Browsing by Author "Sheeba L"

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ANALYSIS OF HEDYCHIUM FLAVUM WASTE POWDER AS A POTENT HEAVY METAL ADSORBENT
(Springer Link, 2023-06-05) Swetha M; Indhumathi S; Sheeba L; Sangeetha G; Anushya Devi T.S; Selvanayaki M
Hedychium flavum, a medicinal, edible, and ornamental plant, is widely cultivated in India. Essential oils from the plant are used for various medical purposes and the leftover plant residue after oil extraction is discarded as a waste. An attempt was made to explore the used of this waste to remove heavy metals from wastewater was analysed. Result shows that the waste powder can be used effectively for metal removal. Hedychium flavum sequence was submitted to the NCBI database to procure accession numbers MN988619.
ANALYSIS OF HEDYCHIUM FLAVUM WASTE POWDER AS A POTENT HEAVY METAL ADSORBENT
(Springer Link, 2023-06-05) Swetha M; Indhumathi S; Sheeba L; Sangeetha G; Anushya Devi T S; Selvanayaki M
Hedychium flavum, a medicinal, edible, and ornamental plant, is widely cultivated in India. Essential oils from the plant are used for various medical purposes and the leftover plant residue after oil extraction is discarded as a waste. An attempt was made to explore the used of this waste to remove heavy metals from wastewater was analysed. Result shows that the waste powder can be used effectively for metal removal. Hedychium flavum sequence was submitted to the NCBI database to procure accession numbers MN988619.
ANTICANCER ACTIVITY OF CATHARANTHUS ROSEUS AND MURRAYA KOENIGII
(Journal of Critical Reviews, 2020-08) Sheeba L; Selvanayaki M; Harshini M
Bio-informatics is an interdisciplinary field of science involved in collecting and analysing biological data. It is processed with the help of software tools thereby to increase the understanding of biological processes. The Anticancer activity is done to arrest or prevent the growth of cancer cells. It can be done either by using drugs or by extracting proteins from plants. Defining the benefits of using drugs as an anti-cancer agent is difficult. As it may harm the patient due to the presence of chemotherapeutic agents and are cost effective .So, the protein extracts of Catharanthus roseus and Murraya Koenigii are the best anti-cancer agents that overcomes the disadvantages of drugs. The extract of Catharanthus roseus and Murraya Koenigii is used in processes like protein estimation, anti-oxidant activity, anti-microbial activity etc., Further MCF-7 cell lines are cultured and the plant extracts are swapped. In this phase the cell death is observed and compared, and the result is analysed
HEALTH MONITORING USING WEARABLE DEVICE
(Karpagam Academy of Higher Education, 2020-02) Selvanayaki M; Sheeba L
The Internet of Things (IoT) has the potential to transform health care by profoundly altering how hospitals, clinics and other care facilities gather and use data by bringing together the major technical and business trends of mobility, automation and data analytics to improve patient care delivery. IOT helps in connecting the people by empowering their health and wealth in a smart way through wearable gadgets. The main aim of this work is to provide an extensive research in capturing the sensor data's, analyzing the data and providing a feedback to patients based on different health parameters. This paper focuses on making the system affordable and user friendly for the mass people. With the increase in popularity of smart wearable devices, an opportunity to provide an Internet of Things (IoT) solution has become more available.
PREDICTING ENERGY CONSUMPTION USING LINEAR REGRESSION
(Michael Job College of Arts and Science for Women, Coimbatore, 2020-02) Selvanayaki M; Sheeba L
Electricity plays a very important role among energy sources. Electricity consumption is important for every national authority when making energy policy. An energy policy has a great impact on industrial development in a country. This paper predicting energy consumption to analyze the consumption of the electrical energy among the various industries.The machine learning technique namely pycharm is used to predict the electrical energy consumption by using the linear regression model. This paper presents a machine learning approach for predicting electrical energy consumption whether the electrical energy is increase or not. The electrical energy consumed by various industries during the year 2008 to 2018 was used for analysis. Using liner regressionmodelithaspredictedthatthe energy consumption will increase by 11 % in the year 2019 and 1% in the year 2020.
TRANSFORMING STUDENT ENGAGEMENT THROUGH AI, AR, VR, AND CHATBOTS IN EDUCATION (Book Chapter)
(IGI Global, 2025-03-05) Viji Gripsy J; Selvakumari, Sheela N. A; Sheeba L; Senthil Kumaran B
Emerging technologies have a relatively short history in the higher education sector. The term “AI-powered chatbots” refers to systems that use conversational AI. Many colleges and universities are taking advantage of conversational AI and deploying AI-powered chatbots to improve the student experience. It is possible to converse with a chatbot via text or voice using an AI-based interactive interface. Data is fed into chatbots, which are programmed to process information already given to them. They respond according to a pre-written script. By mimicking Alexa and Siri at home, conversational AI can help colleges and universities communicate with their students and prospective students in the same way. The primary aim of this chapter is to introduce the integration of Augmented Reality (AR) and Virtual Reality (VR) for AI-powered Chatbots for Transnational Higher Education to enhance the learning experience for students. The ultimate goal is to analyze the role of AI in improving higher education institutions around the globe.