This paper presents a quantum-behaved neurodynamic swarm optimization approach to solve the nonconvex optimization problems with inequality constraints. Firstly, the general constrained optimization problem is addressed and a high-performance feedback neural network for solving convex nonlinear programming problems is introduced. The convergence of the proposed neural network is also proved. Then, combined with the quantum-behaved particle swarm method, a quantum-behaved neurodynamic swarm optimization (QNSO) approach is presented. Finally, the performance of the proposed QNSO algorithm is evaluated through two function tests and three applications including the hollow transmission shaft, heat exchangers and crank–rocker mechanism. Numerical simulations are also provided to verify the advantages of our method.
The wheeled mobile robot has been widely used in various fields nowadays. Combining with a contest of mobile robot used for sorting and conveying objects, this paper designed a non-tracking wheeled mobile robot, which can move according to a reasonable route planned beforehand. First, the overall schematic design of mobile robot was introduced. Then the mechanical design and the circuit system design were discussed in detail. Last, the strategy of sorting and conveying was studied, and the innovative rotary-wheel mechanism can greatly simplify the sorting and conveying strategy. Through experiment verified, the proposed wheeled mobile robot can quickly achieve sorting and conveying according to preplanned paths.
Background As an important treatment for the treatment of kidney disease, peritoneal dialysis has been widely studied and applied due to its low cost and easy operation. Given that chronic kidney disease is growing globally, peritoneal dialysis is receiving increasing attention. With the development and popularization of mobile network technology, mobile telematics began to become a mainstream trend. The emergence of mobile telemedicine system is an important result of applying the universal computing concept to medical purposes. However, as users are not familiar with the medical field, telemedicine technology depends to a large extent on the patient's acceptance of the use of them.Methods By integrating the experience of clinicians, the remote diagnosis and treatment system of peritoneal dialysis developed by Shenzhen Traditional Chinese Medicine Hospital can monitor the whole course of peritoneal dialysis data of patients. We used statistical methods to empirically analyze the peritoneal dialysis data. By exploring data over a standard duration of time, the filtration rate per minute of the peritoneal dialysis patients using a 1.5% low-calcium peritoneal solution was reduced over time and had a power function relationship which can help to remind incorrect data. The linear equation can be obtained by least square regression of the data after the time of peritoneal effusion and the weight of the effluent deformed.Results The least squares method was used to regress the patient's peritoneal dialysis data (logarithm of peritoneal dialysis time and filtration rate per minute), and the regression equation R square was equal to 0.95. The regression coefficient passed the T test and the regression equation fits well. According to the result parameters of the regression equation, we calculated the standard range of filtration rate for each peritoneal dialysis. Taking 441 cases of a random patient as an example, 438 cases of diafiltration rate met the standard range. 3 cases were filtered out below the standard.Conclusions The system can inform the patients of the results according to the confidence interval of the regression prediction, which greatly strengthens the interaction of the system and increases the patients' compliance.
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