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Scaffolding Reflection: Prompting Social Constructive Metacognitive Activity in Non-Formal Learning
The study explores the effects of three different types of non-adaptive, metacognitive scaffolding on social, constructive metacognitive activity and reflection in groups of non-formal learners. Six triads of non-formal learners were assigned randomly to one of the three scaffolding conditions: structuring, problematising or epistemological. The triads were then asked to collaboratively resolve an ill-structured problem and record their deliberations. Evidence from think-aloud protocols was analysed using conversational and discourse analysis. Findings indicate that epistemological scaffolds produced more social, constructive metacognitive activity than either of the two other scaffolding conditions in all metacognitive activities except for task orientation, as well as higher quality interactions during evaluation and reflection phases. However, participants appeared to be less aware of their activities as forming a strategic, self-regulatory response to the problem. This may indicate that for learning transfer, it may be necessary to employ an adaptive, facilitated reflection on learners' activities
A smart radar absorber based on the phase-switched screen
Although conventional (i.e., passive) radar absorbers are widely used for modifying the radar cross-section (RCS) of current military platforms, such absorbers may not have adequate performance to satisfy future requirements. Active absorbers, however, offer the potential to overcome the so-called Rozanov performance limit and to enable additional smart functionality such as monitoring damage, adaptive control of RCS or target appearance, identification-friend-or-foe, and absorb-while-scan. This paper outlines the concept and basic properties of a novel type of active radar absorber, the so-called phase-switched screen (PSS). The basic PSS topology is then modified so as to enable it to operate as a smart radar absorber when used together with an external sensor and feedback control loop. System implementation issues and the optimum choice of design parameters for a range of operational scenarios are discussed, and theoretical predictions are supported by measured performance data
Bolt Detection Signal Analysis Method Based on ICEEMD
The construction quality of the bolt is directly related to the safety of the
project, and as such, it must be tested. In this paper, the improved complete
ensemble empirical mode decomposition (ICEEMD) method is introduced to the bolt
detection signal analysis. The ICEEMD is used in order to decompose the anchor
detection signal according to the approximate entropy of each intrinsic mode
function (IMF). The noise of the IMFs is eliminated by the wavelet soft
threshold de-noising technique. Based on the approximate entropy, and the
wavelet de-noising principle, the ICEEMD-De anchor signal analysis method is
proposed. From the analysis of the vibration analog signal, as well as the bolt
detection signal, the result shows that the ICEEMD-De method is capable of
correctly separating the different IMFs under noisy conditions, and also that
the IMF can effectively identify the reflection signal of the end of the bolt
Wearable Computing for Health and Fitness: Exploring the Relationship between Data and Human Behaviour
Health and fitness wearable technology has recently advanced, making it
easier for an individual to monitor their behaviours. Previously self generated
data interacts with the user to motivate positive behaviour change, but issues
arise when relating this to long term mention of wearable devices. Previous
studies within this area are discussed. We also consider a new approach where
data is used to support instead of motivate, through monitoring and logging to
encourage reflection. Based on issues highlighted, we then make recommendations
on the direction in which future work could be most beneficial
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