Rosana Montes

A web tool to support decision making in the housing market using hesitant fuzzy linguistic term sets

Graphical abstractDisplay Omitted In this paper we present a linguistic multiple-expert multi-criteria decision making model and a web tool to support it, that is centred on the housing market. The web tool is integrated with the usual catalogue of resources for rental or for sale, enriched with the possibility of ranking a subset of properties according to the clients preferences and the internal knowledge associated to the properties. Usually the description of a property is quantitative, thought in our case we add qualitative information corresponding to assessments made by housing agents. These agents are considered experts in the market conditions.We apply the 2-tuple linguistic representation model to keep accuracy in the processes of Computing with Words and the hesitant fuzzy linguistic term sets to qualify in situations of uncertainty and hesitation in the assessments. The software helps the agents in the process of the elicitation of the linguistic expression based on the fuzzy linguistic approach and the use of context-free grammars, and the web clients in the decision of visiting a property.

Building chromosome-wide LD maps

SUMMARY BMapBuilder builds maps of pairwise linkage disequilibrium (LD) in either two or three dimensions. The optimized resolution allows for graphical display of LD for single nucleotide polymorphisms (SNPs) in a whole chromosome. AVAILABILITY The program is coded in Java, which runs on all relevant operating systems, including Windows, Mac and Unix/Linux, and is available from http://bios.ugr.es/BMapBuilder.

Teranga Go!: Carpooling Collaborative Consumption Community with multi-criteria hesitant fuzzy linguistic term set opinions to build confidence and trust

Display Omitted Online communities represent a sustainable model for participatory comsumption.Senegalese community my benefit from sharing the expenses of long journeys.Teranga Go! is an online community for carsharing that uses an intelligent decision support system named Teranga-IDSS.Teranga-IDSS uses linguistic information represented using HFLTS to model opinions about people interacting in a business relation.Teranga-IDSS computes a karma term visible on every user profile.The karma value represents what others say about any user on the basis of knowing this person after real interactions.Teranga Go! is implemented under GPL v2 license. Boosting collaborative or participatory consumption is a priority for the European Commission. It is in line with the provisions of the Europe 2020 Strategy, which proposes that consumption of goods and services should take place in accordance with smart, sustainable and inclusive growth. These have motivated us to develop an online community for collaborative consumption centered in the Senegalese community that travels by car from Europe to Africa named Teranga Go!. Carpooling relationships are based on the sense of a real existing community, social experiences among users, and connection through technology, where confidence is the key concept. To help creating values of confidence, trust and safety among the members of the Teranga Go! community, we have implemented an intelligent decision support system in the platform based on computing with words. The participants of a carpooling experience act as experts that assess the driver aptitudes and determine, together with the history of the driver, a linguistic value for the drivers karma which represents the collective opinion of people that have traveled with the driver. The karma is a public label attached to the site user profiles. A Multi-Expert Multi-Criteria Decision Making model is applied using Hesitant Fuzzy Linguistic Terms to represent the expert opinions.

Generating Lifelong-Learning Communities and Branding with Massive Open Online Courses

The arrival of Massive Open Online Courses MOOCs has stimulated teachers and universities to change in some ways the teaching methodologies. The success of these massive courses is based on involving students to acquire knowledge and skills in a wider community by learning from others and using active learning practices. MOOC providers also help universities to support the mission of transferring knowledge to society in any kind of area, supporting lifelong learning and adopting some kind of internationalization strategy. This is an ongoing trend where 17 of top 30 universities in the worlds adopted MOOC courses. Open learning is a strategic and valuable trend in knowledge society. Opportunities appear in the Anglo and Latin American market, while problems associated with the high drop-out rate, the sustainability, and the feasibility of skill certification should be addressed. In this paper we analyze the properties of a MOOC as a learning community by taking data from a pilot of three MOOC courses performed at AbiertaUGR, the MOOC platform of the University of Granada.

BioCASE: Accelerating Software Development of Genome-Wide Filtering Applications

Due to the high pace that algorithms for scanning genome-wide datasets are produced, most of the software is quickly released. As a consequence, they usually lack in system portability and only provide a text-based user interface. BioCASE is an open-source tool developed to assist bioinformaticians in the task of producing software to perform any kind of computationally-expensive genome-wide scanning. BioCASE will produce efficient software with some other added features such as to be portable, to have a graphical user interface (GUI) and to be easily set up. A first version of BioCASE (http://bios.ugr.es/biocase) has been completed and it is being currently used in the design of a genome- wide tool to perform variable selection of genotype data sets based on multivariate association and transmission-disequilibrium tests.

Turning out a social community into an e-Learning platform for MOOC: the case of AbiertaUGR

This paper considers the interest of traditional high educational institution to bounce into the world of Massive Open Online Courses (MOOC). This learning approach is defined over the concept of Open Educational Resources (OER) in a basis of a high number of users that interact with the learning materials (mostly multimedia resources). This approach implies some challenges to the software platform that lies behind the learning experience. In this work we are going to evaluate the Open Source Social Networking Engine, ELGG, and how it has strongly evolved to AbiertaUGR.

Designing a compact Genetic fuzzy rule-based system for one-class classification

This paper proposes a method for designing Fuzzy Rule-Based Classification Systems to deal with One-Class Classification, where during the training phase we have access only to objects originating from a single class. However, the trained model must be prepared to deal with new, unseen adversarial objects, known as outliers. We use a Genetic Algorithm for learning the granularity, domains and fuzzy partitions of the model and we propose an ad-hoc rule generation method specific for One-Class Classification. Several datasets from UCI repository, previously transformed to one-class problems, are used in the experiments and we compare with two of the classical methods used in the One-Class community, one-class Support Vector Machines and Support Vector Data Description. Our proposal of fuzzy model obtains similar results than the other methods but presents a high interpretability due its reduced number of rules.

Interactive global illumination for quasi-static scenes

This paper describes an approach to obtain interactive recalculation of global illumination for scenes with small moving objects (with respect to the complete geometry), on a standard PC, using density estimation techniques

A decision making model to evaluate the reputation in social networks using HFLTS

We present Teranga Go!, a social network with a linguistic fuzzy model which deals with HFLTS information as a practical application of decision making problems. It is defined to help members to select to whom interact based on collective information regarding real interactions with any user. In this way, we provide a tool intended to build trust among members of a sharing economy community given that is a major drawback from online transactions. As a workbench to run the linguistic decision making model, a web site and a mobile application for iOS and Android offer access to a carpooling service named Teranga Go! that seek to foster the mobility of international migration flows from Europe to Africa, based on concepts of collaborative economy and participatory consumption. The novelty of the site is the possibility of using hesitant linguistic expressions to assess a set of qualitative criteria and the use of the community members as the pool of experts. Unlike many multi criteria decision making problems we do not rank alternatives, we just qualify them using the retrieved opinions, which target a given user, and are collected over any interaction with this person along the time. Based on Computing with Words methodology where inputs are words and output are also words, we obtain from the model a linguistic value that is used to represent a karma property present in the user profile.

An Importance Sampling Method for Arbitrary BRDFs

This paper introduces a new BRDF sampling method with reduced variance, which is based on a hierarchical adaptive PDF. This PDF also is based on rejection sampling with a bounded average number of trials, even in regions where the BRDF exhibits high variations. Our algorithm works in an appropiate way with both physical, analytical and measured reflectance models. Reflected directions are sampled by using importance sampling of the BRDF times the cosine term. This fact improves computation of reflected radiance when Monte-Carlo integration is used in Global Illumination.