Evaluation of free libraries for visual recognition of art imagery on mobile devices

This paper describes a systematic research about free software solutions and techniques for art imagery computer recognition problem.

eKnowledge Project: Developing and piloting a forum tool to support the collaborative construction of knowledge on the UOC's Virtual Campus

Final report of the eKnowledge's project, an online forum tool that offers consultants and students the chance to create spaces for asynchronous communication and collaboration.

Greenberg i Danto : De l'últim gran relat a la fi de l'art

A partir de l'anàlisi comparatiu de l'obra de dos grans teòrics de la modernitat i la postmodernitat com són Clement Greenberg i Arthur C. Danto es fa un estudi de com aquests dos autors han arribat a construir els seus discursos i, en relació a això, com ha anat evolucionant el concepte d'art de la modernitat a la postmodernitat. La qüestió central que se'ns planteja és: què ha canviat en la idea d'art de la postmodernitat respecte a la idea o a la concepció d'art anterior, per arribar-nos a qüestionar si realment hi ha art i, si n'hi ha, què és art i que no ho és? Existeix una idea universal de què ha de ser art? O aquesta és una qüestió intrínsicament relacionada amb la societat en què es produeix; en aquest cas, la societat occidental?

Multiculturalitat i interculturalitat en la Història de Catalunya

La finalitat de la recerca, concebuda com a recerca aplicada ha consistit en confegir un manual d’història de Catalunya (Catalunya+suma) especialment destinat a la immigració. El treball havia de contextualizar aspectes generals d’història política, social i cultural (endògenes), amb les aportacions, ètniques i culturals (exògenes) rebudes a Catalunya al llarg del temps i que han configurat al capdavall la societat catalana, entesa com a formació cultural i socio-política, les variables de la qual han estat en contínua coevolució. Per tant tractar la dialèctica de com, en un període de temps, les aportacions exògenes és converteixen en endògenes, i sempre en una perspectiva temporal i històrica, ha estat l’objectiu del treball. La recerca bibliogràfica i la transposició didàctica han estat les principals components metodològiques. S’han tingut especialment en compte les aportacions de la historiografia contemporània, tot i que s’ha fet un esforç per integrar coneixement generat dels del punt de vista de l’arqueologia i l’antropologia, història de l’art, sociologia, etc. Pel que fa a la recerca didàctica el tret més important ha estat, precisament, el procés de transposició didàctica destinat a convertir el saber disciplinar en saber comprensible. El projecte “Multiculturalitat i interculturalitat en la Història de Catalunya” ha generat un estudi històric i didàctic de síntesi sobre història del país que es concreta en el manual “Catalunya+Suma”. Es tracta d’un manual d‘història de Catalunya dirigit a un horitzó d’ampli espectre i de manera molt especial als immigrants. Cal destacar també que el treball te un caràcter inicial i iniciàtic i que te possibilitats de desenvolupament posterior a partir de l’elaboració de materials didàctics i guies patrimonials expressament adreçada a la immigració i entorns afins. El manual “Catalunya+suma" vol incidir, prioritàriament en la formació inicial i permanent de la immigració, i en els espais formals, i no formals, d’ensenyament i aprenentatge.

Art painting Data Collection

The classification of Art painting images is a computer vision applications that isgrowing considerably. The goal of this technology, is to classify an art paintingimage automatically, in terms of artistic style, technique used, or its author. For thispurpose, the image is analyzed extracting some visual features. Many articlesrelated with these problems have been issued, but in general the proposed solutionsare focused in a very specific field. In particular, algorithms are tested using imagesat different resolutions, acquired under different illumination conditions. Thatmakes complicate the performance comparison of the different methods. In thiscontext, it will be very interesting to construct a public art image database, in orderto compare all the existing algorithms under the same conditions. This paperpresents a large art image database, with their corresponding labels according to thefollowing characteristics: title, author, style and technique. Furthermore, a tool thatmanages this database have been developed, and it can be used to extract differentvisual features for any selected image. This data can be exported to a file in CSVformat, allowing researchers to analyze the data with other tools. During the datacollection, the tool stores the elapsed time in the calculation. Thus, this tool alsoallows to compare the efficiency, in computation time, of different mathematicalprocedures for extracting image data.

Knowledge management for systems biology a general and visually driven framework applied to translational medicine

Background: To enhance our understanding of complex biological systems like diseases we need to put all of the available data into context and use this to detect relations, pattern and rules which allow predictive hypotheses to be defined. Life science has become a data rich science with information about the behaviour of millions of entities like genes, chemical compounds, diseases, cell types and organs, which are organised in many different databases and/or spread throughout the literature. Existing knowledge such as genotype - phenotype relations or signal transduction pathways must be semantically integrated and dynamically organised into structured networks that are connected with clinical and experimental data. Different approaches to this challenge exist but so far none has proven entirely satisfactory. Results: To address this challenge we previously developed a generic knowledge management framework, BioXM™, which allows the dynamic, graphic generation of domain specific knowledge representation models based on specific objects and their relations supporting annotations and ontologies. Here we demonstrate the utility of BioXM for knowledge management in systems biology as part of the EU FP6 BioBridge project on translational approaches to chronic diseases. From clinical and experimental data, text-mining results and public databases we generate a chronic obstructive pulmonary disease (COPD) knowledge base and demonstrate its use by mining specific molecular networks together with integrated clinical and experimental data. Conclusions: We generate the first semantically integrated COPD specific public knowledge base and find that for the integration of clinical and experimental data with pre-existing knowledge the configuration based set-up enabled by BioXM reduced implementation time and effort for the knowledge base compared to similar systems implemented as classical software development projects. The knowledgebase enables the retrieval of sub-networks including protein-protein interaction, pathway, gene - disease and gene - compound data which are used for subsequent data analysis, modelling and simulation. Pre-structured queries and reports enhance usability; establishing their use in everyday clinical settings requires further simplification with a browser based interface which is currently under development.

Splitting statistical potentials into meaningful scoring functions: testing the prediction of near-native structures from decoy conformations

Background: Recent advances on high-throughput technologies have produced a vast amount of protein sequences, while the number of high-resolution structures has seen a limited increase. This has impelled the production of many strategies to built protein structures from its sequence, generating a considerable amount of alternative models. The selection of the closest model to the native conformation has thus become crucial for structure prediction. Several methods have been developed to score protein models by energies, knowledge-based potentials and combination of both.Results: Here, we present and demonstrate a theory to split the knowledge-based potentials in scoring terms biologically meaningful and to combine them in new scores to predict near-native structures. Our strategy allows circumventing the problem of defining the reference state. In this approach we give the proof for a simple and linear application that can be further improved by optimizing the combination of Zscores. Using the simplest composite score () we obtained predictions similar to state-of-the-art methods. Besides, our approach has the advantage of identifying the most relevant terms involved in the stability of the protein structure. Finally, we also use the composite Zscores to assess the conformation of models and to detect local errors.Conclusion: We have introduced a method to split knowledge-based potentials and to solve the problem of defining a reference state. The new scores have detected near-native structures as accurately as state-of-art methods and have been successful to identify wrongly modeled regions of many near-native conformations.

A two-stage approach for tonic identification in indian art music

In this paper we propose a new approach for tonic identification in Indian art music and present a proposal for acomplete iterative system for the same. Our method splits the task of tonic pitch identification into two stages. In the first stage, which is applicable to both vocal and instrumental music, we perform a multi-pitch analysis of the audio signal to identify the tonic pitch-class. Multi-pitch analysisallows us to take advantage of the drone sound, which constantlyreinforces the tonic. In the second stage we estimate the octave in which the tonic of the singer lies and is thusneeded only for the vocal performances. We analyse the predominant melody sung by the lead performer in order to establish the tonic octave. Both stages are individually evaluated on a sizable music collection and are shown toobtain a good accuracy. We also discuss the types of errors made by the method.Further, we present a proposal for a system that aims to incrementally utilize all the available data, both audio and metadata in order to identify the tonic pitch. It produces a tonic estimate and a confidence value, and is iterative in nature. At each iteration, more data is fed into the systemuntil the confidence value for the identified tonic is above a defined threshold. Rather than obtain high overall accuracy for our complete database, ultimately our goal is to develop a system which obtains very high accuracy on a subset of the database with maximum confidence.

A method for extracting semantic information from on-line art music discussion forums

In this paper a method for extracting semantic informationfrom online music discussion forums is proposed. The semantic relations are inferred from the co-occurrence of musical concepts in forum posts, using network analysis. The method starts by defining a dictionary of common music terms in an art music tradition. Then, it creates a complex network representation of the online forum by matchingsuch dictionary against the forum posts. Once the complex network is built we can study different network measures, including node relevance, node co-occurrence andterm relations via semantically connecting words. Moreover, we can detect communities of concepts inside the forum posts. The rationale is that some music terms are more related to each other than to other terms. All in all, this methodology allows us to obtain meaningful and relevantinformation from forum discussions.

Discourse, knowledge, power and politics: towards critical epistemic discourse analysis

Although both are fundamental terms in the humanities and social sciences, discourse and knowledge have seldom been explicitly related, and even less so in critical discourse studies. After a brief summary of what we know about these relationships in linguistics, psychology, epistemology and the social sciences, with special emphasis on the role of knowledge in the formation of mental models as a basis for discourse, I examine in more detail how a critical study of discourse and knowledge may be articulated in critical discourse studies. Thus, several areas of critical epistemic discourse analysis are identified, and then applied in a study of Tony Blair’s Iraq speech on March 18, 2003, in which he sought to legitimatize his decision to go to war in Iraq with George Bush. The analysis shows the various modes of how knowledge is managed and manipulated of all levels of discourse of this speech.

"Pollock broke the ice": la idea d'art nord-americà en el temps de la Guerra Freda. Reflexions sobre Jackson Pollock.

Les avantguardes mostren la deshumanització i la violència de la primera Gran Guerra i del món que va néixer com a conseqüència. La fi de la Segona Guerra va donar pas a un món dividit on dues potències enfrontades pretenien ser el referent mundial, tant en àmbits polítics com en els culturals.L’objecte d’aquest treball és la transformació de la pintura nord-americana des d’inicis dels anys 30 fins als 60, un gir promogut pels crítics d’art en resposta a una pintura concreta: la de l’Expressionisme Abstracte.

Art i part :la figura del/la professional de l'educació social en processos de desenvolupament cultural comunitari

Anàlisi de la figura de l'educador/a social en processos de desenvolupament comunitari a partir d'experiències diverses a Catalunya

Iterated local search

Iterated Local Search has many of the desirable features of a metaheuristic: it is simple, easy to implement, robust, and highly effective. The essential idea of Iterated Local Search lies in focusing the search not on the full space of solutions but on a smaller subspace defined by the solutions that are locally optimal for a given optimization engine. The success of Iterated Local Search lies in the biased sampling of this set of local optima. How effective this approach turns out to be depends mainly on the choice of the local search, the perturbations, and the acceptance criterion. So far, in spite of its conceptual simplicity, it has lead to a number of state-of-the-art results without the use of too much problem-specific knowledge. But with further work so that the different modules are well adapted to the problem at hand, Iterated Local Search can often become a competitive or even state of the artalgorithm. The purpose of this review is both to give a detailed description of this metaheuristic and to show where it stands in terms of performance.

Approximate knowledge of rationality and correlated equilibria

We extend Aumann's theorem [Aumann 1987], deriving correlated equilibria as a consequence of common priors and common knowledge of rationality, by explicitly allowing for non-rational behavior. Wereplace the assumption of common knowledge of rationality with a substantially weaker one, joint p-belief of rationality, where agents believe the other agents are rational with probability p or more. We show that behavior in this case constitutes a kind of correlated equilibrium satisfying certain p-belief constraints, and that it varies continuously in the parameters p and, for p sufficiently close to one,with high probability is supported on strategies that survive the iterated elimination of strictly dominated strategies. Finally, we extend the analysis to characterizing rational expectations of interimtypes, to games of incomplete information, as well as to the case of non-common priors.

Shared knowledge

Agents use their knowledge on the history of the economy in orderto choose what is the optimal action to take at any given moment of time,but each individual observes history with some noise. This paper showsthat the amount of information available on the past evolution of theeconomy is an endogenous variable, and that this leads to overconcentrationof the investment, which can be interpreted as underinvestment in research.It presents a model in which agents have to invest at each period in one of$K$ sectors, each of them paying an exogenous return that follows a welldefined stochastic path. At any moment of time each agent receives an unbiasednoisy signal on the payoff of each sector. The signals differ across agents,but all of them have the same variance, which depends on the aggregate investmentin that particular sector (so that if almost everybody invests in it theperceptions of everybody will be very accurate, but if almost nobody doesthe perceptions of everybody will be very noisy). The degree of hetereogeneityacross agents is then an endogenous variable, evolving across time determining,and being determined by, the amount of information disclosed.As long as both the level of social interaction and the underlying precisionof the observations are relatively large agents behave in a very preciseway. This behavior is unmodified for a huge range of informational parameters,and it is characterized by an excessive concentration of the investment ina few sectors. Additionally the model shows that generalized improvements in thequality of the information that each agent gets may lead to a worse outcomefor all the agents due to the overconcentration of the investment that thisproduces.