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An alert-situation text data augmentation method based on MLM

High technology Letters 2024年第4期30卷 389-396页

作者： DING Weijie MAO Tingyun CHEN Lili ZHOU Mingwei YUAN Ying HU Wentao Department of Computer and Information Security Zhejiang Police CollegeHangzhou 310053P.R.China Key Laboratory of Public Security Information Application Based on Big-Data Architecture Ministry of Public SecurityHangzhou 310053P.R.China Zhejiang Dahua Technology Co. LtdHangzhou 310053P.R.China

The performance of deep learning models is heavily reliant on the quality and quantity of train-ing *** training data will lead to ***,in the task of alert-situation text classification,it is usually difficult to obtain a large amount of training *** paper proposes a text data augmentation method based on masked language model(MLM),aiming to enhance the generalization capability of deep learning models by expanding the training *** method em-ploys a Mask strategy to randomly conceal words in the text,effectively leveraging contextual infor-mation to predict and replace masked words based on MLM,thereby generating new training *** Mask strategies of character level,word level and N-gram are designed,and the performance of each Mask strategy under different Mask ratios is analyzed and *** experimental results show that the performance of the word-level Mask strategy is better than the traditional data augmen-tation method.

关键词： deep learning text data augmentation masked language model(MLM) alert-sit-uation text classification

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A Multi-attribute Decision-making based Importance Assessment Method of Sensor Nodes 3

A Multi-attribute Decision-making based Importance Assessmen...

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3rd International Symposium on Computer technology and Information Science, ISCTIS 2023

作者： Duan, Xiusheng Yang, Jingchao Kong, Dehan Zhang, Weilong Hebei Polytechnic Institute Department of Artificial Intelligence and Big Data China Hebei Jiaotong Vocational and Technical College Shijiazhuang China Hebei Provincial University Road Traffic Perception Intelligent Application Technology Research and Development Center China Hebei University of Environmental Engineering Department of Information Engineering Qinhuangdao China

ISBN: (纸本)9798350325386

In this paper, an air defense early warning sensor network node importance assessment method based on multi-attribute decision was proposed. Firstly, according to the characteristics of the air defense early warning sensor network, the factors that affect the node importance degree were analyzed, and the node importance degree was divided into three aspects, which were performance importance degree, function importance degree and structure importance degree. Secondly, three calculation methods of importance degree were introduced. Then the synthesis method of comprehensive importance degree based on TOPSIS method was proposed. Finally, the validity of the method and model proposed in this paper was verified. © 2023 IEEE.

关键词： Sensor nodes

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Social inequity of park accessibility in Taiyuan:highlighting the unfair layout of parks in second-tier cities of China and the relative role of contributors

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地球空间信息科学学报（英文版） 2024年第4期27卷 1118-1140页

作者： Jing He Fu Ren Jiaxin Dong Huihui Zhang Wenhao Yan Jiping Liu School of Resource and Environmental Sciences Wuhan UniversityWuhanChina School of Resource and Environmental Sciences Wuhan UniversityWuhanChina Key Laboratory of Geographic Information Systems Ministry of EducationWuhan UniversityWuhanChina School of Remote Sensing and Information Engineering Wuhan UniversityWuhanChina Guangdong Provincial Department of Natural Resources Land and Resources Technology CenterGuangzhouChina Research Center of Geospatial Big Data Application Chinese Academy of Surveying and MappingBeijingChina

The scarcity of public resources and environmental pollution caused by rapid urbanization highlight the practical significance of parks in ensuring the sustainable development of a ***,the social equity of parks warrants further *** paper proposes a fine-grained comprehensive evaluation framework that combines geographic accessibility models,geo-statistical analysis,and machine learning algorithms to explore social inequity in Taiyuan,*** this framework,gini coefficient and lorentz curve express spatial equality,accessibility shows spatial equity,and ridge regression model handles the interdependence of variables with different dimensions to quantify the relative effects of local participants on changes in park *** this basis,the imbalance between vulnerable groups and park supply is analyzed to further understand the core concept of social *** highlight serious spatial inequality in all three types of parks allocation of six urban areas,especially in commu-nity *** actual access level of people to parks is also stratified by their demographic and socioeconomic characteristics,revealing the social inequity in access to *** distribution is indeed not conducive to some social vulnerable groups,whose contradiction between supply and demand is highly prominent in urban-rural junctions and new urban *** paper also confirms the unfair layout of public facilities can be observed in second-tier cities of China by highlighting the social inequity of parks in *** findings of this work have profound implications for urban planning and sustainable development.

关键词： Parks social inequity spatial equality accessibility social vulnerable groups Taiyuan

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A BPNN-Based Method for Regional Competitiveness: Taking the Guangdong-Hong Kong-Macau Greater Bay Area as an Example 2nd

A BPNN-Based Method for Regional Competitiveness: Taking the...

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2nd World Conference on Intelligent and 3D Technologies, WCI3DT 2023

作者： Wang, Mini Han Li, Pengsheng Wang, Fengling Zhou, Xiaoshu Wu, Qing Chen, Guoqiang Lin, Zhiyuan Zeng, Peijin Xiao, Qide Beijing Institute of Technology Zhuhai China Faculty of Data Science City University of Macau Macau China Department of Big Data and Artificial Intelligence Zhuhai Institute of Advanced Technology Chinese Academy of Sciences Zhuhai China Hezhou University Hezhou China Gree Polytechnic Zhuhai China Zhuhai Science and Technology Development Promotion Association Zhuhai China

ISBN: (纸本)9789819721436

Guangdong-Hong Kong-Macau Greater Bay Area (GBA) reveals a significant opportunity for self-developing and regional competition since China’s government regards it as one of the most significant developing strategies. However, cities in this area are enhancing comprehensive competitiveness at different levels. This paper proposed a competitiveness evaluation model based on the entropy approach and built a competitiveness measuring and predictive model based on the BPNN machine learning algorithm. The research results illustrate that comprehensive competitiveness is approximately increasing over time, which shows a trend of eastward development. Hong Kong, Guangzhou, Shenzhen, Macau, and Dongguan are the top-5 cities during the three years. On the contrary, Zhongshan is the least competitive city, however, Zhongshan‘s comprehensive competitiveness emerges at the highest increasing rate. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Adversarial machine learning

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Feature deformation network with multi-range feature enhancement for agricultural machinery operation mode identification

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International Journal of Agricultural and Biological Engineering 2024年第4期17卷 265-275页

作者： Weixin Zhai Zhi Xu Jinming Liu Xiya Xiong Jiawen Pan Sun-Ok Chung Dionysis Bochtis Caicong Wu College of Information and Electrical Engineering China Agricultural UniversityBeijing 100083China Key Laboratory of Agricultural Machinery Monitoring and Big Data Application Ministry of Agriculture and Rural AffairsBeijing 100083China Department of Smart Agricultural Systems Graduate SchoolChungnam National UniversityDaejeon 34134Republic of Korea Institute for Bio-Economy and Agri-Technology(iBO) Centre for Research and Technology-Hellas(CERTH)Thessaloniki 57001Greece

Utilizing the spatiotemporal features contained in extensive trajectory data for identifying operation modes of agricultural machinery is an important basis task for subsequent agricultural machinery trajectory *** the present study,to effectively identify agricultural machinery operation mode,a feature deformation network with multi-range feature enhancement was ***,a multi-range feature enhancement module was developed to fully explore the feature distribution of agricultural machinery trajectory ***,to further enrich the representation of trajectories,a feature deformation module was proposed that can map trajectory points to high-dimensional space to form feature ***,EfficientNet-B0 was used to extract features of different scales and depths from the feature map,select features highly relevant to the results,and finally accurately predict the mode of each trajectory *** validate the effectiveness of the proposed method,experiments were conducted to compare the results with those of other methods on a dataset of real agricultural *** the corn and wheat harvester trajectory datasets,the model achieved accuracies of 96.88%and 96.68%,as well as F1 scores of 93.54%and 94.19%,exhibiting improvements of 8.35%and 9.08%in accuracy and 20.99%and 20.04%in F1 score compared with the current state-of-the-art method.

关键词： road-field trajectory classification efficientNet feature deformation network multi-range feature enhancement agricultural machinery operation mode recognition

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RailPC: A large-scale railway point cloud semantic segmentation dataset

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CAAI Transactions on Intelligence technology 2024年第6期9卷 1548-1560页

作者： Tengping Jiang Shiwei Li Qinyu Zhang Guangshuai Wang Zequn Zhang Fankun Zeng Peng An Xin Jin Shan Liu Yongjun Wang Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing Normal UniversityNanjingChina Technology Innovation Center for Integrated Applications in Remote Sensing and Navigation Ministry of Natural ResourcesNanjingChina Eastern Institute of Technology(EIT) NingboChina Tianjin Key Laboratory of Rail Transit Navigation Positioning and Spatio-temporal Big Data Technology TianjinChina College of Computer Science and Engineering Northwest Normal UniversityLanzhouChina Mckelvey School of Engineering Washington University in St.LouisSt.LouisMissouriUSA School of Electronic and Information Engineering Ningbo University of TechnologyNingboChina

Semantic segmentation in the context of 3D point clouds for the railway environment holds a significant economic value,but its development is severely hindered by the lack of suitable and specific ***,the models trained on existing urban road point cloud datasets demonstrate poor generalisation on railway data due to a large domain gap caused by non-overlapping special/rare categories,for example,rail track,track bed *** harness the potential of supervised learning methods in the domain of 3D railway semantic segmentation,we introduce RailPC,a new point cloud *** provides a large-scale dataset with rich annotations for semantic segmentation in the railway ***,RailPC contains twice the number of annotated points compared to the largest available mobile laser scanning(MLS)point cloud dataset and is the first railway-specific 3D dataset for semantic *** covers a total of nearly 25 km railway in two different scenes(urban and mountain),with 3 billion points that are finely labelled as 16 most typical classes with respect to railway,and the data acquisition process is completed in China by MLS *** extensive experimentation,we evaluate the performance of advanced scene understanding methods on the annotated dataset and present a synthetic analysis of semantic segmentation *** on our findings,we establish some critical challenges towards railway-scale point cloud semantic *** dataset is available at https://***/NNU-GISA/GISA-RailPC,and we will continuously update it based on community feedback.

关键词： data benchmark MLS point clouds railway scene semantic segmentation

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Graph Regularized Sparse Non-Negative Matrix Factorization for Clustering

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IEEE Transactions on Computational Social Systems 2023年第3期10卷 910-921页

作者： Deng, Ping Li, Tianrui Wang, Hongjun Wang, Dexian Horng, Shi-Jinn Liu, Rui Southwest Jiaotong University National Engineering Laboratory of Integrated Transportation Big Data Application Technology School of Computing and Artificial Intelligence Chengdu611756 China National Taiwan University of Science and Technology Department of Computer Science and Information Engineering Taipei106 Taiwan North Sichuan Medical College School of Preclinical Medicine Department of Computer and Mathematics Nanchong637100 China

The graph regularized nonnegative matrix factorization (GNMF) algorithms have received a lot of attention in the field of machine learning and data mining, as well as the square loss method is commonly used to measure the quality of reconstructed data. However, noise is introduced when data reconstruction is performed;and the square loss method is sensitive to noise, which leads to degradation in the performance of data analysis tasks. To solve this problem, a novel graph regularized sparse NMF (GSNMF) is proposed in this article. To obtain a cleaner data matrix to approximate the high-dimensional matrix, the l1-norm to the low-dimensional matrix is added to achieve the adjustment of data eigenvalues in the matrix and sparsity constraint. In addition, the corresponding inference and alternating iterative update algorithm to solve the optimization problem are given. Then, an extension of GSNMF, namely, graph regularized sparse nonnegative matrix trifactorization (GSNMTF), is proposed, and the detailed inference procedure is also shown. Finally, the experimental results on eight different datasets demonstrate that the proposed model has a good performance. © 2014 IEEE.

关键词： Matrix algebra

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Is Green Energy the Pathway to Sustainability? – An Explanation From the Perspective of Degrowth Theory

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Strategic Planning for Energy and the Environment 2024年第4期43卷 761-790页

作者： Yuan, Yiming Li, Li Zhang, Rui School of Economics and Management Beijing Information Science & Technology University Beijing100192 China Laboratory of Big Data Decision Making for Green Development Beijing Information Science & Technology University Beijing China Beijing International Science and Technology Cooperation Base of Intelligent Decision Making and Big Data Application Beijing Information Science & Technology University Beijing China

The discourse surrounding energy transition is intensifying due to insufficient global energy resources. Nonetheless, given that the capitalist economy prioritizes expansion and growth, it remains uncertain whether green energy solutions can genuinely pave the way towards sustainability and address the challenges of climate change, energy shortages, and food security concerns. Degrowth calls for a radical reorganization of politics and economics to reduce resource, energy consumption. This paper discusses the crisis of capitalism from multiple dimensions. It uses the Analytic Hierarchy Process (AHP) as an approach to explain degrowth and green energy. It also explores green energy in terms of three aspects of sustainable development: the profit-making industry, the high-efficiency paradox, and the re-challenge to the environment. Finally, it discusses the possible pathways for society to solve the global environmental crisis in the context of degrowth. These movements encourage critical thinking about the transition to green energy and offer a feasible pathway to sustainability without relying on growth ideology. This highlights the viability of the degrowth framework as a means to address a range of problems. © 2024 River Publishers.

关键词： Green development

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Microbiologically Influenced Corrosion Behavior of Fe_(40)(CoCrMnNi)_(60) and Fe_(60)(CoCrMnNi)_(40) Medium Entropy Alloys in the Presence of Pseudomonas Aeruginosa

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Acta Metallurgica Sinica(English Letters) 2023年第3期36卷 379-390页

作者： Weiwei Chang Yangyang Li Huaibei Zheng Hongchang Qian Dawei Guo Shuyuan Zhang Yuntian Lou Chi Tat Kwok Lap Mou Tam Dawei Zhang National Materials Corrosion and Protection Data Center Institute for Advanced Materials and TechnologyUniversity of Science and Technology BeijingBeijing 100083China BRI Southeast Asia Network for Corrosion and Protection(MOE) Shunde Graduate School of University of Science and Technology BeijingFoshan 528399China State Key Laboratory of Metal Material for Marine Equipment and Application Anshan 114002China Department of Electromechanical Engineering University of MacaoMacao 999078China Institute for the Development and Quality Macao 999078China

In this work,the microbiologically influenced corrosion(MIC)of Fe_(40)(CoCrMnNi)_(60) and Fe_(60)(CoCrMnNi)_(40) medium entropy alloys(MEAs)induced by Pseudomonas aeruginosa(***)was *** behaviors during 14 days of immersion in sterile and ***-inoculated culture media are *** sterile conditions,both MEAs exhibited good corrosion resistance against the culture medium *** the presence of ***,the pitting corrosion of MEAs was *** results of inductively coupled plasma‒mass spectrometry(ICP‒MS)and potentiodynamic polarization tests showed that the presence of *** promoted the selective dissolution of passive film and accelerated the corrosion of *** results of X-ray photoelectron spectroscopy(XPS)and Mott-Schottky measurements further demonstrated the degradation effect of *** on the passive *** with Fe_(60)(CoCrMnNi)_(40),Fe_(40)(CoCrMnNi)_(60) manifested better resistance to the MIC caused by ***,which may be attributed to more Cr oxides and fewer Fe oxides of the passive film.

关键词： Microbiologically influenced corrosion Medium entropy alloys Pseudomonas aeruginosa

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Lethal pulmonary thromboembolism in mice induced by intravenous human umbilical cord mesenchymal stem cell-derived large extracellular vesicles in a dose-and tissue factor-dependent manner

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中国药理学报（英文版） 2024年第11期45卷 2300-2312页

作者： Bian-lei Yang Yao-ying Long Qian Lei Fei Gao Wen-xiang Ren Yu-lin Cao Di Wu Liu-yue Xu Jiao Qu He Li Ya-li Yu An-yuan Zhang Shan Wang Hong-xiang Wang Zhi-chao Chen Qiu-bai Li Department of Rheumatology and Immunology Union HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430022China Department of Hematology Union HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430022China West China Biomedical Big Data Center West China HospitalSichuan UniversityChengdu 610041China Department of Hematology Key Laboratory for Molecular Diagnosis of Hubei ProvinceThe Central Hospital of WuhanTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430014China Department of Rheumatology and Immunology Union HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430022China Hubei Engineering Research Center for Application of Extracellular Vesicles Hubei University of Science and TechnologyXianning 437100China

Mesenchymal stem cell-derived extracellular vesicles(MSC-EVs)have obvious advantages over MSC *** the strong procoagulant properties of MSC-EVs pose a potential risk of thromboembolism,an issue that remains insufficiently *** this study,we systematically investigated the procoagulant activity of large EVs derived from human umbilical cord MSCs(UC-EVs)both in vitro and in ***-EVs were isolated from cell culture *** were injected with UC-EVs(0.125,0.25,0.5,1,2,4 μg/g body weight)in 100μL PBS via the tail *** and mortality were monitored for 30 min after *** showed that these UC-EVs activated coagulation in a dose-and tissue factor-dependent ***-EVs-induced coagulation in vitro could be inhibited by addition of tissue factor pathway ***,intravenous administration of high doses of the UC-EVs(1 μg/g body weight or higher)led to rapid mortality due to multiple thrombus formations in lung tissue,platelets,and fibrinogen depletion,and prolonged prothrombin and activated partial thromboplastin ***,we demonstrated that pulmonary thromboembolism induced by the UC-EVs could be prevented by either reducing the infusion rate or by pre-injection of heparin,a known *** conclusion,this study elucidates the procoagulant characteristics and mechanisms of large UC-EVs,details the associated coagulation risk during intravenous delivery,sets a safe upper limit for intravenous dose,and offers effective strategies to prevent such mortal risks when high doses of large UC-EVs are needed for optimal therapeutic effects,with implications for the development and application of large UC-EV-based as well as other MSC-EV-based therapies.

关键词： mesenchymal stem cells extracellular vesicles tissue factor coagulation pulmonary thromboembolism heparin

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