检索结果-内蒙古大学图书馆

The B4-valued propositional logic with unary logical connectives ～1 /～2/┐

Frontiers of Computer Science 2017年第5期11卷 887-894页

作者： Wei LI Yuefei SUI State Key Laboratory of Software Development Environment Beijing University of Aeronautics and Astronautics Beijing 100191 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China

A B4-valued propositional logic will be proposed in this paper which there are three unary logical connectives ～1, ～2, ┐ and two binary logical connectives A, v, and a Gentzen-typed deduction system will be given s... 详细信息

关键词： the Belnap logic modality the soundness thecompleteness

来源：评论

学校读者我要写书评

暂无评论

Parallel finite element computation of incompressible magnetohydrodynamics based on three iterations

引用

Applied Mathematics and Mechanics(English Edition) 2022年第1期43卷 141-154页

作者： Qili TANG Yunqing HUANG Hunan Key Laboratory for Computation and Simulation in Science and Engineering Key Laboratory of Intelligent Computing&Information Processing of Ministry of EducationSchool of Mathematics and Computational ScienceXiangtan UniversityXiangtanHunan Province411105China

Based on local algorithms,some parallel finite element(FE)iterative methods for stationary incompressible magnetohydrodynamics(MHD)are *** approaches are on account of two-grid skill include two major phases:find the FE solution by solving the nonlinear system on a globally coarse mesh to seize the low frequency component of the solution,and then locally solve linearized residual subproblems by one of three iterations(Stokes-type,Newton,and Oseen-type)on subdomains with fine grid in parallel to approximate the high frequency *** error estimates with regard to two mesh sizes and iterative steps of the proposed algorithms are *** numerical examples are implemented to verify the algorithm.

关键词： local and parallel algorithm finite element(FE)method iteration stationary incompressible magnetohydrodynamics(MHD)

来源：评论

学校读者我要写书评

暂无评论

Single Cell RNA-Seq Analysis Reveals Similarities Between Colorectal, Liver and Lung T Cells’ Populations 2nd

Single Cell RNA-Seq Analysis Reveals Similarities Between Co...

引用

2nd International Conference on Applied Intelligence, ICAI 2024

作者： Saada, Bacem Qu, Chen Siga, Estevao Zhang, Jing Hematology Department Eighth Affiliated Hospital of Sun Yat Sen University Shenzhen China Cancer Institute Eighth Affiliated Hospital of Sun Yat Sen University Shenzhen China Animal Biosciences Department University of Guelph Guelph Canada Shenzhen International Institute for Biomedical Research Shenzhen China School of Information Science and Engineering University of Jinan Jinan China Shandong Provincial Key Laboratory of Network-Based Intelligent Computing Jinan China

ISBN: (纸本)9789819619061

In the fields of computational biology and healthcare systems, there is a growing use of genomic data from cancer to improve diagnostic accuracy and to formulate patient-specific tumor treatment strategies. Cancer genomics allow researchers to define the genome instabilities and mutations associated with tumor growth, poor diagnosis, and immune cells heterogeneity in the cancer context. This molecular taxonomy of cancer provides a more precise diagnosis to better fight solid tumors and enhance the treatment strategy. Single-cell RNA sequencing techniques in cancer re-search enable the detailed examination of gene expression on a cell-by-cell basis, shedding light on the diversity within the tumor microenvironment. In addition, they can reconstruct evolutionary lineages and detect rare subpopulations. It is important to perform pan-cancer analysis to examine the similarities and dissimilarities in different tumor microenvironments. This study provides a comprehensive comparative analysis of T-cell populations across breast, colorectal, liver, lung, and pancreatic cancers, unveiling T-cell heterogeneity and gene expression patterns specific to these tumors. By analyzing single-cell RNA sequencing data from breast, colorectal, liver, lung, and pancreatic cancers, our research fills a crucial gap in understanding the diverse immune environments of these malignancies. The study highlights similarities and differences in T-cell populations across these cancers, providing insights for cancer immunotherapy strategies. Our insights into gene expression correlations with tumor progression have significant implications for immunotherapy strategies, suggesting potential biomarkers for personalized treatment approaches and highlighting key molecular targets for future therapeutic development. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Lung cancer

来源：评论

学校读者我要写书评

暂无评论

An Efficient WRF Framework for Discovering Risk Genes and Abnormal Brain Regions in Parkinson's Disease Based on Imaging Genetics Data

引用

Journal of Computer Science & Technology 2021年第2期36卷 361-374页

作者： Xia-An Bi Zhao-Xu Xing Rui-Hui Xu Xi Hu College of Information Science and Engineering Hunan Normal UniversityChangsha 410006China Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing Hunan Normal UniversityChangsha 410006China

As an emerging research field of brain science,multimodal data fusion analysis has attracted broader attention in the study of complex brain diseases such as Parkinson's disease(PD).However,current studies primarily lie with detecting the association among different modal data and reducing data *** data mining method after fusion and the overall analysis framework are *** this study,we propose a weighted random forest(WRF)model as the feature screening *** interactions between genes and brain regions are detected as input multimodal fusion features by the correlation analysis *** implement sample classification and optimal feature selection based on WRF,and construct a multimodal analysis framework for exploring the pathogenic factors of *** experimental results in Parkinson's Progression Markers Initiative(PPMI)database show that WRF performs better compared with some advanced methods,and the brain regions and genes related to PD are *** fusion of multi-modal data can improve the classification of PD patients and detect the pathogenic factors more comprehensively,which provides a novel perspective for the diagnosis and research of *** also show the great potential of WRF to perform the multimodal data fusion analysis of other brain diseases.

关键词： multimodal fusion feature Parkinson's disease pathogenic factor detection sample classification weighted random forest model

来源：评论

学校读者我要写书评

暂无评论

Degradation-Trend-Aware Deep Neural network with Attention Mechanism for Bearing Remaining Useful Life Prediction

IEEE Transactions on Artificial Intelligence

引用

IEEE Transactions on Artificial Intelligence 2024年第6期5卷 2997-3011页

作者： Liu, Yongkang Pan, Donghui Zhang, Haifeng Zhong, Kai Anhui University Key Laboratory of Intelligent Computing and Signal Processing of the Ministry of Education School of Mathematical Sciences Hefei230601 China Anhui University Key Laboratory of Intelligent Computing and Signal Processing of the Ministry of Education Institutes of Physical Science and Information Technology Hefei230601 China

Remaining useful life (RUL) prediction of bearings has extraordinary significance for prognostics and health management (PHM) of rotating machinery. RUL prediction approaches based on deep learning have been dedicated to finding a nonlinear mapping relationship between nonstationary monitoring data and RUL. However, most existing approaches pay little attention to the degradation trend of diverse health stages of bearing and lack the discriminative power of crucial degradation features, resulting in the loss of some important information associated with RUL. To address this challenge, this article proposes a novel RUL prediction framework based on degradation-trend-aware deep neural network with attention mechanism (DTADAN). First the multidirection features with evident degradation trend are extracted via the analysis of bearing vibration signal from both time-domain and time-frequency domain. Next, the deep neural network architecture with attention mechanism is utilized to adaptively learn the critical degradation features beneficial for RUL prediction. Distinct from the existing approaches, the proposed framework is able to dynamically extract key degradation features of the bearing including degradation trend information and effectively fuse multidirection information to improve RUL prediction accuracy. The performance of the proposed approach is evaluated via case studies on XJTU-SY bearing dataset and PRONOSTIA bearing dataset. Compared with other state-of-the-art approaches, the proposed framework has better predictive accuracy and robustness. Additionally, interpretable analysis is provided to reveal the process of model learning and data characteristics, and the analysis results are helpful in guiding model learning. © 2020 IEEE.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Crank-Nicolson difference scheme for the coupled nonlinear Schrödinger equations with the Riesz space fractional derivative

引用

Journal of Computational Physics 2013年 242卷 670-681页

作者： Wang, Dongling Xiao, Aiguo Yang, Wei Hunan Key Laboratory for Computation and Simulation in Science and Engineering Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan Hunan 411105 China

In this paper, the Crank-Nicolson (CN) difference scheme for the coupled nonlinear Schrödinger equations with the Riesz space fractional derivative is studied. The existence of this difference solution is proved by the Brouwer fixed point theorem. The stability and convergence of the CN scheme are discussed in the L2 norm. When the fractional order is two, all those results are in accord with the difference scheme developed for the classical non-fractional coupled nonlinear Schrödinger equations. Some numerical examples are also presented. © 2013 Elsevier Inc.

关键词： Nonlinear equations

来源：评论

学校读者我要写书评

暂无评论

Numerical methods for fractional variational problems depending on indefinite integrals

引用

Journal of Computational and Nonlinear Dynamics 2013年第2期8卷 021018页

作者： Wang, Dongling Xiao, Aiguo Hunan Key Laboratory for Computation and Simulation in Science and Engineering Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan Hunan 411105 China

In this paper, the fractional variational integrators for fractional variational problems depending on indefinite integrals in terms of the Caputo derivative are developed. The corresponding fractional discrete Euler-Lagrange equations are derived. Some fractional variational integrators are presented based on the Grünwald-Letnikov formula. The fractional variational errors are discussed. Some numerical examples are given to illustrate these results. Copyright © 2013 by ASME.

关键词： Numerical methods

来源：评论

学校读者我要写书评

暂无评论

WLAN indoor positioning method based on gradient boosting and particle filtering

引用

International Journal of Simulation and Process Modelling 2019年第6期14卷 535-545页

作者： Hu, Libin Li, Zhongtao Yang, Xinghai Wei, Changzhi Shandong Provincial Key Laboratory of Network Based Intelligent Computing School of Information Science and Engineering University of Jinan Jinan China

Indoor positioning technology has shown its great application prospects in smart cities. The main purpose of this paper is to study a low-cost, low-error indoor positioning method that can get a accurate indoor position when communicating with wireless local area networks (WLAN). The paper optimises the traditional WLAN indoor positioning method based on location fingerprint database, and algorithms about in indoor signal simulation, similarity matching of vector and continuously-positioning are tested in work of this paper, and a WLAN indoor positioning method based on gradient boosting and particle filtering is proposed. The paper finally shows the indoor positioning result with an average error of 1.7 metres. These research results verify the feasibility of WLAN indoor positioning and show that the positioning accuracy will be improved with the further optimisation of the positioning method. The potential application values of WLAN technology make it more convenient for internet of things (IoT) technology. Copyright © 2019 Inderscience Enterprises Ltd.

关键词： Indoor positioning systems

来源：评论

学校读者我要写书评

暂无评论

Mobility-aware Seamless Service Migration and Resource Allocation in Multi-edge IoV Systems

arXiv

引用

arXiv 2025年

作者： Chen, Zheyi Huang, Sijin Min, Geyong Ning, Zhaolong Li, Jie Zhang, Yan College of Computer and Data Science Fuzhou University Fuzhou350116 China Engineering Research Center of Big Data Intelligence Ministry of Education Fujian Key Laboratory of Network Fuzhou350002 China Computing and Intelligent Information Processing [Fuzhou University Fuzhou350116 China Department of Computer Science Faculty of Environment Science and Economy University of Exeter ExeterEX4 4QF United Kingdom School of Communications and Information Engineering Chongqing University of Posts and Telecommunications Chongqing400065 China Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai200240 China Department of Informatics University of Oslo Oslo0316 Norway

Mobile Edge computing (MEC) offers low-latency and high-bandwidth support for Internet-of-Vehicles (IoV) applications. However, due to high vehicle mobility and finite communication coverage of base stations, it is hard to maintain uninterrupted and high-quality services without proper service migration among MEC servers. Existing solutions commonly rely on prior knowledge and rarely consider efficient resource allocation during the service migration process, making it hard to reach optimal performance in dynamic IoV environments. To address these important challenges, we propose SR-CL, a novel mobility-aware seamless Service migration and Resource allocation framework via Convex-optimization-enabled deep reinforcement Learning in multi-edge IoV systems. First, we decouple the Mixed Integer Nonlinear Programming (MINLP) problem of service migration and resource allocation into two sub-problems. Next, we design a new actor-critic-based asynchronous-update deep reinforcement learning method to handle service migration, where the delayed-update actor makes migration decisions and the one-step-update critic evaluates the decisions to guide the policy update. Notably, we theoretically derive the optimal resource allocation with convex optimization for each MEC server, thereby further improving system performance. Using the real-world datasets of vehicle trajectories and testbed, extensive experiments are conducted to verify the effectiveness of the proposed SR-CL. Compared to benchmark methods, the SR-CL achieves superior convergence and delay performance under various scenarios. Copyright © 2025, The Authors. All rights reserved.

关键词： Convex optimization

来源：评论

学校读者我要写书评

暂无评论

DRLO: Optimizing edge server placement in dynamic MEC scenarios using deep reinforcement learning

引用

Computer networks 2025年 268卷

作者： Yingya Guo Cen Chen College of Computer and Data Science Fuzhou University PR China Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University PR China Engineering Research Center of Big Data Intelligence Ministry of Education Fujian PR China

As an emerging computing paradigm, Mobile Edge computing (MEC) significantly enhances user experience and alleviates network congestion by strategically deploying edge servers in close proximity to mobile users. However, the effectiveness of MEC hinges on the precise placement of these edge servers, a critical factor in determining the Quality of Experience (QoE) for mobile users. While existing studies predominantly focus on optimizing edge server placement in static scenarios, they often fall short when faced with user mobility, resulting in a degradation of QoE. To address this challenge, we propose an adaptive edge server placement approach that leverages Deep Reinforcement Learning (DRL) to select the base stations for placing edge servers in a dynamic MEC environment. Our objective is to minimize access delay by optimizing edge server placement for adapting to dynamic environment. To tackle the vast action space associated with edge server placement, we introduce a novel activation function in the actor neural network for efficient exploration. Furthermore, to enhance the adaptability of the derived edge server placement strategy, we meticulously design a new reward function, which takes into account the minimization of total access delay within dynamic MEC scenarios. Finally, to validate the effectiveness of our proposed method, extensive experiments were conducted using the Shanghai Telecom dataset. The results demonstrate that our approach outperforms baseline methods in minimizing access delay for users in dynamic MEC scenarios.

关键词：

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：