University of Houston

About: University of Houston is a education organization based out in Houston, Texas, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 23074 authors who have published 53903 publications receiving 1641968 citations.

A Review of Feature Reduction Techniques in Neuroimaging

Abstract: Machine learning techniques are increasingly being used in making relevant predictions and inferences on individual subjects neuroimaging scan data. Previous studies have mostly focused on categorical discrimination of patients and matched healthy controls and more recently, on prediction of individual continuous variables such as clinical scores or age. However, these studies are greatly hampered by the large number of predictor variables (voxels) and low observations (subjects) also known as the curse-of-dimensionality or small-n-large-p problem. As a result, feature reduction techniques such as feature subset selection and dimensionality reduction are used to remove redundant predictor variables and experimental noise, a process which mitigates the curse-of-dimensionality and small-n-large-p effects. Feature reduction is an essential step before training a machine learning model to avoid overfitting and therefore improving model prediction accuracy and generalization ability. In this review, we discuss feature reduction techniques used with machine learning in neuroimaging studies.

Perceived Information Security, Financial Liability and Consumer Trust in Electronic Commerce Transactions

Abstract: Electronic commerce (EC) transactions are subject to multiple information security threats. Proposes that consumer trust in EC transactions is influenced by perceived information security and distinguishes it from the objective assessment of security threats. Proposes mechanisms of encryption, protection, authentication, and verification as antecedents of perceived information security. These mechanisms are derived from technological solutions to security threats that are visible to consumers and hence contribute to actual consumer perceptions. Tests propositions in a study of 179 consumers and shows a significant relationship between consumers’ perceived information security and trust in EC transactions. Explores the role of limited financial liability as a surrogate for perceived security. However, the findings show that there is a minimal effect of financial liability on consumers’ trust in EC. Engenders several new insights regarding the role of perceived security in EC transactions.

Does Asymmetric Information Drive Capital Structure Decisions

Abstract: Using a novel information asymmetry index based on measures of adverse selection developed by the market microstructure literature, we test if information asymmetry is an important determinant of capital structure decisions, as suggested by the pecking order theory. Our index relies exclusively on measures of the market's assessment of adverse selection risk rather than on ex ante firm characteristics. We find that information asymmetry does affect the capital structure decisions of U.S. firms over the sample period 1973-2002. Our findings are robust to controlling for conventional leverage factors (size, Q ratio, tangibility, profitability) and several firm attributes, such as funding needs, sales growth, real investment, stock return volatility, stock turnover, and intensity of insider trading. For example, we estimate that on average, for every dollar of financing deficit to cover, firms in the highest adverse selection decile issue 30 cents of debt more than firms in the lowest decile. Overall, this evidence explains why the pecking order theory is only partially successful in explaining all of firms' capital structure decisions. It also suggests that the theory finds support when its basic assumptions hold in the data, as it should reasonably be expected of any theory.

The internal dynamics of globular proteins.

Abstract: (1981). The Internal Dynamics of Globular Protein. Critical Reviews in Biochemistry: Vol. 9, No. 4, pp. 293-349.