Abstract To minimize power consumption while maximizing performance, today’s multicore processors rely on fine-grained run-time dynamic information—both in the time domain, e.g. $$\mu $$ μ s to ms, and space core-level. The state-of-the-art for deriving such information is mainly based predetermined models wh...

Abstract. A gridded ocean subsurface salinity dataset with global coverage is useful for research on climate change and its variability. Here, we explore the feed-forward neural network (FFNN) approach to reconstruct a high-resolution (0.25∘ × 0.25∘) (1–2000 m) period 1993–2018 by merging in situ profile observations satellite remote-sensing altimetry absolute dynamic topography (ADT), sea surf...

With the increasing incidence of severe skin diseases, such as cancer, endoscopic medical imaging has become urgent for revealing internal and hidden tissues under skin. Diagnostic information to help doctors make an accurate diagnosis is provided by endoscopy devices. Nonetheless, most diseases have similar features, which it challenging dermatologists diagnose patients accurately. Therefore, ...

Predicting the power obtained at output of photovoltaic (PV) system is fundamental for optimum use PV system. However, it varies different times day depending on intermittent and nonlinear environmental conditions including solar irradiation, temperature wind speed, Short-term prediction vital in systems to reconcile generation demand terms cost capacity reserve. In this study, a Gaussian kerne...

Time series data mining (TSDM) techniques explores large amount of time series data in search of interesting relationships among variables. The TSDM methods overcome limitations including stationarity and linearity requirements of traditional time series analysis by adapting data mining concepts for analyzing time series data. The Feed Forward Neural Net is one of the most widely used neural ne...

This paper presents a relative humidity predictions using feedforward artificial neural network (FFNN). Relative humidity values obtained from weather records for Malaysia are used in training the FFNNs. The prediction of the relative humidity is in terms of Sun shine ration and cloud cover. However, three statistical parameters, namely, mean absolute percentage error, MAPE, mean bias error, MB...

The intellegibility and naturalness of synthetic speech strongly depends on its prosodic quality. Departing from works by Mixdorff on a linguistically motivated model of German intonation based on the Fujisaki model, the current paper presents statistical results concerning the relationship between linguistic and phonetic information underlying an utterance and its prosodic features. Statistica...

The perceived quality of synthetic speech strongly depends on its prosodic naturalness. Departing from works by Mixdorff on a linguistically motivated model of German intonation based on the Fujisaki model, the current paper presents statistical results concerning the relationship between linguistic and phonetic information underlying an utterance and its prosodic features. These results were e...