Doninos de Salamanca, Spain

Pontifical University of Salamanca
Doninos de Salamanca, Spain

The Pontifical University of Salamanca is a private, catholic university, located in Salamanca, Spain, and campus in Salamanca and Madrid. Wikipedia.

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Alvarez C.D.,Pontifical University of Salamanca | Sanchez-Prada A.,Pontifical University of Salamanca
Advances in Intelligent Systems and Computing | Year: 2018

This paper presents the research possibilities of the integration of qualitative and quantitative methodologies to explore gender stereotypes underlying the professional practice of psychology. The self-report technique, used as a research tool for stereotypes, has shown deficiencies in the control of the effect of social desirability on responses. This research accessed through qualitative methodology the discursive forms used by the study population to express covert gender stereotypes in socially acceptable formulations. From the Discussion Group with Psychology students, textual statements concealing these stereotypes were taken to transform them into items of a quantitative scale to assess large samples. The results were analyzed qualitatively by and with participants in the study. The methodological integration was an adequate strategy to access socially shared meanings, both in the design of instruments and in the explanation of the phenomena investigated. © Springer International Publishing AG 2018.

Rios-Aguilar S.,Pontifical University of Salamanca | Llorens-Montes F.-J.,University of Granada
Expert Systems with Applications | Year: 2015

This study analyzes the viability of using employees' smartphones following the BYOD paradigm as a valid tool to enable firms to control effective presence (primarily of remote labor force). We propose a model for a Mobile Presence Control Information System with which to demonstrate experimentally the viability of unifying three elements that have only been examined individually in previous studies: the consumerization of ITs, the real geolocation capabilities of personal mobile devices that employees can use in the workplace, and the exclusive use of Mobile Web technology to obtain universal location information without the need to install native apps. We also propose a new and specific methodology to analyze the precision and accuracy of the location data obtained by smartphone geolocation services. We developed a prototype of the Information System proposed and demonstrated its validity under different real-use conditions, obtaining valuable information on the accuracy and precision of the location data from real devices (based on iOS and Android) under the conditions of heterogeneous connectivity representative of workplaces. This research enables us to establish a new framework for the requirements needed, on both quantitative and qualitative levels, for the accuracy of the mobile location systems that can be used in Presence Control Information Systems, particularly those related to control of remote labor force. © 2015 Elsevier Ltd.

Rodriguez S.,University of Salamanca | De Paz Y.,University of Salamanca | Bajo J.,Pontifical University of Salamanca | Corchado J.M.,University of Salamanca
Expert Systems with Applications | Year: 2011

An idea that seems to be gaining considerable ground is that modeling the interactions of a multi-agent system cannot be related exclusively to the actual agent and its communication capabilities, but must involve the use of concepts found in organizational engineering as well. It is possible to establish different types of agent organizations according to the type of communication, the coordination among agents, and the type of agents that comprise the group. Each organization needs to be supported by a coordinated effort that explicitly determines how the agents should be organized and carry out the actions and tasks assigned to them. This research presents a new global coordination model for an agent organization. The primary novelty of the model consists of the dynamic and adaptive planning capability to distribute tasks among the agent members of the organization as effectively as possible. This model is unique in its conception, allowing an organization in a highly dynamic environment to employ self-adaptive capabilities in execution time. This allows for the behavior of an agent to be determined by the goals it wishes to reach, while still giving consideration to the goals of other agents and any changes in the environment. The model is evaluated in a multi-agent system developed within an architecture oriented toward THOMAS organizations and simulated in a virtual environment. © 2010 Elsevier Ltd. All rights reserved.

Tapia D.I.,University of Salamanca | Fraile J.A.,Pontifical University of Salamanca | Rodriguez S.,University of Salamanca | Alonso R.S.,University of Salamanca | Corchado J.M.,University of Salamanca
Information Sciences | Year: 2013

Ambient Intelligence (AmI) systems require the integration of complex and innovative solutions. In this sense, agents and multi-agent systems have characteristics such as autonomy, reasoning, reactivity, social abilities and pro-activity which make them appropriate for developing distributed systems based on Ambient Intelligence. In addition, the use of context-aware technologies is an essential aspect in these developments in order to perceive stimuli from the context and react to it autonomously. This paper presents the integration of the Hardware-Embedded Reactive Agents (HERA) Platform into the Flexible and User Services Oriented Multi-agent Architecture (FUSIONat), a multi-agent architecture for developing AmI systems that integrates intelligent agents with a service-oriented architecture approach. Because of this integration, FUSION@ has the ability to manage both software and hardware agents by using self-adaptable heterogeneous wireless sensor networks. Preliminary results presented in this paper demonstrate the feasibility of FUSION@ as a future alternative for developing Ambient Intelligence systems where users and systems can use both software and hardware agents in a transparent way, achieving a higher level of ubiquitous computing and communication. © 2012 Elsevier Inc. All rights reserved.

Corchado J.M.,University of Salamanca | Tapia D.I.,University of Salamanca | Bajo J.,Pontifical University of Salamanca
International Journal of Innovative Computing, Information and Control | Year: 2012

Ambient Intelligence has acquired great importance in recent years and requires the development of new innovative solutions. This paper presents a novel architecture which facilitates the integration of multi-agent systems, distributed services and applications to optimize the construction of Ambient Intelligence environments. The architecture proposes a new and easier method to develop distributed intelligent ubiquitous systems, where applications and services can communicate in a distributed way with intelligent agents, even from mobile devices, independent of location restrictions. The core of the architecture is a group of deliberative agents acting as controllers and administrators for all applications and services. This approach provides the systems with a higher ability to recover from errors and a better flexibility to change their behavior at execution time. The architecture is founded on the Ambient Intelligence paradigm. A distributed multi-agent system has been developed to test this architecture. This system is aimed to improve health care and assistance to dependent persons in geriatric residences, and the preliminary results are presented in this paper. © 2012 ICIC International.

Martin-Merino M.,Pontifical University of Salamanca
13th IEEE International Conference on BioInformatics and BioEngineering, IEEE BIBE 2013 | Year: 2013

DNA Microarrays have been successfully applied to the identification of different cancer types considering the gene expression profiles. However, previous studies have shown that labeling errors are not uncommon in microarray studies. In this case, the training set may contain mislabelled examples that may lead the classifier to poor performance. In this paper we propose a new filtering algorithm based on one-class SVM classification to detect mislabelled samples. To this aim, samples and labels are mapped together to feature space using the kernel of dissimilarities. Next, outliers are detected via one-class classification. Mislabeled samples and outliers in input space can be separated comparing the outliers obtained in input and feature spaces. The algorithm proposed has been tested using several complex cancer microarray datasets in which some samples are mislabelled according to the literature. The experimental results suggest that our algorithm is effective detecting labeling errors and compares favorably with a standard technique such as simple SVM. © 2013 IEEE.

Martin-Merino M.,Pontifical University of Salamanca
Advances in Experimental Medicine and Biology | Year: 2010

The -Nearest Neighbor (k-NN) classifier has been applied to the identification of cancer samples using the gene expression profiles with encouraging results. However, the performance of -NN depends strongly on the distance considered to evaluate the sample proximities. Besides, the choice of a good dissimilarity is a difficult task and depends on the problem at hand. In this chapter, we introduce a method to learn the metric from the data to improve the -NN classifier. To this aim, we consider a regularized version of the kernel alignment algorithm that incorporates a term that penalizes the complexity of the family of distances avoiding overfitting. The error function is optimized using a semidefinite programming approach (SDP). The method proposed has been applied to the challenging problem of cancer identification using the gene expression profiles. Kernel alignment -NN outperforms other metric learning strategies and improves the classical -NN algorithm. © 2010 Springer Science+Business Media, LLC.

Martin-Merino M.,Pontifical University of Salamanca
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2011

Pattern Recognition algorithms depend strongly on the dissimilarity considered to evaluate the sample proximities. In real applications, several dissimilarities are available that may come from different object representations or data sources. Each dissimilarity provides usually complementary information about the problem. Therefore, they should be integrated in order to reflect accurately the object proximities. In many applications, the user feedback or the a priori knowledge about the problem provide pairs of similar and dissimilar examples. In this paper, we address the problem of learning a linear combination of dissimilarities using side information in the form of equivalence constraints. The minimization of the error function is based on a quadratic optimization algorithm. A smoothing term is included that penalizes the complexity of the family of distances and avoids overfitting. The experimental results suggest that the method proposed outperforms a standard metric learning algorithm and improves classification and clustering results based on a single dissimilarity and data source. © 2011 Springer-Verlag.

Rubio-Lacoba M.,Pontifical University of Salamanca
Profesional de la Informacion | Year: 2010

Due to both the digitization of press archives and the current financial, economic and journalistic recession, news libraries in online journalism need to re-invent themselves. While performing their traditional tasks, news librarians are developing new skills so that their activity will continue to be considered a necessary and natural component of quality journalism.

Garcia O.A.,Pontifical University of Salamanca | Secades V.A.,Pontifical University of Salamanca
Proceedings of the International Conference e-Learning 2013 | Year: 2013

In the information age, one of the most influential institutions is education. The recent emergence of MOOCS is a sample of the new expectations that are offered to university students. Basing decisions on data and evidence seems obvious, and indeed, research indicates that data-driven decision-making improves organizational productivity. The most dramatic factor shaping the future of higher education is Big Data and analytics. Big Data emphasizes that the data itself is a path to value generation in organizations and it is, also, a critical value for higher education institutions. The emerging practice of academic analytics is likely to become a new useful tool for a new era. Analytics and big data have a significant role to play in the future of higher education. This paper attempts an analytical practice about the use of e-learning technological tools to generate relevant information, for the teacher and the students who try to optimize their learning process.This combination of data-processing and analytical learning is an aid to improve significantly higher education and mark the path to follow in the new educational era.

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