We describe a learning approach to automatically building knowledge bases for information extraction from multiple text based web pages. A frame based representation is introduced to represent domain knowledge as knowledge unit frames. A frame learning algorithm is developed to automatically learn knowledge unit frames from training examples. Some training examples can be obtained by automatica...

1. The runs: • A_brU_1 – features extracted from each frame; SVM per-frame classifier trained on frames in each shot; simple decision tree judging shots based on per-frame results • A_brV_2 – same as A_brU_1, but SVM trained on all training data (the first run divided the training data to training and cross-validation datasets), with SVM configured from the previous run 2. Significant differenc...

literature concerning the effects of ramadan fasting on sports performance presents conflicting results. in this context, some studies reported a significant impairment of sports performance during the month of ramadan. however, other studies suggested that ramadan fasting has no significant effect on physical performance.  the discrepancies between the studies could be explained by time-of-day...

Verification benefits from removing logic that is not relevant for a proof. Techniques for doing this are generally known as localization abstraction. Abstraction is often performed by selecting a subset of gates to be included in the abstracted model; the signals feeding into this subset become unconstrained cutpoints. In this paper, a novel approach to gate-level abstraction is presented, whi...

As envisioned and implemented so far, the enlargement process is long-term and has neither milestones nor deadlines for completion. It is an open process that in principle does not reject beforehand the membership of any European country (as stipulated in Article 10 of the Washington Treaty). Since early 1994, NATO has committed itself to a gradual and transparent process of enlargement, althou...

In this paper the role of the frame length on the computation of Mel Frequency Cepstral Coefficients (MFCCs) is investigated in a text-dependent speaker verification system. The variations of vocal characteristics of subjects along the time and the related information conveyed in the MFCCs cause a significant degradation on verification performance. In our experiments we tested the use of diffe...

Training Artificial Neural Networks (ANNs) with large amounts of speech data is a time intensive task due to the intrinsically sequential nature of the back-propagation algorithm. This paper presents an approach for training ANNs using sentence and frame selection. The goal is to speed-up the training process, and to balance the phonetic coverage of the selected frames, trying to mitigate the c...

An algorithm is proposed for tracking objects in real time. The algorithm is based on neural network implemented on GPU. Investigation and parameter optimization of the algorithm are realized. Tracking process has accelerated by 10 times and the training process has accelerated by 2 times versus to the sequential algorithm version. The maximum resolution of the frame for real-time tracking and ...

We introduce an online action recognition system that can be combined with any set of frame-by-frame feature descriptors. Our system covers the frame feature space with classifiers whose distribution adapts to the hardness of locally approximating the Bayes optimal classifier. An efficient nearest neighbour search is used to find and combine the local classifiers that are closest to the frames ...