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Rolling elements bearings (REBs) is one of the most sensitive components and the common failure unit in mechanical equipment. Bearings failure prognostics, which aims to achieve an effective way to handle the increasing requirements for higher reliability and in the same time reduce unnecessary costs, has been an area of extensive research. The accurate prediction of bearings Remaining Useful Life (RUL) is indispensable for safe and lifetime-optimized operations. To monitor this vital component and planning repair work, a new intelligent method based on Wavelet Packet Decomposition (WPD) and deep learning networks is proposed in this paper. Firstly, features extraction from WPD used as input data. Secondly, these selected features are fed into deep Convolutional Neural Networks (CNNs) to construct the Health Indicator (HI). This study focuses on analysing the relationships such as correlations between the HI and temperature. We develop a solution for the Connectiomics contest dataset of bearings under different operating conditions and severity of defects. The performance of the proposed method is verified by four bearing data sets collected from experimental setup called “PRONOSTIA”. The results show that the health indicator obtains fairly high monotonicity and correlation values and it is beneficial to bearing life prediction. In addition, it is experimentally demonstrated that the proposed method is able to achieve better performance than a traditional neural network based method.

Throughout educational settings there are a range of open-focused learning activities along with those that are much more closed and structured. the plethora of opportunities creates a confusing melee of opportunities for teachers as they attempt to create activities that will engage and motivate learners. In this chapter, the authors demonstrate a learner-centric narrative virtual learning space, where the unrestricted exploration is combined with mechanisms to monitor the student and provide indirect guidance through elements in the learning space. The instructional designer defines the scope of the story in which the teacher and learner create narratives (a sequence of actions and milestones to complete a given task), which can be compared, assessed, and awarded with badges and scores. The model is described using an example from logistics, where incoming orders have to be fulfilled by finding the good and delivering it to a given location in a warehouse. Preliminary studies showed that the model is able to engage the learner and create an intrinsic motivation and therewith curiosity to drive the self-paced learning.

Immersive spaces are innately flexible. However, for learners, some constraints and scaffolding may often be valuable. This paper looks at immersive spaces as soft and hard technologies. Soft technologies are technologies enabling creative and flexible use, while hard technologies embed processes that limit creativity but provide efficiency and freedom from error. Technologies may be softened or hardened by assembly. For instance, if your Learning Management System (LMS) has no wiki, then it may be softened by adding one from outside the system. If your wiki has no assessment management system, then it may be hardened by using a LMS. For learning, the intrinsically soft nature of immersive spaces sometimes requires scaffolded hardening. This paper provides an example of an ongoing project that realizes these soft and hard technologies in an immersive virtual space and discusses the rich potential of such spaces for technology assembly.

This paper identifies the importance of assessment for student learning, especially "authentic assessment". While recognising that authenticity can be judged against the alignment of assessment with learning goals, and of assessment with real-life activities, the paper asserts a new element: the degree to which the Internet is part of the everyday lives of most university students. Thus, a third form of authenticity emerges when assessment is aligned with students' use of the Internet for simultaneous informal and formal learning, and the nature of the Internet as a place of active knowledge networking, involving co-creation of information and knowledgeable content (a consequence of the emergence of Web 2.0). The paper argues that developments in assessment using the Internet will only be authentic if they take account of the way the Internet functions outside of higher education, rather than seeing it as an educational technology divorced from its own authenticity.