This paper studies a federated edge learning system,in which an edge server coordinates a set of edge devices to train a shared machine learning(ML)model based on their locally distributed data samples.During the dist...This paper studies a federated edge learning system,in which an edge server coordinates a set of edge devices to train a shared machine learning(ML)model based on their locally distributed data samples.During the distributed training,we exploit the joint communication and computation design for improving the system energy efficiency,in which both the communication resource allocation for global ML-parameters aggregation and the computation resource allocation for locally updating ML-parameters are jointly optimized.In particular,we consider two transmission protocols for edge devices to upload ML-parameters to edge server,based on the non-orthogonal multiple access(NOMA)and time division multiple access(TDMA),respectively.Under both protocols,we minimize the total energy consumption at all edge devices over a particular finite training duration subject to a given training accuracy,by jointly optimizing the transmission power and rates at edge devices for uploading ML-parameters and their central processing unit(CPU)frequencies for local update.We propose efficient algorithms to solve the formulated energy minimization problems by using the techniques from convex optimization.Numerical results show that as compared to other benchmark schemes,our proposed joint communication and computation design significantly can improve the energy efficiency of the federated edge learning system,by properly balancing the energy tradeoff between communication and computation.展开更多
Objective： Fractures of the capitellum and trochlea constitute less than 1% of all elbow fractures and a shear fracture involving the capitellum and extending medially into most of the trochlea is rarely reported. Ty...Objective： Fractures of the capitellum and trochlea constitute less than 1% of all elbow fractures and a shear fracture involving the capitellum and extending medially into most of the trochlea is rarely reported. Type Ⅳ capitellum fracture is still controversial in regard to its ra- diographic appearance, surgical approach and osteosynthesis. We report 10 cases of type Ⅳ capitellum fracture with a view to elucidating its clinical features and treatment outcome. Methods： We treated 10 patients of type Ⅳ capitellum fracture with a mean age of 32 years. A uniform surgical approach and postoperative rehabilitation were followed. Results： Nine patients presented to us after a mean of 4 days of injury and one patient was nonunion after 6 months of injury who had been treated conservatively by a bone setter. Double arc sign was absent in 6 cases. Intraopera- tively 6 capitellotrochlear fragments were devoid of soft tissue attachments. By Mayo Elbow Performance Score evaluation, 7 patients got excellent, 2 good and 1 fair results. One patient with associated elbow dislocation developed heterotopic ossification. There was no case of avascular necrosis, osteoarthrosis or fixation failures. Conclusions： Type Ⅳ capitellum fractures are rare and belong to complex articular injuries. A good functional out- come can only be achieved with open reduction and stable internal fixation followed by early mobilization. Preopera- tive radiographic assessment and computed tomography help surgeons in choosing the right surgical approach and implants. Good surgical technique and stable internal fixa- tion are the keys to early mobilization and good functional outcome.展开更多
A new fault location method based on six-sequence fault components was developed for parallel lines based on the fault analysis of a joint parallel transmission line. In the six-sequence fault network, the ratio of ...A new fault location method based on six-sequence fault components was developed for parallel lines based on the fault analysis of a joint parallel transmission line. In the six-sequence fault network, the ratio of the root-mean square value of the fault current from two terminals is the function of the line imped- ance, the system impedance, and the fault distance away from the buses. A fault location equation is given to relate these factors. For extremely long transmission lines, the distributed capacitance is divided by the fault point and allocated to the two terminals of the transmission line in a lumped parameter to eliminate the influence of the distributed capacitance on the location accuracy. There is no limit on fault type and syn- chronization of the sampling data. Simulation results show that the location accuracy is high with an average error about 2%, and it is not influenced by factors such as the load current, the operating mode of the power system, or the fault resistance.展开更多
基金the National Key R&D Program of China under Grant 2018YFB1800800Guangdong Province Key Area R&D Program under Grant 2018B030338001the Natural Science Foundation of China under Grant U2001208。
文摘This paper studies a federated edge learning system,in which an edge server coordinates a set of edge devices to train a shared machine learning(ML)model based on their locally distributed data samples.During the distributed training,we exploit the joint communication and computation design for improving the system energy efficiency,in which both the communication resource allocation for global ML-parameters aggregation and the computation resource allocation for locally updating ML-parameters are jointly optimized.In particular,we consider two transmission protocols for edge devices to upload ML-parameters to edge server,based on the non-orthogonal multiple access(NOMA)and time division multiple access(TDMA),respectively.Under both protocols,we minimize the total energy consumption at all edge devices over a particular finite training duration subject to a given training accuracy,by jointly optimizing the transmission power and rates at edge devices for uploading ML-parameters and their central processing unit(CPU)frequencies for local update.We propose efficient algorithms to solve the formulated energy minimization problems by using the techniques from convex optimization.Numerical results show that as compared to other benchmark schemes,our proposed joint communication and computation design significantly can improve the energy efficiency of the federated edge learning system,by properly balancing the energy tradeoff between communication and computation.
文摘Objective： Fractures of the capitellum and trochlea constitute less than 1% of all elbow fractures and a shear fracture involving the capitellum and extending medially into most of the trochlea is rarely reported. Type Ⅳ capitellum fracture is still controversial in regard to its ra- diographic appearance, surgical approach and osteosynthesis. We report 10 cases of type Ⅳ capitellum fracture with a view to elucidating its clinical features and treatment outcome. Methods： We treated 10 patients of type Ⅳ capitellum fracture with a mean age of 32 years. A uniform surgical approach and postoperative rehabilitation were followed. Results： Nine patients presented to us after a mean of 4 days of injury and one patient was nonunion after 6 months of injury who had been treated conservatively by a bone setter. Double arc sign was absent in 6 cases. Intraopera- tively 6 capitellotrochlear fragments were devoid of soft tissue attachments. By Mayo Elbow Performance Score evaluation, 7 patients got excellent, 2 good and 1 fair results. One patient with associated elbow dislocation developed heterotopic ossification. There was no case of avascular necrosis, osteoarthrosis or fixation failures. Conclusions： Type Ⅳ capitellum fractures are rare and belong to complex articular injuries. A good functional out- come can only be achieved with open reduction and stable internal fixation followed by early mobilization. Preopera- tive radiographic assessment and computed tomography help surgeons in choosing the right surgical approach and implants. Good surgical technique and stable internal fixa- tion are the keys to early mobilization and good functional outcome.
文摘A new fault location method based on six-sequence fault components was developed for parallel lines based on the fault analysis of a joint parallel transmission line. In the six-sequence fault network, the ratio of the root-mean square value of the fault current from two terminals is the function of the line imped- ance, the system impedance, and the fault distance away from the buses. A fault location equation is given to relate these factors. For extremely long transmission lines, the distributed capacitance is divided by the fault point and allocated to the two terminals of the transmission line in a lumped parameter to eliminate the influence of the distributed capacitance on the location accuracy. There is no limit on fault type and syn- chronization of the sampling data. Simulation results show that the location accuracy is high with an average error about 2%, and it is not influenced by factors such as the load current, the operating mode of the power system, or the fault resistance.
