In order to solve the scheduling optimization problem in the process-oriented food production and processing finished goods area, this paper proposes an improved wolf pack algorithm to solve the problem and obtain smaller completion time by optimizing the order loading sequence of the finished food production area. A backward learning strategy is used to construct a higher quality initial population, and the ability to jump out of local extremes is enhanced by adding a simulated annealing algorithm, which results in better overall convergence performance and higher stability of the algorithm. The effectiveness of the solution method is proved through simulation experiments, and the operation plan that can improve the production efficiency and meet the production scheduling requirements of process-oriented production enterprises is given under the premise of ensuring the production operation of enterprises.
School-based training is a continuing education way to train all the teachers in the school based on the school as a basic unit where teachers work, for the purpose of improving teaching ability of the teachers, and by means of teaching and research activities. School-based training is meant for: possession of modern educational idea, the active implementation of research exploitation, the establishment of life-learning idea and a strong subject consciousness. The strategies of school-based training are as follows: headmasters are designer and manager of school-based training; school-based training should be guided by experts on education outside school; school-based training should be closely linked with task study; organizations and systems related to school-based training of teachers should be established so that school-based training of teachers in primary and middle schools can be put into systematic orbit step by step.
Temperature-humidity (TH) induced failure mechanism (FM) of metal contacting interfaces in integrated circuit (IC) systems has played a significant role in system reliability issues. This paper focuses on central processing unit (CPU)/motherboard interfaces and studies several factors that are believed to have a great impact on TH performance. They include: Enabling load, surface finish quality, and contacting area. Test vehicles (TVs) of Clarkdale package and of Ibex peak motherboard were designed to measure low level contact resistance (LLCR) for catching any failure. Several sets of design of experiments (DOE) were conducted on 85°C/85% relative humidity and test results were analyzed. A proposal that correlates asperity spots and contact tip design with contact resistance was proposed and thus a cost-effective solution for improving electrical performance under TH was deduced. The proposal has proven to be reasonably effective in practice.
With fast development of science and technology, People gradually need more and more information, causing signicant pressure on the sampling. The sampling rate must be two times higher than the highest frequency of the signal based on Nyquist sampling theorem. Compressed Sensing (CS) employs a special sampling method which can capture and represent compressible signals at a rate signicantly below the Nyquist rate. It can relieve the pressure of sampling process in Wireless Sensor Networks. And a cooperative self-localization method based on probability for wireless sensor networks is proposed. The method rstly estimates the initial Position of the located node based on the joint Probability density function of the distance between the located node and the connected reference nodes. Further, based on the renement principle, a cooperative localization method is studied by making the best of the neighbour nodes and giving the neighbour nodes some condence. The method improves the estimation accuracy as well as makes more unknown nodes to be located.
Abstract In view of the shortcomings of current multi-robot path planning strategies, such as high path coupling, long total path, and long waiting time for collision avoidance, as well as the resulting problems of low system robustness and low robot utilization, the paper proposes Multi-robot path planning particle swarm algorithm based on distributed three-dimensional space-time graphics and motion decomposition. We first generate a dynamic temporary obstacle in the time dimension according to the existing path set and the current robot position, and expand it together with the static obstacle into a three-dimensional search graphics space. Secondly, in the three-dimensional image space, the total path movement time is divided into three parameters: movement time, turning time and staying time in place, and using the conditional depth-first search strategy to calculate all the matching parameters from the starting node to the target node the required path collection. The experimental results show that the path of distributed 3D graphics planning by our proposed particle swarm algorithm has the advantages of total length, less running time, system collision-free, and high robustness, which solves the problem of multi-robot systems completing continuous random tasks.
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