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Research Paper

CARKART: A Machine Learning and Augmented Reality application to ease car retailing

CarKart is a user-friendly futuristic android application with Machine Learning and Augmented reality capabilities. It enables the user to upload the image of the car which can be processed to detect the foremost probable car. The machine learning model is trained on the Stanford car dataset containing 196 classes of cars. Hence, this problem is categorized as a multi-label classification problem. Additionally, the users are going to be able to view various models of cars available within the market alongside their specifications and video feed, Fetch a list of nearby showrooms and repair centers, set service reminders, provide their feedback, survey on used cars, check their availability and costs, be able to contact car dealers, thereby introducing the concept of retail. The app also displays the live-size 3D prototype of certain selected car models using Augmented Reality. So, the user can consider all the essential factors before arriving at an informed decision as per their requirement.

Published by: Mrunalini M., Kasthuri C. M., Pranjal Sharma, Gururaj S. P.

Author: Mrunalini M.

Paper ID: V7I4-1407

Paper Status: published

Published: July 19, 2021

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Research Paper

Facial emotion recognition and detection

Face and Emotion recognition presents a challenging problem in the field of image analysis and computer vision. The security of information is becoming very significant and difficult. Security cameras are presently common in airports, offices, universities, ATMs, and banks, and in any locations with a security system. Face recognition is a biometric system used to identify or verify a person from a digital image. The Face recognition system should be automatically able to detect a face and its emotions. This system would be able to perform for multiple people at a time.

Published by: Pranav S., Praveen C., Niveditha C. B., Asha Rani Borah

Author: Pranav S.

Paper ID: V7I4-1385

Paper Status: published

Published: July 19, 2021

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Review Paper

Seed Vigor Testing in Cotton: A Review

Attaining seed and seedling vigor in cotton is a goal of both researchers and producers. By separating and defining components of seed and seedling vigor, progress can be achieved. Seed vigor should be distinguished from seed viability and defined in terms of low degree of seed deterioration. Being a connecting link between two generations of plants or crops, seed is a carrier of new technology or new improvements made by the breeders, seed vigour is an important parameter, needs to be assessed primarily to supplement germination and viability tests to gain insight into the performance of a cotton seed lot in the field or in storage. Seeds are prime factor for crop production, human nutrition, and food security. The key component of the performance of crop seeds is the complex trait of seed vigour. In Agriculture, the crop yield and resource use efficiency depend on successful plant establishment in the field, and it is the vigour of seeds that defines their ability to germinate and establish seedlings rapidly, uniformly, and robustly across diverse environmental conditions prevailing in region. Improving vigour to enhance the critical and yield-defining stage of crop establishment remains a primary objective of the agricultural industry. The knowledge of the regulation of seed germination has developed greatly in recent decades. However, the understanding of the basis of variation in vigour and therefore seed performance during the establishment of crops remains limited. Here we consider seed vigour at an eco-physiological, molecular, and biomechanical level. We discuss how some seed characteristics that serve as adaptive responses to the natural environment are not suitable for agriculture. Past domestication has provided incremental improvements, but further actively directed change is required to produce seeds with the characteristics required both now and in the future. In this paper, the focus is to discuss ways in which basic plant science could be applied to enhance seed performance in cotton production.

Published by: Dr. Vaibhav V. Ujjainkar, Dr. Manoj W. Marawar

Author: Dr. Vaibhav V. Ujjainkar

Paper ID: V7I4-1347

Paper Status: published

Published: July 19, 2021

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Research Paper

Characteristic study in optimization of Biomethanation process for high TDS spent wash from Distilleries

Acidic in nature, dark brown colored rich source of salts, a highly thick and viscous by-product of the sugar industry is known as Molasses. This molasses also contains sugar which could not be crystallized. It is one of the strongest organic industrial waste and even complex troublesome having extremely very high Chemical Oxygen Demand and Biological Oxygen Demand values. Due to the high concentration of organic contents in distillery spent wash which acts as a potential source of renewable energy. In a developing country like India, distilleries have become a major source of pollution as 88% of its raw materials are converted into waste and discharged into the distillery for every liter of ethanol produced.

Published by: Lalitha Devaraju, Dr. Manju B., Dr. Sathisha N. S., Dr. Kiran B. M.

Author: Lalitha Devaraju

Paper ID: V7I4-1261

Paper Status: published

Published: July 19, 2021

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Research Paper

Effective video retrieval system using Adaptive Shot Detection and Feature Vector Algorithm

In the current situation, around 150 million hours of video are uploaded to the Internet (i.e., YouTube, Netflix, Dailymotion, Vimeo, etc.). It becomes very difficult to extract the required relevant videos from such a large data set. Semantic / context-based matching is fast but highly dependent on the correct tags assigned to the video. On the other hand, due to the large number of frames involved in the video, it is difficult to apply a context-based search to the video. We have developed a novel video retrieval system that can extract the required videos from large sets of video data. The algorithm consists of content-based adaptive shot detection and feature vector extraction from each video from the dataset. The user only needs to provide an image similar to the system input to search for any video in the dataset.

Published by: J. Abhishek Paul, Dr. Sowmyarani C. N.

Author: J. Abhishek Paul

Paper ID: V7I4-1441

Paper Status: withdrawn

Submitted: July 19, 2021

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Research Paper

Comparative study of industrial steel structure (pre-engineered building) and residential RCC structure

Industrial steel structure (PEB) constructions are very popular to their advantages over conventional RCC construction. RCC structures are bulky and impart more seismic weight and less deflection whereas Steel structures instruct more deflections and ductility to the structure, which are advantages to resisting earthquake forces. Industrial steel structure Construction the better properties of both steel and concrete along with lesser cost, speedy construction, better quality control, sustainability, etc. Hence the aim of the present study is to compare a G+2 story residential RCC structure and an industrial steel structure. Both structures are designed for the same loading condition. Beam and column sections are made of either RCC, Steel (PEB) sections. STAAD PRO software is used for analysis and design and analysis results are compared. Cost-effectiveness based on material cost for Steel structure and RCC structure determined. The study concludes that industrial steel structures (PEB) are the best-suited types of constructions in terms of material cost.

Published by: Mahesh Nivrutti Ghumare, S. N. Daule

Author: Mahesh Nivrutti Ghumare

Paper ID: V7I4-1440

Paper Status: published

Published: July 19, 2021

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