Modified term frequency-inverse document frequency based deep hybrid framework for sentiment analysis.

Sentiment Analysis is a highly crucial subfield in Natural Language Processing that attempts to extract the public sentiment from the accessible user opinions. This paper proposes a hybridized neural network based sentiment analysis framework using a modified term frequency-inverse document frequency approach. After preprocessing of data, the basic term frequency-inverse document frequency scheme is improved by introducing a non-linear global weighting factor.

Variational Autoencoder Based Imbalanced COVID-19 Detection Using Chest X-Ray Images.

Early and fast detection of disease is essential for the fight against COVID-19 pandemic. Researchers have focused on developing robust and cost-effective detection methods using Deep learning based chest X-Ray image processing. However, such prediction models are often not well suited to address the challenge of highly imabalanced datasets.

Cu(OAc) catalysed aerobic oxidation of aldehydes to nitriles under ligand-free conditions.

An economically efficient and environmentally benign approach for the direct oxidative transformation of aldehydes to nitriles has been developed using commercially available non-toxic copper acetate as an inexpensive catalyst and ammonium acetate as the source of nitrogen in the presence of aerial oxygen as an eco-friendly oxidant under ligand-free conditions. The reactions were associated with high yield and various sensitive moieties like allyloxy, benzyloxy, -butyldimethylsilyloxy, hetero-aryl, formyl, keto, chloro, bromo, methylenedioxy and cyano were well tolerated in the aforesaid method. The kinetic studies showed first order dependency on the aldehyde substrate in the reaction rate.

An Unsupervised Fuzzy Clustering Approach for Early Screening of COVID-19 From Radiological Images.

A global pandemic scenario is witnessed worldwide owing to the menace of the rapid outbreak of the deadly COVID-19 virus. To save mankind from this apocalyptic onslaught, it is essential to curb the fast spreading of this dreadful virus. Moreover, the absence of specialized drugs has made the scenario even more badly and thus an early-stage adoption of necessary precautionary measures would provide requisite supportive treatment for its prevention.

Evolutionary Algorithm based Ensemble Extractive Summarization for Developing Smart Medical System.

The amount of information in the scientific literature of the bio-medical domain is growing exponentially, which makes it difficult in developing a smart medical system. Summarization techniques help for efficient searching and understanding of relevant information from the medical documents. In the paper, an evolutionary algorithm based ensemble extractive summarization technique is devised as a smart medical application with the idea of hybrid artificial intelligence on natural language processing.

Surfactant-modified alumina: an efficient adsorbent for malachite green removal from water environment.

Surface of alumina was modified with sodium dodecyl sulfate (SDS), an anionic surfactant. The surfactant-modified alumina (SMA) was characterized by FTIR and thermal analysis. The SMA was then used for the removal of malachite green (MG; Basic Green 4), a well-known toxic cationic dye from aqueous environment.