While voice user interfaces offer increased accessibility due to hands-free and eyes-free interactions, older adults often have challenges such as constructing structured requests and perceiving how such devices operate. Voice-first user interfaces have the potential to address these challenges by enabling multimodal interactions. Standalone voice + touchscreen Voice Assistants (VAs), such as Echo Show, are specific types of devices that adopt such interfaces and are gaining popularity. However, the affordances of the additional touchscreen for older adults are unknown. Through a 40-day real-world deployment with older adults living independently, we present a within-subjects study (N = 16; age M = 82.5, SD = 7.77, min. = 70, max. = 97) to understand how a built-in touchscreen might benefit older adults during device setup, conducting self-report diary survey, and general uses. We found that while participants appreciated the visual outputs, they still preferred to respond via speech instead of touch. We identified six design implications that can inform future innovations of senior-friendly VAs for managing healthcare and improving quality of life.

Population aging is an increasingly important consideration for health care in the 21th century, and continuing to have access and interact with digital health information is a key challenge for aging populations. Voice-based Intelligent Virtual Assistants (IVAs) are promising to improve the Quality of Life (QoL) of older adults, and coupled with Ecological Momentary Assessments (EMA) they can be effective to collect important health information from older adults, especially when it comes to repeated time-based events. However, this same EMA data is hard to access for the older adult: although the newest IVAs are equipped with a display, the effectiveness of visualizing time-series based EMA data on standalone IVAs has not been explored. To investigate the potential opportunities for visualizing time-series based EMA data on standalone IVAs, we designed a prototype system, where older adults are able to query and examine the time-series EMA data on Amazon Echo Show - a widely used commercially available standalone screen-based IVA. We conducted a preliminary semi-structured interview with a geriatrician and an older adult, and identified three findings that should be carefully considered when designing such visualizations.

Current medical question answering systems have difficulty processing long, detailed and informally worded questions submitted by patients, called Consumer Health Questions (CHQs). To address this issue, we introduce a medical question understanding and answering system with knowledge grounding and semantic self-supervision. Our system is a pipeline that first summarizes a long, medical, user-written question, using a supervised summarization loss. Then, our system performs a two-step retrieval to return answers. The system first matches the summarized user question with an FAQ from a trusted medical knowledge base, and then retrieves a fixed number of relevant sentences from the corresponding answer document. In the absence of labels for question matching or answer relevance, we design 3 novel, self-supervised and semantically-guided losses. We evaluate our model against two strong retrieval-based question answering baselines. Evaluators ask their own questions and rate the answers retrieved by our baselines and own system according to their relevance. They find that our system retrieves more relevant answers, while achieving speeds 20 times faster. Our self-supervised losses also help the summarizer achieve higher scores in ROUGE, as well as in human evaluation metrics.

Khalil Mrini, Franck Dernoncourt, Seunghyun Yoon, Trung Bui, Walter Chang, Emilia Farcas, Ndapa Nakashole. Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers). 2021.

Khalil Mrini, Emilia Farcas, Ndapa Nakashole. Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers). 2021.

Voice-based Intelligent Virtual Assistants (IVAs) promise to improve healthcare management and Quality of Life (QOL) by introducing the paradigm of hands-free and eye-free interactions. However, there has been little understanding regarding the challenges for designing such systems for older adults, especially when it comes to healthcare related tasks. To tackle this, we consider the processes of care delivery and QOL enhancements for older adults as a collaborative task between patients and providers. By interviewing 16 older adults living independently or semi-independently and 5 providers, we identified 12 barriers that older adults might encounter during daily routine and while managing health. We ultimately highlighted key design challenges and opportunities that might be introduced when integrating voice-based IVAs into the life of older adults. Our work will benefit practitioners who study and attempt to create full-fledged IVA-powered smart devices to deliver better care and support an increased QOL for aging populations.

Automotive and avionics systems are complex, distributed, software-intensive systems-of-systems (SoS). Consequently, system integration is a central challenge in both domains. Important cross-cutting requirements aspects, such as security, authorization, and failure management, are best understood as properties of the interplay among sub-systems. Yet, traditional development processes address the integration challenge only late, at the level of implementation and deployment. Consequently, potentials for reuse within and across product lines are left unrealized. Furthermore, late integration leads to high calibration, configuration and redesign costs. Service-Oriented Architectures (SOAs) have emerged as a solution to the integration challenge. However, inappropriate application of SOA-principles results in a high degree of fragmentation and scattering of functionality-this leads to additional difficulties in requirements traceability and quality assurance. In this article, we give a comprehensive overview of these SOA-challenges, and present Rich Services as a hierarchical SOA blueprint and development process enabling SoS integration in a dependable way. Rich Services introduce services as hierarchical, partial interaction patterns; these interactions are then augmented with infrastructure elements to inject behaviors that address cross-cutting requirements aspects. Rich Services also seamlessly address the mapping from logical to deployment architectures. Using end-to-end failure management as an example, we illustrate the utility of Rich Services.

The Timing Definition Language (TDL) provides a component model and a tool chain as a solution for building time-safe components that can be developed independently and integrated in a distributed platform without changing the observable behavior and the code of existing components. TDL is based on the Logical Execution Time abstraction and supports the decomposition of hard real-time applications into modules that are executed logically in parallel. This paper presents the algorithms for automatic schedule generation of TDL communications over the hyperperiod. As modules may switch modes independently, we combine the messages from all modes in the schedule. Hence, we introduce several optimizations to save bandwidth and improve the schedule's feasibility.

One of the key challenges to successful systems-of-systems integration using Web services technologies is how to address crosscutting architectural concerns such as policy management, governance, and authentication, while still maintaining the lightweight implementation and deployment Jlavor that distinguishes Web services fiom earlier attempts at providing interoperable enterprise systems. To address this challenge, this article introduces the notion of a Rich Service, an extension of the standard service notion, based on an architectural pattern that allows hierarchical decomposition of system architecture according to separate concerns. Rich Services enable the capture of dzfferent system aspects and their interactions. By leveraging emerging Enterprise Service Bus technologies, Rich Services also enable a direct transition from a logical to a deployed service-oriented architecture (SOA). This results in immediate beneJits not only in SOA design, implementation, deployment, and quality assurance, but also in the traceability of architectural requirements to an SOA implementation.

This paper introduces the notion of transparent distribution of real time software components. Transparent distribution means that (1) the functional and temporal behavior of a system is the same no matter where a component is executed, (2) the developer does not have to care about the differences of local versus distributed execution of components, and (3) the components can be developed independently. We present the design and implementation of a component model for real time systems that is well suited for transparent distribution. The component model is based on logical execution time, which abstracts from physical execution time and thereby from both the execution platform and the communication topology.