500 research outputs found
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Enabling Interoperability in the Internet of Things: A OSGi Semantic Information Broker Implementation
No full textSemantic Web technologies act as an interoperability glue among different formats, protocols and platforms, providing a uniform vision of heterogeneous devices and services in the Internet of Things (IoT). Semantic Web technologies can be applied to a broad range of application contexts (i.e., industrial automation, automotive, health care, defense, finance, smart cities) involving heterogeneous actors (i.e., end users, communities, public authorities, enterprises). Smart-M3 is a semantic publish-subscribe software architecture conceived to merge the Semantic Web and the IoT domains. It is based on a core component (SIB, Semantic Information Broker) where data is stored as RDF graphs, and software agents using SPARQL to update, retrieve and subscribe to changes in the data store. This article describes a OSGi SIB implementation extended with a new persistent SPARQL update primitive. The OSGi SIB performance has been evaluated and compared with the reference C implementation. Eventually, a first porting on Android is presented
Kinova Modular Robot Arms for Service Robotics Applications
No full textThis article presents Kinova's modular robotic systems, including the robots JACO2 and MICO2, actuators and grippers. Kinova designs and manufactures robotics platforms and components that are simple, sexy and safe under two business units: Assistive Robotics empowers people living with disabilities to push beyond their current boundaries and limitations while Service Robotics empowers people in industry to interact with their environment more efficiently and safely. Kinova is based in Boisbriand, Québec, Canada. Its technologies are exploited in over 25 countries and are used in many applications, including as service robotics, physical assistance, medical applications, mobile manipulation, rehabilitation, teleoperation and in research in different areas such as computer vision, artificial intelligence, grasping, planning and control interfaces. The article describes Kinova's hardware platforms, their different control modes (position, velocity and torque), control features and possible control interfaces. Integration to other systems and application examples are also presented
Approaches to Work in Reducing Entrenched Patterns of Violent Behavior: The CAI Model – A Peace Intervention
No full textIn this chapter, the author will demonstrate the use of a peace intervention to increase children's self-identity, community attachments, and coping mechanisms. With correct training and awareness, this project could be implemented throughout elementary schools and community organizations. This chapter will highlight the connection between social and emotional learning as a peace intervention to further reduce the impact of trauma at a later stage in a child's life. Leaning on Axline's play therapy principles and Bronfenbrenner's bio-ecological theory, the author will illustrate how this will become a feasible and sustainable peace intervention. For this, the author has developed the CAI model
Investigating Epistemic Stances in Game Play with Data Mining
No full textIn this paper, techniques of statistical computing were applied to data logs to investigate the patterns in students' play of The Fuzzy Chronicles, and how these patterns relate to learning outcomes with regards to Newtonian kinematics. This paper has two goals. The first goal is to investigate the basic claims of the proposed Two-System Framework for Game-Based Learning (or 2SM) (Martinez-Garza & Clark, 2016) that may serve as part of a general-use explanatory framework for educational gaming. The second goal is to explore and demonstrate the use of automatically collected log files of student play as evidence through educational data mining techniques. These techniques could also find general use, and this paper offers a demonstration of plausible methods and processes that are suited for game play data. These goals were pursued via two research questions. The first research question examines whether students playing The Fuzzy Chronicles showed evidence of dichotomous fast/slow modes of solution. The 2SM theorizes that slow modes of solution will correlate to higher learning gains. Congruent with the 2SM, students who use mainly fast iterative solution strategies achieved lower learning gains than students who preferred slow, elaborate solutions, or a more balanced mix of the two. A second research question investigates the connection between conceptual understanding and student performance in conceptually-laden challenges. The finding was that students generally improve their performance in these challenges as gameplay progresses, but that this improvement is strongly moderated by their prior knowledge of physics. Implications of these findings in terms of educational game design, analysis of gameplay logs, and further refinement of the 2SM are discussed
Teachers' Professional Learning Focused on Designs for Early Learners and Technology
No full textIn this chapter, the authors present and discuss findings from a two-year case study on teachers' professional learning. This investigation built upon existing research on early learning and technology to study teachers' professional learning in a community of practice, and the development of classroom-based learning designs and the ongoing inquiry of teachers from four school jurisdictions in the province of Alberta in Canada. Focus was on investigating ongoing continuous improvement of teacher design and assessment practices, to identify and share promising practices from the classroom, to capture teacher learning and engagement, to document the appropriate use of technology for learning and to identify and to understand system affordances and constraints for using technology with young learners
Chinese English Teachers' Perspectives on “Distributed Flip MOOC Blends”: From BMELTT to BMELTE
No full textThis article reports on a study involving experienced university lecturers from mainland China reflecting on how to blend FutureLearn MOOCs into their existing English Language Teaching (ELT) curricula while on an ‘upskilling' teacher education summer course in the UK in academic year 2016-2017. Linked to a British Council ELTRA (English Language Teaching Research Award) project, the study involved: a. the administration of a pre-MOOC survey relating to teachers' beliefs towards online learning in general and MOOCs in particular; b. ‘learning by doing': taking part in a FutureLearn MOOC; c. reflecting on the experience both face-to-face in workshops, in online forums and in a post-MOOC survey. The outcomes of this article highlight that the understanding of what a MOOC is might differ between the UK and China. The article concludes by presenting the perceived pros and cons of adopting a ‘distributed flip MOOC blend' as previously discussed in related work
Musings on Co-designing Identity Aware Realities in Virtual Learning
No full textVirtual learning in the third dimension presents many opportunities for meaningful learning to occur. Learning in which the learner's self and the collective self immerse in the co-creation of authentic experiences. The virtues of these 3D environments are best appreciated holistically through the visual and the spatial perspectives. For meaningful learning many variables interact; however, of great importance is the role selfhood plays. Today's computing power affords original and imaginative rich experiences in which the learner is at the center of the event. The following chapter presents an exploratory journey on the self and holistic design considerations for learning in virtual environments
Forecasting of Electricity Demand by Hybrid ANN-PSO Models
No full textDeveloping economies need to invest in energy projects. Because the gestation period of the electric projects is high, it is of paramount importance to accurately forecast the energy requirements. In the present paper, the future energy demand of the state of Tamil Nadu in India, is forecasted using an artificial neural network (ANN) optimized by particle swarm optimization (PSO) and by General Algorithm (GA). Hybrid ANN Models have the potential to provide forecasts that perform well compared to the more traditional modelling approaches. The forecasted results obtained using the hybrid ANN-PSO models are compared with those of the ARIMA, hybrid ANN-GA, ANN-BP and linear models. Both PSO and GA have been developed in linear and quadratic forms and the hybrid ANN models have been applied to five-time series. Amongst all the hybrid ANN models, ANN-PSO models are the best fit models in all the time series based on RMSE and MAPE
Out of Isolation: Building Online Higher Education Engagement
No full textHaving a supportive community in graduate school is a key element that increases the probability of a student's success in their program. Online learning can often feel very isolating both for students and faculty. In a 1:1 teaching model that offers more personalized feedback to students, students can spend significant time in their studies without communication with other faculty, students or school administrators. Such isolation can inhibit the development of a supportive community. In this chapter, we will explore how a graduate school initiated a transition in their culture from one of isolation to one of community by increasing faculty and students' ability to engage and communicate to each other beyond their courses. We will review the strategies they implemented, the challenges they faced, the successes they saw, how they reviewed their progress and how they plan to use their initial work as a foundation for growing a more engaged graduate culture out of isolation and into community
Building a Certification and Inspection Data Infrastructure to Promote Transparent Markets
No full textThis article reports on data architecture that reduces information asymmetries to support public-private collaboration to govern product certification and inspection for promoting transparent markets and building consumer trust. The data architecture is a proof-of-concept set of data standards called the Certification and Inspection Data Infrastructure Building Block (CIDIBB) for data storage, retrieval, sharing and automated reasoning of data that can be used to respond the question: what constitutes a trustworthy certification and inspection process? CIDIBB consists of three interrelated ontologies, focusing specifically on certified fair-trade coffee that has the potential to become universally applicable to any certification and inspection process for products or services. The evaluation results suggest that CIDIBB is able to test the trustworthiness of certification schemes, providing consistent results. CIDIBB will contribute to support public-private collaboration to solve public problems such as the promotion of sustainable production and fair labor practices