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检索条件"机构=Sch. of Electrical and Computer Engineering"

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Assessment of Control Strategies for Single-Phase Grid-Forming Voltage Source Converters

Assessment of Control Strategies for Single-Phase Grid-Formi...

引用

2023 International Conference on Smart Energy Systems and Technologies, SEST 2023

作者： Matas-Diaz, Francisco Jesus Kontou, Alkistis Barragan-Villarejo, Manuel Kotsampopoulos, Panos Maza-Ortega, Jose Maria Hatziargyriou, Nikos Universidad de Sevilla Dept. of Electrical Engineering Sevilla Spain Sch. of Electrical and Computer Engineering National Technical University of Athens Athens Greece

ISBN: (纸本)9798350397901

The integration of renewable energy resources (RES) in power systems is displacing conventional generation based on synchronous generators. RESs use voltage source converters as the main interface between the primary energy source and the grid. Therefore, these should guarantee in future converter-dominated power systems robust and secure operation through voltage and frequency regulation. Recently, the concept of a virtual synchronous generator (VSG) with grid-forming functionality has emerged in three-phase systems. However, the extension of this concept to single-phase devices has not been widely explored. Taking into account that a significant number of the new RES generation could be connected to distribution systems, it might be necessary to endow a certain number of single-phase RES with grid-forming capability. This paper presents the expansion of the three-phase VSG to a single-phase system including grid-forming functionality. Specifically, the paper proposes two possible implementations in the rotating and stationary reference frames. Both controllers are validated through experimental tests to substantiate their benefits and limitations. © 2023 IEEE.

关键词： Synchronous generators

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Enhancing Energy Efficiency: Statistical Analysis of RRAM Operations using ZnO-based Approach

Enhancing Energy Efficiency: Statistical Analysis of RRAM Op...

引用

2023 IEEE International Conference on Sensors and Nanotechnology, SENNANO 2023

作者： Bature, Usman Isyaku Mohd Nawi, Illani Md Khir, Mohd Haris Ba Hashwan, Saeed S. Zahoor, Furqan Rahman, Mohammad Obaidur Universiti Teknologi Petronas Electrical and Electronic Engineering Seri Iskandar Malaysia Nanyang Technological University Sch. of Computer Science and Engineering 639798 Singapore

ISBN: (纸本)9798350333312

RRAM has garnered significant attention from various perspectives;however, certain barriers hinder its widespread adoption. These challenges revolve around reliability and power operation, making their resolution crucial. This work highlights the effects of operating at high voltages (>10V), which also affect other memory technologies, including Flash memory. The study introduces an insightful approach involving voltage flow analysis coupled with exploring the fundamental thermal energy flow in ZnO-based RRAM stacks operating within 1.2V. The model adopts a two-dimensional arrangement in COMSOL Multiphysics and further employs MATLAB (LiveLinkTM). The research delves into the dynamic resistance switching process, elucidating the role of joule heating effects, field-driven ion transport, and the temperature influence when the operating voltage exceeds 1.2V, as depicted in various plots. This investigation advances our comprehension of the complex dynamics involved in RRAM operation and demonstrates methods to enhance device performance, improve reliability, and ensure long-term functionality in practical applications. © 2023 IEEE.

关键词： Zinc oxide

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Performance Assessment of an Extremely Energy-Efficient Binary Neural Network Using Adiabatic Superconductor Devices 5

Performance Assessment of an Extremely Energy-Efficient Bina...

引用

5th IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2023

作者： Chen, Olivia Li, Zhengang Yamauchi, Tomoharu Wang, Yanzhi Yoshikawa, Nobuyuki Tokyo City University Dept. Computer Science Tokyo Japan Northeasetern University Dept. Electrical and Computer Engineering Boston United States Tokyo City University Grad. Sch. Informative Engineering Tokyo Japan Yokohama National University Dept. Electrical and Computer Engineering Yokohama Japan

ISBN: (纸本)9798350332674

Binary Neural Networks (BNNs) are gaining popularity for solving real-world problems using Deep Neural Networks (DNNs), such as image recognition and natural language processing. BNNs use binary precision for weights and activations, reducing memory usage by 32 times compared to conventional networks using 32-bit floating-point precision. Among various types of BNNs, AQFP-based BNNs utilizing superconducting logic families are promising for energy-efficient computing, using magnetic flux quantization and quantum interference in Josephson-junction-based superconductor loops. This paper presents a performance assessment of a novel AQFP-based BNN architecture, highlighting scalability issues caused by increased inductance in the analog accumulation circuit. We also discuss potential optimization approaches to address these issues and improve scalability. © 2023 IEEE.

关键词： Image recognition

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A novel framework for AI-based dynamic teaming up of students in the context of online collaborative learning activities

A novel framework for AI-based dynamic teaming up of student...

引用

IEEE Education engineering (EDUCON)

作者： Irene Kilanioti Alexandros-Panagiotis Stylos Symeon Papavassiliou Sch. of Electrical & Computer Engineering National Technical University of Athens Athens Greece

ISBN: (数字)9798350394023

ISBN: (纸本)9798350394030

In the era of online learning, automated dynamic suggestions for fruitful collaborations among learners have become crucial. We propose an algorithm that takes into account ethical considerations and suggests interactions among students for collaborative involvement in group activities in an inherently fair manner: all students participate in fairly weighted activities and have a balanced number of weighted interactions. Students' preferences are taken into consideration and can be expressed either directly via their statements or indirectly via their conversations in the context of learning gamification. A synthetic preference graph that simulates students' views and thoughts is constructed. Moreover, we proceed to build a model for personalized interactions that prevents user isolation. The quality of the evolution of interactions is measured based on the diversity of interactions, the interaction graph edit similarity that affects storage cost, granularity of graph construction and fairness criteria. We use deep machine learning for sentiment detection in dialogues in order to conduct sentiment analysis of real data in the context of an online game chat among students. We categorize text as positive, negative or neutral in terms of emotion and produce student profiles. We produce embeddings with an accuracy of 92%. This analysis is extended to all texts in the discussion, resulting in a preference profile for each learner, from which ultimately a quantitative estimate of potential interaction derives for use in the interaction graph. Our approach can be utilised in the teaching practice as an efficient novel framework for online learning activities and gamification, and serves as an automated dynamic method for fair collaboration choices in teaching practice.

关键词： Sentiment analysis Costs Social networking (online) Federated learning Learning automata Heuristic algorithms Collaboration

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Link Quality-Aware Geographic Predictive Routing for V2V Network Based on GPSR

Link Quality-Aware Geographic Predictive Routing for V2V Net...

引用

2023 International Technical Conference on Circuits/Systems, computers, and Communications, ITC-CSCC 2023

作者： Harayama, Michiko Mishioka, Masahiro Gifu University Faculty of Engineering Dept. Electrical Electronic and Computer Engineering Japan Grad. Sch. Natural Science and Technology Gifu University Dept. Intelligence Science and Engineering Japan

ISBN: (纸本)9798350326413

In recent years, advances in automotive IoT technology have not only improved automated driving and driving convenience but have also led to a diminishing number of traffic accidents. Vehicle Ad-hoc Networks (VANETs) have attracted much attention because automotive IoT is based on wireless communications. Ad-hoc routing protocols that apply the characteristics of vehicle-to-vehicle (V2V) networks are needed. One of them is Greedy Perimeter Stateless Forwarding (GPSR), a routing protocol using geographic information. It uses Global Positioning System (GPS) information for routing. However, GPSR may increase the packet drop rate due to radio attenuation and fading. Therefore, C. Li et al. proposed to select the next hop by evaluating the link quality. However, due to the large moving speed of the node, the next hop may be out of the radio propagation range at the communication timing. Therefore, in this study, we propose a new routing method that combines the future location prediction proposed by Z.S. Houssaini et al. The effectiveness of the method is demonstrated by simulations using ns-3 with traffic data acquired by SUMO. © 2023 IEEE.

关键词： Routing protocols

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Assessment of Control Strategies for Single-Phase Grid-Forming Voltage Source Converters

Assessment of Control Strategies for Single-Phase Grid-Formi...

引用

International Conference on Smart Energy Systems and Technologies (SEST)

作者： Francisco Jesús Matas-Díaz Alkistis Kontou Manuel Barragán-Villarejo Panos Kotsampopoulos José María Maza-Ortega Nikos Hatziargyriou Dept. of Electrical Engineering Universidad de Sevilla Sevilla Spain Sch. of Electrical and Computer Engineering National Technical University of Athens Athens Greece

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Enhancing Energy Efficiency: Statistical Analysis of RRAM Operations using ZnO-based Approach

Enhancing Energy Efficiency: Statistical Analysis of RRAM Op...

引用

IEEE International Conference on Sensors and Nanotechnology

作者： Usman Isyaku Bature Illani Mohd Nawi Mohd Haris Md Khir Saeed S. Ba Hashwan Furqan Zahoor Mohammad Obaidur Rahman Electrical and Electronic Engineering Universiti Teknologi Petronas Seri Iskandar Malaysia Sch. of Computer Science and Engineering Nanyang Technological University Singapore

RRAM has garnered significant attention from various perspectives; however, certain barriers hinder its widespread adoption. These challenges revolve around reliability and power operation, making their resolution crucial. This work highlights the effects of operating at high voltages (>10V), which also affect other memory technologies, including Flash memory. The study introduces an insightful approach involving voltage flow analysis coupled with exploring the fundamental thermal energy flow in ZnO-based RRAM stacks operating within 1.2V. The model adopts a two-dimensional arrangement in COMSOL Multiphysics and further employs MATLAB (LiveLinkTM). The research delves into the dynamic resistance switching process, elucidating the role of joule heating effects, field-driven ion transport, and the temperature influence when the operating voltage exceeds 1.2V, as depicted in various plots. This investigation advances our comprehension of the complex dynamics involved in RRAM operation and demonstrates methods to enhance device performance, improve reliability, and ensure long-term functionality in practical applications.

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BCNN: A Bantamweight Convolutional Neural Network for P300 Detection

BCNN: A Bantamweight Convolutional Neural Network for P300 D...

引用

2023 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2023

作者： Liu, M. Wang, S. Beyette, F.R. University of Georgia School of Electrical and Computer Engineering AthensGA United States Hebei Normal Univ. of Sci. & Tech Sch. of Math. and Info. Sci. & Tech Hebei Qinhuangdao China Yanshan University School of Information Science and Engineering Hebei Qinhuangdao China

ISBN: (纸本)9798350341256

As one kind of Event-Related Potentials (ERPs), P300 plays an important role in studying neural activities and cognitive processes, and lays the foundation for P300 speller - the Brain computer Interface (BCI) working by detecting P300. However, due to P300's high subject variability and low Signal Noise Ratio (SNR), it's always a challenge to do P300 detection. Convolutional Neural Networks (CNNs) have been widely recognized as effective methods for P300 detection, leading to the development of increasingly complex CNN architectures for P300 detection in recent years. However, this paper takes a different approach by proposing the bantamweight CNN (BCNN), the simplest and fast-training CNN for P300 detection. BCNN comprises only one convolutional filter and a total of 141 parameters. Surprisingly, it achieves state-of-the-art performance after just 2 epochs of training, making it an exceptionally lightweight and fast CNN for P300 detection. BCNN not only provides new ideas for CNN design, but also effectively address resource and time constrained situations. © 2023 IEEE.

关键词： Brain computer interface

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Design of a Compact Monopole Antenna for Super Wideband and 5G Applications 8

Design of a Compact Monopole Antenna for Super Wideband and ...

引用

8th IEEE International Conference on Adaptive Science and Technology, ICAST 2021

作者： Joseph, Owusu Silas, Akuffo Donmaaye, Sangmen Elvis Nawunzuk, Tindana Jeremiah Loung, Vincent Yong Kai Duah, Nana Twum University of Energy and Natural Resources Department of Electrical and Computer Engineering Sunyani Ghana Universiti Teknologi Malaysia Sch. of Electrical Engineering Faculty of Engineering Wireless Communication Centre Johor Malaysia

ISBN: (纸本)9781665427173

Numerous technologies have been employed as the demand for data requirements and high resolution in wireless communication systems increase. Increased research has led to the evolution of numerous antennas including but not limited to monopole antennas and dipole antennas. An innovative design monopole antenna for Ultra-wideband applications is presented in this paper. The design incorporates a cut-in rectangular patch with, two notches at the upper and lower corners of the patch and a microstrip feed line. The proposed compact antenna is designed on a Rogers RT/Duroid 5880 substrate of dimensions 22 mm x 28 mm x 15 mm which shows its compactness. Testing and simulation results generated from the proposed design showed good Ultra-wideband characteristics between 3.8 GHz and 50 GHz frequencies at 10 dB return loss. The performance of the antenna was tested at the sub-6 GHz spectrum and millimeter-wave spectrum specifically 6 GHz and 28 GHz. The proposed antenna has super-wide bandwidth with good impedance matching and isolation. The antenna's simulated performance characteristics make it applicable in radar, sonar imaging in handheld devices in the Ultra-wideband spectrum, and 5G MIMO application. © 2021 IEEE.

关键词： Monopole antennas

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Genetic Programming-Based Multi-Object Matching for Mussel Floats in Mussel Farm Images

Genetic Programming-Based Multi-Object Matching for Mussel F...

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International Conference on Image and Vision Computing New Zealand, IVCNZ

作者： Dylon Zeng Ying Bi Ivy Liu Bing Xue Ross Vennell Mengjie Zhang Sch. of Engineering and Computer Science Victoria University of Wellington Wellington New Zealand Electrical and Information Engineering Zhengzhou University Zhengzhou China Coastal and Freshwater Group Cawthron Institute Nelson New Zealand

ISBN: (数字)9798331518776

ISBN: (纸本)9798331518783

The demand for Artificial Intelligence (AI)-powered solutions in New Zealand's aquaculture sector, particularly in mussel farms, is fast growing due to the need for enhanced productivity, reduced carbon footprint, and a safer worksite. An effective crop monitoring system that relies on high-resolution images from boat-mounted cameras requires an effective multi-object matching module. This paper presents a new Genetic Programming (GP)-based multi-object matching approach for mussel floats in farm images, addressing site-specific challenges such as a large number of tracklets, near-identical appearances, and low-overlapping scenes. Current object matching methods, including appearance models, motion models, and transformer models, struggle under these conditions. Evaluated on mussel farm images from the Marlborough Sounds of New Zealand, the proposed GP method demonstrates significantly higher matching accuracy, achieving 96.4% compared to 39.6% by a state-of-the-art transformer model. Our GP method achieves accurate multi-object matching in both slow and fast-moving scenarios, outperforming the state-of-the-art particularly in the latter.

关键词： Productivity Accuracy Tracking Genetic programming Crops Transformers Cameras Object recognition Monitoring Carbon footprint

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