Activity based costing (ABC) is a method which can solve many limitations of the traditional cost systems in manufacturing management. In this paper, we investigate how to integrate ABC with workflow technology, and ...Activity based costing (ABC) is a method which can solve many limitations of the traditional cost systems in manufacturing management. In this paper, we investigate how to integrate ABC with workflow technology, and build a workflow meta model supporting ABC. Firstly, the concept and concept model of activity based costing (ABC) are introduced. Next, the meta model of P -PROCE (Process, Product, Resource, Organization, and Cost & Evaluation) is presented. Then the cost meta model is defined by adding ABC to P -PROCE model. Object constraint language (OCL) is used to express meta model and constraints. Finally, we show an enterprise modeling and simulation tool based on the workflow meta model. We can systematically construct an enterprise model and easily and efficiently conduct simulation. Moreover it enables us to analyze and evaluate business processes and its costs.展开更多
目的:运用网状Meta分析评估不同免疫吸附柱治疗类风湿关节炎的有效性与安全性,为临床诊治提供循证依据。方法:计算机检索维普、万方、中国知网、PubMed、CBM、CochraneLibrary、Web of Science等数据库,检索公开发表的免疫吸附柱治疗类...目的:运用网状Meta分析评估不同免疫吸附柱治疗类风湿关节炎的有效性与安全性,为临床诊治提供循证依据。方法:计算机检索维普、万方、中国知网、PubMed、CBM、CochraneLibrary、Web of Science等数据库,检索公开发表的免疫吸附柱治疗类风湿关节炎的研究,检索时限至2024年8月。采用Cochrane 5.4手册对纳入的随机对照试验进行质量评价,采用纽卡斯尔-渥太华量表(NOS)对回顾性队列研究进行质量评价。运用R4.1.1软件进行贝叶斯网状Meta分析。结果:最终纳入13篇研究,总样本量891例,共有4种免疫吸附柱。网状Meta分析结果表明,降低C-反应蛋白前3名排序:HA280型吸附柱+常规西药>PH-350型吸附柱+常规西药>A蛋白吸附柱;降低红细胞沉降率前3名排序:白细胞吸附柱>HA280型吸附柱+常规西药>PH-350型吸附柱+常规西药;降低关节肿胀计数前3名排序:白细胞吸附柱>A蛋白吸附柱+常规西药>PH-350型吸附柱+常规西药;降低关节压痛计数前3名排序:白细胞吸附柱>A蛋白吸附柱+常规西药>PH-350型吸附柱+常规西药;降低患者对疾病活动性评分前3名排序:PH-350型吸附柱+常规西药>白细胞吸附柱>A蛋白吸附柱;降低目测类比评分前3名排序:PH-350型吸附柱+常规西药>A蛋白吸附柱>白细胞吸附柱;降低医师对疾病活动性评分前3名排序:PH-350型吸附柱+常规西药>白细胞吸附柱>常规西药。结论:基于纳入的13篇文献证据表明,在降低C-反应蛋白方面,HA280型吸附柱联合常规西药作为首选;在降低红细胞沉降率、关节肿胀计数、关节压痛计数方面,白细胞吸附柱作为首选;在降低患者对疾病活动性评分、医师对疾病活动性评分及目测类比评分方面,PH-350型吸附柱联合常规西药作为首选,在临床中可根据患者的具体情况合理选择不同的免疫吸附柱。展开更多
Engineering data are separately organized and their schemas are increasingly complex and variable. Engineering data management systems are needed to be able to manage the unified data and to be both customizable and e...Engineering data are separately organized and their schemas are increasingly complex and variable. Engineering data management systems are needed to be able to manage the unified data and to be both customizable and extensible. The design of the systems is heavily dependent on the flexibility and self-description of the data model. The characteristics of engineering data and their management facts are analyzed. Then engineering data warehouse (EDW) architecture and multi-layer metamodels are presented. Also an approach to manage anduse engineering data by a meta object is proposed. Finally, an application flight test EDW system (FTEDWS) is described and meta-objects to manage engineering data in the data warehouse are used. It shows that adopting a meta-modeling approach provides a support for interchangeability and a sufficiently flexible environment in which the system evolution and the reusability can be handled.展开更多
Parameter identification, model calibration, and uncertainty quantification are important steps in the model-building process, and are necessary for obtaining credible results and valuable information. Sensitivity ana...Parameter identification, model calibration, and uncertainty quantification are important steps in the model-building process, and are necessary for obtaining credible results and valuable information. Sensitivity analysis of hydrological model is a key step in model uncertainty quantification, which can identify the dominant parameters, reduce the model calibration uncertainty, and enhance the model optimization efficiency. There are, however, some shortcomings in classical approaches, including the long duration of time and high computation cost required to quantitatively assess the sensitivity of a multiple-parameter hydrological model. For this reason, a two-step statistical evaluation framework using global techniques is presented. It is based on （1） a screening method （Morris） for qualitative ranking of parameters, and （2） a variance-based method integrated with a meta-model for quantitative sensitivity analysis, i.e., the Sobol method integrated with the response surface model （RSMSobol）. First, the Morris screening method was used to qualitatively identify the parameters＇ sensitivity, and then ten parameters were selected to quantify the sensitivity indices. Subsequently, the RSMSobol method was used to quantify the sensitivity, i.e., the first-order and total sensitivity indices based on the response surface model （RSM） were calculated. The RSMSobol method can not only quantify the sensitivity, but also reduce the computational cost, with good accuracy compared to the classical approaches. This approach will be effective and reliable in the global sensitivity analysis of a complex large-scale distributed hydrological model.展开更多
Architecture framework has become an effective method recently to describe the system of systems(SoS)architecture,such as the United States(US)Department of Defense Architecture Framework Version 2.0(DoDAF2.0).As a vi...Architecture framework has become an effective method recently to describe the system of systems(SoS)architecture,such as the United States(US)Department of Defense Architecture Framework Version 2.0(DoDAF2.0).As a viewpoint in DoDAF2.0,the operational viewpoint(OV)describes operational activities,nodes,and resource flows.The OV models are important for SoS architecture development.However,as the SoS complexity increases,constructing OV models with traditional methods exposes shortcomings,such as inefficient data collection and low modeling standards.Therefore,we propose an intelligent modeling method for five OV models,including operational resource flow OV-2,organizational relationships OV-4,operational activity hierarchy OV-5a,operational activities model OV-5b,and operational activity sequences OV-6c.The main idea of the method is to extract OV architecture data from text and generate interoperable OV models.First,we construct the OV meta model based on the DoDAF2.0 meta model(DM2).Second,OV architecture named entities is recognized from text based on the bidirectional long short-term memory and conditional random field(BiLSTM-CRF)model.And OV architecture relationships are collected with relationship extraction rules.Finally,we define the generation rules for OV models and develop an OV modeling tool.We use unmanned surface vehicles(USV)swarm target defense SoS architecture as a case to verify the feasibility and effectiveness of the intelligent modeling method.展开更多
Conventional trajectory optimization techniques have been challenged by their inability to handle threats with irregular shapes and the tendency to be sensitive to control variations of aircraft. Aiming to overcome th...Conventional trajectory optimization techniques have been challenged by their inability to handle threats with irregular shapes and the tendency to be sensitive to control variations of aircraft. Aiming to overcome these difficulties, this paper presents an alternative approach for trajectory optimization, where the problem is formulated into a parametric optimization of the maneuver variables under a tactics template framework. To reduce the size of the problem, global sensitivity analysis （GSA） is performed to identify the less-influential maneuver variables. The probability collectives （PC） algorithm, which is well-suited to discrete and discontinuous optimization, is applied to solve the trajectory optimization problem. The robustness of the trajectory is assessed through multiple sampling around the chosen values of the maneuver variables. Meta-models based on radius basis function （RBF） are created for evaluations of the means and deviations of the problem objectives and constraints. To guarantee the approximation accuracy, the meta-models are adaptively updated during optimization. The proposed approach is demonstrated on a typical airground attack mission scenario. Results reveal that the proposed approach is capable of generating robust and optimal trajectories with both accuracy and efficiency.展开更多
To investigate the application of meta-model for finite element( FE) model updating of structures,the performance of two popular meta-model,i. e.,Kriging model and response surface model( RSM),were compared in detail....To investigate the application of meta-model for finite element( FE) model updating of structures,the performance of two popular meta-model,i. e.,Kriging model and response surface model( RSM),were compared in detail. Firstly,above two kinds of meta-model were introduced briefly. Secondly,some key issues of the application of meta-model to FE model updating of structures were proposed and discussed,and then some advices were presented in order to select a reasonable meta-model for the purpose of updating the FE model of structures. Finally,the procedure of FE model updating based on meta-model was implemented by updating the FE model of a truss bridge model with the measured modal parameters. The results showed that the Kriging model was more proper for FE model updating of complex structures.展开更多
In this study, a new method for conversion of solid finite element solution to beam finite element solution is developed based on the meta-modeling theory which constructs a model consistent with continuum mechanics. ...In this study, a new method for conversion of solid finite element solution to beam finite element solution is developed based on the meta-modeling theory which constructs a model consistent with continuum mechanics. The proposed method is rigorous and efficient compared to a typical conversion method which merely computes surface integration of solid element nodal stresses to obtain cross-sectional forces. The meta-modeling theory ensures the rigorousness of proposed method by defining a proper distance between beam element and solid element solutions in a function space of continuum mechanics. Results of numerical verification test that is conducted with a simple cantilever beam are used to find the proper distance function for this conversion. Time history analysis of the main tunnel structure of a real ramp tunnel is considered as a numerical example for the proposed conversion method. It is shown that cross-sectional forces are readily computed for solid element solution of the main tunnel structure when it is converted to a beam element solution using the proposed method. Further, envelopes of resultant forces which are of primary importance for the purpose of design, are developed for a given ground motion at the end.展开更多
Domain-specific metamodeling language(DSMML) defined by informal method cannot strictly represent its structural semantics,so its properties such as consistency cannot be holistically and systematically verified.In re...Domain-specific metamodeling language(DSMML) defined by informal method cannot strictly represent its structural semantics,so its properties such as consistency cannot be holistically and systematically verified.In response,the paper proposes a formal representation of the structural semantics of DSMML named extensible markup language(XML) based metamodeling language(XMML) and its metamodels consistency verification method.Firstly,we describe our approach of formalization,based on this,the method of consistency verification of XMML and its metamodels based on first-order logical inference is presented;then,the formalization automatic mapping engine for metamodels is designed to show the feasibility of our formal method.展开更多
Wheat is a critical crop,extensively consumed worldwide,and its production enhancement is essential to meet escalating demand.The presence of diseases like stem rust,leaf rust,yellow rust,and tan spot significantly di...Wheat is a critical crop,extensively consumed worldwide,and its production enhancement is essential to meet escalating demand.The presence of diseases like stem rust,leaf rust,yellow rust,and tan spot significantly diminishes wheat yield,making the early and precise identification of these diseases vital for effective disease management.With advancements in deep learning algorithms,researchers have proposed many methods for the automated detection of disease pathogens;however,accurately detectingmultiple disease pathogens simultaneously remains a challenge.This challenge arises due to the scarcity of RGB images for multiple diseases,class imbalance in existing public datasets,and the difficulty in extracting features that discriminate between multiple classes of disease pathogens.In this research,a novel method is proposed based on Transfer Generative Adversarial Networks for augmenting existing data,thereby overcoming the problems of class imbalance and data scarcity.This study proposes a customized architecture of Vision Transformers(ViT),where the feature vector is obtained by concatenating features extracted from the custom ViT and Graph Neural Networks.This paper also proposes a Model AgnosticMeta Learning(MAML)based ensemble classifier for accurate classification.The proposedmodel,validated on public datasets for wheat disease pathogen classification,achieved a test accuracy of 99.20%and an F1-score of 97.95%.Compared with existing state-of-the-art methods,this proposed model outperforms in terms of accuracy,F1-score,and the number of disease pathogens detection.In future,more diseases can be included for detection along with some other modalities like pests and weed.展开更多
In this work,a hybrid meta-model based design space differentiation（HMDSD）method is proposed for practical problems.In the proposed method,an iteratively reduced promising region is constructed using the expensive p...In this work,a hybrid meta-model based design space differentiation（HMDSD）method is proposed for practical problems.In the proposed method,an iteratively reduced promising region is constructed using the expensive points,with two different search strategies respectively applied inside and outside the promising region.Besides,the hybrid meta-model strategy applied in the search process makes it possible to solve the complex practical problems.Tested upon a serial of benchmark math functions,the HMDSD method shows great efficiency and search accuracy.On top of that,a practical lightweight design demonstrates its superior performance.展开更多
目的系统评价食管癌患者术后吻合口瘘(anastomotic leakage,AL)风险预测模型,为建立和改进模型提供指导。方法计算机检索PubMed、Cochrane Library、EMbase、Web of Science、中华医学期刊全文数据库、维普网、万方、中国生物医学文献...目的系统评价食管癌患者术后吻合口瘘(anastomotic leakage,AL)风险预测模型,为建立和改进模型提供指导。方法计算机检索PubMed、Cochrane Library、EMbase、Web of Science、中华医学期刊全文数据库、维普网、万方、中国生物医学文献数据库以及中国知网发表的关于食管癌术后AL风险预测模型的研究,检索时间为建库至2023年10月1日。采用PROBAST工具评估预测模型研究的质量,采用Stata 15软件对建立模型的预测变量进行Meta分析。结果纳入19篇文献,共构建25个食管癌患者术后AL风险预测模型,7373例患者,受试者工作特征曲线下面积(area under the curve,AUC)为0.670~0.960,其中23个预测模型的预测性能较好(AUC>0.7)。13篇文献进行了模型校准,10篇文献进行内部验证,1篇文献进行外部验证。PROBAST评价结果表明19篇文献均为高偏倚风险。最常见的预测因子包括:低蛋白血症(OR=9.362)、术后呼吸系统并发症(OR=7.427)、切口愈合不良(OR=5.330)、吻合方法(OR=2.965)、术前胸腹部手术史(OR=3.181)、术前合并糖尿病(OR=2.445)、术前合并心血管系统疾病(OR=3.260)、术前新辅助治疗(OR=2.977)、术前呼吸系统疾病(OR=4.744)、手术方式(OR=4.312)、美国麻醉医师协会评分(OR=2.424)等。结论目前食管癌术后AL风险预测模型仍处于研发阶段,总体研究质量有待进一步提升。展开更多
Neural networks are being used to construct meta-models in numerical simulation of structures.In addition to network structures and training algorithms,training samples also greatly affect the accuracy of neural netwo...Neural networks are being used to construct meta-models in numerical simulation of structures.In addition to network structures and training algorithms,training samples also greatly affect the accuracy of neural network models.In this paper,some existing main sampling techniques are evaluated,including techniques based on experimental design theory, random selection,and rotating sampling.First,advantages and disadvantages of each technique are reviewed.Then,seven techniques are used to generate samples for training radial neural networks models for two benchmarks:an antenna model and an aircraft model.Results show that the uniform design,in which the number of samples and mean square error network models are considered,is the best sampling technique for neural network based meta-model building.展开更多
文摘Activity based costing (ABC) is a method which can solve many limitations of the traditional cost systems in manufacturing management. In this paper, we investigate how to integrate ABC with workflow technology, and build a workflow meta model supporting ABC. Firstly, the concept and concept model of activity based costing (ABC) are introduced. Next, the meta model of P -PROCE (Process, Product, Resource, Organization, and Cost & Evaluation) is presented. Then the cost meta model is defined by adding ABC to P -PROCE model. Object constraint language (OCL) is used to express meta model and constraints. Finally, we show an enterprise modeling and simulation tool based on the workflow meta model. We can systematically construct an enterprise model and easily and efficiently conduct simulation. Moreover it enables us to analyze and evaluate business processes and its costs.
文摘目的:运用网状Meta分析评估不同免疫吸附柱治疗类风湿关节炎的有效性与安全性,为临床诊治提供循证依据。方法:计算机检索维普、万方、中国知网、PubMed、CBM、CochraneLibrary、Web of Science等数据库,检索公开发表的免疫吸附柱治疗类风湿关节炎的研究,检索时限至2024年8月。采用Cochrane 5.4手册对纳入的随机对照试验进行质量评价,采用纽卡斯尔-渥太华量表(NOS)对回顾性队列研究进行质量评价。运用R4.1.1软件进行贝叶斯网状Meta分析。结果:最终纳入13篇研究,总样本量891例,共有4种免疫吸附柱。网状Meta分析结果表明,降低C-反应蛋白前3名排序:HA280型吸附柱+常规西药>PH-350型吸附柱+常规西药>A蛋白吸附柱;降低红细胞沉降率前3名排序:白细胞吸附柱>HA280型吸附柱+常规西药>PH-350型吸附柱+常规西药;降低关节肿胀计数前3名排序:白细胞吸附柱>A蛋白吸附柱+常规西药>PH-350型吸附柱+常规西药;降低关节压痛计数前3名排序:白细胞吸附柱>A蛋白吸附柱+常规西药>PH-350型吸附柱+常规西药;降低患者对疾病活动性评分前3名排序:PH-350型吸附柱+常规西药>白细胞吸附柱>A蛋白吸附柱;降低目测类比评分前3名排序:PH-350型吸附柱+常规西药>A蛋白吸附柱>白细胞吸附柱;降低医师对疾病活动性评分前3名排序:PH-350型吸附柱+常规西药>白细胞吸附柱>常规西药。结论:基于纳入的13篇文献证据表明,在降低C-反应蛋白方面,HA280型吸附柱联合常规西药作为首选;在降低红细胞沉降率、关节肿胀计数、关节压痛计数方面,白细胞吸附柱作为首选;在降低患者对疾病活动性评分、医师对疾病活动性评分及目测类比评分方面,PH-350型吸附柱联合常规西药作为首选,在临床中可根据患者的具体情况合理选择不同的免疫吸附柱。
文摘Engineering data are separately organized and their schemas are increasingly complex and variable. Engineering data management systems are needed to be able to manage the unified data and to be both customizable and extensible. The design of the systems is heavily dependent on the flexibility and self-description of the data model. The characteristics of engineering data and their management facts are analyzed. Then engineering data warehouse (EDW) architecture and multi-layer metamodels are presented. Also an approach to manage anduse engineering data by a meta object is proposed. Finally, an application flight test EDW system (FTEDWS) is described and meta-objects to manage engineering data in the data warehouse are used. It shows that adopting a meta-modeling approach provides a support for interchangeability and a sufficiently flexible environment in which the system evolution and the reusability can be handled.
基金supported by the National Natural Science Foundation of China (Grant No. 41271003)the National Basic Research Program of China (Grants No. 2010CB428403 and 2010CB951103)
文摘Parameter identification, model calibration, and uncertainty quantification are important steps in the model-building process, and are necessary for obtaining credible results and valuable information. Sensitivity analysis of hydrological model is a key step in model uncertainty quantification, which can identify the dominant parameters, reduce the model calibration uncertainty, and enhance the model optimization efficiency. There are, however, some shortcomings in classical approaches, including the long duration of time and high computation cost required to quantitatively assess the sensitivity of a multiple-parameter hydrological model. For this reason, a two-step statistical evaluation framework using global techniques is presented. It is based on （1） a screening method （Morris） for qualitative ranking of parameters, and （2） a variance-based method integrated with a meta-model for quantitative sensitivity analysis, i.e., the Sobol method integrated with the response surface model （RSMSobol）. First, the Morris screening method was used to qualitatively identify the parameters＇ sensitivity, and then ten parameters were selected to quantify the sensitivity indices. Subsequently, the RSMSobol method was used to quantify the sensitivity, i.e., the first-order and total sensitivity indices based on the response surface model （RSM） were calculated. The RSMSobol method can not only quantify the sensitivity, but also reduce the computational cost, with good accuracy compared to the classical approaches. This approach will be effective and reliable in the global sensitivity analysis of a complex large-scale distributed hydrological model.
基金National Natural Science Foundation of China(71690233,71971213,71901214)。
文摘Architecture framework has become an effective method recently to describe the system of systems(SoS)architecture,such as the United States(US)Department of Defense Architecture Framework Version 2.0(DoDAF2.0).As a viewpoint in DoDAF2.0,the operational viewpoint(OV)describes operational activities,nodes,and resource flows.The OV models are important for SoS architecture development.However,as the SoS complexity increases,constructing OV models with traditional methods exposes shortcomings,such as inefficient data collection and low modeling standards.Therefore,we propose an intelligent modeling method for five OV models,including operational resource flow OV-2,organizational relationships OV-4,operational activity hierarchy OV-5a,operational activities model OV-5b,and operational activity sequences OV-6c.The main idea of the method is to extract OV architecture data from text and generate interoperable OV models.First,we construct the OV meta model based on the DoDAF2.0 meta model(DM2).Second,OV architecture named entities is recognized from text based on the bidirectional long short-term memory and conditional random field(BiLSTM-CRF)model.And OV architecture relationships are collected with relationship extraction rules.Finally,we define the generation rules for OV models and develop an OV modeling tool.We use unmanned surface vehicles(USV)swarm target defense SoS architecture as a case to verify the feasibility and effectiveness of the intelligent modeling method.
基金supported by Open Research Foundation of Science and Technology on Aerospace Flight Dynamics Laboratory (No. 2012afd1010)
文摘Conventional trajectory optimization techniques have been challenged by their inability to handle threats with irregular shapes and the tendency to be sensitive to control variations of aircraft. Aiming to overcome these difficulties, this paper presents an alternative approach for trajectory optimization, where the problem is formulated into a parametric optimization of the maneuver variables under a tactics template framework. To reduce the size of the problem, global sensitivity analysis （GSA） is performed to identify the less-influential maneuver variables. The probability collectives （PC） algorithm, which is well-suited to discrete and discontinuous optimization, is applied to solve the trajectory optimization problem. The robustness of the trajectory is assessed through multiple sampling around the chosen values of the maneuver variables. Meta-models based on radius basis function （RBF） are created for evaluations of the means and deviations of the problem objectives and constraints. To guarantee the approximation accuracy, the meta-models are adaptively updated during optimization. The proposed approach is demonstrated on a typical airground attack mission scenario. Results reveal that the proposed approach is capable of generating robust and optimal trajectories with both accuracy and efficiency.
基金Sponsored by the National Key Technology Research and Development Program of China(Grant No.2011BAK02B02)
文摘To investigate the application of meta-model for finite element( FE) model updating of structures,the performance of two popular meta-model,i. e.,Kriging model and response surface model( RSM),were compared in detail. Firstly,above two kinds of meta-model were introduced briefly. Secondly,some key issues of the application of meta-model to FE model updating of structures were proposed and discussed,and then some advices were presented in order to select a reasonable meta-model for the purpose of updating the FE model of structures. Finally,the procedure of FE model updating based on meta-model was implemented by updating the FE model of a truss bridge model with the measured modal parameters. The results showed that the Kriging model was more proper for FE model updating of complex structures.
文摘In this study, a new method for conversion of solid finite element solution to beam finite element solution is developed based on the meta-modeling theory which constructs a model consistent with continuum mechanics. The proposed method is rigorous and efficient compared to a typical conversion method which merely computes surface integration of solid element nodal stresses to obtain cross-sectional forces. The meta-modeling theory ensures the rigorousness of proposed method by defining a proper distance between beam element and solid element solutions in a function space of continuum mechanics. Results of numerical verification test that is conducted with a simple cantilever beam are used to find the proper distance function for this conversion. Time history analysis of the main tunnel structure of a real ramp tunnel is considered as a numerical example for the proposed conversion method. It is shown that cross-sectional forces are readily computed for solid element solution of the main tunnel structure when it is converted to a beam element solution using the proposed method. Further, envelopes of resultant forces which are of primary importance for the purpose of design, are developed for a given ground motion at the end.
基金the Yunnan Provincial Department of Education Research Fund Key Project(No.2011z025)General Project(No.2011y214)
文摘Domain-specific metamodeling language(DSMML) defined by informal method cannot strictly represent its structural semantics,so its properties such as consistency cannot be holistically and systematically verified.In response,the paper proposes a formal representation of the structural semantics of DSMML named extensible markup language(XML) based metamodeling language(XMML) and its metamodels consistency verification method.Firstly,we describe our approach of formalization,based on this,the method of consistency verification of XMML and its metamodels based on first-order logical inference is presented;then,the formalization automatic mapping engine for metamodels is designed to show the feasibility of our formal method.
基金Researchers Supporting Project Number(RSPD2024R 553),King Saud University,Riyadh,Saudi Arabia.
文摘Wheat is a critical crop,extensively consumed worldwide,and its production enhancement is essential to meet escalating demand.The presence of diseases like stem rust,leaf rust,yellow rust,and tan spot significantly diminishes wheat yield,making the early and precise identification of these diseases vital for effective disease management.With advancements in deep learning algorithms,researchers have proposed many methods for the automated detection of disease pathogens;however,accurately detectingmultiple disease pathogens simultaneously remains a challenge.This challenge arises due to the scarcity of RGB images for multiple diseases,class imbalance in existing public datasets,and the difficulty in extracting features that discriminate between multiple classes of disease pathogens.In this research,a novel method is proposed based on Transfer Generative Adversarial Networks for augmenting existing data,thereby overcoming the problems of class imbalance and data scarcity.This study proposes a customized architecture of Vision Transformers(ViT),where the feature vector is obtained by concatenating features extracted from the custom ViT and Graph Neural Networks.This paper also proposes a Model AgnosticMeta Learning(MAML)based ensemble classifier for accurate classification.The proposedmodel,validated on public datasets for wheat disease pathogen classification,achieved a test accuracy of 99.20%and an F1-score of 97.95%.Compared with existing state-of-the-art methods,this proposed model outperforms in terms of accuracy,F1-score,and the number of disease pathogens detection.In future,more diseases can be included for detection along with some other modalities like pests and weed.
基金Project supported by the Plan for the growth of young teachers,the National Natural Science Foundation of China(No.51505138)the National 973 Program of China(No.2010CB328005)+1 种基金Outstanding Youth Foundation of NSFC(No.50625519)Program for Changjiang Scholars
文摘In this work,a hybrid meta-model based design space differentiation（HMDSD）method is proposed for practical problems.In the proposed method,an iteratively reduced promising region is constructed using the expensive points,with two different search strategies respectively applied inside and outside the promising region.Besides,the hybrid meta-model strategy applied in the search process makes it possible to solve the complex practical problems.Tested upon a serial of benchmark math functions,the HMDSD method shows great efficiency and search accuracy.On top of that,a practical lightweight design demonstrates its superior performance.
文摘目的系统评价食管癌患者术后吻合口瘘(anastomotic leakage,AL)风险预测模型,为建立和改进模型提供指导。方法计算机检索PubMed、Cochrane Library、EMbase、Web of Science、中华医学期刊全文数据库、维普网、万方、中国生物医学文献数据库以及中国知网发表的关于食管癌术后AL风险预测模型的研究,检索时间为建库至2023年10月1日。采用PROBAST工具评估预测模型研究的质量,采用Stata 15软件对建立模型的预测变量进行Meta分析。结果纳入19篇文献,共构建25个食管癌患者术后AL风险预测模型,7373例患者,受试者工作特征曲线下面积(area under the curve,AUC)为0.670~0.960,其中23个预测模型的预测性能较好(AUC>0.7)。13篇文献进行了模型校准,10篇文献进行内部验证,1篇文献进行外部验证。PROBAST评价结果表明19篇文献均为高偏倚风险。最常见的预测因子包括:低蛋白血症(OR=9.362)、术后呼吸系统并发症(OR=7.427)、切口愈合不良(OR=5.330)、吻合方法(OR=2.965)、术前胸腹部手术史(OR=3.181)、术前合并糖尿病(OR=2.445)、术前合并心血管系统疾病(OR=3.260)、术前新辅助治疗(OR=2.977)、术前呼吸系统疾病(OR=4.744)、手术方式(OR=4.312)、美国麻醉医师协会评分(OR=2.424)等。结论目前食管癌术后AL风险预测模型仍处于研发阶段,总体研究质量有待进一步提升。
基金Specialized Research Fund for the Doctoral Program of Higher Education,China (No.20010227012)
文摘Neural networks are being used to construct meta-models in numerical simulation of structures.In addition to network structures and training algorithms,training samples also greatly affect the accuracy of neural network models.In this paper,some existing main sampling techniques are evaluated,including techniques based on experimental design theory, random selection,and rotating sampling.First,advantages and disadvantages of each technique are reviewed.Then,seven techniques are used to generate samples for training radial neural networks models for two benchmarks:an antenna model and an aircraft model.Results show that the uniform design,in which the number of samples and mean square error network models are considered,is the best sampling technique for neural network based meta-model building.
