On the way to solve lighting problems in underwater imaging

A major obstacle to processing images of the ocean floor comes from the absorption and scattering effects of the light in the aquatic environment. Due to the absorption of the natural light, underwater vehicles often require artificial light sources attached to them to provide the adequate illumination. Unfortunately, these flashlights tend to illuminate the scene in a nonuniform fashion, and, as the vehicle moves, induce shadows in the scene. For this reason, the first step towards application of standard computer vision techniques to underwater imaging requires dealing first with these lighting problems. This paper analyses and compares existing methodologies to deal with low-contrast, nonuniform illumination in underwater image sequences. The reviewed techniques include: (i) study of the illumination-reflectance model, (ii) local histogram equalization, (iii) homomorphic filtering, and, (iv) subtraction of the illumination field. Several experiments on real data have been conducted to compare the different approaches

Informed recommender: basing recommendations on consumer product reviews

Recommender systems attempt to predict items in which a user might be interested, given some information about the user's and items' profiles. Most existing recommender systems use content-based or collaborative filtering methods or hybrid methods that combine both techniques (see the sidebar for more details). We created Informed Recommender to address the problem of using consumer opinion about products, expressed online in free-form text, to generate product recommendations. Informed recommender uses prioritized consumer product reviews to make recommendations. Using text-mining techniques, it maps each piece of each review comment automatically into an ontology

Recommender System Based on Consumer Product Reviews

Consumer reviews, opinions and shared experiences in the use of a product is a powerful source of information about consumer preferences that can be used in recommender systems. Despite the importance and value of such information, there is no comprehensive mechanism that formalizes the opinions selection and retrieval process and the utilization of retrieved opinions due to the difficulty of extracting information from text data. In this paper, a new recommender system that is built on consumer product reviews is proposed. A prioritizing mechanism is developed for the system. The proposed approach is illustrated using the case study of a recommender system for digital cameras

Asistentes virtuales en plataformas 3.0

Los asistentes virtuales son herramientas inteligentes que ayudan a los usuarios a buscar información en un conglomerado de recursos web. El despliegue natural de los mismos se realiza en las propias páginas web, donde permiten resolver las dudas de los usuarios formuladas en lenguaje natural usando técnicas de Inteligencia Artificial. En este artículo presentamos las características más relevantes del asistente virtual Elvira y su integración en la página web de la Universidad de Granada. De forma paralela a la aparición de los asistentes virtuales, en la última década, los avances tecnológicos han hecho que el acceso a la información se produzca desde diferentes fuentes, trasladando la necesidad de la asistencia artificial a otros ámbitos. En este trabajo, detallamos la ampliación de los despliegues del asistente virtual Elvira sobre dispositivos móviles y redes sociales.

Nuevas funcionalidades de LocalGIS-DOS

LocalGIS-DOS es la nueva versión oficial de LocalGIS, el Sistema de Información Territorial Software Libre para Entidades Locales que surgió a iniciativa del Ministerio de Industria, Turismo y Comercio y que está englobado dentro del Plan Avanza. La nueva versión LocalGIS-DOS, que estará disponible en marzo de 2010 coincidiendo con las IV Jornadas de SIG Libre de Girona, va a contar con nuevos módulos que dotarán a LocalGIS de importantes mejoras tecnológicas y funcionales de Gestión Municipal. LocalGIS-DOS incluye un nuevo módulo de Enrutamiento y Cálculo de rutas, tanto en el Módulo de Editor GIS como en la Guía Urbana, que permitirá calcular caminos óptimos y zonas de influencia. El nuevo módulo de Movilidad facilitará la gestión de información municipal desde dispositivos móviles, con herramientas para la edición y visualización de la misma y para su correcta replicación con la base de datos central. LocalGIS-DOS permitirá gestionar varios municipios con intereses comunes de forma simultánea, creando el concepto de Entidad Supramunicipal, pudiendo así gestionar de forma conjunta capas, estilos y usuarios. Esta nueva versión incorpora también la Variable Temporal a las capas de información, permitiendo a los usuarios seleccionar por fechas la información que desean visualizar, facilitando así la elaboración de estudios temporales georreferenciados y el versionado histórico de mapas. También incluye un nuevo Módulo de Gestión de la Ciudad, desde donde se gestionarán avisos, mantenimientos y obras ubicadas en el suelo público. Finalmente indicar que a nivel tecnológico LocalGIS-DOS contará, entre otras, con mejoras relativas al acceso a bases de datos externas, al canal cifrado de comunicación, firma digital de documentos y mejoras en la generación de informes

Geolocalizador de noticias temáticas: el caso de los riesgos naturales

Las bases de datos geoespaciales temáticas en distintas escalas geográficas y temporales, son necesarias en multitud de líneas de investigación. Una de ellas es la gestión y alerta temprana de riesgos de desastres por amenazas naturales (inundaciones, huracanes, terremotos, etc.). Las noticias sobre éste tema se publican habitualmente en periódicos digitales de todo el mundo y comportan un alto contenido geográfico. Este trabajo pretende extraer automáticamente las noticias emitidas por canales de re-difusión web (conocidos por las siglas RSS en inglés) para georreferenciarlas, almacenarlas y distribuirlas como datos geoespaciales. Mediante técnicas de procesamiento de lenguaje natural y consultas a bases de datos de topónimos realizaremos la extracción de la información. El caso de estudio se aplicará para México y todos los componentes utilizados serán de código abierto

Collaborative recommender agents based on case-based reasoning and trust

La comunitat científica que treballa en Intel·ligència Artificial (IA) ha dut a terme una gran quantitat de treball en com la IA pot ajudar a les persones a trobar el que volen dins d'Internet. La idea dels sistemes recomanadors ha estat extensament acceptada pels usuaris. La tasca principal d'un sistema recomanador és localitzar ítems, fonts d'informació i persones relacionades amb els interessos i preferències d'una persona o d'un grup de persones. Això comporta la construcció de models d'usuari i l'habilitat d'anticipar i predir les preferències de l'usuari. Aquesta tesi està focalitzada en l'estudi de tècniques d'IA que millorin el rendiment dels sistemes recomanadors. Inicialment, s'ha dut a terme un anàlisis detallat de l'actual estat de l'art en aquest camp. Aquest treball ha estat organitzat en forma de taxonomia on els sistemes recomanadors existents a Internet es classifiquen en 8 dimensions generals. Aquesta taxonomia ens aporta una base de coneixement indispensable pel disseny de la nostra proposta. El raonament basat en casos (CBR) és un paradigma per aprendre i raonar a partir de la experiència adequat per sistemes recomanadors degut als seus fonaments en el raonament humà. Aquesta tesi planteja una nova proposta de CBR aplicat al camp de la recomanació i un mecanisme d'oblit per perfils basats en casos que controla la rellevància i edat de les experiències passades. Els resultats experimentals demostren que aquesta proposta adapta millor els perfils als usuaris i soluciona el problema de la utilitat que pateixen el sistemes basats en CBR. Els sistemes recomanadors milloren espectacularment la qualitat dels resultats quan informació sobre els altres usuaris és utilitzada quan es recomana a un usuari concret. Aquesta tesi proposa l'agentificació dels sistemes recomanadors per tal de treure profit de propietats interessants dels agents com ara la proactivitat, la encapsulació o l'habilitat social. La col·laboració entre agents es realitza a partir del mètode de filtratge basat en la opinió i del mètode col·laboratiu de filtratge a partir de confiança. Els dos mètodes es basen en un model social de confiança que fa que els agents siguin menys vulnerables als altres quan col·laboren. Els resultats experimentals demostren que els agents recomanadors col·laboratius proposats milloren el rendiment del sistema mentre que preserven la privacitat de les dades personals de l'usuari. Finalment, aquesta tesi també proposa un procediment per avaluar sistemes recomanadors que permet la discussió científica dels resultats. Aquesta proposta simula el comportament dels usuaris al llarg del temps basat en perfils d'usuari reals. Esperem que aquesta metodologia d'avaluació contribueixi al progrés d'aquesta àrea de recerca.

The human thalamus processes syntactic and semantic language violations

Numerous linguistic operations have been assigned to cortical brain areas, but the contributions of subcortical structures to human language processing are still being discussed. Using simultaneous EEG recordings directly from deep brain structures and the scalp, we show that the human thalamus systematically reacts to syntactic and semantic parameters of auditorily presented language in a temporally interleaved manner in coordination with cortical regions. In contrast, two key structures of the basal ganglia, the globus pallidus internus and the subthalamic nucleus, were not found to be engaged in these processes. We therefore propose that syntactic and semantic language analysis is primarily realized within cortico-thalamic networks, whereas a cohesive basal ganglia network is not involved in these essential operations of language analysis.

Towards dynamical system models of language-related brain potentials

Event-related brain potentials (ERP) are important neural correlates of cognitive processes. In the domain of language processing, the N400 and P600 reflect lexical-semantic integration and syntactic processing problems, respectively. We suggest an interpretation of these markers in terms of dynamical system theory and present two nonlinear dynamical models for syntactic computations where different processing strategies correspond to functionally different regions in the system's phase space.

Chatterbox challenge as a test-bed for synthetic emotions

Chatterbox Challenge is an annual web-based contest for artificial conversational systems, ACE. The 2010 instantiation was the tenth consecutive contest held between March and June in the 60th year following the publication of Alan Turing’s influential disquisition ‘computing machinery and intelligence’. Loosely based on Turing’s viva voca interrogator-hidden witness imitation game, a thought experiment to ascertain a machine’s capacity to respond satisfactorily to unrestricted questions, the contest provides a platform for technology comparison and evaluation. This paper provides an insight into emotion content in the entries since the 2005 Chatterbox Challenge. The authors find that synthetic textual systems, none of which are backed by academic or industry funding, are, on the whole and more than half a century since Weizenbaum’s natural language understanding experiment, little further than Eliza in terms of expressing emotion in dialogue. This may be a failure on the part of the academic AI community for ignoring the Turing test as an engineering challenge.

Constraints on L2 learners’ processing of wh- dependencies: evidence from eye-movements

Using the eye movement monitoring technique, the present study examined whether wh-dependency formation is sensitive to island constraints in second language (L2) sentence comprehension, and whether the presence of an intervening relative clause island has any effects on learners’ ability to ultimately resolve long wh-dependencies. Participants included proficient learners of L2 English from typologically different language backgrounds (German, Chinese), as well as a group of native English-speaking controls. Our results indicate that both the learners and the native speakers were sensitive to relative clause islands during processing, irrespective of typological differences between the learners’ L1s, but that the learners had more difficulty than native speakers linking distant wh-fillers to their lexical subcategorizers during processing. We provide a unified processing-based account for our findings.

The impact of number mismatch and passives on the real-time processing of relative clauses

Language processing plays a crucial role in language development, providing the ability to assign structural representations to input strings (e.g., Fodor, 1998). In this paper we aim at contributing to the study of children's processing routines, examining the operations underlying the auditory processing of relative clauses in children compared to adults. English-speaking children (6–8;11) and adults participated in the study, which employed a self-paced listening task with a final comprehension question. The aim was to determine (i) the role of number agreement in object relative clauses in which the subject and object NPs differ in terms of number properties, and (ii) the role of verb morphology (active vs. passive) in subject relative clauses. Even though children's off-line accuracy was not always comparable to that of adults, analyses of reaction times results support the view that children have the same structural processing reflexes observed in adults.

Design of a unified data with business rules storage model for OLTP and OLAP systems

This paper reviews the literature concerning the practice of using Online Analytical Processing (OLAP) systems to recall information stored by Online Transactional Processing (OLTP) systems. Such a review provides a basis for discussion on the need for the information that are recalled through OLAP systems to maintain the contexts of transactions with the data captured by the respective OLTP system. The paper observes an industry trend involving the use of OLTP systems to process information into data, which are then stored in databases without the business rules that were used to process information and data stored in OLTP databases without associated business rules. This includes the necessitation of a practice, whereby, sets of business rules are used to extract, cleanse, transform and load data from disparate OLTP systems into OLAP databases to support the requirements for complex reporting and analytics. These sets of business rules are usually not the same as business rules used to capture data in particular OLTP systems. The paper argues that, differences between the business rules used to interpret these same data sets, risk gaps in semantics between information captured by OLTP systems and information recalled through OLAP systems. Literature concerning the modeling of business transaction information as facts with context as part of the modelling of information systems were reviewed to identify design trends that are contributing to the design quality of OLTP and OLAP systems. The paper then argues that; the quality of OLTP and OLAP systems design has a critical dependency on the capture of facts with associated context, encoding facts with contexts into data with business rules, storage and sourcing of data with business rules, decoding data with business rules into the facts with the context and recall of facts with associated contexts. The paper proposes UBIRQ, a design model to aid the co-design of data with business rules storage for OLTP and OLAP purposes. The proposed design model provides the opportunity for the implementation and use of multi-purpose databases, and business rules stores for OLTP and OLAP systems. Such implementations would enable the use of OLTP systems to record and store data with executions of business rules, which will allow for the use of OLTP and OLAP systems to query data with business rules used to capture the data. Thereby ensuring information recalled via OLAP systems preserves the contexts of transactions as per the data captured by the respective OLTP system.

Evidence from neurolinguistic methodologies: can it actually inform linguistic/ language acquisition theories and translate to evidence-based applications?

This special issue is a testament to the recent burgeoning interest by theoretical linguists, language acquisitionists and teaching practitioners in the neuroscience of language. It offers a highly valuable, state-of-the-art overview of the neurophysiological methods that are currently being applied to questions in the field of second language (L2) acquisition, teaching and processing. Research in the area of neurolinguistics has developed dramatically in the past twenty years, providing a wealth of exciting findings, many of which are discussed in the papers in this volume. The goal of this commentary is twofold. The first is to critically assess the current state of neurolinguistic data from the point of view of language acquisition and processing—informed by the papers that comprise this special issue and the literature as a whole—pondering how the neuroscience of language/processing might inform us with respect to linguistic and language acquisition theories. The second goal is to offer some links from implications of exploring the first goal towards informing language teachers and the creation of linguistically and neurolinguistically-informed evidence-based pedagogies for non-native language teaching.