Many new skills are acquired during early childhood. Typical laboratory skill learning tasks are not applicable for developmental studies that involve children younger than 8 years of age. It is not clear whether young children and adults share a basic underlying skill learning mechanism. In the present study, the learning and retention of a simple grapho-motor pattern were studied in three age...

INTRODUCTION The study of expertise tends to focus on humans who can perform extraordinary feats. Although the way in which expertise is acquired is often characterized as similar to everyday skill acquisition, the attainment of basic numeracy skills is rarely considered in the same context as the attainment of expertise. It is clear, though, that average numeracy skills possess all the hallmar...

Athletes devote their lives to practicing their chosen sport so as to attain the highest level of skilled performance. A perennial question is why are some athletes better than others? Most debates on this issue reduce to genetics (natural abilities) vs differences in accumulated deliberative practice. In contrast, the target article under discussion here reports on a study that identified psyc...

OBJECTIVE Box model trainers have been used for many years to facilitate the improvement of laparoscopic skills. However, there are limited data available on box trainers and their impact on skill acquisition, assessed by virtual reality systems. MATERIAL AND METHODS Twenty-two Postgraduate Year 1 gynecology residents with no laparoscopic experience were randomly divided into one group that r...

In this study, we analyze the e¤ects of a decrease in unskilled labor in China on the direction of innovation in the US by incorporating production o¤shoring into a North-South model of directed technical change. We …nd that if o¤shoring is present (absent) in equilibrium, then a decrease in unskilled labor in the South would lead to skill-biased (unskill-biased) technical change in the North. ...

This paper discusses the use of multilayer feed forward neural networks for predicting a stock's excess return based on its exposure to various technical and fundamental factors. To demonstrate the effectiveness of the approach a hedged portfolio which consists of equally capitalized long and short positions is constructed and its historical returns are benchmarked against T-bill returns and th...

Arti cial Neural Networks can be used to predict future returns of stocks in order to take nancial decisions Should one build a separate network for each stock or share the same network for all the stocks In this paper we also explore other alternatives in which some layers are shared and others are not shared When the prediction of future returns for di erent stocks are viewed as di erent task...

This paper presents methodologies to select equities based on soft-computing models which focus on applying fundamental analysis for equities screening. This paper compares the performance of three soft-computing models, namely multi-layer perceptrons (MLP), adaptive neuro-fuzzy inference systems (ANFIS) and general growing and pruning radial basis function (GGAP-RBF). It studies their computat...

Once it is decided that investment is to be made in the stock, the obvious question which arises is: which all stocks should be purchased? Past performance will not guarantee the future, but it is still worthwhile to evaluate the investments based on their ability to deliver consistent returns with minimal risk. Therefore, the ability to generate most profitable return from short term stock tra...