Taoren and Xingren are commonly used herbs in East Asian medicine with different medication functions but huge economic differences,and there are cases of adulterated sales in market transactions.An effective adultera...Taoren and Xingren are commonly used herbs in East Asian medicine with different medication functions but huge economic differences,and there are cases of adulterated sales in market transactions.An effective adulteration recognition based on hyperspectral technology and machine learning was designed as a non-destructive testing method in this paper.A hyperspectral dataset comprising 500 Taoren and 500 Xingren samples was established;six feature selection methods were considered in the modeling of radial basis function-support vector machine(RBF-SVM),whose interaction between the two optimization methods was further researched.Two mixed metaheuristics modeling methods,Mixed-PSO and Mixed-SA,were designed,which fused both band selection and hyperparameter optimization from two-stage into one with detailed process analysis.The metrics of this mixed model were improved by comparing with traditional two-stage method.The accuracy of Mixed-PSO was 89.2%in five-floods crossvalidation that increased 4.818%than vanilla RBF-SVM;the accuracy of Mixed-SA was 88.7%which could reach the same as the traditional two-stage method,but it only relied on 48 crux bands in full 100 bands in RBF-SVM model fitting.展开更多
The investigation was carried out on the technical problems of finishing the inner surface of elbow parts and the action mechanism of particles in elbow precision machining by abrasive flow.This work was analyzed and ...The investigation was carried out on the technical problems of finishing the inner surface of elbow parts and the action mechanism of particles in elbow precision machining by abrasive flow.This work was analyzed and researched by combining theory,numerical and experimental methods.The direct simulation Monte Carlo(DSMC)method and the finite element analysis method were combined to reveal the random collision of particles during the precision machining of abrasive flow.Under different inlet velocity,volume fraction and abrasive particle size,the dynamic pressure and turbulence flow energy of abrasive flow in elbow were analyzed,and the machining mechanism of particles on the wall and the influence of different machining parameters on the precision machining quality of abrasive flow were obtained.The test results show the order of the influence of different parameters on the quality of abrasive flow precision machining and establish the optimal process parameters.The results of the surface morphology before and after the precision machining of the inner surface of the elbow are discussed,and the surface roughness Ra value is reduced from 1.125μm to 0.295μm after the precision machining of the abrasive flow.The application of DSMC method provides special insights for the development of abrasive flow technology.展开更多
Applying high-speed machining technology in shop floor has many benefits, such as manufacturing more accurate parts with better surface finishes. The selection of the appropriate machining parameters plays a very impo...Applying high-speed machining technology in shop floor has many benefits, such as manufacturing more accurate parts with better surface finishes. The selection of the appropriate machining parameters plays a very important role in the implementation of high-speed machining technology. The case-based reasoning is used in the developing of high-speed machining database to overcome the shortage of available high-speed cutting parameters in machining data handbooks and shop floors. The high-speed machining database developed in this paper includes two main components: the machining database and the case-base. The machining database stores the cutting parameters, cutting tool data, work pieces and their materials data, and other relative data, while the case-base stores mainly the successfully solved cases that are problems of work pieces and their machining. The case description and case retrieval methods are described to establish the case-based reasoning high-speed machining database. With the case retrieval method, some succeeded cases similar to the new machining problem can be retrieved from the case-base. The solution of the most matched case is evaluated and modified, and then it is regarded as the proposed solution to the new machining problem. After verification, the problem and its solution are packed up into a new case, and are stored in the case-base for future applications.展开更多
In a time characterized by the availability of vast amounts of data,the effective utilization of information is critical for timely decision-making in military operations.However,processing large amounts of data requi...In a time characterized by the availability of vast amounts of data,the effective utilization of information is critical for timely decision-making in military operations.However,processing large amounts of data requires computational resources and time.Therefore,decision makers have used data-centric technologies to take advantage of public and private data sources to support military operations.This survey explores the integration and application of data-centric technologies,such as data analytics,data science,and machine learning,to optimize decision-making workflows within military contexts supporting the deployment of military assets and resources.To address the information gap,this article presents a literature review,specifically a survey.Our survey examines the use of the mentioned technologies to process and analyze information that contributes to the phases of situational awareness,and planning in military environments.We then introduce a taxonomy of the approaches associated with implementing these technologies in military scenarios.Furthermore,we discuss relevant factors for the seamless integration of data-centric technologies into military decision-making processes,and reveal the importance of specialized personnel,architectures,and cybersecurity issues in the task of developing prototypes and models.The findings of this paper aim to provide valuable insights for military institutions,offering a deeper understanding of the use of data-centric technologies as innovative practices to enhance the effectiveness of military decision-making.展开更多
基金Supported by the Natural Science Foundation of Heilongjiang Province(LH2020C003)。
文摘Taoren and Xingren are commonly used herbs in East Asian medicine with different medication functions but huge economic differences,and there are cases of adulterated sales in market transactions.An effective adulteration recognition based on hyperspectral technology and machine learning was designed as a non-destructive testing method in this paper.A hyperspectral dataset comprising 500 Taoren and 500 Xingren samples was established;six feature selection methods were considered in the modeling of radial basis function-support vector machine(RBF-SVM),whose interaction between the two optimization methods was further researched.Two mixed metaheuristics modeling methods,Mixed-PSO and Mixed-SA,were designed,which fused both band selection and hyperparameter optimization from two-stage into one with detailed process analysis.The metrics of this mixed model were improved by comparing with traditional two-stage method.The accuracy of Mixed-PSO was 89.2%in five-floods crossvalidation that increased 4.818%than vanilla RBF-SVM;the accuracy of Mixed-SA was 88.7%which could reach the same as the traditional two-stage method,but it only relied on 48 crux bands in full 100 bands in RBF-SVM model fitting.
基金Projects(51206011,U1937201)supported by the National Natural Science Foundation of ChinaProject(20200301040RQ)supported by the Science and Technology Development Program of Jilin Province,China+1 种基金Project(JJKH20190541KJ)supported by the Education Department of Jilin Province,ChinaProject(18DY017)supported by Changchun Science and Technology Program of Changchun City,China。
文摘The investigation was carried out on the technical problems of finishing the inner surface of elbow parts and the action mechanism of particles in elbow precision machining by abrasive flow.This work was analyzed and researched by combining theory,numerical and experimental methods.The direct simulation Monte Carlo(DSMC)method and the finite element analysis method were combined to reveal the random collision of particles during the precision machining of abrasive flow.Under different inlet velocity,volume fraction and abrasive particle size,the dynamic pressure and turbulence flow energy of abrasive flow in elbow were analyzed,and the machining mechanism of particles on the wall and the influence of different machining parameters on the precision machining quality of abrasive flow were obtained.The test results show the order of the influence of different parameters on the quality of abrasive flow precision machining and establish the optimal process parameters.The results of the surface morphology before and after the precision machining of the inner surface of the elbow are discussed,and the surface roughness Ra value is reduced from 1.125μm to 0.295μm after the precision machining of the abrasive flow.The application of DSMC method provides special insights for the development of abrasive flow technology.
文摘Applying high-speed machining technology in shop floor has many benefits, such as manufacturing more accurate parts with better surface finishes. The selection of the appropriate machining parameters plays a very important role in the implementation of high-speed machining technology. The case-based reasoning is used in the developing of high-speed machining database to overcome the shortage of available high-speed cutting parameters in machining data handbooks and shop floors. The high-speed machining database developed in this paper includes two main components: the machining database and the case-base. The machining database stores the cutting parameters, cutting tool data, work pieces and their materials data, and other relative data, while the case-base stores mainly the successfully solved cases that are problems of work pieces and their machining. The case description and case retrieval methods are described to establish the case-based reasoning high-speed machining database. With the case retrieval method, some succeeded cases similar to the new machining problem can be retrieved from the case-base. The solution of the most matched case is evaluated and modified, and then it is regarded as the proposed solution to the new machining problem. After verification, the problem and its solution are packed up into a new case, and are stored in the case-base for future applications.
文摘In a time characterized by the availability of vast amounts of data,the effective utilization of information is critical for timely decision-making in military operations.However,processing large amounts of data requires computational resources and time.Therefore,decision makers have used data-centric technologies to take advantage of public and private data sources to support military operations.This survey explores the integration and application of data-centric technologies,such as data analytics,data science,and machine learning,to optimize decision-making workflows within military contexts supporting the deployment of military assets and resources.To address the information gap,this article presents a literature review,specifically a survey.Our survey examines the use of the mentioned technologies to process and analyze information that contributes to the phases of situational awareness,and planning in military environments.We then introduce a taxonomy of the approaches associated with implementing these technologies in military scenarios.Furthermore,we discuss relevant factors for the seamless integration of data-centric technologies into military decision-making processes,and reveal the importance of specialized personnel,architectures,and cybersecurity issues in the task of developing prototypes and models.The findings of this paper aim to provide valuable insights for military institutions,offering a deeper understanding of the use of data-centric technologies as innovative practices to enhance the effectiveness of military decision-making.
