检索结果-内蒙古大学图书馆

arXiv 2023年

作者： Subedi, Sunil Poudel, Bidur Aslami, Pooja Fourney, Robert Rekabdarkolaee, Hossein Moradi Tonkoski, Reinaldo Hansen, Timothy M. The Department of Electrical Engineering and Computer Science The Mathematics and Statistics Department South Dakota State University BrookingsSD57007 United States The Electrical & Computer Engineering Department University of Maine OronoME United States

This research focuses on the evolving dynamics of the power grid, where traditional synchronous generators are being replaced by non-synchronous power electronic converter (PEC)-interfaced renewable energy sources. The non-linear dynamics must be accurately modeled to ensure the stability of future converter-dominated power systems (CDPS). However, obtaining comprehensive dynamic models becomes more complex and computationally intensive as the system grows. This study proposes a scalable and automated data-driven partitioned modeling framework for CDPS dynamics. The method constructs reduced-ordered dynamic linear transfer function models using input-output measurements from a PEC switching model. Validation experiments were conducted on single-house and multi-house scenarios, demonstrating high accuracy (over 97%) and significant computational speed improvements (6.5 times faster) compared to comprehensive models. This framework and modeling approach offers valuable insights for efficient analysis of power system dynamics, aiding in planning, operation, and dispatch. © 2023, CC BY.

关键词： Electric inverters

来源：评论

学校读者我要写书评

暂无评论

Implementing Augmented Reality (AR) Textbooks in Primary Schools: A Systematic Analysis

Implementing Augmented Reality (AR) Textbooks in Primary Sch...

引用

2023 International Conference for Technological engineering and its Applications in Sustainable Development, ICTEASD 2023

作者： Ramli, Noraini Binti Bin Hashim, Mohd Ekram Alhafis Wan Mustafa, Wan Azani Md Ghani, Miharaini Almusawi, Muntather Hanafi, Hafizul Fahri Sultan Idris Educational University Faculty of Art Sustainability & Creative Industry Multimedia Creative Departmet Perak Malaysia University Malaysia Perlis Faculty of Electrical Engineering & Technology Perlis Malaysia University Sains Malaysia School of Communication Pulau Pinang Malaysia The Islamic University Faculty of Engineering Najaf Iraq Sultan Idris Educational University Faculty of Computing and Meta-Technology Department of Computer Science and Digital Technology Perak Malaysia

ISBN: (纸本)9798350336474

This evaluation examined 28 major papers to see if textbooks and augmented reality may be used as instructional technologies. This study, "Implementing Augmented Reality (AR) Textbooks in Elementary Schools: A Systematic Analysis,"examined current status of AR integration, perceived benefits, and impact on the learning environment. The "What is the current status of augmented reality (AR) integration in elementary schools?"review seeks to answer. Some schools have adopted AR textbooks, while others are just starting. Theme AR Integration Studies Today Some schools have adopted AR textbooks, while others are just starting. AR textbooks adapt to varied learning methods and match each student's needs to promote dynamic and engaging learning. Second, perceived benefits emphasise how they boost student motivation, understanding of complex concepts, and passion for learning. The study reveals how augmented reality (AR) textbooks can simplify and deepen learning on hard topics. Impact on the Learning Environment examines how AR textbooks improve classroom engagement, interactivity, and dynamicness. Augmented reality creates immersive and dynamic learning environments, making textbooks more valuable. Synthesising findings illuminates the contributions of various components of augmented reality (AR) textbooks and future research and implementation approaches. This The synthesis of findings shows how augmented reality (AR) textbooks can improve educational technology through the current status of AR integration, perceived benefits, and impact on the learning environment. This study teaches educators, researchers, and policymakers about the potential of textbook material and augmented reality to improve education by answering research questions. © 2023 IEEE.

关键词： Textbooks

来源：评论

学校读者我要写书评

暂无评论

Hyperspectral Image Denoising Using Low-Rank and Sparse Model Based Deep Unrolling

Hyperspectral Image Denoising Using Low-Rank and Sparse Mode...

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Bin Zhao Magnus O. Ulfarsson Jakob Sigurdsson School of Information Science and Engineering Shandong Agricultural University Taian China Faculty of Electrical and Computer Engineering University of Iceland Reykjavik Iceland

Hyperspectral image (HSI) denoising methods that are implemented using deep learning frameworks rarely consider the intrinsic characteristics of HSIs, and often lack both physical interpretability, and generalization. In this paper, a low-rank and sparse model-based unrolled network for HSI de-noising, termed LRS-Net, is proposed. The method unrolls a model-based denoising method into a deep-unrolled network. The network is much faster than the previous method and is also able to automatically select the tuning parameters. The method inherits the advantages of model-based methods, i.e., physical interpretability and generalization, and also advantages from deep learning based methods, i.e., computational efficiency and data-based learning capabilities. Using both simulated and real HSIs it is shown the proposed method can outperform other comparative methods, both in quantitative and visual assessments.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Estimating the AGV load and a battery lifetime based on the current measurement and random forest application

Estimating the AGV load and a battery lifetime based on the ...

引用

IEEE International Conference on Big Data

作者： Krzysztof Hanzel Damian Grzechca Adam Ziebinski Lukas Chruszczyk Artur Janus Department of Telecommunications and Teleinformatics Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice Poland Department of Electronics Electrical Engineering and Microelectronics Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice Poland Department of Distributed Systems and Informatics Devices Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice Poland Student of Electrical Engineering Faculty of Electrical Engineering Silesian University of Technology Gliwice Poland

The paper describes the energy consumption from the battery based on the current measurements for various cases, i.e., speed (PWL adjustment) and loads. The main purpose of the research is to have additional and reliable information about power consumption and battery life estimation for autonomous guided vehicles (AGV). The authors propose a two-step algorithm. In the first step, a linear classifier was proposed. Then, the KNN classifier was tested; however, it did not give satisfactory results, so it was finally decided to use the random forest to estimate the load and PWL. The time domain current measurement is evaluated, and the beforementioned algorithms process the selected statistical measures. It has been proven that a two-step algorithm allows for achieving high accuracy. Based on the current observation, the paper is a good starting point for further investigation of the AGV because it is usually implemented in the AGV – so it does not require additional hardware. Moreover, it can lead to better energy management and increase battery lifetime.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Resource-Rational Process-Level Account of Violation of Stochastic Dominance 44

A Resource-Rational Process-Level Account of Violation of St...

引用

44th Annual Meeting of the Cognitive science Society: Cognitive Diversity, CogSci 2022

作者： Xia, Feng Nobandegani, Ardavan S. Shultz, Thomas R. Bhui, Rahul Department of Mathematics & Statistics McGill University Canada Department of Electrical & Computer Engineering McGill University Canada School of Computer Science McGill University Canada Department of Psychology McGill University Canada Sloan School of Management MIT United States

Dominance is widely considered a pillar of rational choice and has played a major role in the history of theorizing and developing models of human decision-making. A wealth of empirical evidence reveals that humans' violation of dominance is both substantial and systematic. But could violation of dominance be given a rational basis? Specifically, could it be understood in terms of the optimal use of limited cognitive resources? In this work, we present the first resource-rational account of stochastic dominance, the most empirically studied version of dominance. Concretely, we show that a resource-rational process model, sample-based expected utility (SbEU), provides a unified account of a broad range of empirical results on violation of stochastic dominance. We discuss the implications of our work for risky decision-making, and more broadly, human rationality. © 2022 The Author(s). This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY)

关键词： Decision making

来源：评论

学校读者我要写书评

暂无评论

Unleashing the potential of morphotropic phase boundary based hybrid triboelectric–piezoelectric nanogenerator

引用

Journal of Materiomics 2024年第4期10卷 792-802页

作者： Sugato Hajra Aneeta Manjari Padhan Basanta Kumar Panigrahi Phakkhananan Pakawanit Zvonko Jagličić Naratip Vittayakorn Yogendra Kumar Mishra Sanghoon Lee Hoe Joon Kim Department of Robotics and Mechatronics Engineering Daegu Gyeongbuk Institute of Science and TechnologyDaegu42988Republic of Korea Department of Electrical Engineering Siksha O Anusandhan UniversityBhubaneswar751030India Synchrotron Research and Applications Division Synchrotron Light Research InstituteNakhon Ratchasima30000Thailand Institute of Mathematics Physics and Mechanics&Faculty of Civil and Geodetic EngineeringUniversity of LjubljanaJadranska191000LjubljanaSlovenia Advanced Materials Research Unit Department of ChemistrySchool of ScienceKing Mongkut's Institute of Technology LadkrabangBangkok10520Thailand Mads Clausen Institute NanoSYDUniversity of Southern DenmarkAlsion 26400SønderborgDenmark Robotics and Mechatronics Research Center Daegu Gyeongbuk Institute of Science and Technology(DGIST)Daegu42988Republic of Korea

Morphotropic phase boundary(MPB)-based ceramics are excellent for energy harvesting due to their enhanced physical properties at phase boundaries,broad operating temperature range,and ability to customize properties for efficient conversion of mechanical energy into electrical *** this work,Bi_(1–x)Na_(x)Fe_(1–x)Nb_(x)O_(3)(x=0.20,0.30,0.32 and 0.40,BNFNO abbreviation)based ceramics were synthesized using a solid-state route and blended with Polydimethylsiloxane(PDMS)to achieve flexible *** material characterization and energy harvesting were performed by designing a hybrid piezoelectric(PENG)-triboelectric(TENG)*** voltage and current of PENG,TENG,and hybrid bearing same device area(2 cm×2 cm)were recorded as 11 V/0.3μA;60 V/0.7μA;110 V/2.2μ*** strategies for enhancing the output performance of the hybrid device were evaluated,such as increased surface area(creating micro-roughness and porous morphology)and increasing electrode size and multi-layer hybrid device *** self-powered acceleration monitoring was demonstrated using the hybrid ***,the low-frequency-based wave energy is converted into electrical energy,confirming the usage of hybrid PENG-TENG devices as a base for battery-free sensors and blue energy harvesting.

关键词： Lead-free Acceleration Wave energy Morphotropic

来源：评论

学校读者我要写书评

暂无评论

Revisiting Kernel Attention with Correlated Gaussian Process Representation

arXiv

引用

arXiv 2025年

作者： Bui, Long Minh Huu, Tho Tran Dinh, Duy Nguyen, Tan Minh Hoang, Trong Nghia FPT Software AI Center Viet Nam Department of Mathematics National University of Singapore Singapore School of Electrical Engineering and Computer Science Washington State University United States

Transformers have increasingly become the de facto method to model sequential data with state-of-the-art performance. Due to its widespread use, being able to estimate and calibrate its modeling uncertainty is important to understand and design robust transformer models. To achieve this, previous works have used Gaussian processes (GPs) to perform uncertainty calibration for the attention units of transformers and attained notable successes. However, such approaches have to confine the transformers to the space of symmetric attention to ensure the necessary symmetric requirement of their GP’s kernel specification, which reduces the representation capacity of the model. To mitigate this restriction, we propose the Correlated Gaussian Process Transformer (CGPT), a new class of transformers whose self-attention units are modeled as cross-covariance between two correlated GPs (CGPs). This allows asymmetries in attention and can enhance the representation capacity of GP-based transformers. We also derive a sparse approximation for CGP to make it scale better. Our empirical studies show that both CGP-based and sparse CGP-based transformers achieve better performance than state-of-the-art GP-based transformers on a variety of benchmark tasks. The code for our experiments is available at https://***/MinhLong210/CGP-Transformers. Copyright © 2025, The Authors. All rights reserved.

关键词： Global positioning system

来源：评论

学校读者我要写书评

暂无评论

Population-Input Memristor Circuit Based on Matrix-Friendly Genetic Algorithm

IEEE Transactions on Circuits and Systems for Artificial Int...

引用

IEEE Transactions on Circuits and Systems for Artificial Intelligence 2025年第2期2卷 174-182页

作者： Hao Chen Quan Shi Ling Chen Tingwen Huang Chuandong Li College of Electronic and Information Engineering Southwest University Chongqing China Westa College Southwest University Chongqing China School of Electrical and Electronic Engineering Nanyang Technological University Singapore Faculty of Computer Science and Control Engineering Shenzhen University of Advanced Technology Shenzhen China

This paper presents the design and implementation of a novel matrix-friendly genetic algorithm (MGA) based population input memristor circuit. Selection, crossover and mutation operations can be efficiently implemented in MGA by utilizing the unique properties of memristors. The proposed circuit performs well in solving binary nonconvex function optimization problems. Through extensive simulations and comparisons with classical optimization algorithms, our method improves about 4.24% on average in exploring the optimal fitness value, which reflects the advantages of the method in finding the optimal solution. In addition, the existence of its function to visualize the image of a one-dimensional function is also found during the experimental process. The proposed circuit has good scalability and flexibility, demonstrating its potential for a wide range of applications in complex optimization tasks.

关键词： Memristors Circuits Genetic algorithms Biological cells Optimization Genetics Parallel processing Logic gates Education Artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

A multi-task self-supervised approach for mass detection in automated breast ultrasound using double attention recurrent residual U-Net

引用

computers in Biology and Medicine 2025年 188卷 109829-109829页

作者： MohammadiNasab, Poorya Khakbaz, Atousa Behnam, Hamid Kozegar, Ehsan Soryani, Mohsen School of Computer Engineering Iran University of Science and Technology Tehran Iran Department of Medicine Danube Private University Krems Austria School of Electrical Engineering Iran University of Science and Technology Tehran Iran Faculty of Technology and Engineering-East of Guilan University of Guilan Guilan Rudsar Iran

Breast cancer is the most common and lethal cancer among women worldwide. Early detection using medical imaging technologies can significantly improve treatment outcomes. Automated breast ultrasound, known as ABUS, offers more advantages compared to traditional mammography and has recently gained considerable attention. However, reviewing hundreds of ABUS slices imposes a high workload on radiologists, increasing review time and potentially leading to diagnostic errors. Consequently, there is a strong need for efficient computer-aided detection, CADe, systems. In recent years, researchers have proposed deep learning-based CADe systems to enhance mass detection accuracy. However, these methods are highly dependent on the number of training samples and often struggle to balance detection accuracy with the false positive rate. To reduce the workload for radiologists and achieve high detection sensitivities with low false positive rates, this study introduces a novel CADe system based on a self-supervised framework that leverages unannotated ABUS datasets to improve detection results. The proposed framework is integrated into an innovative 3-D convolutional neural network called DATTR2U-Net, which employs a multi-task learning approach to simultaneously train inpainting and denoising pretext tasks. A fully convolutional network is then attached to the DATTR2U-Net for the detection task. The proposed method is validated on the TDSCABUS public dataset, demonstrating promising detection results with a recall of 0.7963 and a false positive rate of 5.67 per volume that signifies its potential to improve detection accuracy while reducing workload for radiologists. The code is available at: ***/Pooryamn/SSL_ABUS. © 2025

关键词： Self-supervised learning

来源：评论

学校读者我要写书评

暂无评论

Evolving Restricted Boltzmann Machine-Kohonen Network for Online Clustering

arXiv

引用

arXiv 2024年

作者： Senthilnath, J. Bhattiprolu, Adithya Singh, Ankur Zhou, Bangjian Wu, Min Benediktsson, Jón Atli Li, Xiaoli Singapore138632 Singapore The Department of Electrical & Electronics Engineering Birla Institute of Technology and Science Pilani333031 India The Faculty of Electrical and Computer Engineering University of Iceland Reykjavik107 Iceland School of Computer Science and Engineering Nanyang Technological University Singapore and A*STAR Centre for Frontier AI Research Singapore138632 Singapore

A novel online clustering algorithm is presented where an Evolving Restricted Boltzmann Machine (ERBM) is embedded with a Kohonen Network called ERBM-KNet. The proposed ERBM-KNet efficiently handles streaming data in a single-pass mode using the ERBM, employing a bias-variance strategy for neuron growing and pruning, as well as online clustering based on a cluster update strategy for cluster prediction and cluster center update using KNet. Initially, ERBM evolves its architecture while processing unlabeled image data, effectively disentangling the data distribution in the latent space. Subsequently, the KNet utilizes the feature extracted from ERBM to predict the number of clusters and updates the cluster centers. By overcoming the common challenges associated with clustering algorithms, such as prior initialization of the number of clusters and subpar clustering accuracy, the proposed ERBM-KNet offers significant improvements. Extensive experimental evaluations on four benchmarks and one industry dataset demonstrate the superiority of ERBM-KNet compared to state-of-the-art approaches. Copyright © 2024, The Authors. All rights reserved.

关键词： Clustering algorithms

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：