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

Disguised Face Identification (DFI) with Facial KeyPoints using Spatial Fusion Convolutional Network

Disguised face identification (DFI) is an extremely challenging problem due to the numerous variations that can be introduced using different disguises. This paper introduces a deep learning framework to first detect 14 facial key-points which are then utilized to perform disguised face identification. Since the training of deep learning architectures relies on large annotated datasets, two annotated facial key-points datasets are introduced. The effectiveness of the facial keypoint detection framework is presented for each keypoint. The superiority of the key-point detection framework is also demonstrated by a comparison with other deep networks. The effectiveness of classification performance is also demonstrated by comparison with the state-of-the-art face disguise classification methods.Comment: To Appear in the IEEE International Conference on Computer Vision Workshops (ICCVW) 201

Universal precaution: practice among doctors in a tertiary care hospital in Manipur

Background: Health workers especially doctors are always at higher risk of exposure to blood borne pathogens in day to day practice. Universal precaution is the only strategy so that all these infections could be prevented. The objective of the study was to assess the practice of Universal Precautions among doctors & factors influencing its use in a tertiary health centre of Manipur.Methods: Cross-sectional study was conducted among the doctors in a tertiary health care centre of Manipur during October 2011 to September 2013. Structured questionnaire was used to collect data. Descriptive statistics like percentage was used to describe the findings using SPSS 20.Results: Total respondents were 366 doctors. Response rate was 98%. Total of 125 (34.2%) respondents always used glove as a measure of universal precaution. Hand-washing after removal of gloves was practiced by more than half of the respondents. Around 2 in 10 participants never used personal protective equipments like gown & mask. Around 7 in 10 participants always practiced recapping after use. Total of 150 respondents (41%) used to dispose sharps in sharp and liquid proof container with removing syringe.74.3% mentioned the reasoning of not practicing universal precaution was lack of supply of personal protective equipment. A total of 50 respondents told that emergency situation was also responsible for not adhering to the practice. Work stress (1.6%), time constraint (5.7%), lack of display of guidelines (3.8%) were the reasons mentioned by few of them.Conclusions: Universal precaution practice was poor. Training of the health care workers, proper equipment supply, posters displaying guidelines and proper hospital policy of patient load management would help in improving the implementation of universal precaution thus restoring occupational safety of health care workers

Autonomous UAV for suspicious action detection using pictorial human pose estimation and classification

Visual autonomous systems capable of monitoring crowded areas and alerting the authorities in occurrence of a suspicious action can play a vital role in controlling crime rate. Previous atte mpts have been made to monitor crime using posture recognition but nothing exclusive to investigating actions of people in large populated area has been cited. In order resolve this shortcoming, we propose an autonomous unmanned aerial vehicle (UAV) visual surveillance system that locates humans in image frames followed by pose estimation using weak constraints on position, appearance of body parts and image parsing. The estimated pose, represented as a pictorial structure, is flagged using the proposed Hough Orientation Calculator (HOC) on close resemblance with any pose in the suspicious action dataset. The robustness of the system is demonstrated on videos recorded using a UAV with no prior knowledge of background, lighting or location and scale of the human in the image. The system produces an accuracy of 71% and can also be applied on various other video sources such as CCTV camera

Revisiting the Thermal AdS partition function

We rewrite the worldsheet torus partition function of the Thermal AdS CFT by isolating the boundary parameters. Using this, we show that the spectrum of the Euclidean BTZ black hole and Lorentzian AdS3 can be extracted -- the latter as a zero temperature limit. A similar procedure recovers the Lorentzian BTZ spectrum proposed in an earlier work. We then use our expression to construct a boundary modular invariant expression as a Poincar\'e series

Экспериментальное исследование по механизму образования нестационарного тока в бетатроне

Исследование нестационарного тока, возникающего во время инжекции, показало, что решающую роль в процессе его образования может играть резонансное затухание амплитуд колебаний электронов, возникающее при взаимодействии циркулирующих электронов с током эмиссии из инжектора. Это означает, что при определенных условиях, когда для большей части электронов происходит уменьшение их амплитуд колебаний, должно происходить сжатие всего пучка электронов, образующих нестационарный ток. Такое явление должно происходить при образовании нестационарного тока на фронтах импульса инжекции малой длительности, когда происходит однократное образование нестационарного тока. Экспериментальное исследование поведения нестационарного тока во времени, проведенное в бетатроне 15 Мэв с помощью системы электрических электродов, показало, что действительно при образовании нестационарного тока на фронтах импульса инжекции происходит сжатие пучка электронов. Таким образом, обнаружение изменения поперечных размеров пучка во время инжекции является прямым подтверждением резонансного механизма образования нестационарного тока

Implementation of ECC and ECDSA for Image Security

the use of digital data has been increase over the past decade which has led to the evolution of digital world. With this evolution the use of data such as text, images and other multimedia for communication purpose over network needs to be secured during transmission. Images been the most extensively used digital data throughout the world, there is a need for the security of images, so that the confidentiality, integrity and availability of the data is maintained. There is various cryptography techniques used for image security of which the asymmetric cryptography is most extensively used for securing data transmission. This paper discusses about Elliptic Curve Cryptography an asymmetric public key cryptography method for image transmission. With security it is also crucial to address the computational aspects of the cryptography methods used for securing images. The paper proposes an Image encryption and decryption method using ECC. Integrity of image transmission is achieved by using Elliptic Curve Digital Signature Algorithm (ECDSA) and also considering computational aspects at each stage