Book Review of “Indigenous Social Work around the World. Towards Culturally Relevant Education and Practice”, 2008, edited by Mel Gray, John Coates and Michael Yellow Bird

One could be seduced into a critique of this volume that focuses on its potential to overstate the momentum for a shift in Western social work ideology when faced with the conundrum of cultural difference. One could posit that the discussion is too broad, the topics covered too numerous, the opportunity for detail missed, the urgency of the messages unnecessarily exaggerated, the “proof” not beyond anecdote and so forth. I reject this temptation to conform to the dominant professional dynamic most emphatically and offer that what Gray, Coates and Yellow Bird have presented to the social work field in this volume is the first tangible step towards an alternative paradigm for an occupation afflicted with unsustainable hypocrisy and thus at the brink of irrelevancy.

Meta-model for calculating the mean energy demand of automated storage and retrieval systems

Energy efficiency has become an important research topic in intralogistics. Especially in this field the focus is placed on automated storage and retrieval systems (AS/RS) utilizing stacker cranes as these systems are widespread and consume a significant portion of the total energy demand of intralogistical systems. Numerical simulation models were developed to calculate the energy demand rather precisely for discrete single and dual command cycles. Unfortunately these simulation models are not suitable to perform fast calculations to determine a mean energy demand value of a complete storage aisle. For this purpose analytical approaches would be more convenient but until now analytical approaches only deliver results for certain configurations. In particular, for commonly used stacker cranes equipped with an intermediate circuit connection within their drive configuration there is no analytical approach available to calculate the mean energy demand. This article should address this research gap and present a calculation approach which enables planners to quickly calculate the energy demand of these systems.