Browsing by Author "Rehana Banu H"

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GC-MS DETERMINATION OF BIOACTIVE COMPONENTS OF WEDELIA CHINENSIS (OSBECK) MERRILL (PDF)
(Journal of Chemical and Pharmaceutical Research, 2013) Rehana Banu H; Nagarajan N
Medicinal plants are sources of important therapeutic aids for alleviating human ailments. The traditional use of medicinal plants leaf extract for diseases is quite common in developing countries like India. In a view to understand the scientific reason behind its medicinal value, an attempt is made in this study, to analyze major bioactive compounds present in the leaf extract from Wedelia chinensis (Osbeck) Merrill (Family Asteraceae) by GC-MS. The major chemical constituents are 2-Tridecanone (CAS) (4.51%), n-(methoxyphenylmethylene) carbamic acid ethyl ester (1.65%), and 9,12,15-Octadecatrienoic acid, methyl ester, (Z,Z,Z) (13.68%). The presence of some of these constituents in the plant extract provides the scientific evidences for the antimicrobial, anti-tumor, and antioxidant properties of the plant. Further study is required to find out the specific phytochemical which isresponsible for its medicinal value.
LEAF IDENTIFICATION USING MACHINE LEARNING ALGORITHMS
(In association with IBM,AICTE,CSIR with Sri Ramakrishna Engineering College, Coimbatore, 2019-07-11) Radha N; Rehana Banu H
Plants play an important role to equalize the carbon-oxygen cycle in the earth. Without knowing the importance of valuable plants, the plants are at the extinction. To help the naïve user to know about plants and it is important there is demand to develop a system to classify the plants based on the leaves. Due to the boon of ICT and machine learning algorithms, the leaves can be easily classified. Plant Leaf images are collected in Coimbatore. The main aim of this paper is to classify the leaves using Support Vector Machine (SVM) using KBF kernel, K-Nearest Neighbor, AdaBoost classifiers and also the accuracy obtained in these classifiers are compared. The performance of the models is evaluated using 10-fold cross validation method and the results are discussed. The classifier using SVM and KNN outperforms well than Adaboost classifiers
A STUDY OF TECHNIQUES ON SECURING PATIENT CONFIDENTIAL INFORMATION USING ECG STEGANOGRAPHY
(International Journal of Engineering Research and Applications, 2018-10) Radha N; Rehana Banu H
Plants play an important role in the earth’s ecology. Without plants, human lives cannot exist in this world. But in the recent days, people are not having knowledge about many types of valuable plants. They are at the risk of extinction. So, it is necessary to protect plants and to catalogue various types of flora diversities and it is important to maintain plant databases which pave a way towards conservation of earth’s biosphere. In the world wide, there are a huge number of plant species available. To handle such volumes of information, development of a quick and efficient classification tool using machine learning algorithms is needed. In addition to the conservation aspect, recognition of plants paves a way to use those plants as an alternative energy source. In this paper, various techniques used to classify the leaf images using machine learning algorithms are studied.
TLC AND HPTLC FINGERPRINTING OF LEAF EXTRACTS OF WEDELIA CHINENSIS (OSBECK) MERRILL.(PDF)
(AkiNik Publications, 2014) Rehana Banu H; Nagarajan N
To establish the fingerprint profile of Wedelia chinensis using thin layer chromatography (TLC) and high performance thin layer chromatography (HPTLC) technique. Methods: TLC and HPTLC studies were carried out in two different solvent systems, which showed different Rf value. Results: TLC profiling of the extract confirm about the presence of various phytochemicals. HPTLC finger printing of methanol extract of leaf revealed various peaks with Rf values in the range of 0.01 to 0.97. Conclusion: It can be concluded that different Rf value of various phytochemicals provide valuable clue regarding their polarity and selection of solvents for separation of phytochemicals. The study will help in future for identifying this plant for further research