Characterization and application of the solid waste generated in the production of calcium carbonate precipitate as a corrective for the soil acidity

The calcium carbonate industry generates solid waste products which, because of their high alkaline content (CaO, CaCO(3) and Ca (OH)(2)), have a substantial impact on the environment. The objectives of this study are to characterize and classify the solid waste products, which are generated during the hydration process of the calcium carbonate industry, according to ABNT`s NBR 10.000 series, and to determine the potential and efficiency of using these solid residues to correct soil acidity. Initially, the studied residue was submitted to gross mass, leaching, solubility, pH. X-ray Diffractometry, Inductive Coupled Plasma - Atomic Emission Spectrometry (ICP-AES), granularity and humidity analyses. The potential and efficiency of the residue for correcting soil acidity was determined by analysis of the quality attributes for soil correctives (PN, PRNT, Ca and Mg contents, granularity). Consequently, the results show that the studied residue may be used as a soil acidity corrective, considering that a typical corrective compound is recommended for each different type of soil. Additionally, the product must be further treated (dried and ground) to suit the specific requirements of the consumer market.

Researchers' information needs in the bibliographic database : a literature review

This article is published online with Open Access and distributed under the terms of the Creative Commons Attribution Non-Commercial License.

Integração e contextualização de modelos 3D no ensino da área da saúde

Mestrado em Engenharia Informática. Sistemas Gráficos e Multimédia.

Calculating an upper bound on the finishing time of a group of threads executing on a GPU: a preliminary case study

Graphics processor units (GPUs) today can be used for computations that go beyond graphics and such use can attain a performance that is orders of magnitude greater than a normal processor. The software executing on a graphics processor is composed of a set of (often thousands of) threads which operate on different parts of the data and thereby jointly compute a result which is delivered to another thread executing on the main processor. Hence the response time of a thread executing on the main processor is dependent on the finishing time of the execution of threads executing on the GPU. Therefore, we present a simple method for calculating an upper bound on the finishing time of threads executing on a GPU, in particular NVIDIA Fermi. Developing such a method is nontrivial because threads executing on a GPU share hardware resources at very fine granularity.

Robot visual localization through local feature fusion: an evaluation of multiple classifiers combination approaches

In the last decade, local image features have been widely used in robot visual localization. In order to assess image similarity, a strategy exploiting these features compares raw descriptors extracted from the current image with those in the models of places. This paper addresses the ensuing step in this process, where a combining function must be used to aggregate results and assign each place a score. Casting the problem in the multiple classifier systems framework, in this paper we compare several candidate combiners with respect to their performance in the visual localization task. For this evaluation, we selected the most popular methods in the class of non-trained combiners, namely the sum rule and product rule. A deeper insight into the potential of these combiners is provided through a discriminativity analysis involving the algebraic rules and two extensions of these methods: the threshold, as well as the weighted modifications. In addition, a voting method, previously used in robot visual localization, is assessed. Furthermore, we address the process of constructing a model of the environment by describing how the model granularity impacts upon performance. All combiners are tested on a visual localization task, carried out on a public dataset. It is experimentally demonstrated that the sum rule extensions globally achieve the best performance, confirming the general agreement on the robustness of this rule in other classification problems. The voting method, whilst competitive with the product rule in its standard form, is shown to be outperformed by its modified versions.

Multy-dimensional composition by objectives in aspect-oriented requirements analysis

Thesis submitted to Faculdade de Ciências e Tecnologia of Universidade Nova de Lisboa in partial fulfilment of the requirements for the degree of Master in Computer Science

Tuning metadata for better movie content-based recommendation systems

The increasing number of television channels, on-demand services and online content, is expected to contribute to a better quality of experience for a costumer of such a service. However, the lack of efficient methods for finding the right content, adapted to personal interests, may lead to a progressive loss of clients. In such a scenario, recommendation systems are seen as a tool that can fill this gap and contribute to the loyalty of users. Multimedia content, namely films and television programmes are usually described using a set of metadata elements that include the title, a genre, the date of production, and the list of directors and actors. This paper provides a deep study on how the use of different metadata elements can contribute to increase the quality of the recommendations suggested. The analysis is conducted using Netflix and Movielens datasets and aspects such as the granularity of the descriptions, the accuracy metric used and the sparsity of the data are taken into account. Comparisons with collaborative approaches are also presented.

IPTV data reduction strategy to measure real users’ behaviours

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

An agent based architecture to support monitoring in plug and produce manufacturing systems using knowledge extraction

In recent years a set of production paradigms were proposed in order to capacitate manufacturers to meet the new market requirements, such as the shift in demand for highly customized products resulting in a shorter product life cycle, rather than the traditional mass production standardized consumables. These new paradigms advocate solutions capable of facing these requirements, empowering manufacturing systems with a high capacity to adapt along with elevated flexibility and robustness in order to deal with disturbances, like unexpected orders or malfunctions. Evolvable Production Systems propose a solution based on the usage of modularity and self-organization with a fine granularity level, supporting pluggability and in this way allowing companies to add and/or remove components during execution without any extra re-programming effort. However, current monitoring software was not designed to fully support these characteristics, being commonly based on centralized SCADA systems, incapable of re-adapting during execution to the unexpected plugging/unplugging of devices nor changes in the entire system’s topology. Considering these aspects, the work developed for this thesis encompasses a fully distributed agent-based architecture, capable of performing knowledge extraction at different levels of abstraction without sacrificing the capacity to add and/or remove monitoring entities, responsible for data extraction and analysis, during runtime.

Scaling In-Memory databases on multicores

Current computer systems have evolved from featuring only a single processing unit and limited RAM, in the order of kilobytes or few megabytes, to include several multicore processors, o↵ering in the order of several tens of concurrent execution contexts, and have main memory in the order of several tens to hundreds of gigabytes. This allows to keep all data of many applications in the main memory, leading to the development of inmemory databases. Compared to disk-backed databases, in-memory databases (IMDBs) are expected to provide better performance by incurring in less I/O overhead. In this dissertation, we present a scalability study of two general purpose IMDBs on multicore systems. The results show that current general purpose IMDBs do not scale on multicores, due to contention among threads running concurrent transactions. In this work, we explore di↵erent direction to overcome the scalability issues of IMDBs in multicores, while enforcing strong isolation semantics. First, we present a solution that requires no modification to either database systems or to the applications, called MacroDB. MacroDB replicates the database among several engines, using a master-slave replication scheme, where update transactions execute on the master, while read-only transactions execute on slaves. This reduces contention, allowing MacroDB to o↵er scalable performance under read-only workloads, while updateintensive workloads su↵er from performance loss, when compared to the standalone engine. Second, we delve into the database engine and identify the concurrency control mechanism used by the storage sub-component as a scalability bottleneck. We then propose a new locking scheme that allows the removal of such mechanisms from the storage sub-component. This modification o↵ers performance improvement under all workloads, when compared to the standalone engine, while scalability is limited to read-only workloads. Next we addressed the scalability limitations for update-intensive workloads, and propose the reduction of locking granularity from the table level to the attribute level. This further improved performance for intensive and moderate update workloads, at a slight cost for read-only workloads. Scalability is limited to intensive-read and read-only workloads. Finally, we investigate the impact applications have on the performance of database systems, by studying how operation order inside transactions influences the database performance. We then propose a Read before Write (RbW) interaction pattern, under which transaction perform all read operations before executing write operations. The RbW pattern allowed TPC-C to achieve scalable performance on our modified engine for all workloads. Additionally, the RbW pattern allowed our modified engine to achieve scalable performance on multicores, almost up to the total number of cores, while enforcing strong isolation.

Task clustering on ETL systems – A pattern-oriented approach

Usually, data warehousing populating processes are data-oriented workflows composed by dozens of granular tasks that are responsible for the integration of data coming from different data sources. Specific subset of these tasks can be grouped on a collection together with their relationships in order to form higher- level constructs. Increasing task granularity allows for the generalization of processes, simplifying their views and providing methods to carry out expertise to new applications. Well-proven practices can be used to describe general solutions that use basic skeletons configured and instantiated according to a set of specific integration requirements. Patterns can be applied to ETL processes aiming to simplify not only a possible conceptual representation but also to reduce the gap that often exists between two design perspectives. In this paper, we demonstrate the feasibility and effectiveness of an ETL pattern-based approach using task clustering, analyzing a real world ETL scenario through the definitions of two commonly used clusters of tasks: a data lookup cluster and a data conciliation and integration cluster.

A modular traffic sampling architecture for flexible network measurements

Dissertação de Mestrado (Programa Doutoral em Informática)

Una infraestructura de metadades bibliogràfiques pel segle XXI

Aquest article tracta l'actual infraestructura bibliogràfica de les biblioteques que va ser creada en els inicis dels ordinadors – abans de la Web, XML, i de la varietat d'altres avenços tecnològics que en l'actualitat ofereixen noves oportunitats. Per una banda, s'identifiquen els requisits generals d'una infraestructura de metadades moderna per a les biblioteques incloent qualitats com: versatilitat, extensibilitat, granularitat i accessibilitat. Per l'altra banda, es proposa un nou tipus d'infraestructura de metadades que mostra, com a mínim, alguna d'aquestes qualitats. S'han identificat alguns temes clau que caldrà superar per tal d'implementar un canvi d'aquesta magnitud.

Análisis y sintonización de aplicaciones paralelas/distribuidas de bioinformática: caso de estudio mpiBLAST

En termes de temps d'execució i ús de dades, les aplicacions paral·leles/distribuïdes poden tenir execucions variables, fins i tot quan s'empra el mateix conjunt de dades d'entrada. Existeixen certs aspectes de rendiment relacionats amb l'entorn que poden afectar dinàmicament el comportament de l'aplicació, tals com: la capacitat de la memòria, latència de la xarxa, el nombre de nodes, l'heterogeneïtat dels nodes, entre d'altres. És important considerar que l'aplicació pot executar-se en diferents configuracions de maquinari i el desenvolupador d'aplicacions no port garantir que els ajustaments de rendiment per a un sistema en particular continuïn essent vàlids per a d'altres configuracions. L'anàlisi dinàmica de les aplicacions ha demostrat ser el millor enfocament per a l'anàlisi del rendiment per dues raons principals. En primer lloc, ofereix una solució molt còmoda des del punt de vista dels desenvolupadors mentre que aquests dissenyen i evaluen les seves aplicacions paral·leles. En segon lloc, perquè s'adapta millor a l'aplicació durant l'execució. Aquest enfocament no requereix la intervenció de desenvolupadors o fins i tot l'accés al codi font de l'aplicació. S'analitza l'aplicació en temps real d'execució i es considra i analitza la recerca dels possibles colls d'ampolla i optimitzacions. Per a optimitzar l'execució de l'aplicació bioinformàtica mpiBLAST, vam analitzar el seu comportament per a identificar els paràmetres que intervenen en el rendiment d'ella, com ara: l'ús de la memòria, l'ús de la xarxa, patrons d'E/S, el sistema de fitxers emprat, l'arquitectura del processador, la grandària de la base de dades biològica, la grandària de la seqüència de consulta, la distribució de les seqüències dintre d'elles, el nombre de fragments de la base de dades i/o la granularitat dels treballs assignats a cada procés. El nostre objectiu és determinar quins d'aquests paràmetres tenen major impacte en el rendiment de les aplicacions i com ajustar-los dinàmicament per a millorar el rendiment de l'aplicació. Analitzant el rendiment de l'aplicació mpiBLAST hem trobat un conjunt de dades que identifiquen cert nivell de serial·lització dintre l'execució. Reconeixent l'impacte de la caracterització de les seqüències dintre de les diferents bases de dades i una relació entre la capacitat dels workers i la granularitat de la càrrega de treball actual, aquestes podrien ser sintonitzades dinàmicament. Altres millores també inclouen optimitzacions relacionades amb el sistema de fitxers paral·lel i la possibilitat d'execució en múltiples multinucli. La grandària de gra de treball està influenciat per factors com el tipus de base de dades, la grandària de la base de dades, i la relació entre grandària de la càrrega de treball i la capacitat dels treballadors.

Allergen-induced IgE-dependent gut inflammation in a human PBMC-engrafted murine model of allergy.

BACKGROUND: Humanized murine models comprise a new tool to analyze novel therapeutic strategies for allergic diseases of the intestine.¦OBJECTIVE: In this study we developed a human PBMC-engrafted murine model of allergen-driven gut inflammation and analyzed the underlying immunologic mechanisms.¦METHODS: Nonobese diabetic (NOD)-scid-γc(-/-) mice were injected intraperitoneally with human PBMCs from allergic donors together with the respective allergen or not. Three weeks later, mice were challenged with the allergen orally or rectally, and gut inflammation was monitored with a high-resolution video miniendoscopic system, as well as histologically.¦RESULTS: Using the aeroallergens birch or grass pollen as model allergens and, for some donors, also hazelnut allergen, we show that allergen-specific human IgE in murine sera and allergen-specific proliferation and cytokine production of human CD4(+) T cells recovered from spleens after 3 weeks could only be measured in mice treated with PBMCs plus allergen. Importantly, these mice had the highest endoscopic scores evaluating translucent structure, granularity, fibrin, vascularity, and stool after oral or rectal allergen challenge and a strong histologic inflammation of the colon. Analyzing the underlying mechanisms, we demonstrate that allergen-associated colitis was dependent on IgE, human IgE receptor-expressing effector cells, and the mediators histamine and platelet-activating factor.¦CONCLUSION: These results demonstrate that allergic gut inflammation can be induced in human PBMC-engrafted mice, allowing the investigation of pathophysiologic mechanisms of allergic diseases of the intestine and evaluation of therapeutic interventions.