Using artificial neural networks for transport decisions: Managerial guidelines

One information technology that may be considered by transportation managers, and which is included in the portfolio of technologies that encompass TMS. is artificial neural networks (ANNs). These artificially intelligent computer decision support software provide solutions by finding and recognizing complex patterns in data. ANNs have been used successfully by transportation managers to forecast transportation demand, estimate future transport costs, schedule vehicles and shipments, route vehicles and classify earners for selection. Artificial neural networks excel in transportation decision environments that are dynamic, complex and unstructured. This article introduces ANNs to transport managers by describing ANN technological capabilities, reporting the current status of transportation neural network applications, presenting ANN applications that offer significant potential for future development and offering managerial guidelines for ANN development

Trichotillomania and related disorders in children and adolescents

Eleven chronic hair pullers, 11 subjects with obsessive-compulsive disorder (OCD), and 11 subjects with a non-OCD anxiety disorder were assessed with structured interviews and the Child Behavior Checklist (CBCL). Only 4 hair pullers (36%) reported both rising tension and relief with hair pulling. Each group had significantly more internalizing than externalizing symptoms on the CBCL. Seven hair pullers (64%) had a lifetime history of at least one other axis I diagnosis. The results provide further evidence that trichotillomania in referred children and adolescents is usually a chronic disorder often associated with internalizing symptoms and psychiatric comorbidity. Rising tension followed by relief with hair pulling may be an unnecessary restriction in the diagnosis of childhood trichotillomania.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/43954/1/10578_2006_Article_BF02353354.pd