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Uncertainties of landslide susceptibility prediction: Influences of random errors in landslide conditioning factors and errors reduction by low pass filter method

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第1期16卷 213-230页

作者： Faming huang Zuokui Teng Chi Yao shui-hua jiang Filippo Catani Wei Chen Jinsong huang School of Infrastructure Engineering Nanchang UniversityNanchang330031China State Key Laboratory of Geohazard Prevention and Geoenvironment Protection Chengdu University of TechnologyChengdu610059China Department of Geosciences University of PadovaPadovaItaly College of Geology and Environment Xi’an University of Science and TechnologyXi’an710054China Discipline of Civil Surveying and Conditioning EngineeringPriority Research Centre for Geotechnical Science and EngineeringUniversity of NewcastleNewcastleNSWAustralia

In the existing landslide susceptibility prediction(LSP)models,the influences of random errors in landslide conditioning factors on LSP are not considered,instead the original conditioning factors are directly taken as the model inputs,which brings uncertainties to LSP *** study aims to reveal the influence rules of the different proportional random errors in conditioning factors on the LSP un-certainties,and further explore a method which can effectively reduce the random errors in conditioning *** original conditioning factors are firstly used to construct original factors-based LSP models,and then different random errors of 5%,10%,15% and 20%are added to these original factors for con-structing relevant errors-based LSP ***,low-pass filter-based LSP models are constructed by eliminating the random errors using low-pass filter ***,the Ruijin County of China with 370 landslides and 16 conditioning factors are used as study *** typical machine learning models,*** perceptron(MLP),support vector machine(SVM)and random forest(RF),are selected as LSP ***,the LSP uncertainties are discussed and results show that:(1)The low-pass filter can effectively reduce the random errors in conditioning factors to decrease the LSP uncertainties.(2)With the proportions of random errors increasing from 5%to 20%,the LSP uncertainty increases continuously.(3)The original factors-based models are feasible for LSP in the absence of more accurate conditioning factors.(4)The influence degrees of two uncertainty issues,machine learning models and different proportions of random errors,on the LSP modeling are large and basically the same.(5)The Shapley values effectively explain the internal mechanism of machine learning model predicting landslide *** conclusion,greater proportion of random errors in conditioning factors results in higher LSP uncertainty,and low-pass filter can effectively reduce these random e

关键词： Landslide susceptibility prediction Conditioning factor errors Low-pass filter method Machine learning models Interpretability analysis

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An updating of landslide susceptibility prediction from the perspective of space and time

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Geoscience Frontiers 2023年第5期14卷 295-307页

作者： Zhilu Chang Faming huang Jinsong huang shui-hua jiang Yuting Liu Sansar Raj Meena Filippo Catani School of Infrastructure Engineering Nanchang UniversityNanchang 330031China Department of Geosciences University of PaduaPaduaItaly Department of Civil Environmental and Architectural EngineeringUniversity of PaduaPadovaItaly Discipline of Civil Surveying and Environmental EngineeringPriority Research Centre for Geotechnical Science and EngineeringUniversity of NewcastleNSWAustralia

Due to the similarity of conditioning factors,the aggregation feature of landslides and the multi-temporal landslide inventory,the spatial and temporal effects of landslides need to be considered in landslide susceptibility prediction(LSP).The ignorance of this issue will result in some biases and time-invariance in landslide ***,a novel framework has been proposed to update landslide susceptibility by simultaneously considering the spatial and temporal effects of landslides at the regional *** this framework,the landslide inventory of Chongyi County has been divided into pre-and fresh-landslide *** to the LSP results predicted by the support vector machine(SVM)model using the slope unit-based conditioning factors and pre-landslide inventory,a normalized spatial distance index(NSDI)is calculated to quantitatively represent the spatial correlation between landslides and surrounding slope units to develop the SVM-NSDI ***,the SVM-Updating model,which incorporates the LSP results of the SVM-NSDI model and fresh-landslide inventory,could be developed to update the LSP ***,the confusion matrix,the area under the receiver operating characteristic curve(AUC)and frequency ratio(FR)accuracy are used to evaluate the prediction performance of the above LSP *** F1-score values of the SVM,SVM-NSDI and SVM-Updating models are 0.776,0.816 and 0.831,*** AUC values are 0.869,0.903 and 0.914 and the FR accuracies are 0.795,0.853 and *** can be concluded that landslide susceptibility is a time-variant variable,which can be updated by considering the spatial correlation between landslides and surrounding slope units as well as the temporal effects of multi-temporal landslide *** study provides a new framework to update landslide susceptibility over time and also provides more accurate LSP results for decisionmakers.

关键词： Landslide susceptibility updating Spatial effect Temporal effect Machine learning

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A New Solution to Intrusion Detection Systems Based on Improved Federated-Learning Chain

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Computers, Materials & Continua 2024年第6期79卷 4491-4512页

作者： Chunhui Li hua jiang School of Computer and Electronic Information Guangxi UniversityNanning530000China Cyber Security and Information Center Guangxi UniversityNanning530000China

In the context of enterprise systems,intrusion detection(ID)emerges as a critical element driving the digital transformation of *** systems spanning various sectors of enterprises geographically dispersed,the necessity for seamless information exchange has surged *** existing cross-domain solutions are challenged by such issues as insufficient security,high communication overhead,and a lack of effective update mechanisms,rendering them less feasible for prolonged application on resource-limited *** study proposes a new cross-domain collaboration scheme based on federated chains to streamline the server-side *** this framework,individual nodes solely engage in training local data and subsequently amalgamate the final model employing a federated learning algorithm to uphold enterprise systems with efficiency and *** curtail the resource utilization of blockchains and deter malicious nodes,a node administration module predicated on the workload paradigm is introduced,enabling the release of surplus resources in response to variations in a node’s contribution *** encountering an intrusion,the system triggers an alert and logs the characteristics of the breach,facilitating a comprehensive global update across all nodes for collective *** results across multiple scenarios have verified the security and effectiveness of the proposed solution,with no loss of its recognition accuracy.

关键词： Cross-domain collaboration blockchain federated learning contribution value node management release slack resources

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Novel intelligent reasoning system for tool wear prediction and parameter optimization in intelligent milling

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Advances in Manufacturing 2024年第1期12卷 76-93页

作者： Long-hua Xu Chuan-Zhen huang Zhen Wang Han-Lian Liu shui-Quan huang Jun Wang School of Mechanical Engineering Yanshan UniversityQinhuangdao066004HebeiPeople’s Republic of China Center for Advanced Jet Engineering Technologies(CaJET) Key Laboratory of High-efficiency and Clean Mechanical Manufacture(Ministry of Education)National Experimental Teaching Demonstration Center for Mechanical Engineering(Shandong University)School of Mechanical EngineeringShandong UniversityJinan250061People’s Republic of China Institute of Manufacturing Technology Guangdong University of TechnologyGuangzhou510006People’s Republic of China

Accurate intelligent reasoning systems are vital for intelligent *** this study,a new intelligent reasoning system was developed for milling processes to accurately predict tool wear and dynamically optimize machining *** developed system consists of a self-learning algorithm with an improved particle swarm optimization(IPSO)learning algorithm,prediction model determined by an improved case-based reasoning(ICBR)method,and optimization model containing an improved adaptive neural fuzzy inference system(IANFIS)and *** results showed that the IPSO algorithm exhibited the best global convergence *** ICBR method was observed to have a better performance in predicting tool wear than standard CBR *** IANFIS model,in combination with IPSO,enabled the optimization of multiple objectives,thus generating optimal milling *** paper offers a practical approach to developing accurate intelligent reasoning systems for sustainable and intelligent manufacturing.

关键词： Improved particle swarm optimization(IPSO)algorithm Improved case-based reasoning(ICBR)method Adaptive neural fuzzy inference system(ANFIS)model Tool wear prediction Intelligent manufacturing

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Finite-time composite learning control for nonlinear teleoperation systems under networked time-varying delays

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Science China(Information Sciences) 2024年第6期67卷 279-296页

作者： Yana YANG Huixin jiang Changchun hua Junpeng LI Institute of Electrical Engineering Yanshan University

The robust finite-time synchronization control problem is investigated for master-slave networked nonlinear telerobotics systems(NNTSs) in this article. Although there have been some research achievements on finite-time control for the NNTSs, these studies are based on the strong assumptions of communication time delays or can only achieve finite-time bounded convergence even when the external forces are *** and in view of the importance of these issues, a novel robust composite learning adaptive control scheme rendering the finite-time master-slave synchronization is proposed in this paper. In particular, the influence of time delays on finite-time convergence of the system is analyzed by employing the multi-dimension finite-time small-gain framework. Meanwhile, in order to achieve accurate and fast estimation of uncertain parameters of the system, both the online historical and the instantaneous data of the estimation data are explored to derive the new parameter adaptive law under a more realizable interval-excitation(IE) ***, the convergence of the position/force synchronization errors and the adaptive parameter estimation errors is obtained in finite time, and enhanced robustness of the closed-loop system will also be ***, the superior performance of the proposed control algorithms is validated by numerical simulations and hardware experiments.

关键词： networked teleoperation systems finite-time control exact parameter estimation small-gain theorem unknown communication delays

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Mechanism of local solidification time variations with melt rate during vacuum arc remelting process of 8Cr4Mo4V high-strength steel

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Journal of Iron and Steel Research(International) 2024年第2期31卷 377-388页

作者： Tao Pan Hong-chun Zhu Zhou-hua jiang hua-bing Li Rui Zhang Hao Feng School of Metallurgy Northeastern UniversityShenyang110819LiaoningChina State Key Laboratory of Rolling and Automation Northeastern UniversityShenyang110819LiaoningChina

A 2D axisymmetric numerical model was established to investigate the variations of molten pool with different melt rates during the vacuum arc remelting of 8Cr4Mo4V high-strength steel,and the ingot growth was simulated by dynamic mesh *** results show that as the ingot grows,the molten pool profile changes from shallow and flat to V-shaped,and both the molten pool depth and the mushy width ***,the variation of both the molten pool shape and the mushy width melt rate is clarified by the thermal equilibrium *** melt rate increases,both the molten pool depth and the mushy width *** is caused by the increment in sensible heat stored in the ingot due to the limitation of the cooling capacity of the *** nonlinear increment in sensible heat leads to a nonlinear increase in the mushy *** addition,as melt rate increases,the local solidification time(LST)of ingot decreases obviously at first and then *** melt rate is controlled in a suitable range,LST is the lowest and the secondary dendrite arm spacing of the ingot is the smallest,which can effectively improve the compactness degree of 8Cr4Mo4V high-strength steel.

关键词： 8Cr4Mo4V high-strength steel Vacuum arc remelting process Melt rate Molten pool Local solidification time

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The Limitations and Ethical Considerations of ChatGPT

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Data Intelligence 2024年第1期6卷 201-239页

作者： Shangying hua Shuangci Jin Shengyi jiang Guangdong University of Foreign Studies Guangzhou 510000China

With the advancements of artificial intelligence technology,ChatGPT,a new practice of artificial intelligence,holds immense potential across multiple *** user-friendly human-machine interface,rapid response capabilities,and delivery of high-quality answers have attracted considerable attention and widespread *** by many as a groundbreaking advancement in AI,ChatGPT represents a new milestone in the ***,as with any technological evolution,the emergence of ChatGPT brings not only benefits,but also inevitable security risks and ethical *** paper provides specific information about ChatGPT,including its technology,limitations,ethical issues,governance paths and future ***,we firstly offered a thorough exploration of the technical implementation details of GPT series ***,we provided an intricate analysis elucidating the reasons for limitations and scrutinized the consequential impacts,such as malicious misuse,privacy violation,and so ***,we explore diverse governance paths to mitigate the impacts of ChatGPT and present future *** review aims to equip users with crucial knowledge,facilitating well-informed decision-making,effectively handling of potential challenges in employing ChatGPT,and staying abreast with the rapidly evolving landscape of this technology.

关键词： ChatGPT ChatGPT Technology Limitations Ethical considerations Artificial Intelligence

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(Parallel) kinetic resolution of 3,3-disubstituted indolines via organocatalyzed reactions with azodicarboxylates

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Science China Chemistry 2024年第3期67卷 973-980页

作者： Qianwen jiang Dekun Zhang Mengyao Tang hua Liu Xiaoyu Yang School of Physical Science and Technology ShanghaiTech UniversityShanghai 201210China

A novel kinetic resolution(KR) method has been developed for 3,3-disubstituted indolines, whose catalytic asymmetric synthesis remains a significant challenge in organic synthesis. The key to the success of this KR protocol lies in the utilization of chiral phosphoric acid-catalyzed triazane formation reaction with azodicarboxylates, which enables the enantioselective synthesis of various substituted indolines bearing C3-quaternary stereocenters with good to high enantioselectivities(with sfactors up to 70). Moreover, an intriguing parallel kinetic resolution(PKR) has been developed by combining triazane formation and dehydrogenation reactions using different azodicarboxylates. Experimental studies have provided insight into the mechanism of this PKR reaction, demonstrating stereoselectivity in both triazane formation and dehydrogenation steps, favoring the opposite enantiomers. The large-scale synthesis and diverse derivatizations of the products, particularly the imine groupcontaining 3H-indoles, demonstrate the value of these(P)KR methods.

关键词： asymmetric organocatalysis kinetic resolution 3 3-disubstituted indolines azodicarboxylate triazanes

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Garnet and Zircon U-Pb Geochronology and Geochemistry Reveal Genesis of the Dafang Au-Pb-Zn-Ag Deposit,Southern Hunan

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Acta Geologica Sinica(English Edition) 2024年第3期98卷 717-735页

作者： jiang hua KONG hua LIU Biao TAN Fucheng QIN Yixue huaNG Jingang ZHU Yu Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring Ministry of EducationSchool of Geosciences and Info-PhysicsCentral South UniversityChangsha 410083China School of Geosciences and Info-Physics Central South UniversityChangsha 410083China Hunan Baoshan Nonferrous Metals and Minerals Co. Ltd.ChenzhouHunan 424402China

Garnet is a primary mineral in skarn deposits and plays a significant role in recording copious mineralization and metallogenic *** study systematically investigates the geochemistry and geochronology of garnet and zircon in the Dafang Au-Pb-Zn-Ag deposit,which represents prominent gold mineralization in southern Hunan,*** samples with distinct zoning patterns and compositional variations were identified using various analytical techniques,including Backscattered Electron(BSE)imaging,Cathodoluminescence(CL)response,textural characterization,and analysis of rare-earth elements(REE),major contents,and trace element *** garnet was dated U-Pb dating,which yielded a lower intercept age of 161.06±1.93 *** age is older than the underlying granodiorite porphyry,which has a concordia age of 155.13±0.95 Ma determined by zircon U-Pb *** results suggest that the gold mineralization may be related to the concealed *** groups of garnet changed from depleted Al garnet to enriched Al garnet,and the rare earth element(REE)patterns of these groups were converted from light REE(LREE)-enriched and heavy REE(HREE)-depleted with positive europium(Eu)anomalies to medium REE(MREE)-enriched from core to rim *** different REE patterns of garnet in various zones may be attributed to changes in the fluid environment and late superposition *** development of distal skarn in the southern Hunan could be a significant indicator for identifying gold mineralization.

关键词： garnet and zircon U-Pb dating LA-ICP-MS mapping Dafang Southern Hunan

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Part-Whole Relational Few-Shot 3D Point Cloud Semantic Segmentation

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Computers, Materials & Continua 2024年第3期78卷 3021-3039页

作者： Shoukun Xu Lujun Zhang Guangqi jiang Yining hua Yi Liu School of Computer Science and Artificial Intelligence Aliyun School of Big Data and School of SoftwareChangzhou UniversityChangzhou213164China Department of Computer Science University of AberdeenKing’s CollegeAberdeenAB243FXUK

This paper focuses on the task of few-shot 3D point cloud semantic *** some progress,this task still encounters many issues due to the insufficient samples given,e.g.,incomplete object segmentation and inaccurate semantic *** tackle these issues,we first leverage part-whole relationships into the task of 3D point cloud semantic segmentation to capture semantic integrity,which is empowered by the dynamic capsule routing with the module of 3D Capsule Networks(CapsNets)in the embedding ***,the dynamic routing amalgamates geometric information of the 3D point cloud data to construct higher-level feature representations,which capture the relationships between object parts and their ***,we designed a multi-prototype enhancement module to enhance the prototype ***,the single-prototype enhancement mechanism is expanded to the multi-prototype enhancement version for capturing rich ***,the shot-correlation within the category is calculated via the interaction of different samples to enhance the intra-category *** studies prove that the involved part-whole relations and proposed multi-prototype enhancement module help to achieve complete object segmentation and improve semantic ***,under the integration of these two modules,quantitative and qualitative experiments on two public benchmarks,including S3DIS and ScanNet,indicate the superior performance of the proposed framework on the task of 3D point cloud semantic segmentation,compared to some state-of-the-art methods.

关键词： Few-shot point cloud semantic segmentation CapsNets

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