Global Journal of Novel Research in Applied Sciences (NRAS) [ISSN: 2583-4487]

Prediction of the evolution of corona-virus using Machine Learning Technique

Tokpe Kossi, Subrata Sahana — Fri, 20 Jan 2023 00:00:00 +0000

The whole world has seen a change in habits in the past two years due to the discovery of the new corona family virus. The new corona virus is classified by The World Health Organization as Covid-19. Everywhere on the planet we are witnessing confirmed decision-making, curfew, restrictions on people, vaccinations, wearing of masks, etc. This paper aims to show how advancement of Machine Learning have provided excellent tools capable of reducing the number of infections while helping medicine in making decisions about testing infected people, reliability, accuracy of tests. We have improved the existing algorithms to produce software that can be able to do the prediction of evolution of corona virus. The implementation is done through Python language. We ensure that the results produced will be reliable and with fewer errors.

An Experimental Study on the Differences between Classical Machine Learning and Quantum Machine Learning Models

Vineet Kumar, Subrata Sahana — Fri, 20 Jan 2023 00:00:00 +0000

The field of Machine Learning (ML) brought a massive revolution and change in how normal day operations used to happen in various businesses. The idea of ML was quite simple, merging two separate fields, Mathematics and Computer Science. This simple idea is the very reason that so many predictive and classification-based applications exist today. The development of such applications is a time-consuming process and is very computationally heavy because in the corporate world, a very large amount of historical data is used and processed. The training processes such as pre-processing, data engineering and transformations, deep learning, training and testing are themselves time consuming. A very new field of computer science deals with solving this exact problem of time consumption. Quantum Computing (QC) tries to solve these problems by using the concepts of Quantum Mechanics during computations. The QC technology claims to be not only fast in its computational speed but also more efficient and accurate as well. The following article consists of an experiment conducted where a machine learning model is trained in a classical computing environment using K-Nearest Neighbors (KNN) algorithm versus in a quantum computing environment using Quantum K-Nearest Neighbors (QKNN) algorithm.

DETECTION OF ETHNO-LINGUAL IDENTITY USING ARTIFICIAL INTELLIGENCE, MACHINE LEARNING AND VOICE ANALYSIS TOOLS: INTRODUCING “AUTOMATED CRIMINAL ETHNICITY IDENTIFICATION SYSTEM” (ACEIS)

Vinny Sharma — Fri, 20 Jan 2023 00:00:00 +0000

Voice evidence is also known as voiceprint like fingerprint, it has been proven to substantiate the findings. Voiceprint is a dissimilar character for different people. In forensic science sometimes, we come across cases where the suspect’s or victim’s ethnicity has to be identified using various number of identification factors like voice, physical and anthropological features etc. In such cases the examination of an individual’s ethnicity may be identified using the other available identification factors but when it comes to the Ethno-Lingual identification then examining the individual’s language for the same and that too without any digital tool, i.e., doing it manually, becomes a sturdy task for the examiner. The database of the voice samples of Hindi, English and Mother language has been successfully created by the authors which is named as the “Automated Criminal Ethnicity Identification System” (ACEIS). In this paper, the author has summarised the various studies conducted on the ethno-lingual identification and their acquisition. Based on the studies, it was concluded in the review that the use of Artificial Intelligence and Machine Learning was used in prior studied but in India it hasn’t been done yet. When known samples were analysed for their ethnicity, we noticed that an 80% matching was there among the samples belonging from same ethnicity. This matching-percentage was calculated on the basis of Pitch, Amplitude, Formant Frequencies, Frequencies and the average time taken to speak a word/letter etc.

STUDY ON OBSTACLES IN THE PATHWAY OF STARTING AND OPERATING MFIs ESPECIALLY SHGs IN INDIA

Soumya Makker — Fri, 20 Jan 2023 00:00:00 +0000

In India, most of them live in the countryside and are engaged in odd jobs. Due to the lack of employment in rural areas, people are migrating to metropolitan areas. Microcredit serves those who are often overlooked in society such as women and the disabled. Microcredit cannot exist without microfinance institutions. In India microfinance operates through two channels:1. SHG – Bank Linkage Programme (SBLP) 2. Micro Finance Institutions (MFIs). The aim of the present study is to find out the obstacles in the pathway of SHG members in starting, operating, and promoting their businesses. As such a study requires in-depth exploration of SHG member’s conditions, their experiences and the problems they face in operating their business so researcher adopt a qualitative methodology to address the research agenda. The researcher concludes that at the very initial stage SHG members get support from the government in terms of getting guidance about how SHG scheme works and how SHG scheme works but still they face problems due to strict social norms that do not allow them to work beyond the boundaries for their home. Also, psychological issues like lack of confidence, lack of communication skills possess problems in their way. At operational stage training related problems and chances of falling into debt due to frauds and high competition in the market are the biggest problems for them. But major comes at promotional stage and this stage is important because failure at this point will put members in huge losses. SHG members face trouble in selling what they have produce because as per today’s trend they are not able to market products like through online platforms.

GLAUCOMA DETECTION SYSTEM ON THE BASIS COMBINING NB and RF CLASSIFIERS

M. Sreedhar, Radhika Baskar — Fri, 20 Jan 2023 00:00:00 +0000

A group of vision-impairing eye conditions known as glaucoma damages the optic nerve, which is essential for clear vision. Frequently, the result is abnormally high ocular pressure. One of the leading causes of blindness in adults over 60 is glaucoma. However, it is more prevalent in older persons of all ages. Glaucoma must be diagnosed as soon as possible. This paper presents the Glaucoma Detection System (GDS), which combines classifiers. For the purpose of glaucoma detection, the GAD system employs the Naive Bayes (NB) and Random Forest (RF) classifiers. The major function of the optic disc and cup is to find anomalies in fundus pictures. The optic cup and optic disc are first extracted from the input fundus pictures, and a region of interest (ROI) is then found.