Robert E. Dorsey

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Artificial Neural Networks have been shown to have the potential to perform well for classification problems in many different environments, including business, science and engineering. Studies in the literature often report that the artificial neural network dominates traditional statistical techniques for most problems examined. Since a neural network can(More)
The escalation of Neural Network research in Business has been brought about by the ability of neural networks, as a tool, to closely approximate unknown functions to any degree of desired accuracy. Although, gradient based search techniques such as back-propagation are currently the most widely used optimization techniques for training neural networks, it(More)
The ability of neural networks to closely approximate unknown functions to any degree of desired accuracy has generated considerable demand for Neural Network research in Business. The attractiveness of neural network research stems from researchers’ need to approximate models within the business environment without having a priori knowledge about the true(More)
The recent surge in activity of Neural Network research in Business is not surprising since the underlying functions controlling business data are generally unknown and the neural network offers a tool that can approximate the unknown function to any degree of desired accuracy. The vast majority of these studies rely on a gradient algorithm, typically a(More)
In this paper, we study the behavior of individuals when facing two different, but incentive-wise identical, institutions. We pair the first price auction with an equivalent lottery. Once a subject is assigned a value for the auctioned object, the first price auction can be modeled as a lottery in which the individual faces a given probability of winning a(More)
A major limitation to current artificial neural network research is the inability to adequately identify unnecessary weights in the solution. If a method were found that would allow unnecessary weights to be identified, decision makers would gain crucial information about the problem at hand as well as benefit by having a network that was more effective and(More)
When attempting to determine the optimal complexity of a neural network the correct decision is dependent upon obtaining the global solution at each stage of the decision process. Failure to ensure that each optimization being considered is near a global solution may lead to misleading and often conflicting results jeopardizing any decision rule for(More)
Cellular mechanisms implicated in Parkinson disease (PD) include oxidative stress, inflammatory response, excess dopamine, DNA damage, and loss of trophic support. These stimuli have been observed to induce changes in cell cycle proteins in several cell types. One of the key regulators of cell cycle progression is the retinoblastoma protein (pRb);(More)
We examined the effects of age and of increasing concentrations of testosterone on the wet weight, protein content, cell number, and cell size of the ventral, dorsal, and lateral lobes of the Brown Norway rat prostate. Young (3 mo of age) and aged (15, 17, and 21 mo of age) rats received implants of increasing sizes of testosterone-filled Silastic capsules(More)