Efficient update and retrieval of objects in a multiresolution geospatial database

Many emerging applications benefit from the extraction of geospatial data specified at different resolutions for viewing purposes. Data must also be topologically accurate and up-to-date as it often represents real-world changing phenomena. Current multiresolution schemes use complex opaque data types, which limit the capacity for in-database object manipulation. By using z-values and B+trees to support multiresolution retrieval, objects are fragmented in such a way that updates to objects or object parts are executed using standard SQL (Structured Query Language) statements as opposed to procedural functions. Our approach is compared to a current model, using complex data types indexed under a 3D (three-dimensional) R-tree, and shows better performance for retrieval over realistic window sizes and data loads. Updates with the R-tree are slower and preclude the feasibility of its use in time-critical applications whereas, predictably, projecting the issue to a one-dimensional index allows constant updates using z-values to be implemented more efficiently.

The mosaic test:benchmarking colour-based image retrieval systems using image mosaics

Evaluation and benchmarking in content-based image retrieval has always been a somewhat neglected research area, making it difficult to judge the efficacy of many presented approaches. In this paper we investigate the issue of benchmarking for colour-based image retrieval systems, which enable users to retrieve images from a database based on lowlevel colour content alone. We argue that current image retrieval evaluation methods are not suited to benchmarking colour-based image retrieval systems, due in main to not allowing users to reflect upon the suitability of retrieved images within the context of a creative project and their reliance on highly subjective ground-truths. As a solution to these issues, the research presented here introduces the Mosaic Test for evaluating colour-based image retrieval systems, in which test-users are asked to create an image mosaic of a predetermined target image, using the colour-based image retrieval system that is being evaluated. We report on our findings from a user study which suggests that the Mosaic Test overcomes the major drawbacks associated with existing image retrieval evaluation methods, by enabling users to reflect upon image selections and automatically measuring image relevance in a way that correlates with the perception of many human assessors. We therefore propose that the Mosaic Test be adopted as a standardised benchmark for evaluating and comparing colour-based image retrieval systems.

Design of an information system for metrology contents

Dimensional and form inspections are key to the manufacturing and assembly of products. Product verification can involve a number of different measuring instruments operated using their dedicated software. Typically, each of these instruments with their associated software is more suitable for the verification of a pre-specified quality characteristic of the product than others. The number of different systems and software applications to perform a complete measurement of products and assemblies within a manufacturing organisation is therefore expected to be large. This number becomes even larger as advances in measurement technologies are made. The idea of a universal software application for any instrument still appears to be only a theoretical possibility. A need for information integration is apparent. In this paper, a design of an information system to consistently manage (store, search, retrieve, search, secure) measurement results from various instruments and software applications is introduced. Two of the main ideas underlying the proposed system include abstracting structures and formats of measurement files from the data so that complexity and compatibility between different approaches to measurement data modelling is avoided. Secondly, the information within a file is enriched with meta-information to facilitate its consistent storage and retrieval. To demonstrate the designed information system, a web application is implemented. © Springer-Verlag Berlin Heidelberg 2010.

Auctioning versus grandfathering in cap-and-trade systems with market power and incomplete information

We compare auctioning and grandfathering as allocation mechanisms of emission permits when there is a secondary market with market power and firms have private information on their own abatement technologies. Based on real-life cases such as the EU ETS, we consider a multi-unit, multi-bid uniform auction. At the auction, each firm anticipates its role in the secondary market, either as a leader or a follower. This role affects each firms’ valuation of the permits (which are not common across firms) as well as their bidding strategies and it precludes the auction from generating a cost-effective allocation of permits, as it occurs in simpler auction models. Auctioning tends to be more cost-effective than grandfathering when the firms’ abatement cost functions are sufficiently different from one another, especially if the follower has lower abatement costs than the leader and the dispersion of the marginal costs is large enough.

Layered Information Modeling and a Knowledge Organization Paradigm: Inherent Classification and the Design of Interoperable Systems

In knowledge technology work, as expressed by the scope of this conference, there are a number of communities, each uncovering new methods, theories, and practices. The Library and Information Science (LIS) community is one such community. This community, through tradition and innovation, theories and practice, organizes knowledge and develops knowledge technologies formed by iterative research hewn to the values of equal access and discovery for all. The Information Modeling community is another contributor to knowledge technologies. It concerns itself with the construction of symbolic models that capture the meaning of information and organize it in ways that are computer-based, but human understandable. A recent paper that examines certain assumptions in information modeling builds a bridge between these two communities, offering a forum for a discussion on common aims from a common perspective. In a June 2000 article, Parsons and Wand separate classes from instances in information modeling in order to free instances from what they call the “tyranny” of classes. They attribute a number of problems in information modeling to inherent classification – or the disregard for the fact that instances can be conceptualized independent of any class assignment. By faceting instances from classes, Parsons and Wand strike a sonorous chord with classification theory as understood in LIS. In the practice community and in the publications of LIS, faceted classification has shifted the paradigm of knowledge organization theory in the twentieth century. Here, with the proposal of inherent classification and the resulting layered information modeling, a clear line joins both the LIS classification theory community and the information modeling community. Both communities have their eyes turned toward networked resource discovery, and with this conceptual conjunction a new paradigmatic conversation can take place. Parsons and Wand propose that the layered information model can facilitate schema integration, schema evolution, and interoperability. These three spheres in information modeling have their own connotation, but are not distant from the aims of classification research in LIS. In this new conceptual conjunction, established by Parsons and Ward, information modeling through the layered information model, can expand the horizons of classification theory beyond LIS, promoting a cross-fertilization of ideas on the interoperability of subject access tools like classification schemes, thesauri, taxonomies, and ontologies. This paper examines the common ground between the layered information model and faceted classification, establishing a vocabulary and outlining some common principles. It then turns to the issue of schema and the horizons of conventional classification and the differences between Information Modeling and Library and Information Science. Finally, a framework is proposed that deploys an interpretation of the layered information modeling approach in a knowledge technologies context. In order to design subject access systems that will integrate, evolve and interoperate in a networked environment, knowledge organization specialists must consider a semantic class independence like Parsons and Wand propose for information modeling.

Sperimentazione di Deep Metric Loss per Self-Supervised Information Retrieval Systems su CORD19.

Dopo lo sviluppo dei primi casi di Covid-19 in Cina nell’autunno del 2019, ad inizio 2020 l’intero pianeta è precipitato in una pandemia globale che ha stravolto le nostre vite con conseguenze che non si vivevano dall’influenza spagnola. La grandissima quantità di paper scientifici in continua pubblicazione sul coronavirus e virus ad esso affini ha portato alla creazione di un unico dataset dinamico chiamato CORD19 e distribuito gratuitamente. Poter reperire informazioni utili in questa mole di dati ha ulteriormente acceso i riflettori sugli information retrieval systems, capaci di recuperare in maniera rapida ed efficace informazioni preziose rispetto a una domanda dell'utente detta query. Di particolare rilievo è stata la TREC-COVID Challenge, competizione per lo sviluppo di un sistema di IR addestrato e testato sul dataset CORD19. Il problema principale è dato dal fatto che la grande mole di documenti è totalmente non etichettata e risulta dunque impossibile addestrare modelli di reti neurali direttamente su di essi. Per aggirare il problema abbiamo messo a punto nuove soluzioni self-supervised, a cui abbiamo applicato lo stato dell'arte del deep metric learning e dell'NLP. Il deep metric learning, che sta avendo un enorme successo soprattuto nella computer vision, addestra il modello ad "avvicinare" tra loro immagini simili e "allontanare" immagini differenti. Dato che sia le immagini che il testo vengono rappresentati attraverso vettori di numeri reali (embeddings) si possano utilizzare le stesse tecniche per "avvicinare" tra loro elementi testuali pertinenti (e.g. una query e un paragrafo) e "allontanare" elementi non pertinenti. Abbiamo dunque addestrato un modello SciBERT con varie loss, che ad oggi rappresentano lo stato dell'arte del deep metric learning, in maniera completamente self-supervised direttamente e unicamente sul dataset CORD19, valutandolo poi sul set formale TREC-COVID attraverso un sistema di IR e ottenendo risultati interessanti.

Special issue: Selected papers from the sixth IFIP 2.6 working conference on visual database systems: Guest editors' introduction

While multimedia data, image data in particular, is an integral part of most websites and web documents, our quest for information so far is still restricted to text based search. To explore the World Wide Web more effectively, especially its rich repository of truly multimedia information, we are facing a number of challenging problems. Firstly, we face the ambiguous and highly subjective nature of defining image semantics and similarity. Secondly, multimedia data could come from highly diversified sources, as a result of automatic image capturing and generation processes. Finally, multimedia information exists in decentralised sources over the Web, making it difficult to use conventional content-based image retrieval (CBIR) techniques for effective and efficient search. In this special issue, we present a collection of five papers on visual and multimedia information management and retrieval topics, addressing some aspects of these challenges. These papers have been selected from the conference proceedings (Kluwer Academic Publishers, ISBN: 1-4020- 7060-8) of the Sixth IFIP 2.6 Working Conference on Visual Database Systems (VDB6), held in Brisbane, Australia, on 29–31 May 2002.

The therapeutic potential of dopamine modulators on the cardiovascular and renal systems

In the periphery, physiological dopamine increases renal blood flow, decreases renal resistance and acts on the kidney tubule to enhance natriuresis and diuresis. The loss of dopamine function may be involoved in the deterioration in kidney function associated with ageing and may have a role in the pathogenesis of hypertension and diabetes. Intravenous dopamine is used as a positive inotrope in the treatment of acute heart failure and cardiogenic shock and as a diuretic in renal failure. The clinical uses of dopamine are limited, as it must be given intravenously, and also has widespread effects. The levels of peripheral dopamine can be increased by the administration of L-dopa to increase synthesis, prodrugs to release dopamine (docarpamine, glu-dopa) or by inhibiting the breakdown of dopamine (nitecapone). Preliminary clinical trials suggest that docarpamine may be useful in patients with low cardiac output syndrome after cardiac surgery and in refractory cirrhotic ascites. Ibopamine is an agonist at dopamine D1 and D2 receptors, which may retard the progression of chronic renal failure. Gludopa is selective for the kidney thus avoiding widespread side effects. The early clinical studies with ibopamine as a diuretic in heart failure were favourable but the subsequent large mortality study showed that ibopamine increased mortality. Fenoldopam is a selective dopamine D1 receptor agonist. Intravenous fenoldopam may be useful in the treatment of hypertension associated with coronary artery bypass surgery or in hypertensive emergencies. Although our understanding of physiological and pathological roles of peripheral dopamine has been increasing rapidly in recent times, we still need more information to allow the design of clinically useful drugs that modify these roles. One priority is an orally-active selective dopamine D1 receptor agonist.

TV Recommendation and Personalization Systems: Integrating Broadcast and Video On-demand Services

he expansion of Digital Television and the convergence between conventional broadcasting and television over IP contributed to the gradual increase of the number of available channels and on demand video content. Moreover, the dissemination of the use of mobile devices like laptops, smartphones and tablets on everyday activities resulted in a shift of the traditional television viewing paradigm from the couch to everywhere, anytime from any device. Although this new scenario enables a great improvement in viewing experiences, it also brings new challenges given the overload of information that the viewer faces. Recommendation systems stand out as a possible solution to help a watcher on the selection of the content that best fits his/her preferences. This paper describes a web based system that helps the user navigating on broadcasted and online television content by implementing recommendations based on collaborative and content based filtering. The algorithms developed estimate the similarity between items and users and predict the rating that a user would assign to a particular item (television program, movie, etc.). To enable interoperability between different systems, programs characteristics (title, genre, actors, etc.) are stored according to the TV-Anytime standard. The set of recommendations produced are presented through a Web Application that allows the user to interact with the system based on the obtained recommendations.

How reporting and controlling systems can be effectively designed to support the decision-making process: The case of a Software SME

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Chemical and structural characterization of soil humic substances under agroforestry and conventional systems

Studies have proven that the agroforestry systems in the semi-arid region of the State of Ceará, Brazil, induce an increase in soil organic C levels. Notwithstanding, there is no information if this increase also results in qualitative changes in different pools of soil organic matter. The objective of this study was to verify the possible chemical and structural alterations in fulvic and humic acids of a Luvisol in areas adopting agroforestry, traditional intensive cultivation and native forest in a long-term experiment conducted in the semi-arid region of Ceará State, Brazil. The study was conducted in an experimental area of the National Goat Research Center (Embrapa) in Sobral, CE. The following treatments were evaluated: agrosilvopasture (AGP), silvopasture (SILV), intensive cultivation under fallow (ICF), and areas with native forest (NF). Soil fulvic and humic acids fractions were extracted from the 0-6 and 6-12 cm layers and characterized by elemental composition, thermogravimetry and infrared spectroscopy analyses. The elemental composition analysis of humic acids confirmed the data found for fulvic acids, showing reduction in the C, H and N levels, followed by an increase in O contents in the AGP and ICF treatments over SILV and NF. In all treatments, except to SILV in the 0-6 cm layer, the percentage of mass loss was highest (300-600 °C) for humic acids in the thermally most stable region. Despite the similarity between infrared spectra, soil fulvic acids in the SILV treatment extracted from 6-12 cm depth decrease the absorption bands at 1708 and 1408 cm-1 followed by an increase in the absorption band at 1608 cm-1 attributed to aromatic C=C groups. This behavior suggests an increase in the aromatic character of the structure. The AGP and ICF treatments, which increase the soil tilling, favored the maintenance of humic substances with a more aromatic character in the soil than SILV and NF. The less aromatic humic substances in the SILV treatment resulted in an increase of exchange sites of soil organic matter, indicating improved nutrient cycling and maintenance of productivity in the system.

Integration of Electronic Commerce and Enterprise Systems

The necessity of EC (Electronic Commerce) and enterprise systems integration is perceived from the integrated nature of enterprise systems. The proven benefits of EC to provide competitive advantages to the organizations force enterprises to adopt and integrate EC with their enterprise systems. Integration is a complex task to facilitate seamless flow of information and data between different systems within and across enterprises. Different systems have different platforms, thus to integrate systems with different platforms and infrastructures, integration technologies, such as middleware, SOA (Service-Oriented Architecture), ESB (Enterprise Service Bus), JCA (J2EE Connector Architecture), and B2B (Business-to-Business) integration standards are required. Huge software vendors, such as Oracle, IBM, Microsoft, and SAP suggest various solutions to address EC and enterprise systems integration problems. There are limited numbers of literature about the integration of EC and enterprise systems in detail. Most of the studies in this area have focused on the factors which influence the adoption of EC by enterprise or other studies provide limited information about a specific platform or integration methodology in general. Therefore, this thesis is conducted to cover the technical details of EC and enterprise systems integration and covers both the adoption factors and integration solutions. In this study, many literature was reviewed and different solutions were investigated. Different enterprise integration approaches as well as most popular integration technologies were investigated. Moreover, various methodologies of integrating EC and enterprise systems were studied in detail and different solutions were examined. In this study, the influential factors to adopt EC in enterprises were studied based on previous literature and categorized to technical, social, managerial, financial, and human resource factors. Moreover, integration technologies were categorized based on three levels of integration, which are data, application, and process. In addition, different integration approaches were identified and categorized based on their communication and platform. Also, different EC integration solutions were investigated and categorized based on the identified integration approaches. By considering different aspects of integration, this study is a great asset to the architectures, developers, and system integrators in order to integrate and adopt EC with enterprise systems.

Computational models for and from biology : simple gene assembly and reaction systems

The advancement of science and technology makes it clear that no single perspective is any longer sufficient to describe the true nature of any phenomenon. That is why the interdisciplinary research is gaining more attention overtime. An excellent example of this type of research is natural computing which stands on the borderline between biology and computer science. The contribution of research done in natural computing is twofold: on one hand, it sheds light into how nature works and how it processes information and, on the other hand, it provides some guidelines on how to design bio-inspired technologies. The first direction in this thesis focuses on a nature-inspired process called gene assembly in ciliates. The second one studies reaction systems, as a modeling framework with its rationale built upon the biochemical interactions happening within a cell. The process of gene assembly in ciliates has attracted a lot of attention as a research topic in the past 15 years. Two main modelling frameworks have been initially proposed in the end of 1990s to capture ciliates’ gene assembly process, namely the intermolecular model and the intramolecular model. They were followed by other model proposals such as templatebased assembly and DNA rearrangement pathways recombination models. In this thesis we are interested in a variation of the intramolecular model called simple gene assembly model, which focuses on the simplest possible folds in the assembly process. We propose a new framework called directed overlap-inclusion (DOI) graphs to overcome the limitations that previously introduced models faced in capturing all the combinatorial details of the simple gene assembly process. We investigate a number of combinatorial properties of these graphs, including a necessary property in terms of forbidden induced subgraphs. We also introduce DOI graph-based rewriting rules that capture all the operations of the simple gene assembly model and prove that they are equivalent to the string-based formalization of the model. Reaction systems (RS) is another nature-inspired modeling framework that is studied in this thesis. Reaction systems’ rationale is based upon two main regulation mechanisms, facilitation and inhibition, which control the interactions between biochemical reactions. Reaction systems is a complementary modeling framework to traditional quantitative frameworks, focusing on explicit cause-effect relationships between reactions. The explicit formulation of facilitation and inhibition mechanisms behind reactions, as well as the focus on interactions between reactions (rather than dynamics of concentrations) makes their applicability potentially wide and useful beyond biological case studies. In this thesis, we construct a reaction system model corresponding to the heat shock response mechanism based on a novel concept of dominance graph that captures the competition on resources in the ODE model. We also introduce for RS various concepts inspired by biology, e.g., mass conservation, steady state, periodicity, etc., to do model checking of the reaction systems based models. We prove that the complexity of the decision problems related to these properties varies from P to NP- and coNP-complete to PSPACE-complete. We further focus on the mass conservation relation in an RS and introduce the conservation dependency graph to capture the relation between the species and also propose an algorithm to list the conserved sets of a given reaction system.