A Regulatory Model for Context-Aware Abstract Framework

Proceedings of: 23rd International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2010, Cordoba, Spain, June 1-4, 2010.This paper presents a general framework to define a context aware application and analyzes social guarantees to be considered to develop this kind of applications following legal assumptions as privacy, human rights, etc. We present a review of legal issues in biometric user identification where several legal aspects have been developed in European Union regulation and a general framework to define context aware applications. As main result, paper presents a legal framework to be taken into account in any context-based application to ensure a harmonious and coherent system for the protection of fundamental rights.This work was supported in part by Projects CICYT TIN2008-06742-C02-02/TSI, CICYT TEC2008-06732-C02-02/TEC, CAM CONTEXTS (S2009/TIC-1485) and DPS2008-07029- C02-02.Publicad

Finding an Evolutionarily Stable Strategy in Agent Reputation and Trust (ART) 2007 Competition

Proceedings of: 23rd International Conference on Industrial Engineering and Other Applications of Applied intelligent Systems, IEA/AIE 2010, Cordoba, Spain, June 1-4, 2010Our proposal is to apply a Game Theoretic approach to the games played in Agent Reputation and Trust Final Competitions. Using such testbed, three international competitions were successfully carried out jointly with the last AAMAS international Conferences. The corresponding way to define the winner of such competitions was to run a game with all the participants (16). Our point is that such game does not represent a complete way to determine the best trust/reputation strategy, since it is not proved that such strategy is evolutionarily stable. Specifically we prove that when the strategy of the winner of the two first international competitions (2006 and 2007) becomes dominant, it is defeated by other participant trust strategies. Then we found out (through a repeated game definition) the right equilibrium of trust strategies that is evolutionarily stable. This kind of repeated game has to be taken into account in the evaluation of trust strategies, and this conclusion would improve the way trust strategies have to be compared.This work was supported in part by Projects CICYT TIN2008-06742-C02-02/ TSI, CICYT TEC2008-06732-C02-02/TEC, SINPROB, CAM MADRINET S-0505/TIC/0255 and DPS2008-07029-C02-02.Publicad

Air Traffic Control: A Local Approach to the Trajectory Segmentation Issue

Proceedings of: 23rd International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems (IEA-AIE 2010) Córdoba-Spain, June 04-06, 2010This paper presents a new approach for trajectory segmentation in the area of Air Traffic Control, as a basic tool for offline validation with recorded opportunity traffic data. Our approach uses local information to classify each measurement individually, constructing the final segments over these classified samples as the final solution of the process. This local classification is based on a domain transformation using motion models to identify the deviations at a local scale, as an alternative to other global approaches based on combinatorial analysis over the trajectory segmentation domain.This work was supported in part by Projects CICYT TIN2008-06742-C02-02/TSI, CICYT TEC2008-06732-C02-02/TEC, CAM CONTEXTS (S2009/TIC-1485) and DPS2008-07029-C02-02.Publicad

Peran Fingering Pada Teknik Pizzicato Dan Harmonics Dalam Reinterpretasi Karya Maurice Ravel

Tujuan dari penelitian ini adalah mengetahui peran fingering pada teknik pizzicato dan harmonics dalam upaya reinterpretasi terhadap repertoar Tzigane karya Maurice Ravel. Sering kita jumpai bahwa solois menerapkan penjarian yang berbeda dari penjarian yang sudah ditentukan dalam partitur. Tidak hanya itu, perbedaan juga terjadi antara solois yang satu dan yang lainnya meskipun memainkan karya yang sama. Penelitian ini menggunakan teori yang meliputi fingering, pizzicato, harmonic dan interpretasi yang nantinya akan membantu dalam proses realisasi pada dinamika, warna suara dan artikulasi sebagai bentuk dari reinterpretasi seorang solois.  Metode Penelitian yang digunakan adalah metode kualitatif dengan pendekatan studi kasus. Kasus yang digunakan adalah teknik pizzicato dan harmonics pada repertoar Tzigane karya Maurice Ravel. Hasil penelitian menunjukkan bahwa fingering pada teknik pizzicato mempengaruhi keberhasilan solois dalam merealisasikan reinterpretasi melalui teknik. Sedangkan fingering pada teknik harmonics dapat mendukung solois dalam merubah atau menguatkan kesan musikal tertentu berdasarkan rancangan reinterpretasi (blueprint).Kata kunci : fingering, pizzicato, harmonics, reinterpretasi, Maurice Ravel. ABSTRACTThe Role Of Fingering In Pizzicato And Harmonics Techniques In Reinterpretation Of Maurice Ravel's WorksThe purpose of this study was determine the role of fingering in the pizzicato technique and harmonics in an effort to reinterpret Maurice Ravel's Tzigane repertoire. We often find that the soloist applies fingering that is different from the fingering that has been determined in the scores. Not only that, differences also occur between one soloist and another even though they play the same work. This Study used the theory that includes fingering, pizzicato, harmonics and interpretation, which will help the process of realizing dynamics, timbre and articulation as a form of reinterpretation by a soloist. The research method used is a qualitative method with a case study approach. The case used is the pizzicato technique and harmonics in Maurice Ravel's Tzigane repertoire. The results of the study show that fingering in the pizzicato technique influences the success of the soloist in realizing reinterpretation through technique. Meanwhile, fingering in harmonics techniques can support soloists in changing or strengthening certain musical impressions based on reinterpretation designs (blueprints).Keywords: fingering, pizzicato, harmonics, reinterpretation, Maurice Ravel

On the Configuration of More and Less Expressive Logic Programs

The decoupling between the representation of a certain problem, i.e., its knowledge model, and the reasoning side is one of main strong points of model-based Artificial Intelligence (AI). This allows, e.g. to focus on improving the reasoning side by having advantages on the whole solving process. Further, it is also well-known that many solvers are very sensitive to even syntactic changes in the input. In this paper, we focus on improving the reasoning side by taking advantages of such sensitivity. We consider two well-known model-based AI methodologies, SAT and ASP, define a number of syntactic features that may characterise their inputs, and use automated configuration tools to reformulate the input formula or program. Results of a wide experimental analysis involving SAT and ASP domains, taken from respective competitions, show the different advantages that can be obtained by using input reformulation and configuration. Under consideration in Theory and Practice of Logic Programming (TPLP).Comment: Under consideration in Theory and Practice of Logic Programming (TPLP

Conceptualizing Landscapes: A Comparative Study of Landscape Categories with Navajo and English-speaking Participants

Abstract. Understanding human concepts, spatial and other, is not only one of the most prominent topics in the cognitive and spatial sciences; it is also one of the most challenging. While it is possible to focus on specific aspects of our spatial environment and abstract away complexities for experimental purposes, it is important to understand how cognition in the wild or at least with complex stimuli works, too. The research presented in this paper addresses emerging topics in the area of landscape conceptualization and explicitly uses a diversity fostering approach to uncover potentials, challenges, complexities, and patterns in human landscape concepts. Based on a representation of different landscapes (images) responses from two different populations were elicited: Navajo and the (US) crowd. Our data provides support for the idea of conceptual pluralism; we can confirm that participant responses are far from random and that, also diverse, patterns exist that allow for advancing our understanding of human spatial cognition with complex stimuli

Best practices for machine learning in antibody discovery and development

Over the past 40 years, the discovery and development of therapeutic antibodies to treat disease has become common practice. However, as therapeutic antibody constructs are becoming more sophisticated (e.g., multi-specifics), conventional approaches to optimisation are increasingly inefficient. Machine learning (ML) promises to open up an in silico route to antibody discovery and help accelerate the development of drug products using a reduced number of experiments and hence cost. Over the past few years, we have observed rapid developments in the field of ML-guided antibody discovery and development (D&D). However, many of the results are difficult to compare or hard to assess for utility by other experts in the field due to the high diversity in the datasets and evaluation techniques and metrics that are across industry and academia. This limitation of the literature curtails the broad adoption of ML across the industry and slows down overall progress in the field, highlighting the need to develop standards and guidelines that may help improve the reproducibility of ML models across different research groups. To address these challenges, we set out in this perspective to critically review current practices, explain common pitfalls, and clearly define a set of method development and evaluation guidelines that can be applied to different types of ML-based techniques for therapeutic antibody D&D. Specifically, we address in an end-to-end analysis, challenges associated with all aspects of the ML process and recommend a set of best practices for each stage

Motifs séquentiels pour la description de séries temporelles d'images satellitaires et la prévision d'événements

Les travaux présentés concernent l’extraction de connaissances dans les données à des fins de description et d’inférence. Comment décrire des Séries Temporelles d’Images Satellitaire (STIS) en mode non supervisé ? Comment prévoir des événements tels que des pannes dans des systèmes complexes ? Des réponses originales s’appuyant sur des techniques de fouille de données extrayant des motifs locaux, les motifs séquentiels, sont développées. Ainsi, de nouveaux motifs, les motifs Séquentiels Fréquents Groupés (motifs SFG), sont-ils proposés afin d’extraire d’une STIS des groupes de pixels faisant sens spatialement et temporellement. Une technique originale permettant de pousser les contraintes associées à ces motifs au sein du processus d’extraction est également détaillée. Des expériences sur des données optiques et radar, à des résolutions différentes, confirment leur potentiel. Un classement de ces motifs basé sur l’information mutuelle et la swap-randomization est par ailleurs proposé afin de mettre en avant les motifs ayant peu de chances d’apparaître dans un jeu de données aléatoires où les fréquences sont conservées, exprimant des changements et progressant dans l’espace. Quant à la prévision d’événements, une approche de type leave-one-out est proposée pour sélectionner des motifs séquentiels, les FLM-règles, génériques et déclenchant le moins possible de fausses alarmes. Une méthode de prévision au plus tôt tirant parti de ces motifs est également avancée et validée sur des données réelles provenant de systèmes mécaniques complexes. Les expériences menées montrent qu’il est possible de prévoir des défaillances pour lesquelles l’expertise technique est insuffisante. Cette méthode de prévision est aujourd’hui brevetée

Machine learning and soft computing approaches to microarray differential expression analysis and feature selection.

Differential expression analysis and feature selection is central to gene expression microarray data analysis. Standard approaches are flawed with the arbitrary assignment of cut-off parameters and the inability to adapt to the particular data set under analysis. Presented in this thesis are three novel approaches to microarray data feature selection and differential expression analysis based on various machine learning and soft computing paradigms. The first approach uses a Separability Index to select ranked genes, making gene selection less arbitrary and more data intrinsic. The second approach is a novel gene ranking system, the Fuzzy Gene Filter, which provides a more holistic and adaptive approach to ranking genes. The third approach is based on a Stochastic Search paradigm and uses the Population Based Incremental Learning algorithm to identify an optimal gene set with maximum inter-class distinction. All three approaches were implemented and tested on a number of data sets and the results compared to those of standard approaches. The Separability Index approach attained a K-Nearest Neighbour classification accuracy of 92%, outperforming the standard approach which attained an accuracy of 89.6%. The gene list identified also displayed significant functional enrichment. The Fuzzy Gene Filter also outperformed standard approaches, attaining significantly higher accuracies for all of the classifiers tested, on both data sets (p < 0.0231 for the prostate data set and p < 0.1888 for the lymphoma data set). Population Based Incremental Learning outperformed Genetic Algorithm, identifying a maximum Separability Index of 97.04% (as opposed to 96.39%). Future developments include incorporating biological knowledge when ranking genes using the Fuzzy Gene Filter as well as incorporating a functional enrichment assessment in the fitness function of the Population Based Incremental Learning algorithm

Assessment and forecasting of solar resource: applications to the solar energy industry

En la presente tesis doctoral se lleva a cabo un estudio de la evaluación y de la predicción del recurso solar para su aplicación en el campo de la industria solar. El objetivo principal es mejorar el conocimiento sobre varios aspectos de la radiación solar como fuente primaria de energía. Sin embargo, a pesar del incesante desarrollo tecnológico y el considerable abaratamiento de costes, su grado de introducción dentro de los sistemas eléctricos a gran escala está todavía lejos de su potencial real. Esto es debido en gran parte a que, a pesar de que la radiación solar es la fuente primaria de energía más abundante del planeta, presenta de forma natural una gran variabilidad espacio-temporal. Esta característica constituye la mayor fuente de incertidumbre en el desarrollo de los proyectos solares, tanto en la fase inicial de estudio de viabilidad como durante la fase de operación. Con el fin de contribuir a la reducción de dicha incertidumbre, en el trabajo de investigación llevado a cabo en esta tesis doctoral se han desarrollado y evaluado métodos para la caracterización y la estimación de la irradiancia solar en superficie, tanto para la componente global (GHI) como para la directa (DNI).In this thesis a study of the assessment and forecasting of the solar resource for its application in the solar industry is carried out. The main objective is to improve the knowledge about various aspects of solar radiation as primary energy source. . However, despite the relentless technological development and the considerable cost reductions, its degree of introduction at large-scale into power systems is still far from its real potential. This is due mainly to the fact that, although solar radiation is the most abundant primary energy source in the planet, it naturally presents a great spatial and temporal variability. This characteristic constitutes the major source of uncertainty in the development of solar projects, both in the initial phase of feasibility study and during the phase of operation. In order to contribute to the reduction of this uncertainty, the research work carried out in this thesis has developed and evaluated methods for the characterization and estimation of surface solar irradiance, both components: global (GHI) and direct (DNI).Tesis Univ. Jaén. Departamento de Física. Leída el 24 de julio de 2017