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Research Paper

Advanced facial recognition attendance and behavioral feedback system

Manually maintaining an attendance system can be tedious and time-consuming. A smart, automated way to manage attendance can be created using biometrics. Facial recognition is just one example. The problems of proxies and fake attendance can be solved with this system. This system also helps overcome time wasted in calling attendance the traditional way. The previous attendance system that relied on face recognition was flawed. Face occlusion meant that some faces went unnoticed. Therefore, our system helps overcome these issues, makes the system more reliable and useful with various techniques like People Counter and Behaviour Analysis. The detection and recognition of faces are the two most important processes in this system. Following that, crosschecking the detected faces against the database of student's faces can be done. This smart system will allow students to keep track of their attendance and records. It also helps institutions get feedback about a class and helps save time on surveys and questionnaires.

Published by: Shashidhar V., Amandeep Singh, Satyam Sahay, Shah Minhal Fida, Vishveshwar Hiremath

Author: Shashidhar V.

Paper ID: V7I4-1538

Paper Status: published

Published: July 27, 2021

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A scholastic review of procedural methods undertaking in piloting qualitative interviews

This paper presents the essence of a pilot study being conducted by the researcher on qualitative research in relation to the study on the use of adaptive technology amongst visually impaired students at tertiary institutions in Malaysia. The researcher carried out the pilot work as a ground work prior to undertaking the large scale study and to answer methodological question (Creswell & Poth, 2017). The definitive description and valuable operational functions of pilot studies in qualitative research studies are distinctly identified. Also, to outline the advantages of pilot work, it explicates the particular viable and methodological concerns appearing in the pilot exercise together with the amendments made for the main research study, as a result of the pilot work. This article describes four ways that proved the implementation of the pilot study is crucial. They are (i) finding obstacles and problems with regards to recruiting prospective participants, (ii) the Employing empathy techniques in which researcher is able to describe the experience from the participants’ angle as well as engage himself from a phenomenological perspective, (iii)reflecting the essence of the research process such as the interviews, epoche and transcribing process, alongside its difficulty in carrying out phenomenological inquiry, and (iv) amending interview questions accordingly. It is, therefore, a useful and a fundamental part to undertake the Pilot study for interview in the course of carrying out qualitative research as it identifies the weaknesses and flaws prior to the full scale research study. This paper discusses the preponderance of pilot study, the methods procedural steps used and what educational aspects has the researcher gained during the course of the process.

Published by: Chow Sak Chin

Author: Chow Sak Chin

Paper ID: V7I4-1534

Paper Status: published

Published: July 27, 2021

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Research Paper

Computational Identification of Promoter Regions in Fungal Genomes

Transcription is the mechanism through which proteins are formed and it is done at the promoter regions. The structural property and the stability of DNA (Deoxyribonucleic Acid) are due to the promoters and these promoters are used to distinguish them from other genomic sequences. Genomic expression patterns were determined in the yeast S.cerevisiae in response to the environmental fluctuations. To measure these changes, DNA Microarrays were used. It is revealed that the yeast genome contains a TATA box. Those genes associated with the TATA box show response mainly to stress conditions.

Published by: Sudheer Menon, Shanmughavel Piramanagakam, Gopal Agarwal

Author: Sudheer Menon

Paper ID: V7I4-1532

Paper Status: published

Published: July 27, 2021

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Research Paper

Online interview based on facial expression

Facial expressions of humans carry more information visually than they do verbally. Human-machine interaction is a crucial part of facial expression recognition. The automated facial expression reputation system can be used for many purposes, including detection of intellectual issues and human behavior information. It is still difficult to recognize facial expressions using computers with high recognition charges. The most well-known techniques used in automatic FER systems are based on look and geometry. Normally, facial expression recognition works in four stages, which include preprocessing, face identification, Feature extraction, and Classification. We also used feature extraction and expression classification to identify the seven key human emotions.

Published by: Kamal Raj T., Sourav P Kachwahe, Tejas S., Shashank C., Sanjay H. S.

Author: Kamal Raj T.

Paper ID: V7I4-1518

Paper Status: published

Published: July 27, 2021

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Research Paper

Soil quality monitoring, automated irrigation system using machine learning and Blynk

India Ranks the second country in the world in farm output of 64% of cultivated land which depends on monsoons. Irrigation accounts for Fifty-five to seventy-five percent of water usage In the World. Also, nearly sixty percent of this water while irrigation is wasted. So now we have to conserve the water by making use of soil moisture sensors resulting in smart water management Another is an issue is people always focus on the crop yield whereas before the crop yield the other process such as soil quality and soil fertility, which crop to be grown and what fertilizers needed plays a very important role in the yield of the crop. So in our project, we have focused on these factors such as irrigation, prediction for fertilizer, and which crop to be grown. This project takes real-time data from the deployed sensors such as temperature, moister, NPK and ph values into account and predicts the output in the IoT machine learning environment. The system implemented will be introduced to the semi-supervised learning model where we will be applying algorithms such as KNN and random forest and SVM to predict fertility and whereas for the crop along with this we have considered other factors such as season and place.

Published by: Kamal Raj T., Kavya G. S., Firdose Tabassum, Reddy Nagadurga, Keerthana Prakash Nayak

Author: Kamal Raj T.

Paper ID: V7I4-1536

Paper Status: published

Published: July 27, 2021

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Research Paper

Design of wheel rim by using design of experiments

There are many failures that occurred such as Defects occurred during manufacturing, Initiation of Crack, over-tightening of bolts, and Corrosion. Some of the people have used FEM methods in their Research. They all have worked only on the negative offset and zero offset wheel rims. In this paper, we are focusing more on the positive offset wheel rim as they consume less material as compared to negative offset and positive offset wheel rims. In this paper, we know the natural frequency and deformation of the original rim and we are going to design more than 2-3 designs for the wheel rim. Using those designs and analysis types such as Static, Modal, and mainly the Design of experiments we are going to produce the alternate design for the wheel rim which will be more sustainable and lesser in cost.

Published by: Mauli Vasant Jadhav, V.C.MALI

Author: Mauli Vasant Jadhav

Paper ID: V7I4-1540

Paper Status: published

Published: July 27, 2021

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