The scientific community faces the challenge of measuring progress toward biodiversity targets and indices have been traditionally used.However,recent inventories in secondary tropical mountain forests using tradition...The scientific community faces the challenge of measuring progress toward biodiversity targets and indices have been traditionally used.However,recent inventories in secondary tropical mountain forests using traditional biodiversity indices have yielded results that are indistinct with primary ones.This shows the need to develop complementary indices that goes beyond species count but integrates the distribution and conservation status of the species.This study developed endemicity and conservation importance index for tropical forest that incorporated the distribution and conservation status of the species.These indices were applied to Mt.Natoo,a remnant primary mossy forest in Buguias,Benguet,Philippines,that resulted to endemicity index of 81.07 and conservation importance index of 42.90.Comparing these with secondary forest sites with comparable Shannon-Wiener,Simpson,Evenness and Margalef’s indices,our endemicity and conservation indices clearly differentiates primary forest(our study site)with higher values from secondary forests with much lower values.Thus,we are proposing these indices for a direct but scientifically-informed identification of specific sites for conservation and protection in tropical forests.Additionally,our study documented a total of 168 vascular plant species(79 endemic and 12 locally threatened species)in Mt.Nato-o.Majority are of tropical elements for both generic and species levels with some temperate elements that could be attributed to the site's high elevation and semi-temperate climate.These are important baseline information for conservation plans and monitoring of tropical mossy forests.展开更多
Survival data with amulti-state structure are frequently observed in follow-up studies.An analytic approach based on a multi-state model(MSM)should be used in longitudinal health studies in which a patient experiences...Survival data with amulti-state structure are frequently observed in follow-up studies.An analytic approach based on a multi-state model(MSM)should be used in longitudinal health studies in which a patient experiences a sequence of clinical progression events.One main objective in the MSM framework is variable selection,where attempts are made to identify the risk factors associated with the transition hazard rates or probabilities of disease progression.The usual variable selection methods,including stepwise and penalized methods,do not provide information about the importance of variables.In this context,we present a two-step algorithm to evaluate the importance of variables formulti-state data.Three differentmachine learning approaches(randomforest,gradient boosting,and neural network)as themost widely usedmethods are considered to estimate the variable importance in order to identify the factors affecting disease progression and rank these factors according to their importance.The performance of our proposed methods is validated by simulation and applied to the COVID-19 data set.The results revealed that the proposed two-stage method has promising performance for estimating variable importance.展开更多
The reliability and sensitivity analyses of stator blade regulator usually involve complex characteristics like highnonlinearity,multi-failure regions,and small failure probability,which brings in unacceptable computi...The reliability and sensitivity analyses of stator blade regulator usually involve complex characteristics like highnonlinearity,multi-failure regions,and small failure probability,which brings in unacceptable computing efficiency and accuracy of the current analysismethods.In this case,by fitting the implicit limit state function(LSF)with active Kriging(AK)model and reducing candidate sample poolwith adaptive importance sampling(AIS),a novel AK-AIS method is proposed.Herein,theAKmodel andMarkov chainMonte Carlo(MCMC)are first established to identify the most probable failure region(s)(MPFRs),and the adaptive kernel density estimation(AKDE)importance sampling function is constructed to select the candidate samples.With the best samples sequentially attained in the reduced candidate samples and employed to update the Kriging-fitted LSF,the failure probability and sensitivity indices are acquired at a lower cost.The proposed method is verified by twomulti-failure numerical examples,and then applied to the reliability and sensitivity analyses of a typical stator blade regulator.Withmethods comparison,the proposed AK-AIS is proven to hold the computing advantages on accuracy and efficiency in complex reliability and sensitivity analysis problems.展开更多
Wetlands are widely distributed all over the world,and have many wildlife resources,which are the main pieces of the puzzle for natural resource conservation and sustainable development on earth and have important irr...Wetlands are widely distributed all over the world,and have many wildlife resources,which are the main pieces of the puzzle for natural resource conservation and sustainable development on earth and have important irreplaceability.In this paper,through questionnaire survey,field research,literature review,etc.,importance weight analysis was conducted by using principal component analysis,and field survey and questionnaire were carried out to collect data on ecological environment function,environmental protection function,landscape beautification function,disaster prevention and mitigation function of urban wetlands.The problems in wetland parks of Nanjing were discussed,such as lack of awareness of landscape planning,deficient late management of wetland parks,weak ability of sustainable development,and unreasonable landscape layout and function.Finally,corresponding solutions were proposed,such as adhering to the planning and design of urban wetland parks with green as the base and health as the basis,persisting in the construction of a wetland system with high biodiversity and near-natural characteristics,adhering to the principle of sustainable development,adopting the construction idea of symbiosis and circulation of urban wetland parks,strengthening education and publicity work,and paying attention to the organic combination of system protection and coordinated construction.The research can build a new development direction for the model of urban wetland parks and green healthy cities,and provide theoretical support for urban sustainable construction.展开更多
Attribute reduction is a hot topic in rough set research. As an extension of rough sets, neighborhood rough sets can effectively solve the problem of information loss after data discretization. However, traditional gr...Attribute reduction is a hot topic in rough set research. As an extension of rough sets, neighborhood rough sets can effectively solve the problem of information loss after data discretization. However, traditional greedy-based neighborhood rough set attribute reduction algorithms have a high computational complexity and long processing time. In this paper, a novel attribute reduction algorithm based on attribute importance is proposed. By using conditional information, the attribute reduction problem in neighborhood rough sets is discussed, and the importance of attributes is measured by conditional information gain. The algorithm iteratively removes the attribute with the lowest importance, thus achieving the goal of attribute reduction. Six groups of UCI datasets are selected, and the proposed algorithm SAR is compared with L<sub>2</sub>-ELM, LapTELM, CTSVM, and TBSVM classifiers. The results demonstrate that SAR can effectively improve the time consumption and accuracy issues in attribute reduction.展开更多
As an important part of CNC machine tools,machining center’s reliability,efficiency and accuracy measure the machining level of a CNC machine tool.Therefore,the research on the importance of CNC machine tools is part...As an important part of CNC machine tools,machining center’s reliability,efficiency and accuracy measure the machining level of a CNC machine tool.Therefore,the research on the importance of CNC machine tools is particularly important.However,as a complex mechanical and electrical equipment,the traditional reliability importance analysis method is too simple.In order to solve this problem,this passage proposes to establish the reliability model of each part of the machining center,and then analyze its dynamic importance,which improves the limitation of only reliability importance analysis.Through the analysis the reliability importance and criticality importance,and then rank the result of importance analysis,finally it can get that the ranking results of the key components accord with the fact,so the results can provide support for the importance research of machining center.展开更多
In The Importance of Being Earnest,Oscar Wilde constructs a dandies’world,in which the persons mock at everything and subvert everything.This research analyzes the dandyish features of the character with the aid of C...In The Importance of Being Earnest,Oscar Wilde constructs a dandies’world,in which the persons mock at everything and subvert everything.This research analyzes the dandyish features of the character with the aid of Charles Baudelaire’s definition of dandy and dandyism,and studies Wilde’s subversion of the preexistent binary oppositions by referring to Jonathan Culler’s interpretation of Jacque Derrida’s deconstruction,and points out that Wilde’s writing in Earnest is a deconstructionist writing.He abandons all the so-called essential matters and only focuses on linguistic surface and comic effect.His stance of dandyism challenges the main-stream social norms at his time and foresees the coming artistic trend.展开更多
In a system of systems(SoS),resilience is an important factor in maintaining the functionality,stability,and enhancing the operation effectiveness.From the perspective of resilience,this paper studies the importance o...In a system of systems(SoS),resilience is an important factor in maintaining the functionality,stability,and enhancing the operation effectiveness.From the perspective of resilience,this paper studies the importance of the SoS,and a resilience-based importance measure analysis is conducted to provide suggestions in the design and optimization of the structure of the SoS.In this paper,the components of the SoS are simplified as four kinds of network nodes:sensor,decision point,influencer,and target.In this networked SoS,the number of operation loops is used as the performance indicator,and an approximate algorithm,which is based on eigenvalue of the adjacency matrix,is proposed to calculate the number of operation loops.In order to understand the performance change of the SoS during the attack and defense process in the operations,an integral resilience model is proposed to depict the resilience of the SoS.From different perspectives of enhancing the resilience,different measures,parameters and the corresponding algorithms for the resilience importance of components are proposed.Finally,a case study on an SoS is conducted to verify the validity of the network modelling and the resiliencebased importance analysis method.展开更多
Based on the observation of importance sampling and second order information about the fail-ure surface of a structure,an importance sampling region is defined in V-space which is obtained by ro-tating a U-space at th...Based on the observation of importance sampling and second order information about the fail-ure surface of a structure,an importance sampling region is defined in V-space which is obtained by ro-tating a U-space at the point of maximum likelihood.The sampling region is a hyper-ellipsoid that con-sists of the sampling ellipse on each plane of main curvature in V-space.Thus,the sampling probabilitydensity function can be constructed by the sampling region center and ellipsoid axes.Several exampleshave shown the efficiency and generality of this method.展开更多
The current measurement was exploited in a more efficient way. Firstly, the system equation was updated by introducing a correction term, which depends on the current measurement and can be obtained by running a subop...The current measurement was exploited in a more efficient way. Firstly, the system equation was updated by introducing a correction term, which depends on the current measurement and can be obtained by running a suboptimal filter. Then, a new importance density function(IDF) was defined by the updated system equation. Particles drawn from the new IDF are more likely to be in the significant region of state space and the estimation accuracy can be improved. By using different suboptimal filter, different particle filters(PFs) can be developed in this framework. Extensions of this idea were also proposed by iteratively updating the system equation using particle filter itself, resulting in the iterated particle filter. Simulation results demonstrate the effectiveness of the proposed IDF.展开更多
Coffea(coffee) species are grown in almost all countries along the Equator. Many members of the genus have a large production history and an important role both in the global market and researches. Seeds(Coffeae semen...Coffea(coffee) species are grown in almost all countries along the Equator. Many members of the genus have a large production history and an important role both in the global market and researches. Seeds(Coffeae semen) are successfully used in food, cosmetic, and pharmaceutical industries due to its caffeine and high polyphenol content. Nowadays, the three best-known coffee species are Arabic(Coffea arabica L.), Robusta(Coffea robusta L. Linden), and Liberian coffees(Coffea liberica Hier.). Even though, many records are available on coffee in scientific literature, wild coffee species like Bengal coffee(Coffea benghalensis Roxb. Ex Schult.) could offer many new opportunities and challenges for phytochemical and medical studies. In this comprehensive summary, we focused on the ethnomedicinal, phytochemical, and medical significance of coffee species up to the present.展开更多
Evaluating the node importance correctly is a crucial issue for complex networks research. If a network has multiple or ambiguous morphological features, the evaluation result of an individual index may be unilateral....Evaluating the node importance correctly is a crucial issue for complex networks research. If a network has multiple or ambiguous morphological features, the evaluation result of an individual index may be unilateral. Meanwhile, the results may be inconsistent if different indexes are adopted simultaneously. To solve the problem, an integrated approach is proposed based on relative entropy. In this approach, a system of multiple indexes is constructed firstly. Then each evaluation result of an individual index is handled into a discrete distribution. Finally an optimal integrated evaluation solution is obtained by linear programming.This approach has a well-formed theoretic basis and an easilycalculated procedure, which can be used in a variety of complex networks. Experimental results show that the proposed approach is more effective than other different methods proposed in some literatures.展开更多
BACKGROUND:Ultrasound has the first line investigation role in the diagnosis of acute appendicitis in children.The purpose of this study was to perform a quality assessment review on the visualization rate of appendix...BACKGROUND:Ultrasound has the first line investigation role in the diagnosis of acute appendicitis in children.The purpose of this study was to perform a quality assessment review on the visualization rate of appendix on ultrasound in children in the community hospital setting.METHODS:A retrospective chart review of the abdominal ultrasound findings for the visualization of the appendix was performed on paediatric patients ranging from 5 to 18 years.Data were collected from the two community hospitals of Toronto by using hospital electronic medical record for the ultrasound findings in patients presented with abdominal pain.RESULTS:Data from two community hospitals indicated visualization rate of the appendix as 11.0%and 23.2%for site 1 and site 2 respectively.In cases where the ultrasound was repeated the visualization rate remains the same.A two-proportion z-test was performed to find whether the visualization of appendix increases the likelihood of diagnosing appendicitis.The results revealed that the visualization of an appendix(P=0.52),significantly improved the diagnosis of appendicitis(z=34,P<0.001).CONCLUSION:Visualization of an appendix on ultrasound increases the likelihood of correctly diagnosing appendicitis.In our study,we found low visualization rate of appendix on ultrasound that could be the result of many factors that contribute towards the low visualization rate of an appendix on ultrasound.Hence,the challenges in identifying appendix should be minimized to improve the visualization and diagnosis of appendicitis on ultrasound.展开更多
In order to achieve the information fusion in the time domain based on the evidence theory, an evidence combination method in the time domain based on reliability and importance is proposed according to the idea of ev...In order to achieve the information fusion in the time domain based on the evidence theory, an evidence combination method in the time domain based on reliability and importance is proposed according to the idea of evidence discount. Firstly, the distortion of the time-domain evidence is judged based on single exponential smoothing. The real-time reliability of the evidence at the adjacent time is obtained by the real-time reliability assessment method of the evidence based on the credibility decay model.Then, the relative importance of the evidence at the adjacent time is obtained by comprehensively considering improved conflict degree and uncertainty. Finally, based on the criterion of evidence discount and the Dempster's rule of combination, the evidence combination is carried out to achieve the sequential combination of time-domain evidence. The numerical simulation and analysis show that this method has fully embodied the dynamic characteristics of time-domain evidence combination, and it has strong processing ability for conflict information and anti-disturbing ability.The proposed method has good applicability to information fusion in the time domain.展开更多
Road safety performance function(SPF) analysis using data-driven and nonparametric methods, especially recent developed deep learning approaches, has gained increasing achievements. However, due to the learning mechan...Road safety performance function(SPF) analysis using data-driven and nonparametric methods, especially recent developed deep learning approaches, has gained increasing achievements. However, due to the learning mechanisms are hidden in a"black box" in deep learning, traffic features extraction and intelligent importance analysis are still unsolved and hard to generate.This paper focuses on this problem using a deciphered version of deep neural networks(DNN), one of the most popular deep learning models. This approach builds on visualization, feature importance and sensitivity analysis, can evaluate the contributions of input variables on model's "black box" feature learning process and output decision. Firstly, a visual feature importance(Vi FI) method that describes the importance of input features is proposed by adopting diagram and numerical-analysis. Secondly,by observing the change of weights using Vi FI on unsupervised training and fine-tuning of DNN, the final contributions of input features are calculated according to importance equations for both steps that we proposed. Sequentially, a case study based on a road SPF analysis is demonstrated, using data collected from a major Canadian highway, Highway 401. The proposed method allows effective deciphering of the model's inner workings and allows the significant features to be identified and the bad features to be eliminated. Finally, the revised dataset is used in crash modeling and vehicle collision prediction, and the testing result verifies that the deciphered and revised model achieves state-of-theart performance.展开更多
The influence maximization is the problem of finding k seed nodes that maximize the scope of influence in a social network.Therefore,the comprehensive influence of node needs to be considered,when we choose the most i...The influence maximization is the problem of finding k seed nodes that maximize the scope of influence in a social network.Therefore,the comprehensive influence of node needs to be considered,when we choose the most influential node set consisted of k seed nodes.On account of the traditional methods used to measure the influence of nodes,such as degree centrality,betweenness centrality and closeness centrality,consider only a single aspect of the influence of node,so the influence measured by traditional methods mentioned above of node is not accurate.In this paper,we obtain the following result through experimental analysis:the influence of a node is relevant not only to its degree and coreness,but also to the degree and coreness of the n-order neighbor nodes.Hence,we propose a algorithm based on the mixed importance of nodes to measure the comprehensive influence of node,and the algorithm we proposed is simple and efficient.In addition,the performance of the algorithm we proposed is better than that of traditional influence maximization algorithms.展开更多
Current urban rail transit has become a major mode of transportation, and passenger is an important factor of urban rail transport, so this article is based on passenger and the degree of the road network structure, c...Current urban rail transit has become a major mode of transportation, and passenger is an important factor of urban rail transport, so this article is based on passenger and the degree of the road network structure, calculating the point intensity of stations of urban rail transit, and then reaching a station importance by integrating many point intensities in a survey cycle time, and getting the station importance of urban rail transit network through concrete examples.展开更多
This study was conducted to enable prompt classification of malware,which was becoming increasingly sophisticated.To do this,we analyzed the important features of malware and the relative importance of selected featur...This study was conducted to enable prompt classification of malware,which was becoming increasingly sophisticated.To do this,we analyzed the important features of malware and the relative importance of selected features according to a learning model to assess how those important features were identified.Initially,the analysis features were extracted using Cuckoo Sandbox,an open-source malware analysis tool,then the features were divided into five categories using the extracted information.The 804 extracted features were reduced by 70%after selecting only the most suitable ones for malware classification using a learning model-based feature selection method called the recursive feature elimination.Next,these important features were analyzed.The level of contribution from each one was assessed by the Random Forest classifier method.The results showed that System call features were mostly allocated.At the end,it was possible to accurately identify the malware type using only 36 to 76 features for each of the four types of malware with the most analysis samples available.These were the Trojan,Adware,Downloader,and Backdoor malware.展开更多
This paper presents component importance analysis for virtualized system with live migration. The component importance analysis is significant to determine the system design of virtualized system from availability and...This paper presents component importance analysis for virtualized system with live migration. The component importance analysis is significant to determine the system design of virtualized system from availability and cost points of view. This paper discusses the importance of components with respect to system availability. Specifically, we introduce two different component importance analyses for hybrid model (fault trees and continuous-time Markov chains) and continuous-time Markov chains, and show the analysis for existing probabilistic models for virtualized system. In numerical examples, we illustrate the quantitative component importance analysis for virtualized system with live migration.展开更多
文摘The scientific community faces the challenge of measuring progress toward biodiversity targets and indices have been traditionally used.However,recent inventories in secondary tropical mountain forests using traditional biodiversity indices have yielded results that are indistinct with primary ones.This shows the need to develop complementary indices that goes beyond species count but integrates the distribution and conservation status of the species.This study developed endemicity and conservation importance index for tropical forest that incorporated the distribution and conservation status of the species.These indices were applied to Mt.Natoo,a remnant primary mossy forest in Buguias,Benguet,Philippines,that resulted to endemicity index of 81.07 and conservation importance index of 42.90.Comparing these with secondary forest sites with comparable Shannon-Wiener,Simpson,Evenness and Margalef’s indices,our endemicity and conservation indices clearly differentiates primary forest(our study site)with higher values from secondary forests with much lower values.Thus,we are proposing these indices for a direct but scientifically-informed identification of specific sites for conservation and protection in tropical forests.Additionally,our study documented a total of 168 vascular plant species(79 endemic and 12 locally threatened species)in Mt.Nato-o.Majority are of tropical elements for both generic and species levels with some temperate elements that could be attributed to the site's high elevation and semi-temperate climate.These are important baseline information for conservation plans and monitoring of tropical mossy forests.
文摘Survival data with amulti-state structure are frequently observed in follow-up studies.An analytic approach based on a multi-state model(MSM)should be used in longitudinal health studies in which a patient experiences a sequence of clinical progression events.One main objective in the MSM framework is variable selection,where attempts are made to identify the risk factors associated with the transition hazard rates or probabilities of disease progression.The usual variable selection methods,including stepwise and penalized methods,do not provide information about the importance of variables.In this context,we present a two-step algorithm to evaluate the importance of variables formulti-state data.Three differentmachine learning approaches(randomforest,gradient boosting,and neural network)as themost widely usedmethods are considered to estimate the variable importance in order to identify the factors affecting disease progression and rank these factors according to their importance.The performance of our proposed methods is validated by simulation and applied to the COVID-19 data set.The results revealed that the proposed two-stage method has promising performance for estimating variable importance.
基金supported by the National Natural Science Foundation of China under Grant Nos.52105136,51975028China Postdoctoral Science Foundation under Grant[No.2021M690290]the National Science and TechnologyMajor Project under Grant No.J2019-IV-0002-0069.
文摘The reliability and sensitivity analyses of stator blade regulator usually involve complex characteristics like highnonlinearity,multi-failure regions,and small failure probability,which brings in unacceptable computing efficiency and accuracy of the current analysismethods.In this case,by fitting the implicit limit state function(LSF)with active Kriging(AK)model and reducing candidate sample poolwith adaptive importance sampling(AIS),a novel AK-AIS method is proposed.Herein,theAKmodel andMarkov chainMonte Carlo(MCMC)are first established to identify the most probable failure region(s)(MPFRs),and the adaptive kernel density estimation(AKDE)importance sampling function is constructed to select the candidate samples.With the best samples sequentially attained in the reduced candidate samples and employed to update the Kriging-fitted LSF,the failure probability and sensitivity indices are acquired at a lower cost.The proposed method is verified by twomulti-failure numerical examples,and then applied to the reliability and sensitivity analyses of a typical stator blade regulator.Withmethods comparison,the proposed AK-AIS is proven to hold the computing advantages on accuracy and efficiency in complex reliability and sensitivity analysis problems.
基金the Innovation Training Planning Project for College Students in Anhui Province(AH202112216134)Key Project of Scientific Research Project of Higher Education of Anhui Province(Natural Science)(2022AH051861)+1 种基金Scientific Research Team Project of Anhui Xinhua University(kytd202202)Key Laboratory Project of Building Structure of General Universities in Anhui Province(KLBSZD202105).
文摘Wetlands are widely distributed all over the world,and have many wildlife resources,which are the main pieces of the puzzle for natural resource conservation and sustainable development on earth and have important irreplaceability.In this paper,through questionnaire survey,field research,literature review,etc.,importance weight analysis was conducted by using principal component analysis,and field survey and questionnaire were carried out to collect data on ecological environment function,environmental protection function,landscape beautification function,disaster prevention and mitigation function of urban wetlands.The problems in wetland parks of Nanjing were discussed,such as lack of awareness of landscape planning,deficient late management of wetland parks,weak ability of sustainable development,and unreasonable landscape layout and function.Finally,corresponding solutions were proposed,such as adhering to the planning and design of urban wetland parks with green as the base and health as the basis,persisting in the construction of a wetland system with high biodiversity and near-natural characteristics,adhering to the principle of sustainable development,adopting the construction idea of symbiosis and circulation of urban wetland parks,strengthening education and publicity work,and paying attention to the organic combination of system protection and coordinated construction.The research can build a new development direction for the model of urban wetland parks and green healthy cities,and provide theoretical support for urban sustainable construction.
文摘Attribute reduction is a hot topic in rough set research. As an extension of rough sets, neighborhood rough sets can effectively solve the problem of information loss after data discretization. However, traditional greedy-based neighborhood rough set attribute reduction algorithms have a high computational complexity and long processing time. In this paper, a novel attribute reduction algorithm based on attribute importance is proposed. By using conditional information, the attribute reduction problem in neighborhood rough sets is discussed, and the importance of attributes is measured by conditional information gain. The algorithm iteratively removes the attribute with the lowest importance, thus achieving the goal of attribute reduction. Six groups of UCI datasets are selected, and the proposed algorithm SAR is compared with L<sub>2</sub>-ELM, LapTELM, CTSVM, and TBSVM classifiers. The results demonstrate that SAR can effectively improve the time consumption and accuracy issues in attribute reduction.
文摘As an important part of CNC machine tools,machining center’s reliability,efficiency and accuracy measure the machining level of a CNC machine tool.Therefore,the research on the importance of CNC machine tools is particularly important.However,as a complex mechanical and electrical equipment,the traditional reliability importance analysis method is too simple.In order to solve this problem,this passage proposes to establish the reliability model of each part of the machining center,and then analyze its dynamic importance,which improves the limitation of only reliability importance analysis.Through the analysis the reliability importance and criticality importance,and then rank the result of importance analysis,finally it can get that the ranking results of the key components accord with the fact,so the results can provide support for the importance research of machining center.
文摘In The Importance of Being Earnest,Oscar Wilde constructs a dandies’world,in which the persons mock at everything and subvert everything.This research analyzes the dandyish features of the character with the aid of Charles Baudelaire’s definition of dandy and dandyism,and studies Wilde’s subversion of the preexistent binary oppositions by referring to Jonathan Culler’s interpretation of Jacque Derrida’s deconstruction,and points out that Wilde’s writing in Earnest is a deconstructionist writing.He abandons all the so-called essential matters and only focuses on linguistic surface and comic effect.His stance of dandyism challenges the main-stream social norms at his time and foresees the coming artistic trend.
基金supported by the National Natural Science Foundation of China(71571004)
文摘In a system of systems(SoS),resilience is an important factor in maintaining the functionality,stability,and enhancing the operation effectiveness.From the perspective of resilience,this paper studies the importance of the SoS,and a resilience-based importance measure analysis is conducted to provide suggestions in the design and optimization of the structure of the SoS.In this paper,the components of the SoS are simplified as four kinds of network nodes:sensor,decision point,influencer,and target.In this networked SoS,the number of operation loops is used as the performance indicator,and an approximate algorithm,which is based on eigenvalue of the adjacency matrix,is proposed to calculate the number of operation loops.In order to understand the performance change of the SoS during the attack and defense process in the operations,an integral resilience model is proposed to depict the resilience of the SoS.From different perspectives of enhancing the resilience,different measures,parameters and the corresponding algorithms for the resilience importance of components are proposed.Finally,a case study on an SoS is conducted to verify the validity of the network modelling and the resiliencebased importance analysis method.
文摘Based on the observation of importance sampling and second order information about the fail-ure surface of a structure,an importance sampling region is defined in V-space which is obtained by ro-tating a U-space at the point of maximum likelihood.The sampling region is a hyper-ellipsoid that con-sists of the sampling ellipse on each plane of main curvature in V-space.Thus,the sampling probabilitydensity function can be constructed by the sampling region center and ellipsoid axes.Several exampleshave shown the efficiency and generality of this method.
基金Project(61271296) supported by the National Natural Science Foundation of China
文摘The current measurement was exploited in a more efficient way. Firstly, the system equation was updated by introducing a correction term, which depends on the current measurement and can be obtained by running a suboptimal filter. Then, a new importance density function(IDF) was defined by the updated system equation. Particles drawn from the new IDF are more likely to be in the significant region of state space and the estimation accuracy can be improved. By using different suboptimal filter, different particle filters(PFs) can be developed in this framework. Extensions of this idea were also proposed by iteratively updating the system equation using particle filter itself, resulting in the iterated particle filter. Simulation results demonstrate the effectiveness of the proposed IDF.
文摘Coffea(coffee) species are grown in almost all countries along the Equator. Many members of the genus have a large production history and an important role both in the global market and researches. Seeds(Coffeae semen) are successfully used in food, cosmetic, and pharmaceutical industries due to its caffeine and high polyphenol content. Nowadays, the three best-known coffee species are Arabic(Coffea arabica L.), Robusta(Coffea robusta L. Linden), and Liberian coffees(Coffea liberica Hier.). Even though, many records are available on coffee in scientific literature, wild coffee species like Bengal coffee(Coffea benghalensis Roxb. Ex Schult.) could offer many new opportunities and challenges for phytochemical and medical studies. In this comprehensive summary, we focused on the ethnomedicinal, phytochemical, and medical significance of coffee species up to the present.
基金supported by the National Natural Science Foundation of China(61273210)
文摘Evaluating the node importance correctly is a crucial issue for complex networks research. If a network has multiple or ambiguous morphological features, the evaluation result of an individual index may be unilateral. Meanwhile, the results may be inconsistent if different indexes are adopted simultaneously. To solve the problem, an integrated approach is proposed based on relative entropy. In this approach, a system of multiple indexes is constructed firstly. Then each evaluation result of an individual index is handled into a discrete distribution. Finally an optimal integrated evaluation solution is obtained by linear programming.This approach has a well-formed theoretic basis and an easilycalculated procedure, which can be used in a variety of complex networks. Experimental results show that the proposed approach is more effective than other different methods proposed in some literatures.
文摘BACKGROUND:Ultrasound has the first line investigation role in the diagnosis of acute appendicitis in children.The purpose of this study was to perform a quality assessment review on the visualization rate of appendix on ultrasound in children in the community hospital setting.METHODS:A retrospective chart review of the abdominal ultrasound findings for the visualization of the appendix was performed on paediatric patients ranging from 5 to 18 years.Data were collected from the two community hospitals of Toronto by using hospital electronic medical record for the ultrasound findings in patients presented with abdominal pain.RESULTS:Data from two community hospitals indicated visualization rate of the appendix as 11.0%and 23.2%for site 1 and site 2 respectively.In cases where the ultrasound was repeated the visualization rate remains the same.A two-proportion z-test was performed to find whether the visualization of appendix increases the likelihood of diagnosing appendicitis.The results revealed that the visualization of an appendix(P=0.52),significantly improved the diagnosis of appendicitis(z=34,P<0.001).CONCLUSION:Visualization of an appendix on ultrasound increases the likelihood of correctly diagnosing appendicitis.In our study,we found low visualization rate of appendix on ultrasound that could be the result of many factors that contribute towards the low visualization rate of an appendix on ultrasound.Hence,the challenges in identifying appendix should be minimized to improve the visualization and diagnosis of appendicitis on ultrasound.
基金supported by the National Natural Science Foundation of China(71571190 71601183+1 种基金 L1534031)the Shanxi Province Natural Science Foundation of China(2014JQ2-7045)
文摘In order to achieve the information fusion in the time domain based on the evidence theory, an evidence combination method in the time domain based on reliability and importance is proposed according to the idea of evidence discount. Firstly, the distortion of the time-domain evidence is judged based on single exponential smoothing. The real-time reliability of the evidence at the adjacent time is obtained by the real-time reliability assessment method of the evidence based on the credibility decay model.Then, the relative importance of the evidence at the adjacent time is obtained by comprehensively considering improved conflict degree and uncertainty. Finally, based on the criterion of evidence discount and the Dempster's rule of combination, the evidence combination is carried out to achieve the sequential combination of time-domain evidence. The numerical simulation and analysis show that this method has fully embodied the dynamic characteristics of time-domain evidence combination, and it has strong processing ability for conflict information and anti-disturbing ability.The proposed method has good applicability to information fusion in the time domain.
基金supported by the National Science and Engineering Research Council of Canada(NSERC)Ontario Research Fund–Research Excellence(ORF-RE)+3 种基金the Ministry of Transportation Ontario(MTO)through Its Highway Infrastructure Innovation Funding Program(HIIFP)Beijing Postdoctoral Science Foundation(ZZ-2019-65)Beijing Chaoyang District Postdoctoral Science Foundation(2019ZZ-45)Beijing Municipal Education Commission(KM201811232016)。
文摘Road safety performance function(SPF) analysis using data-driven and nonparametric methods, especially recent developed deep learning approaches, has gained increasing achievements. However, due to the learning mechanisms are hidden in a"black box" in deep learning, traffic features extraction and intelligent importance analysis are still unsolved and hard to generate.This paper focuses on this problem using a deciphered version of deep neural networks(DNN), one of the most popular deep learning models. This approach builds on visualization, feature importance and sensitivity analysis, can evaluate the contributions of input variables on model's "black box" feature learning process and output decision. Firstly, a visual feature importance(Vi FI) method that describes the importance of input features is proposed by adopting diagram and numerical-analysis. Secondly,by observing the change of weights using Vi FI on unsupervised training and fine-tuning of DNN, the final contributions of input features are calculated according to importance equations for both steps that we proposed. Sequentially, a case study based on a road SPF analysis is demonstrated, using data collected from a major Canadian highway, Highway 401. The proposed method allows effective deciphering of the model's inner workings and allows the significant features to be identified and the bad features to be eliminated. Finally, the revised dataset is used in crash modeling and vehicle collision prediction, and the testing result verifies that the deciphered and revised model achieves state-of-theart performance.
基金This research was supported in part by the Chinese National Natural Science Foundation under grant Nos.61602202 and 61702441the Natural Science Foundation of Jiangsu Province under contracts BK20160428 and BK20161302the Six talent peaks project in Jiangsu Province under contract XYDXX-034 and the project in Jiangsu Association for science and technology.
文摘The influence maximization is the problem of finding k seed nodes that maximize the scope of influence in a social network.Therefore,the comprehensive influence of node needs to be considered,when we choose the most influential node set consisted of k seed nodes.On account of the traditional methods used to measure the influence of nodes,such as degree centrality,betweenness centrality and closeness centrality,consider only a single aspect of the influence of node,so the influence measured by traditional methods mentioned above of node is not accurate.In this paper,we obtain the following result through experimental analysis:the influence of a node is relevant not only to its degree and coreness,but also to the degree and coreness of the n-order neighbor nodes.Hence,we propose a algorithm based on the mixed importance of nodes to measure the comprehensive influence of node,and the algorithm we proposed is simple and efficient.In addition,the performance of the algorithm we proposed is better than that of traditional influence maximization algorithms.
文摘Current urban rail transit has become a major mode of transportation, and passenger is an important factor of urban rail transport, so this article is based on passenger and the degree of the road network structure, calculating the point intensity of stations of urban rail transit, and then reaching a station importance by integrating many point intensities in a survey cycle time, and getting the station importance of urban rail transit network through concrete examples.
基金supported by the Research Program through the National Research Foundation of Korea,NRF-2018R1D1A1B07050864.
文摘This study was conducted to enable prompt classification of malware,which was becoming increasingly sophisticated.To do this,we analyzed the important features of malware and the relative importance of selected features according to a learning model to assess how those important features were identified.Initially,the analysis features were extracted using Cuckoo Sandbox,an open-source malware analysis tool,then the features were divided into five categories using the extracted information.The 804 extracted features were reduced by 70%after selecting only the most suitable ones for malware classification using a learning model-based feature selection method called the recursive feature elimination.Next,these important features were analyzed.The level of contribution from each one was assessed by the Random Forest classifier method.The results showed that System call features were mostly allocated.At the end,it was possible to accurately identify the malware type using only 36 to 76 features for each of the four types of malware with the most analysis samples available.These were the Trojan,Adware,Downloader,and Backdoor malware.
文摘This paper presents component importance analysis for virtualized system with live migration. The component importance analysis is significant to determine the system design of virtualized system from availability and cost points of view. This paper discusses the importance of components with respect to system availability. Specifically, we introduce two different component importance analyses for hybrid model (fault trees and continuous-time Markov chains) and continuous-time Markov chains, and show the analysis for existing probabilistic models for virtualized system. In numerical examples, we illustrate the quantitative component importance analysis for virtualized system with live migration.
