Based on analyzing the influences of a slicing scheme on stair-stepping effect, supporting structure, efficiency and deformation, etc. , analytical hierarchical process （AHP） combining with fuzzy synthetic evaluatio...Based on analyzing the influences of a slicing scheme on stair-stepping effect, supporting structure, efficiency and deformation, etc. , analytical hierarchical process （AHP） combining with fuzzy synthetic evaluation is introduced to make decision in slicing schemes for a processing part. The application in determining the slicing scheme for a computer mouse during prototyping shows that the method increases the rationality during decision- making and improves quality and efficiency for the prototyping part.展开更多
The rapid development of evolutionary deep learning has led to the emergence of various Neural Architecture Search(NAS)algorithms designed to optimize neural network structures.However,these algorithms often face sign...The rapid development of evolutionary deep learning has led to the emergence of various Neural Architecture Search(NAS)algorithms designed to optimize neural network structures.However,these algorithms often face significant computational costs due to the time-consuming process of training neural networks and evaluating their performance.Traditional NAS approaches,which rely on exhaustive evaluations and large training datasets,are inefficient for solving complex image classification tasks within limited time frames.To address these challenges,this paper proposes a novel NAS algorithm that integrates a hierarchical evaluation strategy based on Surrogate models,specifically using supernet to pre-trainweights and randomforests as performance predictors.This hierarchical framework combines rapid Surrogate model evaluations with traditional,precise evaluations to balance the trade-off between performance accuracy and computational efficiency.The algorithm significantly reduces the time required for model evaluation by predicting the fitness of candidate architectures using a random forest Surrogate model,thus alleviating the need for full training cycles for each architecture.The proposed method also incorporates evolutionary operations such as mutation and crossover to refine the search process and improve the accuracy of the resulting architectures.Experimental evaluations on the CIFAR-10 and CIFAR-100 datasets demonstrate that the proposed hierarchical evaluation strategy reduces the search time and costs compared to traditional methods,while achieving comparable or even superior model performance.The results suggest that this approach can efficiently handle resourceconstrained tasks,providing a promising solution for accelerating the NAS process without compromising the quality of the generated architectures.展开更多
In order to meet the demand of testability analysis and evaluation for complex equipment under a small sample test in the equipment life cycle, the hierarchical hybrid testability model- ing and evaluation method （HH...In order to meet the demand of testability analysis and evaluation for complex equipment under a small sample test in the equipment life cycle, the hierarchical hybrid testability model- ing and evaluation method （HHTME）, which combines the testabi- lity structure model （TSM） with the testability Bayesian networks model （TBNM）, is presented. Firstly, the testability network topo- logy of complex equipment is built by using the hierarchical hybrid testability modeling method. Secondly, the prior conditional prob- ability distribution between network nodes is determined through expert experience. Then the Bayesian method is used to update the conditional probability distribution, according to history test information, virtual simulation information and similar product in- formation. Finally, the learned hierarchical hybrid testability model （HHTM） is used to estimate the testability of equipment. Compared with the results of other modeling methods, the relative deviation of the HHTM is only 0.52%, and the evaluation result is the most accu rate.展开更多
Aspect-oriented modeling can uncover potential design faults,yet most existing work fails to achieve both separation and composition in a natural and succinct way.This study presents an aspect-oriented modeling and an...Aspect-oriented modeling can uncover potential design faults,yet most existing work fails to achieve both separation and composition in a natural and succinct way.This study presents an aspect-oriented modeling and analysis approach with hierarchical Coloured Petri Nets(HCPN).HCPN has sub-models and well-defined semantics combining a set of submodels.These two characteristics of HCPN are nicely integrated into aspect oriented modeling.Submodels are used to model aspects while the combination mechanism contributes to aspects weaving.Furthermore,the woven aspect oriented HCPN model can be simulated and analyzed by the CPN Tools.A systematic web application case study is conducted.The results show the system original properties are satisfied after weaving aspects and all design flaws are revealed.As such,the approach can support web application design and analysis in an aspect-oriented fashion concisely and effectively.展开更多
The complexity of large-scale network systems made of a large number of nonlinearly interconnected components is a restrictive facet for their modeling and analysis. In this paper, we propose a framework of hierarchic...The complexity of large-scale network systems made of a large number of nonlinearly interconnected components is a restrictive facet for their modeling and analysis. In this paper, we propose a framework of hierarchical modeling of a complex network system, based on a recursive unsupervised spectral clustering method. The hierarchical model serves the purpose of facilitating the management of complexity in the analysis of real-world critical infrastructures. We exemplify this by referring to the reliability analysis of the 380 kV Italian Power Transmission Network (IPTN). In this work of analysis, the classical component Importance Measures (IMs) of reliability theory have been extended to render them compatible and applicable to a complex distributed network system. By utilizing these extended IMs, the reliability properties of the IPTN system can be evaluated in the framework of the hierarchical system model, with the aim of providing risk managers with information on the risk/safety significance of system structures and components.展开更多
The multi-fidelity Kriging model is a promising technique in surrogate-based design,balancing model accuracy and the cost of sample generation by combining low-and high-fidelity data.However,the cost of building a mul...The multi-fidelity Kriging model is a promising technique in surrogate-based design,balancing model accuracy and the cost of sample generation by combining low-and high-fidelity data.However,the cost of building a multifidelity Kriging model increases significantly as problem complexity grows.To address this issue,we propose an e cient Hierarchical Kriging modeling method.In building the low-fidelity model,distance correlation is used to determine the relative value of the hyperparameter.This transforms the maximum likelihood estimation problem into a one-dimensional optimization task,which can be solved e ciently,significantly improving modeling e ciency.The high-fidelity model is built similarly,with the low-fidelity model's hyperparameter used as the relative value for the high-fidelity model's hyperparameter.The proposed method's e ectiveness is evaluated through analytical problems and a real-world engineering problem involving modeling the isentropic e ciency of a compressor rotor.Experimental results show that the proposed method reduces modeling time significantly without compromising accuracy.For the compressor rotor isentropic e ciency model,the proposed method yields over 99%cost savings compared to conventional approaches,while also achieving higher accuracy.展开更多
Civil aircraft maintenance process simulation model is an effective method for analyzing the maintainability of a civil aircraft. First, we present the Hierarchical Colored Timed Petri Nets for maintenance process mod...Civil aircraft maintenance process simulation model is an effective method for analyzing the maintainability of a civil aircraft. First, we present the Hierarchical Colored Timed Petri Nets for maintenance process modeling of civil aircraft. Then, we expound a general method of civil aircraft maintenance activities, determine the maintenance level for decomposition, and propose the methods of describing logic of relations between the maintenance activities based on Petri Net. Finally, a time Colored Petri multi-level network modeling and simulation procedures and steps are given with the maintenance example of the landing gear burst tire of a certain type of aircraft. The feasibility of the method is proved by the example.展开更多
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
Problem statement: The results of the study of seism acoustic emission arising in a porous two-phase geological environment under acoustic influence are presented. Acoustic emission arising in reservoirs of oil fields...Problem statement: The results of the study of seism acoustic emission arising in a porous two-phase geological environment under acoustic influence are presented. Acoustic emission arising in reservoirs of oil fields using good observations is considered. The regularity of the emission processes of acoustic emission, which manifests itself in the form of discrete spectra of signals similar to oscillations of nonlinearly coupled oscillators, is shown. Spectra have special characteristics for each type of rock. Applied method and design: An algorithm for modeling the process of resonant acoustic response of a porous fluid-saturated reservoir with hierarchical structure and plastic properties on acoustic frequency excitation is developed. That algorithm is developed as an iterative process for the solution integral and integral-differential equations. The frequencies that are parameters of the direct problem are used from the spectra of observed data of acoustic emission in the oil wells. Typical results: For the first time, it had been found the relation between resonant frequencies of the acoustic emission and plastic properties, these values of frequencies had been used in the algorithm of modeling distribution of longitudinal waves in the fluid saturated nonlinear plastic environment. Concluding note (Practical value/implications): The analysis of these emission processes can serve as a source of information about the filtration-capacitive properties of productive reservoirs of a porous type with a hierarchical structure. It is used by practical data of oil fields of Western Siberia.展开更多
This paper deals with the statistical modeling of latent topic hierarchies in text corpora. The height of the topic tree is assumed as fixed, while the number of topics on each level as unknown a priori and to be infe...This paper deals with the statistical modeling of latent topic hierarchies in text corpora. The height of the topic tree is assumed as fixed, while the number of topics on each level as unknown a priori and to be inferred from data. Taking a nonpara-metric Bayesian approach to this problem, we propose a new probabilistic generative model based on the nested hierarchical Dirichlet process (nHDP) and present a Markov chain Monte Carlo sampling algorithm for the inference of the topic tree structure as well as the word distribution of each topic and topic distribution of each document. Our theoretical analysis and experiment results show that this model can produce a more compact hierarchical topic structure and captures more fine-grained topic rela-tionships compared to the hierarchical latent Dirichlet allocation model.展开更多
. In this article, we describe the characteristics of large-scale modeling of the theme text of this site data and important progress in recent years. Topic modeling approach has attracted wide interest in the world, .... In this article, we describe the characteristics of large-scale modeling of the theme text of this site data and important progress in recent years. Topic modeling approach has attracted wide interest in the world, and promote a number of important data mining, development of computer vision and computational biology applications, including automatic text summaries, information retrieval, information recommendation, topic detection and tracking, natural scene understanding human action recognition and gene expression analysis. The main features of the model and the corresponding theme paper focuses on the text of this site data. Data with dynamic, high-end, multi-channel and distributed structure and the structure of the model is only part of the theme before modeling. The paper discussed in the framework of the unity of the three-dimensional Markov model of four structural features of the text of this site data modeling, and analysis of distributed computing and word combination of three-dimensional modeling topics Markov model and type fuzzy systems the possibility of applications. In addition to structural modeling for this site text data, also we discuss some of the three-dimensional Markov model energy minimization of machine learning algorithms.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
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 base...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
In the enormous and still poorly mastered gap between the macro level, where well developed continuum theories of continuous media and engineering methods of calculation and design operate, and atomic, subordinate to ...In the enormous and still poorly mastered gap between the macro level, where well developed continuum theories of continuous media and engineering methods of calculation and design operate, and atomic, subordinate to the laws of quantum mechanics, there is an extensive meso-hierarchical level of the structure of matter. At this level unprecedented previously products and technologies can be artificially created. Nano technology is a qualitatively new strategy in technology: it creates objects in exactly the opposite way—large objects are created from small ones [1]. We have developed a new method for modeling acoustic monitoring of a layered-block elastic medium with several inclusions of various physical and mechanical hierarchical structures [2]. An iterative process is developed for solving the direct problem for the case of three hierarchical inclusions of l, m, s-th ranks based on the use of 2D integro-differential equations. The degree of hierarchy of inclusions is determined by the values of their ranks, which may be different, while the first rank is associated with the atomic structure, the following ranks are associated with increasing geometric sizes, which contain inclusions of lower ranks and sizes. Hierarchical inclusions are located in different layers one above the other: the upper one is abnormally plastic, the second is abnormally elastic and the third is abnormally dense. The degree of filling with inclusions of each rank for all three hierarchical inclusions is different. Modeling is carried out from smaller sizes to large inclusions;as a result, it becomes possible to determine the necessary parameters of the formed material from acoustic monitoring data.展开更多
Interacting multiple models is the hotspot in the research of maneuvering target models at present. A hierarchical idea is introduced into IMM algorithm. The method is that the whole models are organized as two levels...Interacting multiple models is the hotspot in the research of maneuvering target models at present. A hierarchical idea is introduced into IMM algorithm. The method is that the whole models are organized as two levels to co-work, and each cell model is an improved ＂current＂ statistical model. In the improved model, a kind of nonlinear fuzzy membership function is presented to get over the limitation of original model, which can not track weak maneuvering target precisely. At last, simulation experiments prove the efficient of the novel algorithm compared to interacting multiple model and hierarchical interacting multiple model based original ＂current＂ statistical model in tracking precision.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
Hierarchical identity based cryptography is a generalization of identity based encryption that mirrors an organizational hierarchy. It allows a root public key generator to distribute the workload by delegating public...Hierarchical identity based cryptography is a generalization of identity based encryption that mirrors an organizational hierarchy. It allows a root public key generator to distribute the workload by delegating public key generation and identity authentication to lower-level public key generators. Most hierarchical identity based signature schemes are provably secure in the random oracle model or the weak models without random oracles such as gauntlet-ID model. Currently, there is no hierarchical identity based signature scheme that is fully secure in the standard model, with short public parameters and a tight reduction. In this paper, a hierarchical identity based signature scheme based on the q-SDH problem that is fully secure in the standard model is proposed. The signature size is independent of the level of the hierarchy. Moreover, our scheme has short public parameters, high efficiency and a tight reduction.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
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
基金Supported by the Science and Technology Support Key Project of Jiangsu Province (DE2008365)~~
文摘Based on analyzing the influences of a slicing scheme on stair-stepping effect, supporting structure, efficiency and deformation, etc. , analytical hierarchical process （AHP） combining with fuzzy synthetic evaluation is introduced to make decision in slicing schemes for a processing part. The application in determining the slicing scheme for a computer mouse during prototyping shows that the method increases the rationality during decision- making and improves quality and efficiency for the prototyping part.
文摘The rapid development of evolutionary deep learning has led to the emergence of various Neural Architecture Search(NAS)algorithms designed to optimize neural network structures.However,these algorithms often face significant computational costs due to the time-consuming process of training neural networks and evaluating their performance.Traditional NAS approaches,which rely on exhaustive evaluations and large training datasets,are inefficient for solving complex image classification tasks within limited time frames.To address these challenges,this paper proposes a novel NAS algorithm that integrates a hierarchical evaluation strategy based on Surrogate models,specifically using supernet to pre-trainweights and randomforests as performance predictors.This hierarchical framework combines rapid Surrogate model evaluations with traditional,precise evaluations to balance the trade-off between performance accuracy and computational efficiency.The algorithm significantly reduces the time required for model evaluation by predicting the fitness of candidate architectures using a random forest Surrogate model,thus alleviating the need for full training cycles for each architecture.The proposed method also incorporates evolutionary operations such as mutation and crossover to refine the search process and improve the accuracy of the resulting architectures.Experimental evaluations on the CIFAR-10 and CIFAR-100 datasets demonstrate that the proposed hierarchical evaluation strategy reduces the search time and costs compared to traditional methods,while achieving comparable or even superior model performance.The results suggest that this approach can efficiently handle resourceconstrained tasks,providing a promising solution for accelerating the NAS process without compromising the quality of the generated architectures.
基金supported by the National Defense Pre-research Foundation of China(51327030104)
文摘In order to meet the demand of testability analysis and evaluation for complex equipment under a small sample test in the equipment life cycle, the hierarchical hybrid testability model- ing and evaluation method （HHTME）, which combines the testabi- lity structure model （TSM） with the testability Bayesian networks model （TBNM）, is presented. Firstly, the testability network topo- logy of complex equipment is built by using the hierarchical hybrid testability modeling method. Secondly, the prior conditional prob- ability distribution between network nodes is determined through expert experience. Then the Bayesian method is used to update the conditional probability distribution, according to history test information, virtual simulation information and similar product in- formation. Finally, the learned hierarchical hybrid testability model （HHTM） is used to estimate the testability of equipment. Compared with the results of other modeling methods, the relative deviation of the HHTM is only 0.52%, and the evaluation result is the most accu rate.
基金supported by the NSF of China under grants No.61173048 and No.61300041Specialized Research Fund for the Doctoral Program of Higher Education under grant No.20130074110015+2 种基金the Fundamental Research Funds for the Central Universities under Grant No.WH1314038the Humanities and Social Science Research Planning Fund of the Education Ministry of China under grant No.15YJCZH201the Research Innovation Program of Shanghai Municipal Education Commission under grant No.14YZ134
文摘Aspect-oriented modeling can uncover potential design faults,yet most existing work fails to achieve both separation and composition in a natural and succinct way.This study presents an aspect-oriented modeling and analysis approach with hierarchical Coloured Petri Nets(HCPN).HCPN has sub-models and well-defined semantics combining a set of submodels.These two characteristics of HCPN are nicely integrated into aspect oriented modeling.Submodels are used to model aspects while the combination mechanism contributes to aspects weaving.Furthermore,the woven aspect oriented HCPN model can be simulated and analyzed by the CPN Tools.A systematic web application case study is conducted.The results show the system original properties are satisfied after weaving aspects and all design flaws are revealed.As such,the approach can support web application design and analysis in an aspect-oriented fashion concisely and effectively.
文摘The complexity of large-scale network systems made of a large number of nonlinearly interconnected components is a restrictive facet for their modeling and analysis. In this paper, we propose a framework of hierarchical modeling of a complex network system, based on a recursive unsupervised spectral clustering method. The hierarchical model serves the purpose of facilitating the management of complexity in the analysis of real-world critical infrastructures. We exemplify this by referring to the reliability analysis of the 380 kV Italian Power Transmission Network (IPTN). In this work of analysis, the classical component Importance Measures (IMs) of reliability theory have been extended to render them compatible and applicable to a complex distributed network system. By utilizing these extended IMs, the reliability properties of the IPTN system can be evaluated in the framework of the hierarchical system model, with the aim of providing risk managers with information on the risk/safety significance of system structures and components.
基金Supported by Research Program of the University of South China(Grant No.220XQD064)。
文摘The multi-fidelity Kriging model is a promising technique in surrogate-based design,balancing model accuracy and the cost of sample generation by combining low-and high-fidelity data.However,the cost of building a multifidelity Kriging model increases significantly as problem complexity grows.To address this issue,we propose an e cient Hierarchical Kriging modeling method.In building the low-fidelity model,distance correlation is used to determine the relative value of the hyperparameter.This transforms the maximum likelihood estimation problem into a one-dimensional optimization task,which can be solved e ciently,significantly improving modeling e ciency.The high-fidelity model is built similarly,with the low-fidelity model's hyperparameter used as the relative value for the high-fidelity model's hyperparameter.The proposed method's e ectiveness is evaluated through analytical problems and a real-world engineering problem involving modeling the isentropic e ciency of a compressor rotor.Experimental results show that the proposed method reduces modeling time significantly without compromising accuracy.For the compressor rotor isentropic e ciency model,the proposed method yields over 99%cost savings compared to conventional approaches,while also achieving higher accuracy.
文摘Civil aircraft maintenance process simulation model is an effective method for analyzing the maintainability of a civil aircraft. First, we present the Hierarchical Colored Timed Petri Nets for maintenance process modeling of civil aircraft. Then, we expound a general method of civil aircraft maintenance activities, determine the maintenance level for decomposition, and propose the methods of describing logic of relations between the maintenance activities based on Petri Net. Finally, a time Colored Petri multi-level network modeling and simulation procedures and steps are given with the maintenance example of the landing gear burst tire of a certain type of aircraft. The feasibility of the method is proved by the example.
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.
文摘Problem statement: The results of the study of seism acoustic emission arising in a porous two-phase geological environment under acoustic influence are presented. Acoustic emission arising in reservoirs of oil fields using good observations is considered. The regularity of the emission processes of acoustic emission, which manifests itself in the form of discrete spectra of signals similar to oscillations of nonlinearly coupled oscillators, is shown. Spectra have special characteristics for each type of rock. Applied method and design: An algorithm for modeling the process of resonant acoustic response of a porous fluid-saturated reservoir with hierarchical structure and plastic properties on acoustic frequency excitation is developed. That algorithm is developed as an iterative process for the solution integral and integral-differential equations. The frequencies that are parameters of the direct problem are used from the spectra of observed data of acoustic emission in the oil wells. Typical results: For the first time, it had been found the relation between resonant frequencies of the acoustic emission and plastic properties, these values of frequencies had been used in the algorithm of modeling distribution of longitudinal waves in the fluid saturated nonlinear plastic environment. Concluding note (Practical value/implications): The analysis of these emission processes can serve as a source of information about the filtration-capacitive properties of productive reservoirs of a porous type with a hierarchical structure. It is used by practical data of oil fields of Western Siberia.
基金Project (No. 60773180) supported by the National Natural Science Foundation of China
文摘This paper deals with the statistical modeling of latent topic hierarchies in text corpora. The height of the topic tree is assumed as fixed, while the number of topics on each level as unknown a priori and to be inferred from data. Taking a nonpara-metric Bayesian approach to this problem, we propose a new probabilistic generative model based on the nested hierarchical Dirichlet process (nHDP) and present a Markov chain Monte Carlo sampling algorithm for the inference of the topic tree structure as well as the word distribution of each topic and topic distribution of each document. Our theoretical analysis and experiment results show that this model can produce a more compact hierarchical topic structure and captures more fine-grained topic rela-tionships compared to the hierarchical latent Dirichlet allocation model.
文摘. In this article, we describe the characteristics of large-scale modeling of the theme text of this site data and important progress in recent years. Topic modeling approach has attracted wide interest in the world, and promote a number of important data mining, development of computer vision and computational biology applications, including automatic text summaries, information retrieval, information recommendation, topic detection and tracking, natural scene understanding human action recognition and gene expression analysis. The main features of the model and the corresponding theme paper focuses on the text of this site data. Data with dynamic, high-end, multi-channel and distributed structure and the structure of the model is only part of the theme before modeling. The paper discussed in the framework of the unity of the three-dimensional Markov model of four structural features of the text of this site data modeling, and analysis of distributed computing and word combination of three-dimensional modeling topics Markov model and type fuzzy systems the possibility of applications. In addition to structural modeling for this site text data, also we discuss some of the three-dimensional Markov model energy minimization of machine learning algorithms.
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 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In the enormous and still poorly mastered gap between the macro level, where well developed continuum theories of continuous media and engineering methods of calculation and design operate, and atomic, subordinate to the laws of quantum mechanics, there is an extensive meso-hierarchical level of the structure of matter. At this level unprecedented previously products and technologies can be artificially created. Nano technology is a qualitatively new strategy in technology: it creates objects in exactly the opposite way—large objects are created from small ones [1]. We have developed a new method for modeling acoustic monitoring of a layered-block elastic medium with several inclusions of various physical and mechanical hierarchical structures [2]. An iterative process is developed for solving the direct problem for the case of three hierarchical inclusions of l, m, s-th ranks based on the use of 2D integro-differential equations. The degree of hierarchy of inclusions is determined by the values of their ranks, which may be different, while the first rank is associated with the atomic structure, the following ranks are associated with increasing geometric sizes, which contain inclusions of lower ranks and sizes. Hierarchical inclusions are located in different layers one above the other: the upper one is abnormally plastic, the second is abnormally elastic and the third is abnormally dense. The degree of filling with inclusions of each rank for all three hierarchical inclusions is different. Modeling is carried out from smaller sizes to large inclusions;as a result, it becomes possible to determine the necessary parameters of the formed material from acoustic monitoring data.
文摘Interacting multiple models is the hotspot in the research of maneuvering target models at present. A hierarchical idea is introduced into IMM algorithm. The method is that the whole models are organized as two levels to co-work, and each cell model is an improved ＂current＂ statistical model. In the improved model, a kind of nonlinear fuzzy membership function is presented to get over the limitation of original model, which can not track weak maneuvering target precisely. At last, simulation experiments prove the efficient of the novel algorithm compared to interacting multiple model and hierarchical interacting multiple model based original ＂current＂ statistical model in tracking precision.
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 (6057303)the Program for New Century Excellent Talents in University by Ministry of Education (NCET-05-0398)
文摘Hierarchical identity based cryptography is a generalization of identity based encryption that mirrors an organizational hierarchy. It allows a root public key generator to distribute the workload by delegating public key generation and identity authentication to lower-level public key generators. Most hierarchical identity based signature schemes are provably secure in the random oracle model or the weak models without random oracles such as gauntlet-ID model. Currently, there is no hierarchical identity based signature scheme that is fully secure in the standard model, with short public parameters and a tight reduction. In this paper, a hierarchical identity based signature scheme based on the q-SDH problem that is fully secure in the standard model is proposed. The signature size is independent of the level of the hierarchy. Moreover, our scheme has short public parameters, high efficiency and a tight reduction.
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.
