A reaction-diffusion model for a single species with age structure and nonlocal reaction for periodic time t is derived. Some results about the model with monotone birth function are firstly introduced, and then by co...A reaction-diffusion model for a single species with age structure and nonlocal reaction for periodic time t is derived. Some results about the model with monotone birth function are firstly introduced, and then by constructing two auxiliary equations and squeezing method, the spreading speed for the system with nonmonotone birth function is obtained.展开更多
A simple method is proposed to optimize the thickness parameter of the boundary layer of the saturation function in the Complementary Sliding Mode Control (CSMC). A pair of complementary sliding surfaces are construct...A simple method is proposed to optimize the thickness parameter of the boundary layer of the saturation function in the Complementary Sliding Mode Control (CSMC). A pair of complementary sliding surfaces are constructed. And the Taylor series is used to estimate the steady state error of CSMC system to optimize the parameter value for the boundary layer of the saturation function without artificial settings. This proposed CSMC strategy is applied to the speed regulation in permanent magnet synchronous motor with lump uncertainties. The experimental results show that the proposed CSMC strategy can obtain an optimal value for the boundary layer parameter effectively suppressing the chattering and keep an excellent system performance.展开更多
Purpose: A novel image-based method for speed of sound (SoS) estimation is proposed and experimentally validated on a tissue-mimicking ultrasound phantom and normal human liver in vivo using linear and curved array tr...Purpose: A novel image-based method for speed of sound (SoS) estimation is proposed and experimentally validated on a tissue-mimicking ultrasound phantom and normal human liver in vivo using linear and curved array transducers. Methods: When the beamforming SoS settings are adjusted to match the real tissue’s SoS, the ultrasound image at regions of interest will be in focus and the image quality will be optimal. Based on this principle, both a tissue-mimicking ultrasound phantom and normal human liver in vivo were used in this study. Ultrasound image was acquired using different SoS settings in beamforming channels ranging from 1420 m/sec to 1600 m/sec. Two regions of interest (ROIs) were selected. One was in a fully developed speckle region, while the other contained specular reflectors. We evaluated the image quality of these two ROIs in images acquired at different SoS settings in beamforming channels by using the normalized autocorrelation function (ACF) of the image data. The values of the normalized ACF at a specific lag as a function of the SoS setting were computed. Subsequently, the soft tissue’s SoS was determined from the SoS setting at the minimum value of the normalized ACF. Results: The value of the ACF as a function of the SoS setting can be computed for phantom and human liver images. SoS in soft tissue can be determined from the SoS setting at the minimum value of the normalized ACF. The estimation results show that the SoS of the tissue-mimicking phantom is 1460 m/sec, which is consistent with the phantom manufacturer’s specification, and the SoS of the normal human liver is 1540 m/sec, which is within the range of the SoS in a healthy human liver in vivo. Conclusion: Soft tissue’s SoS can be determined by analyzing the normalized ACF of ultrasound images. The method is based on searching for a minimum of the normalized ACF of ultrasound image data with a specific lag among different SoS settings in beamforming channels.展开更多
基金Supported by the NSF of China(11171120)Supported by the Doctoral Program of Higher Education of China(20094407110001)Supported by the NSF of Guangdong Province(10151063101000003)
文摘A reaction-diffusion model for a single species with age structure and nonlocal reaction for periodic time t is derived. Some results about the model with monotone birth function are firstly introduced, and then by constructing two auxiliary equations and squeezing method, the spreading speed for the system with nonmonotone birth function is obtained.
基金Sponsored by the National Natural Science Foundation of China(Grant No.61174051)the Natural Science Foundation of Fujian Province(Grant No.2017J05101)the Technology Project of Fujian Province(Grant No.2019H0007)
文摘A simple method is proposed to optimize the thickness parameter of the boundary layer of the saturation function in the Complementary Sliding Mode Control (CSMC). A pair of complementary sliding surfaces are constructed. And the Taylor series is used to estimate the steady state error of CSMC system to optimize the parameter value for the boundary layer of the saturation function without artificial settings. This proposed CSMC strategy is applied to the speed regulation in permanent magnet synchronous motor with lump uncertainties. The experimental results show that the proposed CSMC strategy can obtain an optimal value for the boundary layer parameter effectively suppressing the chattering and keep an excellent system performance.
文摘Purpose: A novel image-based method for speed of sound (SoS) estimation is proposed and experimentally validated on a tissue-mimicking ultrasound phantom and normal human liver in vivo using linear and curved array transducers. Methods: When the beamforming SoS settings are adjusted to match the real tissue’s SoS, the ultrasound image at regions of interest will be in focus and the image quality will be optimal. Based on this principle, both a tissue-mimicking ultrasound phantom and normal human liver in vivo were used in this study. Ultrasound image was acquired using different SoS settings in beamforming channels ranging from 1420 m/sec to 1600 m/sec. Two regions of interest (ROIs) were selected. One was in a fully developed speckle region, while the other contained specular reflectors. We evaluated the image quality of these two ROIs in images acquired at different SoS settings in beamforming channels by using the normalized autocorrelation function (ACF) of the image data. The values of the normalized ACF at a specific lag as a function of the SoS setting were computed. Subsequently, the soft tissue’s SoS was determined from the SoS setting at the minimum value of the normalized ACF. Results: The value of the ACF as a function of the SoS setting can be computed for phantom and human liver images. SoS in soft tissue can be determined from the SoS setting at the minimum value of the normalized ACF. The estimation results show that the SoS of the tissue-mimicking phantom is 1460 m/sec, which is consistent with the phantom manufacturer’s specification, and the SoS of the normal human liver is 1540 m/sec, which is within the range of the SoS in a healthy human liver in vivo. Conclusion: Soft tissue’s SoS can be determined by analyzing the normalized ACF of ultrasound images. The method is based on searching for a minimum of the normalized ACF of ultrasound image data with a specific lag among different SoS settings in beamforming channels.
