887 resultados para LINK-BASED AND MULTIDIMENSIONAL QUERY LANGUAGE (LMDQL)


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Today, databases have become an integral part of information systems. In the past two decades, we have seen different database systems being developed independently and used in different applications domains. Today's interconnected networks and advanced applications, such as data warehousing, data mining & knowledge discovery and intelligent data access to information on the Web, have created a need for integrated access to such heterogeneous, autonomous, distributed database systems. Heterogeneous/multidatabase research has focused on this issue resulting in many different approaches. However, a single, generally accepted methodology in academia or industry has not emerged providing ubiquitous intelligent data access from heterogeneous, autonomous, distributed information sources. ^ This thesis describes a heterogeneous database system being developed at High-performance Database Research Center (HPDRC). A major impediment to ubiquitous deployment of multidatabase technology is the difficulty in resolving semantic heterogeneity. That is, identifying related information sources for integration and querying purposes. Our approach considers the semantics of the meta-data constructs in resolving this issue. The major contributions of the thesis work include: (i) providing a scalable, easy-to-implement architecture for developing a heterogeneous multidatabase system, utilizing Semantic Binary Object-oriented Data Model (Sem-ODM) and Semantic SQL query language to capture the semantics of the data sources being integrated and to provide an easy-to-use query facility; (ii) a methodology for semantic heterogeneity resolution by investigating into the extents of the meta-data constructs of component schemas. This methodology is shown to be correct, complete and unambiguous; (iii) a semi-automated technique for identifying semantic relations, which is the basis of semantic knowledge for integration and querying, using shared ontologies for context-mediation; (iv) resolutions for schematic conflicts and a language for defining global views from a set of component Sem-ODM schemas; (v) design of a knowledge base for storing and manipulating meta-data and knowledge acquired during the integration process. This knowledge base acts as the interface between integration and query processing modules; (vi) techniques for Semantic SQL query processing and optimization based on semantic knowledge in a heterogeneous database environment; and (vii) a framework for intelligent computing and communication on the Internet applying the concepts of our work. ^

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Over the past five years, XML has been embraced by both the research and industrial community due to its promising prospects as a new data representation and exchange format on the Internet. The widespread popularity of XML creates an increasing need to store XML data in persistent storage systems and to enable sophisticated XML queries over the data. The currently available approaches to addressing the XML storage and retrieval issue have the limitations of either being not mature enough (e.g. native approaches) or causing inflexibility, a lot of fragmentation and excessive join operations (e.g. non-native approaches such as the relational database approach). ^ In this dissertation, I studied the issue of storing and retrieving XML data using the Semantic Binary Object-Oriented Database System (Sem-ODB) to leverage the advanced Sem-ODB technology with the emerging XML data model. First, a meta-schema based approach was implemented to address the data model mismatch issue that is inherent in the non-native approaches. The meta-schema based approach captures the meta-data of both Document Type Definitions (DTDs) and Sem-ODB Semantic Schemas, thus enables a dynamic and flexible mapping scheme. Second, a formal framework was presented to ensure precise and concise mappings. In this framework, both schemas and the conversions between them are formally defined and described. Third, after major features of an XML query language, XQuery, were analyzed, a high-level XQuery to Semantic SQL (Sem-SQL) query translation scheme was described. This translation scheme takes advantage of the navigation-oriented query paradigm of the Sem-SQL, thus avoids the excessive join problem of relational approaches. Finally, the modeling capability of the Semantic Binary Object-Oriented Data Model (Sem-ODM) was explored from the perspective of conceptually modeling an XML Schema using a Semantic Schema. ^ It was revealed that the advanced features of the Sem-ODB, such as multi-valued attributes, surrogates, the navigation-oriented query paradigm, among others, are indeed beneficial in coping with the XML storage and retrieval issue using a non-XML approach. Furthermore, extensions to the Sem-ODB to make it work more effectively with XML data were also proposed. ^

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Today, databases have become an integral part of information systems. In the past two decades, we have seen different database systems being developed independently and used in different applications domains. Today's interconnected networks and advanced applications, such as data warehousing, data mining & knowledge discovery and intelligent data access to information on the Web, have created a need for integrated access to such heterogeneous, autonomous, distributed database systems. Heterogeneous/multidatabase research has focused on this issue resulting in many different approaches. However, a single, generally accepted methodology in academia or industry has not emerged providing ubiquitous intelligent data access from heterogeneous, autonomous, distributed information sources. This thesis describes a heterogeneous database system being developed at Highperformance Database Research Center (HPDRC). A major impediment to ubiquitous deployment of multidatabase technology is the difficulty in resolving semantic heterogeneity. That is, identifying related information sources for integration and querying purposes. Our approach considers the semantics of the meta-data constructs in resolving this issue. The major contributions of the thesis work include: (i.) providing a scalable, easy-to-implement architecture for developing a heterogeneous multidatabase system, utilizing Semantic Binary Object-oriented Data Model (Sem-ODM) and Semantic SQL query language to capture the semantics of the data sources being integrated and to provide an easy-to-use query facility; (ii.) a methodology for semantic heterogeneity resolution by investigating into the extents of the meta-data constructs of component schemas. This methodology is shown to be correct, complete and unambiguous; (iii.) a semi-automated technique for identifying semantic relations, which is the basis of semantic knowledge for integration and querying, using shared ontologies for context-mediation; (iv.) resolutions for schematic conflicts and a language for defining global views from a set of component Sem-ODM schemas; (v.) design of a knowledge base for storing and manipulating meta-data and knowledge acquired during the integration process. This knowledge base acts as the interface between integration and query processing modules; (vi.) techniques for Semantic SQL query processing and optimization based on semantic knowledge in a heterogeneous database environment; and (vii.) a framework for intelligent computing and communication on the Internet applying the concepts of our work.

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Recently, blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) has become a routine clinical procedure for localization of language and motor brain regions and has been replacing more invasive preoperative procedures. However, the fMRI results from these tasks are not always reproducible even from the same patient. Evaluating the reproducibility of language and speech mapping is especially complicated due to the complex brain circuitry that may become activated during the functional task. Non-language areas such as sensory, attention, decision-making, and motor brain regions may also be activated in addition to the specific language regions during a traditional sentence-completion task. In this study, I test a new approach, which utilizes 4-minute video-based tasks, to map language and speech brain regions for patients undergoing brain surgery. Results from 35 subjects have shown that the video-based task activates Wernicke’s area, as well as Broca’s area in most subjects. The computed laterality indices, which indicate the dominant hemisphere from that functional task, have indicated left dominance from the video-based tasks. This study has shown that the video-based task may be an alternative method for localization of language and speech brain regions for patients who are unable to complete the sentence-completion task.

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This research aimed to describe, understand, and discuss the curriculum development process of a Brazilian-Portuguese heritage language community-based school in South Florida. This study was guided by the following research questions: (a) What roles does this HL community-based school aim to play for its students? This investigation was also related to the subsidiary question: (b) How does this HL community-based school organize its curriculum development process? In order to explore these research questions, I observed and interviewed teachers and coordinators based on a qualitative research approach. I analyzed the interviews’ transcripts, and the program’s website with a central focus of describing and understanding their curriculum development process. Hopefully, the findings will help Brazilian and other HL community schools toward discussing and elaborating their own curriculum development, as well as to look for specific teacher training courses.

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The goal of this thesis is twofold. Firstly, it investigates the actual, native use of spatial-deictic demonstratives in Japanese, Finnish and Swedish. Secondly, it investigates and elucidates the interlanguage of Finnish-speaking and Swedish-speaking learners of Japanese regarding their use of Japanese spatial-deictic demonstratives in the light of respective native use and, in comparison to the descriptions of demonstratives in the teaching materials used. Thus, the present study deals with analyses of two sets of empirical data: data produced by native-speaking informants (L1 data) and data produced by language learners (L2 data). These were elicited by Discourse Completion Tasks (DCTs) designed, collected and analyzed using both quantitative and qualitative methods by the author. The results showed that the actual use of demonstratives by the native informants was not always in accordance with the way described in grammars. The typological similarities between Japanese and Finnish were in this study not reflected in the native use of demonstratives, and some uses were not solely based on the spatial relations between the referent, the speaker and the addressee, but rather on social-interactional factors. The main findings regarding the learner data revealed some differences in the usage rate of the demonstratives between the two Finnish-speaking groups and the one Swedish-speaking learner group studied. There were, however, no particular differences found between them regarding the type of demonstrative used. It is suggested that these differences are first and foremost connected both with the teaching materials used and the more or less heterogeneous linguistic environment in which the learners reside, and only thereafter with the typological similarities or differences between their respective native languages, Finnish and Swedish, and the target language, Japanese. It is further argued that the learners’ use of the different Japanese demonstratives, that is the type of demonstrative used, could be explained in terms of familiarity with the grammar. That is, when the situations used in the DCTs were exemplified in teaching materials and were familiar to them, the learners seemed to use Japanese demonstratives as they are described in the teaching materials and as the native Japanese speakers use them. When the situations used in the DCTs were not exemplified in the teaching materials, the learners seem to rely more on their native language. The results, thus, suggest that the learners’ interlanguage is influenced by the grammar of the target language known to the learners, but also by the number of languages (or varieties) that the learners have contact with at the time of learning. The results of the present study have implications for the teaching of Japanese in at least two ways. Firstly, the importance of grammar instruction must be emphasized since its effect on the learners’ language is apparent. Secondly, the contents of teaching materials should be revised on the basis of the native speakers’ actual use of the grammar.

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The present study examined the effect of learning to read a heritage language on Taiwanese Mandarin-English bilingual children’s Chinese and English phonological awareness, Chinese and English oral language proficiency, and English reading skills. Participants were 40 Taiwanese Mandarin-English bilingual children and 20 English monolingual children in the U.S. Based on their performance on a Chinese character reading test, the bilingual participants were divided into two groups: the Chinese Beginning Reader and Chinese Nonreader groups. A single child categorized as a Chinese Advanced Reader also participated. Children received phonological awareness tasks, produced oral narrative samples from a wordless picture book, and took standardized English reading subtests. The bilingual participants received measures in both English and Chinese, whereas English monolingual children received only English measures. Additional demographic information was collected from a language background survey filled out by parents. Results of two MANOVAs indicated that the Chinese Beginning Reader group outperformed the Chinese Nonreader and English Monolingual groups on some phonological awareness measures and the English nonword reading test. In an oral narrative production task in English, the English Monolingual group produced a greater total number of words (TNW) and more different words (NDW) than the Chinese Nonreader group. Multiple regression analyses were conducted to determine whether bilingual children’s Chinese character reading ability would still account for a unique amount of variance in certain outcome variables, independent of nonverbal IQ and other potential demographic or performance variables and to clarify the direction of causality for bilingual children’s performance in the three domains. These results suggested that learning to read in a heritage language directly or indirectly enhances bilingual children’s ability in phonological awareness and certain English reading skills. It also appears that greater oral language proficiency in Chinese promotes early reading in the heritage language. Advanced heritage reading may produce even larger gains. Practical implications of learning a heritage language in the U.S. are discussed.

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The objective of the thesis was to study the possible linguistic differences of English of Finnish mainstream students and Finnish students following content and language integrated learning (CLIL), in terms of the given language test. The difference of test results between the test groups was further analyzed in more detail. The research was carried out by comparing the 9th grade students of the Finnish comprehensive school (the mainstream group) and CLIL students of the 9th grade of the Finnish comprehensive school (the CLIL group). The comparison was based on the national language test for the 9th grade students of the Finnish comprehensive school 2006 (A-English), produced by Sukol-Palvelu, owned by the Federation of Foreign Language Teachers in Finland SUKOL. The mainstream group of the present study consisted of 30 students, whereas the CLIL group included 27 students. Testing was carried out in spring 2007. The test results of the mainstream group (average of 64.1% out of the maximum score) were consistent with the results of the national average (63.9%). The average score of the CLIL students for the present study was 83.3% out of the maximum score. The results of the two groups in question were rather similar in the tasks measuring the skill of listening comprehension, in addition to one of the reading comprehension tasks. Moreover, a particular task with requirements of cultural and reactional skills produced results rather similar between the test groups. The differences between the results of the mainstream group and the CLIL group were most evident in three particular tasks. In general, the CLIL group performed clearly better than the mainstream group in the task measuring the knowledge of the polite conversational manners of the English-speaking world and in the tasks with requirements of lexical and structural knowledge of English. However, the writing task resulted in the most evident difference of results between the groups. In other words, the CLIL students of the present study were clearly more capable of producing English language with more varied vocabulary and more complex structures than the mainstream students. Thus, it might be argued whether the CLIL programme is to enhance the students´ performance in the productive skill of writing in particular. As a result, it might be useful to consider the possibilities of the CLIL programme in developing certain linguistic skills of the mainstream students of English as well.

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Natural language processing has achieved great success in a wide range of ap- plications, producing both commercial language services and open-source language tools. However, most methods take a static or batch approach, assuming that the model has all information it needs and makes a one-time prediction. In this disser- tation, we study dynamic problems where the input comes in a sequence instead of all at once, and the output must be produced while the input is arriving. In these problems, predictions are often made based only on partial information. We see this dynamic setting in many real-time, interactive applications. These problems usually involve a trade-off between the amount of input received (cost) and the quality of the output prediction (accuracy). Therefore, the evaluation considers both objectives (e.g., plotting a Pareto curve). Our goal is to develop a formal understanding of sequential prediction and decision-making problems in natural language processing and to propose efficient solutions. Toward this end, we present meta-algorithms that take an existent batch model and produce a dynamic model to handle sequential inputs and outputs. Webuild our framework upon theories of Markov Decision Process (MDP), which allows learning to trade off competing objectives in a principled way. The main machine learning techniques we use are from imitation learning and reinforcement learning, and we advance current techniques to tackle problems arising in our settings. We evaluate our algorithm on a variety of applications, including dependency parsing, machine translation, and question answering. We show that our approach achieves a better cost-accuracy trade-off than the batch approach and heuristic-based decision- making approaches. We first propose a general framework for cost-sensitive prediction, where dif- ferent parts of the input come at different costs. We formulate a decision-making process that selects pieces of the input sequentially, and the selection is adaptive to each instance. Our approach is evaluated on both standard classification tasks and a structured prediction task (dependency parsing). We show that it achieves similar prediction quality to methods that use all input, while inducing a much smaller cost. Next, we extend the framework to problems where the input is revealed incremen- tally in a fixed order. We study two applications: simultaneous machine translation and quiz bowl (incremental text classification). We discuss challenges in this set- ting and show that adding domain knowledge eases the decision-making problem. A central theme throughout the chapters is an MDP formulation of a challenging problem with sequential input/output and trade-off decisions, accompanied by a learning algorithm that solves the MDP.

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The market for plant-based dairy-type products is growing as consumers replace bovine milk in their diet, for medical reasons or as a lifestyle choice. A screening of 17 different commercial plant-based milk substitutes based on different cereals, nuts and legumes was performed, including the evaluation of physicochemical and glycaemic properties. Half of the analysed samples had low or no protein contents (<0.5 %). Only samples based on soya showed considerable high protein contents, matching the value of cow’s milk (3.7 %). An in-vitro method was used to predict the glycaemic index. In general, the glycaemic index values ranged from 47 for bovine milk to 64 (almond-based) and up to 100 for rice-based samples. Most of the plant-based milk substitutes were highly unstable with separation rates up to 54.39 %/h. This study demonstrated that nutritional and physicochemical properties of plant-based milk substitutes are strongly dependent on the plant source, processing and fortification. Most products showed low nutritional qualities. Therefore, consumer awareness is important when plant-based milk substitutes are used as an alternative to cow’s milk in the diet.

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A framework for and overview of the key elements of language planning is presented covering status planning, corpus planning, language-in-education planning, prestige planning and critical approaches to language planning. Within each of these areas, key articles outlining important recent directions are discussed indicating the field’s new found sense of vitality.

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Except for a few large scale projects, language planners have tended to talk and argue among themselves rather than to see language policy development as an inherently political process. A comparison with a social policy example, taken from the United States, suggests that it is important to understand the problem and to develop solutions in the context of the political process, as this is where decisions will ultimately be made.

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