Purpose: To investigate the efficacy of a new algorithm to increase the volume of tissue ablation via gradual ramp-up of power using an internally cooled electrode for ablating hepatomas 3 cm or less. Materials and Me...Purpose: To investigate the efficacy of a new algorithm to increase the volume of tissue ablation via gradual ramp-up of power using an internally cooled electrode for ablating hepatomas 3 cm or less. Materials and Methods: 44 patients with 62 hepatomas were treated from March 4, 2004 to May 24, 2009. Ablation with a gradual ramp-up of power was performed using a single needle with an internally cooled electrode. Evaluation for tumor response was performed with 4-phase CT at 24 hours and 3 months. All immediate and follow-up complications were recorded. Results: Complete tumor ablation was achieved in 86%. The ablation volumes were 16 cm3 +/- 12 cm3 for tumors 3 +/- 12 cm3 for tumors 2 - 3 cm. Out of 68 total ablation sessions, there were 2 major complications (pleural effusions) requiring intervention (thoracentesis). Conclusion: Compared with existing techniques using a constant full-power setting, ablation of small hepatomas using an algorithm of gradual ramp-up of power provides comparable rate of complete tumor ablation, adequate ablation volumes, and a low rate of complications that require treatment.展开更多
The security of international date encryption algorithm (IDEA(16)), a mini IDEA cipher, against differential cryptanalysis is investigated. The results show that [DEA(16) is secure against differential cryptanal...The security of international date encryption algorithm (IDEA(16)), a mini IDEA cipher, against differential cryptanalysis is investigated. The results show that [DEA(16) is secure against differential cryptanalysis attack after 5 rounds while IDEA(8) needs 7 rounds for the same level of security. The transition matrix for IDEA(16) and its eigenvalue of second largest magnitude are computed. The storage method for the transition matrix has been optimized to speed up file I/O. The emphasis of the work lies in finding out an effective way of computing the eigenvalue of the matrix. To lower time complexity, three mature algorithms in finding eigenvalues are compared from one another and subspace iteration algorithm is employed to compute the eigenvalue of second largest module, with a precision of 0.001.展开更多
An adaptive internal mode control is proposed to eliminate effectively periodic disturbance with uncertain frequency caused by input error angle of PIGA (Pendulous Integrating Gyro Accelerometer). An adaptive algori...An adaptive internal mode control is proposed to eliminate effectively periodic disturbance with uncertain frequency caused by input error angle of PIGA (Pendulous Integrating Gyro Accelerometer). An adaptive algorithm with periodic disturbance frequency identification on line is applied and the internal model controller parameters are adjusted to eliminate disturbance. Then the convergence of this algorithm and the stability of the system are proved by the averaging method. Simulation results verify the proposed scheme can eliminate periodic disturbance and improve the test precision for PIGA effectively.展开更多
A frequency domain method for estimating wind-induced fluctuating internal pressure of structure with single windward opening is presented in this paper and wind tunnel tests were carried out to verify the theory. The...A frequency domain method for estimating wind-induced fluctuating internal pressure of structure with single windward opening is presented in this paper and wind tunnel tests were carried out to verify the theory. The nonlinear differential equation of internal pressure dynamics and iteration algorithm were applied to calculate fluctuating internal pressure and time domain analysis was used to verify the accuracy of the proposed method. A simplified estimation method is also provided and its scope of application is clarified. The mechanism of internal pressure fluctuation is obtained by using the proposed method in the frequency domain and a new equivalent opening ratio is defined to evaluate internal pressure fluctuation. A series of low-rise building models with various openings and internal volumes were designed for wind tunnel tests with results agreeing well with analytical results. It is shown that the proposed frequency domain method based on Gaussian distribution of internal pressure fluctuations can be applied to predict the RMS internal pressure coefficient with adequate accuracy for any opening dimensions, while the simplified method can only be used for structure with single dominant opening. Helmholtz resonance is likely to occur when the equivalent opening ratio is adequately high, and controlling individual opening dimension is an effective strategy for avoiding Helmholtz resonance in engineering.展开更多
According to the characteristics of the large time delay,nonlinearity and the great inertia of temperature control system in biomass pyrolysis reactor,a two-degree-of-freedom Smith internal model controller based on f...According to the characteristics of the large time delay,nonlinearity and the great inertia of temperature control system in biomass pyrolysis reactor,a two-degree-of-freedom Smith internal model controller based on fuzzy control is proposed.Firstly,the mathematical model of the temperature control system is established by using the step response method,and then the two-degree-of-freedom Smith internal model controller is designed,and the good tracking performance and disturbance suppression performance can be obtained by designing the set value tracking controller and interference rejection capability.Secondly,the fuzzy control algorithm is used to realize the on-line tuning of the control parameters of the two-degree-of-freedom Smith internal model algorithm.The simulation results show that,compared with the traditional internal model control,fuzzy internal model PID control and two-degree-of-freedom Smith internal model control,the algorithm proposed in this paper improves the influence of lag time on the control system,realizes the separation control of set point tracking and anti-jamming performance and the self-tuning of control parameters,and improves the control performance of the system.展开更多
This work concerns the study of problems relating to the adaptive internal model control of DC motor in both cases conventional and neural. The most important aspects of design building blocks of adaptive internal mod...This work concerns the study of problems relating to the adaptive internal model control of DC motor in both cases conventional and neural. The most important aspects of design building blocks of adaptive internal model control are the choice of architectures, learning algorithms, and examples of learning. The choice of parametric adaptation algorithm for updating elements of the conventional adaptive internal model control shows limitations. To overcome these limitations, we chose the architectures of neural networks deduced from the conventional models and the Levenberg-marquardt during the adjustment of system parameters of the adaptive neural internal model control. The results of this latest control showed compensation for disturbance, good trajectory tracking performance and system stability.展开更多
For a gantry crane system, this paper presents a comparison between four control algorithms. These algo-rithms are being compared on simplicity, stability and robustness. Goal for the controller is to move the load on...For a gantry crane system, this paper presents a comparison between four control algorithms. These algo-rithms are being compared on simplicity, stability and robustness. Goal for the controller is to move the load on a gantry crane to a new position with minimal overshoot of the load and maximal speed of the load. An-other goal is to provide an insight in the behaviour of the possible controllers. In this article a parallel P-controller, cascade P-controller, fuzzy controller and an internal model controller are used. To be able to validate and design the controllers a model is derived from the gantry crane. The controllers and the model are being implemented in Matlab Simulink. Finally the controllers are validated and tuned in Labview on a laboratory gantry scrane scale model. Main conclusion is that all presented controllers can be used as a con-troller for the gantry crane system but the fuzzy controller is showing the best performance.展开更多
This article proposes a new inner attitude integration algorithm to improve attitude accuracy of the strapdown inertial attitude and heading reference system (SIAHRS) , which, by means of a Kalman filter, integrates...This article proposes a new inner attitude integration algorithm to improve attitude accuracy of the strapdown inertial attitude and heading reference system (SIAHRS) , which, by means of a Kalman filter, integrates the calculated attitude from the accelerometers in inertial measuring unit (IMU) , called damping attitudes, with those from the conventional IMU. As vehicle' s acceleration could produce damping attitude errors, the horizontal outputs from accelerometers are firstly used to judge the vehicle' s motion so as to determine whether the damping attitudes could be reasonably applied. This article also analyzes the limitation of this approach. Furthermore, it suggests a residual chi-square test to judge the validity of damping attitude measurement in real time, and accordingly puts forward proper information fusion strategy. Finally,the effectiveness of the proposed algorithm is proved through the experiments on a real system in dynamic and static states.展开更多
By analyzing the internal features of counting sorting algorithm. Two improvements of counting sorting algorithms are proposed, which have a wide range of applications and better efficiency than the original counting ...By analyzing the internal features of counting sorting algorithm. Two improvements of counting sorting algorithms are proposed, which have a wide range of applications and better efficiency than the original counting sort while maintaining the original stability. Compared with the original counting sort, it has a wider scope of application and better time and space efficiency. In addition, the accuracy of the above conclusions can be proved by a large amount of experimental data.展开更多
Improved picture quality is critical to the effectiveness of object recog-nition and tracking.The consistency of those photos is impacted by night-video systems because the contrast between high-profile items and diffe...Improved picture quality is critical to the effectiveness of object recog-nition and tracking.The consistency of those photos is impacted by night-video systems because the contrast between high-profile items and different atmospheric conditions,such as mist,fog,dust etc.The pictures then shift in intensity,colour,polarity and consistency.A general challenge for computer vision analyses lies in the horrid appearance of night images in arbitrary illumination and ambient envir-onments.In recent years,target recognition techniques focused on deep learning and machine learning have become standard algorithms for object detection with the exponential growth of computer performance capabilities.However,the iden-tification of objects in the night world also poses further problems because of the distorted backdrop and dim light.The Correlation aware LSTM based YOLO(You Look Only Once)classifier method for exact object recognition and deter-mining its properties under night vision was a major inspiration for this work.In order to create virtual target sets similar to daily environments,we employ night images as inputs;and to obtain high enhanced image using histogram based enhancement and iterative wienerfilter for removing the noise in the image.The process of the feature extraction and feature selection was done for electing the potential features using the Adaptive internal linear embedding(AILE)and uplift linear discriminant analysis(ULDA).The region of interest mask can be segmen-ted using the Recurrent-Phase Level set Segmentation.Finally,we use deep con-volution feature fusion and region of interest pooling to integrate the presently extremely sophisticated quicker Long short term memory based(LSTM)with YOLO method for object tracking system.A range of experimentalfindings demonstrate that our technique achieves high average accuracy with a precision of 99.7%for object detection of SSAN datasets that is considerably more than that of the other standard object detection mechanism.Our approach may therefore satisfy the true demands of night scene target detection applications.We very much believe that our method will help future research.展开更多
文摘Purpose: To investigate the efficacy of a new algorithm to increase the volume of tissue ablation via gradual ramp-up of power using an internally cooled electrode for ablating hepatomas 3 cm or less. Materials and Methods: 44 patients with 62 hepatomas were treated from March 4, 2004 to May 24, 2009. Ablation with a gradual ramp-up of power was performed using a single needle with an internally cooled electrode. Evaluation for tumor response was performed with 4-phase CT at 24 hours and 3 months. All immediate and follow-up complications were recorded. Results: Complete tumor ablation was achieved in 86%. The ablation volumes were 16 cm3 +/- 12 cm3 for tumors 3 +/- 12 cm3 for tumors 2 - 3 cm. Out of 68 total ablation sessions, there were 2 major complications (pleural effusions) requiring intervention (thoracentesis). Conclusion: Compared with existing techniques using a constant full-power setting, ablation of small hepatomas using an algorithm of gradual ramp-up of power provides comparable rate of complete tumor ablation, adequate ablation volumes, and a low rate of complications that require treatment.
基金Supported by the National Natural Science Foundation of China (60573032, 90604036)Participation in Research Project of Shanghai Jiao Tong University
文摘The security of international date encryption algorithm (IDEA(16)), a mini IDEA cipher, against differential cryptanalysis is investigated. The results show that [DEA(16) is secure against differential cryptanalysis attack after 5 rounds while IDEA(8) needs 7 rounds for the same level of security. The transition matrix for IDEA(16) and its eigenvalue of second largest magnitude are computed. The storage method for the transition matrix has been optimized to speed up file I/O. The emphasis of the work lies in finding out an effective way of computing the eigenvalue of the matrix. To lower time complexity, three mature algorithms in finding eigenvalues are compared from one another and subspace iteration algorithm is employed to compute the eigenvalue of second largest module, with a precision of 0.001.
文摘An adaptive internal mode control is proposed to eliminate effectively periodic disturbance with uncertain frequency caused by input error angle of PIGA (Pendulous Integrating Gyro Accelerometer). An adaptive algorithm with periodic disturbance frequency identification on line is applied and the internal model controller parameters are adjusted to eliminate disturbance. Then the convergence of this algorithm and the stability of the system are proved by the averaging method. Simulation results verify the proposed scheme can eliminate periodic disturbance and improve the test precision for PIGA effectively.
基金Project (No. 50378085) supported by the National Natural ScienceFoundation of China
文摘A frequency domain method for estimating wind-induced fluctuating internal pressure of structure with single windward opening is presented in this paper and wind tunnel tests were carried out to verify the theory. The nonlinear differential equation of internal pressure dynamics and iteration algorithm were applied to calculate fluctuating internal pressure and time domain analysis was used to verify the accuracy of the proposed method. A simplified estimation method is also provided and its scope of application is clarified. The mechanism of internal pressure fluctuation is obtained by using the proposed method in the frequency domain and a new equivalent opening ratio is defined to evaluate internal pressure fluctuation. A series of low-rise building models with various openings and internal volumes were designed for wind tunnel tests with results agreeing well with analytical results. It is shown that the proposed frequency domain method based on Gaussian distribution of internal pressure fluctuations can be applied to predict the RMS internal pressure coefficient with adequate accuracy for any opening dimensions, while the simplified method can only be used for structure with single dominant opening. Helmholtz resonance is likely to occur when the equivalent opening ratio is adequately high, and controlling individual opening dimension is an effective strategy for avoiding Helmholtz resonance in engineering.
基金financial support was given by Tianjin Technical Expert Project(19JCTPJC59300)
文摘According to the characteristics of the large time delay,nonlinearity and the great inertia of temperature control system in biomass pyrolysis reactor,a two-degree-of-freedom Smith internal model controller based on fuzzy control is proposed.Firstly,the mathematical model of the temperature control system is established by using the step response method,and then the two-degree-of-freedom Smith internal model controller is designed,and the good tracking performance and disturbance suppression performance can be obtained by designing the set value tracking controller and interference rejection capability.Secondly,the fuzzy control algorithm is used to realize the on-line tuning of the control parameters of the two-degree-of-freedom Smith internal model algorithm.The simulation results show that,compared with the traditional internal model control,fuzzy internal model PID control and two-degree-of-freedom Smith internal model control,the algorithm proposed in this paper improves the influence of lag time on the control system,realizes the separation control of set point tracking and anti-jamming performance and the self-tuning of control parameters,and improves the control performance of the system.
文摘This work concerns the study of problems relating to the adaptive internal model control of DC motor in both cases conventional and neural. The most important aspects of design building blocks of adaptive internal model control are the choice of architectures, learning algorithms, and examples of learning. The choice of parametric adaptation algorithm for updating elements of the conventional adaptive internal model control shows limitations. To overcome these limitations, we chose the architectures of neural networks deduced from the conventional models and the Levenberg-marquardt during the adjustment of system parameters of the adaptive neural internal model control. The results of this latest control showed compensation for disturbance, good trajectory tracking performance and system stability.
文摘For a gantry crane system, this paper presents a comparison between four control algorithms. These algo-rithms are being compared on simplicity, stability and robustness. Goal for the controller is to move the load on a gantry crane to a new position with minimal overshoot of the load and maximal speed of the load. An-other goal is to provide an insight in the behaviour of the possible controllers. In this article a parallel P-controller, cascade P-controller, fuzzy controller and an internal model controller are used. To be able to validate and design the controllers a model is derived from the gantry crane. The controllers and the model are being implemented in Matlab Simulink. Finally the controllers are validated and tuned in Labview on a laboratory gantry scrane scale model. Main conclusion is that all presented controllers can be used as a con-troller for the gantry crane system but the fuzzy controller is showing the best performance.
基金Aeronautical Science Foundation of China(20080852011,20070852009)
文摘This article proposes a new inner attitude integration algorithm to improve attitude accuracy of the strapdown inertial attitude and heading reference system (SIAHRS) , which, by means of a Kalman filter, integrates the calculated attitude from the accelerometers in inertial measuring unit (IMU) , called damping attitudes, with those from the conventional IMU. As vehicle' s acceleration could produce damping attitude errors, the horizontal outputs from accelerometers are firstly used to judge the vehicle' s motion so as to determine whether the damping attitudes could be reasonably applied. This article also analyzes the limitation of this approach. Furthermore, it suggests a residual chi-square test to judge the validity of damping attitude measurement in real time, and accordingly puts forward proper information fusion strategy. Finally,the effectiveness of the proposed algorithm is proved through the experiments on a real system in dynamic and static states.
文摘By analyzing the internal features of counting sorting algorithm. Two improvements of counting sorting algorithms are proposed, which have a wide range of applications and better efficiency than the original counting sort while maintaining the original stability. Compared with the original counting sort, it has a wider scope of application and better time and space efficiency. In addition, the accuracy of the above conclusions can be proved by a large amount of experimental data.
文摘Improved picture quality is critical to the effectiveness of object recog-nition and tracking.The consistency of those photos is impacted by night-video systems because the contrast between high-profile items and different atmospheric conditions,such as mist,fog,dust etc.The pictures then shift in intensity,colour,polarity and consistency.A general challenge for computer vision analyses lies in the horrid appearance of night images in arbitrary illumination and ambient envir-onments.In recent years,target recognition techniques focused on deep learning and machine learning have become standard algorithms for object detection with the exponential growth of computer performance capabilities.However,the iden-tification of objects in the night world also poses further problems because of the distorted backdrop and dim light.The Correlation aware LSTM based YOLO(You Look Only Once)classifier method for exact object recognition and deter-mining its properties under night vision was a major inspiration for this work.In order to create virtual target sets similar to daily environments,we employ night images as inputs;and to obtain high enhanced image using histogram based enhancement and iterative wienerfilter for removing the noise in the image.The process of the feature extraction and feature selection was done for electing the potential features using the Adaptive internal linear embedding(AILE)and uplift linear discriminant analysis(ULDA).The region of interest mask can be segmen-ted using the Recurrent-Phase Level set Segmentation.Finally,we use deep con-volution feature fusion and region of interest pooling to integrate the presently extremely sophisticated quicker Long short term memory based(LSTM)with YOLO method for object tracking system.A range of experimentalfindings demonstrate that our technique achieves high average accuracy with a precision of 99.7%for object detection of SSAN datasets that is considerably more than that of the other standard object detection mechanism.Our approach may therefore satisfy the true demands of night scene target detection applications.We very much believe that our method will help future research.