The landscape of research in science and engineering is heavily reliant on computation and data processing. There is continued and expanded usage by disciplines that have historically used advanced computing resources, new usage by disciplines that have not traditionally used HPC, and new modalities of the usage in Data Science, Machine Learning, and other areas of AI. Along with these new patterns have come new advanced computing resource methods and approaches, including the availability of commercial cloud resources. The Coalition for Academic Scientific Computation (CASC) has long been an advocate representing the needs of academic researchers using computational resources, sharing best practices and offering advice to create a national cyberinfrastructure to meet US science, engineering, and other academic computing needs. CASC has completed the first of what we intend to be an annual survey of academic cloud and data center usage and practices in analyzing return on investment in cyberinfrastructure.
Critically important findings from this first survey include the following: many of the respondents are engaged in some form of analysis of return in research computing investments, but only a minority currently report the results of such analyses to their upper-level administration. Most respondents are experimenting with use of commercial cloud resources but no respondent indicated that they have found use of commercial cloud services to create financial benefits compared to their current methods. There is clear correlation between levels of investment in research cyberinfrastructure and the scale of both cpu core-hours delivered and the financial level of supported research grants. Also interesting is that almost every respondent indicated that they participate in some sort of national cooperative or nationally provided research computing infrastructure project and most were involved in academic computing-related organizations, indicating a high degree of engagement by institutions of higher education in building and maintaining national research computing ecosystems. Institutions continue to evaluate cloud-based HPC service models, despite having generally concluded that so far cloud HPC is too expensive to use compared to their current methods.
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Taking Stock of the Present and Future of Smart Technologies for Older Adults and Caregivers
Technology has the opportunity to assist older adults as they age in place, coordinate caregiving resources, and meet unmet needs through access to resources. Currently, older adults use consumer technologies to support everyday life, however these technologies are not always accessible or as useful as they can be. Indeed, industry has attempted to create smart home technologies (e.g., Microsoft HomeOS, Intel CareNet) with older adults as a target user group, however these solutions are oftenmore focused on the technical aspects and are short lived. In this paper, we advocate for older adults being involved in the design process - from initial ideation to product development to deployment. We
encourage federally funded researchers and industry to create compensated, diverse older adult advisory boards to address stereotypes about aging while ensuring their needs are considered.
We envision artificial intelligence (AI) systems that augment resources instead of replacing them - especially in under-resourced communities. Older adults rely on their caregiver networks and community organizations for social, emotional, and physical support; thus, AI should be used to coordinate resources better and lower the burden of connecting with these resources. Although sociotechnical smart systems can help identify needs of older adults, the lack of affordable research
infrastructure and translation of findings into consumer technology perpetuates inequities in designing for diverse older adults. In addition, there is a disconnect between the creation of smart sensing systems and creating understandable, actionable data for older adults and caregivers to utilize. We ultimately
advocate for a well-coordinated research effort across the United States that connects older adults, caregivers, community organizations, and researchers together to catalyze innovative and practical research for all stakeholders.
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- Award ID(s):
- 1814725
- NSF-PAR ID:
- 10249396
- Date Published:
- Journal Name:
- A Computing Community Consortium (CCC) Quadrennial Paper
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Researchers have designed technologies for and with older adults to help them age in place, but there is an opportunity to support older adults in creating customized smart devices for themselves through electronic toolkits. We developed a plan for iterating on Craftec - one of the first electronic toolkits designed for older adults - informed by the results of a participatory design workshop and user evaluation. We focused on supporting older adults to create exemplar artifacts, such as medication adherence systems. We contribute the exemplars and the current plan for components of the Craftec system as a way to support older adults to design technology for themselves.more » « less
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Background As the older adult population increases there is a great need of developing smart healthcare technologies to assist older adults. Robot-based homecare systems are a promising solution to achieving this goal. This study aims to summarize the recent research in homecare robots, understand user needs and identify the future research directions. Methods First, we present an overview of the state-of-the-art in homecare robots, including the design and functions of our previously developed ASCC Companion Robot (ASCCBot). Second, we conducted a user study to understand the stakeholders’ opinions and needs regarding homecare robots. Finally, we proposed the future research directions in this research area in response to the existing problems. Results Our user study shows that most of the interviewees emphasized the importance of medication reminder and fall detection functions. The stakeholders also emphasized the functions to enhance the connection between older adults and their families and friends, as well as the functions to improve the efficiency and productivity of the caregivers. We also identified three major future directions in this research area: human-machine interface, learning and adaptation, and privacy protection. Conclusions The user study discovered some new useful functions that the stakeholders want to have and also validated the developed functions of the ASCCBot. The three major future directions in the homecare robot research area were identified.
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Background Monitoring technologies are used to collect a range of information, such as one’s location out of the home or movement within the home, and transmit that information to caregivers to support aging in place. Their surveilling nature, however, poses ethical dilemmas and can be experienced as intrusive to people living with Alzheimer disease (AD) and AD-related dementias. These challenges are compounded when older adults are not engaged in decision-making about how they are monitored. Dissemination of these technologies is outpacing our understanding of how to communicate their functions, risks, and benefits to families and older adults. To date, there are no tools to help families understand the functions of monitoring technologies or guide them in balancing their perceived need for ongoing surveillance and the older adult’s dignity and wishes.
Objective We designed, developed, and piloted a communication and education tool in the form of a web application called Let’s Talk Tech to support family decision-making about diverse technologies used in dementia home care. The knowledge base about how to design online interventions for people living with mild dementia is still in development, and dyadic interventions used in dementia care remain rare. We describe the intervention’s motivation and development process, and the feasibility of using this self-administered web application intervention in a pilot sample of people living with mild AD and their family care partners.
Methods We surveyed 29 mild AD dementia care dyads living together before and after they completed the web application intervention and interviewed each dyad about their experiences with it. We report postintervention measures of feasibility (recruitment, enrollment, and retention) and acceptability (satisfaction, quality, and usability). Descriptive statistics were calculated for survey items, and thematic analysis was used with interview transcripts to illuminate participants’ experiences and recommendations to improve the intervention.
Results The study enrolled 33 people living with AD and their care partners, and 29 (88%) dyads completed the study (all but one were spousal dyads). Participants were asked to complete 4 technology modules, and all completed them. The majority of participants rated the tool as having the right length (>90%), having the right amount of information (>84%), being very clearly worded (>74%), and presenting information in a balanced way (>90%). Most felt the tool was easy to use and helpful, and would likely recommend it to others.
Conclusions This study demonstrated that our intervention to educate and facilitate conversation and documentation of preferences is preliminarily feasible and acceptable to mild AD care dyads. Effectively involving older adults in these decisions and informing care partners of their preferences could enable families to avoid conflicts or risks associated with uninformed or disempowered use and to personalize use so both members of the dyad can experience benefits.
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