In this paper, we proposed a method to recognize complex human daily activities including body activities and hand gestures simultaneously in an indoor environment. Three wearable motion sensors are attached to the right thigh, the waist, and the right hand of a person, while an optical motion capture system is used to obtain his/her location information. A three-level dynamic Bayesian network is implemented to model the intra-temporal and inter-temporal constraints among the location, body activity and hand gesture. The body activity and hand gesture are estimated using a Bayesian filter and the short-time Viterbi algorithm, which reduces the storage memory and the computational complexity. We conducted experiments in a mock apartment environment and the obtained results showed the effectiveness and accuracy of our algorithms.

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Different types of water resources studies require the information of Suspended Sediment Yield (SSY) in different time resolutions. In ungauged watersheds where hydrometeorogical time series are not available, the mean annual SSY (SSY_a) is solely predictable and catchment area is traditionally used as the predictor because it is the most important variable and generally determined during project planning. Firstly, this research tried to advance the traditional SSY_a model by additionally associating global topographic data. Based on the jack-knife procedure, the modified method considering catchment area with slope greater than 15% was evaluated in 17 gauged catchments in the Lower Mekong Basin and the overall predictive accuracy was improved about 66% in term of mean absolute percentage error. Secondly, the predicted SSY_a in each modeled catchment was monthly distributed using Unit mean annual Sedimentograph (USG_a). The double-average USG_a superior to the single-average one provides overall better quality results than the regionalized USG_a dependent upon the spatial proximity approach. The model performance measured by Nash-Sutcliffe Efficiency (NSE) is about 0.66 in median value and satisfactory results (NSE >0.50) are obtained in 11 catchments. Lastly, the validated regional model was regarded as a potential and feasible tool in solving sediment-ungauged issues in the basin

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