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Research Paper

Prediction of Pneumonia using deep learning

The project is to classify pneumonia by processing the image of chest X-ray using diverse deep learning algorithms. For classification purpose, we have to develop an algorithm which can most accurately predict on a validation set of chest X-rays. Deep learning is very helpful in automatically discovering chest diseases at the experts level, providing the two Liberian radiologists with some respite and used for saving countless lives potentially worldwide. The problem is solved using Convolution neural networks[9]. Convoluted neural networks are used to classify where each neuron is tightly connected to other neurons. Inception network was used in the development of CNN classifiers. Inception network was heavily engineered. It used a lot of tricks to improve performance in terms of speed and accuracy. With much more robust and large dataset our project can intervene in all domains.

Published by: A. Raghavendra Reddy, G. Sai Ravi Teja, D. Sai Tej, P. Vinod Babu

Author: A. Raghavendra Reddy

Paper ID: V5I2-1546

Paper Status: published

Published: April 10, 2019

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Review Paper

The future of food preservation: Nanotechnology

Nanotechnology has been used to treat illnesses for a long time. It has been successfully employed as a means of drug discovery. However, it's used in food preservation is yet to become commonplace. Through this review paper, the authors wish to throw light on the application of nanoparticles in the preservation of food, to improve food color, texture as well as flavor. We also explore the use of nanotechnology in the encapsulation of the foodstuffs as a means of preservation. The article includes details about the usage of nanoparticles in the nutraceutical industry as well as its usefulness as a nanosensor. The purpose of the paper is to make use of nanotechnology in the food industry a well-known application of nanoparticles. It will be useful for professionals working in the food industry or entrepreneurs who wish to venture into the field of food preservation. Scientists may use the information and data provided in the paper to further their research.

Published by: Pragati Gupta, Anjika Shukla, Ujjawal Sharan, Anand Prem Rajan

Author: Pragati Gupta

Paper ID: V5I2-1823

Paper Status: published

Published: April 9, 2019

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Research Paper

An energy efficient approach for data aggregation in wireless sensor networks based on sink mobility

A network that does not include any central controller and allows nodes to enter or leave the network at any time is known as a wireless sensor network. There are very small sized nodes deployed in these networks in large areas. The energy consumption of the nodes in these networks is a major concern since it directly affects the lifetime of the network. These dead node cause several problems. To enhance the network lifetime mobile sink is introduced which improve network performance. But mobile also leads to another challenge such as mobile sink scheduling and (re)routing. The complete network is divided into fixed size clusters and based on the energy and distance, cluster heads are chosen from the clusters. The remaining nodes of the cluster are considered to be individual. Several clustering algorithms have been designed by researchers which can be broadly categorized based on the manner in which clusters are formed and the kinds of parameters included during the selection of cluster heads. This research focuses on aggregating the data from cluster heads by deploying multiple mobile sinks. The bee colony algorithm is used to make the base station mobile. The simulation of the proposed technique is performed in MATLAB and results are analyzed in terms of various parameters.

Published by: Baljinder Singh, Amit Verma, Manit Kapoor, Dr. Naveen Dhillon

Author: Baljinder Singh

Paper ID: V5I2-1755

Paper Status: published

Published: April 9, 2019

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Review Paper

Geofencing for disaster information system

Due to the lack of effective and coordinated disaster management system which consists of the stages like disaster mitigation, preparedness, response, and recovery has led to both the increase in the loss of both life and property. The paper proposes an effective disaster information system which uses the geofencing technique so as to detect the movement of users. This technique creates a geofence around the user and thus monitors the user’s entry and exit from the fence. This model uses a K-Nearest Neighbour (KNN) algorithm along with real-time data collected from smartphones. For crowd disaster mitigation and real-time alert to avoid an occurrence of a stampede, this android application is an easily deployable context-awareness mobile Android Application Package. The application provides high accuracy when the user is in the fence.

Published by: Diksha Kewat, Vaishnavi Tonpe, Kiran Baxani, Dr. Sanjay Sharma

Author: Diksha Kewat

Paper ID: V5I2-1813

Paper Status: published

Published: April 9, 2019

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Review Paper

A novel approach for active safety system

In this modern day automotive world, the occurrence of accidents is much more due to several factors. This can be avoided when the driver is alert. So a system has to be developed which gives the driver the information about the nearby vehicles whether it is a danger, no danger, potential danger. This paper presents you how to classify the vehicles in its ROI and categorize their stage of danger. Specifically, stereo cameras and Millimeter Wave (MMW)-radar are fused to help the driving ego-vehicle. Cameras are used to identify near lateral dynamic objects and MMW radar to detect far longitudinal objects. This process is simulated using python using CV2 library, numpy library.

Published by: Devaharsha Meesarapu, V. V. Sai Rama Datta, G. Sai Krishna Chaitanya

Author: Devaharsha Meesarapu

Paper ID: V5I2-1799

Paper Status: published

Published: April 9, 2019

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Research Paper

Optimizing the level of pressmud compost for bhendi

A field experiment was conducted in a sandy clay loam soil with bhendi as the test crop (cv. Arka Anamika) in Sivapuri village, Chidambaram Taluk, Cuddalore district, Tamil Nadu. to study the effect of pressmud compost on plant growth, yield attributes, yield and nutrient uptake by bhendi. The presumed compost was applied @ 5, 7.5, 10, 12.5, 15, 17.5 and 20 t ha-1 as a basal dose. All the experimental plots received a common fertilizer schedule of 100:60:50 kg NPK ha-1 (RDF). The results of the experiment clearly revealed that application of pressmud compost had a significant influence on growth, yield, and uptake of nutrients. Increasing levels of pressmud compost gradually increased the growth attributes. The significantly maximum value was recorded with the application of 15 tonnes of pressmud compost ha-1. Thereafter, there was no significant improvement. A similar trend was observed in the yield attributes and yield of bhendi. Regarding nitrogen, phosphorus and sulphur uptake by plant and fruit, significantly higher values were recorded with 15 tonnes pressmud compost. However, the subsequent increase in pressmud compost application failed to attain the level of statistical significance.

Published by: K. N. N. Arvindh Ramnathan, Dr. P. Poonkodi, Dr. A. Angayarkanni

Author: K. N. N. Arvindh Ramnathan

Paper ID: V5I2-1796

Paper Status: published

Published: April 9, 2019

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