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Research Paper

Development of protein rich product

The growing public awareness of nutrition & healthcare research substantiates the potential of phytonutrients such as polyphenols, saponins, essential amino acids, dietary fibers, flavonoids on their health benefits. Proteins are the major macronutrient required by the body. Protein Energy Malnutrition (PEM) develops in children whose consumption of protein and energy is insufficient to satisfy the body’s nutritional needs. 91% of Vegetarians in India suffer from PEM. Hence, there is a need to develop a Protein-rich product. Chickpea, Mung& Soy Flour was used in the preparation of chips. These chips were analyzed for their Nutritional, phytochemical, microbial and sensory parameters & a suitable packaging for the product was also developed. The present study showed that the product is a good source of protein (20%) and carbohydrates (62%). The product was liked very much by all the participants (score- 8). High quality 40 microns PET/MET was used as packaging material for the Product which are durable, heat resistant films with very good oxygen barrier properties.

Published by: Suhana Kulavoor, Grishma Ramugade, Subhashini M.

Author: Suhana Kulavoor

Paper ID: V5I1-1239

Paper Status: published

Published: February 6, 2019

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Research Paper

Occupational Therapy rehabilitation of postoperative hand injury cases and their functional independency

Occupational Therapy (OT) after revascularization/replant of hand injury is not available in all center. The prevalence of hand injury cases in India from road traffic incidences is about 30% and the total number of hand injuries would go higher upon adding the industrial injury cases. When primary repair isn't possible, tendon reconstruction is done. Kleinert (active extension, passive flexion) is a basic early motion program for rehabilitation of hand injuries. There have been significant innovations in therapy programme in different zones of tendon injuries in past. The aim of this study was to analyze the functional improvement after a postoperative regimen with the use of splints and Occupational Therapy. The objective is to determine the improvement in the Range of Motion (ROM) and muscles strength with Occupational Therapy (OT) along with home-based activities in hand reconstruction cases Design: Thirty-two patients with different tendon injuries were retrospectively enrolled in this study from one and a half year of routinely collected data. Gross grip, fine grip, and range of motion were measured using JAMAR, pinch O meter, and finger goniometer respectively. Statistically and clinically significant improvement was observed in muscle strength (gross and fine) and range of motion in these patients' hands after modified Kleinert splint, custom made splint and home base exercise in all patients (p <0.001 ). With OT, patients with hand reconstruction surgeries can recover their muscle strength and range of motion to a great extent under supervised therapy and make them self independence in all activities. This can be done through the use of simple home-based tools and occupational therapy exercises.

Published by: Deepak Ganjiwale, Ranjit Pathak, Amitabh Dwivedi

Author: Deepak Ganjiwale

Paper ID: V5I1-1256

Paper Status: published

Published: February 6, 2019

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Survey Report

A detailed survey on blockchain integration for connected cars

This paper provides a complete understanding of connected cars and Blockchain which are trending technologies here the discussion among the shared information among vehicles, V2V, V2X, Path planning and integration of Blockchain. Applications in which how the Blockchain is used for the connected car applications and how those operations can be performed with safety and security policy.

Published by: Illuru Phani Kumar, Aditya Kumar Sinha, Bhupendra Pratap Singh, Dr. M. Sumathi

Author: Illuru Phani Kumar

Paper ID: V5I1-1270

Paper Status: published

Published: February 5, 2019

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Survey Report

Securing cloud storage through face recognition mode

In many cases benefits given by a cloud server isn’t completely trusted by clients. Presently data are corrupted by an unauthenticated user with the help of employee’s. Generally, data are securely handled by Separate Organization but some employees sell their access specifiers to hackers for money due to single level Management and data are not made safe. To overcome this issue we move towards Advance Safe technology where data are downloaded by the user (admin or organization) with the help of face detection video mode when they accept the user request by recognizing their face among the hierarchy of employees and then the data is shared from one place to another. Here Encryption Algorithm is used for sharing data in a secure means by detecting a face in hierarchy.

Published by: Nadar Steffy Felicia Inbamani, Kumar P.

Author: Nadar Steffy Felicia Inbamani

Paper ID: V5I1-1263

Paper Status: published

Published: February 5, 2019

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Research Paper

Improving generalization in reinforcement learning on Atari 2600 games

Deep Reinforcement Learning (DRL) is poised to revolutionize the field of artificial intelligence (AI) and represents a crucial step towards building autonomous systems with a higher-level understanding of the world around them. In particular, deep reinforcement learning has changed the landscape of autonomous agents by achieving superhuman performance on board game Go, a significant milestone in AI research. In this project, we attempt to train a Deep RL network on Demon Attack – an Atari 2600 game and test the model on different game environments to investigate the feasibility of applying Transfer Learning on environments with same action space but slightly different state space. We further extend the project to use established Reinforcement Learning techniques such as DQN, Dueling DQN, and SARSA to examine whether RL agents can be generalized on unfamiliar environments by fine-tuning the hyperparameters. Finally, we borrow classic regularization techniques like 2 regularization and dropout from the world of supervised learning and probe whether these techniques which have received very limited attention in the domain of reinforcement learning are effective in reducing overfitting of Deep RL networks. Deep Networks are expensive to train and complex models take weeks to train using expensive GPUs. We find that the use of the above techniques prevents the network from overfitting on the current environment and gives satisfactory results when tested on slightly different environments thus enabling substantial savings in training time & resources.

Published by: Abhi Savaliya, Chirag Ahuja, Chirayu Shah, Sagar Parikh

Author: Abhi Savaliya

Paper ID: V5I1-1254

Paper Status: published

Published: February 4, 2019

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Research Paper

Experimental study on mechanical behavior of different grade M-sand concrete

In this paper were investigated in the comparison of compression strength and slump strength of M-sand and river sand. M-sand Rock crushed to the required grain size distribution is termed as manufactures sand (M-sand). The natural river sand was the cheapest resources of sand. The size of manufactured sand (M-Sand) is less than 4.75mm. A particle passing 75 microns, Sieve Size/ Granule Thickness IS Codes 150 microns - 4.75 mm and IS - 383: 1970. Then water absorption is 2.2. We are analyzed the specific gravity and moisture content of M-sand and river sand of concrete. Then we're prepared M-sand concrete moulded with help of mold die. The three grade of concrete we are prepared, they are M-sand grade M25, M-30, and M-35. After we conducted a compression test and slump test. Finally, we obtained in M25 grade of concrete; slump values and compression strength are more in comparison with M-sand till 7 days having 30.01 and 28 days we obtained 43.04. In M30 grade of concrete, slump values and compression strength are more in comparison with river sand. slump values of 170 mm > 150 mm (30 min) slump values of 140 mm > 100 mm (60 min) compressive strength 7 days 37.31N/mm2 > 32.02 N/mm compressive strength 28 days 48.5N/mm2 > 43.16 N/mm2. In M35 grade of concrete, slump values and compression strength are more in comparison with river sand. slump values of collapse is better than 170 mm (30 min) slump values of 150 mm > 110 mm (60 min) compressive strength 7 days 41.21N/mm2 > 37.41 N/mm2 compressive strength 28 days 54.32N/mm2 > 50.55 N/mm2.

Published by: R. Balasubramanian

Author: R. Balasubramanian

Paper ID: V5I1-1258

Paper Status: published

Published: February 4, 2019

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