In this study a back-propagation neural network model is designed and its parameters are optimized for prediction of horoscope to identify a person type. Person type is a dynamic system based on the planet system. It is found that the backpropagation neural network is capable to predict the person type by learning planet dataset. The model is trained up to model error (i.e., mean square error) ...

Background: Physical activity combined with some herbal supplementations can affect body energy metabolism, blood lipids and physical fitness levels. However, the effect of exercise training combined with fenugreek on lipid metabolism and body composition in patients with type2 diabetes is unknown. Objective: The aim of present study was to investigate the effects of eight weeks’ enduran...

Face-off is an interesting case of style transfer where the facial expressions and attributes of one person could be fully transformed to another face. We are interested in the unsupervised training process which only requires two sequences of unaligned video frames from each person and learns what shared attributes to extract automatically. In this project, we explored various improvements for...

We present a freely available named-entity recognizer for Greek texts that identifies temporal expressions, person, and organization names. For temporal expressions, it relies on semi-automatically produced patterns. For person and organization names, it employs an ensemble of Support Vector Machines that scan the input text in two passes. The ensemble is trained using active learning, whereby ...

The proposed system is focusing on the detection of three events in airport videos: a person running, a person putting down an object and a person pointing with his/her hand. The system was part of the NIST-TRECVid 2010 campaign, the training dataset consists in 100 hours of video from the Gatwick airport from five different cameras. For the detection of a person running, a non-parametric appro...

Face recognition is challenging especially when the images from different persons are similar to each other due to variations in illumination, expression, and occlusion. If we have sufficient training images of each person which can span the facial variations of that person under testing conditions, sparse representation based classification (SRC) achieves very promising results. However, in ma...

As people learn more facts about a concept, those facts become more difficult to remember. This is called the fan effect, where fan refers to the number of facts known about a concept. Increasing fan has been shown to decrease accuracy and increase response time and left ventrolateral prefrontal cortex (VLPFC) activity during retrieval. In this study, participants learned 36 arbitrary person-lo...