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Background: The burden of Rheumatic Heart Disease (RHD) is concentrated in low-income countries, where health resources are scarce. Echocardiographic (echo) screening is the gold standard...
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In this paper we propose Fractal, a high performance and high productivity system for supporting distributed graph pattern mining (GPM) applications. Fractal employs a dynamic (auto-tuned) load-balancing based on a hierarchical and locality-aware work stealing mechanism, allowing the system to adapt to diferent workload characteristics. Additionally, Fractal enumerates subgraphs by combining a depth-irst strategy with a from scratch processing paradigm to avoid storing large amounts of intermediate state and, thus, improves memory efficiency. Regarding programmer productivity,...
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Abstract: The increase in sophistication and complexity of recommendation algorithms has turned them into black boxes where the algorithmic reasoning behind the predictions is hard to understand by users. A popular approach for increasing model interpretability in the machine learning community is the Locally Interpretable Model-agnostic Explanations (LIME), which proposes to learn local interpretable models for explaining single predictions...
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Most of the modern cloud web services execute on top of runtime environments like .NET’s Common Language Runtime or Java Runtime Environment. On the one hand, runtime environments provide several off-the-shelf benefits like code security and cross-platform execution. On the other hand, runtime’s features such as just-in-time compilation and...
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Trustworthiness is a paramount concern for users and customers in the selection of a software solution, specially in the context of complex and dynamic environments, such as Cloud and IoT. However, assessing and benchmarking trustworthiness (worthiness of software for being trusted) is a challenging task, mainly due to the variety of application scenarios (e.g., business critical, safety-critical),...
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The growing complexity of software makes it difficult or even impossible to detect all faults before deployment, and such residual faults eventually lead to failures at runtime. Online Failure Prediction (OFP) is a technique that attempts to avoid or mitigate such failures by predicting their occurrence based on the analysis of past data and the current state of a system. Given recent technological developments, Machine Learning (ML) algorithms have shown their ability...
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The widespread misuse of cryptography in software systems is the most frequent source of cryptography-related security problems. Several misuses of cryptography have been found to be recurrent in software in general, resulting in vulnerabilities exploitable in real attacks. There is a huge gap between what cryptologists see as misuses of cryptography and what developers see as unsafe use of cryptographic technology. This chapter contributes to fill this gap by addressing the...
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Big Data Analytics are indispensable components of architectures dealing with processing and visualizing results of diverse healthcare-related information sources. In this work, we propose a versatile cloud design where the Health Analytic Tools (HATs) are decoupled from the Datastore and the User-Interface parts, still preserving the element of system trust. This design offers advantages over the process of modifying and...
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We are often unable to plan menus ahead, thus making poor and unhealthy choices of meals. Besides healthy, one may want menus in which ingredients harmonize and cover well the available ingredients in the pantry. In this paper, we propose a novel multi-objective-based recommender of menus that features an optimal balance between nutritional aspects, harmony and coverage of...
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Several systems for processing keyword queries over relational databases rely on the generation and evaluation of Candidate Networks (CNs), i.e., networks of joined relations that when processed as SQL queries, provide a relevant answer to the input keyword query. Although the evaluation of CNs has...
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ATMOSPHERE is funded by the European Union under the Cooperation Programme, Horizon 2020 grant agreement No 777154. Este projeto é resultante da 4ª Chamada Coordenada BR-UE em Tecnologias da Informação e Comunicação (TIC), anunciada pela Rede Nacional de Ensino e Pesquisa (RNP) e pelo Ministério da Ciência, Tecnologia, Inovações e Comunicações (MCTIC), no âmbito to acordo de cooperação Número 51119. Privacy Policy | Disclaimer / Terms of use
