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In this paper, we modify the classical cubic B-spline quasi-interpolant Q 3 by utilizing multi-node higher-order expansions and the P t -exact A-discretization approach. The proposed quartic spline quasi-interpolant Q 3 1 possesses higher accuracy with small computational complexity increased, while requires no additional information of the target function. Applying the proposed quasi-interpolant, we develop high accuracy quadrature formulas and the differentiation matrices. All corresponding error estimates with explicit coefficients are provided. Numerical experiments illustrate the effectiveness of the proposed quasi-interpolants. [ABSTRACT FROM AUTHOR]

For a new project, it is impossible to get a reliable prediction model because of the lack of sufficient training data. To solve the problem, researchers proposed cross-project defect prediction (CPDP). For CPDP, most researchers focus on how to reduce the distribution difference between training data and test data, and ignore the impact of class imbalance on prediction performance. This paper proposes a hybrid multiple models transfer approach (HMMTA) for cross-project software defect prediction. First, several instances that are most similar to each target project instance are selected from all source projects to form the training data. Second, the same number of instances as that of the defected class are randomly selected from all the non-defect class in each iteration. Next, instances selected from the non-defect classes and all defected class instances are combined to form the training data. Third, the transfer learning method called ETrAdaBoost is used to iteratively construct multiple prediction models. Finally, the prediction models obtained from multiple iterations are integrated by the ensemble learning method to obtain the final prediction model. We evaluate our approach on 53 projects from AEEEM, PROMISE, SOFTLAB and ReLink four defect repositories, and compare it with 10 baseline CPDP approaches. The experimental results show that the prediction performance of our approach significantly outperforms the state-of-the-art CPDP methods. Besides, we also find that our approach has the comparable prediction performance as within-project defect prediction (WPDP) approaches. These experimental results demonstrate the effectiveness of HMMTA approach for CPDP. [ABSTRACT FROM AUTHOR]

A novel alternating copolymer of sulfonated poly(ether ether ketone- alt-benzimidazole)s (SPEEK- alt-BI) was synthesized by polycondensation in our previous report. In this article, we examined the properties of SPEEK- alt-BI membranes, such as thermal and mechanical stability, hydrolysis, and swelling properties in water, and proton conductivities at various temperatures and humidity. The experimental results showed that SPEEK- alt-BI membranes exhibited promising oxidative and hydrolysis stabilities. Although the base moieties in SPEEK- alt-BI main chain would capture proton and form reversible salt hindering the proton transfer capability, the conductivity of membrane 60SPEEK- alt-BI-H [Sulfonation degree (S.D.), 60% in form of proton] could achieve 22.61 mS/cm at 80°C and 100% humidity. Meanwhile, the conductivity of membrane could reach 40.12 mS/cm with phosphorus acid doping. The methanol permeation coefficient of 60SPEEK- alt-BI membrane is 2.3 × 10−8 cm2/s at 20°C, which is magnitude lower than that of Nafion®117, 1.11 × 10−6 cm2/s. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2012 [ABSTRACT FROM AUTHOR]