Accelerated Learning is a method of learning that increases the reader's potential to absorb, retain and recall - thus increasing your memory power. This book demonstrates how to use this technique when learning, teaching or training anything - from a foreign language to stress management. It can also help you become a more creative teacher or trainer, who can introduce joy into learning and who can help increase a student's self esteem.

The Book Shows How To Use Your Bodypower To Stay Healthy. It Also Include Simple But Effective Tips On How To Stay Slim; Improve Your Eye Sight; Break Bad Habits And Much, Much More.

'A must read' JAMIE WINDUST 'A beautifully honest book' JUNO ROCHE 'A superb and necessary book' BEN PECHEY As a young, queer, plus-size person, Essie Dennis has spent a lot of time feeling like they weren't enough - not queer enough, not feminine enough, not perfect enough. When they took to social media to share how they felt, they were overwhelmed by how many others felt the same. I look too masculine to be non-binary I look too feminine to be a lesbian Am I too fat for drag? Inviting you to challenge accepted beauty standards and the concept of 'the perfect body', Essie takes everything they have learned on their journey to self-acceptance and body satisfaction to help guide you towards loving your queer body. From gender, sexuality and reclaiming your body, through to food, politics, social media and fatphobia, this radical book starts a conversation about body image and mental health that queer people are so often left out of. Fiercely and unapologetically written, and with honest advice and powerful stories from a diverse range of queer people throughout, this is an inspiring and necessary book that will show you that you are enough.

Perfect for those who want a total body and mind workout.

Upper body power (UBP) is one of the most important factors affecting the performance of cross-country skiers during races. Although some initial studies have already attempted to predict UBP, until now, no study has attempted to apply machine learning methods combined with various feature selection algorithms to identify the discriminative features for prediction of UBP. The purpose of this study is to develop new prediction models for predicting the 10-second UBP (UBP10) and 60-second UBP (UBP60) of cross-country skiers by using General Regression Neural Networks (GRNN), Radial-Basis Function Network (RBF), Multilayer Perceptron (MLP), Support Vector Machine (SVM), Single Decision Tree (SDT) and Tree Boost (TB) along with the Relief-F feature selection algorithm, minimum redundancy maximum relevance (mRMR) feature selection algorithm and the Correlation-based Feature Subset Selection (CFS). Several models have been developed to predict UBP10 and UBP60 of cross-country skiers using two datasets. 10-fold cross validation has been performed for model testing. The efficiency of the prediction models has been calculated with their multiple correlation coefficients (R’s), standard error of estimates (SEE’s) and mean absolute percentage errors (MAPE’s). The results emphasize that GRNN-based prediction models show higher performance than the other regression methods. Also, using less number of predictor variables than the full set of predictor variables can be useful for prediction of UBP10 and UBP60 with comparable error rates.