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Building Reconfigurable Systems Using Commercial FPGAs
Published in Juan José Rodríguez Andina, Eduardo de la Torre Arnanz, María Dolores Valdés Peña, FPGAs, 2017
Juan José Rodríguez Andina, Eduardo de la Torre Arnanz, María Dolores Valdés Peña
Self-management refers to the ability of systems to manage themselves according to high-level objectives, reducing external intervention. This term is equivalent to self-adaptable or autonomic computing, according to the terminology coined by Paul Horn (Kephart and Chess 2003). According to the Oxford Dictionary, adaptation in biology is the process of change by which an organism or species becomes better suited to its environment. In the same way, generalizing the definition for self-adaptive software by Salehie and Tahvildari (2009), a self-managing system can be defined as one that adjusts various artifacts or attributes in response to changes in itself or in its context.
Sensor Networking Software and Architectures
Published in John R. Vacca, Handbook of Sensor Networking, 2015
In MANNA, three functional sets are defined from top to bottom: services set, functions set, and WSN models set. At the top layer, a service consists of multiple functionalities set. In general, a service is called by WSN model(s) according to the configuration of the application. In [42], an example, namely, design and evaluation of fire detection systems, is proposed that demonstrates the application of MANNA. The system is able to provide self-management services: the self-organization, self-configuration, selfservice, and self-maintenance. It illustrated a layered heterogeneous WSN design and analysis of distributed self-management programs.
Cloud computing for big data
Published in Jun Deng, Lei Xing, Big Data in Radiation Oncology, 2019
Cloud computing has also been compared with IBM’s autonomic computing model that was introduced in 2001 (Kephart and Chess 2003). Autonomic computing systems implement self-management procedures, meaning that they can react to internal and external observations without human intervention. They were originally envisioned to overcome the management complexity of computer systems. The Cloud computing model shares some of the autonomic features such as automatic resource provisioning but lacks the complexity of autonomic computing systems.
An empirically grounded sociotechnical perspective on designing virtual agents for older adults
Published in Human–Computer Interaction, 2020
Some work exists that examines the influence of IVA embodiment on OAs’ perceptions of the IVA as connected to the IVAs’ social behavior (e.g. the work by Looije, Neerincx, and Cnossen (2010) on computer-based personal assistants designed to persuade older adults to effectively adopt daily health self-management practices). However, in contrast, the connection between the interface/interaction design of intelligent IVAs and OAs’ personal, social, and cultural aspects remains understudied, especially through the lens of a sociotechnical approach based in information studies. Given the sensitivity of older adults to sociocultural factors (Neves & Savago, 2019; Waycott et al., 2015) and yet at the same time the growing interest in designing IVAs that improve their lives, it becomes increasingly important to integrate socio-cultural factors into design (Munteanu & Salah, 2017).
Employer and academic staff perceptions of science and engineering graduate competencies
Published in Australasian Journal of Engineering Education, 2020
Academic teaching staff highlighted that the top five most important graduate competencies for today were problem solving, critical thinking, written and oral communication, and, self-management (Table 2). They further thought that in 10 years’ time, the most important competencies graduates needed would be problem solving, critical thinking, written communication, self-management, and computer/ICT use. However, when asked for their views of current graduates’ competency levels in comparison to competencies importance, similar to employers, they thought graduates’ performance was below that of importance for all competencies except for digital interpersonal skills.