31,700 research outputs found

    Design Fiction Diegetic Prototyping: A Research Framework for Visualizing Service Innovations

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    The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Purpose: This paper presents a design fiction diegetic prototyping methodology and research framework for investigating service innovations that reflect future uses of new and emerging technologies. Design/methodology/approach: Drawing on speculative fiction, we propose a methodology that positions service innovations within a six-stage research development framework. We begin by reviewing and critiquing designerly approaches that have traditionally been associated with service innovations and futures literature. In presenting our framework, we provide an example of its application to the Internet of Things (IoT), illustrating the central tenets proposed and key issues identified. Findings: The research framework advances a methodology for visualizing future experiential service innovations, considering how realism may be integrated into a designerly approach. Research limitations/implications: Design fiction diegetic prototyping enables researchers to express a range of ‘what if’ or ‘what can it be’ research questions within service innovation contexts. However, the process encompasses degrees of subjectivity and relies on knowledge, judgment and projection. Practical implications: The paper presents an approach to devising future service scenarios incorporating new and emergent technologies in service contexts. The proposed framework may be used as part of a range of research designs, including qualitative, quantitative and mixed method investigations. Originality: Operationalizing an approach that generates and visualizes service futures from an experiential perspective contributes to the advancement of techniques that enables the exploration of new possibilities for service innovation research

    Low-Cost Air Quality Monitoring Tools: From Research to Practice (A Workshop Summary).

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    In May 2017, a two-day workshop was held in Los Angeles (California, U.S.A.) to gather practitioners who work with low-cost sensors used to make air quality measurements. The community of practice included individuals from academia, industry, non-profit groups, community-based organizations, and regulatory agencies. The group gathered to share knowledge developed from a variety of pilot projects in hopes of advancing the collective knowledge about how best to use low-cost air quality sensors. Panel discussion topics included: (1) best practices for deployment and calibration of low-cost sensor systems, (2) data standardization efforts and database design, (3) advances in sensor calibration, data management, and data analysis and visualization, and (4) lessons learned from research/community partnerships to encourage purposeful use of sensors and create change/action. Panel discussions summarized knowledge advances and project successes while also highlighting the questions, unresolved issues, and technological limitations that still remain within the low-cost air quality sensor arena

    What do faculties specializing in brain and neural sciences think about, and how do they approach, brain-friendly teaching-learning in Iran?

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    Objective: to investigate the perspectives and experiences of the faculties specializing in brain and neural sciences regarding brain-friendly teaching-learning in Iran. Methods: 17 faculties from 5 universities were selected by purposive sampling (2018). In-depth semi-structured interviews with directed content analysis were used. Results: 31 sub-subcategories, 10 subcategories, and 4 categories were formed according to the “General teaching model”. “Mentorship” was a newly added category. Conclusions: A neuro-educational approach that consider the roles of the learner’s brain uniqueness, executive function facilitation, and the valence system are important to learning. Such learning can be facilitated through cognitive load considerations, repetition, deep questioning, visualization, feedback, and reflection. The contextualized, problem-oriented, social, multi-sensory, experiential, spaced learning, and brain-friendly evaluation must be considered. Mentorship is important for coaching and emotional facilitation

    IDENTITY ADAPTATION AND THE POTENTIAL FOR PSYCHOLOGICAL GROWTH FOLLOWING ADVERSITY FOR INJURED ATHLETES

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    The study was undertaken to gain a deeper understanding of the transition process out of competitive athletics experienced by competitive athletes after a career-limiting injury by examining three research questions: 1) What is the identity adaptation process of injured athletes? 2) To what extent, if any, do injured athletes experience growth following adversity? 3) What, if any, psychological skills are used in the injury/career transition processes? Nine former elite ath- letes were recruited through key informant sampling. There were three males and six females, with a mean age of 24.6 years. All participants sustained, at minimum, a season-ending injury and no longer participate in high performance athletics. Participants completed a demographic questionnaire, the Athletic Identity Measurement Scale-Plus questionnaire (AIMS-Plus), the Post Traumatic Growth Inventory-42 survey (PTGI-42), and an adapted Change Event Inventory (CEI). Additionally, semi-structured interviews were conducted. Transcripts were analyzed us- ing an Interpretative Phenomenological Analysis and themes and subthemes were identified. Analysis revealed the process of identity adaptation is influenced by pre-injury identity, auton- omy of retirement decision, transition style, current employment and time since the injury. Ac- cess to psychological skills training and competence in psychological skill usage heavily influ- enced the application of psychological skills during the rehabilitation and transition process and the outcome of using these skills. No significant evidence of growth was found using the PTGI- 42; however interview data revealed themes centred on experiencing new opportunities, the ability to transfer sport and psychological skills, changes in social supports/networks, a change in the role of sport, a realization of strength and a desire to assist others. Results indicate injured athletes are able to experience growth following adversity and speak to the dynamic process of identity adaptation. Additionally, the data emphasized the requirement for actively participating in adaptation and in the growth process to increase the opportunities for a desirable outcome for injured athletes. Future studies regarding growth and further understanding the transition process are suggested

    Why Simpler Computer Simulation Models Can Be Epistemically Better for Informing Decisions

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    For computer simulation models to usefully inform climate risk management, uncertainties in model projections must be explored and characterized. Because doing so requires running the model many ti..

    A theoretical view on concept mapping

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    Auto‐monitoring is the pivotal concept in understanding the operation of concept maps, which have been used to help learners make sense of their study and plan learning activities. Central to auto‐monitoring is the idea of a ‘learning arena’ where individuals can manipulate concept representations and engage in the processes of checking, resolving and confirming understandings. The learner is assisted by familiar metaphors (for example, networks) and the possibility of thinking ‘on action’ while ‘in action’. This paper discusses these concepts, and concludes by arguing that maps are part of the process of learning rather than a manifestation of learning itself. Auto‐monitoring is suggested as an appropriate term to describe the process of engaging in the learning arena

    Simple yet efficient real-time pose-based action recognition

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    Recognizing human actions is a core challenge for autonomous systems as they directly share the same space with humans. Systems must be able to recognize and assess human actions in real-time. In order to train corresponding data-driven algorithms, a significant amount of annotated training data is required. We demonstrated a pipeline to detect humans, estimate their pose, track them over time and recognize their actions in real-time with standard monocular camera sensors. For action recognition, we encode the human pose into a new data format called Encoded Human Pose Image (EHPI) that can then be classified using standard methods from the computer vision community. With this simple procedure we achieve competitive state-of-the-art performance in pose-based action detection and can ensure real-time performance. In addition, we show a use case in the context of autonomous driving to demonstrate how such a system can be trained to recognize human actions using simulation data.Comment: Submitted to IEEE Intelligent Transportation Systems Conference (ITSC) 2019. Code will be available soon at https://github.com/noboevbo/ehpi_action_recognitio
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