Sentiment analysis has been an important topic of discussion from two decades since Lee published his first paper on the sentimental analysis in 2002. Apart from the sentimental analysis in English, it has spread its wing to other natural languages whose significance is very important in a multi linguistic country like India. The traditional approaches in machine learning have paved better accuracy for the Analysis. Deep Learning approaches have gained its momentum in recent years in sentimental analysis. Deep learning mimics the human learning so expectations are to meet higher levels of accuracy. In this paper we have implemented sentimental analysis of tweets in South Indian language Malayalam. The model used is Recurrent Neural Networks Long Short-Term Memory, a deep learning technique to predict the sentiments analysis. Achieved accuracy was found increasing with quality and depth of the datasets.

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Objective: To compare and evaluate the bond strength of a fiber post cemented to different post space diameters using two commercially available resin cement. Methodology: 60 freshly extracted maxillary central incisor teeth with similar dimensions were selected and sectioned horizontally from CEJ. Endodontic treatment was done on all specimens and divided into two groups Group 1 and 2 (n=30) based on the post space diameter (0.9mm and 1.1mm). Each group was subdivided into two 1A, 1B, 2A, 2B (n=15) according to the cement used. Following the post space preparations, the canals were rinsed and dried. The adhesive resin cement was applied and posts were seated to full depth and excess cement was removed. After 24 hours specimens underwent 10,000 thermal cycles and preserved in saline solution. Specimens were mounted into universal testing machine and tensile force at a crosshead speed of 1 mm/ min was applied to the posts until they debond from the root canals. Data was analyzed using ANOVA test, Independent t test and Tukey HSD test. Result: The result shows increased bond strength in snug fit than passive fit. ie; more bond strength was observed in Group 1A (mean =26.75 KgF) and Group 1B (mean =15.72 KgF) where post size and peeso reamer drill size were same. When comparing two cements RELYX shows more bond strength (1A=26.75, 2A=14.82) than PANAVIA cement (1B=15.72, 2B=10.51). Conclusion: A post with snug fit post space preparation shows better resistance to pull out test than over prepared post space preparation. Cement RELYX U-200 shows higher tensile bond strength than PANAVIA-F cement.