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Security Management for Controlling Theft using Arduino UNO

Now-a-days theft has become a big threat to people and their property. Securing and monitoring has become the main objective for controlling theft. Several technologies have been developed to control theft. The existing technologies can control only theft but not the culprits who steal the properties. The proposed system is used to provide security to control theft and giving alert to owner when there is a break-in, using Bluetooth. The advanced locking system technology is implemented along with the traditional locking system. There are three techniques to prevent theft. First, IR sensor which is placed infront and rear side of the house. This IR sensor senses the object passes near it. Then the passcode lock system is used to detect the passcode is correct or not. If the entered passcode is incorrect the Arduino UNO controller will be activated. Third is using indicators, it consists of two switches. The two switches are considered as the main power line and fuse box which is placed at the house. When these two switches are on off mode it is considered as power cut. But incase only when the fuse box switch is off the controller activates automatically and the alert is send to the owner through the Bluetooth application which is installed in the mobile phone. If there is any interrupt in any of these techniques, the message will be send to the owner and police station. Total system shutdown option is activated using this application. Then the security system starts monitoring the house. This shutdown option can be made on whenever necessary. This may reduce the power consumption. Such security system gives service at low cost compared to the cost of the available security systems.

Published by: S. Deepika, M. Nisha Angeline

Author: S. Deepika

Paper ID: V3I3-1139

Paper Status: published

Published: May 10, 2017

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Low Power Full Adder Circuit Design Using Two Phase Adiabatic Static CMOS Logic

Adiabatic logic is used to minimize the energy loss during operation of the circuit. Using two phase adiabatic static CMOS logic (2PASCL) the power consumption can be reduced. This paper compare the power consumption of Static Energy Recovery Full Adder(SERF) and the proposed full adder using two phase adiabatic static CMOS logic(2PASCL). The average power consumption of proposed full adder is 4.8pW which is very less in comparative study with SERF. The result of this work focuses on the reduction of power consumption with the scaling down technology.

Published by: Roopali, Uma Nirmal

Author: Roopali

Paper ID: V3I3-1148

Paper Status: published

Published: May 10, 2017

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Smart Attendance Management and Analysis with Signature Verification

The main Aim of this project is to make Smart Attendance Management and Analysis System where after getting individual's signature of the student , the signature is scanned and converted into an image file. After segmentation, features are extracted by Contourlet transform and Moment Invariants from the signature. Verification of signature is made with the Database of student’s Signature and Excel sheet of absence and presence of student's attendance is generated.

Published by: Chauhan Hardika, Dr. Nehal Chitaliya

Author: Chauhan Hardika

Paper ID: V3I3-1150

Paper Status: published

Published: May 10, 2017

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Clinical importance of chlorophytum borivilianum in oligospermia

White Musli is a aphrodisiac drug . It have an natural biological environmental effect on neuro hormonal sexual axis.It maintains the equilibrium in mind and body.It reduces the sexual harassments like libido, impotency, infertility, and oligospermia.It increases sexual disireness , reduces fatigueness, maintains sexual satisfaction level, reduces the early ejaculation, increases sperm maturity, increases sperm number, increases sperm activity, reduces the oligospermia and infertility. It maintains the mental and physical equilibrium by homeostasis of blood include the regulation of temperature and the balance between acidity and alkalinity i.e ph balance of the body.

Published by: Dr. Dipak Swain, Dr. Vivek Mahalwar, Dr. K B Mahapatra, Dr. A. K. Das

Author: Dr. Dipak Swain

Paper ID: V3I3-1245

Paper Status: published

Published: May 8, 2017

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Research Paper

Unsupervised Method for Face Photo – Sketch Synthesis and Recognition

Today face recognition is a very important field in biometric identification. Face sketch recognition is one of the special type face recognition. In this paper, presents an unsupervised method for face photo- sketch recognition. The face photo- sketch synthesis has two main steps. One is edge detection for only recognition of face and secondly is for hair detection. In the recognition step, the artist sketch is compared with the generated sketch. PCA and LDA are used to extract features from the sketch images. The k-nearest neighbor classifier with Euclidean distance is used in the classification step. It has a useful application for digital entertainment and law enforcement.

Published by: Seena Jose, Prof. Shivapanchashari

Author: Seena Jose

Paper ID: V3I3-1177

Paper Status: published

Published: May 4, 2017

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A Smart Phone Based Accident Fall Detection, Positioning and Rescue System

This paper proposes the architecture of accident fall detection, positioning and rescue system that uses 3G networks. To perceive the fall detection algorithm, the angles acquired by the electronic compass and the waveform sequence of the tri-axial accelerometer on the smart phone are used as the system inputs. The obtained signals are used to produce an ordered feature sequence and then tested in consecutive way by the proposed cascade classifier for identification purpose. As soon as equivalent characteristic is confirmed by the classifier at the current state, it can continue to the state; contrarily the system will come back to the initial state and halt for the emergence of another feature sequence. When a fall accident event is diagnosed the victim’s position can be acquired by global positioning system (GPS) and forwarded to the rescue centre via 3G network so that immediate medical help can be provided.With the proposed cascaded classification architecture, the computational burden and power consumption issue on the smart phone system can be mollified. Moreover, known fall incident detection accuracy and reliability up to 92% on the sensitivity and 99. 75% on the specificity.

Published by: Keerthana .B, Nikita Pandya, Pooja Joshi, Neha .N, Dr. S. Sathiyan

Author: Keerthana .B

Paper ID: V3I3-1186

Paper Status: published

Published: May 4, 2017

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