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frameworks for full-stack web development (Node.js, .NET Core, Angular) and data pipelines (Apache Kafka, AWS Glue), comparing performance, scalability and security (RBAC, OAuth 2.0). Study cases of digital
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of LIS ́s researchers, in the framework of Project WATERSCAN - Intelligent Optoelectronic System for Monitoring Water Distribution Networks and Detecting Leaks (CENTRO2030-FEDER-01468500), co-financed by
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of classes, using Machine Learning (ML) techniques such as Decision Trees, K-Nearest Neighbors (KNN), XGBoost, Support Vector Machines (SVM), or Neural Networks. Explore and implement clustering algorithms
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Niphad Grape Leaf Disease. 2. Regional linguistic adaptation prototypes that enable: a. Recognition of local terms in speech-to-text transcription; b. Adjustment of written/spoken responses to the user's
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of large language models (LLMs), risks and threats that affect their security in the context in question, protection/control mechanisms appropriate to the main risks, and appropriate evaluation methodologies
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of the following activities: Review of literature in the field of large language models (LLMs), risks and threats in LLMs, security mechanisms for LLMs, evaluation methodologies, as well as relevant standardisation