Sentence examples for situations recognition from inspiring English sources

The increase of the errorlikelihood effect for OCD patients within low conflict situations (recognition after errorless learning) might be conceptualized as a hyperactive monitoring system.

For high conflict situations (recognition after EF-learning) the opposite effect was observed: whereas the control group showed an increased error-likelihood effect, the OCD group showed a considerable reduction of the error-likelihood effect based on altered ACC learning rates in response to errors [48], [49].

However, within high conflict situations (recognition after EF-learning) the opposite effect was observed: whereas the control group showed an increased error-likelihood effect, the OCD group showed a reduction of the error-likelihood effect based on altered ACC learning rates in response to errors.

As dying at home is dependent on caregivers' capacity to manage domestic situations, recognition of the vital role families and other caregivers play in the community care system is essential.

Traffic situation recognition is one important component for ITS.

Situation recognition, in general, and activity recognition, in particular, provide an added value on the contextual information that can help the ubiquitous networked robot to autonomously provide the best service that meet the needs of the elderly.

This project includes the following research topics: (i) estimation of driver's state, (ii) driver behavior modeling, (iii) intelligent information processing methods for situation recognition and visual enhancement.

The most researched context recognition scenarios are often cited as applications of activity recognition, situation recognition, motion detection, etc., which usually utilize wireless sensor nodes equipped with various sensors to detect situation.

The MATLAB data mining toolboxes [41] are selected for traffic situation recognition because of the portability and domain specific representations of MATLAB programme [42], and the simple efficient interface between the MATLAB signal processing and the USRP receiving platform [43 47].

Fuzzy logic and ANFIS have been successfully used in many engineering areas, for example, pedestrian behavior [15], capacity estimation [16], driving situation recognition [17], collision avoidance support system [18], traffic signal control at isolated intersection [19], rainfall prediction, signal co-ordination, and highway accident analysis [20].

Within a low conflict situation (recognition after EL-learning) OCD-patients compared to the control group show a considerable increase of the error-likelihood effect.