CRACS

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http://localhost:4000/handle/123456789/28
This service develops its activity in the areas of programming languages, parallel and distributed computing, data mining, intelligent systems and software architecture, with emphasis on solving concrete problems in areas of multidisciplinary collaboration, such as Biology, Medicine and Chemistry.

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  • Item
    Mapping e-Learning Interactions using Social Network Analysis
    ( 2009) Álvaro Figueira
    The interactions that occur among participants in online forums frequently are an important criteria in evaluating learning methodologies practiced in e-learning contexts. Not only are the interactions between peers an important resource of information, but also, the way the teacher interacts with students. However, apart from general statistics available in common online learning platforms, this type of information is difficult to retrieve. A graphical mapping based on social network analysis theory, of such interactions that occur in online environments, is proposed as a possible solution for automatically depicting and analyzing relations that are established between participants in online forums. In this paper we present a system which provides learning management systems with an additional tool for graphically mapping and analyzing student-student and teacher-student interactions. The system represents both current network interactions and a historical graphical slideshow of online interactions between participants.
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    Threads and Or-Parallelism Unified
    ( 2010) Inês Dutra ; Vítor Santos Costa ; Ricardo Rocha
    One of the main advantages of Logic Programming (LP) is that it provides an excellent framework for the parallel execution of programs. In this work we investigate novel techniques to efficiently exploit parallelism from real-world applications in low cost multi-core architectures. To achieve these goals, we revive and redesign the YapOr system to exploit or-parallelism based on a multi-threaded implementation. Our new approach takes full advantage of the state-of-the-art fast and optimized YAP Prolog engine and shares the underlying execution environment, scheduler and most of the data structures used to support YapOr's model. Initial experiments with our new approach consistently achieve almost linear speedups for most of the applications, proving itself as a good alternative for exploiting implicit parallelism in the currently available low cost multi-core architectures.
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    Gödel's system T revisited
    ( 2010) Ian Mackie ; Sandra Alves ; Maribel Fernández ; Mário Florido
    The linear lambda calculus, where variables are restricted to occur in terms exactly once, has a very weak expressive power: in particular, all functions terminate in linear time. In this paper we consider a simple extension with natural numbers and a restricted iterator: only closed linear functions can be iterated. We show properties of this linear version of Godel's T using a closed reduction strategy, and study the class of functions that can be represented. Surprisingly, this linear calculus offers a huge increase in expressive power over previous linear versions of T, which are 'closed at construction' rather than 'closed at reduction'. We show that a linear T with closed reduction is as powerful as T.
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    Information measures for infinite sequences
    ( 2010) Luís Filipe Antunes ; André Souto
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    Temporal Anomaly Detection: An Artificial Immune Approach Based on T Cell Activation, Clonal Size Regulation and Homeostasis
    ( 2010) Manuel Eduardo Correia ; Mário João Antunes
    This paper presents an artificial immune system (AIS) based on Grossman's tunable activation threshold (TAT) for temporal anomaly detection. We describe the generic AIS framework and the TAT model adopted for simulating T Cells behaviour, emphasizing two novel important features: the temporal dynamic adjustment of T Cells clonal size and its associated homeostasis mechanism. We also present some promising results obtained with artificially generated data sets, aiming to test the appropriateness of using TAT in dynamic changing environments, to distinguish new unseen patterns as part of what should be detected as normal or as anomalous. We conclude by discussing results obtained thus far with artificially generated data sets.
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    On the implementation of the probabilistic logic programming language ProbLog
    ( 2011) Vítor Santos Costa ; Angelika Kimmig ; Bart Demoen ; Luc De Raedt ; Ricardo Rocha
    The past few years have seen a surge of interest in the field of probabilistic logic learning and statistical relational learning. In this endeavor, many probabilistic logics have been developed. ProbLog is a recent probabilistic extension of Prolog motivated by the mining of large biological networks. In ProbLog, facts can be labeled with probabilities. These facts are treated as mutually independent random variables that indicate whether these facts belong to a randomly sampled program. Different kinds of queries can be posed to ProbLog programs. We introduce algorithms that allow the efficient execution of these queries, discuss their implementation on top of the YAP-Prolog system, and evaluate their performance in the context of large networks of biological entities.
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    Entropy Measures vs. Kolmogorov Complexity
    ( 2011) André Souto ; Luís Filipe Antunes ; Andreia Teixeira ; Armando Matos
    Kolmogorov complexity and Shannon entropy are conceptually different measures. However, for any recursive probability distribution, the expected value of Kolmogorov complexity equals its Shannon entropy, up to a constant. We study if a similar relationship holds for R´enyi and Tsallis entropies of order α, showing that it only holds for α = 1. Regarding a time-bounded analogue relationship, we show that, for some distributions we have a similar result. We prove that, for universal time-bounded distribution mt(x), Tsallis and Rényi entropies converge if and only if α is greater than 1. We also establish the uniform continuity of these entropies.
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    Clustering distributed sensor data streams using local processing and reduced communication
    ( 2011) João Gama ; Pedro Pereira Rodrigues ; Luís Lopes
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    On Combining Linear-Based Strategies for Tabled Evaluation of Logic Programs
    ( 2011) Miguel Gonçalves Areias ; Ricardo Rocha
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    Towards Multi-Threaded Local Tabling Using a Common Table Space
    ( 2012) Miguel Gonçalves Areias ; Ricardo Rocha
    Multi-threading is currently supported by several well-known Prolog systems providing a highly portable solution for applications that can benefit from concurrency. When multi-threading is combined with tabling, we can exploit the power of higher procedural control and declarative semantics. However, despite the availability of both threads and tabling in some Prolog systems, the implementation of these two features implies complex ties to each other and to the underlying engine. Until now, XSB was the only Prolog system combining multi-threading with tabling. In XSB, tables may be either private or shared between threads. While thread-private tables are easier to implement, shared tables have all the associated issues of locking, synchronization and potential deadlocks. In this paper, we propose an alternative view to XSB's approach. In our proposal, each thread views its tables as private but, at the engine level, we use a common table space where tables are shared among all threads.
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    Predicting Ramp Events with a Stream-based HMM framework (Extended Abstract)
    ( 2012) Vítor Santos Costa ; Audun Botterud ; Vladimiro Miranda ; Carlos Ferreira ; João Gama
    The motivation for this work is the study and prediction of wind ramp events occurring in a large-scale wind farm located in the US Midwest. In this paper we introduce the SHREA framework, a stream-based model that continuously learns a discrete HMM model from wind power and wind speed measurements. We use a supervised learning algorithm to learn HMM parameters from discretized data, where ramp events are HMM states and discretized wind speed data are HMM observations. The discretization of the historical data is obtained by running the SAX algorithm over the first order v ariations in the original signal. SHREA updates the HMM using the most recent historical data and includes a orgetting mechanism to model natural time dependence in wind patterns. To forecast ramp events we use recent wind speed forecasts and the Viterbi algorithm, that incrementally finds the most probable ramp event to occur.
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    Predicting Ramp Events with a Stream-based HMM framework
    ( 2012) João Gama ; Audun Botterud ; Vladimiro Miranda ; Vítor Santos Costa ; Carlos Ferreira
    The motivation for this work is the study and prediction of wind ramp events occurring in a large-scale wind farm located in the US Midwest. In this paper we introduce the SHRED framework, a stream-based model that continuously learns a discrete HMM model from wind power and wind speed measurements. We use a supervised learning algorithm to learn HMM parameters from discretized data, where ramp events are HMM states and discretized wind speed data are HMM observations. The discretization of the historical data is obtained by running the SAX algorithm over the rst order variations in the original signal. SHRED updates the HMM using the most recent historical data and includes a forgetting mechanism to model natural time dependence in wind patterns. To forecast ramp events we use recent wind speed forecasts and the Viterbi algorithm, that incrementally nds the most probable ramp event to occur.
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    A design and implementation of the Extended Andorra Model
    ( 2012) Ricardo Lopes ; Vítor Santos Costa ; Fernando Silva
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    Security and privacy issues for the network of the future
    ( 2012) Tiago Travassos Vinhoza ; Paulo F. Oliveira ; Hermann de Meer ; Wojciech Mazurczyk ; Charlott Lorentzen ; Luisa Lima ; Alessandro Lentini ; Antonio Grillo ; Ralph Herkenhoener ; Harald Hauff ; Andreas Fischer ; Markus Fiedler ; João Barros ; Giannis F. Marias ; João P. Vilela ; Krzysztof Szczypiorski ; Enric Pujol ; George C. Polyzos1
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    Studying a Personality Coreference Network in a News Stories Photo Collection
    ( 2012) Cristina Ribeiro ; José Luís Devezas ; Filipe Emanuel Coelho ; Sérgio Nunes
    We build and analyze a coreference network based on entities from photo descriptions, where nodes represent personalities and edges connect people mentioned in the same photo description. We identify and characterize the communities in this network and propose taking advantage of the context provided by community detection methodologies to improve text illustration and general search.
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    Predicting the secondary structure of proteins using Machine Learning algorithms
    ( 2012) Nuno Fonseca ; Vítor Santos Costa ; Alexandre Magalhães ; Miguel de Sousa ; Vânia Guimarães ; Natacha Rosa ; Rui Camacho ; Rita Ferreira
    The functions of proteins in living organisms are related to their 3-D structure, which is known to be ultimately determined by their linear sequence of amino acids that together form these macromolecules. It is, therefore, of great importance to be able to understand and predict how the protein 3D- structure arises from a particular linear sequence of amino acids. In this paper we report the application of Machine Learning methods to predict, with high values of accuracy, the secondary structure of proteins, namely α-helices and ß-sheets, which are intermediate levels of the local structure.
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    The Yap Prolog System
    ( 2012) Vítor Santos Costa ; Ricardo Rocha ; Luís Damas
    Yet Another Prolog (YAP) is a Prolog system originally developed in the mid-eighties and that has been under almost constant development since then. This paper presents the general structure and design of the YAP system, focusing on three important contributions to the Logic Programming community. First, it describes the main techniques used in YAP to achieve an efficient Prolog engine. Second, most Logic Programming systems have a rather limited indexing algorithm. YAP contributes to this area by providing a dynamic indexing mechanism, or just-in-time indexer. Third, a important contribution of the YAP system has been the integration of both or-parallelism and tabling in a single Logic Programming system.
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    Parallel discovery of network motifs
    ( 2012) Fernando Silva ; Pedro Manuel Ribeiro ; Luís Lopes
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