Daytime Data and LSTM can Forecast Tomorrow’s Stress, Health, and Happiness

© 2019 IEEE. Accurately forecasting well-being may enable people to make desirable behavioral changes that could improve their future well-being. In this paper, we evaluate how well an automated model can forecast the next-day's well-being (specifically focusing on stress, health, and happiness) from static models (support vector machine and logistic regression) and time-series models (long short-term memory neural network models (LSTM)) using the previous seven days of physiological, mobile phone, and behavioral survey data. We especially examine how using only a portion of the day's data (e.g. just night-time, or just daytime) influences the forecasting accuracy. The results show that accuracy is improved, across every condition tested, by using an LSTM instead of using static models. We find that daytime-only physiology data from wearable sensors, using an LSTM, can provide an accurate forecast of tomorrow's well-being using students' daily life data (stress: 80.4%, health: 86.0%, and happiness: 79.1%), achieving the same accuracy as using data collected from around the clock. These findings are valuable steps toward developing a practical and convenient well-being forecasting system

Bowdoin Orient v.139, no.1-26 (2009-2010)

https://digitalcommons.bowdoin.edu/bowdoinorient-2010s/1000/thumbnail.jp

Understanding Quantum Technologies 2022

Understanding Quantum Technologies 2022 is a creative-commons ebook that provides a unique 360 degrees overview of quantum technologies from science and technology to geopolitical and societal issues. It covers quantum physics history, quantum physics 101, gate-based quantum computing, quantum computing engineering (including quantum error corrections and quantum computing energetics), quantum computing hardware (all qubit types, including quantum annealing and quantum simulation paradigms, history, science, research, implementation and vendors), quantum enabling technologies (cryogenics, control electronics, photonics, components fabs, raw materials), quantum computing algorithms, software development tools and use cases, unconventional computing (potential alternatives to quantum and classical computing), quantum telecommunications and cryptography, quantum sensing, quantum technologies around the world, quantum technologies societal impact and even quantum fake sciences. The main audience are computer science engineers, developers and IT specialists as well as quantum scientists and students who want to acquire a global view of how quantum technologies work, and particularly quantum computing. This version is an extensive update to the 2021 edition published in October 2021.Comment: 1132 pages, 920 figures, Letter forma