检索结果-内蒙古大学图书馆

Effect of magnetic nanoparticles on magnetic field homogeneity

Chinese Physics B 2023年第5期32卷 188-192页

作者：郭斯琳易文通李壮壮 Laboratory of Science and Technology on Integrated Logistics Support National University of Defense TechnologyChangsha 410073China College of Intelligence Science and Technology National University of Defense TechnologyChangsha 410073China School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074China

The mechanism of magnetic nanoparticles(MNPs)affecting magnetic field uniformity is studied in this *** spatial distribution of MNPs in liquid is simulated based on Monte Carlo *** induced field of the single MNP is combined with the magnetic field distribution of *** the simulation,magnetic field uniformity is described by a statistical *** the chemical shift(CS)and full width at half maximum(FWHM)of magnetic resonance(MR)spectrum can reflect the uniformity of magnetic field,the simulation is verified by spectrum *** and measurement results prove that the CS and FWHM of the MR spectrum are basically positively correlated with the concentration of MNPs and negatively correlated with the *** research results can explain how MNPs play a role in MR by affecting the uniform magnetic field,which is of great significance in improving the temperature measurement accuracy of magnetic nanothermometers and the spatial resolution of magnetic particle imaging.

关键词： magnetic nanoparticle field distribution Monte Carlo method

来源：评论

学校读者我要写书评

暂无评论

Performance-guaranteed adaptive fault-tolerant tracking control of six-DOF spacecraft

引用

science China(Information sciences) 2023年第1期66卷 328-329页

作者： Kewei XIA Yao ZOU Yonsei University Observatory Yonsei University School of Automation and Electrical Engineering University of Science and Technology Beijing Institute of Artificial Intelligence University of Science and Technology Beijing

Dear editor,In recent decades, the six-DOF(degree-of-freedom) spacecraft(i.e., motions of the attitude and the orbit) control has received considerable attention owing to its broad applications in aerospace missions l...

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Discrete-Time Collaborative Neurodynamic Approach to Distributed Global Optimization 13

A Discrete-Time Collaborative Neurodynamic Approach to Distr...

引用

13th International Conference on Intelligent Control and Information Processing, ICICIP 2025

作者： Huang, Haoen Zeng, Zhigang Wang, Jun School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Department of Computer Science Department of Data Science City University of HongKong Kowloon Hong Kong

ISBN: (纸本)9798331516147

In this paper, a discrete-time projection neural network with an adaptive step size (DPNN) is proposed for distributed global optimization. The DPNN is proven to be convergent to a Karush-Kuhn-Tucker point. Several DPNNs are utilized in a collaborative neurodynamic framework for solving distributed global optimization problem. The efficacy of the collaborative neurodynamic approach with DPNNs is demonstrated through simulation results. © 2025 IEEE.

关键词： Neural network models

来源：评论

学校读者我要写书评

暂无评论

Neighbor Library-Aware Graph Neural Network for Third Party Library Recommendation

引用

Tsinghua science and technology 2023年第4期28卷 769-785页

作者： Ying Jin Yi Zhang Yiwen Zhang School of Artificial Intelligence and Big Data Hefei UniversityHefei 230601China School of Computer Science and Technology Anhui UniversityHefei 230601China

Modern software development has moved toward agile growth and rapid delivery,where developers must meet the changing needs of users *** such a situation,plug-and-play Third-Party Libraries(TPLs)introduce a considerable amount of convenience to ***,selecting the exact candidate that meets the project requirements from the countless TPLs is challenging for *** works have considered setting up a personalized recommender system to suggest TPLs for ***,these approaches rarely consider the complex relationships between applications and TPLs,and are unsatisfactory in accuracy,training speed,and convergence *** this paper,we propose a new end-to-end recommendation model called Neighbor Library-Aware Graph Neural Network(NLA-GNN).Unlike previous works,we only initialize one type of node embedding,and construct and update all types of node representations using Graph Neural Networks(GNN).We use a simplified graph convolution operation to alternate the information propagation process to increase the training efficiency and eliminate the heterogeneity of the app-library bipartite graph,thus efficiently modeling the complex high-order relationships between the app and the *** experiments on large-scale real-world datasets demonstrate that NLA-GNN achieves consistent and remarkable improvements over state-of-the-art baselines for TPL recommendation tasks.

关键词： Third-Party Library(TPL) TPL recommendation Graph Neural Network(GNN) bipartite graph

来源：评论

学校读者我要写书评

暂无评论

Whale optimisation algorithm with role labour division for multimodal optimisation

引用

International Journal of Innovative Computing and Applications 2024年第1期15卷 26-37页

作者： Wu, Bowen Xiao, Renbin School of Artificial Intelligence and Automation Huazhong University of Science and Technology Hubei Wuhan430074 China Institute of Artificial Intelligence Huazhong University of Science and Technology Hubei Wuhan430074 China Key Laboratory of Image Processing and Intelligent Control Ministry of Education of China Huazhong University of Science and Technology Hubei Wuhan430074 China

The multimodal optimisation problem challenges the balance between diversity and convergence, which poses a great degree of challenge to traditional population-based intelligence optimisers. The whale optimisation algorithm has the limitation of easily falling into local optimum when facing multimodal optimisation. To address this problem, this paper proposes a whale optimisation algorithm with role labour division (WOA-RDL). In WOA-RDL, a multi-stage role division of labour mechanism is designed to divide the optimisation process into two stages of group hunting. In the first stage, the task allocation in the hunting process is considered as two types of search tasks: exploration and exploitation. The external environmental stimulus of the task and the internal response threshold of the individual were designed to allow individuals to switch between exploration and exploitation tasks flexibly. In the second stage, the distribution mechanism of different roles was designed to simulate the 'strong to weak' distribution rule for the distribution of results after the hunt. The elite roles are selected to further strengthen their capabilities or remain robust, while the inferior roles are predicted and eliminated to improve the overall optimisation of the population and reduce the risk of falling into a local optimum. The results of the optimisation experiments using multimodal, unimodal, CEC2017 combined functions and CEC2009 dynamic functions to validate the effectiveness of the algorithm. Copyright © 2024 Inderscience Enterprises Ltd.

关键词： Optimization algorithms

来源：评论

学校读者我要写书评

暂无评论

A Domain Generalization and Residual Network-Based Emotion Recognition from Physiological Signals

引用

Cyborg and Bionic Systems 2024年第1期5卷 709-720页

作者： Junnan Li Jiang Li Xiaoping Wang Xin Zhan Zhigang Zeng School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074China Hubei Key Laboratory of Brain-inspired Intelligent Systems Huazhong University of Science and TechnologyWuhan 430074China Key Laboratory of Image Processing and Intelligent Control(Huazhong University of Science and Technology) Ministry of EducationWuhan 430074China Institute of Artificial Intelligence Huazhong University of Science and TechnologyWuhan 430074China

Emotion recognition from physiological signals(ERPS)has drawn tremendous attention and can be potentially applied to numerous *** physiological signals are nonstationary time series with high sampling frequency,it is challenging to directly extract features from ***,there are 2 major challenges in ERPS:(a)how to adequately capture the correlations between physiological signals at different times and between different types of physiological signals and(b)how to effectively minimize the negative effect caused by temporal covariate shift(TCS).To tackle these problems,we propose a domain generalization and residual network-based approach for emotion recognition from physiological signals(DGR-ERPS).We first pre-extract time-and frequency-domain features from the original time series to compose a new time ***,in order to fully extract the correlation information of different physiological signals,these time series are converted into 3D image data to serve as input for a residual-based feature encoder(RBFE).In addition,we introduce a domain generalization-based technique to mitigate the issue posed by *** have conducted extensive experiments on 2 real-world datasets,and the results indicate that our DGR-ERPS achieves superior performance under both TCS and non-TCS scenarios.

关键词： physiological signals effectively minimize n capture correlations domain generalization residual network emotion recognition extract features emotion recognition physiological signals erps

来源：评论

学校读者我要写书评

暂无评论

MCFF-Net: Multi-Scale Contextual Feature Fusion Network for Polyp Segmentation

引用

Journal of Shanghai Jiaotong University (science) 2025年 1-13页

作者： Ma, Lei Yan, Jiangkai Shao, Dangguo Li, Jingtao Wang, Jiawei Yan, Yukun Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China Yunnan Provincial Key Laboratory of Artificial Intelligence Kunming650500 China

In clinical practice, technologies for automatically segmenting polyps might greatly improve the speed and accuracy of medical diagnosis, significantly reducing the chances of patients developing colorectal cancer. Nevertheless, the segmentation of polyps presents a considerable challenge due to their low contrast, presence of occlusion, and intricate background disturbances. In this paper, we propose an innovative approach for segmenting polyps, called multi-scale contextual feature fusion network for polyp segmentation (MCFF-Net). Specifically, MCFF-Net includes three modules: feature enhancement module (FEM), global-local feature fusion module (GLFF), and cross-scale feature fusion module (CFFM). Among them, FEM is used to improve the features at each scale. Building on this, the CFFM enables comprehensive interaction among the information across various scales, enhancing the diversity of the feature scales extracted. Moreover, the GLFF fuses global-local features to generate a rough object localization map. This map further modulates the fusion features from the CFFM, facilitating more precise segmentation. On five publicly available datasets, our approach not only segments various polyp types but also surpasses existing methods in terms of accuracy and generalizability. © Shanghai Jiao Tong University 2024.

关键词： Diseases

来源：评论

学校读者我要写书评

暂无评论

Solving multi-goal task assignment and path finding problem with a Single Constraint Tree 43

Solving multi-goal task assignment and path finding problem ...

引用

43rd Chinese Control Conference, CCC 2024

作者： Xu, Xianzhe Yin, Quan Fu, Yuqi Yu, Mengqiang Huazhong University of Science and Technology School of Artificial Intelligence and Automation Wuhan430074 China

ISBN: (纸本)9789887581581

This paper formalize and study the Multi-Goal Task Assignment and Path Finding (MG-TAPF) problem from both theoretical and algorithmic perspectives. The MG-TAPF problem involves determining an assignment scheme for tasks to agents, where each task comprises a series of target locations, and planning collision-free paths for agents to successfully complete the assigned tasks. In this work, we propose the ITA-CBS-MLA algorithm that builds upon CBS-TA-MLA, which aims to find optimal solutions for the MG-TAPF problem. Furthermore, we introduce expanded versions of the algorithm to handle diverse scenarios that may arise in practice. Comprehensive experimental evaluations are conducted on various benchmarks to compare the performance of these algorithms. © 2024 Technical Committee on Control Theory, Chinese Association of automation.

关键词： Trees (mathematics)

来源：评论

学校读者我要写书评

暂无评论

Skill Mount: Personalized Career Skills Development Using Machine Learning Algorithms 11

Skill Mount: Personalized Career Skills Development Using Ma...

引用

11th IEEE International Conference on Advances in Computing and Communications, ICACC 2024

作者： Krishnan, Akhil Joseph, James Nihal, N.N. Salva Fathima, S. Priya, C.V. Muthoot Institute of Technology and Science Department of Artificial Intelligence and Data Science Kerala Kochi India

ISBN: (纸本)9798350379136

In today's rapidly changing job market, achieving career goals requires a strategic approach to skill development. Skill Mount is an intuitive web application designed to guide individuals through their career journeys, aiding in both planning and attainment of objectives through personalized technology-driven methods. Given the constant evolution of job roles and the competitive landscape, continuous skill enhancement is imperative for career advancement, making Skill Mount an indispensable tool. Serving as a personalized coach, it tailors daily skill acquisition plans, monitors progress, and suggests suitable job roles based on individual preferences. Leveraging artificial intelligence (AI), including Natural Language Processing (NLP) and Machine Learning (ML), Skill Mount analyzes user data to provide customized skill suggestions and job descriptions. The proposed system uses Recommendation Systems to propose relevant learning resources and utilizes an ensemble method (random forest algorithm) for job recommendations, As a result system acquired higher accuracy rates. With a focus on user experience (UX), Skill Mount ensures seamless interaction through its intuitive interface and automated features driven by AI. By simplifying the career journey and empowering individuals to adapt to the competitive job market, Skill Mount plays a pivotal role in facilitating career growth and success. © 2024 IEEE.

关键词： Commerce

来源：评论

学校读者我要写书评

暂无评论

Sustainable Urban Street Lighting through Predictive Maintenance using IoT and AI 2

Sustainable Urban Street Lighting through Predictive Mainten...

引用

2nd IEEE International Conference on Emerging Research in Computational science, ICERCS 2024

作者： Sudharson, D. Jananiksha, P. Mukilarasu, R. Sushmita, V. Vaishali, V. Rini Vaishnavi, S.R. Kumaraguru College of Technology Artificial Intelligence and Data Science Coimbatore India Vellore Institute of Technology CSE - Artificial Intelligence and Machine Learning Vellore India

ISBN: (纸本)9798331534950

The potential for transformative urban management is enhanced through the integration of IoT and AI, creating smart ecosystems that revolutionize intelligent lighting systems. This paper explores predictive maintenance solutions for urban street lighting, leveraging advanced machine learning models such as Temporal Fusion Transformer (TFT), Temporal Aggregation and Decomposition-based Attention (TADA), and Graph Neural Networks (GNNs). By analyzing historical operational data, these models detect subtle fault patterns and predict failures, improving system reliability, reducing maintenance costs, and optimizing energy use. The work contributes to United Nations SDGs 11 and 9 by promoting sustainable urban infrastructure and smart city development, fostering a future where IoT and AI systems enhance sustainability and resilience. © 2024 IEEE.

关键词： Sustainable city

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：