Empirical Study of ＂Double Threshold＂ Modified Model on New Product Diffusion

The innovations actually diffuse among social network nowadays.Individual heterogeneity,interactions between individuals and network topology influence a lot.We established a "double threshold" modified model and took the number of neighbors,neighbors' adoption and the cost-benefit parameters as crucial influencing factors.The diffusion of DaLingTong(CDMA450)products in MeiShan city of SiChuan province during 2004 to 2007 has been used to verity the model on Matlab.The validation results fit the actual diffusion pattern of DaLingTong(CDMA450) products very well.The results indicate that there exists a "tipping point(threshold)" in the process of innovation diffusion.If the initial adoption quantity is larger than the tipping point,then the product will spread to a large portion of people,otherwise is will collapse to zero.The model can effectively predict the diffusion of new products,and can influence the diffusion process by changing the value of the parameters.

Low Speed Bearing Fault Diagnosis Based on EMD-CIIT Histogram Entropy and KFCM Clustering

In view of weak defect signals and large acoustic emission(AE) data in low speed bearing condition monitoring, we propose a bearing fault diagnosis technique based on a combination of empirical mode decomposition(EMD), clear iterative interval threshold(CIIT) and the kernel-based fuzzy c-means(KFCM) eigenvalue extraction. In this technique, we use EMD-CIIT and EMD to complete the noise removal and to extract the intrinsic mode functions(IMFs). Then we select the first three IMFs and calculate their histogram entropies as the main fault features. These features are used for bearing fault classification using KFCM technique. The result shows that the combined EMD-CIIT and KFCM algorithm can accurately identify various bearing faults based on AE signals acquired from a low speed bearing test rig.