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With the increased use of social media platforms by people across the world, many new interesting NLP problems have come into existence. One such being the detection of sarcasm in the social media texts. We present a corpus of tweets for training custom word embeddings and a Hinglish dataset labelled for sarcasm detection. We propose a deep learning based approach to address the issue of sarcasm detection in Hindi-English code mixed tweets using bilingual word embeddings derived from FastText and Word2Vec approaches. We experimented with various deep learning models, including CNNs, LSTMs, Bi-directional LSTMs (with and without attention). We were able to outperform all state-of-the-art performances with our deep learning models, with attention based Bi-directional LSTMs giving the best performance exhibiting an accuracy of 78.49%.

Introduction: Increasing competition in every field today also affects the healthcare industry. The most important competitive advantage of health service providers is to provide quality health services The need for increased quality of healthcare services has been identified via health‐ related information and advances in technology, changes in expectations and opinions about health care, an increase in individuals involvement in their health care and increased cost and competitiveness in the health sector. Objective: to assess the level of satisfaction on quality of Nursing care among patients. Design: Descriptive cross sectional survey design was chosen to assess the level of satisfaction on quality of nursing care. Participants: The sample size for the study was 60. Nonprobability convenient sampling technique was used to select the sample. Tools : The research toolwas developed in English after an extensive review of expert opinion. The standardized Laschinger PSNCQQ (Patient Satisfaction with Nursing Care Quality Questionnaire) 19 items rating scale consisting of nursing care during hospital stay was used for this study. Results: Among Patients 24(40%) had excellent satisfaction with quality of nursing care and 18(30%) had very good satisfaction with quality of nursing care and 18(30%) good satisfaction withquality of nursing care and no patient had fair and poor levels satisfaction Conclusion: The study was done to assess the level of satisfaction with quality of nursing care among patients. The result of the study shows that most of the patients were satisfied with thequality of nursing care, and there is significant association between level of level of Satisfaction with quality of Nursing care among patients with their selected demographic variables sex and education.