Data queries over heterogeneous sources

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Context Interchange as a Scalable Solution to Interoperating Amongst Heterogeneous Dynamic Services

Many online services access a large number of autonomous data sources and at the same time need to meet different user requirements. It is essential for these services to achieve semantic interoperability among these information exchange entities. In the presence of an increasing number of proprietary business processes, heterogeneous data standards, and diverse user requirements, it is critical that the services are implemented using adaptable, extensible, and scalable technology. The COntext INterchange (COIN) approach, inspired by similar goals of the Semantic Web, provides a robust solution. In this paper, we describe how COIN can be used to implement dynamic online services where semantic differences are reconciled on the fly. We show that COIN is flexible and scalable by comparing it with several conventional approaches. With a given ontology, the number of conversions in COIN is quadratic to the semantic aspect that has the largest number of distinctions. These semantic aspects are modeled as modifiers in a conceptual ontology; in most cases the number of conversions is linear with the number of modifiers, which is significantly smaller than traditional hard-wiring middleware approach where the number of conversion programs is quadratic to the number of sources and data receivers. In the example scenario in the paper, the COIN approach needs only 5 conversions to be defined while traditional approaches require 20,000 to 100 million. COIN achieves this scalability by automatically composing all the comprehensive conversions from a small number of declaratively defined sub-conversions.

Knowledge discovery using multiple sources of biological data

The primary aim of this dissertation is to develop data mining tools for knowledge discovery in biomedical data when multiple (homogeneous or heterogeneous) sources of data are available. The central hypothesis is that, when information from multiple sources of data are used appropriately and effectively, knowledge discovery can be better achieved than what is possible from only a single source. ^ Recent advances in high-throughput technology have enabled biomedical researchers to generate large volumes of diverse types of data on a genome-wide scale. These data include DNA sequences, gene expression measurements, and much more; they provide the motivation for building analysis tools to elucidate the modular organization of the cell. The challenges include efficiently and accurately extracting information from the multiple data sources; representing the information effectively, developing analytical tools, and interpreting the results in the context of the domain. ^ The first part considers the application of feature-level integration to design classifiers that discriminate between soil types. The machine learning tools, SVM and KNN, were used to successfully distinguish between several soil samples. ^ The second part considers clustering using multiple heterogeneous data sources. The resulting Multi-Source Clustering (MSC) algorithm was shown to have a better performance than clustering methods that use only a single data source or a simple feature-level integration of heterogeneous data sources. ^ The third part proposes a new approach to effectively incorporate incomplete data into clustering analysis. Adapted from K-means algorithm, the Generalized Constrained Clustering (GCC) algorithm makes use of incomplete data in the form of constraints to perform exploratory analysis. Novel approaches for extracting constraints were proposed. For sufficiently large constraint sets, the GCC algorithm outperformed the MSC algorithm. ^ The last part considers the problem of providing a theme-specific environment for mining multi-source biomedical data. The database called PlasmoTFBM, focusing on gene regulation of Plasmodium falciparum, contains diverse information and has a simple interface to allow biologists to explore the data. It provided a framework for comparing different analytical tools for predicting regulatory elements and for designing useful data mining tools. ^ The conclusion is that the experiments reported in this dissertation strongly support the central hypothesis.^

Arquitetura para aquisição de respostas a perguntas frequentes

Dissertação de natureza científica realizada para obtenção do grau de Mestre em Engenharia Informática e de Computadores

Development of regional spatial data infrastructure (SDI) case study in hearth of Borneo

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

State-of-the-art for entity-centric repository and authoring environment for multimedia

Many projects, e.g. VIKEF [13] and KIM [7], present grounded approaches for the use of entities as a means of indexing and retrieval of multimedia resources from heterogeneous sources. In this paper, we discuss the state-of-the-art of entity-centric approaches for multimedia indexing and retrieval. A summary of projects employing entity-centric repositories are portrayed. This paper also looks at the current state-of-the-art authoring environment, Macromedia Authorware, and the possibility of potential extension of this environment for entity-based multimedia authoring.

CES: Um Mecanismo Genérico de Composição de Eventos para Sistemas Sensíveis ao Contexto

Pervasive applications use context provision middleware support as infrastructures to provide context information. Typically, those applications use communication publish/subscribe to eliminate the direct coupling between components and to allow the selective information dissemination based in the interests of the communicating elements. The use of composite events mechanisms together with such middlewares to aggregate individual low level events, originating from of heterogeneous sources, in high level context information relevant for the application. CES (Composite Event System) is a composite events mechanism that works simultaneously in cooperation with several context provision middlewares. With that integration, applications use CES to subscribe to composite events and CES, in turn, subscribes to the primitive events in the appropriate underlying middlewares and notifies the applications when the composed events happen. Furthermore, CES offers a language with a group of operators for the definition of composite events that also allows context information sharing

Shell beds as paleoecological puzzles: A case study from the Upper Permian of the Parana Basin, Brazil

Microstratigraphic, sedimentological, and taphonomic features of the Ferraz Shell Bed, from the Upper Permian (Kazanian-Tatarian?) Corumbatai Formation of Rio Claro Region (the Parana Basin, Brazil), indicate that the bed consists of four distinct microstratigraphic units. They include, from bottom to top, a lag concentration (Unit 1), a partly reworked storm deposit (Unit 2), a rapidly deposited sandstone unit with three thin horizons recording episodes of reworking (Unit 3), and a shell-rich horizon generated by reworking/winnowing that was subsequently buried by storm-induced obrution deposit (Unit 4). The bioclasts of the Ferraz Shell Bed represent exclusively bivalve mollusks. Pinzonella illusa and Terraia aequilateralis are the dominant species. Taphonomic analysis indicates that mollusks are heavily time-averaged (except for some parts of Unit 3). Moreover, different species are time-averaged to a different degree (disharmonious time-averaging). The units differ statistically from one another in their taxonomic and ecological composition, in their taphonomic pattern, and in the size-frequency distributions of the two most common species. Other Permian shell beds of the Parana Basin are similar to the Ferraz Shell Bed in their faunal composition (they typically contain similar sets of 5 to 10 bivalve species) and in their taphonomic, sedimentologic, and microstratigraphic characteristics. However, rare shell beds that include 2-3 species only and are dominated by articulated shells preserved in life position also occur. Diversity levels in the Permian benthic associations of the Parana Basin were very low, with the point diversity of 2-3 species and with the within-habitat and basin-wide (alpha and gamma) diversities of 10 species, at most. The Parana Basin benthic communities may have thus been analogous to low-diversity bivalve-dominated associations of the present-day Baltic Sea. The 'Ferraz-type' shell beds of the Parana Basin represent genetically complex and highly heterogeneous sources of paleontological data. They are cumulative records of spectra of benthic ecosystems time-averaged over long periods of time (10(2)-10(4) years judging from actualistic research). Detailed biostratinomic reconstructions of shell beds can not only offer useful insights into their depositional histories, but may also allow paleoecologists to optimize their sampling designs, and consequently, refine paleoecological and paleoenvironmental interpretations.

Geochronological and structural evolution of the western and central Kaoko Belt in NW Namibia

This thesis focusses on the tectonic evolution and geochronology of part of the Kaoko orogen, which is part of a network of Pan-African orogenic belts in NW Namibia. By combining geochemical, isotopic and structural analysis, the aim was to gain more information about how and when the Kaoko Belt formed. The first chapter gives a general overview of the studied area and the second one describes the basis of the Electron Probe Microanalysis dating method. The reworking of Palaeo- to Mesoproterozoic basement during the Pan-African orogeny as part of the assembly of West Gondwana is discussed in Chapter 3. In the study area, high-grade rocks occupy a large area, and the belt is marked by several large-scale structural discontinuities. The two major discontinuities, the Sesfontein Thrust (ST) and the Puros Shear Zone (PSZ), subdivide the orogen into three tectonic units: the Eastern Kaoko Zone (EKZ), the Central Kaoko Zone (CKZ) and the Western Kaoko Zone (WKZ). An important lineament, the Village Mylonite Zone (VMZ), has been identified in the WKZ. Since plutonic rocks play an important role in understanding the evolution of a mountain belt, zircons from granitoid gneisses were dated by conventional U-Pb, SHRIMP and Pb-Pb techniques to identify different age provinces. Four different age provinces were recognized within the Central and Western part of the belt, which occur in different structural positions. The VMZ seems to mark the limit between Pan-African granitic rocks east of the lineament and Palaeo- to Mesoproterozoic basement to the west. In Chapter 4 the tectonic processes are discussed that led to the Neoproterozoic architecture of the orogen. The data suggest that the Kaoko Belt experienced three main phases of deformation, D1-D3, during the Pan-African orogeny. Early structures in the central part of the study area indicate that the initial stage of collision was governed by underthrusting of the medium-grade Central Kaoko zone below the high-grade Western Kaoko zone, resulting in the development of an inverted metamorphic gradient. The early structures were overprinted by a second phase D2, which was associated with the development of the PSZ and extensive partial melting and intrusion of ~550 Ma granitic bodies in the high-grade WKZ. Transcurrent deformation continued during cooling of the entire belt, giving rise to the localized low-temperature VMZ that separates a segment of elevated Mesoproterozoic basement from the rest of the Western zone in which only Pan-African ages have so far been observed. The data suggest that the boundary between the Western and Central Kaoko zones represents a modified thrust zone, controlling the tectonic evolution of the Kaoko belt. The geodynamic evolution and the processes that generated this belt system are discussed in Chapter 5. Nd mean crustal residence ages of granitoid rocks permit subdivision of the belt into four provinces. Province I is characterised by mean crustal residence ages <1.7 Ga and is restricted to the Neoproterozoic granitoids. A wide range of initial Sr isotopic values (87Sr/86Sri = 0.7075 to 0.7225) suggests heterogeneous sources for these granitoids. The second province consists of Mesoproterozoic (1516-1448 Ma) and late Palaeo-proterozoic (1776-1701 Ma) rocks and is probably related to the Eburnian cycle with Nd model ages of 1.8-2.2 Ga. The eNd i values of these granitoids are around zero and suggest a predominantly juvenile source. Late Archaean and middle Palaeoproterozoic rocks with model ages of 2.5 to 2.8 Ga make up Province III in the central part of the belt and are distinct from two early Proterozoic samples taken near the PSZ which show even older TDM ages of ~3.3 Ga (Province IV). There is no clear geological evidence for the involvement of oceanic lithosphere in the formation of the Kaoko-Dom Feliciano orogen. Chapter 6 presents the results of isotopic analyses of garnet porphyroblasts from high-grade meta-igneous and metasedimentary rocks of the sillimanite-K-feldspar zone. Minimum P-T conditions for peak metamorphism were calculated at 731±10 °C at 6.7±1.2 kbar, substantially lower than those previously reported. A Sm-Nd garnet-whole rock errorchron obtained on a single meta-igneous rock yielded an unexpectedly old age of 692±13 Ma, which is interpreted as an inherited metamorphic age reflecting an early Pan-African granulite-facies event. The dated garnets survived a younger high-grade metamorphism that occurred between ca. 570 and 520 Ma and apparently maintained their old Sm-Nd isotopic systematics, implying that the closure temperature for garnet in this sample was higher than 730 °C. The metamorphic peak of the younger event was dated by electronmicroprobe on monazite at 567±5 Ma. From a regional viewpoint, it is possible that these granulites of igneous origin may be unrelated to the early Pan-African metamorphic evolution of the Kaoko Belt and may represent a previously unrecognised exotic terrane.

Extracting knowledge through friendsourcing: application to new financial services

Personalization has become a key factor for the success of new ICT services. However, the personal information required is not always available in a single site, but scattered in heterogeneous sources, and extracting knowledge from raw information is not an easy job. As a result, many organizations struggle to obtain knowledge on their users useful enough for their business purposes. This paper introduces a comprehensive personal data framework that opens the knowledge extraction process up to collaboration by the involvement of new actors, while enabling users to monitor and control it. The contributions have been validated in a financial services scenario where socioeconomic knowledge on some users is generated by tapping into their social network and used to assists them in raising money from their friends.

Data normalization and integration in robotic systems using web services technologies

The robotics is one of the most active areas. We also need to join a large number of disciplines to create robots. With these premises, one problem is the management of information from multiple heterogeneous sources. Each component, hardware or software, produces data with different nature: temporal frequencies, processing needs, size, type, etc. Nowadays, technologies and software engineering paradigms such as service-oriented architectures are applied to solve this problem in other areas. This paper proposes the use of these technologies to implement a robotic control system based on services. This type of system will allow integration and collaborative work of different elements that make up a robotic system.

Noise-tolerance feasibility for restricted-domain Information Retrieval systems

Information Retrieval systems normally have to work with rather heterogeneous sources, such as Web sites or documents from Optical Character Recognition tools. The correct conversion of these sources into flat text files is not a trivial task since noise may easily be introduced as a result of spelling or typeset errors. Interestingly, this is not a great drawback when the size of the corpus is sufficiently large, since redundancy helps to overcome noise problems. However, noise becomes a serious problem in restricted-domain Information Retrieval specially when the corpus is small and has little or no redundancy. This paper devises an approach which adds noise-tolerance to Information Retrieval systems. A set of experiments carried out in the agricultural domain proves the effectiveness of the approach presented.

Knowledge mediation and overlapping in interfirm networks

Purpose – The literature on interfirm networks devotes scant attention to the ways collaborating firms combine and integrate the knowledge they share and to the subsequent learning outcomes. This study aims to investigate how motorsport companies use network ties to share and recombine knowledge and the learning that occurs both at the organizational and dyadic network levels. Design/methodology/approach – The paper adopts a qualitative and inductive approach with the aim of developing theory from an in-depth examination of the dyadic ties between motorsport companies and the way they share and recombine knowledge. Findings – The research shows that motorsport companies having substantial competences at managing knowledge flows do so by getting advantage of bridging ties. While bridging ties allow motorsport companies to reach distant and diverse sources of knowledge, their strengthening and the formation of relational capital facilitate the mediation and overlapping of that knowledge. Research limitations/implications – The analysis rests on a qualitative account in a single industry and does not take into account different types of inter-firm networks (e.g. alliances; constellations; consortia etc.) and governance structures. Cross-industry analyses may provide a more fine-grained picture of the practices used to recombine knowledge and the ideal composition of inter-firm ties. Practical implications – This study provides some interesting implications for scholars and managers concerned with the management of innovation activities at the interfirm level. From a managerial point of view, the recognition of the different roles played by network spanning connections is particularly salient and raises issues concerning the effective design and management of interfirm ties. Originality/value – Although much of the literature emphasizes the role of bridging ties in connecting to diverse pools of knowledge, this paper goes one step further and investigates in more depth how firms gather and combine distant and heterogeneous sources of knowledge through the use of strengthened bridging ties and a micro-context conducive to high quality relationships.

Bayesian Learning with Dependency Structures via Latent Factors, Mixtures, and Copulas

Bayesian methods offer a flexible and convenient probabilistic learning framework to extract interpretable knowledge from complex and structured data. Such methods can characterize dependencies among multiple levels of hidden variables and share statistical strength across heterogeneous sources. In the first part of this dissertation, we develop two dependent variational inference methods for full posterior approximation in non-conjugate Bayesian models through hierarchical mixture- and copula-based variational proposals, respectively. The proposed methods move beyond the widely used factorized approximation to the posterior and provide generic applicability to a broad class of probabilistic models with minimal model-specific derivations. In the second part of this dissertation, we design probabilistic graphical models to accommodate multimodal data, describe dynamical behaviors and account for task heterogeneity. In particular, the sparse latent factor model is able to reveal common low-dimensional structures from high-dimensional data. We demonstrate the effectiveness of the proposed statistical learning methods on both synthetic and real-world data.

Diseño e implementación de un sistema de soporte de decisiones para el Centro de Documentación Regional “Juan Bautista Vázquez”

El volumen de datos en bibliotecas ha aumentado enormemente en los últimos años, así como también la complejidad de sus fuentes y formatos de información, dificultando su gestión y acceso, especialmente como apoyo en la toma de decisiones. Sabiendo que una buena gestión de bibliotecas involucra la integración de indicadores estratégicos, la implementación de un Data Warehouse (DW), que gestione adecuadamente tal cantidad de información, así como su compleja mezcla de fuentes de datos, se convierte en una alternativa interesante a considerar. El artículo describe el diseño e implementación de un sistema de soporte de decisiones (DSS) basado en técnicas de DW para la biblioteca de la Universidad de Cuenca. Para esto, el estudio utiliza una metodología holística, propuesto por Siguenza-Guzman et al. (2014) para la evaluación integral de bibliotecas. Dicha metodología evalúa la colección y los servicios, incorporando importantes elementos para la gestión de bibliotecas, tales como: el desempeño de los servicios, el control de calidad, el uso de la colección y la interacción con el usuario. A partir de este análisis, se propone una arquitectura de DW que integra, procesa y almacena los datos. Finalmente, estos datos almacenados son analizados y visualizados a través de herramientas de procesamiento analítico en línea (OLAP). Las pruebas iniciales de implementación confirman la viabilidad y eficacia del enfoque propuesto, al integrar con éxito múltiples y heterogéneas fuentes y formatos de datos, facilitando que los directores de bibliotecas generen informes personalizados, e incluso permitiendo madurar los procesos transaccionales que diariamente se llevan a cabo.