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Pultrusion is considered to be a cost efficient method for developing composite structures. It facilitates the fabrication of uniform cross-section products with improved fiber alignment, mechanical properties, good surface characteristics, etc. In order to ascertain the crashworthiness, the pultruded composites shall be able to resist impact loads, and in this concern, the energy absorption capacity of the pultruded composites must be explored. This article presents the experimental and numerical investigation of the crushing behavior of polyester based pultruded composite with rectangular cross section. Pultruded rectangular tubes with e-glass/polyester composites have been developed for this study. The cross-section of the tubes was developed into two triggering profiles, the uniform edge around the section and the tulip pattern. The tubes were subjected to impact loads, and the effect of these triggering profiles on the energy absorption capacity of the tubes has been investigated. The testing of all composites has been carried out at three different impact velocities (10, 20 and 45 mm/min). The results have revealed the dependence of crushing behavior of the tubes on the loading velocity and the triggered profiles. Lower peak load and high specific energy absorption (SEA) was observed in the tube with tulip pattern profile. The results obtained from the simulation have also shown consistency with the real-time experiments.

This paper presents a method for real-time detection and tracking of the human face. This is achieved using the Raspberry Pi microcomputer and the Easylab microcontroller as the main hardware with a camera mounted on servomotors for continuous image feed-in. Real-time face detection is performed using Haar-feature classifiers and ScicosLab in the Raspberry Pi. Then, the Easylab is responsible for face tracking, keeping the face in the middle of the frame through a pair of servomotors that control the horizontal and vertical movements of the camera. The servomotors are in turn controlled based on the state-diagrams designed using SMCube in the EasyLab. The methodology is verified via practical experimentation.

Radar imaging is an area of tremendous interest as radar-based systems are perhaps the only all-weather, long range remote sensing systems. However, radar's continued utility and application in wide-ranging areas is fundamentally dependent on the ability to produce high-quality, artifact-free imagery. To date, the use of radar to identify and image moving objects remains of great interest, and it is well known that motion in the scene gives rise to mispositioning or streaking when target motion is not addressed. Many techniques have been developed to handle moving objects, but these techniques make use of the start-stop approximation, in which a target in motion is assumed to be momentarily stationary while it is being interrogated by a radar pulse. A new linearized imaging theory that combines the spatial, temporal and spectral aspects of scattered waves has been developed. This thesis studies the performance of this new imaging scheme via analysis of the point spread function. It is shown that the imaging PSF localizes, and is translation invariant in phase-space. It is also shown that the behavior of the imaging system is dependent on the aperture geometry and choice of radar waveforms transmitted.