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Institution

Bishop Heber College

About: Bishop Heber College is a based out in . It is known for research contribution in the topics: Thin film & Band gap. The organization has 548 authors who have published 692 publications receiving 7144 citations.


Papers
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01 Jan 2019
TL;DR: In this article, the preliminary phytochemical analysis of Barleria longiflora has been carried out using soxhlet extraction using petroleum ether, chloroform and ethanol.
Abstract: Present investigation deals with the preliminary phytochemical analysis of Barleria longiflora. The leaf, stem and root of this plant were subjected to successive soxhlet extraction using petroleum ether, chloroform and ethanol. The various part of extracts, were subjected to preliminary phytochemical screening for different classes of phytoconstituents. Phytochemical analysis, ethanol extracts showed presence of all compounds.

2 citations

Journal ArticleDOI
TL;DR: It is evident that host preference is prevalently exhibited in larval feeding of Tawny Coster as a new larval host of T. subulata and P. foetida plants respectively.
Abstract: Acraea terpiscore L. is commonly known as the Tawny Coster butterfly, it belongs to the Nymphalidae or Brush-footed butterfly family. Its common larval hosts depend on the availability of Turnera subulata. The study has been carried from January to July 2015 in Thammampatti, Salem district in Tamilnadu. A. terpiscore larvae were found in Turnera subulata and Passiflora foetida. From this observation it is evident that host preference is prevalently exhibited in larval feeding of Tawny Coster. On the availability of T. subulata the choice of P. foetida is found meagre. The caterpillars were counted once a week in both the populations during an observation period of six months. T. subulata and P. foetida plants respectively envisaging its host preference of T. subulata over P. foetida. It is reported here for the first time as a new larval host of Tawny Coster.

2 citations

Journal ArticleDOI
TL;DR: In this paper, the authors focus on the early prediction of occurrence of cognitive disorders such as Autism, Dyslexia and Delirium among children and focus on identifying the disorders among children as an early measure and support towards early mechanism to alleviate from these disorders.
Abstract: Background: The main objective of this paper is to focus on the early prediction of occurrence of cognitive disorders such as Autism, Dyslexia and Delirium among children. The common primary attributes are related to learning, social interaction, behaviour, understanding of objects and so on. Detecting this disorder at an early age is challenge lying among health care specialists, and researchers. Methodology: The proposed prediction method involves the modelling approach such as Meta Heuristic and Fuzzy Cognitive Map named as MEHECOM. Findings: The primary aim of MEHECOM model is to identify the disorders among children as an early measure and support towards early mechanism to alleviate from these disorders. The performance shows that MEHECOM predicts chances of dyslexia and autism disorders at an average of 65.22% compared to 48.7% of FEAST which adopts fuzzy cognitive map and 35.92% of decision tree approach. Applications: This MEHECOM model can be applied for the earlier prediction of all other cognitive disorders like amnesia, dementia etc.

2 citations

Journal ArticleDOI
01 Apr 2016
TL;DR: Better pre-processing techniques such as ECAS stemmer to find root word, Efficient Instance Selection for dimensionality reduction of text data and Pre-computed Kernel Support Vector Machine for classification of selected instances are used.
Abstract: Automatic text classification is a prominent research topic in text mining. The text pre-processing is a major role in text classifier. The efficiency of pre-processing techniques is increasing the performance of text classifier. In this paper, we are implementing ECAS stemmer, Efficient Instance Selection and Pre-computed Kernel Support Vector Machine for text classification using recent research articles. We are using better pre-processing techniques such as ECAS stemmer to find root word, Efficient Instance Selection for dimensionality reduction of text data and Pre-computed Kernel Support Vector Machine for classification of selected instances. In this experiments were performed on 750 research articles with three classes such as engineering article, medical articles and educational articles. The EIS-SVM classifier provides better performance in real-time research articles classification.

2 citations

Journal ArticleDOI
01 Jan 2004-Ionics
TL;DR: In this paper, the reduction behavior of 3-acetoxyflavone was compared with 3-hydroxyflavones on glassy carbon electrode with DMF and 60% DMF/Britton Robinson buffer at pH 3.8 and 10.1 using cyclic voltammetry (CV) and on dme using normal pulse polarography (NPP).
Abstract: Electrochemical reduction behavior of 3-acetoxyflavone was compared with 3-hydroxyflavone on glassy carbon electrode with DMF and 60% DMF/Britton Robinson buffer at pH 3.8 & 10.1 using cyclic voltammetry (CV) and on dme using normal pulse polarography (NPP). Single irreversible reduction waves were observed due to the reduction of keto moiety. The effects of change in medium, pH and sweep rate were evaluated. The electrode process was found to be diffusion controlled and enhanced substituent effect was noticed due to extended conjugation. Kinetic parameters were calculated from CV & NPP measurements using R.S. Nicholson and I. Shain equation and Meites & Isreal equation, respectively.

2 citations


Authors
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20224
2021101
202059
201977
201860
201770