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Narcolyser

As the use of drugs is becoming a controversial issue today in the society, we discussed it as a group, to explore this issue further as we possess a high interest in how drugs cause an effect on the civil group. The proposed design ‘Narcolyzer’ is a device which is used to detect the presence of narcotic drugs through saliva/breath. If drug usage is detected, its confirmation is done by a blood test which is similar to a blood glucose test. The main objective of the design is to make it easier for the police to detect the drugs by making the process of taking samples easier and obtaining results faster, without causing much inconvenience and time delay to the passengers. The device is based on sensor technology and is easy to handle & maintain and able to provide accurate results.

Published by: Uthara Renjith, Anupama K. N., Athul A. S., Chandichan Alex

Author: Uthara Renjith

Paper ID: V5I3-1801

Paper Status: withdrawn

Submitted: June 7, 2019

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Research Paper

Detection of suspicious URLs using machine learning

The increasing volume of malicious content in social networks requires automating methods to detect and eliminate malicious content the URLs. This shows a supervised machine learning classification model that has been built to detect malicious content in online social networks. Multisource features are used to detect social network posts that contain malicious Uniform Resource Locators (URL's). These URLs could direct users to websites that contain malicious content, drive-by download attacks, phishing, spam, and scams and some other problems. For, the data collected from such URL's, the Twitter streaming application programming interface (API) was used.

Published by: Ashwini Mahajan, Darshana Patil, Ritesh Bhojwani, Lalit Mahajan, Niranjan Dhake

Author: Ashwini Mahajan

Paper ID: V5I3-1804

Paper Status: published

Published: June 7, 2019

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Survey Report

Usage of incremental approach in the formulation of collective behavior: A survey

The work of collective behavior is to understand and how actors behave in a social networking environment. A large population is involved in social media like Facebook, Twitter, Flicker, and YouTube that provide opportunities and challenges to study collective behavior on a large scale. In this paper, we aim to learn to predict collective behavior in social media. Consider for given information about some actors, how can we infer the behavior of unobserved actors in the same network? However, Connections in social media is not homogeneous. A social-dimension based approach which represents the relations associated capture prominent interaction among different actors to show effective in addressing the heterogeneity of connections included in social media. The social media has are normally of large size, involving hundreds of thousands of actors. The scale of these networks entails scalable learning of models for collective behavior prediction. We propose an edge-centric clustering scheme to extract sparse social dimensions. With sparse social dimensions, the proposed approach can efficiently handle millions of actors while describing a comparable prediction performance to other non-scalable methods.

Published by: Vijay Kumar S.

Author: Vijay Kumar S.

Paper ID: V5I3-1784

Paper Status: published

Published: June 7, 2019

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Survey Report

Survey on forgery detection of image

The advancement in the digital media world has paved the path for many critical security issues that doubts the integrity of the digital media with the availability of sophisticated and high-resolution image capturing device and various image processing or editing tool and software’s the images can be manipulated or altered easily. Thus resulting in the forgery of the image.

Published by: Sruthi Lekshmi K.

Author: Sruthi Lekshmi K.

Paper ID: V5I3-1772

Paper Status: published

Published: June 7, 2019

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Research Paper

Antimicrobial activity of Roccella montagnei against pathogenic microorganisms

An attempt was made to study the antimicrobial activity of saxicolous lichen Roccella montagnei under invitro conditions. The antimicrobial activities of Methanol, Ethanol, Ethyl Acetate and Acetone extracts of Roccella montagnei were assayed against nine pathogenic microorganisms using standard welldiffusion method. The Acetonic extract was found most effective antibacterial whereas the Ethanolic extract was found most effective antifungal against most of the organisms. The maximum inhibition zone was recorded in E.coli with inhibition zone 34 mm. Fungal pathogens showed their inhibition zones in varying levels as 32 mm in Candida albicans and Fusarium oxysporium and 30 mm in Aspergillus niger. The present study reveals that extracts obtained from R. montagnei have potential compounds that can lead to control of human pathogenic microorganisms in the future.

Published by: Devashree, Anand Pandey, Anupam Dikshit, Sanjeeva Nayaka

Author: Devashree

Paper ID: V5I3-1769

Paper Status: published

Published: June 7, 2019

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Research Paper

Intelligent chatbot using machine learning

The aim is to create a program chatbot will be designed to simulate an intelligent conversation with one or more human users. The ability of this program or the chatbot will be to learn and gather knowledge on its own, and with every passing conversation it will grow itself to be more intelligent and reply with sophistication and charming manner. The main idea behind this whole program is to teach the program to learn, adapt and respond accordingly on its own. We will be using some basic databases to give it a headstart but after that it will do its work on its own. The users will interact with the bot and find it to be not much sophisticated but after using it for few days the bot will learn and find a pattern and will reply with more perfection and better understanding on the subject.Our final aim is to implement this program on facebook as a messenger app for companies which deals with high user request and questions and find it difficult to help everyone, but this as can do the work for them and that too with multiple users at the same given time.

Published by: Tridib Chakraborty, Trishita Ghosh, Chowdhury Md Mizan, Indrani Dey

Author: Tridib Chakraborty

Paper ID: V5I3-1755

Paper Status: published

Published: June 7, 2019

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