Know more about how Music Therapy helps patients of Alzheimers/Dementia in faster recovery.
Alzheimers disease is a developing disease during middle or old age that demolishes memory and important mental functions due to the decline of the brain. Alzheimers disease, also known as Dementia, is one of the most common diseases in people over the age of sixty five. It can be caused by a combination of genetics, lifestyle, and environmental factors which can effect the brain over time. The main symptoms of Alzheimers are confusion and memory loss. Many people experience a combination of symptoms that are cognitive, behavioral, mood related, and psychological. Treatment for this disease can involve cognitive-enhancing medication. However, this can only temporarily improve the symptoms. Although, there is no cure for people that have Alzheimers, music has been shown to be a very powerful tool for minimizing symptoms and recalling memories for these patients.
Music therapy has been shown to be one of the most effective ways of helping patients with Alzheimers disease. It is one of the types of active aging programs which are offered to elderly people. Pharmacological treatment for symptoms of this disease requires very high doses of medication. These drugs actually worsen motor function causing a decline in cognitive function. A natural treatment for Alzheimers/Dementia includes music therapy. Music therapy uses music to improve communication, learning, mobility, and other mental and physical functions.
Devi Kasturi graduated from the University of Texas at Dallas in May of 2022 with a Bachelor of Science degree in Psychology and a minor in Vocal Music. She has been passionate about music her entire life and can testify that music has made a major difference in her life. Devi has won several awards for singing both state and district wide. She likes to spend her time volunteering at nursing homes and with hospice patients. Devi thinks music is a calling and a gift that will benefit all of mankind. Science and music are a powerful combination and she hopes to continue her research in this field. Her future plans include starting pharmacy school and she will continue to practice music as a way of life.
Diving deep into the analysis of financial talks on Reddit that made the fluctuation in the stock prices.
The following document by Omkar Ajnadkar shows that the social media has become an important part of digital web life, the effect it has on financial decisions is also increasing. The social media conversations on websites like Twitter, Reddit and Facebook are having an ever-increasing effect on stock prices as well as the way in which companies make decisions. This has made it important to analyze this data to make accurate predictions of stock prices in future. In this paper, we try to analyze financial discussions among users of Reddit by extracting hidden patterns, themes and user characters to predict future actions and consequences on the market.
We explore techniques based on natural language processing to pass conversations through data pipeline along with extracting stock tickers, manual as well as automatic theme extraction and word clouds. We also discuss common text processing techniques which can also be applied to other problems involving text analysis along with correlation model focusing on sentiment analysis as a predictor of stock movement.
Omkar Ajnadkar is a MSCS student at The University of Texas at Dallas in Machine and Deep learning . He has worked in the domain of Data Science, Machine Learning and Full Stack Web Development in various startups. He also likes to research in the domain of Computer Vision and Natural Language Processing and have published papers.
Solving an Image with Sudoku 9×9 grid using image-processing techniques and backtracking algorithm
This project aims to assist users during the sudoku’s solving process, which could help users know if they are solving the puzzle correctly. The user needs to input an image of a 9×9 Sudoku grid which the model will use to solve the puzzle. The model is developed in Python using image processing, optical character recognition, and backtracking algorithm. These techniques are used in cutting edge technologies like the autonomous vehicle for parking assistant, detecting lanes enabling security, enabling virtual advertisement in sports, etc.
Akash is a graduate student at The University of Texas at Dallas, and currently, he is pursuing a Master’s in Computer Science with a specialization in Intelligent Systems. His areas of interest can be broadly classified as Computer Vision, Robotics & Software Development.
Please feel free to connect with Akash over LinkedIn.