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The particle concentration distribution in the foundry is very important not only for the occupational health of foundry workers but also for creating green foundry industry. In this study, the authors measured the particle concentration distribution in a foundry workshop, and analysis the characteristics of foundry dust pollution with the consideration of total dust control in the recent foundry industry. The results show that the concentrations of PM10 and PM2.5 are high in the central and low in the ends of the workshop. It is about 54% of all test sites with higher concentration of PM10 and PM2.5 than the limit values of national standards. However, the PM4 concentrations of about 31% test sites are higher than limit of national standards. It is obviously that sandfilling process, cavity repair and sweeping in mold making process can produce a lot of dust. This study may provide guidance for the foundry pollution control engineering and workshop operation management system.

a low surface energy coating with a long chain fluorine siloxane is prepared, and the performance in anti-freezing adhesive is studied. It is determined that the optimum proportion of (Heptadecafluoro-1,1,2,2-tetradecyl) trimethoxysilane (FAS) and SiO2 nanopowder are 1.1% and 1.6%,respectively. the times of coating bear pendulum impact is least in this proportion. the conclusion is that bionic superhydrophobic coating plays a certain guiding role on solving material surface frozen sticky problem.

The purpose of this paper is to improve the efficiency of the Gene Expression Programming (GEP) algorithm. The GEP algorithm is an evolutionary computation. It inherits the characteristics of Genetic Algorithm and Genetic Programming. Through its own characteristics, the GEP algorithm can get the optimal solution of the complicated problem. So, the GEP algorithm has achieved good results in many areas. However, there are also some inevitable drawbacks about the GEP algorithm itself. This paper proposes 5 deficiencies aspects of the GEP algorithm (expression meaning, fitness calculation, local convergence, variable selection, genetic operations, selection of genetic operation rates), and gives the corresponding solutions.

This paper proposed a method to detect the defects of keyboard characters. The work, which is a part of the keyboard inspection system, integrates two key technologies to realize the recognition function. First, Feature extraction is applied to select the best properties of the keyboard characters to distinguish the difference and six features are chosen. Second, we integrate support vector machine (SVM) into the classification method and the radial basis kernel function is used to map the training data into higher dimensional space to facilitate the classification. We get a satisfied result in the classification finally which demonstrate the proposed approach is effective.

Accompany with fast development of location technology, more and more trajectories datasets are collected on the real applications. So it is something of value in the theory and applied research to mine the clusters from these datasets. In this paper, a trajectory clustering algorithm, called Density-Based Spatial Clustering of Application with noise (Tra-DBSCAN for short), based on DBSCAN that is a classic clustering algorithm. In this framework, each trajectory firstly partitions into sub-trajectories as clustering object, and then line hausdorff distance is used to measure the distance between two sub-trajectories. Next, DBSCAN is introduced to cluster sub-trajectory to form cluster area, and then connecting different moments of clustering area is regarded as trajectory movement patterns. Finally, the experimental results show our framework’s effective.