Titlebook: Mathematical Analysis and Computing; ICMAC 2019, Kalavak R. N. Mohapatra,S. Yugesh,C. Kalaivani Conference proceedings 2021 The Editor(s)

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A. Anat Jaslin Jini,S. Monikandanentation. In the task of subword-aware language modeling, pattern-based models outperform character-based analogues by 2–20 perplexity points. Also, a recurrent neural network in which a word is represented as a sum of embeddings of its patterns is on par with a competitive and significantly more so

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Geetha BalachandarN), termed as MCG-Net, to extract discriminative information from the brain functional connectivity based on the resting-state fMRI data. We used the F-score and KNN algorithms to remove the abundant connectivities in the functional connectivity matrix from global and local level. Besides, the brain

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Ananya Dwivedi,Ram Kevalence patterns. We compute TCR sequence .-mers, applying sparse coding to extract key features. Domain knowledge integration improves predictive embeddings, incorporating cancer properties like Human leukocyte antigen (HLA) types, gene mutations, clinical traits, immunological features, and epigeneti

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Spartan

A. Atkinswestley,S. Chandrasekarr, we develop a novel algorithm called OSMIA (Osmosis inspired Algorithm) for multiobjective optimization problems. The proposed algorithm is inspired by the well-known physio-chemical osmosis process. For validation purposes, we have realized a case study in that we compared our proposed algorithm

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J. Viswanath,C. T. Dorapravina,T. Karthikeyan,A. Stanley Rajng the initial classification of . species, with an average of 98.36%. Using MLP classifier, only one species has been misallocated. It is essential, therefore, to employ a method that does not generate type I or type II misclassifications where . is concerned. In comparison, only K-NN classifier ha

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