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An experimental investigation of natural soil stabilized with sewage sludge for flexible pavement

Soil is very important in civil engineering constructions. The poor engineering properties of the local soils may present many difficulties for construction and therefore need to improve their engineering properties. Stabilization techniques can be used to improve the properties of soil. Soil stabilization improves various engineering properties e.g. bearing capacity, compressibility, strength, and various other properties of soil. In this study the impact of Sewage Sludge to improve the strength of soil The soil was stabilized with Sewage Sludge in the stepped concentration of 5%, 10%, 15%, 20%, 25% and 30% by dry weight of the soil individually. All stabilized soil samples were also cured for 96 hours for the CBR test in a fully saturated condition. The test results indicate that the addition of Sewage Sludge enhances the percentage of grain size distribution but with addition of Sewage Sludge till 20% the LL, PL, PI and decreases, while these parameters further increase in this limit beyond i.e. 20% to 30% of Sewage Sludge, but in the case of the optimal percentage of Sewage Sludge at which maximum CBR is achieved is selected, Specific gravity value of Natural Soil is 2.57, but a percentage of Sewage Sludge is increased, specific gravity value decreases gradually from 2.57 to 2.44 with increase in percentage of Sewage Sludge from 0 to 30% and value of raw soil is achieved as 1.85 gm/cc at OMC of 13.65%. It got increased to 1.93 gm/cc at OMC of 12.30 % when Sewage Sludge is increased from 0 to 20% is effective beyond also there is decreasing in MDD from 1.93 gm/cc at OMC of 12.30% to 1.89 gm/cc at OMC of 13.20% when Sewage Sludge is increased from 20 to 30%. The CBR value increases with the addition of Sewage Sludge till 20%, while it decreases beyond the limit 20% to 30% with the addition of Sewage Sludge. For both soaked and unsoaked conditions.

Published by: Sumi Shrivastava, P. K. Singhai, Veena Mandlekar

Author: Sumi Shrivastava

Paper ID: V6I2-1160

Paper Status: published

Published: March 5, 2020

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Research Paper

Fruit quality detection using machine vision techniques

Machine vision techniques are now widely used to detect the quality of fruits. Image processing is usually the first step in detecting the quality of fruits. The process starts by capturing the image of the fruits using raspberry pi. Then, the image is transmitted to the processing stage where it can extract the features of the fruit like shape, size, and color. These processes are done using image processing. It helps to identify and compare the fruit shape, size, and color with the trained datasets. This is done during the training and testing stage. A diversity of methods for automatic separation of fruits is developed. Artificial Neural Network is the one that helps to segregate the fruits based on the quality such as good, moderate and rotten fruit. The existing system can only separate the fruits into good and rotten one with an accuracy of 87.4% but our proposed system is capable of separating the fruits into good, moderate and rotten one with an accuracy of 94.12%.

Published by: S. Krishna Kumar, J. Kaviya, G. Dilip Prakash, K. Srinivasan

Author: S. Krishna Kumar

Paper ID: V6I2-1148

Paper Status: published

Published: March 5, 2020

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Research Paper

Bitcoin Prices (Statistical Analysis)

In this paper with the help of mathematical tools, I will analyze how Bitcoin prices have fared over the span of 3 years from January 2017 to December 2019. The tools will help to forecast the future value of bitcoin but the values forecasted do not consider any external factors just makes an estimate according to the previous values. We will also use time series tools like moving averages to find a general trend of the prices of bitcoin.

Published by: Tanmay Gupta

Author: Tanmay Gupta

Paper ID: V6I2-1159

Paper Status: published

Published: March 5, 2020

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Research Paper

Cloud based web integrated development environment

The Cloud IDE is capable of providing a user with higher-end realistic features over the web interface that facilitates remote development. It allows user to initiate and develop applications nevertheless the bottleneck faced by environmental setup, relying upon personal devices, configuration, backup, etc. The principle of interaction between Frontend and Backend follows the real-time Message Queuing (MQ) system which enables user to carry out the work even in poor network. Moreover the system come out with advanced container technology that serves a comparatively large number of users at a time with the maximum speed of environment creation, request handling and program execution. On the other hand, the Extension development provision enables the creation and share a variety of tools to be used on the IDE including the language compilers.

Published by: S. Saparna, Manoj R., Dhivyananthan R., Kanagasabapathy T.

Author: S. Saparna

Paper ID: V6I2-1147

Paper Status: published

Published: March 5, 2020

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Research Paper

Brain Tumor Analysis using Convolutional Neural Network with MRI Images

Brain Tumor Analysis plays a vital role in detecting the tumored cells of the brain. A brain tumor can become very lethal at its advance stages. It can easily spread to other parts of the brain and affect the healthy cells of the brain as well. They reproduce uncontrollably. Hence, detection at early stages is very essential in treatment for improvement of the life expectancy of the patients. However, the detection of the tumor is a difficult and challenging task since the tumor possesses complex characteristics in appearance and boundaries. Magnetic resonance imaging (MRI) is being used extensively for the detection of brain tumors that requires segmenting huge volumes of 3D MRI images which is very challenging if done manually. It is the most commonly used medical image for brain tumor analysis. So, we are using MRI images for detecting the brain tumor. In this system, we are going to use Keras and Convolutional neural network(CNN) for the automatic segmentation and detection of a brain tumor using MRI images. It is considered as one of the efficient methods for detection of brain tumors. It has one or more convolutional layers and is used mainly for image classification and segmentation techniques. It helps in achieving high accuracy and is optimal as well.

Published by: Deepalakshmi K., Priyavadhana S. R., Hannah Elezebath M. A., Jetlin C. P.

Author: Deepalakshmi K.

Paper ID: V6I2-1144

Paper Status: published

Published: March 5, 2020

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Research Paper

Implementation of Artificial Intelligence in Motels

The most essential requirement of everyone’s lives is food .In this research paper I am writing about an idea of implementation of Artificial techniques in the motels by which food is served replacing the labor. Also to reduce the wastage caused by the humans while preparing food in the hotels.

Published by: Keerthana P.

Author: Keerthana P.

Paper ID: V6I2-1152

Paper Status: published

Published: March 4, 2020

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