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The number of people turning to the Internet to search for a diverse range of health-related subjects continues to grow and with this multitude of information available, duplicate questions become more frequent and finding the most appropriate answers becomes problematic. This issue is important for questionanswering platforms as it complicates the retrieval of all information relevant to the same topic, particularly when questions similar in essence are expressed differently, and answering a given medical question by retrieving similar questions that are already answered by human experts seems to be a promising solution. In this paper we present our novel approach to detect question entailment by determining the type of question asked rather than focusing on the type of the ailment given. This unique methodology makes the approach robust towards examples which have different ailment names but are synonyms of each other. Also it enables us to check entailment at a much more fine-grained level.

In this paper, we describe our system for COIN 2019 Shared Task 1: Commonsense Inference in Everyday Narrations Ostermann et al. (2019). We show the power of leveraging state-of-the-art pre-trained language models such as BERT (Bidirectional Encoder Representations from Transformers) Devlin et al. (2018) and XLNet Yang et al. (2019) over other Commonsense Knowledge Base Resources such as ConceptNet Speer et al. (2018) and NELL Mitchell et al. (2015) for modeling machine comprehension. We used an ensemble of BERT Large and XLNet Large. Experimental results show that our model gives substantial improvements over the baseline and other systems incorporating knowledge bases and got the 2nd position on the final test set leaderboard with an accuracy of 90.5%.

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Deployment of renewable energy resources on distributed energy system has reduced the reliance and transmission losses from the utility grid. It also helps to improve the system stability near the load center. Solar and wind are the two highly utilized green energy resources in present scenario. However, the fluctuations of solar irradiation, temperature, wind velocity are the preeminent issue for this type of systems which affects the efficiency of the solar and wind energy system. It requires the interfacing unit to stabilize the output voltage. The proposed work deals with the close loop boost converter with PID controller, which is used to attain a stabilized voltage despite of parameter changes and load disturbances. Designed system will help to analyze the better stable output voltage with efficient system having minimum fluctuation.