which aims to accelerate the convergence speed. Thirdly, a global evolutionary strategy is proposed to optimize original decision variable space by the competitive swarm optimizer, aiming to maintain the diversity. Finally, the experiments demonstrate that our proposed VICCA has the significant advantage in solving LMOPs when compared with state-of-the-art evolutionary algorithms. © 2024 IEEE.

关键词： Optimization algorithms

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On the Generalization of Machine-Learning-aided QoT Estimation in Optical Networks 32

On the Generalization of Machine-Learning-aided QoT Estimati...

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32nd Wireless and Optical Communications Conference, WOCC 2023

作者： Gao, Hanyu Zhang, Liang Zhang, Bin Chen, Xiaoliang Li, Zhaohui School of Electronics and Information Technology Sun Yat-sen University Guangdong Provincial Key Labratory of Optoelectronic Information Processing Chips and Systems Guangzhou China Southern Marine Science and Engineering Guangdong Laboratory Zhuhai China George Mason University Department of Electrical and Computer Engineering FairfaxVA22030 United States

ISBN: (纸本)9798350337150

This paper presents a composable machine learning method for generalizing the quality-of-transmission (QoT) metric estimation in optical networks. The composable machine learning approach characterizes this metric for lightpaths of arbitrary lengths by compositions of launch, propagation and readout modules. Results verify the feasibility of the design and show its successful application in facilitating autonomous lightpath provisioning. © 2023 IEEE.

关键词： Fiber optic networks

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Near-field communications:characteristics,technologies,and engineering

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Frontiers of Information Technology & Electronic engineering 2024年第12期25卷 1580-1626页

作者： Yajun ZHAO Linglong DAI Jianhua ZHANG Ran JI Mengnan JIAN Hao XUE Hongkang YU Yunqi SUN Yu LU Zidong WU Zhuo XU Jinke LI Haiyang MIAO Zhiqiang YUAN Pan TANG Jiayu SHEN Tierui GONG Haixia LIU Jiaqi HAN Qiang FENG Zhi CHEN Lingxiang LI Gang YANG Yong ZENG Cunhua PAN Wang LIU Kangda ZHI Weidong HU Yuanwei LIU Xidong MU Chau YUEN Mérouane DEBBAH Chongwen HUANG Long LI Ping ZHANG State Key Laboratory of Mobile Network and Mobile Multimedia Technology Shenzhen 518055China ZTE Corporation Beijing 100192China Department of Electronic Engineering Tsinghua UniversityBeijing 100084China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 100876China College of Information Science and Electronic Engineering Zhejiang UniversityHangzhou 310007China Key Laboratory of High Speed Circuit Design and EMC of Ministry of Education School of Electronic EngineeringXidian UniversityXi’an 710071China Collaborative Innovation Center of Information Sensing and Understanding Xidian UniversityXi’an 710071China National Key Laboratory of Wireless Communications University of Electronic Science and Technology of ChinaChengdu 611731China National Mobile Communications Research Laboratory Southeast UniversityNanjing 210096China Purple Mountain Laboratories Nanjing 211111China School of Electrical Engineering and Computer Science Technical University of BerlinBerlin 10623Germany School of Integrated Circuits and Electronics Beijing Institute of TechnologyBeijing 100081China Department of Electrical and Electronic Engineering The University of Hong KongHong KongChina Centre for Wireless Innovation(CWI) School of ElectronicsElectrical Engineering and Computer ScienceQueen’s University BelfastBelfast BT39DTUK School of Electrical and Electronic Engineering Nanyang Technological UniversitySingapore 639798Singapore KU 6G Research Center Khalifa University of Science and TechnologyAbu DhabiUnited Arab Emirates

Near-field technology is increasingly recognized due to its transformative potential in communication systems,establishing it as a critical enabler for sixth-generation(6G)telecommunication *** paper presents a comprehensive survey of recent advancements in near-field technology ***,we explore the near-field propagation fundamentals by detailing definitions,transmission characteristics,and performance ***,we investigate various near-field channel models—deterministic,stochastic,and electromagnetic information theory based models,and review the latest progress in near-field channel testing,highlighting practical performance and *** evolving channel models,traditional mechanisms such as channel estimation,beamtraining,and codebook design require redesign and optimization to align with near-field propagation *** then introduce innovative beam designs enabled by near-field technologies,focusing on non-diffractive beams(such as Bessel and Airy)and orbital angular momentum(OAM)beams,addressing both hardware architectures and signal processing frameworks,showcasing their revolutionary potential in near-field communication ***,we highlight progress in both engineering and standardization,covering the primary 6G spectrum allocation,enabling technologies for near-field propagation,and network deployment ***,we conclude by identifying promising future research directions for near-field technology development that could significantly impact system *** comprehensive review provides a detailed understanding of the current state and potential of near-field technologies.

关键词： 6G Near-field technology Channel model Codebook Non-diffractive beams Orbital angular momentum engineering and standardization

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Edge-Assisted Accelerated Cooperative Sensing for CAVs: Task Placement and Resource Allocation

arXiv

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arXiv 2024年

作者： Wang, Yuxuan Qu, Kaige Wu, Wen Shen, Xuemin Frontier Research Center Pengcheng Laboratory China School of Electronic and Computer Engineering Peking University China School of Transportation Science and Engineering Beihang University China Department of Electrical and Computer Engineering University of Waterloo Canada

In this paper, we propose a novel road side unit (RSU)-assisted cooperative sensing scheme for connected autonomous vehicles (CAVs), with the objective to reduce completion time of sensing tasks. Specifically, LiDAR sensing data of both RSU and CAVs are selectively fused to improve sensing accuracy, and computing resources therein are cooperatively utilized to process tasks in real time. To this end, for each task, we decide whether to compute it at the CAV or at the RSU and allocate resources accordingly. We first formulate a joint task placement and resource allocation problem for minimizing the total task completion time while satisfying sensing accuracy constraint. We then decouple the problem into two subproblems and propose a two-layer algorithm to solve them. The outer layer first makes task placement decision based on the Gibbs sampling theory, while the inner layer makes spectrum and computing resource allocation decisions via greedy-based and convex optimization subroutines, respectively. Simulation results based on the autonomous driving simulator CARLA demonstrate the effectiveness of the proposed scheme in reducing total task completion time, comparing to benchmark schemes. Copyright © 2024, The Authors. All rights reserved.

关键词： Convex optimization

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