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Panama, Panama

The Technological University of Panama, Universidad Tecnológica de Panamá in Spanish, is the second largest university in Panama. It is a university comprising six faculties in seven campuses nationwide. The main campus is a 60-hectare piece of land located in Panama City, the country’s capital city. Wikipedia.

Vargas S.,Charles III University of Madrid | Vargas S.,Technological University of Panama | Vazquez C.,Charles III University of Madrid
Optics Express | Year: 2014

A polarization independent reconfigurable optical demultiplexer with low crosstalk between adjacent channels and high number of potential allocated channels is designed on silicon on insulator technology. On to off state transitions can be implemented by changing the coupling factor or the ring length. Wavelength selective switch units are cascaded to form the demultiplexer. Crosstalks below -30dB with 50GHz channel spacing and losses below 1.5dB in the off state are obtained from simulations. Designs using carrier dispersion effect and power consumption estimations are included. © 2014 Optical Society of America.

Pinzon C.I.,Technological University of Panama | Bajo J.,University of Salamanca | De Paz J.F.,University of Salamanca | Corchado J.M.,University of Salamanca
Expert Systems with Applications | Year: 2011

During the last years the use of Web Service-based applications has notably increased. However, the security has not evolved proportionally, which makes these applications vulnerable and objective of attacks. One of the most common attacks requiring novel solutions is the denial of service attack (DoS), caused for the modifications introduced in the XML of the SOAP messages. The specifications of existing security standards do not focus on this type of attack. This article presents the S-MAS architecture as a novel adaptive approach for dealing with DoS attacks in Web Service environments, which represents an alternative to the existing centralized solutions. S-MAS proposes a distributed hierarchical multi-agent architecture that implements a classification mechanism in two phases. The main benefits of the approach are the distributed capabilities of the multi-agent systems and the self-adaption ability to the changes that occur in the patterns of attack. A prototype of the architecture was developed and the results obtained are presented in this study. © 2010 Elsevier Ltd. All rights reserved.

Montero-Prado P.,Aragon Institute of Engineering Research | Montero-Prado P.,Technological University of Panama | Bentayeb K.,Aragon Institute of Engineering Research | Nerin C.,Aragon Institute of Engineering Research
Food Chemistry | Year: 2013

The volatile compounds of four peach cultivars (Prunus persica L.) were studied: Sudanell, San Lorenzo, Miraflores and Calanda (two clones, Calante and Jesca). 17-23 Samples of each cultivar with the same maturity level were analyzed, measuring color, firmness, and soluble solids content. The pulp was crushed and mixed with water prior to HS-SPME analysis, and GC-MS was used to determine the volatile compounds. Sixty-five compounds were identified using spectral library matching, Kovat's indices and, when available, pure standards. The main components were lactones and C6 compounds. From the distribution of these compounds, Principal Component Analysis led to the clustering of the samples according to their different cultivars. Finally, Canonical Component Analysis was used to create a classification function that identifies the origin of an unknown sample from its volatile composition. The results obtained will help to avoid fraud and protect the European Designation of Origin 'Melocotón de Calanda'. © 2012 Elsevier Ltd. All rights reserved.

De Leon A.T.,Technological University of Panama
Global Journal of Engineering Education | Year: 2014

This study provides an overview of the development of hard and soft skills from project-based curriculum planning, and suggests ways to evaluate them in the context of engineering education and their importance in the training of future engineers. The research described here is descriptive and analytical, involving a detailed study to determine the skills generated by the end of the semester. Data collection was performed by applying a questionnaire of closed assertions with five levels of response, consisting of 24 items based on the proficiencies established in the CDIO Syllabus to geology course students. From the results obtained, it seems that students have high expectations in relation to the competencies generated, and it became evident that students have a good level of intellectual capital, but they have poor non-technical skills. The main student perceptions regarding the impact of the course were associated with the ability to obtain a positive outcome the end of the course, and the need to gain the theoretical background knowledge of a basic science course as the common core in engineering. © WIETE 2014

Pinzon C.I.,Technological University of Panama | De Paz J.F.,University of Salamanca | Herrero A.,University of Burgos | Corchado E.,University of Salamanca | And 2 more authors.
Information Sciences | Year: 2013

This study presents a multiagent architecture aimed at detecting SQL injection attacks, which are one of the most prevalent threats for modern databases. The proposed architecture is based on a hierarchical and distributed strategy where the functionalities are structured on layers. SQL-injection attacks, one of the most dangerous attacks to online databases, are the focus of this research. The agents in each one of the layers are specialized in specific tasks, such as data gathering, data classification, and visualization. This study presents two key agents under a hybrid architecture: a classifier agent that incorporates a Case-Based Reasoning engine employing advanced algorithms in the reasoning cycle stages, and a visualizer agent that integrates several techniques to facilitate the visual analysis of suspicious queries. The former incorporates a new classification model based on a mixture of a neural network and a Support Vector Machine in order to classify SQL queries in a reliable way. The latter combines clustering and neural projection techniques to support the visual analysis and identification of target attacks. The proposed approach was tested in a real-traffic case study and its experimental results, which validate the performance of the proposed approach, are presented in this paper.

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