Abstract:Lithium-ion batteries (Li-ion) have revolutionized energy storage technology, becoming integral to our daily lives by powering a diverse range of devices and applications. Their high energy density, fast power response, recyclability, and mobility advantages have made them the preferred choice for numerous sectors. This paper explores the seamless integration of Prognostics and Health Management within batteries, presenting a multidisciplinary approach that enhances the reliability, safety, and performance of these powerhouses. Remaining useful life (RUL), a critical concept in prognostics, is examined in depth, emphasizing its role in predicting component failure before it occurs. The paper reviews various RUL prediction methods, from traditional models to cutting-edge data-driven techniques. Furthermore, it highlights the paradigm shift toward deep learning architectures within the field of Li-ion battery health prognostics, elucidating the pivotal role of deep learning in addressing battery system complexities. Practical applications of PHM across industries are also explored, offering readers insights into real-world implementations.This paper serves as a comprehensive guide, catering to both researchers and practitioners in the field of Li-ion battery PHM.
Abstract:Geriatric depression is a common mental health condition affecting majority of older adults in the US. As per Attention Restoration Theory (ART), participation in outdoor activities is known to reduce depression and provide restorative benefits. However, many older adults, who suffer from depression, especially those who receive care in organizational settings, have less access to sensory experiences of the outdoor natural environment. This is often due to their physical or cognitive limitations and from lack of organizational resources to support outdoor activities. To address this, we plan to study how technology can bring the restorative benefits of outdoors to the indoor environments through augmented spatial natural soundscapes. Thus, we propose an interview and observation-based study at an assisted living facility to evaluate how augmented soundscapes substitute for outdoor restorative, social, and experiential benefits. We aim to integrate these findings into a minimally intrusive and intuitive design of an interactive augmented soundscape, for indoor organizational care settings.
Abstract:Traditional single-factor authentication possesses several critical security vulnerabilities due to single-point failure feature. Multi-factor authentication (MFA), intends to enhance security by providing additional verification steps. However, in practical deployment, users often experience dissatisfaction while using MFA, which leads to non-adoption. In order to understand the current design and usability issues with MFA, we analyze aggregated user generated comments (N = 12,500) about application-based MFA tools from major distributors, such as, Amazon, Google Play, Apple App Store, and others. While some users acknowledge the security benefits of MFA, majority of them still faced problems with initial configuration, system design understanding, limited device compatibility, and risk trade-offs leading to non-adoption of MFA. Based on these results, we provide actionable recommendations in technological design, initial training, and risk communication to improve the adoption and user experience of MFA.