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Test crosses evaluation for identification of maintainer and restorer lines in hybrid rice breeding programme

The study was conducted to identify potential maintainers and restorers in developing rice hybrids through a three-line system. During Kharif 2018 six established CMS lines were crossed with 34 elite lines and 87 F1s were evaluated during 2019 in test cross nursery. Among these 49 genotypes recorded effective the restorability with more than 75% spikelet fertility, 9 genotypes recorded partial fertility with 50-75% spikelet fertility, 3 genotypes were partial maintainers with 1-50% spikelet fertility, and 25 genotypes as maintainers with 100% pollen sterility. In the present study, high frequency of restorers (56%) was observed than maintainers (29%). The genotypes NTCN1, NTCN 31, and NTCN 93 can be used for the development of new CMS lines through recurrent backcrossing programme and other potential restorers like NTCN 2, NTCN 3, NTCN 18, NTCN 19, NTCN 31, NTCN 33, NTCN 58, NTCN 78, NTCN 79, NTCN 80, NTCN 85, NTCN 97, NTCN 98, NTCN 101, NTCN 102, NTCN 103, NTCN 104, NTCN 105, NTCN 109, NTCN 111, NTCN 115, NTCN 113, NTCN 116, NTCN 118 and NTCN 119 can be used for developing early to medium duration hybrids in rice.

Published by: N. K. Gayathri, M. Subba Rao, P. Pullibai, S. Vasundhara, S. Md Rafi

Author: N. K. Gayathri

Paper ID: V7I2-1475

Paper Status: published

Published: April 28, 2021

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Research Paper

Enhancement of heat transfer using perforated fin

In many engineering applications, extended surfaces referred to as fins are used to enhance convective heat transfer. The problem of forced convection heat transfer for perforated fins was investigated in this work. An experimental study was conducted to investigate the heat by forced convection transfer in a rectangular non-perforated fin and circular perforated fin. The investigation is conducted to compare the heat transfer rate of two different fins one is with circular perforation and another one is without perforations. The work done on various kinds of fins, the effect of perforation shape or geometry on the heat transfer was simulated in ANSYS 17.2 to work out the simplest type of fin to be used. The parameters which were considered are the thermal properties of the fin and perforations. The study takes into account the gain in fin surface area and the extent of heat transfer enhancement due to perforations. The comparison between experimental results and software results of the kinds of fins perforation was analyzed for the heat transfer coefficient to clarify the simplest perforation shape for the specified application.

Published by: Aditya Vasant Hadawale, Sourabh Gautam Gawai, Vidisha Gautam Karwade, Archana Namdeo Rupnar, Prathamesh Patil

Author: Aditya Vasant Hadawale

Paper ID: V7I2-1522

Paper Status: published

Published: April 28, 2021

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Research Paper

A comparative analysis of machine learning techniques for automatic text classification

Text processing and its related activities have reached their peak demand in the present days due to the increase of unstructured data. The underlying structure in any text can be derived through categorization techniques. The capacity of text classification algorithms to perform the conversion from structured to unstructured data is the key factor in all text processing activities. To further enhance this, many concepts from other disciplines such as statistics, physics, and mathematics were tailored to suit the needs of text analyzing pipelines. Text classification techniques help to build the template necessary for extracting meaningful information. Hence, this paper undertakes a study of comparison on various text classification algorithms to reiterate their suitability for particular classes of problems. The algorithms such as ‘Naïve Bayes’, ‘Support Vector Machine’, ‘K- nearest neighbor’, and ‘Decision Tree’ were studied based on empirical analysis with respect to the WEKA data analysis platform. From the experimental results, it is seen that the strength of algorithms depended on the data type, nature of attributes, and representation of the classes. This is verified by various accuracy metrics used in the study such as precision, recall, accuracy, F1- scores, and ROC values.

Published by: Sivakami M., Dr. M. Thangaraj, P. Aruna Saraswathy

Author: Sivakami M.

Paper ID: V7I2-1523

Paper Status: published

Published: April 28, 2021

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Review Paper

Education and women empowerment in India

Education is one of the most creative means of empowerment. It helps a person to realize his or her potential in a social group to achieve higher social mobility and the state to maintain good social order. Empowerment through education can also be dealt with by following a capabilities approach. Being an important component of developing capabilities, education has an intrinsic role to play in developing freedom and leaving the rest to be attained through institutional and legal means. Education is fundamental for achieving full human potential, developing an equitable and just society, and promoting national development. Providing universal access to quality education is the key to India’s continued ascent, and leadership on the global stage in terms of economic growth, social justice and equality, scientific advancement, national integration, and cultural preservation. Universal high-quality education is the best way forward for developing and maximizing India`s rich talents and resources for the good of the individual, the society, the country, and the world at large. India will have the highest population of young women in the world over the next decade, and our ability to provide high-quality educational opportunities to them will determine the future of their progress, development, and empowerment.

Published by: Dr. P. Prameela Margaret

Author: Dr. P. Prameela Margaret

Paper ID: V7I2-1297

Paper Status: published

Published: April 28, 2021

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Research Paper

Design and analysis of aircraft landing gear

The landing gear is a vital structural unit of an aircraft that enables it to take off and land safely on the ground. A variety of landing gear arrangements are used depending on the type and size of an aircraft. Nowadays we can see that majority of failures of aircraft structure take place because of the malfunction of the landing gear system solely. This work is mainly focused on structural design and analysis of the main landing gear for an aircraft, that is economical and possesses a high strength to weight ratio but still simple in design. A typical landing load case will be assumed for which structural analysis will be carried out. During landing, there will be three different types of loads: 1. Vertical load (Compressive Load) 2. Drag load 3. Sideload Drag load and sideload values are terribly tiny in comparison to compressive load. So we will be focusing on the Vertical load. So we have taken the standard landing gear of an aircraft and it is designed by using Solid-works 2019 and analyzed for structural safety using ANSYS 19.2 software. The maximum possible load is given as design load. The landing gear assembly is analyzed for the traditional metallic materials like Aluminium Alloy-AlSI1030 Carbon Steel, Structural Steel IS2062 Fe440, and Titanium Alloy-Ti-8Al-1Mo-1V using ANSYS software and by comparing the results obtained by the mentioned material the best suitable material will be concluded that may be considered as best suitable and safer material.

Published by: Mahesh Ashok Raut, Rohit Thirrupathi Tumma, Shravani Suresh Desai, Satyendra Rajkumar Upadhyay, Prathamesh Preetam Choughule

Author: Mahesh Ashok Raut

Paper ID: V7I2-1437

Paper Status: published

Published: April 28, 2021

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Research Paper

Brain tumor detection and classification using convolutional neural network

Brain tumors can cause cancer if not detected and diagnosed at early stages. Currently, Brain tumor detection and classification is done by performing Biopsy which is a very time-consuming process. Improvement in technology and Machine learning algorithms can help radiologists in tumor diagnostics in less time and effort. We propose a model that would first segment the MR image and identify the presence of tumor in the brain and if detected then a deep learning-based CNN architecture that would classify the tumors in MRI images into Benign and Malignant tumors and act as a strong base for the staff to decide the curing procedure. The development of the model will be divided into training and testing phases and would be tested using multiple databases and different methods. Having achieved high accuracy, reliability, and execution speed, the developed CNN architecture would act as a strong decision-supportive tool in medical diagnostics for radiologists.

Published by: Darshan Bhamare, Vijay Sawale, Vinay Gupta, Ajay Ghosade

Author: Darshan Bhamare

Paper ID: V7I2-1496

Paper Status: published

Published: April 28, 2021

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