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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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Research Paper

Credit Card Fraud Prediction

Fraud detection by credit companies is essential in this digital era where the majority of financial transactions are made online. Fraudsters use loopholes in the payment systems to their benefit. Such problems can be solved to a large extent if the companies add an extra layer of security before confirming the transactions using machine learning algorithms. This project intends to use the Isolation Forest algorithm to enhance the security of credit card transactions by predicting the credibility of the transaction before authorization. Detecting 100% of the fraudulent transaction, minimizing the incorrect fraud classifications, and making the process automated is our objective.

Published by: Yash Rajesh, Thyagaraj Tanjavur

Author: Yash Rajesh

Paper ID: V7I4-1435

Paper Status: published

Published: July 19, 2021

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Research Paper

Used car price prediction

This research paper is the combination of datasets collected by cardekho.com and we have used ML to predict the price of a used car by creating a model using python, flask, and HTML the algorithm that we have used is Random Forest Regression. The price of the car is determined by the manufacturer and not everyone can afford it so they look for some low-cost alternative such as used car and this helps to build a big and evergreen used car market but due to the price irregularities this market is facing lots of problems so we have used machine learning to develop a new model that will predict the price and help consumers to buy the used car at a perfect price.

Published by: Abhishek Jha, Dr. Ramveer Singh, Manish, Imran Saifi, Shipra Srivastava

Author: Abhishek Jha

Paper ID: V7I4-1434

Paper Status: published

Published: July 19, 2021

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