Cyberbullying frequency is related to a wide range of negative outcomes. Little research has attempted to delineate the long-term predictors and mechanisms to predict cyberbullying. Study 1 (N 493) used a correlational study that tested our long-term model of cyberbullying. This model predicted that cyberbullying is a function of positive attitudes toward cyberbullying, which are formed by atti...

In this article, the author provides a framework to guide research in emotional intelligence. Studies conducted up to the present bear on a conception of emotional intelligence as pertaining to the domain of consciousness and investigate the construct with a correlational approach. As an alternative, the author explores processes underlying emotional intelligence, introducing the distinction be...

Snoring detection is important for diagnosing obstructive sleep apnea syndrome (OSAS) and other respiratory sleep disorders. In general, audio signal processing such as snoring sound analysis uses the frequency characteristics of the signal. Recently, a correlational filter Multilayer Perceptron neural network (f-MLP) has been proposed, which has the first hidden layer of correlational filter o...

Common representation learning (CRL), wherein different descriptions (or views) of the data are embedded in a common subspace, has been receiving a lot of attention recently. Two popular paradigms here are canonical correlation analysis (CCA)-based approaches and autoencoder (AE)-based approaches. CCA-based approaches learn a joint representation by maximizing correlation of the views when proj...

In homelessness research and policymaking, it seems to be axiomatic that single adults experience 3 temporally based types of homelessness: chronic, episodic, and transitional. We discuss problems with the theorization of this typology and with the research design, data analysis, and time-aggregated conceptualization and measurement of temporality in the empirical work supporting the typology. ...

Longitudinal study designs are indispensable for investigating age-related functional change. There now are well-established methods for addressing missing data in longitudinal studies. Modern missing data methods not only minimize most problems associated with missing data (e.g., loss of power and biased parameter estimates), but also have valuable new applications such as research designs tha...