This paper extends the previously developed method of optimizing Road Weather Information Systems(RWIS)station placement by unveiling a sophisticated multi-variable semivariogram model that concurrently considers mult...This paper extends the previously developed method of optimizing Road Weather Information Systems(RWIS)station placement by unveiling a sophisticated multi-variable semivariogram model that concurrently considers multiple vital road weather variables.Previous research primarily centered on single-variable analysis focusing on road surface temperature(RST).The study bridges this oversight by introducing a framework that integrates multiple critical weather variables into the RWIS location allocation framework.This novel approach ensures balanced and equitable RWIS distribution across zones and aligns the network with areas both prone to traffic accidents and areas of high uncertainty.To demonstrate the effectiveness of this refinement,the authors applied the framework to Maine’s existing RWIS network,conducted a gap analysis through varying planning scenarios and generated optimal solutions using a heuristic optimization algorithm.The analysis identified areas that would benefit most from additional RWIS stations and guided optimal resource utilization across different road types and priority locations.A sensitivity analysis was also performed to evaluate the effect of different weightings for weather and traffic factors on the selection of optimal locations.The location solutions generated have been adopted by MaineDOT for future implementations,attesting to the model’s practicality and signifying an important advancement for more effective management of road weather conditions.展开更多
The construction method of background value is improved in the original multi-variable grey model (MGM(1,m)) from its source of construction errors. The MGM(1,m) with optimized background value is used to elimin...The construction method of background value is improved in the original multi-variable grey model (MGM(1,m)) from its source of construction errors. The MGM(1,m) with optimized background value is used to eliminate the random fluctuations or errors of the observational data of all variables, and the combined prediction model together with the multiple linear regression is established in order to improve the simulation and prediction accuracy of the combined model. Finally, a combined model of the MGM(1,2) with optimized background value and the binary linear regression is constructed by an example. The results show that the model has good effects for simulation and prediction.展开更多
A novel flocking control approach is proposed for multi-agent systems by integrating the variables of velocities, motion directions, and positions of agents. A received signal strength indicator (RSSI) is applied as...A novel flocking control approach is proposed for multi-agent systems by integrating the variables of velocities, motion directions, and positions of agents. A received signal strength indicator (RSSI) is applied as a variable to estimate the inter-distance between agents. A key parameter that contains the local information of agents is defined, and a multi-variable controller is proposed based on the parameter. For the position control of agents, the RSSI is introduced to substitute the distance as a control variable in the systems. The advantages of RSSI include that the relative distance between every two agents can be adjusted through the communication quality under different environments, and it can shun the shortage of the limit of sensors. Simulation studies demonstrate the effectiveness of the proposed control approach.展开更多
The modern industrial control objects become more and more complicated,and higher control quality is required, so a series of new control strategies appear,applied,modified and develop quickly.This paper researches a ...The modern industrial control objects become more and more complicated,and higher control quality is required, so a series of new control strategies appear,applied,modified and develop quickly.This paper researches a new control strategy- prediction control-and its application in Multi-Variable Control Process.The research result is worthy for automatic control in pro- cess industry.展开更多
It is well known that Landsat TM images are the most widely used remote sensing data in various fields.Usually,it has 7 different electromagnetic spectrum bands,among which the sixth one has much lower ground resoluti...It is well known that Landsat TM images are the most widely used remote sensing data in various fields.Usually,it has 7 different electromagnetic spectrum bands,among which the sixth one has much lower ground resolution compared with the other six bands.Nevertheless,it is useful in the study of rock spectrum reflection,geothermal resources exploration,etc.To improve the ground resolution of TM6 to the level as that of the other six bands is a problem .This paper presents an algorithm based on the combination of multivariate regression model with semivariogram function which can improve the ground resolution of TM6 by "fusing" the data of other six bands.It includes the following main steps: (1) testing the correlation between TM6 and one of TM15,7.If the correlation coefficient between TM6 and another one is greater than a given threshold value,then select the band to the regression analysis as an argument.(2) calculating the size of the template window within which some parameters needed by the regression model will be calculated; (3) replacing the original pixel values of TM6 by those obtained by regression analysis; (4) using image entropy as a measurement to evaluate the quality of the fused image of TM6.The basic mechanism of the algorithm is discussed and the V C ++ program for implementing this algorithm is also presented.A simple application example is given in the last part of this paper,showing the effectiveness of the algorithm.展开更多
By modeling direct transient heat conduction problems via finite element method (FEM) and precise integral algorithm, a new approach is presented to solve transient inverse heat conduction problems with multi-variable...By modeling direct transient heat conduction problems via finite element method (FEM) and precise integral algorithm, a new approach is presented to solve transient inverse heat conduction problems with multi-variables. Firstly, the spatial space and temporal domain are discretized by FEM and precise integral algorithm respectively. Then, the high accuracy semi-analytical solution of direct problem can be got. Finally, based on the solution, the computing model of inverse problem and expression of sensitivity analysis are established. Single variable and variables combined identifications including thermal parameters, boundary conditions and source-related terms etc. are given to validate the approach proposed in 1-D and 2-D cases. The effects of noise data and initial guess on the results are investigated. The numerical examples show the effectiveness of this approach.展开更多
As an active defenses technique,multivariant execution(MVX)can detect attacks by monitoring the consistency of heterogeneous variants with parallel execution.Compared with patch-style passive defense,MVX can defend ag...As an active defenses technique,multivariant execution(MVX)can detect attacks by monitoring the consistency of heterogeneous variants with parallel execution.Compared with patch-style passive defense,MVX can defend against known and even unknown vulnerability-based attacks without relying on attack feature information.However,variants generated with software diversity technologies will introduce new vulnerabilities when they execute in parallel.First,we analyze the security of MVX theory from the perspective of formal description.Then we summarize the general forms and techniques for attacks against MVX,and analyze the new vulnerabilities arising from the combination of variant generation technologies.We propose SecMVX,a secure MVX architecture and variant generation technology.Experimental evaluations based on CVEs and SPEC 2006 benchmark show that SecMVX introduces 11.29%of the average time overhead,and avoids vulnerabilities caused by the improper combination of variant generation technologies while keeping the defensive ability of MVX.展开更多
The immense quest for proficient numerical schemes for the solution of mathematical models featuring nonlinear differential equations led to the realization of the Adomian decomposition method (ADM) in the 80<sup&g...The immense quest for proficient numerical schemes for the solution of mathematical models featuring nonlinear differential equations led to the realization of the Adomian decomposition method (ADM) in the 80<sup>th</sup>. Undoubtedly, the solution of nonlinear differential equations using ADM is presided over by the acquisition of Adomian polynomials, which are not always easy to find. Thus, the present study proposes easy-to-implement Maple programs for the computation of Adomian polynomials. In fact, the proposed algorithms performed remarkably on several test functions, consisting of one- and multi-variable nonlinearities. Moreover, the introduced programs are advantageous in terms of simplicity;coupled with the requirement of less computational time in comparison with what is known in the literature.展开更多
This paper aims to study a novel expansion discrete grey forecasting model, which could aggregate input information more effectively. In general, existing multi-factor grey forecasting models, such as one order and h ...This paper aims to study a novel expansion discrete grey forecasting model, which could aggregate input information more effectively. In general, existing multi-factor grey forecasting models, such as one order and h variables grey forecasting model (GM (1, h)), always aggregate the main system variable and independent variables in a linear form rather than a nonlinear form, while a nonlinear form could be used in more cases than the linear form. And the nonlinear form could aggregate collinear independent factors, which widely lie in many multi-factor forecasting problems. To overcome this problem, a new approach, named as the Solow residual method, is proposed to aggregate independent factors. And a new expansion model, feedback multi-factor discrete grey forecasting model based on the Solow residual method (abbreviated as FDGM (1, h)), is proposed accordingly. Then the feedback control equation and the parameters' solution of the FDGM (1, h) model are given. Finally, a real application is used to test the modelling accuracy of the FDGM (1, h) model. Results show that the FDGM (1, h) model is much better than the nonhomogeneous discrete grey forecasting model (NDGM) and the GM (1, h) model.展开更多
The multi-variable finite element algorithm based on the generalized Gulerkin's method is more flexible to establish a finite element model in the continuum mechanics. By using this algorithm and numerical tests a...The multi-variable finite element algorithm based on the generalized Gulerkin's method is more flexible to establish a finite element model in the continuum mechanics. By using this algorithm and numerical tests a new singular finite element for elasto-plastic fracture analysis has been formulated. The results of numerical tests show that the new element possesses high accuracy and good performance. Some rules for formulating a multi-variable singular finite element are also discussed in this paper.展开更多
Parkinson’s disease(PD)is a neurodegenerative disease in the central nervous system.Recently,more researches have been conducted in the determination of PD prediction which is really a challenging task.Due to the dis...Parkinson’s disease(PD)is a neurodegenerative disease in the central nervous system.Recently,more researches have been conducted in the determination of PD prediction which is really a challenging task.Due to the disorders in the central nervous system,the syndromes like off sleep,speech disorders,olfactory and autonomic dysfunction,sensory disorder symptoms will occur.The earliest diagnosing of PD is very challenging among the doctors community.There are techniques that are available in order to predict PD using symptoms and disorder measurement.It helps to save a million lives of future by early prediction.In this article,the early diagnosing of PD using machine learning techniques with feature selection is carried out.In the first stage,the data preprocessing is used for the preparation of Parkinson’s disease data.In the second stage,MFEA is used for extracting features.In the third stage,the feature selection is performed using multiple feature input with a principal component analysis(PCA)algorithm.Finally,a Darknet Convolutional Neural Network(DNetCNN)is used to classify the PD patients.The main advantage of using PCA-DNetCNN is that,it provides the best classification in the image dataset using YOLO.In addition to that,the results of various existing methods are compared and the proposed DNetCNN proves better accuracy,performance in detecting the PD at the initial stages.DNetCNN achieves 97.5%of accuracy in detecting PD as early.Besides,the other performance metrics are compared in the result evaluation and it is proved that the proposed model outperforms all the other existing models.展开更多
This paper introduces a new notion of weighted least-square orthogonal polynomials in multivariables from the triangular form. Their existence and uniqueness is studied and some methods for their recursive computation...This paper introduces a new notion of weighted least-square orthogonal polynomials in multivariables from the triangular form. Their existence and uniqueness is studied and some methods for their recursive computation are given. As an application, this paper constructs a new family of Pade-type approximates in multi-variables from the triangular form.展开更多
In this article, we studied the bearings made by one company in Shanghai. Through statistical process controlling the quality characteristic of bearings’ diameters and multi-vary analysis is applied to find the key v...In this article, we studied the bearings made by one company in Shanghai. Through statistical process controlling the quality characteristic of bearings’ diameters and multi-vary analysis is applied to find the key variation factors which have an influence on the quality characteristic of the bearings, the quality level of the bearings of this company is improved.展开更多
This paper investigates State Space Model Predictive Control (SSMPC) of an aerothermic process. It is a pilot scale heating and ventilation system equipped with a heater grid and a centrifugal blower, fully connected ...This paper investigates State Space Model Predictive Control (SSMPC) of an aerothermic process. It is a pilot scale heating and ventilation system equipped with a heater grid and a centrifugal blower, fully connected through a data acquisition system for real time control. The interaction between the process variables is shown to be challenging for single variable controllers, therefore multi-variable control is worth considering. A multi-variable state space model is obtained from on-line experimental data. The controller design is translated into a Quadratic Programming (QP) problem, in which a cost function subject to actuators linear inequality constraints is minimized. The outcome of the experimental results is that the main control objectives, such as set-point tracking and perturbations rejection under actuators constraints, are well achieved for both controlled variables simultaneously.展开更多
Based on the interval mathematics and possibility theory, the variables existing in hydraulic turbine blade are described. Considering the multi-failure mode in turbine blade, multi-variable model is established to me...Based on the interval mathematics and possibility theory, the variables existing in hydraulic turbine blade are described. Considering the multi-failure mode in turbine blade, multi-variable model is established to meet the actual situation. Thus, non-probabilistic reliability index is presented by comparing with the output range and the given range.展开更多
Using an operator ordering method for some commutative superposition operators,we introduce two new multi-variable special polynomials and their generating functions,and present some new operator identities and integr...Using an operator ordering method for some commutative superposition operators,we introduce two new multi-variable special polynomials and their generating functions,and present some new operator identities and integral formulas involving the two special polynomials.Instead of calculating compli-cated partial differential,we use the special polynomials and their generating functions to concsely address the normalzation,photoount distributions and Wigner distributions of several quantum states that can be realized physically,the rsults of which provide real convenience for further investigating the properties and applications of these states.展开更多
This work evaluated the practicability and economy of the enhanced weathering(EW)-based CO_(2) capture in series packed bubble column(S-PBC)contactors operated with different process configurations and conditions.The ...This work evaluated the practicability and economy of the enhanced weathering(EW)-based CO_(2) capture in series packed bubble column(S-PBC)contactors operated with different process configurations and conditions.The S-PBC contactors are designed to fully use the advantages of abundant seawater and highly efficient freshwater through a holistic M4 model,including multi-physics,machine learning,multi-variable and multiobjective optimisation.An economic analysis is then performed to investigate the cost of different S-PBC configurations.A data-driven surrogate model based on a novel machine learning algorithm,extended adaptive hybrid functions(E-AHF),is implemented and trained by the data generated by the physics-based models.GA and NSGA-II are applied to perform single-and multi-objective optimisation to achieve maximum CO_(2) capture rate(CR)and minimum energy consumption(EC)with the optimal values of eight design variables.The R2 for the prediction of CR and EC is higher than 0.96 and the relative errors are lower than 5%.The M4 model has proven to be an efficient way to perform multi-variable and multi-objective optimisation,that significantly reduces computational time and resources while maintaining high prediction accuracy.The trade-off of the maximum CR and minimum EC is presented by the Pareto front,with the optimal values of 0.1014 kg h−1 for CR and 6.1855 MJ kg−1 CO_(2) for EC.The calculated net cost of the most promising S-PBC configuration is around 400$t−1 CO_(2),which is about 100$t−1 CO_(2) lower than the net cost of current direct air capture(DAC),but compromised by slower CO_(2) capture rate.展开更多
The reports of severe adverse effects and fatalities associated with herbal medicinal products adulterated with synthetic compounds have raised global concerns.The objective of this study is to analyze one commercial ...The reports of severe adverse effects and fatalities associated with herbal medicinal products adulterated with synthetic compounds have raised global concerns.The objective of this study is to analyze one commercial herbal medicinal product suspected to be adulterated with synthetic drugs in order to identify potential adulterants,to verify if the product contained the herbs listed as ingredients in label claim and to determine quality consistency among different batches of the product.Analyses of suspected product obtained from seven different batches were performed using ultra performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry(UPLC-Q-TOF-MS) with multiple data processing tools and multivariate analyses.In addition,23 individual powdered herbs(12 as per label claim and 11 suspected herbs),11 marker compounds of the labeled herbs and five suspected synthetic drugs as adulterants were also concurrently analyzed to have clear understanding of product composition.Based on our analysis,the major ingredients of studied product were found to be 5 synthetic compounds:caffeine,chlorphenamine,piroxicam,betamethasone and oxethazaine.Three of them have been found to exceed their recommended doses.From the herbal composition analysis,Gan Cao(Glycyrrhizae radix et rhizoma) was found to be the main ingredient,which is not among the claimed 12 herbs that were supposed to be in the product.Other herbs detected as minor ingredients were Mu Gua(Chaenomelis fructus),Dang Gui(Angelicae sinensis radix),and Huang Qi(Astragali radix),which are among the 12 herbs that were supposed to be in the product.Based on our results we demonstrated that UPLC-QTOF MS is an effective and versatile tool for the analysis of herbal medicinal products.It is highly desirable to have a streamlined process with automatic workflow and fit-forpurpose database to increase efficiency and productivity of sample analysis.Results of this work also highlight the need for the better quality control and regulatory measures to protect consumers from the potentially harmful effects of such adulterated products.展开更多
Constrained by orbital configuration and spectrum sharing,non-geostationary orbit(NGEO)satellites may be interfered when they are in the beam range of geostationary orbit(GEO)satellite.However,it is difficult for NGEO...Constrained by orbital configuration and spectrum sharing,non-geostationary orbit(NGEO)satellites may be interfered when they are in the beam range of geostationary orbit(GEO)satellite.However,it is difficult for NGEO operators to determine the signal source.Herein,we propose a method to locate the GEO signal source and estimate beam features,including beam pointing azimuth,elevation,and beamwidth,by the beam edge positions.We transform this estimation problem into two optimization problems by minimizing the estimation error,and solve both of them through a multi-variable joint iteration method with acceptable computation complexity.Numerical results show that when NGEO satellites pass through the beam twice,the longitude estimation error is about 0.01 degree,and the estimation results will be more and more accurate as the number of passing times increases.Besides,the proposed method is also effective when there are kilometer-level errors in beam edge positions.展开更多
基金supported by a grant from the MaineDOT and Vanasse Hangen Brustlin(VHB).Grant number:VHB 52874.03 WIN 026140.00,Name of the author who received the funding:Tae J.Kwon.
文摘This paper extends the previously developed method of optimizing Road Weather Information Systems(RWIS)station placement by unveiling a sophisticated multi-variable semivariogram model that concurrently considers multiple vital road weather variables.Previous research primarily centered on single-variable analysis focusing on road surface temperature(RST).The study bridges this oversight by introducing a framework that integrates multiple critical weather variables into the RWIS location allocation framework.This novel approach ensures balanced and equitable RWIS distribution across zones and aligns the network with areas both prone to traffic accidents and areas of high uncertainty.To demonstrate the effectiveness of this refinement,the authors applied the framework to Maine’s existing RWIS network,conducted a gap analysis through varying planning scenarios and generated optimal solutions using a heuristic optimization algorithm.The analysis identified areas that would benefit most from additional RWIS stations and guided optimal resource utilization across different road types and priority locations.A sensitivity analysis was also performed to evaluate the effect of different weightings for weather and traffic factors on the selection of optimal locations.The location solutions generated have been adopted by MaineDOT for future implementations,attesting to the model’s practicality and signifying an important advancement for more effective management of road weather conditions.
基金supported by the National Natural Science Foundation of China(71071077)the Ministry of Education Key Project of National Educational Science Planning(DFA090215)+1 种基金China Postdoctoral Science Foundation(20100481137)Funding of Jiangsu Innovation Program for Graduate Education(CXZZ11-0226)
文摘The construction method of background value is improved in the original multi-variable grey model (MGM(1,m)) from its source of construction errors. The MGM(1,m) with optimized background value is used to eliminate the random fluctuations or errors of the observational data of all variables, and the combined prediction model together with the multiple linear regression is established in order to improve the simulation and prediction accuracy of the combined model. Finally, a combined model of the MGM(1,2) with optimized background value and the binary linear regression is constructed by an example. The results show that the model has good effects for simulation and prediction.
基金supported by the National Basic Research Program of China (973Program) under Grant No. 2010CB731800the National Natural Science Foundation of China under Grant No. 60934003 and 61074065the Key Project for Natural Science Research of Hebei Education Departmentunder Grant No. ZD200908
文摘A novel flocking control approach is proposed for multi-agent systems by integrating the variables of velocities, motion directions, and positions of agents. A received signal strength indicator (RSSI) is applied as a variable to estimate the inter-distance between agents. A key parameter that contains the local information of agents is defined, and a multi-variable controller is proposed based on the parameter. For the position control of agents, the RSSI is introduced to substitute the distance as a control variable in the systems. The advantages of RSSI include that the relative distance between every two agents can be adjusted through the communication quality under different environments, and it can shun the shortage of the limit of sensors. Simulation studies demonstrate the effectiveness of the proposed control approach.
文摘The modern industrial control objects become more and more complicated,and higher control quality is required, so a series of new control strategies appear,applied,modified and develop quickly.This paper researches a new control strategy- prediction control-and its application in Multi-Variable Control Process.The research result is worthy for automatic control in pro- cess industry.
文摘It is well known that Landsat TM images are the most widely used remote sensing data in various fields.Usually,it has 7 different electromagnetic spectrum bands,among which the sixth one has much lower ground resolution compared with the other six bands.Nevertheless,it is useful in the study of rock spectrum reflection,geothermal resources exploration,etc.To improve the ground resolution of TM6 to the level as that of the other six bands is a problem .This paper presents an algorithm based on the combination of multivariate regression model with semivariogram function which can improve the ground resolution of TM6 by "fusing" the data of other six bands.It includes the following main steps: (1) testing the correlation between TM6 and one of TM15,7.If the correlation coefficient between TM6 and another one is greater than a given threshold value,then select the band to the regression analysis as an argument.(2) calculating the size of the template window within which some parameters needed by the regression model will be calculated; (3) replacing the original pixel values of TM6 by those obtained by regression analysis; (4) using image entropy as a measurement to evaluate the quality of the fused image of TM6.The basic mechanism of the algorithm is discussed and the V C ++ program for implementing this algorithm is also presented.A simple application example is given in the last part of this paper,showing the effectiveness of the algorithm.
文摘By modeling direct transient heat conduction problems via finite element method (FEM) and precise integral algorithm, a new approach is presented to solve transient inverse heat conduction problems with multi-variables. Firstly, the spatial space and temporal domain are discretized by FEM and precise integral algorithm respectively. Then, the high accuracy semi-analytical solution of direct problem can be got. Finally, based on the solution, the computing model of inverse problem and expression of sensitivity analysis are established. Single variable and variables combined identifications including thermal parameters, boundary conditions and source-related terms etc. are given to validate the approach proposed in 1-D and 2-D cases. The effects of noise data and initial guess on the results are investigated. The numerical examples show the effectiveness of this approach.
基金National Key Research and Development Program of China(Grant No.2018YF0804003)the National Key Research and Development Program of China under Grant No.2017YFB0803204.
文摘As an active defenses technique,multivariant execution(MVX)can detect attacks by monitoring the consistency of heterogeneous variants with parallel execution.Compared with patch-style passive defense,MVX can defend against known and even unknown vulnerability-based attacks without relying on attack feature information.However,variants generated with software diversity technologies will introduce new vulnerabilities when they execute in parallel.First,we analyze the security of MVX theory from the perspective of formal description.Then we summarize the general forms and techniques for attacks against MVX,and analyze the new vulnerabilities arising from the combination of variant generation technologies.We propose SecMVX,a secure MVX architecture and variant generation technology.Experimental evaluations based on CVEs and SPEC 2006 benchmark show that SecMVX introduces 11.29%of the average time overhead,and avoids vulnerabilities caused by the improper combination of variant generation technologies while keeping the defensive ability of MVX.
文摘The immense quest for proficient numerical schemes for the solution of mathematical models featuring nonlinear differential equations led to the realization of the Adomian decomposition method (ADM) in the 80<sup>th</sup>. Undoubtedly, the solution of nonlinear differential equations using ADM is presided over by the acquisition of Adomian polynomials, which are not always easy to find. Thus, the present study proposes easy-to-implement Maple programs for the computation of Adomian polynomials. In fact, the proposed algorithms performed remarkably on several test functions, consisting of one- and multi-variable nonlinearities. Moreover, the introduced programs are advantageous in terms of simplicity;coupled with the requirement of less computational time in comparison with what is known in the literature.
基金supported by the National Natural Science Foundation of China(7117111370901041)
文摘This paper aims to study a novel expansion discrete grey forecasting model, which could aggregate input information more effectively. In general, existing multi-factor grey forecasting models, such as one order and h variables grey forecasting model (GM (1, h)), always aggregate the main system variable and independent variables in a linear form rather than a nonlinear form, while a nonlinear form could be used in more cases than the linear form. And the nonlinear form could aggregate collinear independent factors, which widely lie in many multi-factor forecasting problems. To overcome this problem, a new approach, named as the Solow residual method, is proposed to aggregate independent factors. And a new expansion model, feedback multi-factor discrete grey forecasting model based on the Solow residual method (abbreviated as FDGM (1, h)), is proposed accordingly. Then the feedback control equation and the parameters' solution of the FDGM (1, h) model are given. Finally, a real application is used to test the modelling accuracy of the FDGM (1, h) model. Results show that the FDGM (1, h) model is much better than the nonhomogeneous discrete grey forecasting model (NDGM) and the GM (1, h) model.
文摘The multi-variable finite element algorithm based on the generalized Gulerkin's method is more flexible to establish a finite element model in the continuum mechanics. By using this algorithm and numerical tests a new singular finite element for elasto-plastic fracture analysis has been formulated. The results of numerical tests show that the new element possesses high accuracy and good performance. Some rules for formulating a multi-variable singular finite element are also discussed in this paper.
文摘Parkinson’s disease(PD)is a neurodegenerative disease in the central nervous system.Recently,more researches have been conducted in the determination of PD prediction which is really a challenging task.Due to the disorders in the central nervous system,the syndromes like off sleep,speech disorders,olfactory and autonomic dysfunction,sensory disorder symptoms will occur.The earliest diagnosing of PD is very challenging among the doctors community.There are techniques that are available in order to predict PD using symptoms and disorder measurement.It helps to save a million lives of future by early prediction.In this article,the early diagnosing of PD using machine learning techniques with feature selection is carried out.In the first stage,the data preprocessing is used for the preparation of Parkinson’s disease data.In the second stage,MFEA is used for extracting features.In the third stage,the feature selection is performed using multiple feature input with a principal component analysis(PCA)algorithm.Finally,a Darknet Convolutional Neural Network(DNetCNN)is used to classify the PD patients.The main advantage of using PCA-DNetCNN is that,it provides the best classification in the image dataset using YOLO.In addition to that,the results of various existing methods are compared and the proposed DNetCNN proves better accuracy,performance in detecting the PD at the initial stages.DNetCNN achieves 97.5%of accuracy in detecting PD as early.Besides,the other performance metrics are compared in the result evaluation and it is proved that the proposed model outperforms all the other existing models.
文摘This paper introduces a new notion of weighted least-square orthogonal polynomials in multivariables from the triangular form. Their existence and uniqueness is studied and some methods for their recursive computation are given. As an application, this paper constructs a new family of Pade-type approximates in multi-variables from the triangular form.
文摘In this article, we studied the bearings made by one company in Shanghai. Through statistical process controlling the quality characteristic of bearings’ diameters and multi-vary analysis is applied to find the key variation factors which have an influence on the quality characteristic of the bearings, the quality level of the bearings of this company is improved.
文摘This paper investigates State Space Model Predictive Control (SSMPC) of an aerothermic process. It is a pilot scale heating and ventilation system equipped with a heater grid and a centrifugal blower, fully connected through a data acquisition system for real time control. The interaction between the process variables is shown to be challenging for single variable controllers, therefore multi-variable control is worth considering. A multi-variable state space model is obtained from on-line experimental data. The controller design is translated into a Quadratic Programming (QP) problem, in which a cost function subject to actuators linear inequality constraints is minimized. The outcome of the experimental results is that the main control objectives, such as set-point tracking and perturbations rejection under actuators constraints, are well achieved for both controlled variables simultaneously.
基金the Key Scientific Research Fund Project of Xihua University(No.Z1320406)the National Natural Science Foundation of China(No.51379179)
文摘Based on the interval mathematics and possibility theory, the variables existing in hydraulic turbine blade are described. Considering the multi-failure mode in turbine blade, multi-variable model is established to meet the actual situation. Thus, non-probabilistic reliability index is presented by comparing with the output range and the given range.
基金the National Natural Science Foundation of China(Grant No.11347026)the Natural Science Foundation of Shandong Province(Grant Nos.ZR2016AM03 and ZR2017M A011).
文摘Using an operator ordering method for some commutative superposition operators,we introduce two new multi-variable special polynomials and their generating functions,and present some new operator identities and integral formulas involving the two special polynomials.Instead of calculating compli-cated partial differential,we use the special polynomials and their generating functions to concsely address the normalzation,photoount distributions and Wigner distributions of several quantum states that can be realized physically,the rsults of which provide real convenience for further investigating the properties and applications of these states.
基金supported by UK Engineering and Physical Sciences Research Council(EPSRC)under the grant numbers EP/V042432/1 and EP/V011863/1The authors also gratefully acknowledge the financial support from the National Natural Science Foundation of China(21978118).
文摘This work evaluated the practicability and economy of the enhanced weathering(EW)-based CO_(2) capture in series packed bubble column(S-PBC)contactors operated with different process configurations and conditions.The S-PBC contactors are designed to fully use the advantages of abundant seawater and highly efficient freshwater through a holistic M4 model,including multi-physics,machine learning,multi-variable and multiobjective optimisation.An economic analysis is then performed to investigate the cost of different S-PBC configurations.A data-driven surrogate model based on a novel machine learning algorithm,extended adaptive hybrid functions(E-AHF),is implemented and trained by the data generated by the physics-based models.GA and NSGA-II are applied to perform single-and multi-objective optimisation to achieve maximum CO_(2) capture rate(CR)and minimum energy consumption(EC)with the optimal values of eight design variables.The R2 for the prediction of CR and EC is higher than 0.96 and the relative errors are lower than 5%.The M4 model has proven to be an efficient way to perform multi-variable and multi-objective optimisation,that significantly reduces computational time and resources while maintaining high prediction accuracy.The trade-off of the maximum CR and minimum EC is presented by the Pareto front,with the optimal values of 0.1014 kg h−1 for CR and 6.1855 MJ kg−1 CO_(2) for EC.The calculated net cost of the most promising S-PBC configuration is around 400$t−1 CO_(2),which is about 100$t−1 CO_(2) lower than the net cost of current direct air capture(DAC),but compromised by slower CO_(2) capture rate.
文摘The reports of severe adverse effects and fatalities associated with herbal medicinal products adulterated with synthetic compounds have raised global concerns.The objective of this study is to analyze one commercial herbal medicinal product suspected to be adulterated with synthetic drugs in order to identify potential adulterants,to verify if the product contained the herbs listed as ingredients in label claim and to determine quality consistency among different batches of the product.Analyses of suspected product obtained from seven different batches were performed using ultra performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry(UPLC-Q-TOF-MS) with multiple data processing tools and multivariate analyses.In addition,23 individual powdered herbs(12 as per label claim and 11 suspected herbs),11 marker compounds of the labeled herbs and five suspected synthetic drugs as adulterants were also concurrently analyzed to have clear understanding of product composition.Based on our analysis,the major ingredients of studied product were found to be 5 synthetic compounds:caffeine,chlorphenamine,piroxicam,betamethasone and oxethazaine.Three of them have been found to exceed their recommended doses.From the herbal composition analysis,Gan Cao(Glycyrrhizae radix et rhizoma) was found to be the main ingredient,which is not among the claimed 12 herbs that were supposed to be in the product.Other herbs detected as minor ingredients were Mu Gua(Chaenomelis fructus),Dang Gui(Angelicae sinensis radix),and Huang Qi(Astragali radix),which are among the 12 herbs that were supposed to be in the product.Based on our results we demonstrated that UPLC-QTOF MS is an effective and versatile tool for the analysis of herbal medicinal products.It is highly desirable to have a streamlined process with automatic workflow and fit-forpurpose database to increase efficiency and productivity of sample analysis.Results of this work also highlight the need for the better quality control and regulatory measures to protect consumers from the potentially harmful effects of such adulterated products.
基金supported by the National Natural Science Foundation of China(Grant No.91738101)Shanghai Municipal Science and Technology Major Project(Grant No.2018SHZDZX04)Interdisciplinary Major Project of School of Information Science and Technology,Tsinghua University(Grant No.20031887521).
文摘Constrained by orbital configuration and spectrum sharing,non-geostationary orbit(NGEO)satellites may be interfered when they are in the beam range of geostationary orbit(GEO)satellite.However,it is difficult for NGEO operators to determine the signal source.Herein,we propose a method to locate the GEO signal source and estimate beam features,including beam pointing azimuth,elevation,and beamwidth,by the beam edge positions.We transform this estimation problem into two optimization problems by minimizing the estimation error,and solve both of them through a multi-variable joint iteration method with acceptable computation complexity.Numerical results show that when NGEO satellites pass through the beam twice,the longitude estimation error is about 0.01 degree,and the estimation results will be more and more accurate as the number of passing times increases.Besides,the proposed method is also effective when there are kilometer-level errors in beam edge positions.