检索结果-内蒙古大学图书馆

Using NSGA-Ⅲ for optimising biomedical ontology alignment

CAAI Transactions on Intelligence Technology 2019年第3期4卷 135-141页

作者： Xingsi Xue Jiawei Lu Junfeng Chen College of Information Science and Engineering Fujian University of TechnologyFuzhouFujianPeople’s Republic of China Intelligent Information Processing Research Center Fujian University of TechnologyFuzhouFujianPeople’s Republic of China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of TechnologyFuzhouFujianPeople’s Republic of China Fujian Key Laboratory for Automotive Electronics and Electric Drive Fujian University of TechnologyFuzhouFujianPeople’s Republic of China College of IOT Engineering Hohai UniversityChangzhouJiangsuPeople’s Republic of China

To support semantic inter-operability between the biomedical information systems, it is necessary to determine the correspondences between the heterogeneous biomedical concepts, which is commonly known as biomedical ontology matching. Biomedical concepts are usually complex and ambiguous, which makes matching biomedical ontologies a challenge. Since none of the similarity measures can distinguish the heterogeneous biomedical concepts in any context independently, usually several similarity measures are applied together to determine the biomedical concepts mappings. However, the ignorance of the effects brought about by different biomedical concept mapping’s preference on the similarity measures significantly reduces the alignment’s quality. In this study, a non-dominated sorting genetic algorithm (NSGA)-III-based biomedical ontology matching technique is proposed to effectively match the biomedical ontologies, which first utilises an ontology partitioning technique to transform the large-scale biomedical ontology matching problem into several ontology segment-matching problems, and then uses NSGA-III to determine the optimal alignment without tuning the aggregating weights. The experiment is conducted on the anatomy track and large biomedic ontologies track which are provided by the Ontology Alignment Evaluation Initiative (OAEI), and the comparisons with OAEI’s participants show the effectiveness of the authors’ approach.

关键词： ontology ontologies transform together Ontology complex context effects

来源：评论

学校读者我要写书评

暂无评论

LG-Umer: UNet-like Network Integrate Local-Global Feature with Novel Attention for Road Extraction from Remote Sensing Images

引用

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2025年

作者： Niu, Penghui Cai, Taotao Zhang, Yajuan Zhang, Ping Xu, Wenjia Gu, Junhua Han, Jungong Hebei University of Technology School of Artificial Intelligence Tianjin300401 China University of Southern Queensland Toowoomba487- 535 Australia Hebei Prospecting Institute of Hydrogeology and Engineering Geological Shijiazhuang050021 China Hebei University of Technology Hebei Province Key Laboratory of Big Data Calculation Tianjin300401 China University of Sheffield Department of Computer Science S10 2TN United Kingdom

Road extraction from remote sensing images (RSIs) is a key research area in smart city development. While deep learning techniques have demonstrated remarkable effectiveness in this domain, existing approaches exhibit limitations: convolutional neural network (CNN)-based methods struggle to capture global contextual information for long-range road networks, vision transformer (ViT)-based methods fail to adequately extract multi-scale local features, and hybrid CNN-ViT architectures overlook the synergistic guidance between local and global features. To address these challenges, we propose LG-Umer, a UNet-like network that integrates Local-Global features with a novel attention mechanism, combining the complementary strengths of CNNs and ViTs within an encoder-decoder framework. Specifically, the encoder employs a Multi-scale Strip Deformational (MSD) module, which utilizes deformable convolutions to adaptively extract topological structures and variable-shaped local road features. In the decoder, a Multi-stage Gate Unit (MGU) module is introduced, incorporating a novel attention mechanism to model long-range dependencies by leveraging local features as attention operators for global feature refinement. Extensive experiments on three public benchmarks demonstrate the superiority of LG-Umer. It achieves IoU scores of 70.4%, 71.2% and 68.7% on the Massachusetts Road, DeepGlobe Road, and CHN6-CUG datasets, respectively, surpassing recent state-ofthe-art (SOTA) methods by 1.2%, 0.9%, and 1.1%. These results validate the effectiveness of our approach in balancing local detail preservation and global contextual modeling for road extraction tasks. © 2008-2012 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Forecasting Chinese Stock Market Prices using Baidu Search Index with a Learning-Based data Collection Method

Forecasting Chinese Stock Market Prices using Baidu Search I...

引用

作者： Dong, Jichang Dai, Wei Liu, Ying Yu, Lean Wang, Jie School of Economics and Management University of Chinese Academy of Sciences Beijing100190 China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing100190 China School of Economics and Management Beijing University of Chemical Technology Beijing100029 China Department of Civil and Environmental Engineering Stanford University StanfordCA94305 United States

In this study, to address search index selection and volatility problems, we propose a learning-based search index collection method that collects the search data fraction for modeling by learning the best criteria from robust statistics. Based on the fraction of collected search index from internet search engine (***) data sources, a novel model is formulated for Chinese stock market price forecasting. We empirically test our method on the two main Chinese stock market price indexes and discover that the prediction accuracy is equivalent or superior to the benchmarks from previous studies that used alternative search index collection methods or lagged data prediction models. All prediction results outstand the importance of an effective data collection method for the robustness of forecast models and demonstrate the utility of a learning-based collection method for addressing search index collection problem, leading to a significant improvement in Chinese stock market price prediction accuracy. © 2019 World Scientific Publishing Company.

关键词： Search engines

来源：评论

学校读者我要写书评

暂无评论

Research on KDT-DBSCAN-based Personal Semantic Location Acquisition

Research on KDT-DBSCAN-based Personal Semantic Location Acqu...

引用

第32届中国控制与决策会议

作者： Rong Nie Zixuan Yao Dong Wei Kaizhang Hou Jishuai Lin Beijing Engineering Research Center of Security Alarm and Security Check School of Electrical and Information Engineering Beijing University of Civil Engineering and Architecture Beijing Key Laboratory of Intelligent Processing for Building Big Data Beijing Municipal Science and Technology Commission Haidian Branch of Beijing Public Security Bureau

With the development of science and technology in recent years,the planning and construction of smart cities have entered a new *** them,smart city safety management is the foundation that supports the stable development of the entire city,and location-based services are one of its important technical *** popularity of GPS-equipped devices provides a large amount of data for trajectory *** personal semantic locations by mining these data is an application based on location *** semantic locations are frequently visited by individual users and have significant semantic meaning to users（such as home,work place,etc.）.The discovery of the user’s personal semantic location involves obtaining the physical location and *** present,related research mostly uses clustering algorithms to obtain the physical location,of which the DBSCAN algorithm is the most commonly *** the traditional DBSCAN algorithm determines whether a sample belongs to a certain cluster,it will generate a large number of repeated calculations,which will reduce the program operation *** order to solve this problem,this paper proposes an improved DBSCAN algorithm *** algorithm uses a k-d tree to screen samples that need to be *** excluding samples that do not need to be calculated,the purpose of improving the calculation efficiency can be *** the problem of semantic location recognition,this paper pre-defines the daily behavior patterns of people,and identifies the location semantics based on the temporal characteristics of the samples in each *** calculating the distance between samples,the algorithm proposed here is 8.8 times more efficient than the traditional algorithm.

关键词： Personal Semantic Location DBSCAN K-D Tree

来源：评论

学校读者我要写书评

暂无评论

Kernelized multiview subspace analysis by self-weighted learning

arXiv

引用

arXiv 2019年

作者： Wang, Huibing Wang, Yang Zhang, Zhao Fu, Xianping Wang, Meng College of Information and Science Technology Dalian Maritime University Dalian Liaoning116021 China Key Laboratory of Knowledge Engineering with Big Data Ministry of Education Hefei University of Technology China

—With the popularity of multimedia technology, information is always represented or transmitted from multiple views. Most of the existing algorithms are graph-based ones to learn the complex structures within multiview data but overlooked the information within data representations. Furthermore, many existing works treat multiple views discriminatively by introducing some hyperparameters, which is undesirable in practice. To this end, abundant multiview based methods have been proposed for dimension reduction. However, there are still no research to leverage the existing work into a unified framework. To address this issue, in this paper, we propose a general framework for multiview data dimension reduction, named Kernelized Multiview Subspace Analysis (KMSA). It directly handles the multi-view feature representation in the kernel space, which provides a feasible channel for direct manipulations on multiview data with different dimensions. Meanwhile, compared with those graph-based methods, KMSA can fully exploit information from multiview data with nothing to lose. Furthermore, since different views have different influences on KMSA, we propose a self-weighted strategy to treat different views discriminatively according to their contributions. A co-regularized term is proposed to promote the mutual learning from multi-views. KMSA combines self-weighted learning with the co-regularized term to learn appropriate weights for all views. We also discuss the influence of the parameters in KMSA regarding the weights of multi-views. We evaluate our proposed framework on 6 multiview datasets for classification and image retrieval. The experimental results validate the advantages of our proposed method. Copyright © 2019, The Authors. All rights reserved.

关键词： Multimedia systems

来源：评论

学校读者我要写书评

暂无评论

ΛcN interaction in leading-order covariant chiral effective field theory

引用

Physical Review C 2020年第6期102卷 065208-065208页

作者： Jing Song Yang Xiao Zhi-Wei Liu Chun-Xuan Wang Kai-Wen Li Li-Sheng Geng School of Physics Beihang University Beijing 102206 China Université Paris-Saclay CNRS/IN2P3 IJCLab Orsay 91405 France Beijing Advanced Innovation Center for Big Data-Based Precision Medicine School of Medicine and Engineering Beihang University Key Laboratory of Big Data-Based Precision Medicine (Beihang University) Ministry of Industry and Information Technology Beijing 100191 China Beijing Key Laboratory of Advanced Nuclear Materials and Physics Beihang University Beijing 102206 China School of Physics and Microelectronics Zhengzhou University Zhengzhou Henan 450001 China

We study the ΛcN interaction in the covariant chiral effective field theory (ChEFT) at leading order. All the relevant low-energy constants are determined by fitting to the lattice QCD simulations from the HAL QCD Collaboration. Extrapolating the results to the physical point, we show that the ΛcN interaction is weakly attractive in the S01 channel, but in the S13 channel it is only attractive at extremely low energies and soon turns repulsive for larger laboratory energy. Furthermore, we show that the neglect of the S13−D13 coupling provided by the leading-order covariant ChEFT would result in an attractive interaction in the S13 channel at the physical point, which coincides with the previous nonrelativistic ChEFT study. As a byproduct, we predict the D13 phase shifts and the mixing angel ɛ1, which can be checked by future lattice QCD simulations. In addition, we compare the ΛcN interaction with the ΛN and NN interactions to study how the baryon-nucleon (BN) interactions evolve as a function of the baryon mass with the replacement of a light quark by a strange or charm quark in the baryon (B).

关键词： Effective field theory Hadron-hadron interactions Lattice QCD QCD in nuclear reactions

来源：评论

学校读者我要写书评

暂无评论

Ready for emerging threats to recommender systems? A graph convolution-based generative shilling attack

arXiv

引用

arXiv 2021年

作者： Wu, Fan Gao, Min Yu, Junliang Wang, Zongwei Liu, Kecheng Wang, Xu Key Laboratory of Dependable Service Computing in Cyber Physical Society Chongqing University Ministry of Education Chongqing401331 China School of Big Data and Software Engineering Chongqing University Chongqing401331 China School of Information Technology and Electrical Engineering The University of Queensland Queensland4072 Australia Informatics Research Centre Henley Business School University of Reading Berkshire ReadingRG6 6UD United Kingdom School of Mechanical Engineering Chongqing University Chongqing400044 China

To explore the robustness of recommender systems, researchers have proposed various shilling attack models and analyzed their adverse effects. Primitive attacks are highly feasible but less effective due to simplistic handcrafted rules, while upgraded attacks are more powerful but costly and difficult to deploy because they require more knowledge from recommendations. In this paper, we explore a novel shilling attack called Graph cOnvolution-based generative shilling ATtack (GOAT) to balance the attacks' feasibility and effectiveness. GOAT adopts the primitive attacks' paradigm that assigns items for fake users by sampling and the upgraded attacks' paradigm that generates fake ratings by a deep learning-based model. It deploys a generative adversarial network (GAN) that learns the real rating distribution to generate fake ratings. Additionally, the generator combines a tailored graph convolution structure that leverages the correlations between co-rated items to smoothen the fake ratings and enhance their authenticity. The extensive experiments on two public datasets evaluate GOAT's performance from multiple perspectives. Our study of the GOAT demonstrates technical feasibility for building a more powerful and intelligent attack model with a much-reduced cost, enables analysis the threat of such an attack and guides for investigating necessary prevention measures. Copyright © 2021, The Authors. All rights reserved.

关键词： Recommender systems

来源：评论

学校读者我要写书评

暂无评论

Effect of Functional Groups of Hydration Heat Controlling Materials on Cement Hydration and its Mechanism

SSRN

引用

SSRN 2022年

作者： Liu, Xiao Xie, Hui Luo, Qifeng Xia, Chunlei Ding, Yungchin Chen, Yichen Gao, Ruijun Wei, Zhongyuan Bai, Xiabing He, Rui Zhou, Wu Zhou, Xiangzheng Wang, Ziming Cui, Suping Faculty of Materials and Manufacturing Key Laboratory of Advanced Functional Materials Ministry of Education Beijing University of Technology Beijing100024 China Beijing Municipal Engineering Research Institute Beijing100037 China Institute of Mineral Resources Engineering National Taipei University of Technology Taipei10608 Taiwan China Building Materials Academy Beijing100024 China Tangshan Longyi Tech. Co. Ltd. Tangshan063004 China Beijing NAURA Microelectronics Equipment Co. Ltd. Beijing100176 China Engineering Research Center of Transportation Materials of Ministry of Education Chang’ an University Xi'An710061 China Guangxi Keda Building Material Chemicals Co. Ltd. Nanning530221 China Faculty of Materials and Manufacturing National Engineering Laboratory for Industrial Big-data Application Technology Beijing University of Technology Beijing100124 China

Severe temperature rise of mass concrete caused by cement hydration can lead to thermal cracks which further reduce the durability of concrete. In this study, three types of hydration heat controlling materials (HHCMs) respectively containing pure hydroxyl (polyvinyl alcohol, PVA), carboxyl (polyacrylic acid, PAA) and ester groups (maleic acid-ethylene glycol ester, P(MA-EG)) were synthesized and mixed with cement-based materials, and the hydration heat and setting time of cement pastes and the adiabatic temperature rise and strength of mortars were tested. The results showed that PAA and P(MA-EG) reduced the peak value of hydration heat release rate of cement paste by 77.45% and 62.28% respectively, and prolonged 54.14h and 15.56h respectively. The cumulative heat release within 72h decreased by 42.42% and 64.50% respectively, and the central temperatures of mortars containing PAA and P(MA-EG) decreased by 11.9 °C and 18.5 °C respectively. The mechanism of HHCMs was further revealed in terms of adsorption capacity, hydrodynamic radius, and conductivity and hydration products of cement pastes. The HHCMs containing carboxyl or hydroxyl groups, adsorbed on cement particles by Ca 2+ complexation, while the HHCMs containing ester groups, i.e. P(MA-EG), continuously hydrolyzed to carboxyl groups in alkaline cement pastes, which hydrolysis rate changed with the hydration temperature of cement-based materials to further regulate the hydration process. This study aims to provide technical feasibility and theoretical basis for exploring new avenues of synthesizing HHCMs with different functional groups. These novel HHCMs with great potentials can be as new admixtures to reduce thermal cracks in concrete. © 2022, The Authors. All rights reserved.

关键词： Ethylene glycol

来源：评论

学校读者我要写书评

暂无评论

Multi-objective Cross-layer Resource Scheduling for Internet of Things in Edge-Cloud Computing

Multi-objective Cross-layer Resource Scheduling for Internet...

引用

IEEE International Conference on Cloud Computing, CLOUD

作者： Ruichao Mo Fei Dai Qi Liu Wanchun Dou Xiaolong Xu School of Computer and Software Nanjing University of Information Science and Technology Nanjing China School of Big Data and Intelligence Engineering Southwest Forestry University Kunming China State Key Laboratory for Novel Software Technology Nanjing University Nanjing China

ISBN: (数字)9781728187808

ISBN: (纸本)9781728187815

Nowadays, Edge computing is being introduced as a powerful paradigm to collaborate with the cloud to provide sufficient computing resources for IoT to implement intelligent analysis and data mining. Generally, due to the edge nodes are closer to mobile users, the access latency and the cost of using cloud services are effectively reduced. However, the implementation of cross-layer resource scheduling between edge nodes and servers deployed in the cloud to meet service requirements (i.e., shortest completion time, maximum resource utilization, lower energy consumption, etc.) still faces great challenges. To address this challenge, a cross-layer resource scheduling method, named CRSM, for the IoT applications is proposed in this paper. Technically, the Pareto archived evolution strategy (PAES) is employed to optimize the time cost of IoT applications, resource utilization and energy consumption of edge node. Then, the technique for order preference by similarity to ideal solution (TOPSIS) and the multiple criteria decision making (MCDM) are leveraged to acquired the optimal cross-layer resource scheduling strategy. Finally, the comprehensive analysis of CRSM is introduced in detail.

关键词： Cloud computing Energy consumption Processor scheduling Internet of Things Resource management Servers Faces

来源：评论

学校读者我要写书评

暂无评论

Substrate-independent nano-coating with persistent antibacterial and tooth whitening activities for dental health

引用

Chinese Chemical Letters 2025年

作者： Yi Liu Xiaolin Yu Wenyun Mu Minsi Meng Baixue Li Jie Liu Haixin Qian Lin Weng Tingting Yu Nan Hu Xin Chen Yi Hao College of Chemical Engineering Sichuan University of Science & Engineering Zigong 643000 China Institute of Precision Medicine Zigong Academy of Big Data and Artificial Intelligence in Medical Science Zigong Fourth People's Hospital Zigong 643000 China Department of Chemical Engineering Shaanxi Key Laboratory of Energy Chemical Process Intensification Institution of Polymer Science in Chemical Engineering School of Chemical Engineering and Technology Xi'an Jiaotong University Xi'an 710049 China Sichuan Clinical Research Center for Clinical Laboratory Zigong Fourth People's Hospital Zigong 643000 China Department of Laboratory Medicine Zigong Fourth People's Hospital Zigong 643000 China Department of Prosthodontics Shanghai Ninth People's Hospital College of Stomatology Shanghai Jiao Tong University School of Medicine National Clinical Research Center of Stomatology Shanghai Key Laboratory of Stomatology and Shanghai Research Institute of Stomatology Shanghai 200240 China

Bacteria and stains on tooth and various dental materials severely harm dental health and beauty and require feasible solutions. In this study, a simple strategy was developed to produce nano-coating on different substrates for persistent antibacterial and whitening. The coating is formed by the lysozyme (Lys), hemoglobin (Hb), and glucose oxidase (GOD) via co-assembly, in which the phase transition of Lys initiated the co-assembly to anchor other two proteins. During therapy, the GOD continuously oxidizes glucose in the oral environment to cut off the nutrition of bacteria meanwhile generating H 2 O 2 , which would be further catalyzed by the ferrous ions in Hb to produce reactive oxygen species (ROS) for effective decomposition of surrounding bacteria and stains. Moreover, the Hb can perform persistent release of oxygen, which not only enhances the efficiency of glucose oxidation to produce more ROS but directly suppresses anaerobic bacteria via reversing the local hypoxia environment in the mouth. The experimental results indicated that our strategy is able to form nano-film of proteins both on the surface of dental orthosis and human tooth, which further causes obvious reduction of the bacteria not only on the coated substrate but in the surrounding tissue with up to 100% of the bacteriostatic rate. In addition, both the dental orthosis and human tooth were also rapidly cleaned due to the local ROS generation, leading to a sustained anti-staining property in the long term.

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：