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Identification of Sarcasm in Textual Data: A Comparative Study

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Journal of Data and Information Science 2019年第4期4卷 56-83页

作者： pulkit Mehndiratta Devpriya Soni Jaypee Institute of Information Technology

Purpose:Ever increasing penetration of the Internet in our lives has led to an enormous amount of multimedia content generation on the *** data contributes a major share towards data generated on the world wide *** people’s sentiment is an important aspect of natural language processing,but this opinion can be biased and incorrect,if people use sarcasm while commenting,posting status updates or reviewing any product or a ***,it is of utmost importance to detect sarcasm correctly and make a correct prediction about the people’s ***/methodology/approach:This study tries to evaluate various machine learning models along with standard and hybrid deep learning models across various standardized *** have performed vectorization of text using word embedding *** has been done to convert the textual data into vectors for analytical *** have used three standardized datasets available in public domain and used three word embeddings i.e Word2Vec,GloVe and fastText to validate the ***:The results were analyzed and conclusions are *** key finding is:the hybrid models that include Bidirectional LongTerm Short Memory(Bi-LSTM)and Convolutional Neural Network(CNN)outperform others conventional machine learning as well as deep learning models across all the datasets considered in this study,making our hypothesis *** limitations:Using the data from different sources and customizing the models according to each dataset,slightly decreases the usability of the ***,overall this methodology provides effective measures to identify the presence of sarcasm with a minimum average accuracy of 80%or above for one dataset and better than the current baseline results for the other *** implications:The results provide solid insights for the system developers to integrate this model into real-time analysis of any review or comment posted in the public *** study

关键词： Machine learning Artificial neural networks Word embedding Text vectorization Accuracy

Attenuation characteristics of monolayer graphene by Pi-and T-networks modeling of multilayer microstrip line

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Journal of Semiconductors 2017年第9期38卷 25-30页

作者： pulkit Sharma Sumit Pratap Singh Kamlesh Patel Department of Electronic Science University of Delhi South CampusBenito Juarez RoadNew Delhi-110021India

The impedances of Pi- and T- networks are obtained from the measured S-parameters of the multilayer microstrip line by modeling as an attenuator. The changes in impedances have been analyzed for the properties of various superstrates at the microwave ranges. With graphene on glass and graphene on quartz loadings, the impedances have increased and shifted towards lower frequency more in Pi-network than T-network modeling. This shift has become more prominent at higher frequency for the graphene on glass than graphene on quartz. A little increase in attenuation is found for graphene on glass or quartz than bare glass and quartz. The present study can be extended to obtain attenuation characteristic of any thin film by simple experimental method in the microwave frequencies.

关键词： microstrip line attenuator graphene S-parameters impedance

Attention deficit hyperactivity disorder and comorbidity: A review of literature

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World Journal of Clinical Cases 2019年第17期7卷 2420-2426页

作者： Sundar Gnanavel Pawan Sharma pulkit Kaushal Sharafat Hussain Child Mental Health Services TeesEsk and Wear Valleys NHS Foundation TrustDurham DH1 4LWUnited Kingdom Department of Psychiatry Patan Academy of Health SciencesPatan 44700Nepal Northumberland Tyne and Wear NHS foundation TrustNewcastle NE3 3XTUnited Kingdom

Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder with onset in early *** is a clinically heterogenous condition with comorbidity posing a distinct challenge to diagnosing and managing these children and *** review aims to provide an overview of comorbidity with ADHD including other neurodevelopmental disorders,learning disorders,externalising and internalising *** in screening for,diagnosing and managing comorbidity with ADHD are ***,methodological challenges and future directions in research in this interesting field are highlighted.

关键词： Attention deficit hyperactivity disorder Comorbidity Review

Regression analysis and features of negative activation energy for MHD nanofluid flow model:A comparative study

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Propulsion and Power Research 2023年第2期12卷 273-283页

作者： B.Kumara Prachi Abhinav Singhal R.Nandkeolyar pulkit Kumar Ali J.Chamkha School of Mathematics Thapar Institute of Engineering and TechnologyPatiala 147004PunjabIndia Department of Applied Sciences and Humanities RITRoorkee 247667India School of Sciences Christ(Deemed to be University)Delhi NCR 201003India Department of Mathematics National Institute of TechnologyJamshedpur 831014India Department of Applied Mechanics Indian Institute of TechnologyDelhi 110016India Faculty of Engineering Kuwait College of Science and TechnologyDoha DistrictKuwait

This article elucidates the impact of activation energy on magnetohydrodynamic(MHD)stagnation point nanofluid flow over a slippery surface in a porous regime with thermophoretic and Brownian *** activation energy is scarce in practice,but the impact of negative activation energy could not be neglected as it is noticed in chemical *** rate of some Arrhenius-compliant reactions is retarded by increasing the temperature and is therefore associated with negative activation energies,such as exothermic binding of urea or *** some processes,the temperature dependence of the pressure-induced unfolding and the urea-induced unfolding of proteins at ambient pressure give negative activation *** present mathematical model is solved with successive linearization method(a spectral technique).A comparison of results is made for negative and positive values of activation *** from it,the quadratic multiple regression model is discussed briefly and explained with bar *** is observed that with rise in unsteadiness parameter from 0 to 1(taking positive activation energy),skin friction and Sherwood number are increased by 9.36%and 19%respectively,and Nusselt number is decreased by 26%.However,for negative activation energy,9.36%and 112%enhancement is observed in skin friction and Sherwood number,respectively.

关键词： Negative activation energy Regression analysis Successive linearization method Porous medium

High Dimensionality Effects on the Efficient Frontier: A Tri-Nation Study

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Journal of Data Analysis and Information Processing 2016年第1期4卷 13-20页

作者： Rituparna Sen pulkit Gupta Debanjana Dey Indian Statistical Institute Chennai India Indian Institute of Technology Kharagpur India Indian Institute of Management Calcutta India

Markowitz Portfolio theory under-estimates the risk associated with the return of a portfolio in case of high dimensional data. El Karoui mathematically proved this in [1] and suggested improved estimators for unbiased estimation of this risk under specific model assumptions. Norm constrained portfolios have recently been studied to keep the effective dimension low. In this paper we consider three sets of high dimensional data, the stock market prices for three countries, namely US, UK and India. We compare the Markowitz efficient frontier to those obtained by unbiasedness corrections and imposing norm-constraints in these real data scenarios. We also study the out-of-sample performance of the different procedures. We find that the 2-norm constrained portfolio has best overall performance.

关键词： High Dimensional Covariance Matrix Estimation Minimum-Variance Portfolio Norm Con-Strained Portfolio