An inverse model is used to infer the circulation in Prydz Bay and its adjacent open ocean using hydrographic data obtained by the cruise of the 7th Chinese National Antarctic Research Expedition (CHINARE-7), 1990/91....An inverse model is used to infer the circulation in Prydz Bay and its adjacent open ocean using hydrographic data obtained by the cruise of the 7th Chinese National Antarctic Research Expedition (CHINARE-7), 1990/91. Barotropie components are found to be strong in the study area, esp. at the Antarctic Divergence, and from a whole view, the velocity is rather small. In the open ocean, the flow is quasizonal, but outside the bay it shows a tendency of pressing onto the shelf from surface to bottom, and a feature of intensification just east of Fram Bank. We suggest here be the most important place to detect the possibility of the Antarctic Bottom Water formation. The meridional profiles of the distribution indicate a strong (relative to the ambient) core and a slope-trapped part into the bargain. In the southeastern part of the bay, there seems to exist a strong coastal current flowing westward. The computed upwelling centers are mainly situated in the west of the study region, as agrees quite well展开更多
Searching for rare astronomical objects based on spectral data is similar to finding needles in a haystack owing to their rarity and the immense data volume gathered from large astronomical spectroscopic surveys.In th...Searching for rare astronomical objects based on spectral data is similar to finding needles in a haystack owing to their rarity and the immense data volume gathered from large astronomical spectroscopic surveys.In this paper,we propose a novel automated approximate nearest neighbor search method based on unsupervised hashing learning for rare spectra retrieval.The proposed method employs a multilayer neural network using autoencoders as the local compact feature extractors.Autoencoders are trained with a non-gradient learning algorithm with graph Laplace regularization.This algorithm also simplifies the tuning of network architecture hyperparameters and the learning control hyperparameters.Meanwhile,the graph Laplace regularization can enhance the robustness by reducing the sensibility to noise.The proposed model is data-driven;thus,it can be viewed as a general-purpose retrieval model.The proposed model is evaluated in experiments and real-world applications where rare Otype stars and their subclass are retrieved from the dataset obtained from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope(Guo Shoujing Telescope).The experimental and application results show that the proposed model outperformed the baseline methods,demonstrating the effectiveness of the proposed method in rare spectra retrieval tasks.展开更多
In the present paper, the authors announce a newlyproved theorem of theirs. This theorem is of principal significance to numerical computation of solutions of variational equations.
The authors announce a newly proved theorem of theirs. This theorem is of principal significance to numerical computation of operator equations of the first kind.
In this paper, two theorems are proved for zero cost function (or precise I/O mapping) training algorithms about three-layered feedforward neural networks. Two training algorithms based on Moore-Penrose pseudoinverse ...In this paper, two theorems are proved for zero cost function (or precise I/O mapping) training algorithms about three-layered feedforward neural networks. Two training algorithms based on Moore-Penrose pseudoinverse (MPPI) matris together with corresponding structure design guidelines are also proposed.展开更多
To reduce the risk of infection in medical personnel working in infectious-disease areas, we proposed ahyper-redundant mobile medical manipulator (HRMMM) to perform contact tasks in place of healthcare workers.A kinem...To reduce the risk of infection in medical personnel working in infectious-disease areas, we proposed ahyper-redundant mobile medical manipulator (HRMMM) to perform contact tasks in place of healthcare workers.A kinematics-based tracking algorithm was designed to obtain highly accurate pose tracking. A kinematic modelof the HRMMM was established and its global Jacobian matrix was deduced. An expression of the trackingerror based on the Rodrigues rotation formula was designed, and the relationship between tracking errors andgripper velocities was derived to ensure accurate object tracking. Considering the input constraints of the physicalsystem, a joint-constraint model of the HRMMM was established, and the variable-substitution method was usedto transform asymmetric constraints to symmetric constraints. All constraints were normalized by dividing bytheir maximum values. A hybrid controller based on pseudo-inverse (PI) and quadratic programming (QP) wasdesigned to satisfy the real-time motion-control requirements in medical events. The PI method was used whenthere was no input saturation, and the QP method was used when saturation occurred. A quadratic performanceindex was designed to ensure smooth switching between PI and QP. The simulation results showed that theHRMMM could approach the target pose with a smooth motion trajectory, while meeting different types of inputconstraints.展开更多
文摘An inverse model is used to infer the circulation in Prydz Bay and its adjacent open ocean using hydrographic data obtained by the cruise of the 7th Chinese National Antarctic Research Expedition (CHINARE-7), 1990/91. Barotropie components are found to be strong in the study area, esp. at the Antarctic Divergence, and from a whole view, the velocity is rather small. In the open ocean, the flow is quasizonal, but outside the bay it shows a tendency of pressing onto the shelf from surface to bottom, and a feature of intensification just east of Fram Bank. We suggest here be the most important place to detect the possibility of the Antarctic Bottom Water formation. The meridional profiles of the distribution indicate a strong (relative to the ambient) core and a slope-trapped part into the bargain. In the southeastern part of the bay, there seems to exist a strong coastal current flowing westward. The computed upwelling centers are mainly situated in the west of the study region, as agrees quite well
基金supported by the Postdoctoral Science Foundation of China(Grant No.2020M682348)the Key Research Foundation of Henan Higher Education Institutions(Grant No.21A520002)+1 种基金the National Key Research and Development Program of China(Grant No.2018AAA0100203)the Joint Research Fund in Astronomy(Grant No.U1531242)under a cooperative agreement between the National Natural Science Foundation of China and the Chinese Academy of Sciences(CAS)。
文摘Searching for rare astronomical objects based on spectral data is similar to finding needles in a haystack owing to their rarity and the immense data volume gathered from large astronomical spectroscopic surveys.In this paper,we propose a novel automated approximate nearest neighbor search method based on unsupervised hashing learning for rare spectra retrieval.The proposed method employs a multilayer neural network using autoencoders as the local compact feature extractors.Autoencoders are trained with a non-gradient learning algorithm with graph Laplace regularization.This algorithm also simplifies the tuning of network architecture hyperparameters and the learning control hyperparameters.Meanwhile,the graph Laplace regularization can enhance the robustness by reducing the sensibility to noise.The proposed model is data-driven;thus,it can be viewed as a general-purpose retrieval model.The proposed model is evaluated in experiments and real-world applications where rare Otype stars and their subclass are retrieved from the dataset obtained from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope(Guo Shoujing Telescope).The experimental and application results show that the proposed model outperformed the baseline methods,demonstrating the effectiveness of the proposed method in rare spectra retrieval tasks.
文摘In the present paper, the authors announce a newlyproved theorem of theirs. This theorem is of principal significance to numerical computation of solutions of variational equations.
文摘The authors announce a newly proved theorem of theirs. This theorem is of principal significance to numerical computation of operator equations of the first kind.
文摘In this paper, two theorems are proved for zero cost function (or precise I/O mapping) training algorithms about three-layered feedforward neural networks. Two training algorithms based on Moore-Penrose pseudoinverse (MPPI) matris together with corresponding structure design guidelines are also proposed.
基金the National Natural Science Foundation of China(No.52175103)。
文摘To reduce the risk of infection in medical personnel working in infectious-disease areas, we proposed ahyper-redundant mobile medical manipulator (HRMMM) to perform contact tasks in place of healthcare workers.A kinematics-based tracking algorithm was designed to obtain highly accurate pose tracking. A kinematic modelof the HRMMM was established and its global Jacobian matrix was deduced. An expression of the trackingerror based on the Rodrigues rotation formula was designed, and the relationship between tracking errors andgripper velocities was derived to ensure accurate object tracking. Considering the input constraints of the physicalsystem, a joint-constraint model of the HRMMM was established, and the variable-substitution method was usedto transform asymmetric constraints to symmetric constraints. All constraints were normalized by dividing bytheir maximum values. A hybrid controller based on pseudo-inverse (PI) and quadratic programming (QP) wasdesigned to satisfy the real-time motion-control requirements in medical events. The PI method was used whenthere was no input saturation, and the QP method was used when saturation occurred. A quadratic performanceindex was designed to ensure smooth switching between PI and QP. The simulation results showed that theHRMMM could approach the target pose with a smooth motion trajectory, while meeting different types of inputconstraints.
