Adaptive computer-based training systems aim to enhance the learning experience by personalising the presentation and content delivery according to the preferences of each particu...
This paper proposes a novel approach to the problem of training classifiers to detect and correct grammar and usage errors in text by selectively introducing mistakes into the tra...
This paper presents our work in solving one of the weakest links in 802.11-based indoor-localization: the training of ground-truth received signal strength data. While crowdsourcin...
How could computer games be used to augment training for fighter pilots? This paper is aimed at providing one answer to this research question. Three current methods of training f...
This paper studies the effects of training data on binary text classification and postulates that negative training data is not needed and may even be harmful for the task. Tradit...
We introduce a novel training algorithm for unsupervised grammar induction, called Zoomed Learning. Given a training set T and a test set S, the goal of our algorithm is to identi...
Motivation – Investigations of large-scale outages in the North American interconnected electric system often attribute the causes to three T’s: Trees, Training and Tools. To ...
Frank L. Greitzer, Robin Podmore, Marck Robinson, ...
—Simulation based training system can play an important role in education. It provides fruitful configurations with low cost of maintenance and further development compared to th...
—Multi-core technology is becoming the mainstream of processor architecture. It is a great challenge for universities to offer students new theories because of the continuous cha...
The problem of placing training symbols optimally for orthogonal frequency-division multiplexing (OFDM) and single-carrier systems is considered. The channel is assumed to be quasi...