Efficient semiparametric estimation of time-censored intensity-reduction models for repairable systems

The rate reduction models have been widely used to model the recurrent failure data for their capabilities in quantifying the repair effects. Despite the widespread popularity, there have been limited studies on statistical inference of most failure rate reduction models. In view of this fact, this study proposes a semiparametric estimation...

SlimML: Removing Non- critical Input Data in Large-scale Iterative Machine Learning

The core of many large-scale machine learning (ML) applications, such as neural networks (NN), support vector machine (SVM), and convolutional neural network (CNN), is the training algorithm that iteratively updates model parameters by processing massive datasets. From a plethora of studies aiming at accelerating ML, being data...

Germanene on single-layer ZnSe substrate: Novel electronic and optical properties

In this work, the structural, electronic and optical properties of germanene and ZnSe substrate nanocomposites have been investigated using first-principles calculations. We found that the large direct-gap ZnSe semiconductors and zero-gap germanene form a typical orbital hybridization heterostructure with a strong binding energy, which shows...

Promoting sensitivity and selectivity of HCHO sensor based on strained InP₃ monolayer: A DFT study

Sensitive materials for formaldehyde (HCHO) sensor need high sensitivity and selectivity. The research on two dimensional (2D) sensitive material is growing, and most studies focus on the pristine or modified graphene. So it is essential to introduce other 2D materials into HCHO gas sensor. In this report, the adsorption behaviors of organic...