检索结果-内蒙古大学图书馆

General Optimal Trajectory Planning:Enabling Autonomous Vehicles with the Principle of Least Action

engineering 2024年第2期33卷 63-76页

作者： Heye Huang Yicong Liu Jinxin Liu Qisong Yang Jianqiang Wang David Abbink Arkady Zgonnikov School of Vehicle and Mobility Tsinghua UniversityBeijing 100084China Department of Cognitive Robotics Faculty of MechanicalMaritime and Materials Engineering(3mE)Delft University of TechnologyDelft 2628Netherlands Department of Software Technology Faculty of Electrical EngineeringMathematics and Computer ScienceDelft University of TechnologyDelft 2628Netherlands Xi’an Institute of High-Technology Xi’an 710051China

This study presents a general optimal trajectory planning(GOTP)framework for autonomous vehicles(AVs)that can effectively avoid obstacles and guide AVs to complete driving tasks safely and ***,we employ the fifth-order Bezier curve to generate and smooth the reference path along the road *** coordinates are then transformed to achieve the curvature continuity of the generated *** the road constraints and vehicle dynamics,limited polynomial candidate trajectories are generated and smoothed in a curvilinear coordinate ***,in selecting the optimal trajectory,we develop a unified and auto-tune objective function based on the principle of least action by employing AVs to simulate drivers’behavior and summarizing their manipulation characteristics of“seeking benefits and avoiding losses.”Finally,by integrating the idea of receding-horizon optimization,the proposed framework is achieved by considering dynamic multi-performance objectives and selecting trajectories that satisfy feasibility,optimality,and *** simulations and experiments are performed,and the results demonstrate the framework’s feasibility and effectiveness,which avoids both dynamic and static obstacles and applies to various scenarios with multi-source interactive traffic ***,we prove that the proposed method can guarantee real-time planning and safety requirements compared to drivers’manipulation.

关键词： Autonomous vehicle Trajectory planning Multi-performance objectives Principle of least action

来源：评论

学校读者我要写书评

暂无评论

ATmega2560 MCU Space Vector Modulation Implementation on Three-phase Inverter and Validation via Typhoon HIL 402 5

ATmega2560 MCU Space Vector Modulation Implementation on Thr...

引用

5th IEEE International Conference on Smart Systems and Technologies, SST 2022

作者： Brandis, Andrej Pelin, Denis Šimić, Zvonimir Vidošić, Ivan Department of Electromechanical Engineering Faculty of Electrical Engineering Computer Science and Information Technology Osijek Osijek Croatia Department of Power Engineering Faculty of Electrical Engineering Computer Science and Information Technology Osijek Osijek Croatia Faculty of Electrical Engineering Computer Science and Information Technology Osijek Osijek Croatia

ISBN: (数字)9781665482158

ISBN: (纸本)9781665482158

In this paper, a space vector modulation implementation is done via ATmega2560 microcontroller with the Arduino development board. The control parameters are defined by the user in MATLAB software and sent to Arduino to start or stop the controller or to change the controller parameters. Space vector switching times for chosen parameters are calculated and given. The implemented algorithm is validated via Typhoon HIL 402 system on a three-phase inverter model for two different operation points. Voltage and current waveforms are obtained in Typhoon HIL. Line and phase voltage, as well as the phase current spectrum analysis is done via Typhoon HIL and processed in MATLAB for given system parameters. The measurement results validates the implemented space vector control algorithm. © 2022 IEEE.

关键词： Microcontrollers

来源：评论

学校读者我要写书评

暂无评论

A novel approach to deriving adaboost classifier weights using squared loss function for overlapping speech detection

引用

Multimedia Tools and Applications 2025年 1-28页

作者： Asbai, Nassim Bounazou, Hadjer Zitouni, Sihem Department of Electronics Faculty of Sciences and Technology Mohamed El Bachir El Ibrahimi University Bordj Bou Arreridj City34030 Algeria Speech Com. & Signal Proc. Lab. Faculty of Electrical Engineering USTHB Bab Ezzouar City16111 Algeria Department of Computer Science Faculty of Mathematics and Computer Science Mohamed El Bachir El Ibrahimi University Bordj Bou Arreridj City34030 Algeria

In this paper, we address the complex problem of detecting overlapping speech segments, a key challenge in speech processing with applications in speaker diarization, automatic transcription, and multi-speaker recognition systems. Traditional approaches, often relying on exponential loss functions within the AdaBoost framework, struggle to maintain robustness in noisy or imbalanced data environments. To enhance detection accuracy, we propose a novel AdaBoost variant—SLFAdaBoost—utilizing a squared loss function specifically tailored for overlapping speech detection. This model demonstrates superior stability and convergence, significantly outperforming conventional methods. Experimental evaluation on the NIST 2005 corpus revealed that SLFAdaBoost achieves an accuracy range of 92.5% to 98.6%, with F1 scores between 95.4% and 99.2%, notably surpassing standard AdaBoost and Random Forest classifiers. Additionally, our model shows resilience in noisy conditions, maintaining precision and recall metrics at higher noise levels than other classifiers. These results underscore SLFAdaBoost's capacity to handle intricate data patterns, offering a more robust solution for real-world speech processing applications where overlapping segments are prevalent. This contribution provides an efficient, high-performing model, advancing the capabilities of ensemble methods in complex audio environments. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2025.

关键词： Speech recognition

来源：评论

学校读者我要写书评

暂无评论

Maximizing Energy Efficiency in IRS-Assisted Phase Cooperative PS-SWIPT-Based Self-Sustainable IoT Network

IEEE Open Journal of the Communications Society

引用

IEEE Open Journal of the Communications Society 2025年 6卷 4311-4327页

作者： Sadia, Haleema Kamal Hassan, Ahmad Haq Abbas, Ziaul Abbas, Ghulam Baker, Thar Saeed, Nasir United Arab Emirates University College of Engineering Department of Electrical and Communication Engineering Al Ain United Arab Emirates Ghulam Ishaq Khan Institute of Engineering and Technology Faculty of Electrical Engineering Topi23460 Pakistan Ghulam Ishaq Khan Institute of Engineering and Technology Faculty of Computer Science and Engineering Topi23460 Pakistan University of Brighton School of Architecture Technology and Engineering BrightonBN2 4GJ United Kingdom

Power splitting based simultaneous wireless information and power transfer (PS-SWIPT) appears to be a promising solution to support future self-sustainable Internet of Things (SS-IoT) networks. However, the performance of these networks is constrained by radio frequency signal strength and channel impairments. To overcome this challenge, intelligent reflecting surfaces (IRSs) have recently been introduced in IoT networks to improve network efficiency by controlling signal reflections. In this article, we propose a novel IRS-enabled phase cooperative framework that aims to maximize the energy efficiency (EE) of the PS-SWIPT based SS-IoT network. Our framework leverages the idea of phase cooperation between two distinct networks without requiring additional hardware resources. We employed transmit beamforming (BF) at access points (APs) and phase shift optimization at the IRS with effective phase cooperation between APs. The EE maximization problem turns out to be NP-hard, so first, an alternating optimization (AO) is solved for the user’s network using heuristic BF approaches and phase optimization via semidefinite relaxation (SDR) approaches. To combat the computational complexity of AO, we also propose a low-complexity alternative solution by exploiting heuristic BF schemes and an iterative algorithm, i.e., the element-wise block-coordinate descent method for phase shifts optimization. The proposed solutions’ analysis shows low computational complexity and fast convergence, achieving near-optimal EE performance for different network settings. We conducted extensive simulations to evaluate our proposed framework’s performance and unveiled significant EE performance achieved by the IoT network consistent with the numerical findings. This work demonstrates the potential of IRS phase cooperation for enhancing the EE of different networks without constraining hardware resources. © 2020 IEEE.

关键词： Energy transfer

来源：评论

学校读者我要写书评

暂无评论

Unseen Named Entity Recognition for Thai Language 21

Unseen Named Entity Recognition for Thai Language

引用

21st International System-on-Chip Design Conference, ISOCC 2024

作者： Kuntichod, Watcharet Lee, Wilaiporn Prayote, Akara King Mongkut's University of Technology North Bangkok Faculty of Applied Science Department of Computer and Information Science Bangkok10800 Thailand King Mongkut's University of Technology North Bangkok Faculty of Engineering Department of Electrical and Computer Engineering Bangkok10800 Thailand

ISBN: (纸本)9798350377088

Most common challenges in Named-entity recognition (NER) require suitable and annotated datasets, tailored to the specific domain of the documents under analysis, for example, legal, medical, and financial documents each require distinct datasets. Reliable identification of named entities within the training set is crucial. Annotations is a vital role in building an effective mechanism. However, creating training sets demands significant human effort, contributing to the high costs associated with NER. High quality training materials are indispensable for evolving machine-learning algorithms, underscoring the importance of dependable training data. Thus, the primary challenge lies in acquiring and managing data rather than in the algorithms themselves. To overcome most common situations of finding new unseen names, this paper proposes a mechanism to detect a new undiscovered name in Thai language based on sentence contexts. The method uses BI-LSTM model to learn sentence structures and predict a new unseen name from its context. Our framework comprises two main tasks. The first one is word entity extraction. The second task is using the model to identify unrecognized named entities. Evaluation of the proposed method is described with a successful rate of accuracy in discovering newly identified entities. This contributes to the expansion of entity recognition capabilities in Thai language processing. © 2024 IEEE.

关键词： BI-LSTM Herb Entity Unseen Named Entity

来源：评论

学校读者我要写书评

暂无评论

Dynamic Insights: Well-being Activity Infused Fine-Tuning of Large Language Models

Dynamic Insights: Well-being Activity Infused Fine-Tuning of...

引用

2024 IEEE International Conference on Big Data, BigData 2024

作者： Mohammed, Hamza Haruna Kiss, Gabriel Serrano, J. Artur Lindseth, Frank Norwegian University of Science and Technology Faculty of Information Technology and Electrical Engineering Department of Computer Science Trondheim Norway Norwegian University of Science and Technology Faculty of Medicine and Health Sciences Department of Neuromedicine and Movement Science Trondheim Norway

ISBN: (纸本)9798350362480

The fast development of Large Language Models (LLMs) has made transformative applications in several fields attainable or possible. However, language models must often be more effective in specialized areas, especially health and prevention. This paper presents a novel method for fine-tuning LLMs using activity-related data to optimize them for the applicability of such models in health and wellbeing applications. We thus empirically evaluate this approach on the Cardiac Exercise Research corpus for fine-tuning the LLMs. The fine-tuning utilizes Quantized Low-Rank Adaptation (QLoRA) to ensure the models' size remains small while maintaining high performance and accuracy to keep the semantic understanding and relevance with health-related queries. Our results in answering domain-related prompts showed an improved user satisfaction and sentiment scores, providing strong confidence in the method's effectiveness. This study highlights the potential of domain-specific LLMs in advancing personalized healthcare. It instills a sense of optimism about the future of healthcare and the seamless integration of AI within health prevention and well-being domains. © 2024 IEEE.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

ResMHA-Net:Enhancing Glioma Segmentation and Survival Prediction Using a Novel Deep Learning Framework

引用

computers, Materials & Continua 2024年第10期81卷 885-909页

作者： Novsheena Rasool Javaid Iqbal Bhat Najib Ben Aoun Abdullah Alharthi Niyaz Ahmad Wani Vikram Chopra Muhammad Shahid Anwar Department of Computer Science School of Engineering and TechnologyIslamic University of Science and TechnologyAwantipora192122India Faculty of Computing and Technology Al-Baha UniversityAlaqiq65779-7738Saudi Arabia Research Groups in Intelligent Machines National School of Engineers of SfaxUniversity of SfaxSfax3038Tunisia Department of Electrical Engineering College of EngineeringKing Khalid UniversityAbha61421Saudi Arabia Department of Computer Science and Engineering Thapar Institute of Engineering and TechnologyPatiala147004Punjab Department of Electrical and Instrumentation Engineering Thapar Institute of Engineering and TechnologyPatiala147004Punjab Department of AI and Software Gachon UniversitySeongnam-si13120Republic of Korea

Gliomas are aggressive brain tumors known for their heterogeneity,unclear borders,and diverse locations on Magnetic Resonance Imaging(MRI)*** factors present significant challenges for MRI-based segmentation,a crucial step for effective treatment planning and monitoring of glioma *** study proposes a novel deep learning framework,ResNet Multi-Head Attention U-Net(ResMHA-Net),to address these challenges and enhance glioma segmentation ***-Net leverages the strengths of both residual blocks from the ResNet architecture and multi-head attention *** powerful combination empowers the network to prioritize informative regions within the 3D MRI data and capture long-range *** doing so,ResMHANet effectively segments intricate glioma sub-regions and reduces the impact of uncertain tumor *** rigorously trained and validated ResMHA-Net on the BraTS 2018,2019,2020 and 2021 ***,ResMHA-Net achieved superior segmentation accuracy on the BraTS 2021 dataset compared to the previous years,demonstrating its remarkable adaptability and robustness across diverse ***,we collected the predicted masks obtained from three datasets to enhance survival prediction,effectively augmenting the dataset *** features were then extracted from these predicted masks and,along with clinical data,were used to train a novel ensemble learning-based machine learning model for survival *** model employs a voting mechanism aggregating predictions from multiple models,leading to significant improvements over existing *** ensemble approach capitalizes on the strengths of various models,resulting in more accurate and reliable predictions for patient ***,we achieved an impressive accuracy of 73%for overall survival(OS)prediction.

关键词： Glioma MRI segmentation multihead attention survival prediction deep learning

来源：评论

学校读者我要写书评

暂无评论

Multiband Slotted Crescent-shaped Patch Antenna for K-band Satellite and mmWave Communications

引用

IEIE Transactions on Smart Processing and Computing 2022年第3期11卷 213-221页

作者： Hossain, Md Najmul Paul, Liton Chandra Rahim, Md Abdur Shin, Jungpil Department of Electrical Electronic and Communication Engineering Faculty of Engineering and Technology Pabna University of Science and Technology Pabna6600 Bangladesh Department of Computer Science and Engineering Faculty of Engineering and Technology Pabna University of Science and Technology Pabna6600 Bangladesh School of Computer Science and Engineering The University of Aizu Aizuwakamatsu Fukushima965-8580 Japan

In this paper, a multiband miniaturized crescent-shaped patch antenna with circular slots is presented for ultra-wideband applications. The proposed antenna is constructed on a Flame Retardant 4 (FR-4) dielectric substrate. Next-generation wireless communication systems, such as beyond 5G (B5G) and 6G mobile communication systems require a wider bandwidth and higher data rates. The overall size of the proposed antenna is 11.4 mm3 operating in the frequency range of 17.73 GHz to 26.04 GHz and 29.6 GHz to 31.02 GHz for satellite communications and radar systems, respectively, as well as 35.40 GHz to 38.65 GHz for future mmWave B5G mobile applications. These frequency ranges usually fall into the K-band and mmWave frequency spectrums. Simulation results demonstrate that the peak gain of the proposed antenna is 4.68 dB, which is obtained at 25 GHz. © 2022 The Institute of Electronics and Information Engineers.

关键词： Microstrip antennas

来源：评论

学校读者我要写书评

暂无评论

Adaptive Memory Differential Evolutionary Algorithm for Network Management Using Variants of Dominating Set Models 2

Adaptive Memory Differential Evolutionary Algorithm for Netw...

引用

2nd International Conference of Intelligent Methods, Systems and Applications, IMSA 2024

作者： Hedar, Abdel-Rahman Tarek, Fatma El-Zahraa Mohamed, Mostafa El-Sayed, Gamal A. Assiut University Faculty of Computers & Information Department of Computer Science Assiut71526 Egypt Assiut University Faculty of Engineering Department of Electrical Engineering Assiut71515 Egypt Umm Al-Qura University Department of Computer Science in Jamoum Makkah25371 Saudi Arabia

ISBN: (纸本)9798350362633

In wireless sensor networks, where multiple sensors are typically concentrated in a confined area, determining the optimal size of wireless sensors to use for communication and coordination over the network is essential due to concerns about the preservation of energy and battery. In this paper, we introduce new competitive memory-based differential evolution methods to solve wireless sensor network management problems using variants of dominating set models. The problems considered are formulated as constrained optimization problems that are transformed into unconstrained optimization problems using the penalty principle. Then, differential evolution with several memory-based enhanced procedures is designed to find solutions to the reformed optimization problems. Two versions of the proposed Adaptive Memory Differential Evolutionary Algorithm (AMDEA) are designed to deal with the minimum dominating set problem and its variants. The results obtained from the proposed methods show that they are promising compared to some benchmark methods. © 2024 IEEE.

关键词： Constrained optimization

来源：评论

学校读者我要写书评

暂无评论

Neural Network Controlled Grid Synchronization of Single-Phase Inverter Using SOGI-PLL for Efficient Solar Power Integration 13

Neural Network Controlled Grid Synchronization of Single-Pha...

引用

13th International Conference on System Modeling and Advancement in Research Trends, SMART 2024

作者： Mishra, Vinayak Singh, Narendra Pal Singh, Umesh Kumar Jain, Akshit Kumar, Doshi Saumya Rakesh Teerthanker Mahaveer University Moradabad Faculty of Engineering Electrical Engineering Department Uttar Pradesh India Invertis University Bareilly Department of Computer Science and Engineering Uttar Pradesh India

ISBN: (纸本)9798350380583

This paper presents a comprehensive Artificial Neural Network (ANN)-based control scheme for single-phase grid-connected inverters, emphasizing efficient and accurate synchronization. Using Echo State Networks (ESN) within the ANN framework, this method generates a precise modulating wave for Pulse Width Modulation (PWM) control. Combined with a Second order generalised algorithms (SOGI) Phase-Locked Loop (PLL) system, the approach effectively aligns the inverter's output with grid phase and frequency, achieving low Total Harmonic Distortion (THD). Simulations in MATLAB/Simulink verify the superior performance of this method over traditional Proportional Integral (PI) and PR control systems in terms of steady-state and transient performance. © 2024 IEEE.

关键词： Phase locked loops

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：