Accurate detection of exercise fatigue based on physiological signals is vital for reason-able physical activity.As a non-invasive technology,phonocardiogram(PCG)signals possess arobust capability to reflect cardiovas...Accurate detection of exercise fatigue based on physiological signals is vital for reason-able physical activity.As a non-invasive technology,phonocardiogram(PCG)signals possess arobust capability to reflect cardiovascular information,and their data acquisition devices are quiteconvenient.In this study,a novel hybrid approach of fractional Fourier transform(FRFT)com-bined with linear and discrete wavelet transform(DWT)features extracted from PCG is proposedfor PCG multi-class classification.The proposed system enhances the fatigue detection performanceby combining optimized FRFT features with an effective aggregation of linear features and DWTfeatures.The FRFT technique is employed to convert the 1-D PCG signal into 2-D image which issent to a pre-trained convolutional neural network structure,called VGG-16.The features from theVGG-16 were concatenated with the linear and DWT features to form fused features.The fusedfeatures are sent to support vector machine(SVM)to distinguish six distinct fatigue levels.Experi-mental results demonstrate that the proposed fused features outperform other feature combinationssignificantly.展开更多
The aim of this paper is to employ fractional order proportional integral derivative(FO-PID)controller and integer order PID controller to control the position of the levitated object in a magnetic levitation system(M...The aim of this paper is to employ fractional order proportional integral derivative(FO-PID)controller and integer order PID controller to control the position of the levitated object in a magnetic levitation system(MLS),which is inherently nonlinear and unstable system.The proposal is to deploy discrete optimal pole-zero approximation method for realization of digital fractional order controller.An approach of phase shaping by slope cancellation of asymptotic phase plots for zeros and poles within given bandwidth is explored.The controller parameters are tuned using dynamic particle swarm optimization(d PSO)technique.Effectiveness of the proposed control scheme is verified by simulation and experimental results.The performance of realized digital FO-PID controller has been compared with that of the integer order PID controllers.It is observed that effort required in fractional order control is smaller as compared with its integer counterpart for obtaining the same system performance.展开更多
In this paper, we apply a discrete Littlewood-Paley analysis to obtain Hardy spaces HP（Rn1× … ×Rnk） of arbitrary number of parameters characterized by discrete Littlewood-Paley square function and derive ...In this paper, we apply a discrete Littlewood-Paley analysis to obtain Hardy spaces HP（Rn1× … ×Rnk） of arbitrary number of parameters characterized by discrete Littlewood-Paley square function and derive the boundedness of singular integral operators onHP（Rn1× … ×Rnk） and fromHP（Rn1× … ×Rnk）toLP（Rn1× … ×Rnk）.展开更多
This paper constructs the first mixed finite element for the linear elasticity problem in 3D using P3 polynomials for the stress and discontinuous P2 polynomials for the displace-ment on tetrahedral meshes under some ...This paper constructs the first mixed finite element for the linear elasticity problem in 3D using P3 polynomials for the stress and discontinuous P2 polynomials for the displace-ment on tetrahedral meshes under some mild mesh conditions.The degrees of freedom of the stress space as well as the corresponding nodal basis are established by characterizing a space of certain piecewise constant symmetric matrices on a patch around each edge.Macro-element techniques are used to define a stable interpolation to prove the discrete inf-sup condition.Optimal convergence is obtained theoretically.展开更多
Identification of attacks by a network intrusion detection system （NIDS） is an important task. In signature or rule based detection, the previously encountered attacks are modded, and signatures/rules are extracted....Identification of attacks by a network intrusion detection system （NIDS） is an important task. In signature or rule based detection, the previously encountered attacks are modded, and signatures/rules are extracted. These rules are used to detect such attacks in future, but in anomaly or outlier detection system, the normal network traffic is modeled. Any deviation from the normal model is deemed to be an outlier/attack. Data mining and machine learning techniques are widely used in offline NIDS. Unsupervised and supervised learning techniques differ the way NIDS dataset is treated. The characteristic features of unsupervised and supervised learning are finding patterns in data, detecting outliers, and determining a learned function for input features, generalizing the data instances respectively. The intuition is that if these two techniques are combined, better performance may be obtained. Hence, in this paper the advantages of unsupervised and supervised techniques are inherited in the proposed hierarchical model and devised into three stages to detect attacks in NIDS dataset. NIDS dataset is clustered using Dirichiet process （DP） clustering based on the underlying data distribution. Iteratively on each cluster, local denser areas are identified using local outlier factor （LOF） which in turn is discretized into four bins of separation based on LOF score. Further, in each bin the normal data instances are modeled using one class classifier （OCC）. A combination of Density Estimation method, Reconstruction method, and Boundary methods are used for OCC model. A product rule combination of the three methods takes into consideration the strengths of each method in building a stronger OCC model. Any deviation from this model is considered as an attack. Experiments are conducted on KDD CUP＇99 and SSENet-2011 datasets. The results show that the proposed model is able to identify attacks with higher detection rate and low false alarms.展开更多
In this research, the temperatures of three- dimensional （3D） protruding heaters mounted on a conductive substrate in a horizontal rectangular channel with laminar airflow are related to the independent power dissip...In this research, the temperatures of three- dimensional （3D） protruding heaters mounted on a conductive substrate in a horizontal rectangular channel with laminar airflow are related to the independent power dissipation in each heater by using a matrix G＋ with invariant coefficients, which are dimensionless. These coefficients are defined in this study as the conjugate influence coefficients （g＋） caused by the forced convec- tion-conduction nature of the heaters＇ cooling process. The temperature increase of each heater in the channel is quantified to clearly identify the contributions attributed to the self-heating and power dissipation in the other heaters （both upstream and downstream）. The conjugate coefficients are invariant with the heat generation rate in the array of heaters when assuming a defined geometry, invariable fluid and flow rate, and constant substrate and heater conductivities. The results are numerically obtained by considering three 3D protruding heaters on a twodimensional （2D） array by ANSYS/FluentTM 15.0 software. The conservation equations are solved by a coupled procedure within a single calculation domain comprising of solid and fluid regions and by considering a steady state laminar airflow with constant properties. Some examples are shown, indicating the effects of substrate thermal conductivity and Reynolds number on conjugate influence coefficients.展开更多
基金the National Natural Sci-ence Foundation of China(No.62301056)the Fundamental Research Funds for Central Universities(No.2022QN005).
文摘Accurate detection of exercise fatigue based on physiological signals is vital for reason-able physical activity.As a non-invasive technology,phonocardiogram(PCG)signals possess arobust capability to reflect cardiovascular information,and their data acquisition devices are quiteconvenient.In this study,a novel hybrid approach of fractional Fourier transform(FRFT)com-bined with linear and discrete wavelet transform(DWT)features extracted from PCG is proposedfor PCG multi-class classification.The proposed system enhances the fatigue detection performanceby combining optimized FRFT features with an effective aggregation of linear features and DWTfeatures.The FRFT technique is employed to convert the 1-D PCG signal into 2-D image which issent to a pre-trained convolutional neural network structure,called VGG-16.The features from theVGG-16 were concatenated with the linear and DWT features to form fused features.The fusedfeatures are sent to support vector machine(SVM)to distinguish six distinct fatigue levels.Experi-mental results demonstrate that the proposed fused features outperform other feature combinationssignificantly.
基金supported by the Board of Research in Nuclear Sciences of the Department of Atomic Energy,India(2012/36/69-BRNS/2012)
文摘The aim of this paper is to employ fractional order proportional integral derivative(FO-PID)controller and integer order PID controller to control the position of the levitated object in a magnetic levitation system(MLS),which is inherently nonlinear and unstable system.The proposal is to deploy discrete optimal pole-zero approximation method for realization of digital fractional order controller.An approach of phase shaping by slope cancellation of asymptotic phase plots for zeros and poles within given bandwidth is explored.The controller parameters are tuned using dynamic particle swarm optimization(d PSO)technique.Effectiveness of the proposed control scheme is verified by simulation and experimental results.The performance of realized digital FO-PID controller has been compared with that of the integer order PID controllers.It is observed that effort required in fractional order control is smaller as compared with its integer counterpart for obtaining the same system performance.
文摘In this paper, we apply a discrete Littlewood-Paley analysis to obtain Hardy spaces HP（Rn1× … ×Rnk） of arbitrary number of parameters characterized by discrete Littlewood-Paley square function and derive the boundedness of singular integral operators onHP（Rn1× … ×Rnk） and fromHP（Rn1× … ×Rnk）toLP（Rn1× … ×Rnk）.
文摘This paper constructs the first mixed finite element for the linear elasticity problem in 3D using P3 polynomials for the stress and discontinuous P2 polynomials for the displace-ment on tetrahedral meshes under some mild mesh conditions.The degrees of freedom of the stress space as well as the corresponding nodal basis are established by characterizing a space of certain piecewise constant symmetric matrices on a patch around each edge.Macro-element techniques are used to define a stable interpolation to prove the discrete inf-sup condition.Optimal convergence is obtained theoretically.
文摘Identification of attacks by a network intrusion detection system （NIDS） is an important task. In signature or rule based detection, the previously encountered attacks are modded, and signatures/rules are extracted. These rules are used to detect such attacks in future, but in anomaly or outlier detection system, the normal network traffic is modeled. Any deviation from the normal model is deemed to be an outlier/attack. Data mining and machine learning techniques are widely used in offline NIDS. Unsupervised and supervised learning techniques differ the way NIDS dataset is treated. The characteristic features of unsupervised and supervised learning are finding patterns in data, detecting outliers, and determining a learned function for input features, generalizing the data instances respectively. The intuition is that if these two techniques are combined, better performance may be obtained. Hence, in this paper the advantages of unsupervised and supervised techniques are inherited in the proposed hierarchical model and devised into three stages to detect attacks in NIDS dataset. NIDS dataset is clustered using Dirichiet process （DP） clustering based on the underlying data distribution. Iteratively on each cluster, local denser areas are identified using local outlier factor （LOF） which in turn is discretized into four bins of separation based on LOF score. Further, in each bin the normal data instances are modeled using one class classifier （OCC）. A combination of Density Estimation method, Reconstruction method, and Boundary methods are used for OCC model. A product rule combination of the three methods takes into consideration the strengths of each method in building a stronger OCC model. Any deviation from this model is considered as an attack. Experiments are conducted on KDD CUP＇99 and SSENet-2011 datasets. The results show that the proposed model is able to identify attacks with higher detection rate and low false alarms.
文摘In this research, the temperatures of three- dimensional （3D） protruding heaters mounted on a conductive substrate in a horizontal rectangular channel with laminar airflow are related to the independent power dissipation in each heater by using a matrix G＋ with invariant coefficients, which are dimensionless. These coefficients are defined in this study as the conjugate influence coefficients （g＋） caused by the forced convec- tion-conduction nature of the heaters＇ cooling process. The temperature increase of each heater in the channel is quantified to clearly identify the contributions attributed to the self-heating and power dissipation in the other heaters （both upstream and downstream）. The conjugate coefficients are invariant with the heat generation rate in the array of heaters when assuming a defined geometry, invariable fluid and flow rate, and constant substrate and heater conductivities. The results are numerically obtained by considering three 3D protruding heaters on a twodimensional （2D） array by ANSYS/FluentTM 15.0 software. The conservation equations are solved by a coupled procedure within a single calculation domain comprising of solid and fluid regions and by considering a steady state laminar airflow with constant properties. Some examples are shown, indicating the effects of substrate thermal conductivity and Reynolds number on conjugate influence coefficients.
