A new discriminant subspace analysis approach for multi-class problems

Fukunaga–Koontz Transform (FKT) is a famous feature extraction method in statistical pattern recognition, which aims to find a set of vectors that have the best representative power for one class while the poorest representative power for the other class. Li and Savvides [1] propose a one-against-all strategy to deal with multi-class problems, in which the two-class FKT method can be directly applied to find the presentative vectors of each class. Motivated by the FKT method, in this paper we propose a new discriminant subspace analysis (DSA) method for the multi-class feature extraction problems. To solve DSA, we propose an iterative algorithm for the joint diagonalization (JD) problem. Finally, we generalize the linear DSA method to handle nonlinear feature extraction problems via the kernel trick. To demonstrate the effectiveness of the proposed method for pattern recognition problems, we conduct extensive experiments on real data sets and show that the proposed method outperforms most commonly used feature extraction methods.     

电纺纳米纤维在食品分析中的应用

电纺纳米纤维因具有快速的吸/脱附特性和较高的吸/脱附效率等独特优势,近年来被广泛用于食品分析检测。本文简述了纳米纤维特性及静电纺丝技术,重点综述了电纺纳米纤维在食品分析检测中的应用,其中着重对聚苯乙烯(PS)、尼龙6等单组份电纺纳米纤维以及聚冠醚/聚苯乙烯(PCE-PS)等混合组份纳米纤维在食品分析中的应用进展做了阐述,同时对其他一些纳米材料如纳米晶簇、碳纳米管、石墨烯、磁性纳米粒子、纳米金属氧化物、量子点在食品分析检测中的某些最新研究成果和应用做了简要介绍;此外还展示了一些纳米纤维固相萃取器件和装置,并对其做了简要说明;最后对电纺纳米纤维在食品分析检测中的应用作了总结和展望。     

A new approach for optimization of electrospun nanofiber formation process

Precise control of fiber diameter during electrospinning is very crucial for many applications. A systematic and quantitative study on the effects of processing variables enables us to control the properties of electrospun nanofibers. In this contribution, response surface methodology (RSM) was employed to quantitatively investigate the simultaneous effects of four of the most important parameters, namely solution concentration (C), spinning distance (d), applied voltage (V) and volume flow rate (Q), on mean fiber diameter (MFD) as well as standard deviation of fiber diameter (StdFD) in electrospinning of polyvinyl alcohol (PVA) nanofibers.