A global optimum approach for one-layer neural networks

The article presents a method for learning the weights in one-layer feedforward neural networks minimizing either the sum of squared errors or the maximum absolute error, measured in the input scale. This leads to the existence of a global optimum that can be easily obtained solving linear systems of equations or linear programming problems, using much less computational power than the one associated with the standard methods. Another version of the method allows computing a large set of estimates for the weights, providing robust, mean or median, estimates for them, and the associated standard errors, which give a good measure for the quality of the fit. Later, the standard one-layer neural network algorithms are improved by learning the neural functions instead of assuming them known. A set of examples of applications is used to illustrate the methods. Finally, a comparison with other high-performance learning algorithms shows that the proposed methods are at least 10 times faster than the fastest standard algorithm used in the comparison.     

Visual detection and tracking with UAVs,following a mobile object

ABSTRACT

Conception and development of an Unmanned Aerial Vehicle (UAV) capable of detecting, tracking and following a moving object with unknown dynamics is presented in this work, considering a human face as a case of study. Object detection is accomplished by a Haar cascade classifier. Once an object is detected, it is tracked with the help of a Kalman Filter (KF), and an estimation of the relative position with respect to the target is obtained. A linear controller is used to validate the proposed vision scheme and for regulating the aerial robot's position in order to keep a constant distance with respect to the mobile target, employing as well the extra available information from the embedded sensors. The proposed system was extensively tested in real-time experiments, through different conditions, using a commercial quadcopter connected via wireless to a ground station running under the Robot Operative System (ROS). The proposed overall strategy shows a good performance even under disadvantageous conditions as outdoor flight, being robust against illumination changes, image noise and the presence of other people in the scene.     

Service oriented evolutionary algorithms

This work presents a service oriented architecture for evolutionary algorithms, and an implementation of this architecture using a specific technology (called OSGiLiath). Service oriented architecture is a computational paradigm where users interact using services to increase the integration between systems. The presented abstract architecture is formed by loosely coupled, highly configurable and language-independent services. As an example of an implementation of this architecture, a complete process development using a specific service oriented technology is explained. With this implementation, less effort than classical development in integration, distribution mechanisms and execution time management has been attained. In addition, steps, ideas, advantages and disadvantages, and guidelines to create service oriented evolutionary algorithms are presented. Using existing software, or from scratch, researchers can create services to increase the interoperability in this area.     

A percentile system optimization approach with and without path enumeration

In this paper we deal with the travel time reliability PUE (probabilistic user equilibrium) problem studied by Lo et al. (2006) [12] and Nie (2011) [15] and we propose an alternative model that assumes a location-scale family for the path travel times, whose means and variances are evaluated in terms of link travel times. This avoids the use of the central limit theorem and convolutions providing a flexible and simple alternative. Contrary to the most existing models that require path enumeration or an iterative method to add paths sequentially, we present a percentile system optimization in its two versions: with and without path enumeration. Two examples of applications, one of them real, are used to illustrate the power of the proposed method. The cpu times required to solve the problem seem reasonable. In addition, we answer an open question raised by Nie (2011) [15] about the permutability of percentiles and partial derivatives of route travel times with respect to route flows. A family of counterexamples is given to demonstrate that the two operations: (a) obtain percentiles and (b) partial derivation of route travel times do not commute. Finally, to reproduce the trial-and-error sequence followed by users when selecting paths, we also present an algorithm that simulates this iterative process and shows that the final long-term user behavior coincides with PUE (probabilistic user equilibrium) problem resulting from some existing models.     

A case study on business process recovery using an e‐government system

Business processes have become one of the key assets of organization, since these processes allow them to discover and control what occurs in their environments, with information systems automating most of an organization's processes. Unfortunately, and as a result of uncontrolled maintenance, information systems age over time until it is necessary to replace them with new and modernized systems. However, while systems are aging, meaningful business knowledge that is not present in any of the organization's other assets gradually becomes embedded in them. The preservation of this knowledge through the recovery of the underlying business processes is, therefore, a critical problem. This paper provides, as a solution to the aforementioned problem, a model‐driven procedure for recovering business processes from legacy information systems. The procedure proposes a set of models at different abstraction levels, along with the model transformations between them. The paper also provides a supporting tool, which facilitates its adoption. Moreover, a real‐life case study concerning an e‐government system applies the proposed recovery procedure to validate its effectiveness and efficiency. The case study was carried out by following a formal protocol to improve its rigor and replicability. Copyright © 2011 John Wiley & Sons, Ltd.     

Characterisation of an enamelled metallic object found in Guerrero Negro (Baja California) by PIXE and RBS techniques

The coast of Guerrero Negro (Baja California) has been known for a long time by archaeologists for its shipwrecks. Archaeologists are recovering objects that come from sunken Spanish galleons in the colonial period, and reach the American coast in the frontier of the USA with Mexico.An enamelled metallic object was found next to the beach in Guerrero Negro. We have analysed the piece with proton induced X-ray emission (PIXE) and Rutherford backscattering (RBS) in an attempt to establish whether the object could come from one of the colonial shipwrecks and to valuate its cleaning process.Scanning electron microscopy (SEM) and energy dispersive X-ray spectrometry (EDS) have been also performed in three samples taken from the object in order to observe the heterogeneity of the material.The materials found revealed the presence of typical lead-glass enamels from with pigments such as cuprite (red), or lead-tin yellow used in colonial times. The metallic part consisted of brass. As for the cleaning process, the average efficiency considered as the weight% of chlorine removed, was of 83.4% for brass and 100% for enamels.     

Human brain metabolic response to caffeine and the effects of tolerance

OBJECTIVE: Since there is limited information concerning caffeine's metabolic effects on the human brain, the authors applied a rapid proton echo-planar spectroscopic imaging technique to dynamically measure regional brain metabolic responses to caffeine ingestion. They specifically measured changes in brain lactate due to the combined effects of caffeine's stimulation of glycolysis and reduction of cerebral blood flow. METHOD: Nine heavy caffeine users and nine caffeine-intolerant individuals, who had previously discontinued or substantially curtailed use of caffeinated products because of associated anxiety and discomforting physiological arousal, were studied at baseline and then during 1 hour following ingestion of caffeine citrate (10 mg/kg). To assess state-trait contributions and the effects of caffeine tolerance, five of the caffeine users were restudied after a 1- to 2-month caffeine holiday. RESULTS: The caffeine-intolerant individuals, but not the regular caffeine users, experienced substantial psychological and physiological distress in response to caffeine ingestion. Significant increases in global and regionally specific brain lactate were observed only among the caffeine-intolerant subjects. Reexposure of the regular caffeine users to caffeine after a caffeine holiday resulted in little or no adverse clinical reaction but significant rises in brain lactate which were of a magnitude similar to that observed for the caffeine-intolerant group. CONCLUSIONS: These results provide direct evidence for the loss of caffeine tolerance in the human brain subsequent to caffeine discontinuation and suggest mechanisms for the phenomenon of caffeine intolerance other than its metabolic effects on elevating brain lactate.     

Four‐parameter beta distribution estimation and skewness test

Sequential tolerance control (STC) is a tolerance control methodology used in discrete parts manufacturing. Recently, an adaptive sphere‐fitting method for STC (ASF–STC) was developed to account for potential skewness in manufacturing operations' distributions, a factor not considered in conventional STC. ASF–STC offers significant improvements over conventional STC when such skewness exists. The direction of skewness of an operations' distribution is a necessary input to ASF–STC. Thus, a novel approach to determining the skewness of a distribution for small sample sizes is presented here. ASF–STC has an additional requirement of distribution information for each operation. The beta distribution is an ideal candidate here, as it is very flexible in shape. The literature on four‐parameter beta estimation is very limited, and their performance for small sample sizes is poor. STC was designed for low‐volume production, thus the estimation for small sample sizes is necessary here. This study presents a heuristic, based on the method of moments estimates for a beta distribution, that estimates the four parameters for a beta distribution with small sample size. Several computational results are provided to compare this heuristic to the best‐known procedure, with the heuristic found to perform better for the test problems considered. Copyright © 2002 John Wiley & Sons, Ltd.