Eye in the Sky: Real-time Drone Surveillance System (DSS) for Violent Individuals Identification using ScatterNet Hybrid Deep Learning Network

Drone systems have been deployed by various law enforcement agencies to monitor hostiles, spy on foreign drug cartels, conduct border control operations, etc. This paper introduces a real-time drone surveillance system to identify violent individuals in public areas. The system first uses the Feature Pyramid Network to detect humans from aerial images. The image region with the human is used by the proposed ScatterNet Hybrid Deep Learning (SHDL) network for human pose estimation. The orientations between the limbs of the estimated pose are next used to identify the violent individuals. The proposed deep network can learn meaningful representations quickly using ScatterNet and structural priors with relatively fewer labeled examples. The system detects the violent individuals in real-time by processing the drone images in the cloud. This research also introduces the aerial violent individual dataset used for training the deep network which hopefully may encourage researchers interested in using deep learning for aerial surveillance. The pose estimation and violent individuals identification performance is compared with the state-of-the-art techniques.Comment: To Appear in the Efficient Deep Learning for Computer Vision (ECV) workshop at IEEE Computer Vision and Pattern Recognition (CVPR) 2018. Youtube demo at this: https://www.youtube.com/watch?v=zYypJPJipY

Energy efficient task scheduling in data center

First of all, I am thankful to God for his blessings and showing me the right direction. With His mercy, it has been made possible for me to reach so far. Foremost, I would like to express my sincere gratitude to my advisor Prof. Durga Prasad Mohapatra for the continuous support of my M.Tech study and research, for his patience, motivation, enthusiasm, and immense knowledge. I am thankful for her continual support, encouragement, and invaluable suggestion. His guidance helped me in all the time of research and writing of this thesis. I could not have imagined having a better advisor and mentor for my M.Tech study. Besides my advisor, I extend my thanks to our HOD, Prof. S. K. Rath and Prof. B. D. Sahoo for their valuable advices and encouragement. I express my gratitude to all the sta members of Computer Science and Engineering Department for providing me all the facilities required for the completion of my thesis work. I would like to say thanks to all my friends especially Dilip Kumar, Alok Pandey for their support. Last but not the least I am highly grateful to all my family members for their inspiration and ever encouraging moral support, which enables me to purse my studies

Flow and mixing studies in a co-rotating intermeshing twin screw extruder

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The basic understanding of mixing in the process of polymer melt extrusion by twin screw extruder is limited by their geometrical complexity and the interactions of the process parameters. Mixing and flow in a 100mm diameter, trapezoidal channeled, intermeshing co-rotating twin-screw extruder have been characterised by determination of residence time distribution (RTD) and of the paths taken by tracers added to the melt. The axial mixing and the effects of varius parameters on it were established by studying RTD using tracer techniques. As the tail of the distribution is of paramount importance, the reproducibility of the RTD curve was extensively studied. Radioactive NnO2 was used as a tracer and detected by gamma ray spectroscopy giving more reproducible results than added barytes estimated gravimetrically after ashing. Shock cooling of the extruder and sectioning of the solidified compound in the screw channels was used to-study the flow mechanism. The maximum throughput achieved, polymer melting mechanism, filled volume and axial mixing Are interrelated, and are dependent on the configuration and position of segmented mixing discs present in the screw profile. In the upstream position these act as melting discs and their efficiency is increased in a closed configuration. Initial melting is achieved over a remarkably short distance along the screw profile. The screw speed affects the axial mixing which is shown to be related to the net relative pressure change at the screw tips. A flow model is proposed such that the overall material flow taking place in an anticlockwise direction along the screw channel comprises two separate flow regimes. The upper regime rotates anti-clockwise and is made up of main and small tetrahedron flow and calender flow. The lower flow regime rotates clockwise and is made up of main and small side leakage flows and a portion of the main tetrahedron flows together with a central flow. The flow studies show conclusively that the melt from a particular site ahead of the intermeshing zone occupies a predestined site after passing through the intermeshing zone