An index structure supporting rule activation in pervasive applications

World Wide Web - Rule mechanism has been widely used in many areas, such as databases, artificial intelligent and pervasive computing. In a rule mechanism, rule activation decides which rules are...     

Characterizations of friction welding joint interface for AISI 316

Because of heat amount is different from peripheral to central of friction welding interface, which is leaded to vary the characterizations along that interface. Current study, respectively, focused on the effect of different friction pressure on micro-structural and mechanical properties of that friction welding joint interface. Presently, these friction pressures are 110, 130, 150 and 170 MPa while kept all other conditions constant. The effects of different friction pressure on welding interface characterization were investigated by EDX, SEM, tensile, compression, impact and hardness tests. The tensile tests carried out on the standardized test piece with diameter 6 mm and 8 mm, thus, compression tests were extracted from the positions of 0°, 45° 90° with test specimen of 4 mm diameter and 6.5 mm length at weld center. Whereas, the impact test pieces were picked up in two positions, the first one is symmetrical, which it obtained to the respect of the rotation axis and the interface, on the other hand, the second one is non-symmetrical with the axis of rotation and symmetrical to the interface, for making the notch head coincide with the center of the welded joint, The obtained results showed that with reducing of friction pressure will present lack of bonding increasing from peripheral toward the welding center, which will responsible on reducing of the mechanical properties such as tensile, compression and impact strength.     

蛋类礼盒包装结构的缓冲性能研究

目的研究蛋类礼盒包装结构的缓冲性能。方法以蛋类尺寸为基础,建立可发性聚乙烯(expandable polyethylene. EPE)缓冲单元结构和组合结构,进行静态仿真分析和实验验证,比较结构在形状、叠合层数、组合形式等参数变化时的载荷与位移。结果结构层数变化相同时,单元结构的极限载荷从143N增加到236 N,组合结构的极限载荷从224 N增加到476 N,均呈近线性增长。结论蛋类礼盒包装中,组合结构的承载能力优于单元结构,通过单元结构的组合,可满足不同蛋类的包装要求。     

Reconstructing gene regulatory networks with a memetic-neural hybrid based on fuzzy cognitive maps

Reconstructing gene regulatory networks (GRNs) plays an important role in identifying the complicated regulatory relationships, uncovering regulatory patterns in cells, and gaining a systematic view for biological processes. In order to reconstruct large-scale GRNs accurately, in this paper, we first use fuzzy cognitive maps (FCMs), which are a kind of cognition fuzzy influence graphs based on fuzzy logic and neural networks, to model GRNs. Then, a novel hybrid method is proposed to reconstruct GRNs from time series expression profiles using memetic algorithm (MA) combined with neural network (NN), which is labeled as MANN_FCM-GRN. In MANN_FCM-GRN, the MA is used to determine regulatory connections in GRNs and the NN is used to determine the interaction strength of the regulatory connections. In the experiments, the performance of MANN_FCM-GRN is validated on both synthetic data and the benchmark dataset DREAM3 and DREAM4. The experimental results demonstrate the efficacy of MANN_FCM-GRN and show that MANN_FCM-GRN can reconstruct GRNs with high accuracy without expert knowledge. The comparison with existing algorithms also shows that MANN_FCM-GRN outperforms ant colony optimization, non-linear Hebbian learning, and real-coded genetic algorithms.

     

MPE: a mobility pattern embedding model for predicting next locations

World Wide Web - The wide spread use of positioning and photographing devices gives rise to a deluge of traffic trajectory data (e.g., vehicle passage records and taxi trajectory data), with each...