检索结果-内蒙古大学图书馆

Gen Z Oriented engineering Education in the 'Industry 4.0' Age 64

Gen Z Oriented Engineering Education in the 'Industry 4.0' A...

64th IEEE Annual International Scientific Conference on power and electrical engineering of Riga Technical University, RTUCON 2023

作者： Raud, Zoja Vodovozov, Valery Petlenkov, Eduard Tallinn University of Technology Department of Electrical Power Engineering and Mechatronics Tallinn Estonia Tallinn University of Technology Department of Computer Systems Tallinn Estonia

ISBN: (纸本)9798350317732

The study analyses and offers the active blended learning methodology oriented on the students belonging to the so-called Generation Z (Gen Z). The goal is to support achieving the creativity, innovation, and other targets stated by the 'Industry 4.0' age. Two disciplines are examined, namely Robotics at the bachelor's level and Advanced Robotics at the master's level for the local, Erasmus+, EuroTeQ, Asian, and African students. The results represent the specificity of active blended learning in view of the formative assessment, poll-supported lectures, and online quizzing. The main strengths of the Gen Z representatives are most strongly manifested in computer forms of training, especially in exercises and labs, where practical skills are acquired. © 2023 IEEE.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

Edge-Driven Industrial Computing power Networks: Digital Twin-Empowered Service Provisioning by Hybrid Soft Actor-Critic

引用

IEEE Transactions on Vehicular Technology 2025年第5期74卷 8095-8109页

作者： Zhang, Long Song, Deng-Ao Zhang, Hongliang Tian, Ni Zhuang, Zirui Niyato, Dusit Han, Zhu Hebei University of Engineering School of Information and Electrical Engineering Handan056038 China Peking University State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Beijing100871 China Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology Beijing100876 China Nanyang Technological University College of Computing and Data Science 639798 Singapore University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States Kyung Hee University Department of Computer Science and Engineering Seoul446-701 Korea Republic of

With the proliferation of data-intensive industrial applications, the collaboration of computing powers among standalone edge servers is vital to provision such services for smart devices. In this paper, we propose an edge-driven industrial computing power network (CPN) by orchestrating the computing and network resources of edge servers through the centralized resource scheduling and decentralized task computing. However, efficient task offloading and collaborative processing is challenging, which requires higher degrees of network automation and intelligence. Therefore, we incorporate digital twins (DTs) into the edge-driven CPN architecture, where the DTs are created as the digital replicas to assist both the computation offloading and collaborative processing. A joint optimization problem of the computing power assignment, service association, task partition, and transmit power control is formulated for maximizing the system average weighted utility. Due to the temporal-spatial variability of tasks and the resulted dynamic environment, we transform the original problem as a Markov decision process aiming at maximizing the long-term average weighted utility. To efficiently handle the high-dimensional discrete-continuous action space, a hybrid soft actor-critic based deep reinforcement learning algorithm is developed for optimizing the joint design. Simulation results validate the superiority of our proposed algorithm over the benchmarks, showing the significant gains obtained by integrating DTs into the edge-driven CPN. © 1967-2012 IEEE.

关键词： Markov processes

来源：评论

学校读者我要写书评

暂无评论

Real-time binaural speech reproduction with deep neural networks and dynamic head tracking 156

Real-time binaural speech reproduction with deep neural netw...

引用

AES Madrid 2024: 156th Audio engineering Society Convention

作者： Papavasileiou, Ioannis Thoidis, Iordanis Sevastiadis, Christos Vryzas, Nikolaos Papanikolaou, George Laboratory of Electroacoustics and TV Systems School of Electrical and Computer Engineering Faculty of Engineering Aristotle University of Thessaloniki Thessaloniki Greece Laboratory of Electronic Media Department of Journalism and Mass Media Aristotle University of Thessaloniki Thessaloniki Greece

This study examines the efficacy of a deep learning-based binaural speech reproduction system via headphones that integrates real-time head tracking to simulate a stable speech source in a virtual environment. We developed a binaural speech reproduction system that operates in real time using a custom head-tracking device based on the Arduino platform and a pre-trained neural network model for binaural speech synthesis. The system dynamically adapts audio output based on the head orientation of the listener, operating with an overall latency of 70 ms on standard computing hardware. We conducted a subjective speech localization task with 15 young, normal-hearing participants. Initial results showed a 40% accuracy in localizing a static speech source, which significantly improved with dynamic head movements. Participants reported minimal dizziness and distortion, indicating good tolerability and sound quality. Despite some limitations, such as non-personalized settings and perceivable latency, the findings demonstrate the potential of deep learning approaches to enhance realism in virtual auditory environments. Further research is needed to refine these technologies for broader applications in immersive audio settings. © AES Madrid 2024: 156th Audio engineering Society Convention. All rights reserved.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Recent Advances in Parity-Time Symmetry-Enabled Electromagnetic Sensors

引用

Progress In Electromagnetics Research B 2024年 105卷 107-121页

作者： Yang, Minye Ye, Zhilu Chen, Pai-Yen Erricolo, Danilo Department of Electrical and Computer Engineering University of Illinois Chicago ChicagoIL60607 United States State Key Laboratory for Manufacturing Systems Engineering Electronic Materials Research Laboratory Key Laboratory of the Ministry of Education School of Electronic Science and Engineering Xi’an Jiaotong University Shaanxi Xi’an710049 China State Key Laboratory for Manufacturing Systems Engineering The Key Laboratory of Biomedical Information Engineering of Ministry of Education Center for Mitochondrial Biology and Medicine School of Life Science and Technology International Joint Laboratory for Micro/Nano Manufacturing and Measurement Technology Xi’an Key Laboratory for Biomedical Testing and High-end Equipment Xi’an Jiaotong University Shaanxi Xi’an710049 China

Parity-time (PT) reversal symmetry, as a representative example in the field of non-Hermitian physics, has attracted widespread research interest in the past few years due to its extraordinary wave dynamics. PT symmetry enables unique spectral singularities including the exceptional point (EP) degeneracy where two or more eigenvalues and eigenvectors coalesce, as well as the coherent perfect absorber-laser (CPAL) point where laser and its time-reversal counterpart (i.e., coherent perfect absorber) can coexist at the same frequency. These singular points not only give rise to new physical phenomena but also provide new plausibility for building the next-generation sensors and detectors with unprecedented sensitivity. To date, investigations into EPs and CPAL points have unveiled their great potential in various sensing scenarios across a broad spectral range, spanning optics, photonics, electronics, and acoustics. In this review article, we will discuss ongoing developments of EP- and CPAL-based sensors composed of PT-synthetic structures and offer a glimpse into the future research directions in this emerging field. © (2024), (Electromagnetics Academy). All rights reserved.

关键词： Eigenvalues and eigenfunctions

来源：评论

学校读者我要写书评

暂无评论

A Transformer Design with PCB Litz Wire Concept for Solid State Transformer

A Transformer Design with PCB Litz Wire Concept for Solid St...

引用

2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023

作者： Li, Zheqing Jin, Feng Lou, Xin Hsieh, Yi-Hsun Li, Qiang Lee, Fred C. Virginia Polytechnic and State University Center for Power Electronic Systems Bradley Department of Electrical and Computer Engineering BlacksburgVA24061 United States

ISBN: (纸本)9798350316445

Litz wire is known for its ability to minimize winding losses in high-frequency applications. However, its implementation in PCB winding poses significant challenges. This paper presents a novel PCB Litz wire concept aimed at minimizing winding loss in high-frequency applications, specifically in the design of a solid-state transformer using PCB-winding-based technology. The proposed PCB Litz wire is designed in a circular winding configuration with curved strands, optimizing its performance. The construction method and the turn-to-turn connection are demonstrated. Factors affecting the resistance of the PCB Litz wire, including the number of strands, their width, and section, are discussed. The results show that compared to traditional PCB winding, the PCB Litz wire achieves a 30% reduction in winding loss and significantly improves current distribution, leading to enhanced thermal performance. To validate the concept's effectiveness, a prototype of a 1.6/1.05kV, 190kHz, 30-kW CLLC converter is built, demonstrating an impressive 98.8% efficiency. © 2023 IEEE.

关键词： PCB Litz PCB winding Solid-state transformer (SST) Transformer design

来源：评论

学校读者我要写书评

暂无评论

Enhancing Energy Management System for a Hybrid Wind Solar Battery Based Standalone Microgrid

Enhancing Energy Management System for a Hybrid Wind Solar B...

引用

2023 IEEE International Conference on Environment and electrical engineering and 2023 IEEE Industrial and Commercial power systems Europe, EEEIC / I and CPS Europe 2023

作者： Aghmadi, Ahmed Hussein, Hossam Mohammed, Osama A. Florida International University Energy Systems Research Laboratory Department of Electrical and Computer Engineering MiamiFL33174 United States

ISBN: (纸本)9798350347432

This paper introduces a highly efficient energy management system for a microgrid that combines PV system, wind turbine, and battery. The study presents an effective energy management system specifically designed for a small-scale hybrid microgrid, focusing on the development of solar and wind energy conversion systems and battery storage systems. power electronic converters and control algorithms are implemented to evaluate the microgrid's operation. The energy management system plays a crucial role in maintaining power balance amidst varying renewable energy generation and load demand conditions. The microgrid is a testing platform to evaluate control algorithms, energy management systems, and various test scenarios. It provides a controlled environment for assessing the performance and efficiency of these systems. The efficient energy management system comprises photovoltaic (PV) modules, wind turbines, and batteries. The proposed strategy effectively manages the switching between the PV panel and the battery storage system while prioritizing power generation from the wind turbine. The efficacy and success of this strategy in microgrid control under various operational circumstances are demonstrated through MATLAB simulation results. © 2023 IEEE.

关键词： Wind power

来源：评论

学校读者我要写书评

暂无评论

Enhancing Solar Radiation Forecasting with Hybrid Ensemble Empirical Mode Decomposition and Machine Learning Techniques

Enhancing Solar Radiation Forecasting with Hybrid Ensemble E...

引用

2023 IEEE International Conference on Environment and electrical engineering and 2023 IEEE Industrial and Commercial power systems Europe, EEEIC / I and CPS Europe 2023

作者： Aghmadi, Ahmed Mohammed, Osama Florida International University Energy Systems Research Laboratory Department of Electrical and Computer Engineering MiamiFL33174 United States

ISBN: (纸本)9798350347432

The importance of short-term solar radiation forecasting for power system use and management cannot be overstated. However, Non-stationarity and unpredictability make accurate forecasting difficult. Time series approaches are suitable for forecasting stationary time series derived from a non-stationary sequence. Empirical Mode Decomposition (EMD) and Ensemble Empirical Mode Decomposition (EEMD) are time-domain decomposition methods used to separate the components of the original solar radiation time series that have distinct time1-scale characteristics. As a result, the components are forecasted using the Back Propagation Neural Network (BPNN) model, which is a simple and effective machine learning method. This paper presents a hybrid EMD/EEMD-BPNN model for predicting short-term solar irradiance. To identify unique data information at different time scales, EMD/EEMD first breaks up the solar radiation time series into several stationary or fundamental sub-series. The next step is to create BPNN models with specified parameters for each subsequence to forecast new ones. Finally, each subsequence's projected value is combined to generate the final forecast result. The accuracy of solar forecasts has greatly increased, especially when utilizing hybrid methods. Furthermore, using the proposed hybrid technique for multistep forecasting resulted in even more improvement. The basic BPNN model for 15 min time step achieves predicting with a root mean square error (RMSE) of roughly 416.04 W/m2 for 15min;however, this error decreases to 65.25 W/m2 with the EMD-Hybrid Model, and 32.86 W/m2 with the EEMD-Hybrid Model. In addition, the results of the skill score have proven clearly that EMD/EEMD-BPNN Model performs better compared to typical BPNN using several meteorological inputs © 2023 IEEE.

关键词： Empirical mode decomposition

来源：评论

学校读者我要写书评

暂无评论

Control of Pick-and-Place Robots with Reduced power Consumption 64

Control of Pick-and-Place Robots with Reduced Power Consumpt...

引用

64th IEEE Annual International Scientific Conference on power and electrical engineering of Riga Technical University, RTUCON 2023

作者： Vodovozov, Valery Raud, Zoja Petlenkov, Eduard Tallinn University of Technology Department of Electrical Power Engineering and Mechatronics Tallinn Estonia Tallinn University of Technology Department of Computer Systems Tallinn Estonia

ISBN: (纸本)9798350317732

In such industries as assembling, welding, packaging, quality control, loading, and wrapping, the specific robot operation is requested, which is to pick processing objects to a given area of the workspace and hold them there rather long time comparing with motion and positioning processes. The goal of the developed control approach is to minimise power consumed by the robot during the pick-and-place operation. The proposed and tested methodology is based on the mutual solution of the forward kinematics, inverse kinematics, and inverse statics problems of robotics. In this work, model development, simulation, and experimental stages are described. © 2023 IEEE.

关键词： Inverse problems

来源：评论

学校读者我要写书评

暂无评论

Open-Switches Fault Diagnosis and Fault Tolerant Direct Torque Control of Voltage Source Inverter Fed Induction Motor 5th

Open-Switches Fault Diagnosis and Fault Tolerant Direct Torq...

引用

5th International Conference on electrical engineering and Control Applications, ICEECA 2022

作者： Boubou, Fouad Eddine Nedjai, Abd Elouahed Ammar, Abdelkarim Power and Control Engineering Department Institute of Electrical and Electronic Engineering University of M’hamed Bougara of Boumerdes Boumerdes35000 Algeria Signals and Systems Laboratory LSS Institute of Electrical and Electronic Engineering University of M’hamed Bougara of Boumerdes Boumerdes35000 Algeria

ISBN: (纸本)9789819700448

Fault diagnosis and fault tolerance are considered essential features in critical industrial applications in order to maintain the necessary levels of availability and dependability. The components that are most frequently affected by failures in closed-loop controlled power converters are semiconductors and sensors. This work focuses on fault tolerant direct torque control (DTC) of induction motor drive systems under inverter open-switch failure. This system detects and isolates the fault, and then ensures the system’s operation under the new conditions. The solution was accomplished using a new reduced switch converter. This system modifies the DTC switching table using available stator voltage vectors in two-phase mode with a Four Switch Three Phase Inverter (FSTPI) topology to maintain the performance of the motor as in the Six Switch Three Phase Inverter (SSTPI) mode. The effectiveness of the fault detection method and fault tolerant control algorithm have been investigated using MATLAB/Simulink software. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： MATLAB

来源：评论

学校读者我要写书评

暂无评论

Dynamic Pulsed Load Mitigation in PV-Battery-Supercapacitor systems: A Hybrid PI-NN Controller Approach

Dynamic Pulsed Load Mitigation in PV-Battery-Supercapacitor ...

引用

2023 IEEE Design Methodologies Conference, DMC 2023

作者： Aghmadi, Ahmed Ali, Ola Hussein, Hossam Mohammed, Osama A. Florida International University Energy Systems Research Laboratory Department of Electrical and Computer Engineering MiamiFL33174 United States

ISBN: (纸本)9798350315547

DC microgrids are becoming more and more popular, however there are still difficulties involving ongoing instability that are mostly caused by imbalances in energy supply and demand, particularly in situations with pulse load or variable pulse load patterns. Innovative solutions are required since these disruptive load dynamics significantly decrease the effectiveness of conventional PV-Battery control systems. conventional Proportional-Integral (PI) controllers, although widely employed, may encounter limitations when confronted with the unique challenges posed by specific load patterns, notably pulse load scenarios. These dynamic load profiles, characterized by rapid and unpredictable changes. The inherent non-linearity and variability in such load conditions can result in suboptimal control performance, potentially leading to voltage instability and transients within the microgrid. To overcome these issues and improve control performance, the introduction of Neural Network (NN) controllers promises to be a potential approach. NN controllers have a remarkable capacity to learn and adapt from data, making them particularly well-suited for situations characterized by non-linear and dynamic load behavior. In this study, a hybrid PI-NN (Proportional-Integral Neural Network) controller is introduced to reduce load effects, especially pulsed loads, in PV systems with batteries and supercapacitors. This method efficiently optimizes energy storage. For voltage control, it utilizes a PI system, which divides the reference current into low and high-frequency components for battery and supercapacitor control. For enhanced sensitivity and dynamic responsiveness, neural network control replaces conventional PIs. The performance of the hybrid PI-NN controller is evaluated in this work, with an emphasis on its potential to improve PV system efficiency in severe load circumstances. © 2023 IEEE.

关键词： Supercapacitor

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：