INTRODUCTION AND OBJECTIVES: Currently, no social media platform has deployed a real time system which can analyse users' state of mind based on day to day posts on continual basis and detect the onset of depression, suicidal or self harming behaviour etc. Platforms majorly rely on manual reporting of suicidal and self harming behavior. In this paper, we propose a real time, deep learning based system for affective analysis of a user's online social media posts of multimodal nature, with the objective of detecting onset of depression and suicidal or self harming behaviour; as depression often drives people to commit suicide or harm themselves physically.METHODS: Joint representations are obtained by fusing the individual vector representations of multiple modalities from user's social media feed: text, image and videos. These vector representations are in turn obtained through state of the art approaches for each modality e.g. VGG-16 for feature extraction from images, word2vec for text and Faster R-CNN on video frames. These joint representations are used to obtain weighted average score which can be used for making the final classification using the Softmax prediction layer. SIGNIFICANCE AND IMPACT: To the best of our knowledge, this is the first research where the use of deep learning techniques has been proposed for real time detection of onset of depression and suicidal behaviour by analysing multimodal user generated content.
Software industry always demands high-quality software that must be reliable, robust, flexible, reusable, effective, and extendable. To improve software quality refactoring is an efficient and frequently opted technique. Most of the refactoring work has been done on the source code level less work has been done on model-based. Model base refactoring is more difficult to estimate. In this research paper, the multi-objective evolutionary algorithm based on decomposition (MOEA/D) is applied to find how software quality is affected by refactoring technique. It impacts the software quality in both positive as well as negative way.
Academic management system, which is a comprehensive software solution designed to streamline and automate various administrative and academic processes within educational institutions. The system serves as a centralized platform that integrates multiple functionalities, including student information management, course registration, attendance tracking, academic record keeping, etc.
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