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2024 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2024

作者： Albukhari, Waleed M. Liu, Yilu Till, Abigail Alshuaibi, Khaled M. The University of Tennessee Department of Electrical Engineering and Computer Science KnoxvilleTN United States Oak Ridge National Laboratory Oak RidgeTN United States King Saud University Department of Electrical Engineering Riyadh Saudi Arabia

ISBN: (纸本)9798350313604

Lately, solar photovoltaic (PV) has received significant interest due to its economic and environmental benefits. As the integration of renewable energy sources (RES) increases into existing power grids, challenges such as the decrease in short circuit ratio (SCR) are introduced. This paper investigates a case study of the Saudi power grid, examining the voltage stability as the grid transitions from traditional power generation to 100% penetration of solar PV gradually. Moreover, the paper explores the relationship between the increase in solar penetration and the potential effects on the short circuit MVA (SCMVA), which could significantly impact the overall SCR of the system. To meet the North American Electric Reliability Corporation (NERC) recommendation of maintaining SCR at a particular level, synchronous condensers (SC)s were integrated into the grid. The effectiveness of utilizing SCs to maintain the system voltage at optimal levels in a fully solar grid is also considered. In addition, this paper covers the weak grid analysis via utilizing the Newton-Raphson load flow method, along with PV and QV curve analyses. The purpose behind that is to determine weak bus locations in need of voltage improvements, and to meet the amount of reactive power to be injected. Finally, the amount of power being delivered by SCs will be added progressively in three scenarios to show the enhancements on SCR more precisely. © 2024 IEEE.

关键词： Reactive power

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Quantum dot coherent comb lasers for B5G/6G mobile and terrestrial communication systems 28

Quantum dot coherent comb lasers for B5G/6G mobile and terre...

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Integrated Optics: Devices, Materials, and Technologies XXVIII 2024

作者： Lu, Z.G. Liu, G.C. Liu, J.R. Poole, P.J. Mao, Y.X. Zeb, K. Xie, X.R. Rahim, M. Vachon, M. Song, C.Y. Qi, Y. Weber, J. Barrios, P. Poitras, D. Sabourin, N. Chen, S. Zhao, P. Huang, L. Askarian, A. Zhang, X.P. Yao, J.P. Wu, K. Advanced Elec. and Photonics Research Centre National Research Council OttawaON Canada Depart. Electrical and Computer Engineering Concordia University MontrealQC Canada School of Elec. Engineering and Computer Science University of Ottawa OttawaON Canada Department of Electrical Engineering Ecole Polytechnique Montreal MontrealQC Canada

ISBN: (纸本)9781510670389

Future mobile and terrestrial communication systems B5G/6G are strongly expected to heterogeneously realize typically diversified performances, i.e. high-data-rate, high-mobility, low-latency, high-capacity, massive-connectivity and low-energy in order to satisfy the highly diversified application requirements. To achieve those goals the operation band of B5G/6G should be primarily in the millimeter-wave (mmW) range. Generation and distribution of mmW with traditional methods is limited by electronic bottleneck and associated complexity. Consequently broad bandwidth, simple, efficient, and cost-effective photonic mmW-over-fiber (mmWoF) transmission systems are solutions for B5G/6G. The spectral purity of mmW carriers is necessary. Numerous approaches have been proposed to generate pure mmW signals. Compared with other technologies, quantum dash or dot (QD) coherent comb lasers (QD CCLs) have great advantages for mmW generation because QD-CCLs with low power consumption and chip-scale integration capacity with silicon can provide multiple highly correlated and low noise optical channels. In this paper we will present our developed InAs/InP QD-CCLs around 1550 nm with the channel spacing from 10 GHz to 1000 GHz and the output power up to 50 mW. By using a C-band QD CCL and based on the single- and dual-optical carrier modulation schemes, an up to 16-Gb/s mmWoF optical heterodyne wireless signal at 28 GHz through a 25-km single mode fiber before the mmW carrier is optically synthesized remotely for detection over a 2-m free space. The data capacity and performance of the proposed mmWoF link can be significantly increased by utilizing a duplex mmWoF link with MIMO and WDM technique, which provides a cost-efficient and promising solution for Terabit/s capacity mmWoF fronthaul systems of B5G/6G networks. © 2024 SPIE.

关键词： Radio-over-fiber

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Deep Learning-Based Image Analysis to Track Vehicles 2

Deep Learning-Based Image Analysis to Track Vehicles

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2nd International Conference on Disruptive Technologies, ICDT 2024

作者： Prabakaran, P. Jayasudha, R. Sandhu, Mukta Gupta, Sandeep School of Computing Sciences Vels Institute of Science Technology and Advanced Studies Department of Computer Applications Chennai India Dr.N.G.P.Institute of Technology Department of Mathematics Coimbatore India Shri Vishwakarma Skill University Skill Department of Computer Science and Engineering Haryana Palwal India Department of Electrical Engineering Dehradun India

ISBN: (纸本)9798350371055

There are many ways to track the traffic conditions on roads. With the rise of AI-based image processing technology, there has been a surge in interest in developing traffic monitoring systems that rely on camera vision data. An improved road monitoring system may be derived from the data collected in this research by placing a camera at a junction. The technique detects and classifies vehicles using a deep-learning-based methodology (YOLOv4). By comparing the positions of the vehicle with the map HD, lane-by-lane trajectories of the vehicle may be approximated. The predicted vehicle trajectories are used to calculate each lane's wait lengths and traffic volumes, broken down by travel direction. This technique was evaluated using five distinct metrics: vehicle detection rates, trajectory prediction, type of vehicle categorization, traffic volume estimate, and queue length assessment. Thousands of samples were used to assess its performance. Based on the findings, it is acceptable to assume that the system can identify vehicles with a 98% success rate and an error rate of less than 25% regarding lane-by-lane trip volume estimation and vehicle type classification. Therefore, this study's approach reveals the viability of collecting comprehensive traffic information from a camera set up at a junction. Current traffic monitoring schemes have a reasonable likelihood of being developed by this study's significant contribution, which is a strategy that combines AI with HD map approaches. © 2024 IEEE.

关键词： Artificial Intelligence HD Map Traffic Monitoring System Vehicle Type Classification YOLOv4

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Design of artificial biomimetic channels with Na^(+)permeation rate and selectivity potentially outperforming the natural sodium channel

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Nano Research 2024年第9期17卷 8638-8646页

作者： Zhi Zhu Yan Zhao Chao Chang Shaojian Yan Tingyu Sun Shiyu Gu Yangmei Li Dengsong Zhang Chunlei Wang Xiao Cheng Zeng School of Optical-Electrical and Computer Engineering University of Shanghai for Science and TechnologyShanghai 200093China Innovation Laboratory of Terahertz Biophysics National Innovation Institute of Defense TechnologyBeijing 100071China School of Physics Peking UniversityBeijing 100871China International Joint Laboratory of Catalytic Chemistry College of SciencesShanghai UniversityShanghai 200444China Department of Materials Science and Engineering City University of Hong KongHong Kong 999077China

Artificial ion channels that enable high-efficiency ion transport have important implications in nanofluidics and biomedical applications such as drug ***,we show a simulation-based chemical design of a biomimetic sodium channel that possesses permeation rate and selectivity potentially higher than those of the state-of-the-art natural vertebrate voltage-gated sodium ***,our theoretical findings have undergone empirical testing,aligning well with the Arrhenius law as derived from a diverse range of experimental *** high-efficiency ion transport is achieved by anchoring the carboxylate functional groups within the channel filter.A key chemical guiding principle underlying the ion channel design is that the free-energy barrier for the Na^(+)passage across the channel should be comparable to typical thermal energy at room *** the implementation of the chemical design,we found that the relatively low free-energy barrier can be attributed to the compensation effect of the carboxylate groups to the partially lost oxygen shell of the ion within the ion channel,as well as to the consonant vibration of the ions inside and outside the *** mechanistic understanding brings new insight,at the molecular level,into the high-efficiency ion transport across the designed membrane *** proof of principle achieved from the simulations will stimulate future experimental confirmation and potential applications of the high-performance artificial channels in nanofluidics and in bioinspired iontronics.

关键词： sodium channels anchoring carboxylate functional groups molecular dynamics simulations low free-energy barrier for ion passage thermal kinetic energy

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Tackling the Qubit Mapping Problem with Permutation-Aware Synthesis 4

Tackling the Qubit Mapping Problem with Permutation-Aware Sy...

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4th IEEE International Conference on Quantum Computing and engineering, QCE 2023

作者： Liu, Ji Younis, Ed Weiden, Mathias Hovland, Paul Kubiatowicz, John Iancu, Costin Argonne National Laboratory Mathematics and Computer Science Division United States Lawrence Berkeley National Laboratory Computational Research Division United States University of California Department of Electrical Engineering and Computer Science Berkeley United States

ISBN: (纸本)9798350343236

We propose a scalable, hierarchical qubit mapping and routing algorithm that harnesses the power of circuit synthesis. First, we decompose large circuits into subcircuits small enough to be directly resynthesized. For each block, we pre-synthesize them for all permutations of its input and output qubits. Following this offline step, we employ a permutation-aware, block-based generalization of the popular SABRE mapping algorithm. This mapping step stitches together blocks by choosing an input-output permutation that minimizes intrablock gate count and required inter-block communication (SWAP and bridge gates). Our approach has a twofold advantage: 1) circuit synthesis may eliminate more two-qubit gates than other optimizing compilers;2) considering all permutations of input and output qubits eliminates communication operations transparently. In contrast, other mapping algorithms can only introduce communication operations. We show that we can produce better-quality circuits than commercial compilers: shorter by up to 68% (18% on average) fewer gates than Qiskit, up to 36% (9% on average) fewer gates than Tket. We outperform BQSkit, a permutation-unaware, synthesis-based compiler, by up to 67% (21% on average) fewer gates. We also exceed experimental optimal mappers such as OLSQ in quality (10.7% shorter circuits) and time to solution. Our scalable, heuristic approach can be seamlessly integrated into any quantum circuit compiler or optimization infrastructure, and it applies well to any qubit technology, such as superconducting and trapped ions. © 2023 IEEE.

关键词： Conformal mapping

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Prediction of Geopolymer Concrete Compressive Strength Using Convolutional Neural Networks

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computer Modeling in engineering & sciences 2024年第5期139卷 1455-1486页

作者： Kolli Ramujee Pooja Sadula Golla Madhu Sandeep Kautish Abdulaziz S.Almazyad Guojiang Xiong Ali Wagdy Mohamed Department of Civil Engineering VNR Vignana Jyothi Institute of Engineering and TechnologyHyderabadTelangana500090India Department of Information Technology VNR Vignana Jyothi Institute of Engineering and TechnologyHyderabadTelangana500090India Department of Computer Science LBEF Campus(Asia Pacific University of Technology&InnovationMalaysia)Kathmandu44600Nepal Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Guizhou Key Laboratory of Intelligent Technology in Power System College of Electrical EngineeringGuizhou UniversityGuiyang550025China Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmmanJordan

Geopolymer concrete emerges as a promising avenue for sustainable development and offers an effective solution to environmental *** attributes as a non-toxic,low-carbon,and economical substitute for conventional cement concrete,coupled with its elevated compressive strength and reduced shrinkage properties,position it as a pivotal material for diverse applications spanning from architectural structures to transportation *** this context,this study sets out the task of using machine learning(ML)algorithms to increase the accuracy and interpretability of predicting the compressive strength of geopolymer concrete in the civil engineering *** achieve this goal,a new approach using convolutional neural networks(CNNs)has been *** study focuses on creating a comprehensive dataset consisting of compositional and strength parameters of 162 geopolymer concrete mixes,all containing Class F fly *** selection of optimal input parameters is guided by two distinct *** first criterion leverages insights garnered from previous research on the influence of individual features on compressive *** second criterion scrutinizes the impact of these features within the model’s predictive *** to enhancing the CNN model’s performance is the meticulous determination of the optimal *** a systematic trial-and-error process,the study ascertains the ideal number of epochs for data division and the optimal value of k for k-fold cross-validation—a technique vital to the model’s *** model’s predictive prowess is rigorously assessed via a suite of performance metrics and comprehensive score ***,the model’s adaptability is gauged by integrating a secondary dataset into its predictive framework,facilitating a comparative evaluation against conventional prediction *** unravel the intricacies of the CNN model’s learning trajectory,a loss plot is deployed to elucidate its learning rat

关键词： Class F fly ash compressive strength geopolymer concrete prediction deep learning convolutional neural network

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Stretchable array electromyography sensor with graph neural network for static and dynamic gestures recognition system

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npj Flexible Electronics 2023年第1期7卷 361-373页

作者： Hyeyun Lee Soyoung Lee Jaeseong Kim Heesoo Jung Kyung Jae Yoon Srinivas Gandla Hogun Park Sunkook Kim Department of Advanced Materials Science and Engineering Sungkyunkwan UniversitySuwon 16419Republic of Korea Department of Electrical and Computer Engineering Sungkyunkwan UniversitySuwon 16419Republic of Korea Department of Artificial Intelligence Sungkyunkwan UniversitySuwon 16419Republic of Korea Department of Physical&Rehabilitation Medicine Kangbuk Samsung HospitalSungkyunkwan University School of MedicineSeoul 03181Republic of Korea Department of Computer Science and Engineering Sungkyunkwan UniversitySuwon 16419Republic of Korea

With advances in artificial intelligence(AI)-based algorithms,gesture recognition accuracy from sEMG signals has continued to *** multichannel-sEMG signals substantially increase the quantity and reliability of the data for any type of ***,we report an array of bipolar stretchable sEMG electrodes with a self-attention-based graph neural network to recognize gestures with high *** array is designed to spatially cover the skeletal muscles to acquire the regional sampling data of EMG activity from 18 different *** system can differentiate individual static and dynamic gestures with~97%accuracy when training a single trial per ***,a sticky patchwork of holes adhered to an array sensor enables skin-like attributes such as stretchability and water vapor permeability and aids in delivering stable EMG *** addition,the recognition accuracy(~95%)remained unchanged even after long-term testing for over 72 h and being reused more than 10 times.

关键词： system dynamic unchanged

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Additively Manufactured Electric Machine Conductors with Integrated End Turn Heat Exchangers

Additively Manufactured Electric Machine Conductors with Int...

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2022 International Conference on electrical Machines, ICEM 2022

作者： Pecotich, James Klink, David Heins, Greg Bahrani, Behrooz Monash University Power Engineering Advanced Research Laboratory Department of Electrical and Computer System Engineering Melbourne Australia

ISBN: (数字)9781665414326

ISBN: (纸本)9781665414326

Conductors within a loaded electric machine commonly induce the highest loss. Numerous cooling solutions exist for high-power density electric machine conductors with external water jackets being the most common. The inherent disadvantage of water jacket cooling is the thermal resistance between the conductor and the cooling medium, which reduces the maximum cooling capacity, regardless of the jacket design. This restriction commonly leads designers to implement solutions such as end-turn cooling. The advances in additive manufacturing have unlocked new potential for conductor end-turn cooling. This paper investigates an additively-manufactured conductor with an integrated end-turn heat exchanger. The conductor is based around a Formula Student in-hub motor. This concept utilizes air-cooling and demonstrates a steady-state current density of 11 A/mm2 for a AlSi10Mg end-turn heat-exchanger conductor, without the added mass and complexity of liquid cooling solutions. If copper is used instead of AlSi10Mg, this value increases to approximately 22 A/mm2. © 2022 IEEE.

关键词： Electric losses

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EduPar 2024 Keynote Speaker

EduPar 2024 Keynote Speaker

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IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Charles E. Leiserson MIT Department of Electrical Engineering and Computer Science MIT Computer Science and Artificial Intelligence Laboratory

ISBN: (数字)9798350364606

ISBN: (纸本)9798350364613

Aside from pure intellectual interest, why do we teach our students parallel computing? Most people would agree that the primary goal is to produce greater application performance. Yet students frequently parallelize code only to discover that it runs disappointingly slower because they don't understand performance. To exploit parallelism effectively, it must operate synergistically with a host of other techniques, including caching, vectorization, algorithms, bit tricks, loop unrolling, using compiler switches, tailoring code to the architecture, exploiting sparsity, changing data representation, metaprogramming, etc. Software performance engineering, which encompasses these techniques, is the science and art of making code run fast or otherwise limiting its consumption of resources, such as energy, memory footprint, network utilization, response time, etc. In this talk, I will argue that the end of Moore's Law makes software performance engineering a critical skill for our students to learn.

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Predicting the friction angle of clays using a multi-layer perceptron neural network enhanced by yeo-johnson transformation and coral reefs optimization

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Journal of Rock Mechanics and Geotechnical engineering 2024年第10期16卷 3982-4003页

作者： Libing Yang Trung Nguyen-Thoi Trung-Tin Tran College of Civil Engineering and Architecture Hunan Institute of Science and TechnologyYueyang414006China Laboratory for Applied and Industrial Mathematics Institute for Computational Science and Artificial IntelligenceVan Lang UniversityHo Chi Minh CityViet Nam Faculty of Mechanical-Electrical and Computer Engineering School of TechnologyVan Lang UniversityHo Chi Minh CityViet Nam Department of Information Technology Greenwich VietnamFPT UniversityDa Nang550000Viet Nam

The accurate prediction of the friction angle of clays is crucial for assessing slope stability in engineering *** study addresses the importance of estimating the friction angle and presents the development of four soft computing models:YJ-FPA-MLPnet,YJ-CRO-MLPnet,YJ-ACOC-MLPnet,and *** of all,the Yeo-Johnson(YJ)transformation technique was used to stabilize the variance of data and make it more suitable for parametric statistical models that assume normality and equal *** technique is expected to improve the accuracy of friction angle prediction *** friction angle prediction models then utilized multi-layer perceptron neural networks(MLPnet)and metaheuristic optimization algorithms to further enhance performance,including flower pollination algorithm(FPA),coral reefs optimization(CRO),ant colony optimization continuous(ACOC),and cuckoo search algorithm(CSA).The prediction models without the YJ technique,***-MLPnet,CRO-MLPnet,ACOC-MLPnet,and CSA-MLPnet,were then compared to those with the YJ technique,***-FPA-MLPnet,YJ-CRO-MLPnet,YJ-ACOC-MLPnet,and *** these,the YJ-CRO-MLPnet model demonstrated superior reliability,achieving an accuracy of up to 83%in predicting the friction angle of clay in practical engineering *** improvement is significant,as it represents an increase from 1.3%to approximately 20%compared to the models that did not utilize the YJ transformation technique.

关键词： Natural hazards Slope stability Friction angle Clay Soft computing models Geotechnical engineering

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