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  <title>DSpace Communidade:</title>
  <link rel="alternate" href="http://repositorio.ufc.br/handle/riufc/23995" />
  <subtitle />
  <id>http://repositorio.ufc.br/handle/riufc/23995</id>
  <updated>2026-06-11T16:52:02Z</updated>
  <dc:date>2026-06-11T16:52:02Z</dc:date>
  <entry>
    <title>Automação de testes de benchmark em máquinas virtuais Linux na AWS: um estudo de caso com a AWS Academy</title>
    <link rel="alternate" href="http://repositorio.ufc.br/handle/riufc/85367" />
    <author>
      <name>Silva, Francisco Renato Ferreira da</name>
    </author>
    <id>http://repositorio.ufc.br/handle/riufc/85367</id>
    <updated>2026-03-17T14:10:14Z</updated>
    <published>2026-01-01T00:00:00Z</published>
    <summary type="text">Título: Automação de testes de benchmark em máquinas virtuais Linux na AWS: um estudo de caso com a AWS Academy
Autor(es): Silva, Francisco Renato Ferreira da
Abstract: This work presents the development of an automation prototype for conducting benchmark tests on Linux instances within the AWS Academy. The central problem resides in the opacity and variability of performance in public cloud environments, which complicates the ideal choice of resources for subjects such as Databases and Web Development. Through a Python script, using the Boto3 and Paramiko libraries, 77 instances were tested in various CPU and I/O load scenarios. The results, validated by the Kruskal-Wallis statistical test, revealed a deterministic predictability for processing (p = 2.54×10−26) with gains of up to 100% in new hardware generations, contrasting with a highly variable Cauda (P95) latency (p = 0.99). The work concludes with the consolidation of performance pro les for the C, Z, I, R, M, and T families, offering a decision support guide that optimizes the cost-bene t ratio and academic performance in the AWS Academy environment.
Tipo: TCC</summary>
    <dc:date>2026-01-01T00:00:00Z</dc:date>
  </entry>
  <entry>
    <title>Avaliação da interface e experiência do usuário na aplicação moodle da UFC Campus de Quixadá - CE</title>
    <link rel="alternate" href="http://repositorio.ufc.br/handle/riufc/85366" />
    <author>
      <name>Araújo, Antônia Vitória da Silva</name>
    </author>
    <id>http://repositorio.ufc.br/handle/riufc/85366</id>
    <updated>2026-03-17T14:02:43Z</updated>
    <published>2026-01-01T00:00:00Z</published>
    <summary type="text">Título: Avaliação da interface e experiência do usuário na aplicação moodle da UFC Campus de Quixadá - CE
Autor(es): Araújo, Antônia Vitória da Silva
Abstract: Virtual learning environments play a significant role in the academic context, directly influencing the flexibility, engagement, and performance of students and teachers. In constant evolution, these systems seek to adapt to users’ needs through continuous improvements, often guided by feedback related to satisfaction and usability. In this context, this study aims to evaluate the User Interface (UI) and User Experience (UX) of the Moodle platform at the Federal University of Ceará (UFC), Quixadá Campus, based on the perceptions of students who use the system through mobile devices. The research is characterized as descriptive, using the survey method, with the application of a structured questionnaire directed at Moodle Mobile users. The study seeks to contribute to the understanding of the importance of UI and UX strategies in virtual learning environments, especially in the context of mobile device usage, highlighting the need for more intuitive, organized, and user-centered interfaces.
Tipo: TCC</summary>
    <dc:date>2026-01-01T00:00:00Z</dc:date>
  </entry>
  <entry>
    <title>A experiência do jogador em jogos empáticos: uma análise do Jogo Florence através do modelo MALTU</title>
    <link rel="alternate" href="http://repositorio.ufc.br/handle/riufc/85365" />
    <author>
      <name>Batista, Tarço Israel Freitas</name>
    </author>
    <id>http://repositorio.ufc.br/handle/riufc/85365</id>
    <updated>2026-03-17T13:53:27Z</updated>
    <published>2026-01-01T00:00:00Z</published>
    <summary type="text">Título: A experiência do jogador em jogos empáticos: uma análise do Jogo Florence através do modelo MALTU
Autor(es): Batista, Tarço Israel Freitas
Abstract: This study aims to understand the factors that emotionally engage players in contemporary digital games, focusing on the relationship between User Experience (UX) and Player Experience (PX) in the empathetic game Florence (2018). The central problem lies in explaining how a game based on simple mechanics can produce a deep emotional impact, challenging the assumption that software success is primarily determined by technical performance. The main objective was to analyze the balance between functionality and emotion, seeking to identify the elements that sustain satisfaction in interactive narratives. The methodological approach combined quantitative rigor with qualitative interpretation, applying the User Textual Language Assessment Model (MALTU) to a corpus of 7,106 spontaneous user reviews collected from the Steam platform. The results indicate a phenomenon of "technical invisibility", in which interface and usability aspects become imperceptible when the narrative experience is strong. While technical usability showed little influence on player recommendation, visceral engagement, narrative construction, and visual aesthetics emerged as the main pillars of player experience. The study concludes that the simplicity of Florence is not a limitation, but a deliberate design strategy that enhances emotional immersion, reinforcing the role of empathetic games as powerful tools for human connection.
Tipo: TCC</summary>
    <dc:date>2026-01-01T00:00:00Z</dc:date>
  </entry>
  <entry>
    <title>Gestão automatizada de infraestrutura de redes: desenvolvimento de um assistente digital baseado em IA para análise de dados</title>
    <link rel="alternate" href="http://repositorio.ufc.br/handle/riufc/85364" />
    <author>
      <name>Silva, Rodrigo Cauã Moreira</name>
    </author>
    <id>http://repositorio.ufc.br/handle/riufc/85364</id>
    <updated>2026-03-17T13:39:34Z</updated>
    <published>2026-01-01T00:00:00Z</published>
    <summary type="text">Título: Gestão automatizada de infraestrutura de redes: desenvolvimento de um assistente digital baseado em IA para análise de dados
Autor(es): Silva, Rodrigo Cauã Moreira
Abstract: In the technology sector, managing network operations and interpreting the vast volume of data generated by servers has become an increasingly critical challenge. To address this practically, tools that facilitate error detection and provide rapid responses are essential, as manual analysis is often hindered by information overload. This study aimed to develop a solution leveraging Arti cial Intelligence (AI) to assist system administrators through a digital assistant that enables natural language queries regarding network status. The project was deployed on a cloud server, integrating automation and databases to intelligently process event logs. For validation, a case study was conducted using a messaging application, evaluating the tool’s ability to identify issues and send automated alerts about the environment’s health. The results demonstrated that AI integration signi cantly reduced fault diagnosis time, allowing complex server log queries to be resolved in seconds. Furthermore, the automated alert system showed high precision in anomaly detection, preempting structural bottlenecks before they impacted the end-user experience. This study concludes that the proposed solution not only optimizes the operational workload of network administrators but also establishes a scalable and ef cient model for critical infrastructure management mediated by intelligent assistants.
Tipo: TCC</summary>
    <dc:date>2026-01-01T00:00:00Z</dc:date>
  </entry>
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