Logo do repositório

Percorrer por autor "Neves, Mariana"

A mostrar 1 - 2 de 2
  • Employees balance and stability as key points in organizational performance
    Publication . Neves, José; Maia, Nuno; Marreiros, Goreti; Neves, Mariana; Fernandes, Ana; Ribeiro, Jorge; Araújo, Isabel; Araújo, Nuno; Ávidos, Liliana; Ferraz, Filipa; Capita, António; Lori, Nicolás; Alves, Victor; Vicente, Henrique
    System analyses deal with interrelationships between different variables that keep the system in balance. In many analysis of complex thinking, a system is viewed as a complex unit in which the ‘whole’ is not reduced to the ‘sum’ of its parts; the system becomes an ambiguous item because it consists of several entities that interact with unforeseen results or, in other words, it is situated at a transdisciplinary level, it is impossible for an area to have a complete reading of its complexity. It was also mentioned that the concept of the open system best describes complexity by stating that ‘the laws of the organization are not equilibrium, but an imbalance that is restored or compensated for by stabilized dynamics’. This idea originated from the field of thermodynamics and the second law, in which the imbalance that it maintains allows the system for an apparent balance. This fragile steady state has something of a paradox, since the structures remain the same, but their constituents are changeable. The concept of open system undoes the door to a theory of evolution that can only derive from the interactions between a system and its ecosystem. Within this systemic approach, the focus of the analysis takes into account the ambiguity, multidisciplinary and complexity associated with system adjustment, i.e. it is intended to qualify an employee job based on their experience and knowledge as a measure of their impact on the organization performance.
    2022Artigo científico Acesso aberto Ver mais
  • NutriScan: Nutrition analysis system
    Publication . Ribeiro, Hugo; Soares, Filipe; Mendes, Gonçalo; Serra, João; Neves, Mariana; Gonçalves, Tiago
    Growing public awareness of the connection between diet and health has increased the need for accessible and comprehensible nutritional information. To address this, we developed NutriScan, a web-based expert system designed to provide real-time nutritional analysis of food products. The system integrates barcode recognition with a knowledge base powered by Drools and Prolog inference engines, enabling intelligent reasoning over nutritional data. NutriScan offers detailed product evaluations and scoring. Through personalized user profiles, it identifies potential allergens, generates tailored alerts, and suggests healthier alternatives. The architecture combines both Java (Drools) and Prolog inference back-end components to explore the impact of two different technologies over AI techniques. The system demonstrates the integration of symbolic AI through Prolog-based logical inference and a structured knowledge database, showcasing how expert systems can deliver transparent, rule-driven nutritional analysis and decision support. While both Drools and Prolog can be applied to rule-based reasoning, their underlying mechanisms differ substantially: Prolog employs backward chaining for logic-based inference, facilitating complex reasoning and knowledge representation, whereas Drools applies forward chaining to enable efficient, scalable rule evaluation with greater implementation clarity. Overall, NutriScan leverages expert system principles and AI reasoning to support informed and health-conscious consumer decisions. The successful development and validation of NutriScan highlight the effectiveness of combining distinct inference paradigms to create intelligent, user-oriented decision-support tools.
    2025-12-09Comunicação em conferência Acesso aberto Ver mais