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Research Paper

Replacement of fine aggregate by using glass material in concrete

Glass powder (GP) used in concrete making leads to a greener environment. In shops, damaged glass sheets & sheet glass cuttings are going to waste, which is not recycled at present and usually delivered to landfills for disposal. Using GP in concrete is an interesting possibility for the economy on waste disposal sites and conservation of the environment. This project examines the possibility of using GP as the fine aggregate replacement in concrete. Natural sand was partially replaced (0%-20%) with GP in concrete. Compressive strength (cubes and cylinders) up to 28 days of age were compared with those of high-performance concrete made with natural sand.

Published by: Ratilal Narayan Patil, Dr. S. L. Patil, Chetan Pandurang Patil, Suvarna Namdev Patil, Pratima Tedgya Valvi, Puja Vishwas Gade

Author: Ratilal Narayan Patil

Paper ID: V5I2-1626

Paper Status: published

Published: March 30, 2019

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Others

P2DB-chat

The project titled peer-to-peer distributed blockchain database messaging presents the development of an instant messaging application based on the concept of peer-to-peer using Inter Planetary File System (IPFS) and Blockchain. The P2P architecture is a decentralized architecture, where neither client nor server status exists in a network. Every client act as a server. This report describes one possible way to implement a chat system using a Peer-To-Peer model instead of a client/server model without the need to sign up for the specified service to be able to use it.

Published by: Kesavan S., Charles R., Raja Prithya P., Rajavel V., B. Kiruba

Author: Kesavan S.

Paper ID: V5I2-1615

Paper Status: published

Published: March 29, 2019

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Review Paper

Construction of predictive modelling for cardiac patient using probabilistic neural network

Coronary Artery Disease (CAD) is a major disorder in heart rhythm invoices the reduction or blockage of blood flow due to the narrow artery which results in coronary artery disease Our project is to investigate and detect the occurrence of coronary artery disease (cardiac block) using a probabilistic neural network. We would apply the probabilistic neural network to CT Images and, Feature extraction by using the Gray Level Co-Occurrence Matrix (GLCM). Image recognition and image compression are done by using the Gaussian bilateral filter method and also large dimensionality of the data is reduced. Automatic cardiac block classification is done by using a Probabilistic Neural Network (PNN). The segmentation process is done by using the K-means clustering algorithm and also detects the cardiac block spread region. PNN is the fastest technique and also provide good classification accuracy.

Published by: Nivetha P., Keerthi S., Kamalesh S.

Author: Nivetha P.

Paper ID: V5I2-1578

Paper Status: published

Published: March 29, 2019

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Research Paper

Net metering based bi-directional power flow system and power quality improvement using multilevel inverter

Recent advancements in Power Electronics converters has led to the development of Multilevel Inverters that has proved to be one of the most promising solutions for the medium voltage, high power applications. Multilevel Inverters are considered to be the best available choice for the Grid-connected Photovoltaic Modules (PV) as they (PV Modules) comprise of several sources on the DC side. By the use of MLI, output with high quality and with less harmonic distortions can be obtained which can further be improved by increasing the level of the Multilevel Inverter. This paper presents a model of a 15-level Cascaded H-Bridge MLI interfaced suitably with a Boost Converter and PV arrays. The proposed 15-level inverter is modeled and simulated in MATLAB 2018a using Simulink and Sim Power System toolboxes. Passive filters for power quality improvement is also used at the output stage of Multilevel Inverter.

Published by: Himanshi Sikarwar

Author: Himanshi Sikarwar

Paper ID: V5I2-1558

Paper Status: published

Published: March 29, 2019

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Research Paper

Tracking the prisoner location and escape prevention

The main aim of the project is to track the prisoner whether he or she is inside or outside the prison by using RSSI(Received Signal Strength Indication) and using GPS. The location of the prisoner can be viewed by jailor wherever and whenever by using IOT device. If the prisoner is trying to move outside the jail it automatically indicates through buzzer in the control room based on the signal strength. When the signal strength is low the device automatically activates the neuron simulator. If the prisoner is trying to break the module is sensed by the vibration sensor, it will automatically produce alarm in the prisoner section and control section.

Published by: Venkateswararao P., Vengatesh D., Vetrivel R., Haresh R., Ajay Karthik B.

Author: Venkateswararao P.

Paper ID: V5I2-1608

Paper Status: published

Published: March 29, 2019

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Crime scene prediction and analysing its accuracy with frames using deep neural network

Crime scene prediction without human intervention can have an outstanding impact on computer vision. In this paper, we present DNN in the use of a detect knife, blood, and gun in order to reach a prediction whether a crime has occurred in a particular image. We emphasized the accuracy of detection so that it hardly gives us the wrong alert to ensure efficient use of the system. This paper use Nonlinearity ReLu, Convolutional Neural Layer, Fully connected layer and dropout function of DNN to reach a result for the detection. We use Tensorflow open source platform to implement NN to achieve our expected output. This system can achieve the test accuracy of 90.2 % for the datasets we have that is very much competitive with other systems for this particular task.

Published by: Devishree D. S., Divakar K. M., Ashini K. A., Arnav Singh Bhardwaj, Sheikh Mohammad Younis

Author: Devishree D. S.

Paper ID: V5I2-1604

Paper Status: published

Published: March 29, 2019

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