Studies have shown that influential nodes play an important role in all kinds of dynamic behavior in the complex network. Excavation or recognition of such nodes contributes to the development of application areas such as social network advertising and user interest recommendation. Although some heuristic algorithms such as degree, betweenness, closeness and k-shell (or k-core) can identify influential nodes at the same time, they are disadvantaged in terms of accuracy and time complexity. Based on this, the authors propose a novel local weight index to distinguish the node influence based on the theory of ties strength. This index emphasizes that the node influence is jointly decided by the quantity and quality of the neighbors, and its time complexity is much lower than closeness and betweenness. With the aid of SIR information transmission model, this paper verifies the validity of local weight index.
The printed circuit boards (PCBs) are the basis of all electrical and electronic equipment (EEE) and thus are one of the most important branches of WEEE stream. Present researches mainly concentrate on the processes of reusing noble metals and copper, and a great deal of nonmetals in PCBs are disposed by combustion or filling, which may cause secondary pollution and resource-wasting. So in this paper, we study how nonmetals are used to produce recycling boards through adding different adhesives, and obtain the best formulation and working conditions. The best formulation is that the binder is Polypropylene (less than 20%), additive are methenamine (little) and stearic acid (little). Effects of working conditions on the molding results are investigated. The results show that the optimum conditions for hydraulic pressure machine are the temperatures of 160 °C, warming and pressing time of 10 minutes and the press of 30MPa.
The compound Fill Sphere Model (cFSM), which is an extension of common Fill Sphere Model, is widely used in real-time haptic interaction with deformable body. Comparing with finite element based model, the simplicity and efficiency are advantages of cFSM. However, determining implicit parameters of cFSM is a difficult task since a vivid deformation should be attained during haptic interaction. In this paper, to improve the simulation precision, parameter matrices of the cFSM are identified through an analytical method for the first time to our best knowledge. After deriving parameter matrices by linearization, the stiffness matrix, damp matrix and mass matrix of the cFSM are obtained by minimizing errors between stiffness matrix of the Finite Element Model (FEM). In order to evaluate the performance of derived parameters, comparative experiment has been conducted between the cFSM and FEM. Additionally, based on the derived parameters, a real-time haptic interactive scenario is constructed to validate the performance of deformation simulation.
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