An Entropy Model of Artifical Grammar Learning

We propose a model to characterize the type of knowledge acquired in Artificial Grammar Learning (AGL). In particular, we suggest a way to compute the complexity of different test items in an AGL task, relative to the training items, based on the notion of Shannon entropy: The more predictable a test item is from training items, the higher the likelihood that it will be selected as compatible to the training items. Our model is an attempt to formalize some aspects of inductive inference by providing a quantitative measure of the knowledge abstracted by experience. We motivate our particular approach from research in reasoning and categorization, where reduction of entropy has also been seen as a plausible cognitive objective. This may suggest that reducing (Shannon) uncertainty may provide a single explanatory framework for modeling as diverse aspects of cognition, as learning, reasoning, and categorization

Economic Contribution of Colleges and Universities in Maine

Maine has 38 colleges and universities that educate 72,605 students, employ a combined 14,621 nonstudent workers, and generate about $2.2 billion in annual revenue. Colleges and universities in Maine generate a total annual economic contribution—including the spending of students and visitors, and multiplier effects—of an estimated$4.5 billion in output, 31,267 full- and part-time jobs, and $1.7 billion in labor income. Maine’s colleges and universities support at least ten jobs in 125 Maine sectors, and there are statewide employment impacts of twenty jobs or more in 108 industries. This report examines the statewide economic contribution of colleges and universities in Maine. Economic contribution is defined as the direct revenue generated by these institutions and the spending of their students and visitors; employment and employee compensation in Maine’s colleges and universities and the jobs and earnings supported by the spending of students and visitors; and the multiplier effects associated with the spending of workers (i.e., induced effects) and companies (i.e., indirect effects) connected to Maine’s institutions of higher learning (and the workers and businesses supported by the spending of students and visitors). The economic impact analysis includes 38 institutions of postsecondary education (e.g., private colleges, public universities, community colleges) and uses data from the U.S. Department of Education (Integrated Postsecondary Education Data System, National Center for Education Statistics), surveys of student expenditures, past economic impact studies, and information collected from the websites of Maine’s colleges and universities. The multiplier effects and some of the direct impacts (e.g., labor income) are estimated by a Maine input-output model (IMPLAN)

Economic Contributions of Colleges and Universities in Maine

This report shows the following: Maine has 38 colleges and universities that educate 72,605 students, employ a combined 14,621 non-student workers, and generate about $2.2 billion in annual revenue. Colleges and universities in Maine generate a total annual economic contribution— including the spending of students and visitors, and multiplier effects—of an estimated$4.5 billion in output, 31,267 full- and part-time jobs (not including student workers), and $1.7 billion in labor income. Maine’s colleges and universities support at least ten jobs in 125 Maine sectors, and there are statewide employment impacts of twenty jobs or more in 108 industrie

Rules work on one representation; similarity compares two representations

Abstract: Rules and similarity refer to qualitatively different processes. The classification of a stimulus by rules involves abstract and usually domain-specific knowledge operating primarily on the target representation. In contrast, similarity is a relation between the target representation and another representation of the same type. It is also useful to distinguish associationist processes as a third type of cognitive process

Convergence of RProp and variants

This paper examines conditions under which the Resilient Propagation-Rprop algorithm fails to converge, identifies limitations of the so-called Globally Convergent Rprop-GRprop algorithm which was previously thought to guarantee convergence, and considers pathological behaviour of the implementation of GRprop in the neuralnet software package. A new robust convergent backpropagation-ARCprop algorithm is presented. The new algorithm builds on Rprop, but guarantees convergence by shortening steps as necessary to achieve a sufficient reduction in global error. Simulation results on four benchmark problems from the PROBEN1 collection show that the new algorithm achieves similar levels of performance to Rprop in terms of training speed, training accuracy, and generalization

Testing Educational Strategies for Shaken Baby Syndrome

Shaken Baby Syndrome (SBS) occurs from the violent shaking of an infant, which may lead to brain damage or death. The goal of this study was to assess educational methods used to teach new mothers about SBS

Method of varying template dimensions to achieve alignment during imprint lithography

A method of determining and correcting alignment during imprint lithography process is described. During an imprint lithographic process the template may be aligned with the substrate by the use of alignment marks disposed on both the template and substrate. The alignment may be determined and corrected for before the layer is processed.Board of Regents, University of Texas Syste