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Research on Machine Learning

In machine learning, a computer first learns to perform a task by studying a training set of examples. The computer then performs the same task with data it hasn't encountered before. This article presents a brief overview of machine-learning technologies. The article below contains an introduction to the machine learning, the difference between machine learning and artificial intelligence and also seven steps of machine learning to better understand on how the machine learning works.

Published by: Amulya Ramesh

Author: Amulya Ramesh

Paper ID: V4I1-1302

Paper Status: published

Published: February 12, 2018

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Case Study

IOT Based Smart Car Parking System for Smart Cities

In recent times the concept of smart cities has become very popular. Thanks to the Internet of things the idea of the smart city now seems to be completed. Consistent efforts are being made in the field of IoT in order to maximize the productivity and reliability of urban infrastructure. Problems such as traffic congestion, limited car parking facilities, and road safety are being addressed by IoT. In this paper, we present an IoT based cloud integrated smart parking system. The proposed Smart Parking system consists of an on-site deployment of an IoT module that is used to monitor and signalize the state of availability of each single parking space. A mobile application is also provided that allows an end user to check the availability of parking space and book a parking slot accordingly. The paper also describes a high-level view of the system architecture.

Published by: Nazish Fatima, Akshaya Natkar, Pratiksha Jagtap, Snehal Tukaram Choudhari

Author: Nazish Fatima

Paper ID: V4I1-1332

Paper Status: published

Published: February 10, 2018

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Thesis

Design of Heat Recovery System in a Sheet Rock Plant

This report is about the design of heat recovery system in a sheet rock plant. A sheet rock is basically a gypsum board which is mainly used as a finish for walls, ceilings in households and commercial buildings. According to the given problem, during summer months the city water supplies to the manufacturing plant at a higher temperature of 900 F but during other months the temperature of water supply as 450 F. The de mand of water temperature is 85o F for the process so the city water is heated by natural gas burners when it’s in a storage tank. During the final stage of sheet rock production, heated air is used in a closed oven with sheet rock for the drying process. The air gets exhausted from aluminum stacks. This waste heat energy is being recovered it in the form of energy with the help of specially selected heat exchanger. The energy recovered will be minimising the need of natural gas burner which is to heat the city water receiving at a temperature of 450 F. This would reduce the need of natural gas to use as the main source of heating the city water for production of sheet rock. The heat recovery system would be compatible to work for 24 hr in a 6 days week frame till 8 months. The report will include the type of heat exchanger selected, pump for heat recovery and piping system with fittings and be routing for heat recovery. This would also include the cost involved in the whole additional process as installation, operational and maintenance cost with a calculated payback period of time for investment.

Published by: Abhishek Chaturvedi

Author: Abhishek Chaturvedi

Paper ID: V4I1-1222

Paper Status: published

Published: February 10, 2018

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Research Paper

Design of Attachment for Shock Absorbers Outertube

From the most high-grade raw material, they manufacture shock absorber and provides a smoother ride for the customer while driving. Shock absorber they manufactured is very efficient in performance. They improve the durability of the shock absorber by plating them chrome and nickel to prevent corrosion. The casting part of shock absorber body is imported. While machining on the casting body of shock absorber different defects occurs. Due to this many components were rejected. Causes due to which component was defected are milling width oversized and m6 tapping. In our research, we find some remedies to overcome these defects which occur during the machining processes. To overcome from defect of milling width oversized we are going to provide coolant arrangement in the current industry locator design. And to overcome from second defect M6 Tapping we are going to provide coolant arrangement in current drill tool. So, in this way, our project aim is to overcome these two defects and improve the production rate of the company by eliminating occurring defect due to machining.  

Published by: Nikhil A. Sangale

Author: Nikhil A. Sangale

Paper ID: V4I1-1352

Paper Status: published

Published: February 10, 2018

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Case Study

Class II Correction Using Twin Block Appliance: A Case Report

The aim of this study was to see the effect of twin block appliance in permanent dentition phase. Twin block from its inception and evolution of the appliance itself has been widely accepted as a more competent Class II corrector compared to earlier bulky monopoly appliances. The effect of the twin block functional appliances is mostly dent alveolar having a small skeletal effect. Functional appliances can be used successfully in growing patient with certain Class II malocclusion. It is dependent on patient’s compliance. It also simplifies the fixed appliance phase. A 13-year-old girl was treated with twin block appliance. The design of appliance and treatment results were demonstrated in following case report. In permanent dentition, twin block appliance produces a similar effect as in mixed dentition phase. With proper case selection and good patient cooperation, we can obtain a significant result with twin block appliance.  

Published by: Abdul Baais Akhoon, Prof. Mohammad Mushtaq

Author: Abdul Baais Akhoon

Paper ID: V4I1-1337

Paper Status: published

Published: February 9, 2018

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Research Paper

CNN Based Landmark Detection and Alzheimer’s Diagnosis Using Landmark Feature

One of the fundamental challenges in anatomical landmark detection, based on deep neural networks, is the constrained availability of medical imaging data for network mastering. To address this trouble, we present a two-stage task-oriented deep learning method to detect big-scale anatomical landmarks simultaneously in actual time using restrained education statistics. Especially, our technique includes deep convolutional neural networks (CNN), with every specializing in one particular project. In particular, to alleviate the trouble of limited training statistics, within the first stage, we endorse a CNN primarily based regression model the use of millions of image patches as input, aiming to examine inherent associations between nearby photo patches and target anatomical landmarks. to similarly version the correlations amongst image patches, in the second stage, we expand some other CNN model, which includes a) a fully convolutional networks (FCN) that shares the same architecture and community weights as the CNN used within the first stage and additionally b) numerous more layers to at the same time predict coordinates of a couple of anatomical landmarks. Importantly, our technique can jointly locate big-scale (e.g. hundreds of) landmarks in actual time. Using these landmark points we extract HOG and longitudinal features and using SVM to diagnose the Alzheimer’s disease.

Published by: Ayisha Shamna .K K, Jamsheera .K, Shameena .P P

Author: Ayisha Shamna .K K

Paper ID: V4I1-1240

Paper Status: published

Published: February 9, 2018

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