Mca project download with source code

  Predicting dark triad personality traits from twitter usage and a linguistic analysis of tweets   PROJECT ID: PYTHON20   PROJECT NAME: Predicting dark triad personality traits from twitter usage and a linguistic analysis of tweets   PROJECT CATEGORY: MCA / BCA / BCCA / MCM / POLY / ENGINEERING   PROJECT ABSTRACT: Social media sites are now the most populardestination for Internet users, providing social scientists with agreat opportunity to understand online behaviour. There are agrowing number of research papers related to social media, asmall number of which focus on personality prediction. To date,studies have typically focused on the Big Five traits ofpersonality, but one area which is relatively unexplored is that ofthe anti-social traits of narcissism, Machiavellianism andpsychopathy, commonly referred to as the Dark Triad. Thisstudy explored the extent to which it is possible to determine anti-social personality traits based on Twitter use. This wasperformed by

  Parkinson disease prediction using Regression technique     PROJECT ID: PYTHON19   PROJECT NAME: Parkinson disease prediction using Regression technique   PROJECT CATEGORY: MCA / BCA / BCCA / MCM / POLY / ENGINEERING   PROJECT ABSTRACT: Parkinson’s disease (PD) is a member of a larger group of neuromotor diseases marked by the progressive death of dopamineproducing cells in the brain. Providing computational tools for Parkinson disease using a set of data that contains medical information is very desirable for alleviating the symptoms that can help the amount of people who want to discover the risk of disease at an early stage. This paper proposes a new hybrid intelligent system for the prediction of PD progression using noise removal, clustering and prediction methods. Principal Component Analysis (PCA) and Expectation Maximization (EM) are respectively employed to address the multi-collinearity problems in the experimental datasets and clustering the data. We then

  Object detection using openCV RNN algorithm     PROJECT ID: PYTHON18   PROJECT NAME: Object detection using openCV RNN algorithm   PROJECT CATEGORY: MCA / BCA / BCCA / MCM / POLY / ENGINEERING   PROJECT ABSTRACT: Object detection is a task in computer vision that involves identifying the presence, location, and type of one or more objects in a given photograph. It is a challenging problem that involves building upon methods for object recognition (e.g. where are they), object localization (e.g. what are their extent), and object classification (e.g. what are they). In recent years, deep learning techniques have achieved state-of-the-art results for object detection, such as on standard benchmark datasets and in computer vision competitions. Most notably is the R-CNN, or Region-Based Convolutional Neural Networks, and the most recent technique called Mask R-CNN that is capable of achieving state-of-the-art results on a range of object detection tasks. The regio