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Research Paper

Machine Learning and NLP based System for Medical Data Analytics and Prediction

In the present technical era, healthcare providers generate large amounts of medical data on a day-to-day basis. Produced clinical information is placed away carefully as Electronic Health Record (EHR) as essential information archive of medical clinics. These days Artificial Intelligence (AI) have been developing rapidly in recent years. Particularly, wellbeing data framework can get most advantages from the AI benefits. Specifically, symptom based disease prediction expectation exploration and creation turned out to be progressively mainstream in the medical care area as of late. In the paper, we have proposed a structure to assess the proficiency of applying both Natural Language Processing (NLP) and Machine learning (ML) advances for disease prediction framework. As an example we have interpreted n2c2 heart related disease symptom datasets from DBMI portal. The acquired patient records is in XML format which is parsed and converted to structured format and naive Bayes algorithm is applied for training.

Published by: Pooja S. P., Harshitha H. N., Meghashree M., Navyashree A. M., Merin Meleet

Author: Pooja S. P.

Paper ID: V7I3-1977

Paper Status: published

Published: June 21, 2021

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Research Paper

Business process management and its future

For any enterprise operations, it has always been at the heart to optimize its business processes. And with the allure to serve organizations in achieving operational excellence, increasing productivity, or saving costs, there has been growing interest and boom in Business Process Management (BPM). And as there is growth in sophistication and Artificial Intelligence (AI) becomes more cost-efficient, there has been an increasing impact of AI from lower-level functional tasks to the highest levels of enterprise restructuring in BPM. With significant growth in machine learning and AI, we can expect it to have a greater impact on BPM.

Published by: Sanjay Singh Rawat, Chetna Achar

Author: Sanjay Singh Rawat

Paper ID: V7I3-1965

Paper Status: published

Published: June 21, 2021

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Research Paper

LIFI Technology

Light Fidelity (LIFI) is Visible Light Communication (VLC) based innovation that makes a light as a media of correspondence supplanting the link wire correspondence. LIFI develop to defeat the pace in WIFI, while utilizing LIFI the pace can reach up to 14 Gbps. This paper presents a presentation, geographies, Performance, Advantage and Disadvantage of the LIFI innovation. The consequence of this paper can be utilized as a source of perspective to foster LIFI innovation.

Published by: Karan Singh, Sarala Mary

Author: Karan Singh

Paper ID: V7I3-2005

Paper Status: published

Published: June 21, 2021

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Research Paper

Effective implementation of smart agriculture monitoring system using IoT sensor network

Agriculture is an essential part of the Indian economy. More than 60% of India's agriculture-based population and a third of the nation's income comes from farming practices. Hence, it plays an important role in the country's development. The possible solution to these problems is to go for modernized agriculture that is part of modern trends. Therefore, agriculture can be made smart with the help of IoT and other technologies. Smart agriculture increases crop yields and reduces water waste and the imbalanced use of fertilizers. The most prominent feature of the project is that it measures various agricultural parameters that affect yields like moisture sensor, temperature sensor, ultrasonic sensor, and rain sensor using ATMEGA4809 chip and displays in LCD. Secondly, it sends all data to the cloud for analysis. The paper also includes an android mobile application that allows farmers to easily access information. In addition, the work also proposes an intelligent irrigation system that can optimize water consumption.

Published by: S. Purushothaman, Ajay Kanna R., Dhivakar G., Ashok Kumar K., Dilip Kumar E.

Author: S. Purushothaman

Paper ID: V7I3-1975

Paper Status: published

Published: June 21, 2021

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Research Paper

Study on quantitative & qualitative assessment on phytochemical activity and in-vitro study on antioxidant & antimicrobial activity from different organic extracts

The present study was to evaluate the phytochemical attributes and overall inhibitory effects of oceanic algal species of UlvaLactua, Gracilaria Corticata, and Ascophyllum Nodossum, collected from the area near Kovalam Beach (fisher’s spot), East Coast, Chennai, Tamil Nadu. Algal species are rich in bioactive compounds. Besides, the selected species are a highly diverse group of organisms from secondary metabolites of the natural source are potential sources. Oceanic algae are an interesting group in their broad spectrum of biological activities such as antibacterial, antioxidant, and anticancer. Methods: The algal extracts were prepared using a solvent extract approach involving ethanol, acetone, DMS, DCM, and double-distilled water as the solvent of interest for the study. Furthermore, the antibacterial activity and phytochemical activity of Ulva Lactua, Gracilaria Corticata, and Ascophyllum Nodossum. were tested against Candida albicans and Aspergillus niger and Escherichia coli and Proteas Vulgaris by well diffusion method. The phytochemical assay screening of the extracted species of Ulva Lactua, Gracilaria Corticata, and Ascophyllum Nodossum showed a greater degree of phytochemical attributes. In the antibacterial activity the growth of two virulent strains of pathogenic bacteria, E. coli and Proteas Vulgaris, and similarly concerning fungal strains of Candida albicans and Aspergillus niger were observed to exhibit a greater degree of inhibitory effect by the algal extracts, which are observed via the zone of inhibition (in mm). These results showed the investigated oceanic algal species, Ulva Lactua, Gracilaria Corticata, and Ascophyllum Nodossum showcased great biological potential, which could be considered for future uses in pharmaceuticals, food.

Published by: A. Dhipak Prince

Author: A. Dhipak Prince

Paper ID: V7I3-1972

Paper Status: published

Published: June 21, 2021

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Research Paper

Social distance monitoring using HOG and DNN

As of now, the world is facing its greatest pandemic COVID-19. Social distancing has become a part of our lives more than ever during the recent times .From our project, we would like to analyze a video that displays people walking around and provide the output in the same frame whether or not the people shown in the video are maintaining a social distance between them. The code will then be generalized in order to take any sample video as input and to provide the output.This will potentially help authorities to monitor public areas for practicing social distance, which will eventually help to curb the spread of a contagious disease.

Published by: N. Sai Karthik, G.Dinesh kumar, P.Ponnammal

Author: N. Sai Karthik

Paper ID: V7I3-1976

Paper Status: published

Published: June 21, 2021

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