检索结果-南通市图书馆

A novel CGBoost deep learning algorithm for coseismic landslide susceptibility prediction

Geoscience Frontiers 2024年第2期15卷 349-365页

作者： Qiyuan Yang xianmin wang Jing Yin Aiheng Du Aomei Zhang Lizhe wang Haixiang Guo Dongdong Li Hubei Subsurface Multi-scale Imaging Key Laboratory School of Geophysics and GeomaticsChina University of GeosciencesWuhan 430074China State Key Laboratory of Biogeology and Environmental Geology China University of GeosciencesWuhan 430074China Key Laboratory of Geological and Evaluation of Ministry of Education China University of GeosciencesWuhan 430074China Laboratory of Natural Disaster Risk Prevention and Emergency Management School of Economics and ManagementChina University of GeosciencesWuhan 430074China College of Electronic Science and Engineering National University of Defense TechnologyChangsha 410073China

The accurate prediction of landslide susceptibility shortly after a violent earthquake is quite vital to the emergency rescue in the 72-h‘‘golden window”.However,the limited quantity of interpreted landslides shortly after a massive earthquake makes landslide susceptibility prediction become a challenge.To address this gap,this work suggests an integrated method of Crossing Graph attention network and xgBoost(CGBoost).This method contains three branches,which extract the interrelations among pixels within a slope unit,the interrelations among various slope units,and the relevance between influencing factors and landslide probability,respectively,and obtain rich and discriminative features by an adaptive fusion mechanism.Thus,the difficulty of susceptibility modeling under a small number of coseismic landslides can be reduced.As a basic module of CGBoost,the proposed Crossing graph attention network(Crossgat)could characterize the spatial heterogeneity within and among slope units to reduce the false alarm in the susceptibility results.Moreover,the rainfall dynamic factors are utilized as prediction indices to improve the susceptibility performance,and the prediction index set is established by terrain,geology,human activity,environment,meteorology,and earthquake factors.CGBoost is applied to predict landslide susceptibility in the Gorkha meizoseismal area.3.43%of coseismic landslides are randomly selected,of which 70%are used for training,and the others for testing.In the testing set,the values of Overall Accuracy,Precision,Recall,F1-score,and Kappa coefficient of CGBoost attain 0.9800,0.9577,0.9999,0.9784,and 0.9598,respectively.Validated by all the coseismic landslides,CGBoost outperforms the current major landslide susceptibility assessment methods.The suggested CGBoost can be also applied to landslide susceptibility prediction in new earthquakes in the future.

关键词： Coseismic landslide Landslide susceptibility prediction Graph neural network Deep learning

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Tactile-sensing-based robotic grasping stability analysis

引用

Science China Technological Sciences 2024年第6期67卷 1817-1828页

作者： HUANG YanJiang wang HaoNan ZHANG xianmin South China University of Technology Guangdong Provincial Key Laboratory of Precision Equipment and Manufacturing Technology

Tactile signals play a crucial role in enabling robots to successfully manipulate unfamiliar objects. For robots to grasp unknown objects securely and without causing damage, it is essential that they can analyze grasping stability in real time through tactile signals and respond promptly. This study introduces a novel method for analyzing the stability of robotic hand grasping, utilizing the Wilcoxon signed rank test. The efficacy of this method is demonstrated through its static and dynamic performance, and evaluated across a series of experiments. The findings of this research highlight the method’s ability to accurately detect when an object begins to slip from the robot’s grasp. Employing this method allows the gripper to maintain a secure hold on objects by applying the minimal necessary force. It also enables the gripper to dynamically adjust the force it applies in real time, thus preventing the object from slipping during the movement of the robotic arm. Moreover, the gripper demonstrates the ability to stably grasp objects of varied weights and with unknown characteristics, showcasing the versatility and effectiveness of the proposed method.

关键词： grasping stability manipulation tactile sensors

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Molecular mechanisms of stress resistance in sorghum: Implications for crop improvement strategies

引用

Journal of Integrative Agriculture 2024年第3期23卷 741-768页

作者： Hongxiang Zheng Yingying Dang xianmin Diao Na Sui Shandong Provincial Key Laboratory of Plant Stress/College of life Sciences Shandong Normal UniversityJinan 250014China Institute of Crop Sciences Chinese Academy of Agricultural SciencesBeijing 100081China

Abiotic stresses, such as drought, salt, extreme temperatures, and heavy metal pollution, are the main environmental factors that limit crop growth and yield. Sorghum, a C4 grass plant with high photosynthetic efficiency, can grow in adverse environmental conditions due to its excellent stress resistance characteristics. Therefore, unraveling the stress-resistance mechanism of sorghum could provide a theoretical basis for developing and cultivating various stress-resistant crops. This understanding could also help to create a conducive environment for using marginal soil in agriculture and ensuring food security. In this review, we discuss the adaptation mechanisms of sorghum under drought, salinity, temperature, and soil heavy metal stresses, the specific response to stress, the screening of sorghum-resistant germplasm, and the identification and functional analysis of the relevant genes and quantitative trait loci(QTL). In addition, we discuss the application potential of different stress-tolerant sorghum germplasms reported to date and emphasize the feasibility and potential use in developing and promoting highly stress-tolerant sorghum in marginal soil.

关键词： abiotic stress C4 plants QTL sorghum stress resistance yield stability

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Timing effect of high temperature exposure on the plasticity of internode and plant architecture in maize

引用

Journal of Integrative Agriculture 2024年第2期23卷 551-565页

作者： Binbin Li xianmin Chen Tao Deng Xue Zhao Fang Li Bingchao Zhang Xin wang Si Shen Shunli Zhou College of Agronomy and Biotechnology China Agricultural UniversityBeijing 100193China China Tobacco Hunan Industrial Corporation Changsha 410019China Innovation Center of Agricultural Technology for Lowland Plain of Hebei Wuqiao 061802China

The occurrence of high temperature(HT)in crop production is becoming more frequent and unpredictable with global warming,severely threatening food security.The state of an organ’s growth and development is largely determined by the temperature conditions it is exposed to over time.Maize is the main cereal crop,and its stem growth and plant architecture are closely related to lodging resistance,and especially sensitive to temperature.However,systematic research on the timing effect of HT on the sequentially developing internode and stem is currently lacking.To identify the timing effect of HT on the morphology and plasticity of the stem in maize,two hybrids(Zhengdan 958(ZD958),Xianyu 335(XY335))characterized by distinct morphological traits in the stem were exposed to a 7-day HT treatment from the V6 to V17 stages(Vn presents the vegetative stage with n leaves fully expanded)in 2019-2020.The results demonstrated that exposure to HT during V6-V12 accelerated the rapid elongation of stems.For instance,HT occurring at V7 and V12 specifically promoted the lengths and weights of the 3rd-5th and 9th-11th internodes,respectively.Meanwhile,HT slowed the growth of internodes adjacent to the promoted internodes.Interestingly,compared with control,the plant height was significantly increased soon after HT treatment,but the promotion effect became narrower at the subsequent flowering stage,demonstrating a self-adjusting mechanism in the maize plant in response to HT.Importantly,HT altered the plant architectures,including a rising of the ear position and increase in the ear position coefficient.XY335 exhibited greater sensitivity in stem development than ZD958 under HT treatment.These findings improve our systematic understanding of the plasticity of internode and plant architecture in response to the timing of HT exposure.

关键词： maize high temperature internode growth plasticity plant architecture

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Near real-time spatial prediction of earthquake-induced landslides:A novel interpretable self-supervised learning method

引用

International Journal of Digital Earth 2023年第1期16卷 1885-1906页

作者： Xuewen wang xianmin wang Xinlong Zhang Lizhe wang Haixiang Guo Dongdong Li Hubei Subsurface Multi-scale Imaging Key Laboratory School of Geophysics and GeomaticsChina University of GeosciencesWuhanPeople’s Republic of China State Key Laboratory of Biogeology and Environmental Geology China University of GeosciencesWuhanPeople’s Republic of China Key Laboratory of Geological and Evaluation of Ministry of Education China University of GeosciencesWuhanPeople’s Republic of China Laboratory of Natural Disaster Risk Prevension and Emergency Management School of Economics and ManagementChina University of GeosciencesWuhanPeople’s Republic of China College of Electronic Science and Engineering National University of Defense TechnologyChangshaPeople’s Republic of China

Near real-time spatial prediction of earthquake-induced landslides(EQILs)can rapidly forecast the occurrence position of widespread landslides just after a violent earthquake;thus,EQIL prediction is very crucial to the 72-hour‘golden window’for survivors.This work focuses on a series of earthquake events from 2008 to 2022 occurring in the Tibetan Plateau,a famous seismically-active zone,and proposes a novel interpretable self-supervised learning(ISeL)method for the near real-time spatial prediction of EQILs.This new method innovatively introduces swap noise at the unsupervised mechanism,which can improve the generalization performance and transferability of the model,and can effectively reduce false alarm and improve accuracy through supervisedfine-tuning.An interpretable module is built based on a self-attention mechanism to reveal the importance and contribution of various influencing factors to EQIL spatial distribution.Experimental results demonstrate that the ISeL model is superior to the excellent state-of-the-art machine learning and deep learning methods.Furthermore,according to the interpretable module in the ISeL method,the critical controlling and triggering factors are revealed.The ISeL method can also be applied in other earthquake-frequent regions worldwide because of its good generalization and transferability.

关键词： Coseismic landslide near real-time interpretable artificial intelligence self-supervised learning spatial distribution prediction

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Attentive Neighborhood Feature Augmentation for Semi-supervised Learning

引用

Intelligent Automation & Soft Computing 2023年第8期37卷 1753-1771页

作者： Qi Liu Jing Li xianmin wang Wenpeng Zhao School of Computer Science and Cyber Engineering Guangzhou UniversityGuangzhou510002China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang UniversityFuzhou350121China

Recent state-of-the-art semi-supervised learning(SSL)methods usually use data augmentations as core components.Such methods,however,are limited to simple transformations such as the augmentations under the instance’s naive representations or the augmentations under the instance’s semantic representations.To tackle this problem,we offer a unique insight into data augmentations and propose a novel data-augmentation-based semi-supervised learning method,called Attentive Neighborhood Feature Aug-mentation(ANFA).The motivation of our method lies in the observation that the relationship between the given feature and its neighborhood may contribute to constructing more reliable transformations for the data,and further facilitating the classifier to distinguish the ambiguous features from the low-dense regions.Specially,we first project the labeled and unlabeled data points into an embedding space and then construct a neighbor graph that serves as a similarity measure based on the similar representations in the embedding space.Then,we employ an attention mechanism to transform the target features into augmented ones based on the neighbor graph.Finally,we formulate a novel semi-supervised loss by encouraging the predictions of the interpolations of augmented features to be consistent with the corresponding interpolations of the predictions of the target features.We carried out exper-iments on SVHN and CIFAR-10 benchmark datasets and the experimental results demonstrate that our method outperforms the state-of-the-art methods when the number of labeled examples is limited.

关键词： Semi-supervised learning attention mechanism feature augmentation consistency regularization

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Active High-Locality Landslides in Mao County: Early Identification and Deformational Rules

引用

地球科学学刊:英文版 2023年第5期34卷 1596-1615页

作者： xianmin wang Jing Yin Menghan Luo Haifeng Ren Jing Li Lizhe wang Dongdong Li Guojun Li Hubei Subsurface Multi-Scale Imaging Key Laboratory School of Geophysics and GeomaticsChina University of GeosciencesWuhan 430074China Changsha Planning Information Service Center Changsha Municipal Bureau of Natual Resources and PlanningChangsha 410221China National Engineering Research Center for Geoinformatics Aerospace Information Research InstituteChinese Academy of SciencesChinese Academy of SciencesBeijing 100101China College of Electronic Science and Engineering National University of Defense TechnologyChangsha 410073China Laboratory of Beyond LOS Reliable Information Transmission Chongqing University of Posts and TelecommunicationsChongqing 400065China

High-locality landslides are located on slopes at high elevations and are characterized by long sliding distances, large gravitational potential energy, high movement velocities, tremendous kinetic energy, and sudden onset. Thus, they often cause catastrophic damage to human lives and engineering facilities. It is of great significance to identify active high-locality landslides in their early deformational stages and to reveal their deformational rules for effective disaster mitigation. Due to alpinecanyon landforms, Mao County is a representative source of high-locality landslides. This work employs multisource data(geological, terrain, meteorological, ground sensor, and remote sensing data) and timeseries In SAR technology to recognize active high-locality landslides in Mao County and to reveal their laws of development. Some new viewpoints are suggested.(1) Nineteen active high-locality landslides are identified by the time-series In SAR technique, of which 7 are newly discovered in this work. All these high-locality landslides possessed good concealment during their early deformational stages. The newly discovered HL-16 landslide featured a large scale and a great slope height, posing a large threat to the surrounding buildings and residents.(2) The high-locality landslides in Mao County were mainly triggered by three factors: earthquakes, precipitation, and road construction.(3) Three typical high-locality landslides that were triggered by different factors are highlighted with their deformational rules under the functions of steep terrain, shattered rocks, fissure-water penetration, precipitation, and road construction. This work may provide clues to the prevention and control of high-locality landslides and can be applied to the determination of active high-locality landslides in other hard-hit areas.

关键词： high-locality landslide landslide identification deformational rule landslides engineering geology

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

A complete reference genome assembly for foxtail millet and Setaria-db, a comprehensive database for Setaria

引用

Molecular Plant 2024年第2期17卷 219-222页

作者： Qiang He Chunchao wang Qiang He Jun Zhang Hongkai Liang Zefu Lui Kun Xie Sha Tang Yuhan Zhou Bin Liu Hui Zhi Guanqing Jia Ganggang Guo Huilong Du xianmin Diao State Key Laboratory of Crop Gene Resources and Breeding Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijing 100081China School of Life Sciences Institute of Life Sciences and Green DevelopmentHebei UniversityBaoding 071000China State Key Laboratory of Rice Biology&Breeding Zhejang Provincial Key Laboratory of Crop GermplasmThe Advanced Seed InstituteZhejiang UniversityHangzhouChina

Dear Editor,,Foxtail millet(Setaria italica)and its wild ancestor green foxtail(S.viridis),are two C4 genetic model plants known for their desirable traits,such as small size,short life cycle,ease of transformation,and a compact genome size(~420 Mb)(He et al.,2023).Foxtail millet stands out as the only cultivated species within the Setaria genus.As a foundational crop for ancient east Asian agriculture civilization,it possesses remarkable drought and soil-nutrient deficiency tolerance.

关键词： comprehensive soil cultivated

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

A Novel Trajectory Tracking Control of AGV Based on Udwadia-Kalaba Approach

引用

IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 1069-1071页

作者： Rongrong Yu Han Zhao Shengchao Zhen Kang Huang xianmin Chen Hao Sun Ke Shao the School of Mechanical Engineering Hefei University of TechnologyHefei 230009China the College of Mechanical and Electronic Engineering Shandong University of Science and TechnologyQingdao 266590China the University of Science and Technology of China Hefei 230026China

Dear Editor,This letter is about an automated guided vehicle(AGV)trajectory tracking control method based on Udwadia-Kalaba(U-K)approach.This method provides a novel,concise and explicit motion equation for constrained mechanical systems with holonomic and/or nonholonomic constraints as well as constraints that may be ideal or nonideal.In this letter.

关键词： letter constraints constrained

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Instance Reweighting Adversarial Training Based on Confused Label

引用

Intelligent Automation & Soft Computing 2023年第8期37卷 1243-1256页

作者： Zhicong Qiu xianmin wang Huawei Ma Songcao Hou Jing Li Zuoyong Li Institute of Artificial Intelligence and Blockchain Guangzhou UniversityGuangzhou511442China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang UniversityFuzhou350121China

Reweighting adversarial examples during training plays an essential role in improving the robustness of neural networks,which lies in the fact that examples closer to the decision boundaries are much more vulnerable to being attacked and should be given larger weights.The probability margin(PM)method is a promising approach to continuously and path-independently mea-suring such closeness between the example and decision boundary.However,the performance of PM is limited due to the fact that PM fails to effectively distinguish the examples having only one misclassified category and the ones with multiple misclassified categories,where the latter is closer to multi-classification decision boundaries and is supported to be more critical in our observation.To tackle this problem,this paper proposed an improved PM criterion,called confused-label-based PM(CL-PM),to measure the closeness mentioned above and reweight adversarial examples during training.Specifi-cally,a confused label(CL)is defined as the label whose prediction probability is greater than that of the ground truth label given a specific adversarial example.Instead of considering the discrepancy between the probability of the true label and the probability of the most misclassified label as the PM method does,we evaluate the closeness by accumulating the probability differences of all the CLs and ground truth label.CL-PM shares a negative correlation with data vulnerability:data with larger/smaller CL-PM is safer/riskier and should have a smaller/larger weight.Experiments demonstrated that CL-PM is more reliable in indicating the closeness regarding multiple misclassified categories,and reweighting adversarial training based on CL-PM outperformed state-of-the-art counterparts.

关键词： Reweighting adversarial training adversarial example boundary closeness confused label

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

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

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

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

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

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：