Investigating the Use of Augmented Reality and Machine Learning in Electrical Engineering Courses

The use of augmented reality (AR) in education and training is growing increasingly. However, applications to integrate augmented reality learning content into training for basic electrical engineering courses are scarce. The individual learning objectives of trainees complicate the digitalization of learning content, particularly for the drawing of circuit diagrams. To increase trainees\u27 learning outcome while simultaneously relieving instructors of classroom supervision, we designed and developed an AR-based prototype, to enhance hand-drawn circuit diagrams in vocational training. The context sensitivity is achieved by combining AR with image recognition. In an experiment with twelve participants, a positive impact of the prototype on trainees’ learning outcomes was observed, in comparison to a control group that received instructions without the prototype

Statistical analysis of the owl:sameAs network for aligning concepts in the linking open data cloud

The massively distributed publication of linked data has brought to the attention of scientific community the limitations of classic methods for achieving data integration and the opportunities of pushing the boundaries of the field by experimenting this collective enterprise that is the linking open data cloud. While reusing existing ontologies is the choice of preference, the exploitation of ontology alignments still is a required step for easing the burden of integrating heterogeneous data sets. Alignments, even between the most used vocabularies, is still poorly supported in systems nowadays whereas links between instances are the most widely used means for bridging the gap between different data sets. We provide in this paper an account of our statistical and qualitative analysis of the network of instance level equivalences in the Linking Open Data Cloud (i.e. the sameAs network) in order to automatically compute alignments at the conceptual level. Moreover, we explore the effect of ontological information when adopting classical Jaccard methods to the ontology alignment task. Automating such task will allow in fact to achieve a clearer conceptual description of the data at the cloud level, while improving the level of integration between datasets. <br/

Opinion diversity and the resilience of cooperation in dynamical networks

Across various scenarios, individuals cooperate with others to contribute towards a shared goal and ensure self-preservation. In game theory, the act of cooperation is considered as an individual producing some form of benefit to be utilised by others, under the expectation others will return the favour. In several scenarios, individuals make use of their own information to aid with their decision about who to connect and cooperate with. However, the choice of cooperation can be taken advantage of by opportunistic defectors, which can lead to significant disruption. This paper investigates how the diversity of opinion can contribute to the structure and mechanics of a dynamical network model and to the resilience of cooperation, by utilising a computational model where individuals make use of both public and private information to implement their decision. Our results show that increasing diversity leads to more stable, less connected and less prosperous networks coupled to more frequent, but shallower information cascades. Our work generally shows that the outcome of the conflict between cooperators and cheaters strongly depends on the interplay between population structure, individual decision making and individual opinions

Uncrewed Ocean Gliders and Saildrones Support Hurricane Forecasting and Research

In the United States alone, hurricanes have been responsible for thousands of deaths and over US$1 trillion in damages since 1980 (https://www.ncdc.noaa.gov/billions/). These impacts are significantly greater globally, particularly in regions with limited hurricane early warning systems and where large portions of the population live at or near sea level. The high socioeconomic impacts of tropical cyclones will increase with a changing climate, rising sea level, and increasing coastal populations. To mitigate these impacts, efforts are underway to improve hurricane track and intensity forecasts, which drive storm surge models and evacuation orders and guide coastal preparations. Hurricane track forecasts have improved steadily over past decades, whileintensity forecasts have lagged until recently (Cangialosi et al., 2020). Hurricane intensity changes are influenced by a combination of large-scale atmospheric circulation, internal storm dynamics, and air-sea interactions (Wadler et al.,2021, and references therein)

Assessment of multiple choice question exams quality using graphical methods

Exams should be valid, reliable, and discriminative. Multiple informative methods are used for exam analysis. Displaying analysis results numerically, however, may not be easily comprehended. Using graphical analysis tools could be better for the perception of analysis results. Two such methods were employed: standardized x-bar control charts with standard error of measurement as control limits and receiver operator characteristic curves. Exams of two medical classes were analyzed. For each exam, the mean, standard deviation, reliability, and standard error of measurement were calculated. The means were standardized and plotted against the reference lines of the control chart. The means were chosen as cut-off points to calculate sensitivity and specificity. The receiver operator characteristic curve was plotted and area under the curve determined. Standardized control charts allowed clear, simultaneous comparison of multiple exams. Calculating the control limits from the standard error of measurement created acceptable limits of variability in which the standard deviation and reliability were incorporated. The receiver operator characteristic curve graphically showed the discriminative power of the exam. Observations made with the graphical and classical methods were consistent. Using graphical methods to analyse exams could make their interpretation more accessible and the identification of exams that required further investigation easier

Why business angels reject investment opportunities: Is it personal?

A major focus of research on business angels has examined their decision-making processes and investment criteria. As business angels reject most of the opportunities that they receive, this article explores the reasons informing such decisions. In view of angel heterogeneity, investment opportunities might be expected to be rejected for differing reasons. Two sources of data are used to examine this issue. Face-to-face interviews with 30 business angels in Scotland and Northern Ireland provided information on typical ‘deal killers’. This was complemented by an Internet survey of United Kingdom that attracted responses from 238 UK business angels. The findings confirm that the main reason for rejection relates to the entrepreneur/management team. However, angel characteristics do not explain the number of reasons given for opportunity rejection nor do they predict the reasons for rejecting investment opportunities. This could be related to the increasing trend for business angels to join organised groups which, in turn, leads to the development of a shared repertoire of investment approaches. We suggest the concept of ‘communities-of-practice’ as an explanation for this finding

Your space or mine? : Mapping self in time

Peer reviewedPublisher PD