The present study examined the time and frequency structure of force output in adult humans to determine whether the changes in complexity with age are dependent on external task demands. Healthy young (20-24 yr), old (60-69 yr), and older-old (75-90 yr) humans produced isometric force contractions to constant and sine wave targets that also varied in force level. First, force variability on ea...

Stimulus-triggered averaging (StTA) of electromyographic (EMG) activity is a form of intracortical microstimulation that enables documentation in awake animals of the sign, magnitude, latency, and distribution of output effects from cortical and brainstem areas to motoneurons of different muscles. In this study, we show that the properties of effects in StTAs are stable and mostly independent o...

In this work, we explore multiple neural architectures adapted for the task of automatic post-editing of machine translation output. We focus on neural endto-end models that combine both inputs mt (raw MT output) and src (source language input) in a single neural architecture, modeling {mt, src} → pe directly. Apart from that, we investigate the influence of hard-attention models which seem to ...

A novel ultra-high compliance, low power, very accurate and high output impedance current output stage (COS) with extremely high output current drive capability is proposed in this paper. The principle of operation of this unique structure is discussed, its most important formulas are derived and its outstanding performance is verified by HSPICE simulation in TSMC 0.18µm CMOS, BSIM3, and Level4...

Conflagration is the major safety issue of electric vehicles (EVs). Due to their well-kept appearance and structure, which demonstrate salient visual changes after combustion, EV bodies are recognized as an important basis for on-spot inspection burnt EVs make application using semantic segmentation possible. The combination deep learning-based recognition traces would provide preliminary analy...

The automatic fluency assessment of spontaneous speech without reference text is a challenging task that heavily depends on the accuracy recognition (ASR). Considering this scenario, it necessary to explore an method combines ASR. This mainly due fact in addition acoustic features being essential for assessment, output by ASR may also contain potentially information. However, most existing stud...

This paper describes our participation at the LifeCLEF Fish task 2015. The task is about video-based fish identification. Firstly, we applied foreground detection method with selective search to extract candidate fish object window. Then deep convolutional neural network is used to classify fish species per window. Classification results are post-processed to produce final identification output...

This article reports on the findings of a study that investigated the impact of manipulating task performance conditions on listening task performance by learners of English as a foreign language (EFL). The study was designed to explore the effects of changing complexity dimensions on listening task performance and to achieve two aims: to see how listening comprehension task performance was aff...