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Kinetic study of growth for high biomass production using Chlorella Pyrenoidosa

In this paper, biomass production parameter optimization was performed using Chlorella medium by design of experiment (DOE) with the help of Qualitek-4 software with bigger is better as quality characteristics with four media components and they are studied at three levels in submerged culture condition. I have studied four parameters like pH, Na2CO3, NH4Cl, and NaNO3 with three levels. These factors are optimized based on their S/N ratios are obtained from Qualitek-4 software and their significant individual interactions, and interactions with each other have been studied. During experimental studies, I had worked on the optimization of several parameters. It has found that there was an enhancement of chlorella pyrenoidose by 6% in chlorella medium

Published by: Atul Chavan

Author: Atul Chavan

Paper ID: V5I2-2068

Paper Status: published

Published: April 26, 2019

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Research Paper

Feature extraction in emotion recognition: An analysis of emotion using Praat

Machine learning is being used to help robots to detect human emotions. Speech is an important tool to recognize emotion. It has been observed after reading different research papers from different researchers that pitch and intensity are major features to detect the emotion of sound. Consequently, the present research study is oriented towards discussing aspects pertaining to emotion recognition using speech. This paper presents the illustration of emotions that can be recognized by the speech of a person. Future research will be focused on enhancing features like energy, frequency, and amplitude of a speech.

Published by: Kunal Kapoor, Lokesh Kumar, Kshitiz Sagar Verma, Kunal Sehgal

Author: Kunal Kapoor

Paper ID: V5I2-2108

Paper Status: published

Published: April 26, 2019

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Research Paper

Fire detection and extinguisher robot

Fire detection and Extinguisher Robot is a Hardware-based model used to extinguish the fire during fire accidents. It works in two modes autonomous mode and manual mode. In manual mode, the robot can be operated by use of remote control and live streaming camera. In autonomous mode, Robot has been developed which features to move in the direction with respect to the fire intensity. The flame sensing capability of the robot is varied by the flame sensor, above which the robot starts responding to the fire. The temperature sensor provides a backup to the flame sensor if needed in vast circumstances. The most added advantage of this Robot is that it turns ON automatically as it detects the fire around its surroundings, using flame sensor and tries to extinguish it by moving in the direction with respect to the fire. The Robot shield is coated with aluminum boards that are capable of withstanding very high temperatures. The Robot finds its applications in Rescue operations during fire accidents, where the possibility for servicemen to enter the fire-prone areas is very less and also during wars to perform rescue functions.

Published by: Pruthvi R., Mohan Varma K., Vinayaka L. S., Veeresh M., Vani A.

Author: Pruthvi R.

Paper ID: V5I2-2033

Paper Status: published

Published: April 26, 2019

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Research Paper

Cost effective optical mark recognition software for educational institutions

Optical Mark Recognition (OMR) is a technology for effectively extracting data from filled-in fields or bubbles on printed forms. The current systems available for OMR are very expensive and they detect only a marking scheme. Moreover, the image processing techniques used for scanning the OMR sheet also consumes a lot of time and is quite complex, as it includes various restrictions related to the positioning of the sheet. In this paper, a solution to this problem is proposed, where an OMR system is developed using a scanner or a multifunctional printer as an input. The quality of the OMR sheet used in this system is low cost and easily available to any educational institution. The image processing techniques are implemented with the help of PyCharm IDE that not only helps to detect various marking schemes like bubble shape mark and tick mark but also verifies the answers in the sheet and displays the total marks obtained by the student, in a more efficient manner. In order to make the system user-friendly, the GUI of the system is improved and personalized by integrating an online website with the OMR software that displays the results of individual student.

Published by: Vidisha Ware, Nithya Menon, Prajakti Varute, Rachana Dhannawat

Author: Vidisha Ware

Paper ID: V5I2-2089

Paper Status: published

Published: April 26, 2019

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Research Paper

Supervised vehicular operation using WAN

The need for vehicular supervision system is of the utmost need due to the sheer number of vehicles plying every day on our roads. With the rise in numbers of vehicles, there is also an increase in the need to prevent potentially fatal on-road incidents. Drowsiness and fatigue are large contributors to most on-road accidents. Prevention of such accidents can be achieved using a drowsiness detection system and drivers emotion recognition. Such a system employs recognition of facial expressions to identify emotions using a camera. The feed from the camera is processed to obtain instances of drowsiness or stress. Accordingly, tasks can be triggered such as slowing down or stopping the vehicle.

Published by: Deepak Kathoria, Noor Alleema, Srijan Mandal, Prabhat Kumar

Author: Deepak Kathoria

Paper ID: V5I2-2084

Paper Status: published

Published: April 26, 2019

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Others

Sensor navigation for blind

The fundamental point of this paper is to grow the electronic travel help for the visually impaired and outwardly debilitated people on foot by rising into the ultrasonic innovation. The paper speaks to an inventive task plan and execution of an Ultrasonic Navigation framework so as to furnish completely programmed deterrent evasion with capable of being heard warning for visually impaired people on foot. This visually impaired direction framework is protected, dependable and practical.

Published by: Naveen C., Noor Alleema N., Priyadarshini K., Thiluzhika R., Umang Sharma

Author: Naveen C.

Paper ID: V5I2-2083

Paper Status: published

Published: April 26, 2019

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