The accurate representation of lithium plating and aging phenomena has posed a persistent challenge within the battery research community.Empirical evidence underscores the pivotal role of cell structure in influencin...The accurate representation of lithium plating and aging phenomena has posed a persistent challenge within the battery research community.Empirical evidence underscores the pivotal role of cell structure in influencing aging behaviors and lithium plating within lithium-ion batteries(LIBs).Available lithium-ion plating models often falter in detailed description when integrating the structural intricacies.To address this challenge,this study proposes an innovative hierarchical model that intricately incorporates the layered rolling structure in cells.Notably,our model demonstrates a remarkable capacity to predict the non-uniform distribution of current density and overpotential along the rolling direction of LIBs.Subsequently,we delve into an insightful exploration of the structural factors that influence lithium plating behavior,leveraging the foundation laid by our established model.Furthermore,we easily update the hierarchical model by considering aging factors.This aging model effectively anticipates capacity fatigue and lithium plating tendencies across individual layers of LIBs,all while maintaining computational efficiency.In light of our findings,this model yields novel perspectives on capacity fatigue dynamics and local lithium plating behaviors,offering a substantial advancement compared to existing models.This research paves the way for more efficient and tailored LIB design and operation,with broad implications for energy storage technologies.展开更多
Due to the shortcomings of the diagnosis systems for complex electronic devices such as failure models hard to build and low fault isolation resolution, a new hierarchical modeling and diagnosis method is proposed bas...Due to the shortcomings of the diagnosis systems for complex electronic devices such as failure models hard to build and low fault isolation resolution, a new hierarchical modeling and diagnosis method is proposed based on multisignal model and support vector machine （SVM）. Multisignal model is used to describe the failure propagation relationship in electronic device system, and the most probable failure printed circuit boards （PCBs） can be found by Bayes inference. The exact failure modes in the PCBs can be identified by SVM. The results show the proposed modeling and diagnosis method is effective and suitable for diagnosis for complex electronic devices.展开更多
Multilevel modeling (MLM) has emerged as a powerful statistical framework for analyzing complex data structures with nested relationships. With its hierarchical modeling approach, MLM enables researchers to account fo...Multilevel modeling (MLM) has emerged as a powerful statistical framework for analyzing complex data structures with nested relationships. With its hierarchical modeling approach, MLM enables researchers to account for dependencies and variations within and between different levels of a hierarchy. By explicitly modeling these relationships, MLM provides a robust and accurate analysis of data. It has become increasingly popular in the field of education. MLM enables the investigation of various research issues, the evaluation of individual and group-level indicators, and the calculation of both fixed and random effects. Overall, MLM revolutionizes data analysis by uncovering patterns, understanding contextual effects, and making more precise statistical inferences in complex datasets. For fitting multilevel models in R, use lmer function provided by lme4 package. Through this examination, the use of a multilevel model is expected to increase and revolutionize data analysis and decision-making. The Constrained Intermediate Model (CIM) and Augmented Intermediate model (AIM) deviation are compared using the Likelihood-ratio (LR) test and the ANOVA function. This study analyzes student results from the University of Agriculture Faisalabad, collected via stratified random sampling. A linear mixed-effect model under multilevel modeling estimates the impact on CGPA, considering department, gender, intermediate marks, and entry test scores. These results indicate that Entry test is a significant predictor of CGPA, but the effect of department identifier CMC on CGPA is not statistically significant.展开更多
Document-level machine translation(MT)remains challenging due to its difficulty in efficiently using documentlevel global context for translation.In this paper,we propose a hierarchical model to learn the global conte...Document-level machine translation(MT)remains challenging due to its difficulty in efficiently using documentlevel global context for translation.In this paper,we propose a hierarchical model to learn the global context for documentlevel neural machine translation(NMT).This is done through a sentence encoder to capture intra-sentence dependencies and a document encoder to model document-level inter-sentence consistency and coherence.With this hierarchical architecture,we feedback the extracted document-level global context to each word in a top-down fashion to distinguish different translations of a word according to its specific surrounding context.Notably,we explore the effect of three popular attention functions during the information backward-distribution phase to take a deep look into the global context information distribution of our model.In addition,since large-scale in-domain document-level parallel corpora are usually unavailable,we use a two-step training strategy to take advantage of a large-scale corpus with out-of-domain parallel sentence pairs and a small-scale corpus with in-domain parallel document pairs to achieve the domain adaptability.Experimental results of our model on Chinese-English and English-German corpora significantly improve the Transformer baseline by 4.5 BLEU points on average which demonstrates the effectiveness of our proposed hierarchical model in document-level NMT.展开更多
Understanding plant community assembly is crucial for effective ecosystem conservation and restoration.The ecological filter framework describes community assembly as a process shaped by dispersal,environmental,and bi...Understanding plant community assembly is crucial for effective ecosystem conservation and restoration.The ecological filter framework describes community assembly as a process shaped by dispersal,environmental,and biotic filters.Additionally,functional traits and phylogenetic relationships are increasingly recognized as important factors influencing species coexistence and community structure.However,both the ecological filter framework and the roles of functional traits and phylogeny in community assembly remain underexplored in the Algerian steppes—particularly in the El Bayadh region,where ongoing vegetation degradation threatens ecosystem stability.This study applied Hierarchical Modeling of Species Communities(HMSC)as an integrative approach to assess how ecological filters influence plant community assembly in the El Bayadh steppe and to evaluate the roles of functional traits and phylogenetic relationships in this process.Environmental data—including soil properties,topography,precipitation,and land use types(grazing and exclosure)—were collected across 50 plots in April and October,2023,along with functional traits from 24 species.These traits include root length,leaf area,specific leaf area,clonality,life history,and seed mass.HMSC results revealed that soil properties and precipitation were the primary drivers of community structure,while sand height and elevation had a moderate influence.In contrast,competition and grazing played relatively minor roles.Species responses to environmental covariates were heterogeneous:soil fertility and texture had mixed effects,benefiting some species while limiting others;sand encroachment and precipitation variability generally had negative impacts,whereas grazing exclusion favored many species.A weak phylogenetic signal was recorded,indicating that community assembly was driven more by environmental filtering than by shared evolutionary history.Functional trait responses to environmental variation reflected plant strategies that balanced resource acquisition and conservation.Specifically,seed mass,leaf area,and root length increased under higher soil moisture and nutrient availability but declined in response to salinity,precipitation variability,and sand height.Clonality and perennial life history traits enhanced the survival of plant species under harsh conditions.Overall,this study provides a holistic understanding of community assembly processes in the El Bayadh steppe and offers valuable insights for ecosystem management and restoration in arid and degraded ecosystem environments.展开更多
Temperate rainforests have historically been considered highly vulnerable to disturbance.Climate change,which is expected to increase the intensity,frequency,and impacts of disturbance events,is consequently a signifi...Temperate rainforests have historically been considered highly vulnerable to disturbance.Climate change,which is expected to increase the intensity,frequency,and impacts of disturbance events,is consequently a significant threat to their long-term persistence.However,data describing the long-term response of temperate rainforests to disturbance is rare.In the cool temperate rainforests of northern New South Wales,Australia,Nothofagus moorei is considered especially vulnerable to climate change due to a decreasing number of mature individuals,limited remaining suitable habitat,and low rates of sexual regeneration.In this study,we used over 50 years of empirical data from silvicultural experiments with multiple thinning intensities to characterise the demographic responses(i.e.,growth,mortality,and recruitment)of cool temperate rainforest species,including N.moorei,to disturbance over time.Cool temperate rainforest species showed resilience to disturbance,predominantly through their widespread ability to basally coppice.Nothofagus moorei,in particular,demonstrated higher rates of successful sexual and vegetative recruitment and grew faster in response to higher intensities of disturbance,in comparison to very low rates of recruitment pre-disturbance.These results challenge successional models that position rainforests as disturbance-sensitive ecosystems and identify N.moorei as a species that requires large-scale disturbance to successfully regenerate.Management regimes that actively exclude disturbance from these forests risk the local loss of disturbance-dependent rainforest species such as N.moorei.展开更多
Maintaining optimal quality of life(QoL)is a pivotal for“successful aging”.Understanding how the QoL of the elderly develops and what role psychological factors play in its development will help improve QoL from a p...Maintaining optimal quality of life(QoL)is a pivotal for“successful aging”.Understanding how the QoL of the elderly develops and what role psychological factors play in its development will help improve QoL from a psychological perspective.Embedded within the lifespan theory of control,this longitudinal study aimed to(1)map the temporal trajectory of QoL among Chinese older adults,(2)examine differential effects of tripartite negative emotions(stress,anxiety,depression),and(3)test themoderating role of control strategies(goal engagement,goal disengagement,self-protection)in emotion-QoL dynamics.A prospective cohort of 345 community-dwelling older adults(Mage=83.84±8.49 years;55.1%female)completed validated measures-SF-36 for QoL,DASS-21 for negative emotions,and an adapted Control Strategies Questionnaire(CAS)-at three waves spanning 12 months.Hierarchical linear modeling(HLM)with time-nested structure analyzed intraindividual changes and interindividual differences.QoL exhibited a significant linear decline over time(β=−4.75,p<0.001).Stress(β=−14.12,p<0.001)and anxiety(β=−11.24,p<0.001)robustly predicted QoL decline,whereas depression showed no significant effect.Control strategies had divergent associations:goal engagement(β=3.51,p<0.001)and self-protection(β=2.38,p=0.015)predicted higher baseline QoL,while goal disengagement accelerated decline(β=−7.00,p<0.001;interaction with time:β=−2.46,p<0.001).Contrary to hypotheses,control strategies did not moderate emotion-QoL associations(ΔR2=0.02,p=0.21).The results showed that stress and anxiety played an important role in the QoL of the elderly.At the same time,goal engagement and self-protection were beneficial to the QoL of the elderly,while goal disengagement was not conducive to QoL and its development among the elderly.Meanwhile,the negative effect of anxiety and stress on the QoL of the elderly was not affected by the control strategies.展开更多
In structural simulation and design,an accurate computational model directly determines the effectiveness of performance evaluation.To establish a high-fidelity dynamic model of a complex assembled structure,a Hierarc...In structural simulation and design,an accurate computational model directly determines the effectiveness of performance evaluation.To establish a high-fidelity dynamic model of a complex assembled structure,a Hierarchical Model Updating Strategy(HMUS)is developed for Finite Element(FE)model updating with regard to uncorrelated modes.The principle of HMUS is first elaborated by integrating hierarchical modeling concept,model updating technology with proper uncorrelated mode treatment,and parametric modeling.In the developed strategy,the correct correlated mode pairs amongst the uncorrelated modes are identified by an error minimization procedure.The proposed updating technique is validated by the dynamic FE model updating of a simple fixed–fixed beam.The proposed HMUS is then applied to the FE model updating of an aeroengine stator system(casings)to demonstrate its effectiveness.Our studies reveal that(A)parametric modeling technique is able to build an efficient equivalent model by simplifying complex structure in geometry while ensuring the consistency of mechanical characteristics;(B)the developed model updating technique efficiently processes the uncorrelated modes and precisely identifies correct Correlated Mode Pairs(CMPs)between FE model and experiment;(C)the proposed HMUS is accurate and efficient in the FE model updating of complex assembled structures such as aeroengine casings with large-scale model,complex geometry,high-nonlinearity and numerous parameters;(D)it is appropriate to update a complex structural FE model parameterized.The efforts of this study provide an efficient updating strategy for the dynamic model updating of complex assembled structures with experimental test data,which is promising to promote the precision and feasibility of simulation-based design optimization and performance evaluation of complex structures.展开更多
Online accurate recognition of target tactical intention in beyond-visual-range (BVR) air combat is an important basis for deep situational awareness and autonomous air combat decision-making, which can create pre-emp...Online accurate recognition of target tactical intention in beyond-visual-range (BVR) air combat is an important basis for deep situational awareness and autonomous air combat decision-making, which can create pre-emptive tactical opportunities for the fighter to gain air superiority. The existing methods to solve this problem have some defects such as dependence on empirical knowledge, difficulty in interpreting the recognition results, and inability to meet the requirements of actual air combat. So an online hierarchical recognition method for target tactical intention in BVR air combat based on cascaded support vector machine (CSVM) is proposed in this study. Through the mechanism analysis of BVR air combat, the instantaneous and cumulative feature information of target trajectory and relative situation information are introduced successively using online automatic decomposition of target trajectory and hierarchical progression. Then the hierarchical recognition model from target maneuver element, tactical maneuver to tactical intention is constructed. The CSVM algorithm is designed for solving this model, and the computational complexity is decomposed by the cascaded structure to overcome the problems of convergence and timeliness when the dimensions and number of training samples are large. Meanwhile, the recognition result of each layer can be used to support the composition analysis and interpretation of target tactical intention. The simulation results show that the proposed method can effectively realize multi-dimensional online accurate recognition of target tactical intention in BVR air combat.展开更多
In this paper, we propose an impact finite element （FE） model for an airbag landing buf- fer system. First, an impact FE model has been formulated for a typical airbag landing buffer system. We use the independence ...In this paper, we propose an impact finite element （FE） model for an airbag landing buf- fer system. First, an impact FE model has been formulated for a typical airbag landing buffer system. We use the independence of the structure FE model from the full impact FE model to develop a hierarchical updating scheme for the recovery module FE model and the airbag system FE model. Second, we define impact responses at key points to compare the computational and experimental results to resolve the inconsistency between the experimental data sampling frequency and experi- mental triggering. To determine the typical characteristics of the impact dynamics response of the airbag landing buffer system, we present the impact response confidence factors （IRCFs） to evalu- ate how consistent the computational and experiment results are. An error function is defined between the experimental and computational results at key points of the impact response （KPIR） to serve as a modified objective function. A radial basis function （RBF） is introduced to construct updating variables for a surrogate model for updating the objective function, thereby converting the FE model updating problem to a soluble optimization problem. Finally, the developed method has been validated using an experimental and computational study on the impact dynamics of a classic airbag landing buffer system.展开更多
Towards integration of supply chain, manufacturing/production and investment decision making, this paper presents a hierarchical model architecture which contains six sub-models covering the areas of manufacturing con...Towards integration of supply chain, manufacturing/production and investment decision making, this paper presents a hierarchical model architecture which contains six sub-models covering the areas of manufacturing control, production operation, design and revamp, production management, supply chain and investment decision making. Six types of flow, material, energy, information, humanware, partsware and capital are clasified. These flows connect enterprise components/subsystems to formulate system topology and logical structure. Enterprise components/subsystems are abstracted to generic elementary and composite classes. Finally, the model architecture is applied to a management system of an integrated suply chain, and suggestion are made on the usage of the model architecture and further development of the model as well as implementation issues.展开更多
In the hierarchical random effect linear model, the Bayes estimator of random parameter are not only dependent on specific prior distribution but also it is difficult to calculate in most cases. This paper derives the...In the hierarchical random effect linear model, the Bayes estimator of random parameter are not only dependent on specific prior distribution but also it is difficult to calculate in most cases. This paper derives the distributed-free optimal linear estimator of random parameters in the model by means of the credibility theory method. The estimators the authors derive can be applied in more extensive practical scenarios since they are only dependent on the first two moments of prior parameter rather than on specific prior distribution. Finally, the results are compared with some classical models and a numerical example is given to show the effectiveness of the estimators.展开更多
Among complex network models,the hierarchical network model is the one most close to such real networks as world trade web,metabolic network,WWW,actor network,and so on.It has not only the property of power-law degree...Among complex network models,the hierarchical network model is the one most close to such real networks as world trade web,metabolic network,WWW,actor network,and so on.It has not only the property of power-law degree distribution,but also the scaling clustering coefficient property which Barabási-Albert(BA)model does not have.BA model is a model of network growth based on growth and preferential attachment,showing the scale-free degree distribution property.In this paper,we study the evolution of cooperation on a hierarchical network model,adopting the prisoner's dilemma(PD)game and snowdrift game(SG)as metaphors of the interplay between connected nodes.BA model provides a unifying framework for the emergence of cooperation.But interestingly,we found that on hierarchical model,there is no sign of cooperation for PD game,while the fre-quency of cooperation decreases as the common benefit decreases for SG.By comparing the scaling clustering coefficient prop-erties of the hierarchical network model with that of BA model,we found that the former amplifies the effect of hubs.Considering different performances of PD game and SG on complex network,we also found that common benefit leads to cooperation in the evolution.Thus our study may shed light on the emergence of cooperation in both natural and social environments.展开更多
This paper presents an anomaly detection approach to detect intrusions into computer systems. In this approach, a hierarchical hidden Markov model （HHMM） is used to represent a temporal profile of normal behavior in...This paper presents an anomaly detection approach to detect intrusions into computer systems. In this approach, a hierarchical hidden Markov model （HHMM） is used to represent a temporal profile of normal behavior in a computer system. The HHMM of the norm profile is learned from historic data of the system＇s normal behavior. The observed behavior of the system is analyzed to infer the probability that the HHMM of the norm profile supports the observed behavior. A low probability of support indicates an anomalous behavior that may result from intrusive activities. The model was implemented and tested on the UNIX system call sequences collected by the University of New Mexico group. The testing results showed that the model can clearly identify the anomaly activities and has a better performance than hidden Markov model.展开更多
This study developed a hierarchical Bayesian(HB)model for local and regional flood frequency analysis in the Dongting Lake Basin,in China.The annual maximum daily flows from 15 streamflow-gauged sites in the study are...This study developed a hierarchical Bayesian(HB)model for local and regional flood frequency analysis in the Dongting Lake Basin,in China.The annual maximum daily flows from 15 streamflow-gauged sites in the study area were analyzed with the HB model.The generalized extreme value(GEV)distribution was selected as the extreme flood distribution,and the GEV distribution location and scale parameters were spatially modeled through a regression approach with the drainage area as a covariate.The Markov chain Monte Carlo(MCMC)method with Gibbs sampling was employed to calculate the posterior distribution in the HB model.The results showed that the proposed HB model provided satisfactory Bayesian credible intervals for flood quantiles,while the traditional delta method could not provide reliable uncertainty estimations for large flood quantiles,due to the fact that the lower confidence bounds tended to decrease as the return periods increased.Furthermore,the HB model for regional analysis allowed for a reduction in the value of some restrictive assumptions in the traditional index flood method,such as the homogeneity region assumption and the scale invariance assumption.The HB model can also provide an uncertainty band of flood quantile prediction at a poorly gauged or ungauged site,but the index flood method with L-moments does not demonstrate this uncertainty directly.Therefore,the HB model is an effective method of implementing the flexible local and regional frequency analysis scheme,and of quantifying the associated predictive uncertainty.展开更多
3D and 2D closed form plate models are here applied to static analysis of simply supported square isotropic plates. 2D theories are hierarchically classified on the basis of the accuracy of the displacements and stres...3D and 2D closed form plate models are here applied to static analysis of simply supported square isotropic plates. 2D theories are hierarchically classified on the basis of the accuracy of the displacements and stresses obtained by comparison to the 3D exact results that could be assumed by the reader as benchmark for further analyses. Attention is mainly paid on localized loading conditions, that is, piecewise constant load. Also bi-sinusoidal and uniformly distributed loadings are taken into account. All of those configurations are considered in order to investigate the behavior of the 2D models in the case of continu- ous/uncontinuous, centric or off-centric loading conditions. The ratio between the side length a and the plate thickness h has been assumed as analysis parameter. Higher order 2D models yield accurate results for any considered load condition in the case of moderately thick plates, a/h=10. In the case of thick plates, a/h=5, and continuous/uncontinuous centric loading conditions high accuracy is also obtained. For the considered off-centric load condition and thick plates good results are provided for some output quantities. A better solution could be achieved by simply increasing the polynomial approximation order of the axiomatic 2D displacement field.展开更多
In order to compare the aviation network of mid-south,northwest and southwest of China to reveal the structure similarity and difference for providing quantitative evidence to construct regional aviation network and i...In order to compare the aviation network of mid-south,northwest and southwest of China to reveal the structure similarity and difference for providing quantitative evidence to construct regional aviation network and improve its structure,hierarchical index model of regional aviation network was established through dividing the aviation network into layers to research its structure characters.Data matrixes were defined to record the basic state of regional aviation network.Index matrixes were constructed to describe the quantitative features of regional aviation network.On the basis of these indexes,several structure indexes of all layers of aviation network were calculated to show the structure features of aviation network,such as ratio of passenger volume within the region with across the region,share rate of passenger volume among layers,ratio of average number of airline for each airport,ratio of average passenger volume for each airline and ratio of airline rate.According to the statistical data,similar structure of share rate of passenger volume among layers and average passenger volume for each airline in their regional aviation network was found after calculating.But on the side of ratio of passenger volume within the region with across the region,ratio of average number of airlines for each airport and ratio of airline rate were different.展开更多
Digital libraries are complex systems and this brings difficulties for their evaluation. This paper proposes a hierarchical model to solve this problem, and puts the entangled matters into a clear-layered structure. F...Digital libraries are complex systems and this brings difficulties for their evaluation. This paper proposes a hierarchical model to solve this problem, and puts the entangled matters into a clear-layered structure. Firstly, digital libraries(DLs thereafter)are classified into 5 groups in ascending gradations, i.e. mini DLs, small DLs, medium DLs,large DLs, and huge DLs by their scope of operation. Then, according to the characteristics of DLs at different operational scope and level of sophistication, they are further grouped into unitary DLs, union DLs and hybrid DLs accordingly. Based on this simulated structure,a hierarchical model for digital library evaluation is introduced, which evaluates DLs differentiatingly within a hierarchical scheme by using varying criteria based on their specific level of operational complexity such as at the micro-level, medium-level, and/or at the macro-level. Based on our careful examination and analysis of the current literature about DL evaluation system, an experiment is conducted by using the DL evaluation model along with its criteria for unitary DLs at micro-level. The main contents resulting from this evaluation experimentation and also those evaluation indicators and relevant issues of major concerns for DLs at medium-level and macro-level are also to be presented at some length.展开更多
Hierarchical evolutionary algorithms based on genetic algorithms (GAs) and Nash strategy of game theory are proposed to accelerate the optimization process and implemented in transonic aerodynamic shape optimization p...Hierarchical evolutionary algorithms based on genetic algorithms (GAs) and Nash strategy of game theory are proposed to accelerate the optimization process and implemented in transonic aerodynamic shape optimization problems Inspired from the natural evolution history that different periods with certain environments have different criteria for the evaluations of individuals’ fitness, a hierarchical fidelity model is introduced to reach high optimization efficiency The shape of an NACA0012 based airfoil is optimized in maximizing the lift coefficient under a given transonic flow condition Optimized results are presented and compared with the single model results and traditional GA展开更多
Computational complexity of complex system multiple fault diagnosis is a puzzle at all times. Based on the well known Mozetic＇s approach, a novel hierarchical model-based diagnosis methodology is put forward for impr...Computational complexity of complex system multiple fault diagnosis is a puzzle at all times. Based on the well known Mozetic＇s approach, a novel hierarchical model-based diagnosis methodology is put forward for improving efficency of multi-fault recognition and localization. Structural abstraction and weighted fault propagation graphs are combined to build diagnosis model. The graphs have weighted arcs with fault propagation probabilities and propagation strength. For solving the problem of coupled faults, two diagnosis strategies are used： one is the Lagrangian relaxation and the primal heuristic algorithms; another is the method of propagation strength. Finally, an applied example shows the applicability of the approach and experimental results are given to show the superiority of the presented technique.展开更多
基金the financial support from The National Key Research and Development Program of China(2022YFB3305402)The National Natural Science Foundation of China(12272072)+1 种基金The Key Project of Chongqing Technology Innovation and Application Development(CSTB2022TIAD-KPX0037)Research Project of the State Key Laboratory of Intel igent Vehicle Safety Technology(NVHSKL-202207)
文摘The accurate representation of lithium plating and aging phenomena has posed a persistent challenge within the battery research community.Empirical evidence underscores the pivotal role of cell structure in influencing aging behaviors and lithium plating within lithium-ion batteries(LIBs).Available lithium-ion plating models often falter in detailed description when integrating the structural intricacies.To address this challenge,this study proposes an innovative hierarchical model that intricately incorporates the layered rolling structure in cells.Notably,our model demonstrates a remarkable capacity to predict the non-uniform distribution of current density and overpotential along the rolling direction of LIBs.Subsequently,we delve into an insightful exploration of the structural factors that influence lithium plating behavior,leveraging the foundation laid by our established model.Furthermore,we easily update the hierarchical model by considering aging factors.This aging model effectively anticipates capacity fatigue and lithium plating tendencies across individual layers of LIBs,all while maintaining computational efficiency.In light of our findings,this model yields novel perspectives on capacity fatigue dynamics and local lithium plating behaviors,offering a substantial advancement compared to existing models.This research paves the way for more efficient and tailored LIB design and operation,with broad implications for energy storage technologies.
基金supported by the Defense Foundation Scientific Research Fund under Grant No.9140A17030308DZ02,9140A16060409DZ02the National Natural Science Fundation of Chinaunder Grant No.60934002Dr.Lianke for the extensive discussions on the subject and UESTC for its support under Grant No.JX0756,Y02018023601059
文摘Due to the shortcomings of the diagnosis systems for complex electronic devices such as failure models hard to build and low fault isolation resolution, a new hierarchical modeling and diagnosis method is proposed based on multisignal model and support vector machine （SVM）. Multisignal model is used to describe the failure propagation relationship in electronic device system, and the most probable failure printed circuit boards （PCBs） can be found by Bayes inference. The exact failure modes in the PCBs can be identified by SVM. The results show the proposed modeling and diagnosis method is effective and suitable for diagnosis for complex electronic devices.
文摘Multilevel modeling (MLM) has emerged as a powerful statistical framework for analyzing complex data structures with nested relationships. With its hierarchical modeling approach, MLM enables researchers to account for dependencies and variations within and between different levels of a hierarchy. By explicitly modeling these relationships, MLM provides a robust and accurate analysis of data. It has become increasingly popular in the field of education. MLM enables the investigation of various research issues, the evaluation of individual and group-level indicators, and the calculation of both fixed and random effects. Overall, MLM revolutionizes data analysis by uncovering patterns, understanding contextual effects, and making more precise statistical inferences in complex datasets. For fitting multilevel models in R, use lmer function provided by lme4 package. Through this examination, the use of a multilevel model is expected to increase and revolutionize data analysis and decision-making. The Constrained Intermediate Model (CIM) and Augmented Intermediate model (AIM) deviation are compared using the Likelihood-ratio (LR) test and the ANOVA function. This study analyzes student results from the University of Agriculture Faisalabad, collected via stratified random sampling. A linear mixed-effect model under multilevel modeling estimates the impact on CGPA, considering department, gender, intermediate marks, and entry test scores. These results indicate that Entry test is a significant predictor of CGPA, but the effect of department identifier CMC on CGPA is not statistically significant.
基金supported by the National Natural Science Foundation of China under Grant Nos.61751206,61673290 and 61876118the Postgraduate Research&Practice Innovation Program of Jiangsu Province of China under Grant No.KYCX20_2669a project funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD).
文摘Document-level machine translation(MT)remains challenging due to its difficulty in efficiently using documentlevel global context for translation.In this paper,we propose a hierarchical model to learn the global context for documentlevel neural machine translation(NMT).This is done through a sentence encoder to capture intra-sentence dependencies and a document encoder to model document-level inter-sentence consistency and coherence.With this hierarchical architecture,we feedback the extracted document-level global context to each word in a top-down fashion to distinguish different translations of a word according to its specific surrounding context.Notably,we explore the effect of three popular attention functions during the information backward-distribution phase to take a deep look into the global context information distribution of our model.In addition,since large-scale in-domain document-level parallel corpora are usually unavailable,we use a two-step training strategy to take advantage of a large-scale corpus with out-of-domain parallel sentence pairs and a small-scale corpus with in-domain parallel document pairs to achieve the domain adaptability.Experimental results of our model on Chinese-English and English-German corpora significantly improve the Transformer baseline by 4.5 BLEU points on average which demonstrates the effectiveness of our proposed hierarchical model in document-level NMT.
基金supported by the Foundation of the University of Quebec in Abitibi-Témiscamingue(FUQAT)Quebec Research Fund(FRQ)(2021-SE7-282961)。
文摘Understanding plant community assembly is crucial for effective ecosystem conservation and restoration.The ecological filter framework describes community assembly as a process shaped by dispersal,environmental,and biotic filters.Additionally,functional traits and phylogenetic relationships are increasingly recognized as important factors influencing species coexistence and community structure.However,both the ecological filter framework and the roles of functional traits and phylogeny in community assembly remain underexplored in the Algerian steppes—particularly in the El Bayadh region,where ongoing vegetation degradation threatens ecosystem stability.This study applied Hierarchical Modeling of Species Communities(HMSC)as an integrative approach to assess how ecological filters influence plant community assembly in the El Bayadh steppe and to evaluate the roles of functional traits and phylogenetic relationships in this process.Environmental data—including soil properties,topography,precipitation,and land use types(grazing and exclosure)—were collected across 50 plots in April and October,2023,along with functional traits from 24 species.These traits include root length,leaf area,specific leaf area,clonality,life history,and seed mass.HMSC results revealed that soil properties and precipitation were the primary drivers of community structure,while sand height and elevation had a moderate influence.In contrast,competition and grazing played relatively minor roles.Species responses to environmental covariates were heterogeneous:soil fertility and texture had mixed effects,benefiting some species while limiting others;sand encroachment and precipitation variability generally had negative impacts,whereas grazing exclusion favored many species.A weak phylogenetic signal was recorded,indicating that community assembly was driven more by environmental filtering than by shared evolutionary history.Functional trait responses to environmental variation reflected plant strategies that balanced resource acquisition and conservation.Specifically,seed mass,leaf area,and root length increased under higher soil moisture and nutrient availability but declined in response to salinity,precipitation variability,and sand height.Clonality and perennial life history traits enhanced the survival of plant species under harsh conditions.Overall,this study provides a holistic understanding of community assembly processes in the El Bayadh steppe and offers valuable insights for ecosystem management and restoration in arid and degraded ecosystem environments.
基金supported by the Bushfire and Natural Hazards Cooperative Research Centre and New South Wales National Parks and Wildlife Service.
文摘Temperate rainforests have historically been considered highly vulnerable to disturbance.Climate change,which is expected to increase the intensity,frequency,and impacts of disturbance events,is consequently a significant threat to their long-term persistence.However,data describing the long-term response of temperate rainforests to disturbance is rare.In the cool temperate rainforests of northern New South Wales,Australia,Nothofagus moorei is considered especially vulnerable to climate change due to a decreasing number of mature individuals,limited remaining suitable habitat,and low rates of sexual regeneration.In this study,we used over 50 years of empirical data from silvicultural experiments with multiple thinning intensities to characterise the demographic responses(i.e.,growth,mortality,and recruitment)of cool temperate rainforest species,including N.moorei,to disturbance over time.Cool temperate rainforest species showed resilience to disturbance,predominantly through their widespread ability to basally coppice.Nothofagus moorei,in particular,demonstrated higher rates of successful sexual and vegetative recruitment and grew faster in response to higher intensities of disturbance,in comparison to very low rates of recruitment pre-disturbance.These results challenge successional models that position rainforests as disturbance-sensitive ecosystems and identify N.moorei as a species that requires large-scale disturbance to successfully regenerate.Management regimes that actively exclude disturbance from these forests risk the local loss of disturbance-dependent rainforest species such as N.moorei.
文摘Maintaining optimal quality of life(QoL)is a pivotal for“successful aging”.Understanding how the QoL of the elderly develops and what role psychological factors play in its development will help improve QoL from a psychological perspective.Embedded within the lifespan theory of control,this longitudinal study aimed to(1)map the temporal trajectory of QoL among Chinese older adults,(2)examine differential effects of tripartite negative emotions(stress,anxiety,depression),and(3)test themoderating role of control strategies(goal engagement,goal disengagement,self-protection)in emotion-QoL dynamics.A prospective cohort of 345 community-dwelling older adults(Mage=83.84±8.49 years;55.1%female)completed validated measures-SF-36 for QoL,DASS-21 for negative emotions,and an adapted Control Strategies Questionnaire(CAS)-at three waves spanning 12 months.Hierarchical linear modeling(HLM)with time-nested structure analyzed intraindividual changes and interindividual differences.QoL exhibited a significant linear decline over time(β=−4.75,p<0.001).Stress(β=−14.12,p<0.001)and anxiety(β=−11.24,p<0.001)robustly predicted QoL decline,whereas depression showed no significant effect.Control strategies had divergent associations:goal engagement(β=3.51,p<0.001)and self-protection(β=2.38,p=0.015)predicted higher baseline QoL,while goal disengagement accelerated decline(β=−7.00,p<0.001;interaction with time:β=−2.46,p<0.001).Contrary to hypotheses,control strategies did not moderate emotion-QoL associations(ΔR2=0.02,p=0.21).The results showed that stress and anxiety played an important role in the QoL of the elderly.At the same time,goal engagement and self-protection were beneficial to the QoL of the elderly,while goal disengagement was not conducive to QoL and its development among the elderly.Meanwhile,the negative effect of anxiety and stress on the QoL of the elderly was not affected by the control strategies.
基金co-supported by National Natural Science Foundation of China(No.51975124)Shanghai International Cooperation Project of One Belt and One Road of China(No.20110741700)Major Research Special Project of Aeroengine and Gas Turbine of China(No.J2019-IV-0016)。
文摘In structural simulation and design,an accurate computational model directly determines the effectiveness of performance evaluation.To establish a high-fidelity dynamic model of a complex assembled structure,a Hierarchical Model Updating Strategy(HMUS)is developed for Finite Element(FE)model updating with regard to uncorrelated modes.The principle of HMUS is first elaborated by integrating hierarchical modeling concept,model updating technology with proper uncorrelated mode treatment,and parametric modeling.In the developed strategy,the correct correlated mode pairs amongst the uncorrelated modes are identified by an error minimization procedure.The proposed updating technique is validated by the dynamic FE model updating of a simple fixed–fixed beam.The proposed HMUS is then applied to the FE model updating of an aeroengine stator system(casings)to demonstrate its effectiveness.Our studies reveal that(A)parametric modeling technique is able to build an efficient equivalent model by simplifying complex structure in geometry while ensuring the consistency of mechanical characteristics;(B)the developed model updating technique efficiently processes the uncorrelated modes and precisely identifies correct Correlated Mode Pairs(CMPs)between FE model and experiment;(C)the proposed HMUS is accurate and efficient in the FE model updating of complex assembled structures such as aeroengine casings with large-scale model,complex geometry,high-nonlinearity and numerous parameters;(D)it is appropriate to update a complex structural FE model parameterized.The efforts of this study provide an efficient updating strategy for the dynamic model updating of complex assembled structures with experimental test data,which is promising to promote the precision and feasibility of simulation-based design optimization and performance evaluation of complex structures.
基金The authors gratefully acknowledge the support of the National Natural Science Foundation of China under Grant No.62076204 and Grant No.61612385in part by the Postdoctoral Science Foundation of China under Grants No.2021M700337in part by the Fundamental Research Funds for the Central Universities under Grant No.3102019ZX016.
文摘Online accurate recognition of target tactical intention in beyond-visual-range (BVR) air combat is an important basis for deep situational awareness and autonomous air combat decision-making, which can create pre-emptive tactical opportunities for the fighter to gain air superiority. The existing methods to solve this problem have some defects such as dependence on empirical knowledge, difficulty in interpreting the recognition results, and inability to meet the requirements of actual air combat. So an online hierarchical recognition method for target tactical intention in BVR air combat based on cascaded support vector machine (CSVM) is proposed in this study. Through the mechanism analysis of BVR air combat, the instantaneous and cumulative feature information of target trajectory and relative situation information are introduced successively using online automatic decomposition of target trajectory and hierarchical progression. Then the hierarchical recognition model from target maneuver element, tactical maneuver to tactical intention is constructed. The CSVM algorithm is designed for solving this model, and the computational complexity is decomposed by the cascaded structure to overcome the problems of convergence and timeliness when the dimensions and number of training samples are large. Meanwhile, the recognition result of each layer can be used to support the composition analysis and interpretation of target tactical intention. The simulation results show that the proposed method can effectively realize multi-dimensional online accurate recognition of target tactical intention in BVR air combat.
基金co-supported by the National Natural Science Foundation of China(No.11472132)the Fundamental Research Funds for Central Universities in China(No.NS2014002)+1 种基金the Research Fund of State Key Laboratory of Mechanics and Control of Mechanical Structures(Nanjing University of Aeronautics and Astronautics)(No.0113Y01)the Priority Academic Program Development(PAPD)of Jiangsu Higher Education Institutions in China
文摘In this paper, we propose an impact finite element （FE） model for an airbag landing buf- fer system. First, an impact FE model has been formulated for a typical airbag landing buffer system. We use the independence of the structure FE model from the full impact FE model to develop a hierarchical updating scheme for the recovery module FE model and the airbag system FE model. Second, we define impact responses at key points to compare the computational and experimental results to resolve the inconsistency between the experimental data sampling frequency and experi- mental triggering. To determine the typical characteristics of the impact dynamics response of the airbag landing buffer system, we present the impact response confidence factors （IRCFs） to evalu- ate how consistent the computational and experiment results are. An error function is defined between the experimental and computational results at key points of the impact response （KPIR） to serve as a modified objective function. A radial basis function （RBF） is introduced to construct updating variables for a surrogate model for updating the objective function, thereby converting the FE model updating problem to a soluble optimization problem. Finally, the developed method has been validated using an experimental and computational study on the impact dynamics of a classic airbag landing buffer system.
基金Supported by the National Natural Science Foundation of China (No. 79931000) and The State Major Basic Research Development Program (No. G20000263).
文摘Towards integration of supply chain, manufacturing/production and investment decision making, this paper presents a hierarchical model architecture which contains six sub-models covering the areas of manufacturing control, production operation, design and revamp, production management, supply chain and investment decision making. Six types of flow, material, energy, information, humanware, partsware and capital are clasified. These flows connect enterprise components/subsystems to formulate system topology and logical structure. Enterprise components/subsystems are abstracted to generic elementary and composite classes. Finally, the model architecture is applied to a management system of an integrated suply chain, and suggestion are made on the usage of the model architecture and further development of the model as well as implementation issues.
基金supported by the National Science Foundation of China under Grant Nos.71361015,71340010,71371074the Jiangxi Provincial Natural Science Foundation under Grant No.20142BAB201013+2 种基金China Postdoctoral Science Foundation under Grant No.2013M540534China Postdoctoral Fund special Project under Grant No.2014T70615Jiangxi Postdoctoral Science Foundation under Grant No.2013KY53
文摘In the hierarchical random effect linear model, the Bayes estimator of random parameter are not only dependent on specific prior distribution but also it is difficult to calculate in most cases. This paper derives the distributed-free optimal linear estimator of random parameters in the model by means of the credibility theory method. The estimators the authors derive can be applied in more extensive practical scenarios since they are only dependent on the first two moments of prior parameter rather than on specific prior distribution. Finally, the results are compared with some classical models and a numerical example is given to show the effectiveness of the estimators.
基金Project supported by the Natural Science Foundation of ZhejiangProvince, China (No. Y105697)the Ningbo Natural ScienceFoundation,China (No. 2005A610004)
文摘Among complex network models,the hierarchical network model is the one most close to such real networks as world trade web,metabolic network,WWW,actor network,and so on.It has not only the property of power-law degree distribution,but also the scaling clustering coefficient property which Barabási-Albert(BA)model does not have.BA model is a model of network growth based on growth and preferential attachment,showing the scale-free degree distribution property.In this paper,we study the evolution of cooperation on a hierarchical network model,adopting the prisoner's dilemma(PD)game and snowdrift game(SG)as metaphors of the interplay between connected nodes.BA model provides a unifying framework for the emergence of cooperation.But interestingly,we found that on hierarchical model,there is no sign of cooperation for PD game,while the fre-quency of cooperation decreases as the common benefit decreases for SG.By comparing the scaling clustering coefficient prop-erties of the hierarchical network model with that of BA model,we found that the former amplifies the effect of hubs.Considering different performances of PD game and SG on complex network,we also found that common benefit leads to cooperation in the evolution.Thus our study may shed light on the emergence of cooperation in both natural and social environments.
基金Supported by the Science and Technology Development Project Foundation of Tianjin (033800611, 05YFGZGX24200)
文摘This paper presents an anomaly detection approach to detect intrusions into computer systems. In this approach, a hierarchical hidden Markov model （HHMM） is used to represent a temporal profile of normal behavior in a computer system. The HHMM of the norm profile is learned from historic data of the system＇s normal behavior. The observed behavior of the system is analyzed to infer the probability that the HHMM of the norm profile supports the observed behavior. A low probability of support indicates an anomalous behavior that may result from intrusive activities. The model was implemented and tested on the UNIX system call sequences collected by the University of New Mexico group. The testing results showed that the model can clearly identify the anomaly activities and has a better performance than hidden Markov model.
基金supported by the National Natural Science Foundation of China(Grants No.51779074 and 41371052)the Special Fund for the Public Welfare Industry of the Ministry of Water Resources of China(Grant No.201501059)+3 种基金the National Key Research and Development Program of China(Grant No.2017YFC0404304)the Jiangsu Water Conservancy Science and Technology Project(Grant No.2017027)the Program for Outstanding Young Talents in Colleges and Universities of Anhui Province(Grant No.gxyq2018143)the Natural Science Foundation of Wanjiang University of Technology(Grant No.WG18030)
文摘This study developed a hierarchical Bayesian(HB)model for local and regional flood frequency analysis in the Dongting Lake Basin,in China.The annual maximum daily flows from 15 streamflow-gauged sites in the study area were analyzed with the HB model.The generalized extreme value(GEV)distribution was selected as the extreme flood distribution,and the GEV distribution location and scale parameters were spatially modeled through a regression approach with the drainage area as a covariate.The Markov chain Monte Carlo(MCMC)method with Gibbs sampling was employed to calculate the posterior distribution in the HB model.The results showed that the proposed HB model provided satisfactory Bayesian credible intervals for flood quantiles,while the traditional delta method could not provide reliable uncertainty estimations for large flood quantiles,due to the fact that the lower confidence bounds tended to decrease as the return periods increased.Furthermore,the HB model for regional analysis allowed for a reduction in the value of some restrictive assumptions in the traditional index flood method,such as the homogeneity region assumption and the scale invariance assumption.The HB model can also provide an uncertainty band of flood quantile prediction at a poorly gauged or ungauged site,but the index flood method with L-moments does not demonstrate this uncertainty directly.Therefore,the HB model is an effective method of implementing the flexible local and regional frequency analysis scheme,and of quantifying the associated predictive uncertainty.
文摘3D and 2D closed form plate models are here applied to static analysis of simply supported square isotropic plates. 2D theories are hierarchically classified on the basis of the accuracy of the displacements and stresses obtained by comparison to the 3D exact results that could be assumed by the reader as benchmark for further analyses. Attention is mainly paid on localized loading conditions, that is, piecewise constant load. Also bi-sinusoidal and uniformly distributed loadings are taken into account. All of those configurations are considered in order to investigate the behavior of the 2D models in the case of continu- ous/uncontinuous, centric or off-centric loading conditions. The ratio between the side length a and the plate thickness h has been assumed as analysis parameter. Higher order 2D models yield accurate results for any considered load condition in the case of moderately thick plates, a/h=10. In the case of thick plates, a/h=5, and continuous/uncontinuous centric loading conditions high accuracy is also obtained. For the considered off-centric load condition and thick plates good results are provided for some output quantities. A better solution could be achieved by simply increasing the polynomial approximation order of the axiomatic 2D displacement field.
文摘In order to compare the aviation network of mid-south,northwest and southwest of China to reveal the structure similarity and difference for providing quantitative evidence to construct regional aviation network and improve its structure,hierarchical index model of regional aviation network was established through dividing the aviation network into layers to research its structure characters.Data matrixes were defined to record the basic state of regional aviation network.Index matrixes were constructed to describe the quantitative features of regional aviation network.On the basis of these indexes,several structure indexes of all layers of aviation network were calculated to show the structure features of aviation network,such as ratio of passenger volume within the region with across the region,share rate of passenger volume among layers,ratio of average number of airline for each airport,ratio of average passenger volume for each airline and ratio of airline rate.According to the statistical data,similar structure of share rate of passenger volume among layers and average passenger volume for each airline in their regional aviation network was found after calculating.But on the side of ratio of passenger volume within the region with across the region,ratio of average number of airlines for each airport and ratio of airline rate were different.
文摘Digital libraries are complex systems and this brings difficulties for their evaluation. This paper proposes a hierarchical model to solve this problem, and puts the entangled matters into a clear-layered structure. Firstly, digital libraries(DLs thereafter)are classified into 5 groups in ascending gradations, i.e. mini DLs, small DLs, medium DLs,large DLs, and huge DLs by their scope of operation. Then, according to the characteristics of DLs at different operational scope and level of sophistication, they are further grouped into unitary DLs, union DLs and hybrid DLs accordingly. Based on this simulated structure,a hierarchical model for digital library evaluation is introduced, which evaluates DLs differentiatingly within a hierarchical scheme by using varying criteria based on their specific level of operational complexity such as at the micro-level, medium-level, and/or at the macro-level. Based on our careful examination and analysis of the current literature about DL evaluation system, an experiment is conducted by using the DL evaluation model along with its criteria for unitary DLs at micro-level. The main contents resulting from this evaluation experimentation and also those evaluation indicators and relevant issues of major concerns for DLs at medium-level and macro-level are also to be presented at some length.
基金Start-up foundation item of the Educational Department of China for returnees
文摘Hierarchical evolutionary algorithms based on genetic algorithms (GAs) and Nash strategy of game theory are proposed to accelerate the optimization process and implemented in transonic aerodynamic shape optimization problems Inspired from the natural evolution history that different periods with certain environments have different criteria for the evaluations of individuals’ fitness, a hierarchical fidelity model is introduced to reach high optimization efficiency The shape of an NACA0012 based airfoil is optimized in maximizing the lift coefficient under a given transonic flow condition Optimized results are presented and compared with the single model results and traditional GA
文摘Computational complexity of complex system multiple fault diagnosis is a puzzle at all times. Based on the well known Mozetic＇s approach, a novel hierarchical model-based diagnosis methodology is put forward for improving efficency of multi-fault recognition and localization. Structural abstraction and weighted fault propagation graphs are combined to build diagnosis model. The graphs have weighted arcs with fault propagation probabilities and propagation strength. For solving the problem of coupled faults, two diagnosis strategies are used： one is the Lagrangian relaxation and the primal heuristic algorithms; another is the method of propagation strength. Finally, an applied example shows the applicability of the approach and experimental results are given to show the superiority of the presented technique.
