Identification of computer-generated facial composites.

Two studies examined the effectiveness of the Mac-a-Mug Pro, a computerized facial composite production system. In the first study, college freshmen prepared from memory composites of other students and faculty from their former high schools. Other students who had attended the same high schools could not recognize the composites of either students or faculty members when the composites of individuals known to them (n?=?10) were mixed with composites of a large number (n?=?40) of strangers. Neither preparer familiarity with the target, preparer-assessed composite quality, nor viewer familiarity predicted composite recognition. Study 2 indicated that naive witnesses who viewed the composites could not select the people depicted in the composites from photo lineups (1 target and 4 foils) . The results raise questions about the efficacy of composite systems as tools to promote recognition of suspects in criminal contexts. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Spatial interaction modelling

Abstract. Spatial interaction (SI) is the process whereby entities at different points in physical space make contacts, demand/supply decisions or locational choices. The entities can be individuals or firms and the choices can include housing, jobs, production quantities, exports, imports, face-to-face contacts, schools, retail centres and activity centres. The first SI models can be grouped under the generic heading gravity models. Their main characteristic is that they model the behaviour of demand or supply segments, rather than that of individuals and firms. This article traces the development of these models from their inception in the early part of the twentieth century to the present. The key advances include the replacement of the gravity analogy by the more general concepts of entropy or information theory, a statistical framework commonly used in physics. With the arrival of the regional science paradigm over 50 years ago, a key challenge has been to broaden these models compared to those arising in spatial economics, thus arriving at a more inclusive probabilistic framework. These efforts are discussed here, as well as inclusion of geographical advances, embracing activities as generators of travel, time-geography, recognition of spatial interdependencies, and use of neuro-computing principles.