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Review Paper

Automatic opening and closing of railway gates and signaling in railways using IoT

The Internet of Things (IoT) is a group of devices which are connected together in the network. It is used in sound vibrator and ZigBee transceiver which will receive frequency of the vibration and the time from which the train reaches the sensor from the server. In this, we are using a sound vibrator which will detect vibrations from the track and the signal is transferred to the gear motor and the gate will get closed automatically. When the train passes the gate another sound vibration sensor is fixed at another end and it will transfer the signal to the gate and gate will open automatically. Here the additional features added are we can calculate the current speed of the train and we can also track the track damage. The main objective of this work is to provide automatic closing and the opening of gates and railway system. We can avoid careless mistakes done by the gatekeeper and we can reduce manpower in the railway system.

Published by: Dinesh Kumar S., Prem Kumar R., Venkatesan G., Vinston Raja R.

Author: Dinesh Kumar S.

Paper ID: V5I2-1304

Paper Status: published

Published: March 16, 2019

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Research Paper

Bunch ensemble with averaged co-association matrix maximizing the expected margin

The problem considered is cluster analysis with the usage of the ensemble approach. The paper proposes a method for finding optimal weights for the averaged co-association matrix applied to the construction of the ensemble partition. The main idea is to find such weights for which the expectation of ensemble margin takes its maximum value. A latent variable pairwise classification model is used for determining margin characteristics dependent on cluster validity indices. To construct the ensemble partition, we apply a minimum spanning tree found on the averaged co-association matrix as an adjacency matrix. The efficiency of the method is confirmed by Monte-Carlo simulations with artificial data sets.

Published by: A. V. S. N. Kaushik, D. Harsha vardhan, Dr. M. Rama Krishna Murthy, B. Sai Chaitanya, G. Nikhil Das

Author: A. V. S. N. Kaushik

Paper ID: V5I2-1303

Paper Status: published

Published: March 16, 2019

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Research Paper

Extended hybrid approach for detecting spammers on Twitter

One of the biggest social networks is Twitter for providing message posting and use direct message services via “tweets”.366 million currently active users on Twitter, Is the second largest space to share common news or message post. These features are also used by spammers on Twitter, spammers are not new on Twitter. spammers must be detected in improving the quality of Twitter message services. In this spammer detected by using metadata, content, interaction, and community-based features methods. Tweet meta information extracted and analyzed based on user-id, tweets,tweet-time and tweet-type. Content Features are extracted based on user posting content with URL, Mention-tags and hash-tags. Interaction and community-based features are analyzed by following and follower information. The proposed approach to introducing network-based features for spammer ratio detection by using unique IP address based user classification. Spammers can be detected by analyzing their tweets based on the extended hybrid approach by using the random forest, decision tree, and Bayesian network on the Twitter dataset that has benign users and spammers.

Published by: Subash G., S. Yuvalatha, V. Lenin Kumar, G. Manimegalai

Author: Subash G.

Paper ID: V5I2-1295

Paper Status: published

Published: March 16, 2019

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Review Paper

Enormous information for Internet of Things

With the quick advancement of the Internet of Things (IoT), Big Data innovations have risen as a basic information examination instrument to convey the learning inside IoT frameworks to all the more likely meet the reason of the IoT frameworks and bolster basic leadership. In spite of the fact that the point of Big Data investigation itself is widely examined, the dissimilarity between IoT areas, (for example, social insurance, vitality, transportation furthermore, others) has disconnected the advancement of Big Data approaches in each IoT area. Along these lines, the common understanding crosswise over IoT areas can propel the advancement of Big Data examine in IoT. In this work, we along these lines direct a study on Big Data innovations in various IoT areas to encourage and animate information sharing over the IoT spaces. In light of our audit, this paper talks about the likenesses and contrasts among Big Data advances utilized in various IoT spaces, proposes how certain Big Data innovation utilized in one IoT area can be re-utilized in another IoT space, furthermore, builds up a reasonable system to plot the basic Big Data advancements over all the audited IoT spaces.

Published by: P. Mounika, N. Nalini

Author: P. Mounika

Paper ID: V5I2-1292

Paper Status: published

Published: March 16, 2019

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Research Paper

A novel prototype to secure network using malware detection framework against malware attack in wireless network

A new and novel proposed algorithm based on malware detection has been used that overcomes the disadvantages of the existing algorithms and helps to eliminate viruses and worms from entrusted environment. In the wireless networks suffers from various spyware programs that prevents access to legitimate users who obtains services from target web server. In our proposed prototype helps to authenticate the sender to make the dynamic rule set to avoid the formations of unavailable networks which any user who obtain web services. In our proposal architecture diagnose malware whether malware based data has been really being sent to the valid user or is it being morphed by the attacker in the middle. The proposed algorithm has been tested against various existing algorithms to study how effectively the algorithm is working, and how effectively it is overcoming the drawbacks of the present malware detection algorithms. The algorithm is projected to serve the purpose of prevention of being used malware based programs to drop it by the user and also to identify that the non-infectious message is reaching only to the valid user.

Published by: G. Jagadish, L. Jaswanth, K. Sowjanya, P. Sri Harsha, M. Nikhil Kumar

Author: G. Jagadish

Paper ID: V5I2-1278

Paper Status: published

Published: March 16, 2019

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Research Paper

Development of particle reinforced composite by plastic and e-waste

The main aim of this project is to develop Particle reinforced composites. Thermoplastic is taken as matrix material. Thermosetting plastics and E-Waste glass powder of 60µm is taken as particles. The formed structure exhibits high strength, low mass density and less weight compare to wood and steel. Due to its superior performance, the composite reinforced materials are mainly used indoors, frames, the automobile industry, especially for vehicle body applications. In this project particle reinforced Composite formed from Plastics and Electronic wastes. A formed specimen is subjected to tensile, hardness and bend test. It exhibits high tensile and bending strength.

Published by: A. Kanagaraj, C. Franciskennathamreth, M. Ajithkumar, V. Anandh, R. Nagaraj

Author: A. Kanagaraj

Paper ID: V5I2-1320

Paper Status: published

Published: March 16, 2019

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