http://localhost:8080/xmlui/handle/123456789/3548 2026-06-23T06:30:01Z http://localhost:8080/xmlui/handle/123456789/3551 Title: A Musical Composition Assistant System using LSTM Authors: Fegade, Poonam G.; Jagtap, Trupti Abstract: Universally, music is one of the elements that create harmony in this world. Traditionally playing music or creating it has always been seen as a manual task. Music can be created with the help of instruments, voices and sounds. In the Modern Era of technology and AI, we can automate this process. For this, we must understand the basic structure of how music forms and view it scientifically. For the proposed system, we are using RNN-LSTM algorithm to generate music from given sample inputs. A Musical Composition Assistant System (MCAS) involves transformation of music scores into time series representation, encoding the music. A model is designed to execute this algorithm where data is represented with the help of musical instrument digital interface (MIDI) file format for easier access and better understanding. Pre-processing of data before feeding it into the model, revealing methods to read, process and prepare MIDI files for input are used. This system creates good music pieces in MIDI format with given input. The proposed system uses Flask API to interact with the frontend 2022-07-15T00:00:00Z http://localhost:8080/xmlui/handle/123456789/3550 Title: Motions Detection of Senior Citizen Using Machine Learning Authors: Bagal, V. C.; Hanpode, Pratik Abstract: Recognizing human motions is important from security point of view at any level and scenario. As there are plenty of human motions in a fraction of second, so classification of each motion is challenging task in real world. A Human activity Recognition System recognizes the Shapes and or orientation depending on implementation to task the system into per forming some job. Movement is a form of nonverbal information. A person can make numerous movements at a time. The proposed work aims to detect the movement and actions of a person using image detection methodology. Human activity recognition (HAR) aims to recognize activities from a series of observations on the actions of subjects and the environmental conditions. The vision-based HAR research is the basis of many applications including video surveillance, healthcare, and human-computer interaction (HCI). The proposed work is suitable to identify objectionable human motions of senior citizen who live alone at home. 2022-09-15T00:00:00Z