Percorrer por autor "Fachada, Nuno"

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    Assessing the feasibility of OpenCL CPU implementations for agent-based simulations
    (AGENT-BASED MODELING, 2017-05) Fachada, Nuno; Rosa, Agostinho C.; Escola de Comunicação, Arquitetura, Artes e Tecnologias da Informação
    Agent-based modeling (ABM) is a bottom-up modeling approach, where each entity of the system being modeled is uniquely represented as a self-determining agent. Large scale emergent behavior in ABMs is population sensitive. As such, it is advisable that the number of agents in a simulation is able to reflect the reality of the system being modeled. This means that in domains such as social modeling, ecology, and biology, systems can contain millions or billions of individuals. Such large scale simulations are only feasible in non-distributed scenarios when the computational power of commodity processors, such as GPUs and multi-core CPUs, is fully exploited. In this paper we evaluate the feasibility of using CPU-oriented OpenCL for high-performance simulations of agent-based models. We compare a CPU-oriented OpenCL implementation of a reference ABM against a parallel Java version of the same model. We show that there are considerable gains in using CPU-based OpenCL for developing and implementing ABMs, with speedups up to 10x over the parallel Java version on a 10-core hyper-threaded CPU.
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    Automated Generation of Map Pieces for Snappable Meshes
    (ACM, 2023-04-12) Andrade, Diogo de; Fachada, Nuno
    Snappable Meshes is an algorithm that procedurally generates 3D environments by iteratively selecting and linking pre-built map pieces. These pieces are triangular meshes annotated by designers with connectors marking potential links, and bounding volumes indicating where overlaps should be avoided. In this article, we present a method for automatically generating connectors and bounding volumes from generic non-manifold triangular meshes for use with the Snappable Meshes algorithm, minimizing artist/designer work, while encouraging iteration of map piece design, an essential part of successful environment generation.
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    Biofeedback Game Design
    (2018) Luz, Filipe Costa; Fachada, Nuno; Junior, Roberto; Escola de Comunicação, Arquitetura, Artes e Tecnologias da Informação
    This project aims to explore the psychological effect of the player during gaming and how reciprocally game designers can manipulate the sensations of the player through biofeedback information (physiological sensors) and implementation of certain game mechanics.
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    cf4ocl: A C framework for OpenCL
    (Elsevier, 2017) Fachada, Nuno; Lopes, Vitor V.; Martins, Rui C.; Rosa, Agostinho C.; Escola de Comunicação, Arquitetura, Artes e Tecnologias da Informação
    OpenCL is an open standard for parallel programming of heterogeneous compute devices, such as GPUs, CPUs, DSPs or FPGAs. However, the verbosity of its C host API can hinder application development. In this paper we present cf4ocl, a software library for rapid development of OpenCL programs in pure C. It aims to reduce the verbosity of the OpenCL API, offering straightforward memory management, integrated profiling of events (e.g., kernel execution and data transfers), simple but extensible device selection mechanism and user-friendly error management. We compare two versions of a conceptual application example, one based on cf4ocl, the other developed directly with the OpenCL host API. Results show that the former is simpler to implement and offers more features, at the cost of an effectively negligible computational overhead. Additionally, the tools provided with cf4ocl allowed for a quick analysis on how to optimize the application.
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    ColorShapeLinks: A board game AI competition for educators and students
    (Elsevier, 2021-02-23) Fachada, Nuno; Escola de Comunicação, Arquitetura, Artes e Tecnologias da Informação
    ColorShapeLinks is an AI board game competition framework specially designed for students and educators in videogame development, with openness and accessibility in mind. The competition is based on an arbitrarily-sized version of the Simplexity board game, the motto of which, “simple to learn, complex to master”, is curiously also applicable to AI agents. ColorShapeLinks offers graphical and text-based frontends and a completely open and documented development framework built using industry standard tools and following software engineering best practices. ColorShapeLinks is not only a competition, but both a game and a framework which educators and students can extend and use to host their own competitions. It has been successfully used for running internal competitions in AI classes, as well as for hosting an international AI competition at the IEEE Conference on Games.
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    A computational pipeline for modeling and predicting wildfire behavior
    (SciTePress, 2022-04-24) Fachada, Nuno; Faculdade de Engenharia
    Wildfires constitute a major socioeconomic burden. While a number of scientific and technological methods have been used for predicting and mitigating wildfires, this is still an open problem. In turn, agent-based modeling is a modeling approach where each entity of the system being modeled is represented as an independent decision-making agent. It is a useful technique for studying systems that can be modeled in terms of interactions between individual components. Consequently, it is an interesting methodology for modeling wildfire behavior. In this position paper, we propose a complete computational pipeline for modeling and predicting wildfire behavior by leveraging agent-based modeling, among other techniques. This project is to be developed in collaboration with scientific and civil stakeholders, and should produce an open decision support system easily extendable by stakeholders and other interested parties. Keywords: Agent-based Modeling, High-performance Computing, Computational Intelligence, Verification and Validation, Wildfires.
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    Desafios no Ensino de Programação a Alunos de Videojogos
    (Sociedade Portuguesa de Ciências dos Videojogos, 2020-05) Fachada, Nuno; Escola de Comunicação, Arquitetura, Artes e Tecnologias da Informação
    As unidades curriculares (UCs) de programação num curso de Videojogos devem ter dois objetivos: 1) um objetivo mais geral, que consiste em fornecer aos alunos as bases que lhes permitam assimilar conceitos gerais de programação, matemática e física, bem como desenvolver o seu pensamento lógico e algorítmico; e, 2) um objetivo mais específico, que consiste na aprendizagem das ferramentas e conceitos concretos que permitam aos alunos trabalhar de forma fluída no game engine de eleição do curso. Este último objetivo enquadra as UCs de programação numa lógica top-down, pois a seleção do game engine guia a forma como os respetivos programas são preparados. Dentro desta perspetiva, as UCs de Programação devem alimentar e ter em vista possíveis colaborações com as restantes UCs, em especial as de game development puro. De forma transversal, os exemplos de aula e projetos de avaliação devem estar devidamente adaptados aos alunos em questão, de modo a tornar a exposição das matérias o mais apelativa possível. Neste documento discutiremos a forma como estes desafios estão a ser abordados na Licenciatura em Videojogos da Universidade Lusófona de Humanidades e Tecnologias.
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    Drop Project: an automatic assessment tool for programming assignments
    (Elsevier B.V., 2022-06-01) Cipriano, Bruno Pereira; Fachada, Nuno; Alves, Pedro; Faculdade de Engenharia
    Automated assessment tools (AATs) are software systems used in teaching environments to automate the evaluation of computer programs implemented by students. These tools can be used to stimulate the interest of computer science students in programming courses by providing quick feedback on their work and highlighting their mistakes. Despite the abundance of such tools, most of them are developed for a specific course and are not production-ready. Others lack advanced features that are required for certain pedagogical goals (e.g. Git integration) and/or are not flexible enough to be used with students having different computer literacy levels, such as first year and second year students. In this paper we present Drop Project (DP), an automated assessment tool built on top of the Maven build automation software. We have been using DP in our teaching activity since 2018, having received more than fifty thousand submissions between projects, classroom exercises, tests and homework assignments. The tool’s automated feedback has allowed us to raise the difficulty level of the course’s projects, while the grading process has become more efficient and consistent between different teachers. DP is an extensively tested, production-ready tool. The software’s code and documentation are available in GitHub under an open-source software license. Keywords: Automated assessment ;Computer science education; Programming education ; Unit testing
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    Enlarged PLIN5-uncoated lipid droplets in inner regions of skeletal muscle type II fibers associate with type 2 diabetes
    (Edições Universitárias Lusófonas, 2022-02) Fachada, Vasco; Rahkila, Paavo; Fachada, Nuno; Turpeinen, Tuomas; Kujala, Urho M.; Kainulainen, Heikki; Faculdade de Engenharia
    Skeletal muscle physiology remains of paramount importance in understanding insulin resistance. Due to its high lipid turnover rates, regulation of intramyocellular lipid droplets (LDs) is a key factor. Perilipin 5 (PLIN5) is one of the most critical agents in such regulation, being often referred as a protector against lipotoxicity and consequent skeletal muscle insulin resistance. We examined area fraction, size, subcellular localization and PLIN5 association of LDs in two fiber types of type 2 diabetic (T2D), obese (OB) and healthy (HC) individuals by means of fluorescence microscopy and image analysis. We found that T2D type II fibers have a significant sub-population of large and internalized LDs, uncoated by PLIN5. Based on this novel result, additional hypotheses for the pathophysiology of skeletal muscle insulin resistance are formulated, together with future research directions. Keywords: Lipid droplets, PLIN5, Type II diabetes, Skeletal muscle, Insulin resistance, Fiber type
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    Fun Maths for All Game Development Students
    (ACM, 2020-06) Andrade, Diogo de; Fachada, Nuno; Escola de Comunicação, Arquitetura, Artes e Tecnologias da Informação
    We present an approach for teaching maths to game development undergraduates from a wide variety of backgrounds. We discuss the concepts behind an introductory maths course, its assessment and put forward some preliminary results on a practical implementation.
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    generateData—A 2D data generator
    (Elsevier B.V., 2020-05) Fachada, Nuno; Rosa, Agostinho C.; Escola de Comunicação, Arquitetura, Artes e Tecnologias da Informação
    generateData is a MATLAB/Octave function for generating 2D data clusters. Data is created along straight lines, which can be more or less parallel depending on the selected input parameters. The function also allows to fine-tune the generated data with respect to number of clusters, total data points, average cluster separation and several other distributional properties.
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    Generating multidimensional clusters with support lines
    (Elsevier, 2023) Fachada, Nuno; de Andrade, Diogo; Faculdade de Engenharia
    Synthetic data is essential for assessing clustering techniques, complementing and extending real data, and allowing for more complete coverage of a given problem’s space. In turn, synthetic data generators have the potential of creating vast amounts of data – a crucial activity when real-world data is at premium – while providing a well-understood generation procedure and an interpretable instrument for methodically investigating cluster analysis algorithms. Here, we present Clugen, a modular procedure for synthetic data generation, capable of creating multidimensional clusters supported by line segments using arbitrary distributions. Clugen is open source, comprehensively unit tested and documented, and is available for the Python, R, Julia, and MATLAB/Octave ecosystems. We demonstrate that our proposal can produce rich and varied results in various dimensions, is fit for use in the assessment of clustering algorithms, and has the potential to be a widely used framework in diverse clustering-related research tasks. Keywords: Synthetic data, Clustering, Data generation, Multidimensional data
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    Humans vs AI : an exploratory study with online and offline learners
    (Springer Nature, 2024-01-02) Inácio, João; Fachada, Nuno; Carvalho, João P. Matos; Fernandes, Carlos M.
    We present an exploratory study comparing human player performance against online and offline AI learning techniques—the Naive Bayes Classifier and Genetic Algorithms, respectively—using a simple turn-based game. Human player performance is also assessed according to gender, age, experience playing games, and boredom level during game sessions. Human players and AI techniques are shown to obtain statistically equivalent score distributions. No gender performance differences were found, although performance seems to decrease with age. To a lesser extent, performance appears to improve with self-assessed experience and boredom levels. This study offers a base for more comprehensive experiments, suggesting various directions for future research.
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    A method for detecting statistically significant differences in EEG data
    (OHBM, 2017) Fachada, Nuno; Cruz, Janir R. da; Herzog, Michael H.; Figueiredo, Patrícia; Rosa, Agostinho C.; Escola de Comunicação, Arquitetura, Artes e Tecnologias da Informação
    The highly multivariate nature of EEG data often limits the search for statistically significant differences in data collected from two or more groups of subjects. We have recently developed a new technique for assessing whether two or more multidimensional samples are drawn from the same distribution. Here, we apply this to EEG data collected from schizophrenia patients and healthy controls while performing a Visual Backward Masking (VBM) task.
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    micompm: A MATLAB/Octave toolbox for multivariate independent comparison of observations
    (JOSS, 2018) Fachada, Nuno; Rosa, Agostinho C.; Escola de Comunicação, Arquitetura, Artes e Tecnologias da Informação
    micompm is a MATLAB / GNU Octave port of the original micompr R package for comparing multivariate samples associated with different groups. Its purpose is to determine if the compared samples are significantly different from a statistical point of view. This method uses principal component analysis to convert multivariate observations into a set of linearly uncorrelated statistical measures, which are then compared using statistical tests and score plots. This technique is independent of the distributional properties of samples and automatically selects features that best explain their differences, avoiding manual selection of specific points or summary statistics. The procedure is appropriate for comparing samples of time series, images, spectrometric measures or similar multivariate observations. It is aimed at researchers from all fields of science, although it requires some knowledge on design of experiments, statistical testing and multidimensional data analysis.
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    MN-DS: A Multilabeled News Dataset for News Articles Hierarchical Classification
    (Multidisciplinary Digital Publishing Institute (MDPI), 2023-04-23) Petukhova, Alina; Fachada, Nuno; Faculdade de Engenharia; COPELABS (FCT) - Centro de Investigação em Computação Centrada nas Pessoas e Cognição (CTS)
    This article presents a dataset of 10,917 news articles with hierarchical news categories collected between 1 January 2019 and 31 December 2019. We manually labeled the articles based on a hierarchical taxonomy with 17 first-level and 109 second-level categories. This dataset can be used to train machine learning models for automatically classifying news articles by topic. This dataset can be helpful for researchers working on news structuring, classification, and predicting future events based on released news. Keywords: news dataset; text classification; NLP; media topic taxonomy
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    Model-independent comparison of simulation output
    (Elsevier, 2017) Fachada, Nuno; Lopes, Vitor V.; Martins, Rui C.; Rosa, Agostinho C.; Escola de Comunicação, Arquitetura, Artes e Tecnologias da Informação
    Computational models of complex systems are usually elaborate and sensitive to implementation details, characteristics which often affect their verification and validation. Model replication is a possible solution to this issue. It avoids biases associated with the language or toolkit used to develop the original model, not only promoting its verification and validation, but also fostering the credibility of the underlying conceptual model. However, different model implementations must be compared to assess their equivalence. The problem is, given two or more implementations of a stochastic model, how to prove that they display similar behavior? In this paper, we present a model comparison technique, which uses principal component analysis to convert simulation output into a set of linearly uncorrelated statistical measures, analyzable in a consistent, model-independent fashion. It is appropriate for ascertaining distributional equivalence of a model replication with its original implementation. Besides model-independence, this technique has three other desirable properties: a) it automatically selects output features that best explain implementation differences; b) it does not depend on the distributional properties of simulation output; and, c) it simplifies the modelers’ work, as it can be used directly on simulation outputs. The proposed technique is shown to produce similar results to the manual or empirical selection of output features when applied to a well-studied reference model.
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    Modelling physiological sensor noise to movement-based virtual reality activities
    (Scitepress, 2024-01-01) Lopes, Phil; Fachada, Nuno; Fonseca, Micaela; Gamboa, Hugo; Quaresma, Claudia; Faculdade de Engenharia
    This position paper proposes the hypothesis that physiological noise artefacts can be classified based on the type of movements performed by participants in Virtual Reality contexts. To assess this hypothesis, a detailed research plan is proposed to study the influence of movement on the quality of the captured physiological signals. This paper argues that the proposed plan can produce a valid model for classifying noisy physiological signal features, providing insights into the influence of movement on artefacts, while contributing to the development of movement-based filters and the implementation of best practices for using various associated technologies.
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    Parallelization strategies for spatial agent-based models
    (Springer New York, 2017) Fachada, Nuno; Lopes, Vitor V.; Martins, Rui C.; Rosa, Agostinho C.; Escola de Comunicação, Arquitetura, Artes e Tecnologias da Informação
    Agent-based modeling (ABM) is a bottom-up modeling approach, where each entity of the system being modeled is uniquely represented as an independent decision-making agent. Large scale emergent behavior in ABMs is population sensitive. As such, the number of agents in a simulation should be able to reflect the reality of the system being modeled, which can be in the order of millions or billions of individuals in certain domains. A natural solution to reach acceptable scalability in commodity multi-core processors consists of decomposing models such that each component can be independently processed by a different thread in a concurrent manner. In this paper we present a multithreaded Java implementation of the PPHPC ABM, with two goals in mind: (1) compare the performance of this implementation with an existing NetLogo implementation; and, (2) study how different parallelization strategies impact simulation performance on a shared memory architecture. Results show that: (1) model parallelization can yield considerable performance gains; (2) distinct parallelization strategies offer specific trade-offs in terms of performance and simulation reproducibility; and, (3) PPHPC is a valid reference model for comparing distinct implementations or parallelization strategies, from both performance and statistical accuracy perspectives.
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    ParShift: a Python package to study order and differentiation in group conversations
    (Elsevier B.V., 2023-12-01) Carvalho, João P. Matos; Fachada, Nuno; Pita, Manuel Arturo Marques; Saraiva, Bruno David Ferreira; Matos-Carvalho, João Pedro; COPELABS (FCT) - Centro de Investigação em Computação Centrada nas Pessoas e Cognição (CTS); CICANT (FCT) - Centro de Investigação em Comunicação Aplicada, Cultura e Novas Tecnologias; Escola de Comunicação, Arquitetura, Artes e Tecnologias da Informação
    Collective organization in multi-party conversations emerges through the exchange of utterances between participants. While most research has focused on content-centred mechanisms that lead to emergent conversational coordination, less attention has been given to explaining conversational order based on who is addressed and who responds, especially when dealing with large conversational datasets. In this paper, we introduce a Python library, ParShift, that implements a state-of-the-art theoretical quantitative framework known as Participation Shifts. This framework enables researchers to study participant-centred order and differentiation in multi-party conversations. With ParShift, researchers can characterize conversations by quantifying the probabilities of events related to how people address each other during conversations. This library is particularly useful for studying conversation threads in social networks, parliamentary debates, team meetings, or student debates on a large scale. Keywords: Small groups Social interaction Participation shifts Interpersonal coordination Turn-taking Emergent social behaviour