Mobile texts and migrant audiences : rethinking literacy and assessment in a new media age

This article highlights the importance of rethinking literacy assessment in a digital and global world. Although pressures currently abound to narrow conceptions and practices of literacy, especially in an era of high stakes testing, digital multimodality and connectivity offer the potential for new ways of thinking, representing, and communicating, as well as new avenues for participating in relationships across social, geographic, and cultural difference. We explore the challenges of redesigning assessments so that they better take into account children's multiliterate capabilities. In so doing, we offer examples from our work in afterschool contexts that demonstrate how we have grappled with the complexities of assessment in new times.

Condition monitoring and fault prediction via an adaptive neural network

This paper describes the application of an adaptive neural network, called Fuzzy ARTMAP (FAM), to handle fault prediction and condition monitoring problems in a power generation station. The FAM network, which is supplemented with a pruning algorithm, is used as a classifier to predict different machine conditions, in an off-line learning mode. The process under scrutiny in the power plant is the Circulating Water (CW) system, with prime attention to monitoring the heat transfer efficiency of the condensers. Several phases of experiments were conducted to investigate the `optimum' setting of a set of parameters of the FAM classifier for monitoring heat transfer conditions in the power plant.