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Annual North-American Power Symposium

作者： Lyric Haylow Diana Wallison Jonathan Snodgrass Thomas Overbye Department of Electrical and Computer Engineering Texas A&M University College Station TX

ISBN: (数字)9798331521035

ISBN: (纸本)9798331521042

With the increase in electric vehicles (EV) and heavy-duty electric vehicles (HDEV) on the roads today, an appropriate increase in charging infrastructure needs to be made to keep up with the growing load demand they”re making. To appropriately plan for developing new charging infrastructure, preliminary studies with synthetic grids that can accurately simulate how the electric grid may react are necessary. However, previous synthetic models have been insufficient as they”re either too restricting or assume ideal conditions for distribution or transmission grid aspects. With new large-scale combined transmission and distribution (T&D) grid models, the impact of both EVs and HDEVs can be accurately measured, and corresponding changes to the grid can be ensured. In a recent study to test how the I45 highway from Dallas to Houston within the U.S. state of Texas can withstand 96 test case scenarios, full T&D synthetic model simulations resulted in roughly 67.9 GB of resultant data. This paper aims to present methods for aggregating, summarizing, and analyzing the optimal power flow (OPF), generator cost, least marginal price (LMP), and overload results into easily interpretable sizes.

关键词： Costs Roads Big Data Electric vehicles Data models Generators North America Load modeling Load flow

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Recent Advances in Three-Dimensional Frequency Selective Structures

Recent Advances in Three-Dimensional Frequency Selective Str...

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2022 IEEE Region 10 International Conference, TENCON 2022

作者： Li, Bo Zhu, Lei College of Electronic and Optical Engineering Nanjing University of Posts and Telecommunications Nanjing China University of Macau Department of Electrical and Computer Engineering China

ISBN: (数字)9781665450959

ISBN: (纸本)9781665450959

Frequency-selective structure (FSS) is a periodic artificial structure that can produce electromagnetic selectivity. Conventionally, it consists of single- or multi-layer elements periodically arranged in a plane, which can manipulate spatial electromagnetic waves under different frequencies, polarizations, and angles of incidence. Various types of structures, analysis theories, and design methods have been developed for conventional FSSs. Unfortunately, these conventional surfaces manipulate electromagnetic waves through their 2-D or 2.5-D periodic elements, thus leading to serious limitations to their filtering performance and design flexibilities. Recently, a new class of 3-D FSS, consisting of 3-D multimode elements of waveguide cavities or transmission-line structures, has attracted much attention. Owing to this special construction of periodic elements, 3-D FSSs can provide more degrees of freedom in the spatial dimensions to exhibit superior performance features. This paper aims to provide a review of recent 3-D FSSs based on slot-lines with a focus on the state-of-the-art techniques in the design and exploration of bandpass FSSs and wideband polarizers. © 2022 IEEE.

关键词： Degrees of freedom (mechanics)

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Beam Steering for Adhoc Mesh Network Wireless Power Transfer at 2.45 GHz

Beam Steering for Adhoc Mesh Network Wireless Power Transfer...

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2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022

作者： Gaire, Pawan Islam, Md Khadimul Khan, Md Rayhan Chibane, Cherif Bhardwaj, Shubhendu Florida International University College of Engineering and Computing Dept. of Electrical and Computer Engineering MiamiFL33199 United States WiGL Inc. HamptonVA23666 United States

ISBN: (数字)9781665496582

ISBN: (纸本)9781665496582

We present beam steering module for wireless power transfer system with our ad-hoc mesh network modality. The system comprises of 4×4 butler matrix and 4 1 × 4 patch antenna array operating at 2.45 GHz and provides total azimuthal coverage of 107.3°. This module is then paired with our wireless power transfer system. © 2022 IEEE.

关键词： Energy transfer

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A swarm optimizer with attention-based particle sampling and learning for large scale optimization

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Journal of Ambient Intelligence and Humanized computing 2023年第7期14卷 9329-9341页

作者： Sheng, Mengmeng Wang, Zidong Liu, Weibo Wang, Xi Chen, Shengyong Liu, Xiaohui School of Computer Science and Technology Zhejiang University of Technology Hangzhou300023 China College of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao266590 China Department of Computer Science Brunel University London Middlesex UxbridgeUB8 3PH United Kingdom Zhejiang Police College Hangzhou310053 China School of Computer Science and Technology Tianjin University of Technology Tianjin300382 China

Attention mechanism, which is a cognitive process of selectively concentrating on certain information while ignoring others, has been successfully employed in deep learning. In this paper, we introduce the attention mechanism into a particle swarm optimizer and propose an attention-based particle swarm optimizer (APSO) for large scale optimization. In the proposed method, the attention mechanism is introduced such that activating different particles to participate in evolution at different stages of evolution. Further, an attention-based particle learning is devised to randomly select three particles from a predominant sub-swarm, which is activated by the attention mechanism, to guide the learning of particles. The cooperation of these two strategies could be employed to achieve a balanced evolution search, thus appropriately searching the space of large-scale optimization problems. Extensive experiments have been carried out on CEC’2010 and CEC’2013 large scale optimization benchmark functions to evaluate the performance of proposed method and to compare with related methods. The results show the superiority of proposed method. © 2022, The Author(s).

关键词： Particle swarm optimization (PSO)

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Epilepsy Detection Through EEG Signal Classification Using Machine Learning Methods 4

Epilepsy Detection Through EEG Signal Classification Using M...

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4th IEEE International Conference on ICT in Business Industry and Government, ICTBIG 2024

作者： Deshpande, Vivek Gajendran, P. Ojha, Varun Latha, B. Soni, Ishika Arunkumar, D.T. Vishwakarma Institute of Technology Department of Computer Engineering Pune India Karpagam College of Engineering Department of Electrical and Electronics Engineering Coimbatore641032 India Chitkara University Centre of Research Impact and Outcome Punjab Rajpura140417 India Prince Shri Venkateshwara Padmavathy Engineering College Department of It Chennai127 India Chitkara University Chitkara Centre for Research and Development Himachal Pradesh 174103 India Karnataka Bangalore India

ISBN: (纸本)9798331518981

In this exertion demonstrates the application of a deep learning algorithm to the analysis of focal and non-focal EEG data for the finding of epilepsy. This research presents a strategy for automating the diagnosis of epilepsy by making use of a soft computing resource. By using the ANFIS classification technique, focal and non-focal samples may be distinguished. Structures computation, features classification, and features transformation are the three pillars upon which this technique rests. For an electroencephalogram (EEG) data, the Approximate and Directional bands are produced when the suggested NSCT is used. NSDF and Non-Subsampled Pyramid Filter are the two main components of this NSCT. These fall into two categories: low pass, which includes power frequencies, and high pass, which includes high frequency noise. To do this, we construct directed subbands and reroute the high-pass signal using NSDF. Step two of decomposition involves creating high and low frequency sub bands by passing the low pass sub band signal via the Non-Sub Sampled Pixel Frequency (NSPF). The directed sub bands that are created are achieved by retransmitting the high-frequency sub band signal via NSDF. Using the statistical properties obtained from these sub-bands, the ANFIS classification method divides the overall EEG signal into focal and non-focal samples. Applying the proposed method to a collection of EEG signal extraction measurements allows for validation. © 2024 IEEE.

关键词： Deep learning

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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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Applying Machine Learning & Knowledge Discovery to Intelligent Agent-Based Recommendation for Online Learning Systems

Applying Machine Learning & Knowledge Discovery to Intellige...

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2023 IEEE International Conference on Device Intelligence, computing and Communication Technologies, DICCT 2023

作者： Murugesan, S. Bharathiraja, N. Pradeepa, K. Ravindhar, N.V. Kumar, M. Vinoth Marappan, Raja Tagore Engineering College Department of It Chennai India Chitkara University Chitkara University Institute of Engineering and Technology Punjab India St. Michael College of Engineering and Technology Department of Computer Science and Engineering TN Sivaganga India Saveetha Engineering College Department of Cse Tamil Nadu India Dmi-St.Eugene University Dept. of Cse Zambia Sastra Deemed University School of Computing Thanjavur India

ISBN: (纸本)9781665474924

E-learning is one of the favorite jobs where all the learners can learn through different online sites to update their knowledge acquisition. Though online learning supports several benefits, there are many challenges to be considered, for example, the information resources, quality of the search, accessing the correct information, getting the search results within a reasonable computing time, etc. This research develops the new natural language processing (NLP) intelligent and online recommender using the learner's profile information and semantic analysis of the search history at different times. The intelligent clustering strategy is applied, so the system learns automatically, and the learner's characteristics are analyzed periodically. The simulation results of the proposed research are compared with the state-of-the-art techniques and provide the minimized error rates to the selection of courses and recommendations with the recommendation accuracy in (98.2%, 98.9%). The MAE lies between (0.12, 0.35) for the considered clusters. Compared to the other methods, the method works well for clusters of sizes 10, 20, 30, 40, and 50. © 2023 IEEE.

关键词： Knowledge acquisition

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IRS-Assisted Data and Energy Transfer MAC Protocol

IRS-Assisted Data and Energy Transfer MAC Protocol

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International Conference on Ubiquitous Information Management and Communication (IMCOM)

作者： Weiyue Xing Yijun Piao Tae-Jin Lee Department of Electrical and Computer Engineering College of Information and Communication Engineering Sungkyunkwan University Suwon South Korea

In the next-generation wireless networks, an enormous number of devices are expected to communicate with one another. However, due to the battery limitation of devices and insufficient energy supplement, data transmission efficiency of the network can be reduced. Intelligent Reflecting Surface (IRS) can work as helper for energy harvesting. In this paper, we propose an energy-efficient Medium Access Control (MAC) protocol that utilizes Non-Orthogonal Multiple Access (NOMA) with IRS. In the proposed protocol, devices can transmit data to the Hybrid Access Point (H-AP) simultaneously through NOMA and achieve sufficient energy from the H-AP with the help of IRS. The simulation results show that the proposed protocol has notable improvement in the system throughput and energy efficiency.

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Transmission Analysis of OFDM System Based on Index Modulation and QPSK 14

Transmission Analysis of OFDM System Based on Index Modulati...

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14th IEEE International Conference on computer Research and Development, ICCRD 2022

作者： Ye, Jiaqi Yao, Hongtao College of communication and information engineering Shanghai University Shanghai China McGill University Department of Electrical and Computer Engineering MontrealQC Canada

ISBN: (纸本)9781728177212

With the continuous development of communication technology, people put forward higher and higher requirements for the next generation mobile communication system. With the large-scale popularization of 4G technology, the research of 5G technology has become the first research task of major institutions in recent years. How to design a communication system with higher speed, higher capacity and lower energy consumption has become an urgent task. Carrier index modulation system has become one of the research hotspots in recent years because of its better advantages such as low peak to average ratio and anti frequency offset. Starting from the transmission performance, this paper theoretically analyzes and deduces the bit error rate and spectrum of index modulation OFDM system, mainly studies the impact of bit rate on spectrum bandwidth and the advantages of SIM-OFDM compared with traditional OFDM system. © 2022 IEEE.

关键词： Orthogonal frequency division multiplexing

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An Empirical Evaluation of Machine Learning Algorithms for Groundwater Quality Classification 3

An Empirical Evaluation of Machine Learning Algorithms for G...

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3rd International Conference on Innovative Practices in Technology and Management, ICIPTM 2023

作者： Domakonda, Vinay Kumar Sasirekha, K. Sangeetha, S. Umasankar, L. Nagendiran, S. Kumar, M Jogendra Vignan's Foundation for Science and Technology Department of Mechanical Engineering Andhra Pradesh India R.M.D Engineering College Department of Computer Science Kavarapettai India Veltech Multitech Department of Information Technology Chennai India R.M.K College of Engineering and Technology Department of Electrical and Electronics Chennai India R.M.K Engineering College Department of Artificial Intelligence Kavaraipettai India KoneruLakshmaiah Education Foundation Department of Computer Science Vaddeswaram India

ISBN: (纸本)9798350336238

Groundwater is an effective monitoring system is essential, one of the most vulnerable resources. The use of spatial data to measure spatial changes in groundwater one of the most key things of soil monitoring. As a result, the most important water constituents based on groundwater characteristics is critical for an effective soil monitoring programmed the development of an efficient reference system that estimates. We evaluated the performance of neural network (NN)-based algorithms and event prediction models (EPM)) to estimate the severity of SS in some Indian regions throughout this study. Using 16 years of We developed a regional and local model remote sensing dataset to estimate the SS of the entire Indian basin and each catchment in the study area. Based on EPM and NN regional models had accuracy and SS of 88%, 96%, 88%, and 87%, The estimation and SS outperformed both the regional and spatial NN by 50-84% and 71-84%, whereas the local model was the empirically derived model, respectively. Consequently, according to the findings, machine learning methods should be used to accurately and continuously monitor groundwater quality parameters. In complex topography of India and other similar land classifications. © 2023 IEEE.

关键词： Landsat

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