Authentication of Individuals using Hand Geometry Biometrics: A Neural Network Approach

Biometric based systems for individual authentication are increasingly becoming indispensable for protecting life and property. They provide ways for uniquely and reliably authenticating people, and are difficult to counterfeit. Biometric based authenticity systems are currently used in governmental, commercial and public sectors. However, these systems can be expensive to put in place and often impose physical constraint to the users. This paper introduces an inexpensive, powerful and easy to use hand geometry based biometric person authentication system using neural networks. The proposed approach followed to construct this system consists of an acquisition device, a pre-processing stage, and a neural network based classifier. One of the novelties of this work comprises on the introduction of hand geometry’s related, position independent, feature extraction and identification which can be useful in problems related to image processing and pattern recognition. Another novelty of this research comprises on the use of error correction codes to enhance the level of performance of the neural network model. A dataset made of scanned images of the right hand of fifty different people was created for this study. Identification rates and Detection Cost Function (DCF) values obtained with the system were evaluated. Several strategies for coding the outputs of the neural networks were studied. Experimental results show that, when using Error Correction Output Codes (ECOC), up to 100% identification rates and 0% DCF can be obtained. For comparison purposes, results are also given for the Support Vector Machine method.     

Efficient code development for improving execution performance in high-performance computing centers

The Journal of Supercomputing - Thanks to high-performance computing (HPC), it is possible to solve all kinds of highly complex projects from multiple scientific disciplines that require...     

Information Systems Strategy and its Relationship With Innovation Differentiation and Organizational Performance

ABSTRACT

This study, from the resource-based view, analyzes the different typologies of information systems (IS) strategy and their effects on firms’ innovation differentiation strategy and performance. Distinguishing between innovative and conservative IS strategy, results from the Spanish food industry show that an innovative IS strategy has a stronger direct effect on organizational performance, but that a conservative IS strategy can be a safer way to support the innovation differentiation strategy of firms.     

A model to evaluate the effects of price fairness perception in online hotel booking

Research on consumer and market behavior related to prices has increased remarkably in recent years. Researchers have paid special attention to the effects of price perception in consumer purchasing processes. In this paper a model of antecedents and consequences of consumer price fairness perception in an online hotel booking setting is proposed. The results show that consumers use reference prices and are guided by their familiarity with online hotel bookings in determining price fairness. Moreover, when consumers perceive prices as fair, they show more confidence in the decisions made and are more satisfied with the price. However, there is no direct influence on loyalty, although this relationship appears indirectly through satisfaction with the price and confidence in the decision.