Chandigarh University

About: Chandigarh University is a education organization based out in Mohali, India. It is known for research contribution in the topics: Computer science & Chemistry. The organization has 1358 authors who have published 2104 publications receiving 10050 citations.

Ensemble Classification Approach for Sarcasm Detection.

Abstract: Cognitive science is a technology which focuses on analyzing the human brain using the application of DM. The databases are utilized to gather and store the large volume of data. The authenticated information is extracted using measures. This research work is based on detecting the sarcasm from the text data. This research work introduces a scheme to detect sarcasm based on PCA algorithm, - means algorithm, and ensemble classification. The four ensemble classifiers are designed with the objective of detecting the sarcasm. The first ensemble classification algorithm (SKD) is the combination of SVM, KNN, and decision tree. In the second ensemble classifier (SLD), SVM, logistic regression, and decision tree classifiers are combined for the sarcasm detection. In the third ensemble model (MLD), MLP, logistic regression, and decision tree are combined, and the last one (SLM) is the combination of MLP, logistic regression, and SVM. The proposed model is implemented in Python and tested on five datasets of different sizes. The performance of the models is tested with regard to various metrics.

Antifungal potential of Fenugreek Seeds (Trigonella foenum-graecum) Crude Extracts against Microsporum gypseum

Abstract: Trigonella foenum-graecum (fabaceae) is commonly used as condiments and spices in Indian and Asian food to flavour, colour, and texture of food, and it is employed in various medicinal purposes in traditional systems. The biological activity of fenugreek can be easily accessed from previous research conducted by several researchers. The present research was conducted to find out the antifungal potential of various extracts of dried powder of fenugreek seeds by means of paper disc diffusion method, with petroleum ether, ethyl acetate, ethanol, and aqueous solvents in 25 μml, 50 μml and 100 μml concentrations against Microsporum gypseum. Clotrimazole was used as a standard. The present study revealed that fenugreek is a potent antifungal agent against Microsporum gypseum. The ethanol extract of fenugreek using 100 μml concentrations depicted the highest zone of inhibition of 16.510+ 0.85mm and 38.395% of mycelial inhibition against a tested pathogen. While drug extracts in other solvents also revealed reasonable to least antifungal potential. This finding tells us that fenugreek extracts tested proved to be a potent antifungal agent against Microsporum gypseum. It was found that ethanol extract of fenugreek is best effective against tested strain. This exploration of fenugreek extracts has confirmed its importance, particularly in the area of influence on dermatophytic fungal strain.