检索结果-内蒙古大学图书馆

EEG-Based Motion Intention Detection for Robotic Rehabilitation: Evaluating Classification and Regression Algorithms

引用

SN Computer Science 2024年第8期5卷 1057页

作者： Khan, Abdul Manan Khan, Fatima Dwivedi, Anshu Kumar Semwal, Vijay Bhaskar Martha, Sheshikala Bijalwan, Vishwanath Department of Aerospace Engineering University of Bristol Bristol United Kingdom Graduate School of Cancer Science and Policy National Cancer Center Ilsan South Korea School of Computer Science Engineering and Technology Bennett University Greater Noida India Department of CSE Maulana Azad National Institute of Technology Bhopal India School of Computer Science & amp Artificial Intelligence SR University Warangal Warangal India Department of Electrical and Electronics Engineering University of West London London United Kingdom

Rehabilitation robots have shown significant efficacy in restoring lost motor functions in stroke survivors by providing compliant assistance during rehabilitation tasks. However, accurately understanding the desired motion intention (DMI) of the subjects is a significant challenge in providing effective robotic assistance. This work aims to determine the desired motion intention (DMI) for compliant robotic assistance through the analysis of upper limb motions using electroencephalography (EEG) signals. A group of fifteen individuals who were in good health carried out six distinct exercises. These movements were categorized using decision trees, random forest, and deep learning algorithms. Using deep learning, we achieved the highest accuracy rates, reaching 82% for movement-to-movement classification and 90% for movement-to-rest classification. The random forest method achieved superior performance compared to the other algorithms in regression tests, with an accuracy rate of 83%. The results demonstrate the effectiveness of our proposed EEG-based classification and regression techniques in detecting DMI for robotic help in *** study was conducted with a small sample size, exclusively involving healthy subjects, which is a critical factor to consider. This may limit the generalizability of the results, particularly when populations with motor impairments are taken into account. However, the study offers valuable insights into the potential of the EEG-based models for real-time rehabilitation applications despite this limitation. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： C-RNN Deep learning Desired motion intention EEG signals Machine learning Rehabilitation

来源：评论

学校读者我要写书评

暂无评论

Design and Performance Comparison of Low Dropout Regulators for a 32-bit Microcontroller Using 22nm Technology

Design and Performance Comparison of Low Dropout Regulators ...

引用

IEEE Latin American Symposium on Circuits and Systems (LASCAS)

作者： Emmanuel K. M. Johnson Luis Victor N. Lima Pamela. R. A. N. Campagnucci Sandro A. P. Haddad Wellington A. Amaral Daniel M. Muñoz Department of Mechanical Engineering Mechatronics Graduate Program University of Brasilia Brasilia DF Brazil Faculty of Gama Electronics Engineering Undergraduate Program University of Brasilia Brasilia DF Brazil

ISBN: (数字)9798331522124

ISBN: (纸本)9798331522131

This paper presents a comparison between two LDOs (Low Dropout Regulators) developed for a PMIC (Power Management Integrated Circuit) responsible for powering a 32-bit microcontroller based on the RISC-V microarchitecture, designed in 22 nm technology. The microcontroller will be integrated with a radio frequency interface for IoT (Internet of Things) applications. Two LDOs were designed: one with external compensation and the other a capacitor-less LDO. Both operate with an input voltage of 2.5V, an output voltage of 0.8V, and a maximum current of 150mA. The externally compensated LDO exhibited greater stability in response to load variations and a higher PSRR (Power Supply Rejection Ratio), while the capacitor-less LDO demonstrated faster regulation speed and occupied a chip area similar to the externally compensated LDO.

关键词： Regulators Microcontrollers Power supplies Power system management Simulation Stability analysis Regulation Circuit stability Internet of Things Voltage control

来源：评论

学校读者我要写书评

暂无评论

Multiband Patch Antenna Design Using Nature-Inspired Optimization Method

IEEE Open Journal of Antennas and Propagation

引用

IEEE Open Journal of Antennas and Propagation 2021年 2卷 151-162页

作者： Boursianis, Achilles D. Papadopoulou, Maria S. Pierezan, Juliano Mariani, Viviana C. Coelho, Leandro S. Sarigiannidis, Panagiotis Koulouridis, Stavros Goudos, Sotirios K. ELEDIA@AUTH Research Group School of Physics Aristotle University of Thessaloniki Thessaloniki54124 Greece Department of Electrical Engineering Federal University of Parana Curitiba80060-000 Brazil Industrial and Systems Engineering Graduate Program and Mechanical Engineering Graduate Program Pontifical Catholic University of Parana Curitiba80215-901 Brazil Department of Electrical and Computer Engineering University of Western Macedonia Kozani501 00 Greece Electrical and Computer Engineering Department University of Patras Patras26504 Greece

Radio frequency energy harvesting has attracted considerable interest as a technique of enabling self-powered wireless networks. This technique faces several challenges, such as the receiving and the rectifying modules of a rectenna system. Multiband antennas provide several comparative advantages against the goal of maximizing the amount of energy harvesting. In this work, we present a multiband microstrip patch antenna with three slits operating in the LoRaWAN (Long Range Wide Area Network) and the cellular (GSM-1800 and UMTS) communication frequency bands. A feasible solution of the antenna is obtained by the application of a recently introduced nature-inspired optimization technique, namely the Coyote Optimization Algorithm. The proposed antenna operates satisfactorily in the LoRaWAN (Long Range Wide Area Network) and the cellular (GSM-1800 and UMTS) communication frequency bands. Measured results of the proposed antenna exhibit an acceptable performance (multiband frequency operation, maximum gain of 3.94 dBi, broadside operation) and demonstrate features of operation, which make it a strong candidate for various RF energy harvesting applications. © 2020 IEEE.

关键词： Microstrip antennas

来源：评论

学校读者我要写书评

暂无评论

Motor Characteristics Map Prediction Using Deep Operator Neural Networks

Motor Characteristics Map Prediction Using Deep Operator Neu...

引用

IEEE Conference on Electromagnetic Field Computation

作者： Hidenori Sasaki Kazuhisa Iwata Takahiro Sato Yuki Sato Department of Electrical and Electronic Engineering Hosei University Koganei JAPAN Graduate School of Science and Engineering Hosei University Koganei JAPAN Graduate School of Engineering Muroran Institute of Technology Muroran JAPAN Department of Electrical Engineering and Electronics Aoyama Gakuin University Sagamihara JAPAN

ISBN: (数字)9798350348958

ISBN: (纸本)9798350348965

A novel deep learning model that predicts motor characteristics using a deep operator network and convolutional neural networks is proposed. The proposed method accurately predicts motor characteristics under various currents and rotation angles. The proposed method improves the prediction accuracy by 43.5% compared to the conventional method.

关键词： Deep learning Accuracy Neural networks Predictive models Motors Electromagnetic fields Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Control of Three-Level PWM Inverter-Fed Induction Motor Drives

Control of Three-Level PWM Inverter-Fed Induction Motor Driv...

引用

IEEE Conference and Expo Transportation Electrification Asia-Pacific (ITEC Asia-Pacific)

作者： Sutthimat Mueangngoen Neerakorn Jarutus Yuttana Kumsuwan Department of Electrical Engineering Faculty of Engineering Graduate Program in Electrical Engineering Chiang Mai University Chiang Mai Thailand Department of Electrical Engineering Faculty of Engineering Chiang Mai University Chiang Mai Thailand

This paper presents the control of three-level PWM committed to a three-level twelve-switch inverter-fed induction motor drive. The proposed control is totally capable of extracting the maximum DC utilization with the classical continuous and discontinuous PWM. Moreover, in the light of the multi-level inherency, the low switching frequency is attractive to this application to avoid the high power losses, while it can maintain the stability of the operation. Regardless of the single or double carrier waves, optimized switching states associated with the proposed logical operation part, which is responsible for obtaining the multi-level characteristic of the inverter, are also proposed. Importantly, through the MATLAB/Simulink program, the steady-state and dynamic response of the high-performance drive with the classically indirect vector control are definitely investigated to confirm the effectiveness of the proposed control strategy.

关键词：

来源：评论

学校读者我要写书评

暂无评论

On-Board Integrated Charger Based on Open-End Winding AC Machine

On-Board Integrated Charger Based on Open-End Winding AC Mac...

引用

IEEE Conference and Expo Transportation Electrification Asia-Pacific (ITEC Asia-Pacific)

作者： Thidarat Thanakam Neerakorn Jarutus Yuttana Kumsuwan Department of Electrical Engineering Faculty of Engineering Graduate Program in Electrical Engineering Chiang Mai University Chiang Mai Thailand Department of Electrical Engineering Faculty of Engineering Chiang Mai University Chiang Mai Thailand

This paper presents an on-board integrated charger for electric vehicles (EVs) based on an open-end winding AC machine. To reduce weight, volume, and costs, including additional space area in EVs, the main component of the traction system is utilized as a part of the charger system, i.e., the wound rotor open-end winding AC machine fed by a dual converter with a single battery source. In charging operation, the rotor winding side of the AC machine is at standstill and reconfigured through magnetic contactors to interface with the three-phase utility grid, whereas the stator winding side is still connected to the converters. It performs as a transformer isolated by itself. On the other hand, the rotor windings are shorted together for the driving operation. Besides, the charger system assists the stability of the utility grid by consuming constant power, absorbing maximum power rated at 22 kW. To enhance excellent control, the modulation strategy of the dual converter is determined by means of different phase angles of 120° As a result, the differential-mode voltage problem is suppressed. The simulation results are validated to confirm the performance of the proposed system.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Darknet Traffic Classification with Machine Learning Algorithms and SMOTE Method 7

Darknet Traffic Classification with Machine Learning Algorit...

引用

7th International Conference on Computer Science and engineering, UBMK 2022

作者： Karagol, Hasan Erdem, Oguzhan Akbas, Barkin Soylu, Tuncay Trakya University Department of Electrical and Electronics Engineering Edirne Turkey University of Health Sciences Department of Occupational Health and Safety Program Istanbul Turkey

ISBN: (数字)9781665470100

ISBN: (纸本)9781665470100

The Darknet is a network that can be accessed with certain privileges and runs a non-standard communication protocol. The Darknet traffic that consists of data from several known networks such as Tor and the P2P is often used for criminal activities due to its anonymity. It is so critical to correctly classify Darknet traffic to differentiate the individual flows for security purposes. In this paper, we proposed three different machine learning (ML) based traffic classification approaches;the binary classification of Darknet and Benign traffic classes (Case 1);the quadruple classification of classes Tor, NonTor, VPN, and NonVpn (Case 2);an traffic classification of eight sub-traffic classes (Case 3). We further applied the SMOTE method for balancing the sizes of the classes in the traffic dataset and feature selection (FS) algorithms to identify the most effective attributes where the number of features in the original dataset were reduced from 63 to 8, 8 and 6 for Case 1, 2 and 3 respectively. For all three cases, classification was performed with six different machine learning algorithms with and without SMOTE, and the highest accuracy values were obtained with SMOTE method. The highest accuracy values were obtained with the Random Forest Algorithm as 97.22%, 97.16% and 85.99% for Case 1, 2 and 3, respectively. © 2022 IEEE.

关键词： Decision trees

来源：评论

学校读者我要写书评

暂无评论

Retraining-free Constraint-aware Token Pruning for Vision Transformer on Edge Devices

Retraining-free Constraint-aware Token Pruning for Vision Tr...

引用

IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Yun-Chia Yu Mao-Chi Weng Ming-Guang Lin An-Yeu Andy Wu Department of Electrical Engineering National Taiwan University Taipei Taiwan Graduate Institute of Electronics Engineering National Taiwan University Taipei Taiwan

ISBN: (数字)9798350330991

ISBN: (纸本)9798350331004

Vision transformer (ViT) and its variants have demonstrated great potential in various computer vision tasks. However, intensive computation requirements with respect to the token size hinder ViT from being deployed on edge devices with diverse computation resources. Recently, token pruning has been proven to be a promising method to exploit the redundancy of tokens. However, it often requires a laborious retraining process to meet different resource constraints. In this paper, we introduce Fisher information (FI) from tokens to evaluate token importance across different transformer blocks and propose a Retraining-free Constraint-aware Token Pruning (RCTP) framework. RCTP employs a two-step process to obtain the optimal pruning thresholds without retraining under different FLOPs constraints. In the first step, a candidate threshold table and a FLOPs-Fisher table are constructed through a three-stage pipeline to record the trade-off between FLOPs and FI loss of each candidate threshold. In the second step, a modified Viterbi algorithm determines optimal threshold sets with minimum overall FI loss under different FLOPs-constraints in one shot. Our experiment illustrates that RCTP attains better accuracy-FLOPs trade-off than prior pruning-based approaches.

关键词： Computer vision Viterbi algorithm Circuits and systems Machine vision Image edge detection Pipelines Termination of employment

来源：评论

学校读者我要写书评

暂无评论

Comparison of 2L and 3L-NPC Power Converter-Based a Level-2 Isolated Off-Board Charger

Comparison of 2L and 3L-NPC Power Converter-Based a Level-2 ...

引用

electrical, Computer and Energy Technologies (ICECET), International Conference on

作者： Thidarat Thanakam Yuttana Kumsuwan Department of Electrical Engineering Faculty of Engineering Graduate Program in Electrical Engineering Chiang Mai University Chiang Mai Thailand Department of Electrical Engineering Faculty of Engineering Chiang Mai University Chiang Mai Thailand

This paper presents an off-board charger system for any electric vehicle based on a single-stage power converter operation that performs as a three-phase pulse width modulation rectifier. To enhance the safety issue by itself, a step-down transformer with galvanic isolation is added. Additionally, the off-board charger system allows bidirectional power flow in both grid-to-vehicle (G2V) and vehicle-to-grid operations. To analyze this system, only G2V operation is shown by comparing a two-level power converter charger with a three-level neutral point clamped power converter charger. In light of its controller, the off-board charger is designed to charge a battery in constant current and constant voltage mode in compliance with Level 2 of charging power. Based on this controller, it can support grid power quality under a unity power factor. Simulation-based verification is conducted on a maximum power rating of 22 kW to claim the performance of steady-state operation and dynamic operation.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Enhanced Efficiency in Fog Computing: A Fuzzy Data-Driven Machine Selection Strategy

引用

International Journal of Fuzzy Systems 2024年第1期26卷 368-389页

作者： Zavieh, Hadi Javadpour, Amir Ja’fari, Forough Sangaiah, Arun Kumar Slowik, Adam School of Economics and Statistics Guangzhou University Guangzhou510006 China Harbin Institute of Technology Shenzhen China Department of Computer Engineering Sharif University of Technology Tehran Iran International Graduate School of AI National Yunlin University of Science and Technology Douliu Taiwan Department of Electronics and Computer Science Koszalin University of Technology Koszalin Poland ADiT-Lab Electrotechnics and Telecommunications Department Instituto Politécnico de Viana do Castelo Porto4900–347 Portugal Department of Electrical and Computer Engineering Lebanese American University Byblos Lebanon

With the rapid proliferation of IoT and Cloud networks and the corresponding number of devices, handling incoming requests has become a significant challenge. Task scheduling problems have emerged as a common concern, necessitating the exploration of new methods for request management. This paper proposes a novel approach called the Fuzzy Inverse Markov Data Envelopment Analysis Process (FIMDEAP). Our method combines the strengths of the Fuzzy Inverse Data Envelopment Analysis (FIDEA) and Fuzzy Markov Decision Process (FMDP) techniques to enable the efficient selection of physical and virtual machines while operating in a fuzzy mode. We represent data as triangular fuzzy numbers and employ the alpha-cut method to solve the proposed models. The paper provides a mathematical optimization model for the proposed method and presents a numerical example for illustration. Furthermore, we evaluate the performance of our method in a cloud environment through simulations. The results demonstrate that our approach outperforms existing methods, namely PSO + ACO and FBPSO + FBACO, in terms of key metrics, including energy consumption, execution cost, response time, gain of cost, and makespan. © The Author(s) 2023.

关键词： Markov processes

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：