1101 |
Shaping the dome: understanding how leisure service ecosystems can support forest ecosystem servicesMaria Inês Costa Lago 17 July 2026 (has links)
No description available.
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1102 |
Gamification in a public school environment through a continuous improvement mobile applicationFilipe Azeredo da Silva 13 July 2023 (has links)
No description available.
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1103 |
Short lifecycle items detection for demand forecastingJoão Pedro Oliveira Neves 19 July 2023 (has links)
No description available.
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1104 |
Desenho e implementação de uma estratégia de pull-flow numa indústria de ciclismoRaquel Maria Antunes Carvalho 13 July 2026 (has links)
No description available.
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1105 |
Generative AI: An integrated approach with symbolic systems and people for product catalog analysisJoão Macedo Afonso Moreira 21 July 2023 (has links)
No description available.
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1106 |
Os Efeitos e Impactos da Qualidade dos Dados nas Oportunidades de InovaçãoLucas Cardoso Aguiar Teixeira 13 October 2023 (has links)
No description available.
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1107 |
Assessing the Effectiveness of Defect Prediction-based Test Suites at Localizing FaultsOrlando Jorge Ribeiro Macedo 08 November 2023 (has links)
Debugging a software program constitutes a significant and laborious task for programmers, often consuming a substantial amount of time. The need to identify faulty lines of code further compounds this challenge, leading to decreased overall productivity. Consequently, the development of automated tools for fault detection becomes imperative to streamline the debugging process and enhance programmer productivity.
In recent years, the field of automatic test generation has witnessed remarkable advancements, significantly improving the efficacy of automatic tests in detecting faults. The localization of faults can be further optimized through the utilization of such sophisticated tools.
This dissertation aims to conduct an experimental study that assembles specialized automatic test generation tools designed to detect faults by estimating the likelihood of code being faulty. These tools will be compared against each other to discern their relative performance and effectiveness. Additionally, the study will comprehensively compare developer-generated tests with automatically generated tests to evaluate their respective aptitude for fault detection. Through this investigation, we seek to identify the most effective automated test generation tool while providing valuable insights into the relative merits of developer-generated and automatically generated tests for fault detection.
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1108 |
Implementation of a Shared Control Strategy for Myoeletrically Controlled Transradial ProsthesesJoana Francisca Barros Matos 12 October 2025 (has links)
No description available.
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1109 |
AI-based Conditional Generation of Diffusion MR ImagesPedro Fernandes Sousa 08 November 2023 (has links)
No description available.
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1110 |
Proposta de um modelo data driven para gestão de segurança do trabalhoPedro Miguel Santos Reis 15 October 2026 (has links)
No description available.
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