Temporal PDMs for gait classification

Gait classification is a developing research area, particularly with regards to biometrics. It aims to use the distinctive spatial and temporal characteristics of human motion to classify differing activities. As a biometric, this extends to recognising different people by the heterogeneous aspects of their gait. This research aims to use a modified deformable model, the temporal PDM, to distinguish the movements of a walking and miming person. The movement of 2D points on the moving form is used to provide input into the model and classify the type of gait present.

Rapid multi sample DNA amplification using rotary-linear polymerase chain reaction device (PCRDisc)

Multiple sample DNA amplification was done by using a novel rotary-linear motion polymerase chain reaction (PCR) device. A simple compact disc was used to create the stationary sample chambers which are individually temperature controlled. The PCR was performed by shuttling the samples to different temperature zones by using a combined rotary-linear movement of the disc. The device was successfully used to amplify up to 12 samples in less than 30 min with a sample volume of 5 μl. A simple spring loaded heater mechanism was introduced to enable good thermal contact between the samples and the heaters. Each of the heater temperatures are controlled by using a simple proportional–integral–derivative pulse width modulation control system. The results show a good improvement in the amplification rate and duration of the samples. The reagent volume used was reduced to nearly 25% of that used in conventional method.

Robust adaptive backstepping controller design for DC-DC buck converters with external disturbances

In modern power electronic systems, DC-DC converter is one of the main controlled power sources for driving DC systems. But the inherent nonlinear and time-varying characteristics often result in some difficulties mostly related to the control issue. This paper presents a robust nonlinear adaptive controller design with a recursive methodology based on the pulse width modulation (PWM) to drive a DC-DC buck converter. The proposed controller is designed based on the dynamical model of the buck converter where all parameters within the model are assumed as unknown. These unknown parameters are estimated through the adaptation laws and the stability of these laws are ensured by formulating suitable control Lyapunov functions (CLFs) at different stages. The proposed control scheme also provides robustness against external disturbances as these disturbances are considered within the model. One of the main features of the proposed scheme is that it overcomes the over-parameterization problems of unknown parameters which usually appear in some conventional adaptive methods. Finally, the effectiveness of the proposed control scheme is verified through the simulation results and compared to that of an existing adaptive backstepping controller. Simulation results clearly indicate the performance improvement in terms of a faster output voltage tracking response.