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Research Paper

Getting art to the market: how is the price of paintings determined?

This paper is aimed at finding a correlation, if any, between the factors determining the price of an artwork. Based on quantitative analysis of a personal survey with 31 respondents, the factors do not form any particular abstract formula which could be derived. It was indicative that the surveyees approached pricing in a variety of ways. To make sense of the variety, the author used an inductive technique to identify and categorize various price styles. The results of the polls were tallied to determine the variables that each artist considered when making their selection. Individual respondents' most prevalent choice aspects are revealed through this method.

Published by: Divyanshi Saroff

Author: Divyanshi Saroff

Paper ID: V8I1-1273

Paper Status: published

Published: January 24, 2022

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Research Paper

Universal Turing machine simulator

In this, we introduce a Turing Machine and Pushdown Automata Simulators as an effective setting for getting to know technique models and automata concepts. The 2-fold contribution of these paintings could be a novel use of modern-day generation to enhance getting to know and longitudinal experimental analysis of its use in context. An introductory evaluation suggests the effectiveness of the simulators inside the schoolroom

Published by: Rohit Gurav, Sakshi Suryawanshi, Parth Narkhede, Sankalp Patil, Sejal Hukare, Kuldeep Vayadande

Author: Rohit Gurav

Paper ID: V8I1-1268

Paper Status: published

Published: January 24, 2022

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Research Paper

Heart Disease Prediction

Heart Disease prediction is one of the most complicated tasks in the medical field. Day by day the cases of heart diseases are increasing at a rapid rate and it’s very important and concerning to predict any such diseases beforehand. This diagnosis is a difficult task i.e. it should be performed precisely and efficiently. We prepared a heart disease prediction system to predict whether the patient is likely to be diagnosed with heart disease or not using the medical history of the patient. Traditional approaches that involve the collection of data from devices into one centralized repository for further analysis are not always applicable due to a large amount of collected data, the use of communication channels with limited bandwidth, security and privacy requirements, etc. Federated learning (FL) is an emerging approach that allows one to analyze data directly on data sources and to federate the results of each analysis to yield a result as traditional centralized data processing. Available electronic medical records of patients quantify symptoms, body features, and clinical laboratory test values, which can be used in predicting heart disease.

Published by: Medasani Hari Kumar, Kottamasu Sai Anila, Doppalapudi Sriram, Rizwan Patan

Author: Medasani Hari Kumar

Paper ID: V8I1-1248

Paper Status: retracted

Submitted: January 24, 2022

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Research Paper

Detection of Brain Tumors from MRI images using Improved Fuzzy C means and K means template-based algorithm

For decades even with the advancement of scanning and evolving imagery systems, the detection of tumors present in the brain has become increasingly challenging and is still one of the most sensitive areas in the field of medicine. In this research work, a enhanced model is proposed in which I have employed a combination of two algorithms. The first algorithm is the K Means Clustering which is a method of vector quantization. The second is the Fuzzy C-means clustering in which each data point can be attributed to more than one cluster. When used together the algorithms give enhanced performance and is called the TKFCM algorithm. Here in this paper, first in order to initialize the segmentation the k-means algorithm is used and the template is selected based on the Gray level of the image. Then the membership that is updated is primarily determined using the distance from the centroid of the cluster to the data points of the cluster using the FCM algorithm. Next, the improved FCM clustering algorithm is fundamentally used to detect the position of the tumor based on the function that is obtained by different features that include energy, contrast, entropy, homogeneity, dissimilarity and also the correlation. The results of the paper indicate that the algorithm is capable of detecting tissues that are abnormal in a improved time window.

Published by: Karan Vikram Singh Bhatia

Author: Karan Vikram Singh Bhatia

Paper ID: V8I1-1256

Paper Status: published

Published: January 24, 2022

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Review Paper

Majeeth (Rubia codifolia linn): A review

Rubia cordifolia Linn also called as common Madder or Indian Madder, is a species of flowering plant. Rubia cordifolia is a branched climber with small, greenish white flowers that are arranged in a cluster of round, fleshy, purple fruits. Its roots have a brownish red bark from which a red dye is obtained. This plant grows well in hilly areas, and the root has medicinal values It is an important member of the Rubiaacea family. Dried roots of Rubia cordifolia, is a rich source of anthraquinones responsible for its traditional, phytochemical and pharmacological activities. Today clinical investigations of herbal formulations and their market preparations, both are on demanding because of better safety and efficacy without or minimal side effects. Many studies suggested that Rubia cordifolia has many biological effects such as antioxidant, anticancer, anti-inflammatory and analgesic, hepato-protective, anti-acne, blood purifier activity, astringent, antimicrobial, anti-dysentric, antiseptic, nephron-protective properties. The present article describes a detailed review of literature for this plant species including taxonomy pharmacology and photochemistry in an organized way. This review paper will surely serve as an important source for the future scientific investigations on this plant.

Published by: Shabnam Bano, Wajeeha Begum

Author: Shabnam Bano

Paper ID: V8I1-1261

Paper Status: published

Published: January 24, 2022

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Research Paper

Life in Sundarbans: Spatial Dimensions of Amitav Ghosh’s Gun Island

Space and Time were always treated as a fascinating matter for the aspiring research fraternity of English literature. It is of contemporary relevance and practicality to discuss the topic in detail. Many theorists like Henry Lefebvre, Edward Soja, Yi Fu Tuan were leading the discussions based on Space through their seminal literary works. Here intention of this paper is to analyse the novel Gun Island in the light of space theory and study how spatial dimension were employed by Amitav Ghosh in his narrative. Sundarbans, the tide country is the focus of the narrative though which he talks about the major themes like marginalisation, trauma of the destitute, man vs. nature conflict and so on. The inclusive view of Sundarbans especially Lusibari is narrated here pinpointing the issues of refugees, ordeal of Dalits, Natural calamities etc. Lusibari, its people their beliefs, jobs, social conditions, educational background, economic aspects, and so on were talked about. The uneducated people who were strong believers and how intimately they keep and pass on their tradition beliefs, legends etc were shown in the novel. This paper will add knowledge regarding the space Lusibari and its culture to the reading public.

Published by: Sarada P. V., Dr. T. K. Pius

Author: Sarada P. V.

Paper ID: V8I1-1259

Paper Status: published

Published: January 24, 2022

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