576 resultados para schema,


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Early phase clinical trial designs have long been the focus of interest for clinicians and statisticians working in oncology field. There are several standard phse I and phase II designs that have been widely-implemented in medical practice. For phase I design, the most commonly used methods are 3+3 and CRM. A newly-developed Bayesian model-based mTPI design has now been used by an increasing number of hospitals and pharmaceutical companies. The advantages and disadvantages of these three top phase I designs have been discussed in my work here and their performances were compared using simulated data. It was shown that mTPI design exhibited superior performance in most scenarios in comparison with 3+3 and CRM designs. ^ The next major part of my work is proposing an innovative seamless phase I/II design that allows clinicians to conduct phase I and phase II clinical trials simultaneously. Bayesian framework was implemented throughout the whole design. The phase I portion of the design adopts mTPI method, with the addition of futility rule which monitors the efficacy performance of the tested drugs. Dose graduation rules were proposed in this design to allow doses move forward from phase I portion of the study to phase II portion without interrupting the ongoing phase I dose-finding schema. Once a dose graduated to phase II, adaptive randomization was used to randomly allocated patients into different treatment arms, with the intention of more patients being assigned to receive more promising dose(s). Again simulations were performed to compare the performance of this innovative phase I/II design with a recently published phase I/II design, together with the conventional phase I and phase II designs. The simulation results indicated that the seamless phase I/II design outperform the other two competing methods in most scenarios, with superior trial power and the fact that it requires smaller sample size. It also significantly reduces the overall study time. ^ Similar to other early phase clinical trial designs, the proposed seamless phase I/II design requires that the efficacy and safety outcomes being able to be observed in a short time frame. This limitation can be overcome by using validated surrogate marker for the efficacy and safety endpoints.^

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Background: The failure rate of health information systems is high, partially due to fragmented, incomplete, or incorrect identification and description of specific and critical domain requirements. In order to systematically transform the requirements of work into real information system, an explicit conceptual framework is essential to summarize the work requirements and guide system design. Recently, Butler, Zhang, and colleagues proposed a conceptual framework called Work Domain Ontology (WDO) to formally represent users’ work. This WDO approach has been successfully demonstrated in a real world design project on aircraft scheduling. However, as a top level conceptual framework, this WDO has not defined an explicit and well specified schema (WDOS) , and it does not have a generalizable and operationalized procedure that can be easily applied to develop WDO. Moreover, WDO has not been developed for any concrete healthcare domain. These limitations hinder the utility of WDO in real world information system in general and in health information system in particular. Objective: The objective of this research is to formalize the WDOS, operationalize a procedure to develop WDO, and evaluate WDO approach using Self-Nutrition Management (SNM) work domain. Method: Concept analysis was implemented to formalize WDOS. Focus group interview was conducted to capture concepts in SNM work domain. Ontology engineering methods were adopted to model SNM WDO. Part of the concepts under the primary goal “staying healthy” for SNM were selected and transformed into a semi-structured survey to evaluate the acceptance, explicitness, completeness, consistency, experience dependency of SNM WDO. Result: Four concepts, “goal, operation, object and constraint”, were identified and formally modeled in WDOS with definitions and attributes. 72 SNM WDO concepts under primary goal were selected and transformed into semi-structured survey questions. The evaluation indicated that the major concepts of SNM WDO were accepted by 41 overweight subjects. SNM WDO is generally independent of user domain experience but partially dependent on SNM application experience. 23 of 41 paired concepts had significant correlations. Two concepts were identified as ambiguous concepts. 8 extra concepts were recommended towards the completeness of SNM WDO. Conclusion: The preliminary WDOS is ready with an operationalized procedure. SNM WDO has been developed to guide future SNM application design. This research is an essential step towards Work-Centered Design (WCD).

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The importance of treatment fidelity in evaluations of all human service programs, including intensive family preservation services (IFPS), is examined in this article. Special attention is focused on the issue of treatment fidelity in IFPS programs attempting to adhere to a specific program model (Homebuilders©), and on the problems that lack of treatment fidelity has caused for research that has been conducted on this and other program models. Attempts to address the issue of treatment fidelity in other program areas offer models for constructing treatment fidelity assessment tools for IFPS. The authors suggest a schema for assessing treatment fidelity in evaluations of IFPS programs that should help to explore relationships among different approaches to IFPS, the consistency with which they are being implemented, and the outcomes that result.

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Enrique Pichon-Rivière (1907-1977) fue uno de los fundadores de la psicología social en Argentina. En este trabajo revisaremos su biografía y trayectoria institucional junto con sus aportes teóricos y epistemológicos. Sostenemos que Enrique Pichon-Rivière dio muestra de una actitud crítica con respecto a las divisiones disciplinares y a la distancia entre conocimiento académico y praxis social. Nuestro recorte privilegiará aquellos aspectos de su obra que consideramos de mayor relevancia para las ciencias sociales, incluyendo sus nociones de necesidad social, matrices de aprendizaje, esquema conceptual referencial operativo (E.C.R.O.) y epistemología convergente

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Enrique Pichon-Rivière (1907-1977) fue uno de los fundadores de la psicología social en Argentina. En este trabajo revisaremos su biografía y trayectoria institucional junto con sus aportes teóricos y epistemológicos. Sostenemos que Enrique Pichon-Rivière dio muestra de una actitud crítica con respecto a las divisiones disciplinares y a la distancia entre conocimiento académico y praxis social. Nuestro recorte privilegiará aquellos aspectos de su obra que consideramos de mayor relevancia para las ciencias sociales, incluyendo sus nociones de necesidad social, matrices de aprendizaje, esquema conceptual referencial operativo (E.C.R.O.) y epistemología convergente

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Enrique Pichon-Rivière (1907-1977) fue uno de los fundadores de la psicología social en Argentina. En este trabajo revisaremos su biografía y trayectoria institucional junto con sus aportes teóricos y epistemológicos. Sostenemos que Enrique Pichon-Rivière dio muestra de una actitud crítica con respecto a las divisiones disciplinares y a la distancia entre conocimiento académico y praxis social. Nuestro recorte privilegiará aquellos aspectos de su obra que consideramos de mayor relevancia para las ciencias sociales, incluyendo sus nociones de necesidad social, matrices de aprendizaje, esquema conceptual referencial operativo (E.C.R.O.) y epistemología convergente

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Gelegentlich einer Diskussion über die Perioden der Polarlichterscheinungen und damit in Zusammenhang stehender Phänomene wurde die Meinung geäußert, daß die in verschiedenen Arbeiten abgeleiteten Perioden (insbesondere der Jahresgang der Nordlichthäufigkeit) möglicherweise nur örtlichen Charakter haben. Ich sah mich daher veranlaßt, bevor ich an eine zusammenfassende Darstellung des aus verschiedenen Gegenden der Nord- und Süd-Halbkugel stammenden Materials gehe, noch die aus Island und den Faer Oern vorliegenden Beobachtungen gesondert zu behandeln. Da die Bearbeitung nach dem gleichen Schema erfolgen kann wie die von mir in der "Polarforschung", Jahrgang 1948, veröffentlichte Arbeit über die in Grönland beobachteten Nordlichter, soll sie hier in stichwortartiger Kürze wiedergegeben werden.

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Die in den Ablagerungen des marinen Elster-Saale-Interglazials (= Holstein-See = Stör-Meer) gefundenen und als autochthon betrachteten Foraminiferen und Ostrakoden kommen alle noch rezent vor. In vielen Proben wurden daneben aus dem Tertiär und der Oberkreide aufgearbeitete Foraminiferen gefunden. In den Proben aus Muldsberg, Albersdorf und Esbjerg konnte eine gleichgerichtete Faunen-veränderung vom Liegenden zum Hangenden beobachtet werden. Die Formen der jeweils unteren Proben gehören subarktischen bis hochborealen Temperaturen, etwa vollmarinem Milieu und mindestens 30 m Wassertiefe an. Ins Hangende hinein wurde nach Foraminiferen und Ostrakoden das Meer flacher, wärmer und brackischer, bis es schließlich in den obersten Proben wattähnliche Verhältnisse mit wahrscheinlich etwas geringerer Temperatur als am heutigen südlichen Nordseerand erreichte. Diese Beobachtung stimmt überein mit den von GRAHLE (1936) an Mollusken gewonnenen Erkenntnissen und den Schlüssen, die andere Bearbeiter aus einzelnen Mikrofaunen zogen. Es wurde versucht, die Faunen der restlichen Aufschlüsse in das oben erwähnte Schema einzuordnen. Dies gelang nur in zwei Fällen nicht. In Oldenhütten ist das Versagen wahrscheinlich auf unentwirrte Lagerungsstörungen zurückzuführen, in der Austernbank Tarbek liegen abweichende fazielle Verhältnisse vor. Die restlichen Aufschlüsse zeigen, daß aus den vom Eis gestörten Sedimenten doch oft ein sinnvolles Bild rekonstruiert werden kann. Die im kälteren Teil der Holstein-See auftretende Foraminifere Elphidium subarcticum CUSHMAN scheint in den Absätzen des schleswig-holsteinischen Eem-Meeres zu fehlen.

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In this paper, we describe a complete development platform that features different innovative acceleration strategies, not included in any other current platform, that simplify and speed up the definition of the different elements required to design a spoken dialog service. The proposed accelerations are mainly based on using the information from the backend database schema and contents, as well as cumulative information produced throughout the different steps in the design. Thanks to these accelerations, the interaction between the designer and the platform is improved, and in most cases the design is reduced to simple confirmations of the “proposals” that the platform dynamically provides at each step. In addition, the platform provides several other accelerations such as configurable templates that can be used to define the different tasks in the service or the dialogs to obtain or show information to the user, automatic proposals for the best way to request slot contents from the user (i.e. using mixed-initiative forms or directed forms), an assistant that offers the set of more probable actions required to complete the definition of the different tasks in the application, or another assistant for solving specific modality details such as confirmations of user answers or how to present them the lists of retrieved results after querying the backend database. Additionally, the platform also allows the creation of speech grammars and prompts, database access functions, and the possibility of using mixed initiative and over-answering dialogs. In the paper we also describe in detail each assistant in the platform, emphasizing the different kind of methodologies followed to facilitate the design process at each one. Finally, we describe the results obtained in both a subjective and an objective evaluation with different designers that confirm the viability, usefulness, and functionality of the proposed accelerations. Thanks to the accelerations, the design time is reduced in more than 56% and the number of keystrokes by 84%.

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OntoTag - A Linguistic and Ontological Annotation Model Suitable for the Semantic Web 1. INTRODUCTION. LINGUISTIC TOOLS AND ANNOTATIONS: THEIR LIGHTS AND SHADOWS Computational Linguistics is already a consolidated research area. It builds upon the results of other two major ones, namely Linguistics and Computer Science and Engineering, and it aims at developing computational models of human language (or natural language, as it is termed in this area). Possibly, its most well-known applications are the different tools developed so far for processing human language, such as machine translation systems and speech recognizers or dictation programs. These tools for processing human language are commonly referred to as linguistic tools. Apart from the examples mentioned above, there are also other types of linguistic tools that perhaps are not so well-known, but on which most of the other applications of Computational Linguistics are built. These other types of linguistic tools comprise POS taggers, natural language parsers and semantic taggers, amongst others. All of them can be termed linguistic annotation tools. Linguistic annotation tools are important assets. In fact, POS and semantic taggers (and, to a lesser extent, also natural language parsers) have become critical resources for the computer applications that process natural language. Hence, any computer application that has to analyse a text automatically and ‘intelligently’ will include at least a module for POS tagging. The more an application needs to ‘understand’ the meaning of the text it processes, the more linguistic tools and/or modules it will incorporate and integrate. However, linguistic annotation tools have still some limitations, which can be summarised as follows: 1. Normally, they perform annotations only at a certain linguistic level (that is, Morphology, Syntax, Semantics, etc.). 2. They usually introduce a certain rate of errors and ambiguities when tagging. This error rate ranges from 10 percent up to 50 percent of the units annotated for unrestricted, general texts. 3. Their annotations are most frequently formulated in terms of an annotation schema designed and implemented ad hoc. A priori, it seems that the interoperation and the integration of several linguistic tools into an appropriate software architecture could most likely solve the limitations stated in (1). Besides, integrating several linguistic annotation tools and making them interoperate could also minimise the limitation stated in (2). Nevertheless, in the latter case, all these tools should produce annotations for a common level, which would have to be combined in order to correct their corresponding errors and inaccuracies. Yet, the limitation stated in (3) prevents both types of integration and interoperation from being easily achieved. In addition, most high-level annotation tools rely on other lower-level annotation tools and their outputs to generate their own ones. For example, sense-tagging tools (operating at the semantic level) often use POS taggers (operating at a lower level, i.e., the morphosyntactic) to identify the grammatical category of the word or lexical unit they are annotating. Accordingly, if a faulty or inaccurate low-level annotation tool is to be used by other higher-level one in its process, the errors and inaccuracies of the former should be minimised in advance. Otherwise, these errors and inaccuracies would be transferred to (and even magnified in) the annotations of the high-level annotation tool. Therefore, it would be quite useful to find a way to (i) correct or, at least, reduce the errors and the inaccuracies of lower-level linguistic tools; (ii) unify the annotation schemas of different linguistic annotation tools or, more generally speaking, make these tools (as well as their annotations) interoperate. Clearly, solving (i) and (ii) should ease the automatic annotation of web pages by means of linguistic tools, and their transformation into Semantic Web pages (Berners-Lee, Hendler and Lassila, 2001). Yet, as stated above, (ii) is a type of interoperability problem. There again, ontologies (Gruber, 1993; Borst, 1997) have been successfully applied thus far to solve several interoperability problems. Hence, ontologies should help solve also the problems and limitations of linguistic annotation tools aforementioned. Thus, to summarise, the main aim of the present work was to combine somehow these separated approaches, mechanisms and tools for annotation from Linguistics and Ontological Engineering (and the Semantic Web) in a sort of hybrid (linguistic and ontological) annotation model, suitable for both areas. This hybrid (semantic) annotation model should (a) benefit from the advances, models, techniques, mechanisms and tools of these two areas; (b) minimise (and even solve, when possible) some of the problems found in each of them; and (c) be suitable for the Semantic Web. The concrete goals that helped attain this aim are presented in the following section. 2. GOALS OF THE PRESENT WORK As mentioned above, the main goal of this work was to specify a hybrid (that is, linguistically-motivated and ontology-based) model of annotation suitable for the Semantic Web (i.e. it had to produce a semantic annotation of web page contents). This entailed that the tags included in the annotations of the model had to (1) represent linguistic concepts (or linguistic categories, as they are termed in ISO/DCR (2008)), in order for this model to be linguistically-motivated; (2) be ontological terms (i.e., use an ontological vocabulary), in order for the model to be ontology-based; and (3) be structured (linked) as a collection of ontology-based triples, as in the usual Semantic Web languages (namely RDF(S) and OWL), in order for the model to be considered suitable for the Semantic Web. Besides, to be useful for the Semantic Web, this model should provide a way to automate the annotation of web pages. As for the present work, this requirement involved reusing the linguistic annotation tools purchased by the OEG research group (http://www.oeg-upm.net), but solving beforehand (or, at least, minimising) some of their limitations. Therefore, this model had to minimise these limitations by means of the integration of several linguistic annotation tools into a common architecture. Since this integration required the interoperation of tools and their annotations, ontologies were proposed as the main technological component to make them effectively interoperate. From the very beginning, it seemed that the formalisation of the elements and the knowledge underlying linguistic annotations within an appropriate set of ontologies would be a great step forward towards the formulation of such a model (henceforth referred to as OntoTag). Obviously, first, to combine the results of the linguistic annotation tools that operated at the same level, their annotation schemas had to be unified (or, preferably, standardised) in advance. This entailed the unification (id. standardisation) of their tags (both their representation and their meaning), and their format or syntax. Second, to merge the results of the linguistic annotation tools operating at different levels, their respective annotation schemas had to be (a) made interoperable and (b) integrated. And third, in order for the resulting annotations to suit the Semantic Web, they had to be specified by means of an ontology-based vocabulary, and structured by means of ontology-based triples, as hinted above. Therefore, a new annotation scheme had to be devised, based both on ontologies and on this type of triples, which allowed for the combination and the integration of the annotations of any set of linguistic annotation tools. This annotation scheme was considered a fundamental part of the model proposed here, and its development was, accordingly, another major objective of the present work. All these goals, aims and objectives could be re-stated more clearly as follows: Goal 1: Development of a set of ontologies for the formalisation of the linguistic knowledge relating linguistic annotation. Sub-goal 1.1: Ontological formalisation of the EAGLES (1996a; 1996b) de facto standards for morphosyntactic and syntactic annotation, in a way that helps respect the triple structure recommended for annotations in these works (which is isomorphic to the triple structures used in the context of the Semantic Web). Sub-goal 1.2: Incorporation into this preliminary ontological formalisation of other existing standards and standard proposals relating the levels mentioned above, such as those currently under development within ISO/TC 37 (the ISO Technical Committee dealing with Terminology, which deals also with linguistic resources and annotations). Sub-goal 1.3: Generalisation and extension of the recommendations in EAGLES (1996a; 1996b) and ISO/TC 37 to the semantic level, for which no ISO/TC 37 standards have been developed yet. Sub-goal 1.4: Ontological formalisation of the generalisations and/or extensions obtained in the previous sub-goal as generalisations and/or extensions of the corresponding ontology (or ontologies). Sub-goal 1.5: Ontological formalisation of the knowledge required to link, combine and unite the knowledge represented in the previously developed ontology (or ontologies). Goal 2: Development of OntoTag’s annotation scheme, a standard-based abstract scheme for the hybrid (linguistically-motivated and ontological-based) annotation of texts. Sub-goal 2.1: Development of the standard-based morphosyntactic annotation level of OntoTag’s scheme. This level should include, and possibly extend, the recommendations of EAGLES (1996a) and also the recommendations included in the ISO/MAF (2008) standard draft. Sub-goal 2.2: Development of the standard-based syntactic annotation level of the hybrid abstract scheme. This level should include, and possibly extend, the recommendations of EAGLES (1996b) and the ISO/SynAF (2010) standard draft. Sub-goal 2.3: Development of the standard-based semantic annotation level of OntoTag’s (abstract) scheme. Sub-goal 2.4: Development of the mechanisms for a convenient integration of the three annotation levels already mentioned. These mechanisms should take into account the recommendations included in the ISO/LAF (2009) standard draft. Goal 3: Design of OntoTag’s (abstract) annotation architecture, an abstract architecture for the hybrid (semantic) annotation of texts (i) that facilitates the integration and interoperation of different linguistic annotation tools, and (ii) whose results comply with OntoTag’s annotation scheme. Sub-goal 3.1: Specification of the decanting processes that allow for the classification and separation, according to their corresponding levels, of the results of the linguistic tools annotating at several different levels. Sub-goal 3.2: Specification of the standardisation processes that allow (a) complying with the standardisation requirements of OntoTag’s annotation scheme, as well as (b) combining the results of those linguistic tools that share some level of annotation. Sub-goal 3.3: Specification of the merging processes that allow for the combination of the output annotations and the interoperation of those linguistic tools that share some level of annotation. Sub-goal 3.4: Specification of the merge processes that allow for the integration of the results and the interoperation of those tools performing their annotations at different levels. Goal 4: Generation of OntoTagger’s schema, a concrete instance of OntoTag’s abstract scheme for a concrete set of linguistic annotations. These linguistic annotations result from the tools and the resources available in the research group, namely • Bitext’s DataLexica (http://www.bitext.com/EN/datalexica.asp), • LACELL’s (POS) tagger (http://www.um.es/grupos/grupo-lacell/quees.php), • Connexor’s FDG (http://www.connexor.eu/technology/machinese/glossary/fdg/), and • EuroWordNet (Vossen et al., 1998). This schema should help evaluate OntoTag’s underlying hypotheses, stated below. Consequently, it should implement, at least, those levels of the abstract scheme dealing with the annotations of the set of tools considered in this implementation. This includes the morphosyntactic, the syntactic and the semantic levels. Goal 5: Implementation of OntoTagger’s configuration, a concrete instance of OntoTag’s abstract architecture for this set of linguistic tools and annotations. This configuration (1) had to use the schema generated in the previous goal; and (2) should help support or refute the hypotheses of this work as well (see the next section). Sub-goal 5.1: Implementation of the decanting processes that facilitate the classification and separation of the results of those linguistic resources that provide annotations at several different levels (on the one hand, LACELL’s tagger operates at the morphosyntactic level and, minimally, also at the semantic level; on the other hand, FDG operates at the morphosyntactic and the syntactic levels and, minimally, at the semantic level as well). Sub-goal 5.2: Implementation of the standardisation processes that allow (i) specifying the results of those linguistic tools that share some level of annotation according to the requirements of OntoTagger’s schema, as well as (ii) combining these shared level results. In particular, all the tools selected perform morphosyntactic annotations and they had to be conveniently combined by means of these processes. Sub-goal 5.3: Implementation of the merging processes that allow for the combination (and possibly the improvement) of the annotations and the interoperation of the tools that share some level of annotation (in particular, those relating the morphosyntactic level, as in the previous sub-goal). Sub-goal 5.4: Implementation of the merging processes that allow for the integration of the different standardised and combined annotations aforementioned, relating all the levels considered. Sub-goal 5.5: Improvement of the semantic level of this configuration by adding a named entity recognition, (sub-)classification and annotation subsystem, which also uses the named entities annotated to populate a domain ontology, in order to provide a concrete application of the present work in the two areas involved (the Semantic Web and Corpus Linguistics). 3. MAIN RESULTS: ASSESSMENT OF ONTOTAG’S UNDERLYING HYPOTHESES The model developed in the present thesis tries to shed some light on (i) whether linguistic annotation tools can effectively interoperate; (ii) whether their results can be combined and integrated; and, if they can, (iii) how they can, respectively, interoperate and be combined and integrated. Accordingly, several hypotheses had to be supported (or rejected) by the development of the OntoTag model and OntoTagger (its implementation). The hypotheses underlying OntoTag are surveyed below. Only one of the hypotheses (H.6) was rejected; the other five could be confirmed. H.1 The annotations of different levels (or layers) can be integrated into a sort of overall, comprehensive, multilayer and multilevel annotation, so that their elements can complement and refer to each other. • CONFIRMED by the development of: o OntoTag’s annotation scheme, o OntoTag’s annotation architecture, o OntoTagger’s (XML, RDF, OWL) annotation schemas, o OntoTagger’s configuration. H.2 Tool-dependent annotations can be mapped onto a sort of tool-independent annotations and, thus, can be standardised. • CONFIRMED by means of the standardisation phase incorporated into OntoTag and OntoTagger for the annotations yielded by the tools. H.3 Standardisation should ease: H.3.1: The interoperation of linguistic tools. H.3.2: The comparison, combination (at the same level and layer) and integration (at different levels or layers) of annotations. • H.3 was CONFIRMED by means of the development of OntoTagger’s ontology-based configuration: o Interoperation, comparison, combination and integration of the annotations of three different linguistic tools (Connexor’s FDG, Bitext’s DataLexica and LACELL’s tagger); o Integration of EuroWordNet-based, domain-ontology-based and named entity annotations at the semantic level. o Integration of morphosyntactic, syntactic and semantic annotations. H.4 Ontologies and Semantic Web technologies (can) play a crucial role in the standardisation of linguistic annotations, by providing consensual vocabularies and standardised formats for annotation (e.g., RDF triples). • CONFIRMED by means of the development of OntoTagger’s RDF-triple-based annotation schemas. H.5 The rate of errors introduced by a linguistic tool at a given level, when annotating, can be reduced automatically by contrasting and combining its results with the ones coming from other tools, operating at the same level. However, these other tools might be built following a different technological (stochastic vs. rule-based, for example) or theoretical (dependency vs. HPS-grammar-based, for instance) approach. • CONFIRMED by the results yielded by the evaluation of OntoTagger. H.6 Each linguistic level can be managed and annotated independently. • REJECTED: OntoTagger’s experiments and the dependencies observed among the morphosyntactic annotations, and between them and the syntactic annotations. In fact, Hypothesis H.6 was already rejected when OntoTag’s ontologies were developed. We observed then that several linguistic units stand on an interface between levels, belonging thereby to both of them (such as morphosyntactic units, which belong to both the morphological level and the syntactic level). Therefore, the annotations of these levels overlap and cannot be handled independently when merged into a unique multileveled annotation. 4. OTHER MAIN RESULTS AND CONTRIBUTIONS First, interoperability is a hot topic for both the linguistic annotation community and the whole Computer Science field. The specification (and implementation) of OntoTag’s architecture for the combination and integration of linguistic (annotation) tools and annotations by means of ontologies shows a way to make these different linguistic annotation tools and annotations interoperate in practice. Second, as mentioned above, the elements involved in linguistic annotation were formalised in a set (or network) of ontologies (OntoTag’s linguistic ontologies). • On the one hand, OntoTag’s network of ontologies consists of − The Linguistic Unit Ontology (LUO), which includes a mostly hierarchical formalisation of the different types of linguistic elements (i.e., units) identifiable in a written text; − The Linguistic Attribute Ontology (LAO), which includes also a mostly hierarchical formalisation of the different types of features that characterise the linguistic units included in the LUO; − The Linguistic Value Ontology (LVO), which includes the corresponding formalisation of the different values that the attributes in the LAO can take; − The OIO (OntoTag’s Integration Ontology), which  Includes the knowledge required to link, combine and unite the knowledge represented in the LUO, the LAO and the LVO;  Can be viewed as a knowledge representation ontology that describes the most elementary vocabulary used in the area of annotation. • On the other hand, OntoTag’s ontologies incorporate the knowledge included in the different standards and recommendations for linguistic annotation released so far, such as those developed within the EAGLES and the SIMPLE European projects or by the ISO/TC 37 committee: − As far as morphosyntactic annotations are concerned, OntoTag’s ontologies formalise the terms in the EAGLES (1996a) recommendations and their corresponding terms within the ISO Morphosyntactic Annotation Framework (ISO/MAF, 2008) standard; − As for syntactic annotations, OntoTag’s ontologies incorporate the terms in the EAGLES (1996b) recommendations and their corresponding terms within the ISO Syntactic Annotation Framework (ISO/SynAF, 2010) standard draft; − Regarding semantic annotations, OntoTag’s ontologies generalise and extend the recommendations in EAGLES (1996a; 1996b) and, since no stable standards or standard drafts have been released for semantic annotation by ISO/TC 37 yet, they incorporate the terms in SIMPLE (2000) instead; − The terms coming from all these recommendations and standards were supplemented by those within the ISO Data Category Registry (ISO/DCR, 2008) and also of the ISO Linguistic Annotation Framework (ISO/LAF, 2009) standard draft when developing OntoTag’s ontologies. Third, we showed that the combination of the results of tools annotating at the same level can yield better results (both in precision and in recall) than each tool separately. In particular, 1. OntoTagger clearly outperformed two of the tools integrated into its configuration, namely DataLexica and FDG in all the combination sub-phases in which they overlapped (i.e. POS tagging, lemma annotation and morphological feature annotation). As far as the remaining tool is concerned, i.e. LACELL’s tagger, it was also outperformed by OntoTagger in POS tagging and lemma annotation, and it did not behave better than OntoTagger in the morphological feature annotation layer. 2. As an immediate result, this implies that a) This type of combination architecture configurations can be applied in order to improve significantly the accuracy of linguistic annotations; and b) Concerning the morphosyntactic level, this could be regarded as a way of constructing more robust and more accurate POS tagging systems. Fourth, Semantic Web annotations are usually performed by humans or else by machine learning systems. Both of them leave much to be desired: the former, with respect to their annotation rate; the latter, with respect to their (average) precision and recall. In this work, we showed how linguistic tools can be wrapped in order to annotate automatically Semantic Web pages using ontologies. This entails their fast, robust and accurate semantic annotation. As a way of example, as mentioned in Sub-goal 5.5, we developed a particular OntoTagger module for the recognition, classification and labelling of named entities, according to the MUC and ACE tagsets (Chinchor, 1997; Doddington et al., 2004). These tagsets were further specified by means of a domain ontology, namely the Cinema Named Entities Ontology (CNEO). This module was applied to the automatic annotation of ten different web pages containing cinema reviews (that is, around 5000 words). In addition, the named entities annotated with this module were also labelled as instances (or individuals) of the classes included in the CNEO and, then, were used to populate this domain ontology. • The statistical results obtained from the evaluation of this particular module of OntoTagger can be summarised as follows. On the one hand, as far as recall (R) is concerned, (R.1) the lowest value was 76,40% (for file 7); (R.2) the highest value was 97, 50% (for file 3); and (R.3) the average value was 88,73%. On the other hand, as far as the precision rate (P) is concerned, (P.1) its minimum was 93,75% (for file 4); (R.2) its maximum was 100% (for files 1, 5, 7, 8, 9, and 10); and (R.3) its average value was 98,99%. • These results, which apply to the tasks of named entity annotation and ontology population, are extraordinary good for both of them. They can be explained on the basis of the high accuracy of the annotations provided by OntoTagger at the lower levels (mainly at the morphosyntactic level). However, they should be conveniently qualified, since they might be too domain- and/or language-dependent. It should be further experimented how our approach works in a different domain or a different language, such as French, English, or German. • In any case, the results of this application of Human Language Technologies to Ontology Population (and, accordingly, to Ontological Engineering) seem very promising and encouraging in order for these two areas to collaborate and complement each other in the area of semantic annotation. Fifth, as shown in the State of the Art of this work, there are different approaches and models for the semantic annotation of texts, but all of them focus on a particular view of the semantic level. Clearly, all these approaches and models should be integrated in order to bear a coherent and joint semantic annotation level. OntoTag shows how (i) these semantic annotation layers could be integrated together; and (ii) they could be integrated with the annotations associated to other annotation levels. Sixth, we identified some recommendations, best practices and lessons learned for annotation standardisation, interoperation and merge. They show how standardisation (via ontologies, in this case) enables the combination, integration and interoperation of different linguistic tools and their annotations into a multilayered (or multileveled) linguistic annotation, which is one of the hot topics in the area of Linguistic Annotation. And last but not least, OntoTag’s annotation scheme and OntoTagger’s annotation schemas show a way to formalise and annotate coherently and uniformly the different units and features associated to the different levels and layers of linguistic annotation. This is a great scientific step ahead towards the global standardisation of this area, which is the aim of ISO/TC 37 (in particular, Subcommittee 4, dealing with the standardisation of linguistic annotations and resources).

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Esta tesis realiza una contribución metodológica en el estudio de medidas de adaptación potencialmente adecuadas a largo plazo, donde los sistemas de recursos hídricos experimentan fuertes presiones debido a los efectos del cambio climático. Esta metodología integra el análisis físico del sistema, basándose en el uso de indicadores que valoran el comportamiento de éste, y el análisis económico mediante el uso del valor del agua. El procedimiento metodológico inicia con la construcción de un conjunto de escenarios futuros, que capturan por un lado las características de variabilidad de las aportaciones de diversos modelos climáticos y, por otro, las características hidrológicas de la zona de estudio. Las zonas de estudio seleccionadas fueron las cuencas del Guadalquivir, Duero y Ebro y se utilizaron como datos observados las series de escorrentía en régimen natural estimadas por el modelo SIMPA que está calibrado en la totalidad del territorio español. Estas series observadas corresponden al periodo 1961-1990. Los escenarios futuros construidos representan el periodo 2071-2100. La identificación de medidas de adaptación se apoyó en el uso de indicadores que sean capaces de caracterizar el comportamiento de un sistema de recursos hídricos frente a los efectos del cambio climático. Para ello se seleccionaron los indicadores de calidad de servicio (I1) y de confiabilidad de la demanda (I2) propuestos por Martin-Carrasco et al. (2012). Estos indicadores valoran el comportamiento de un sistema mediante la identificación de los problemas de escasez de agua que presente, y requieren para su cuantificación el uso de un modelo de optimización. Para este estudio se ha trabajado con el modelo de optimización OPTIGES. La determinación de estos indicadores fue realizada para análisis a corto plazo donde los efectos del cambio climático no son de relevancia, por lo que fue necesario analizar su capacidad para ser usados en sistemas afectados por dichos efectos. Para este análisis se seleccionaron tres cuencas españolas: Guadalquivir, Duero y Ebro, determinándose que I2 no es adecuado para este tipo de escenarios. Por ello se propuso un nuevo indicador “Indicador de calidad de servicio bajo cambio climático” (I2p) que mantiene los mismos criterios de valoración que I2 pero que responde mejor bajo fuertes reducciones de aportaciones producto del cambio climático. La metodología propuesta para la identificación de medidas de adaptación se basa en un proceso iterativo en el cual se van afectando diversos elementos que conforman el esquema del sistema bajo acciones de gestión previamente identificadas, hasta llegar a un comportamiento óptimo dado por el gestor. Las mejoras de estas afectaciones son cuantificadas mediante los indicadores I1 e I2p, y de este conjunto de valores se selecciona la que se acerca más al comportamiento óptimo. Debido a la extensa cantidad de información manejada en este análisis, se desarrolló una herramienta de cálculo automatizada en Matlab. El proceso seguido por esta herramienta es: (i) Ejecución del modelo OPTIGES para las diferentes modificaciones por acciones de gestión; (ii) Cálculo de los valores de I1 e I2p para cada una de estas afectaciones; y (iii) Selección de la mejor opción. Este proceso se repite hasta llegar al comportamiento óptimo buscado, permitiendo la identificación de las medidas de adaptación mas adecuadas. La aplicación de la metodología para la identificación de medidas de adaptación se realizó en la cuenca del Guadalquivir, por ser de las tres cuencas analizadas bajo los indicadores I1 e I2p la que presenta los problemas más serios de escasez de agua. Para la identificación de medidas de adaptación se analizaron dos acciones de gestión: 1) incremento de los volúmenes de regulación y 2) reducción de las demandas de riego, primero bajo la valoración del comportamiento físico del sistema (análisis de sensibilidad) permitiendo identificar que la primera acción de gestión no genera cambios importantes en el comportamiento del sistema, que si se presentan bajo la segunda acción. Posteriormente, con la acción que genera cambios importantes en el comportamiento del sistema (segunda acción) se identificaron las medidas de adaptación más adecuadas, mediante el análisis físico y económico del sistema. Se concluyó que en la cuenca del Guadalquivir, la acción de reducción de las demandas de riego permite minimizar e incluso eliminar los problemas de escasez de agua que se presentarían a futuro bajo diferentes proyecciones hidrológicas, aunque estas mejoras implicarían fuertes reducciones en dichas demandas. Siendo las demandas más afectadas aquellas ubicadas en cabecera de cuenca. Los criterios para la reducción de las demandas se encuentran en función de las productividades y garantías con las que son atendidas dichas demandas. This thesis makes a methodological contribution to the study of potentially suitable adaptation measures in the long term, where water resource systems undergo strong pressure due to the effects of climate change. This methodology integrates the physical analysis of the system, by the use of indicators which assess its behavior, and the economic analysis by the use of the value of water. The methodological procedure begins with the building of a set of future scenarios that capture, by one hand, the characteristics and variability of the streamflow of various climate models and, on the other hand, the hydrological characteristics of the study area. The study areas chosen were the Guadalquivir, Ebro and Duero basins, and as observed data where used runoff series in natural regimen estimated by the SIMPA model, which is calibrated in the whole Spanish territory. The observed series are for the 1961-1990 period. The future scenarios built represent the 2071-2100 periods. The identification of adaptation measures relied on the use of indicators that were able of characterize the behavior of one water resource system facing the effects of climate change. Because of that, the Demand Satisfaction Index (I1) and the Demand Reliability Index (I2) proposed by Martin-Carrasco et al. (2012) were selected. These indicators assess the behavior of a system by identifying the water scarcity problems that it presents, and require in order to be quantified the use of one optimization model. For this study the OPTIGES optimization model has been used. The determination of the indicators was made for the short-term analysis where the climates change effect are not relevant, so it was necessary to analyze their capability to be used in systems affected by those these. For this analysis three Spanish basins were selected: Guadalquivir, Duero and Ebro. It was determined that the indicator I2 is not suitable for this type of scenario. It was proposed a new indicator called “Demand Reliability Index under climate change” (I2p), which keeps the same assessment criteria than I2, but responsive under heavy reductions of streamflow due to climate change. The proposed methodology for identifying adaptation measures is based on an iterative process, in which the different elements of the system´s schema are affected by previously defined management actions, until reach an optimal behavior given by the manager. The improvements of affectations are measured by indicators I1 e I2p, and from this set of values it is selected the affectation that is closer to the optimal behavior. Due to the large amount of information managed in this analysis, it was developed an automatic calculation tool in Matlab. The process followed by this tool is: Firstly, it executes the OPTIGES model for the different modifications by management actions; secondly, it calculates the values of I1 e I2p for each of these affectations; and finally it chooses the best option. This process is performed for the different iterations that are required until reach the optimal behavior, allowing to identify the most appropriate adaptation measured. The application of the methodology for the identification of adaptation measures was conducted in the Guadalquivir basin, due to this was from the three basins analyzed under the indicators I1 e I2p, which presents the most serious problems of water scarcity. For the identification of adaptation measures there were analyzed two management actions: 1) To increase the regulation volumes, and 2) to reduce the irrigation demands, first under the assessment of the physical behavior of the system (sensibility analysis), allowing to identify that the first management action does not generate significant changes in the system´s behavior, which there are present under the second management action. Afterwards, with the management action that generates significant changes in the system´s behavior (second management action), there were identified the most adequate adaptation measures, through the physical and economic analysis of the system. It was concluded that in the Guadalquivir basin, the action of reduction of irrigation demands allows to minimize or even eliminate the water scarcity problems that could exist in the future under different hydrologic projections, although this improvements should involve strong reductions of the irrigation demands. Being the most affected demands those located in basins head. The criteria for reducing the demands are based on the productivities and reliabilities with which such demands are meet.

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In the information society large amounts of information are being generated and transmitted constantly, especially in the most natural way for humans, i.e., natural language. Social networks, blogs, forums, and Q&A sites are a dynamic Large Knowledge Repository. So, Web 2.0 contains structured data but still the largest amount of information is expressed in natural language. Linguistic structures for text recognition enable the extraction of structured information from texts. However, the expressiveness of the current structures is limited as they have been designed with a strict order in their phrases, limiting their applicability to other languages and making them more sensible to grammatical errors. To overcome these limitations, in this paper we present a linguistic structure named ?linguistic schema?, with a richer expressiveness that introduces less implicit constraints over annotations.

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There is no empirical evidence whatsoever to support most of the beliefs on which software construction is based. We do not yet know the adequacy, limits, qualities, costs and risks of the technologies used to develop software. Experimentation helps to check and convert beliefs and opinions into facts. This research is concerned with the replication area. Replication is a key component for gathering empirical evidence on software development that can be used in industry to build better software more efficiently. Replication has not been an easy thing to do in software engineering (SE) because the experimental paradigm applied to software development is still immature. Nowadays, a replication is executed mostly using a traditional replication package. But traditional replication packages do not appear, for some reason, to have been as effective as expected for transferring information among researchers in SE experimentation. The trouble spot appears to be the replication setup, caused by version management problems with materials, instruments, documents, etc. This has proved to be an obstacle to obtaining enough details about the experiment to be able to reproduce it as exactly as possible. We address the problem of information exchange among experimenters by developing a schema to characterize replications. We will adapt configuration management and product line ideas to support the experimentation process. This will enable researchers to make systematic decisions based on explicit knowledge rather than assumptions about replications. This research will output a replication support web environment. This environment will not only archive but also manage experimental materials flexibly enough to allow both similar and differentiated replications with massive experimental data storage. The platform should be accessible to several research groups working together on the same families of experiments.

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As a thermal separation method, distillation is one of the most important technologies in the chemical industry. Given its importance, it is no surprise that increasing efforts have been made in reducing its energy inefficiencies. A great deal of research is focused in the design and optimization of the Divided-Wall Column. Its applications are still reduced due to distrust of its controllability. Previous references studied the decentralized control of DWC but still few papers deal about Model Predictive Control. In this work we present a decentralized control of both a DWC column along with its equivalent MPC schema.

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A día de hoy, XML (Extensible Markup Language) es uno de los formatos más utilizados para el intercambio y almacenamiento de información estructurada en la World Wide Web. Es habitual que las aplicaciones que utilizan archivos XML presupongan en ellos una estructura determinada, pudiendo producirse errores si se intentase emplear documentos que no la cumplan. A fin de poder expresar este tipo de limitaciones y poder verificar que un documento las cumple, se definió en el mismo estándar XML el DTD, si bien pronto se mostró bastante limitado en cuanto a su capacidad expresiva. Es por este motivo que se decidió crear el XML Schema, un lenguaje XML para definir qué estructura deben tener otros documentos XML. Contar con un esquema tiene múltiples ventajas, siendo la principal de ellas el poder validar documentos contra él para comprobar si su estructura es correcta u otras como la generación automática de código. Sin embargo, definir una estructura común a varios documentos XML de una manera óptima puede convertirse en una tarea ardua si se hace de manera manual. Este problema puede salvarse contando con una herramienta que automatice el proceso de creación de dichos XSDs. En este proyecto, desarrollaremos una herramienta en Java que, a partir de una serie de documentos XML de entrada, inferirá automáticamente un esquema contra el que validen todos ellos, expresando su estructura de manera completa y concisa. Dicha herramienta permitirá elegir varios parámetros de inferencia, a fin de que el esquema generado se adapte lo más posible a los propósitos del usuario. Esta herramienta generará también una serie de estadísticas adicionales, que permitirán conocer más información sobre los ficheros de entrada.