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Chip-scale spontaneous quasi-phase matched second harmonic generation in a micro-racetrack resonator

Science China(Physics,Mechanics & Astronomy) 2023年第8期66卷 66-74页

作者： Tingge Yuan Jiangwei Wu Yi'an Liu Xiongshuo Yan Haowei Jiang Hao Li Zhaokang Liang Qiang Lin Yuping Chen Xianfeng Chen State Key Laboratory of Advanced Optical Communication Systems and Networks School of Physics and Astronomy.Shanghai Jiao Tong UniversityShanghai 200240China Collaborative Innovation Center of Light Manipulations and Applications Shandong Normal UniversityJinan 250358China Department of Electrical and Computer Engineering University of RochesterNew York 14627USA

In this paper,we demonstrate efficient spontaneous quasi-phase matched(SQPM)second harmonic generation(SHG)in a microracetrack resonator on X-cut thin film lithium *** approach does not involve poling,but exploits the anisotropy of the crystals to allow the phase-matching condition to be fulfilled spontaneously as the TE-polarized light circulates in a specifically designed racetrack *** experiment,normalized on-chip conversion efficiencies of 1.01×10-4/W and 0.43×10-4/W are achieved by 37th-order and 111th-order SQPM,*** configurable SQPM will benefit the application of nonlinear frequency conversion and quantum source generation in chip-scale integrated photonics compatible with standard CMOS fabrication processes.

关键词： lithium niobate on insulator quasi-phase matching second harmonic generation

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RAJA Performance Suite: Performance Portability Analysis with Caliper and Thicket

RAJA Performance Suite: Performance Portability Analysis wit...

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2024 Workshops of the International Conference for High Performance Computing, Networking, Storage and Analysis, SC Workshops 2024

作者： Pearce, Olga Burmark, Jason Hornung, Rich Bogale, Befikir Lumsden, Ian Mckinsey, Michael Yokelson, Dewi Boehme, David Brink, Stephanie Taufer, Michela Scogland, Tom Lawrence Livermore National Laboratory LivermoreCA United States University of Tennessee Department of Electrical Engineering and Computer Science KnoxvilleTN United States Texas A&M University Department of Computer Science and Engineering College StationTX United States

ISBN: (纸本)9798350355543

Maintaining performant code in a world of fast-evolving computer architectures and programming models poses a significant challenge to scientists. Typically, benchmark codes are used to model some aspects of a large application code's performance, and are easier to build and run. Such benchmarks can help assess the effects of code or algorithm changes, system updates, and new hardware. However, most performance benchmarks are not written using a wide range of GPU programming models. The RAJA Performance Suite provides a comprehensive set of computational kernels implemented in a variety of programming models. We integrated the performance measurement and analysis tools Caliper and Thicket into the RAJA Performance Suite to facilitate performance comparison across kernel implementations and architectures. This paper describes the RAJA Performance Suite, performance metrics that can be collected, and experimental analysis with case studies. The RAJA Performance Suite and integration of Caliper and Thicket enabled us to effectively measure the variety of implementations on the variety of hardware, and automatically characterize subsets of kernels which exhibit similar bottlenecks - and therefore perform similarly on new architectures which provide a different balance between resources such as FLOPS and memory bandwidth. We definitively demonstrate that the most memory bound kernels show the most performance gains on architectures with high-bandwidth memory (HBM), and that the kernels that have other bottleneck may, to a lesser extent, benefit from the higher-FLOPS GPUs. © 2024 IEEE.

关键词： benchmarking high performance computing performance analysis performance portability

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Development of Internet of Things Circuitry for Intelligent Interactions of Smart Meters with Users 2

Development of Internet of Things Circuitry for Intelligent ...

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2nd International Conference on Multidisciplinary engineering and Applied Science, ICMEAS 2023

作者： Abdulfatai, Abdulhakeem Oladele Musa, Abdulwaheed Faruk, Nasir Kwara State University Department of Electrical & Computer Engineering Malete Nigeria Kwara State University Centre for Artificial Intelligence and Machine Learning Systems Department of Electrical & Computer Engineering Malete Nigeria Sule Lamido University Department of Information Technology Kafin Hausa Nigeria

ISBN: (纸本)9798350358834

In modern times, people's fast-paced lifestyles make it challenging to keep track of essential recurring bills such as electricity, water, and gas. This paper proposes a unified smart metering system utilizing the Internet of Things (IoT) technology to address this need. This system comprises two interconnected sub-systems that manage resource consumption. The first subsystem is a unified metering sub-system, while the second is a cloud-controlled sub-system that stores and analyzes data. Both sub-systems communicate wirelessly, and the server is automatically updated as resources are consumed. The design employs an intelligent interaction approach that leverages information and communication technologies to improve user experiences, task performance, and quality of life. The expected outcome is the development of a mobile application that integrates a billing portal for payment processing. The implementation of this solution is expected to enhance resource utilization, promote sustainability practices, and revolutionize the user experience of interacting with utility services. © 2023 IEEE.

关键词： Smart meters

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A hybrid deep learning approach for phenotype prediction from clinical notes

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Journal of Ambient Intelligence and Humanized Computing 2023年第4期14卷 4503-4513页

作者： Khalafi, Sahar Ghadiri, Nasser Moradi, Milad Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan84156-83111 Iran Institute for Artificial Intelligence Center for Medical Statistics Informatics and Intelligent Systems Medical University of Vienna Vienna Austria

Identifying patient cohorts from clinical notes in secondary use of electronic health records is a fundamental task in clinical information management. The patient cohort identification process requires identifying the patient phenotypes. However, the growing number of clinical notes makes it difficult to analyze the data manually. Therefore, automatically extracting clinical concepts is crucial to identify patient phenotypes correctly. This paper’s proposed hybrid model is based on a neural bidirectional sequence model (BiLSTM or BiGRU) and a Convolutional Neural Network (CNN) for identifying patients’ phenotypes in clinical notes. Furthermore, an extra CNN layer is run parallel to the hybrid proposed model to extract more features related to each phenotype. We used pre-trained embeddings such as FastText and Word2vec separately as the input layers to evaluate other embedding’s performance in identifying patient phenotypes. We also measured the effect of adding additional data cleaning steps on discharge reports to identify patient phenotypes using deep learning models. Results demonstrated the proposed hybrid model extracts more features than existing methods of patient phenotype extraction and provides a better F1-score. We show that complementing the proposed hybrid model with an extra CNN in identifying different phenotypes improves the F1 scores. In addition, eliminating punctuation, numbers, and stop words in discharge reports before training hybrid models increased model performance. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Embeddings

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Android-Based Visualization of Vehicle Trip Data for Accident Reconstruction

Android-Based Visualization of Vehicle Trip Data for Acciden...

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2024 International Conference on electrical engineering and Informatics, ICELTICs 2024

作者： Alkifani, Ahmad Mufadhdhal Fitria, Maya Sitorus, Muhammad Daffa Adrian Maulana, T. Muhammad Caesar Humaira Dawood, Rahmad Universitas Syiah Kuala Department of Electrical and Computer Engineering Indonesia Interactive Intelligent Systems Research Group Universitas Syiah Kuala Banda Aceh23111 Indonesia

ISBN: (纸本)9798350366822

Vehicle traffic accident investigations often depend on eyewitness testimony, which can be unreliable, especially in remote areas where no closed circuit television (CCTV) footage is available. A mobile data logger was developed, equipped with a range of sensors, including an accelerometer and gyroscope, to collect and store data related to vehicle movements. An additional Flutter-driven program was developed to extract and visualize data from the mobile logger, and thus improve the accuracy of accident detection and allow incidents to be rebuilt. These programs were subjected to black-box testing, which produced results consistent with the anticipated outcomes for both the recording and data visualization tests. The data visualization application was subjected to testing using the system usability scale (SUS) technique and obtained a score of 89.5, corresponding to an A grade, the highest possible score of the 5 grade levels. © 2024 IEEE.

关键词： Black-box testing

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Recent Progress in Reduced Order Models for Electromagnetic Particle-in-Cell Kinetic Plasma Simulations

Recent Progress in Reduced Order Models for Electromagnetic ...

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2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2023

作者： Nayak, I. Nicolini, J.L. Na, D.-Y. Teixeira, F.L. The Ohio State University ElectroScience Laboratory Department of Electrical and Computer Engineering ColumbusOH43212 United States Department of Electrical Engineering Gyeongbuk Province Pohang Korea Republic of

ISBN: (纸本)9781665442282

We discuss recent progress on several model order reduction techniques for electromagnetic particle-in-cell (EM- PIC) simulations of kinetic plasmas: Proper Orthogonal De-composition (POD), Dynamic Mode Decomposition (DMD), and Koopman autoencoder (KAE). In the past, these techniques have been employed as powerful tools for data-driven modeling of nonlinear complex systems in general. For EMPIC kinetic plasma simulations, we show that they can reduce the number of degrees of freedom by projecting the solution space into a smaller space constituted of representative spatiotemporal modes. The trade- off between accuracy and cost can be controlled, in a tunable fashion, by adjusting the number of retained modes in the reduced model. POD, DMD, and KAE reduced order models are highly desirable to enable kinetic plasma simulations at a much reduced cost and hence more efficient parameter space sweeps during optimization loops for device design. These reduced order models are also useful as diagnosis tools for better understanding of the underlying plasma dynamics through the extraction of dominant features of the solution in a hierarchical fashion. © 2023 IEEE.

关键词： Plasma simulation

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Robust Wireless Power Transfer by Self-Oscillating Controlled Inverter and Circular Pads 3

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

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3rd International Conference on electrical Machines and Drives, ICEMD 2023

作者： Eikani, Alireza Amirkhani, Mohammad Jafari, Hossein Vaez-Zadeh, Sadegh Mirsalim, Mojtaba Khaburi, Davood Arab University of Tehran Advanced Motion Systems Research Lab School of Electrical and Computer Engineering College of Engineering Tehran Iran Department of Electrical Engineering Tehran Iran Iran University of Science and Technology Department of Electrical Engineering Tehran Iran

ISBN: (纸本)9798350393743

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. © 2023 IEEE.

关键词： Energy transfer

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Multi-Agent Cooperative Games Using Belief Map Assisted Training 26

Multi-Agent Cooperative Games Using Belief Map Assisted Trai...

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26th European Conference on Artificial Intelligence, ECAI 2023

作者： Luo, Chen Huang, Qinwei Wu, Alex B. Khan, Simon Li, Hai Qiu, Qinru Department of Electrical Engineering & Computer Science Syracuse University United States Fayetteville-Manlius High School United States Air Force Research Laboratory United States Department of Electrical Engineering & Computer Science Duke University United States

ISBN: (纸本)9781643684369

In a multi-agent system, agents share their local observations to gain global situational awareness for decision making and collaboration using a message passing system. When to send a message, how to encode a message, and how to leverage the received messages directly affect the effectiveness of the collaboration among agents. When training a multi-agent cooperative game using reinforcement learning (RL), the message passing system needs to be optimized together with the agent policies. This consequently increases the model's complexity and poses significant challenges to the convergence and performance of learning. To address this issue, we propose the Belief-map Assisted Multi-agent System (BAMS), which leverages a neuro-symbolic belief map to enhance training. The belief map decodes the agent's hidden state to provide a symbolic representation of the agent's understanding of the environment and other agents' status. The simplicity of symbolic representation allows the gathering and comparison of the ground truth information with the belief, which provides an additional channel of feedback for the learning. Compared to the sporadic and delayed feedback coming from the reward in RL, the feedback from the belief map is more consistent and reliable. Agents using BAMS can learn a more effective message passing network to better understand each other, resulting in better performance in the game. We evaluate BAMS's performance in a cooperative predator and prey game with varying levels of map complexity and compare it to previous multi-agent message passing models. The simulation results showed that BAMS reduced training epochs by 66%, and agents who apply the BAMS model completed the game with 34.62% fewer steps on average. © 2023 The Authors.

关键词： Multi agent systems

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Isolated Single-stage Three-phase AC/DC Converter using Bidirectional Switches

Isolated Single-stage Three-phase AC/DC Converter using Bidi...

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2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023

作者： Narwal, Ramandeep Wong, Isaac Bhattacharya, Subhashish Baliga, B. Jayant Hopkins, Douglas C. North Carolina State University Freedm Systems Center Department of Electrical and Computer Engineering RaleighNC27695 United States

ISBN: (纸本)9798350316445

The advent of the SiC Bidirectional FET (BiDFET), a monolithic 1.2 kV bidirectional switch, has rendered the single-stage three-phase AC/DC converter topology a promising approach for implementing AC/DC converters. This topology, which integrates a full-bridge converter with a single-phase to three-phase matrix converter via a high-frequency transformer, is particularly suitable for applications requiring galvanic isolation, buck-boost functionality, and bidirectional power flow. The single-stage design eliminates the need for bulky and unreliable electrolytic capacitors, and utilizes a single magnetic component for power transfer. In the matrix converter, bidirectional switches, which were traditionally implemented using combinations of multiple semiconductor devices such as MOSFETs, IGBTs, and diodes, can now be realized using the single-chip solution, BiDFET. This advancement leads to a lower switch count, compact converter implementation, with lower inductance commutation cells, thereby enhancing the overall efficiency and compactness of the system. The paper presents a unified model of the converter, considering all control parameters, including the duty cycles and phase shift of transformer voltages. Detailed expressions for power transfer, transformer currents, and currents at AC and DC ports are provided. Additionally, the paper outlines the conditions necessary for soft-switching of all switches and the commutation schemes required for the practical implementation of the matrix converter modulation scheme. A hardware prototype of a 10 kW, 480 VRMS, LL/ 800 V AC/DC system has been developed, and experimental results are presented to demonstrate its performance. © 2023 IEEE.

关键词： BiDFET Bidirectional switches commutation dual active bridge (DAB) four-quadrant switches isolated AC/DC converter matrix converter modeling modulation SiC bidirectional FET soft switching zero voltage switching (ZVS)

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Optimal Load Forecasting Model for Peer-to-Peer Energy Trading in Smart Grids

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computers, Materials & Continua 2022年第1期70卷 1053-1067页

作者： Lijo Jacob Varghese K.Dhayalini Suma Sira Jacob Ihsan Ali Abdelzahir Abdelmaboud Taiseer Abdalla Elfadil Eisa Department of Electrical and Electronics Engineering Christian College of Engineering and TechnologyOddanchatram624619India Department of Electrical and Electronics Engineering K.Ramakrishnan College of EngineeringTiruchirappalli621112India Department of Computer Science and Engineering Christian College of Engineering and TechnologyOddanchatram624619India Department of Computer System and Technology Faculty of Computer Science and Information TechnologyUniversity of Malaya50603Kuala LumpurMalaysia Department of Information Systems King Khalid UniversityMuhayel Aseer62529Saudi Arabia Department of Information Systems-Girls Section King Khalid UniversityMahayil62529Saudi Arabia

Peer-to-Peer(P2P)electricity trading is a significant research area that offers maximum fulfilment for both prosumer and *** also decreases the quantity of line loss incurred in Smart Grid(SG).But,uncertainities in demand and supply of the electricity might lead to instability in P2P market for both prosumer and *** recent times,numerous Machine Learning(ML)-enabled load predictive techniques have been developed,while most of the existing studies did not consider its implicit features,optimal parameter selection,and prediction *** order to overcome fulfill this research gap,the current research paper presents a new Multi-Objective Grasshopper Optimisation Algorithm(MOGOA)with Deep Extreme Learning Machine(DELM)-based short-term load predictive technique i.e.,MOGOA-DELM model for P2P Energy Trading(ET)in *** proposed MOGOA-DELM model involves four distinct stages of operations namely,data cleaning,Feature Selection(FS),prediction,and parameter *** addition,MOGOA-based FS technique is utilized in the selection of optimum subset of ***,DELM-based predictive model is also applied in forecasting the load *** proposed MOGOA model is also applied in FS and the selection of optimalDELM parameters to improve the predictive *** inspect the effectual outcome of the proposed MOGOA-DELM model,a series of simulations was performed using UK Smart Meter *** the experimentation procedure,the proposed model achieved the highest accuracy of 85.80%and the results established the superiority of the proposed model in predicting the testing data.

关键词： Peer to Peer energy trade smart grid load forecasting machine learning feature selection

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