In this paper, multivariate skew-normal distribution is em- ployed for analyzing an outcome based dropout model for repeated mea- surements with non-random dropout in skew regression data sets. A probit regression is considered as the conditional probability of an ob- servation to be missing given outcomes. A simulation study of using the proposed methodology and comparing it with a semi-parame...

Power generated from a piezoelectric material usually comes with poor characteristics such as high voltage, low current and high impedance. In order to drive the embedded sensor circuit, piezoelectric power needs to be characterized and regulated. In this paper, we present an analysis on the power generation characteristics and the efficiency of power conversion of the stiff lead zirconate tita...

The digital low dropout regulator (D-LDO) has drawn significant attention recently for its low-voltage operation and process scalability. However, the tradeoff between current efficiency and transient response speed has limited its applications. In this brief, a coarse–fine-tuning technique with burst-mode operation is proposed to the D-LDO. Once the voltage undershoot/ overshoot is detected, t...

Anultra-low power capacitor less low-dropout voltage regulator with improved transient response using gain enhanced feed forward path compensation is presented in this paper. It is based on a cascade of a voltage amplifier and a transconductor stage in the feed forward path with regular error amplifier to form a composite gainenhanced feed forward stage. It broadens the gain bandwidth and thus ...

We introduce Information Dropout, a generalization of dropout that is motivated by the Information Bottleneck principle and highlights the way in which injecting noise in the activations can help in learning optimal representations of the data. Information Dropout is rooted in information theoretic principles, it includes as special cases several existing dropout methods, like Gaussian Dropout ...

BACKGROUND Dropout rates in binge eating disorder (BED) treatment are high (17-30%), and predictors of dropout are unknown. METHOD Participants were 376 patients following an intensive outpatient cognitive behavioural therapy programme for BED, 82 of whom (21.8%) dropped out of treatment. An exploratory logistic regression was performed using eating disorder variables, general psychopathology...

In networked control systems, time delay and data dropout can degrade the performance of the control system and even destabilize the system. In the present paper, the Extended Kalman filter is employed to compensate the effects of time delay and data dropout in feedforward and feedback paths of networked control systems. In the proposed method, the extended Kalman filter is used as an observer ...

Dropout is often used as an outcome measure in clinical trials of antipsychotic medication. Previous research is inconclusive regarding (a) differences in dropout rates between first- and second-generation antipsychotic medications and (b) how trial design features reduce dropout. Meta-analysis of randomized controlled trials (RCTs) of antipsychotic medication was conducted to compare dropout r...

Dropout is a popular technique for regularizing artificial neural networks. Dropout networks are generally trained by minibatch gradient descent with a dropout mask turning off some of the units—a different pattern of dropout is applied to every sample in the minibatch. We explore a very simple alternative to the dropout mask. Instead of masking dropped out units by setting them to zero, we per...