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Soumya Sen

Researcher at University of Calcutta

Publications -  103
Citations -  1029

Soumya Sen is an academic researcher from University of Calcutta. The author has contributed to research in topics: Data warehouse & Computer science. The author has an hindex of 15, co-authored 98 publications receiving 737 citations. Previous affiliations of Soumya Sen include Information Technology University.

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Evaluation of chemical constituents and free-radical scavenging activity of Swarnabhasma (gold ash), an ayurvedic drug.

TL;DR: Qualitative analyses indicated that Swarnabhasma contained not only gold but also several microelements (Fe, Al, Cu, Zn, Co, Mg, Ca, As, Pb, etc.).
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Chemical and Pharmacological Evaluation of Different Ayurvedic Preparations of Iron

TL;DR: Ayurvedic preparations of metallic iron commonly categorised as different 'putas' of 'Louha Bhasma' was chemically analysed and pharmacologically investigated in iron deficiency anemia and revealed the presence of various proportions of important metals along with varied concentration of iron.
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Clinical application of modified bag-of-features coupled with hybrid neural-based classifier in dengue fever classification using gene expression data

TL;DR: A modified bag-of-features method has been proposed to select the most promising genes in the classification process and results indicated a highly statistically significant improvement with the proposed classifier over the traditional ANN-CS model.
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A systematic survey on influential spreaders identification in complex networks with a focus on K-shell based techniques

TL;DR: The main objective of this paper is to analyze and compare the major variations of the k-shell based methods along with representative network topology based hybrid techniques by considering a toy network with detailed computations.
Proceedings ArticleDOI

Stock Price Prediction Using LSTM on Indian Share Market

TL;DR: A framework using LSTM (Long ShortTerm Memory) model and companies’ net growth calculation algorithm to analyze as well as prediction of future growth of a company is proposed.