Grass-roots initiatives such as the 1000 Functional Connectomes Project (FCP) and International Neuroimaging Data- sharing Initiative (INDI) [1] are successfully amassing and sharing large-scale brain ...

Abstract: Text preprocessing is a key step in Natural Language Processing (NLP) that deals with the cleaning, tokenization and structure of text before building models. A comparison of the recent ...

A controversy is swirling at a Texas university. The trigger? A flowchart. On Dec. 1, the new chancellor of the Texas Tech University system sent professors a diagram laying out a chain of approval ...

What if you could simplify the complexities of natural language processing (NLP) without sacrificing accuracy or efficiency? For years, developers and researchers have wrestled with the steep learning ...

The Automated Answer Paper Evaluator leveragesmachine learning techniques to provide an efficient and accurate assessment of student answer sheets. This system integrates various technologies, ...

The Dataset and the dialect identification problem were addressed by Qatar Computing Research Institute. I implemented a data-scraper, data-preprocessor (Regex and NLTK), data-modeling (SVM with ...

ABSTRACT: Pregnancy presents a unique clinical scenario where the safety of pharmacological interventions is of paramount importance. The potential teratogenic risks associated with drug intake during ...

Abstract: Research in Bengali Natural Language Processing (BNLP) is rapidly expanding. Despite being one of the most widely spoken languages in the world, BNLP research remains insufficient, ...

Test automation has always been about speed. We measured success by how many tests we ran per minute and celebrated shorter regression cycles. However, we now stand at the edge of the next evolution.