Methods to forecast electric loads and generation timeseries are widely applied in power system operation balancing. For this purpose, most sophisticated forecasting methods complex, since the net electricity consumption is not dependent on explainable by a single cause. The increasing complexity furthers trend towards machine-learning that achieve more accurate load forecasts with exogenous fe...

The relationship between implicit/incidental sequence learning and working memory motivated a series of research because it is plausible that higher working memory capacity opens a "larger window" to a sequence, allowing thereby the sequence learning process to be easier. Although the majority of studies found no relationship between implicit sequence learning and working memory capacity, in th...

Motor sequence learning on the serial reaction time task involves the integration of response-, stimulus-, and effector-based information. Human primary motor cortex (M1) and the inferior parietal lobule (IPL) have been identified with supporting the learning of effector-dependent and -independent information, respectively. Current neurocognitive data are, however, exclusively based on learning...

Distinctive phonetic features (DPFs) abstractedly describe the place, manner of articulation, and voicing language phonemes. While DPFs are powerful speech signals that capture unique articulatory characteristics each phoneme, task DPF extraction is challenged by need for efficient computational model. Unlike ordinary acoustic can be directly determined form waveform using closed-form expressio...