National Institute of Technology, Karnataka

About: National Institute of Technology, Karnataka is a education organization based out in Mangalore, Karnataka, India. It is known for research contribution in the topics: Computer science & Corrosion. The organization has 5017 authors who have published 7057 publications receiving 70367 citations.

A Hybrid Nine-Level Inverter Topology With Boosting Capability and Reduced Component Count

Abstract: Nowadays, output voltage boosting gain property along with curtailment in the circuit voltage stress, and component count are considered as the essential topological features for the new multilevel inverter (MLI) circuits. Recognizing the above, a hybrid nine-level inverter topology (HNIT) for DC-AC conversion is proposed in this brief. Each phase of the HNIT is designed with only eight semiconductor switches, one diode, and two electrolytic capacitors. Herein, series-parallel and conventional-series techniques are utilized effectively to balance the capacitor voltages. Further, cost and quantitative comparisons are carried among the state-of-art circuits to highlight the supremacy of proposed circuit. Subsequently, the performance of HNIT is verified experimentally with the fundamental switching PWM technique at different load conditions.

An improved sentiment analysis of online movie reviews based on clustering for box-office prediction

Abstract: With the rapid development of E-commerce, more online reviews for products and services are created, which form an important source of information for both sellers and customers. Research on sentiment and opinion mining for online review analysis has attracted increasingly more attention because such study helps leverage information from online reviews for potential economic impact. The paper discusses applying sentiment analysis and machine learning methods to study the relationship between the online reviews for a movie and the movies box office revenue performance. The paper shows that a simplified version of the sentiment-aware autoregressive model can produce very good accuracy for predicting the box office sale using online review data. Document level sentiment analysis is used which consists of Term Frequency (TF) and Inverse Document Frequency (IDF) values as features along with Fuzzy Clustering which results in positive and negative sentiments. This lead to the creation of a simpler model which could be more efficient to train and use. In addition, a classification model is created using Support Vector Machine (SVM) Classifier for predicting the trend of the box office revenue from the review sentiment.

Synthesis, characterization, anticancer, and antioxidant activity of some new thiazolidin-4-ones in MCF-7 cells

Abstract: There are limited studies centring on the potential of thiazolidin-4-ones as anticancer agents. In this study, a new series of 2-(3-substituted-1H-pyrazol-4-yl)-3-(3-substituted-5-sulfanyl-1,2,4-triazol-4-yl)-1,3-thiazolidin-4-one (4a–o) have been synthesized by cyclo-condensation reaction of 5-substituted-4-[(3-substituted-1H-pyrazol-4-ylmethylidene)amino]-2H-1,2,4-triazole-3-thione (3a–o) and thioglycolic acid. The structures of all the synthesized compounds were confirmed by elemental analysis, spectral techniques like IR, 1H NMR, and mass spectroscopy. Few compounds exhibited dose-dependent cytotoxic effect in MTT assay in human breast cancer (MCF-7) cells. Apoptotic degradation of DNA due to action of potent thiazolidin-4-ones was analysed by agarose gel electrophoresis and visualized by ethidium bromide staining (comet assay). A concentration-dependent increase in tail length and olive tail moment was observed when treated with thiazolidin-4-ones. In vitro antioxidant studies like DPPH and ABTS-free radical scavenging assays-indicated moderate activity of thiazolidin-4-ones.