Classification of sporting activities using smartphone accelerometers

In this paper we present a framework that allows for the automatic identification of sporting activities using commonly available smartphones. We extract discriminative informational features from smartphone accelerometers using the Discrete Wavelet Transform (DWT). Despite the poor quality of their accelerometers, smartphones were used as capture devices due to their prevalence in today’s society. Successful classification on this basis potentially makes the technology accessible to both elite and non-elite athletes. Extracted features are used to train different categories of classifiers. No one classifier family has a reportable direct advantage in activity classification problems to date; thus we examine classifiers from each of the most widely used classifier families. We investigate three classification approaches; a commonly used SVM-based approach, an optimized classification model and a fusion of classifiers. We also investigate the effect of changing several of the DWT input parameters, including mother wavelets, window lengths and DWT decomposition levels. During the course of this work we created a challenging sports activity analysis dataset, comprised of soccer and field-hockey activities. The average maximum F-measure accuracy of 87% was achieved using a fusion of classifiers, which was 6% better than a single classifier model and 23% better than a standard SVM approach

An advanced virtual dance performance evaluator

The ever increasing availability of high speed Internet access has led to a leap in technologies that support real-time realistic interaction between humans in online virtual environments. In the context of this work, we wish to realise the vision of an online dance studio where a dance class is to be provided by an expert dance teacher and to be delivered to online students via the web. In this paper we study some of the technical issues that need to be addressed in this challenging scenario. In particular, we describe an automatic dance analysis tool that would be used to evaluate a student's performance and provide him/her with meaningful feedback to aid improvement

Title III of the ADA Allows a Qualified Disabled Entrant to Use a Motorized Cart on the Professional Golf Tour: \u3cem\u3ePGA Tour, Inc. v. Martin\u3c/em\u3e

The Supreme Court of the United States held that Title III of the ADA protects access to professional golf tournaments by a qualified entrant with a disability, and that a disabled participant\u27s use of a motorized golf cart during play would not fundamentally alter the nature of tournament play. PGA Tour, Inc. v. Martin, 121 S.Ct. 1879 (2001

Comparison of C═C bond hydrogenation in C-4 unsaturated nitriles over Pt/alumina

The hydrogenation of allyl cyanide (but-1-ene-4-nitrile, AC), trans- and cis-crotononitrile (E- and Z-but-2-ene nitrile, TCN and CCN), and methacrylonitrile (2-cyano-1-propene, MCN) were studied, both singly and competitively, over a Pt/alumina catalyst in the liquid phase. Each unsaturated nitrile only underwent C═C bond hydrogenation: no evidence was found for the formation of the saturated or unsaturated amine. The nonconjugated allyl cyanide was found to be the most reactive unsaturated nitrile. Activation energies for the hydrogenation of the C═C bond in AC and MCN were determined giving values of 64 ± 7 kJ mol–1 for AC and 37 ± 4 kJ mol–1 for MCN. The reaction was zero order for both nitriles. Competitive hydrogenations revealed that not only does allyl cyanide react preferentially over the other isomers but also it inhibits the hydrogenation of the other isomers. When all four nitriles were simultaneously hydrogenated, inhibition effects were easily seen suggesting that in terms of strength of bonding to the surface an order of AC > CCN > TCN ∼ MN can be generated