检索结果-内蒙古大学图书馆

IEEE Networking Letters 2023年第4期5卷 299-303页

作者： Zhou, Changshi Ansari, Nirwan New Jersey Institute of Technology Department of Electrical and Computer Engineering NewarkNJ07102 United States

Network data analytics function (NWDAF), introduced to provision data analytics and machine learning model training in the 5G core network, is expected to be an essential functional entity and play a significant role in the emerging AI-native 6G wireless network. However, refining the NWDAF architecture to support machine learning (ML) model sharing among multiple NWDAFs with distributed data sources and different privacy constraints remains a major challenge. To address this challenge, we propose a federated learning enabled NWDAF architecture with Partial Homomorphic Encryption to secure ML model sharing with privacy preserving. Simulation results demonstrate the feasibility of our proposed architecture. © 2019 IEEE.

关键词： Network architecture

来源：评论

学校读者我要写书评

暂无评论

Performance Comparison of Different Methods of Torque Ripple Reduction for Permanent Magnet-assisted Synchronous Reluctance Motor 3

Performance Comparison of Different Methods of Torque Ripple...

引用

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

作者： Amiri, Amir Hosein Abdollahi, Seyed Ehsan Hasanzadeh, Saeed Babol Noshirvani University of Technology Electrical and Computer Engineering Department Babol Iran Qom University of Technology Electrical and Computer Engineering Department Qom Iran

ISBN: (纸本)9798350393743

In recent years, synchronous reluctance machines (SynRM) have been widely used in many different industrial applications because of their high efficiency, fast dynamic response, robustness, and lower production costs, making them suitable for traction applications. However, their usage is limited due to their low power factor and high torque ripple. To improve the power factor Ferrite magnets are commonly used in their rotor (PM-assisted SynRM). Adding these Ferrite magnets increases the torque ripple as well. To enhance the torque ripple many different methods are proposed such as skewing, employing different winding configurations, and rotor topology modifications. Machine designers should select a suitable technique as each method has limitations. This paper is aiming at analyzing the effects of these three different methods on the performance of the machine. A four-pole 1.5 kw SynRM is designed and the magnets are placed in the barriers of the rotor while keeping the insulation ratio constant then the performance of different methods is evaluated and compared. First, the rotor is skewed, and then a short-pitch winding is used for the stator. Finally, a new design for barrier ends is proposed, and their effect on the torque profile is independently evaluated. The simulations are done in 2D FEM and the results are evaluated and discussed. © 2023 IEEE.

关键词： Topology

来源：评论

学校读者我要写书评

暂无评论

Efficient Framework with Sparse Acquisition in CMOS Image Sensors for Low-Power Edge Devices 10

Efficient Framework with Sparse Acquisition in CMOS Image Se...

引用

10th IEEE International Symposium on Smart Electronic Systems, iSES 2024

作者： Kisku, Wilfred Kaur, Amandeep Mishra, Deepak Indian Institute of Technology Department of Electrical Engineering Jodhpur India Indian Institute of Technology Department of Computer Science and Engineering Jodhpur India

ISBN: (纸本)9798331533229

Memory bandwidth and power consumption is of utmost importance in the design of low power edge devices. This makes it essential to conserve power both at the sensor node and the computational unit. Our paper proposes a system design methodology to save power by acquiring compressed data at the CMOS Image Sensor (CIS) and making the Convolutional Neural Network (CNN) models lightweight for edge applications. A detailed study highlights the effect of sensor directed sparsity at the CIS, and its effect on CNN models such as VGG-16, MobileNet, ResNet50, EfficientNet, and ResNext models. It provides empirical evidence that the performance is mostly maintained even after pruning and quantization of considered models. The imagenette dataset is used to curate the data with the proposed acquisition pipeline that introduces data sparsity, and the experimental results provide evidence that the proposed pipeline performs at par with conventional CIS acquisition mode. For example, the analysis of VGG-16 model for a sparsity threshold level of 0.2 shows compression of × 7.6, × 16, and × 61 using only pruning (P), only quantization (Q), and with both pruning+quantization (P+Q), respectively. It is also observed that the proposed acquisition pipeline can achieve significant parameter reduction through pruning for model compression, comparable to convectional pipeline. © 2024 IEEE.

关键词： CMOS integrated circuits

来源：评论

学校读者我要写书评

暂无评论

Analysis Of Load Composition Impact On the Bankability Of Rural Mini-Grids

Analysis Of Load Composition Impact On the Bankability Of Ru...

引用

2024 IEEE PES/IAS PowerAfrica, PowerAfrica 2024

作者： Gelchu, Milky Ali Ehnberg, Jimmy School of Electrical and Computer Engineering Addis Ababa University Addis Ababa Ethiopia Department of Electrical Engineering Chalmers University of Technology Gothenburg Sweden

ISBN: (纸本)9798350389388

To provide electricity to rural areas in sub-Saharan Africa that currently lack access, mini-grids have been considered a solution. However, the deployment of mini-grids is challenging in rural areas of sub-Saharan Africa, due to the low demand, discounted tariffs set by the public power authority, and the limited paying capacity of rural populations. As a result, many mini-grid proj ects in these areas heavily rely on financial aid from donors or government subsidies. While studies have explored ways to improve the bankability of installed mini-grids by incorporating productive uses, each with different load characteristics, there has been limited research on fixed-capacity mini-grids. This study aims to investigate how future load compositions can impact the bankability of rural mini-grids with a fixed capacity. The results indicate that the future load composition, specifically the integration of productive uses such as small bars and millers with the existing household load, can enhance the bankability of the mini-grid. © 2024 IEEE.

关键词： bankability load Composition mini-grid

来源：评论

学校读者我要写书评

暂无评论

Machine visual perception from sim-to-real transfer learning for autonomous docking maneuvers

引用

Neural Computing and Applications 2024年第4期37卷 2285-2312页

作者： Worth, Derek Choate, Jeffrey Raettig, Ryan Nykl, Scott Taylor, Clark Department of Electrical and Computer Engineering Air Force Institute of Technology 2950 Hobson Way Wright-Patterson AFBOH45433 United States

This paper presents a comprehensive approach to enhancing autonomous docking maneuvers through machine visual perception and sim-to-real transfer learning. By leveraging relative vectoring techniques, we aim to replicate the human ability to execute precise docking operations. Our study focuses on autonomous aerial refueling as a use case, demonstrating significant advancements in relative navigation and object detection. We introduce a novel method for aligning digital twins using fiducial targets and motion capture data, which facilitates accurate pose estimation from real-world imagery. Additionally, we develop cost-efficient annotation automation techniques for generating high-quality You Only Look Once training data. Experimental results indicate that our transfer learning methodologies enable accurate and reliable relative vectoring in real-world conditions, achieving error margins of less than 3 cm at contact (when vehicles are approximately 4 m from the camera) and maintaining performance at over 56 fps. The research findings underscore the potential of augmented reality and scene augmentation in improving model generalization and performance, bridging the gap between simulation and real-world applications. This work lays the groundwork for deploying autonomous docking systems in complex and dynamic environments, minimizing human intervention and enhancing operational efficiency. © This is a U.S. Government work and not under copyright protection in the US;foreign copyright protection may apply 2024.

关键词： Augmented reality

来源：评论

学校读者我要写书评

暂无评论

Operation of the Step-Up/Down Bidirectional Partial Power Converter Near Zero Series Voltage 17

Operation of the Step-Up/Down Bidirectional Partial Power Co...

引用

17th IEEE International Conference on Compatibility, Power Electronics and Power engineering, CPE-POWERENG 2023

作者： Hassanpour, Naser Chub, Andrii Blinov, Andrei Vinnikov, Dmitri Tallinn University of Technology Departments of Electrical Power Engineering and Mechatronics Tallinn Estonia

ISBN: (纸本)9798350300048

The advantages of step-up/down series partial power converters (S-PPCs) are comprehensively addressed in the literature. However, their functionality at the critical point of equal port voltages is neglected. This paper analyzes a bi-directional step-up/down S-PPC to confirm its correct operation at this critical point. This S-PPC contains a four-quadrant DC-DC stage. Two modulation strategies are applied to the converter depending on the power flow direction. The phase shift modulation (PSM) regulates the current and voltage in the buck mode of the DC-DC stage. The reverse power flow control can extend the boost function of the DC-DC stage in the S-PPC when it works in the second and fourth quadrants. The series port voltage is decreased to almost zero to investigate the functionality of the S-PPC in all modes. The experimental prototype is tested under 5A current and 350V port voltage and the results confirm the correctness of the theoretical analysis. © 2023 IEEE.

关键词： Electric load flow

来源：评论

学校读者我要写书评

暂无评论

An information-theoretic lower bound in time-uniform estimation 37

An information-theoretic lower bound in time-uniform estimat...

引用

37th Annual Conference on Learning Theory, COLT 2024

作者： Duchi, John Haque, Saminul Departments of Statistics and Electrical Engineering Stanford University United States Department of Computer Science Stanford University United States

We present an information-theoretic lower bound for the problem of parameter estimation with time-uniform coverage guarantees. Via a new a reduction to sequential testing, we obtain stronger lower bounds that capture the hardness of the time-uniform setting. In the case of location model estimation, logistic regression, and exponential family models, our Ω(√n-1 log log n) lower bound is sharp to within constant factors in typical settings. © 2024 J. Duchi & S. Haque.

关键词： Logistic regression

来源：评论

学校读者我要写书评

暂无评论

Large Language Models (LLMs) Assisted Wireless Network Deployment in Urban Settings 100

Large Language Models (LLMs) Assisted Wireless Network Deplo...

引用

100th IEEE Vehicular technology Conference, VTC 2024-Fall

作者： Sevim, Nurullah Ibrahim, Mostafa Ekin, Sabit Texas A&m University Electrical and Computer Engineering College StationTX United States Texas A&m University Engineering Technology and Electrical and Computer Engineering College StationTX United States

ISBN: (纸本)9798331517786

The advent of Large Language Models (LLMs) has revolutionized language understanding and human-like text generation, drawing interest from many other fields with this question in mind: What else are the LLMs capable of? Despite their widespread adoption, ongoing research continues to explore new ways to integrate LLMs into diverse *** paper explores new techniques to harness the power of LLMs for 6G (6th Generation) wireless communication technologies, a domain where automation and intelligent systems are pivotal. The inherent adaptability of LLMs to domain-specific tasks positions them as prime candidates for enhancing wireless systems in the 6G *** introduce a novel Reinforcement Learning (RL) based framework that leverages LLMs for network deployment in wireless communications. Our approach involves training an RL agent, utilizing LLMs as its core, in an urban setting to maximize coverage. The agent's objective is to navigate the complexities of urban environments and identify the network parameters for optimal area coverage. Additionally, we integrate LLMs with Convolutional Neural Networks (CNNs) to capitalize on their strengths while mitigating their limitations. The Deep Deterministic Policy Gradient (DDPG) algorithm is employed for training purposes. The results suggest that LLM-assisted models can outperform CNN-based models in some cases while performing at least as well in others. © 2024 IEEE.

关键词： Intelligent systems

来源：评论

学校读者我要写书评

暂无评论

Short- and Medium-Term electrical Load Forecasting in Bangladesh Using Machine Learning Approaches

Short- and Medium-Term Electrical Load Forecasting in Bangla...

引用

2024 International Conference on Advances in Computing, Communication, electrical, and Smart Systems, iCACCESS 2024

作者： Cheragee, Sheikh Hasib Pall, Shuvo Chandra Kanchan, Muntasir Hasan Islam, Md. Samiul Tarek, Muhammad Masud Joy, Shoriful Huq Rahman, Md Toufiqur Bangladesh University of Engineering and Technology Electrical and Electronic Engineering Dhaka Bangladesh State University of Bangladesh Computer Science and Engineering Dhaka Bangladesh University of Rajshahi Electrical and Electronic Engineering Rajshahi Bangladesh

ISBN: (纸本)9798350350289

Planning and managing a power grid relies heavily on accurate predictions of future load. Operational choices involving resource utilization, infrastructural management, implementation schedule planning, investment plans, and maximizing power use while minimizing waste due to under or over-generation all rely on load prediction. In this study, it is utilized three different machine learning algorithms for medium- and short-term load forecasting, namely K-Nearest Neighbors (KNN) based Regression, Random Forest (RF) based regression, and Decision Tree (DT) Regression, to see how well these methods work on half-hourly historical electricity load data from the Bangladesh Power system (BPS) network, which can be found on the Power Grid Company of Bangladesh (PGCB) website and was downloaded between January 2021 and December 2022. To determine the most appropriate method for load forecasting of BPS, a comparison is made between the three approaches concerning the accuracy, mean absolute percentage error (MAPE), root means squared error (RMSE), and mean squared error (MSE). According to the findings, the RF model is superior to the others in making short- and medium-term forecasts due to its greater accuracy, minimal MSE, RMSE, and MAPE. © 2024 IEEE.

关键词： Decision trees

来源：评论

学校读者我要写书评

暂无评论

Image-based Plant Diseases Detection using Deep Learning

引用

Materials Today: Proceedings 2023年 80卷 3500-3506页

作者： Panchal, Adesh V. Patel, Subhash Chandra Bagyalakshmi, K. Kumar, Pankaj Khan, Ihtiram Raza Soni, Mukesh Department of Computer Science & Engineering GEC Patan India School of Computer Science and Engineering VIT Bhopal University Sehore MP Bhopal India Electrical and Electronics Engineering SRI Ranganathar Institute of Engineering and Technology Coimbatore India Department of Computer Science & Engineering Institute of Engineering & Technology Uttar Pradesh Greater Noida India Jamia Hamdard Computer Science Department Delhi India Jagran Lakecity University Bhopal India

Agriculture plays a major role in developing countries like India, however the food security still remains a vital issue. Most of the crops get wasted due to lack of storage facility, transportation, and plant diseases. More than 15% of the crops get wasted in India due to diseases and hence it has become one of the major concern to be resolved. There is a need of automatic system that can identify these diseases and help farmers to take appropriate steps to get rid of crop loss. Farmers have followed the conventional method of identifying the plant disease with their naked eyes, and it not possible for all the farmers to identify these diseases the same way. With the advance in Artificial Intelligence, there is a need to incorporate the facilities of the computer vision in the field of agriculture. Deep Learning rich libraries and user as well as developer friendly environment to work with, all these qualities make Deep Learning as the favorable method to get started with this problem. In this paper we have used Deep Learning because of the advantages it offers to work with images especially in image classification to get improvised results. The methodology includes taking leaves of infected crops and label them as per the disease pattern. The images of infected leaves are processed pixel based operations are applied to improve the information from the image. As a next step feature extraction is done followed by image segmentation and at the last classification of crop diseases based on the patterns extracted from the diseased leaves. The CNN (Convolutional Neural Network) is used for the classification of diseases, for the demonstration purpose the public dataset is used consisting of around 87 K images (RGB type images) including healthy as well as diseased leaves. © 2021

关键词： Crops

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：