<?xml version="1.0" encoding="UTF-8"?>
<feed xmlns="http://www.w3.org/2005/Atom" xmlns:dc="http://purl.org/dc/elements/1.1/">
  <title>Colibri Colección : Incluye artículos, objetos de conferencias, seminarios y jornadas, reportes técnicos, comunicaciones y otros</title>
  <link rel="alternate" href="https://hdl.handle.net/20.500.12008/5205" />
  <subtitle>Incluye artículos, objetos de conferencias, seminarios y jornadas, reportes técnicos, comunicaciones y otros</subtitle>
  <id>https://hdl.handle.net/20.500.12008/5205</id>
  <updated>2026-09-11T18:10:32Z</updated>
  <dc:date>2026-09-11T18:10:32Z</dc:date>
  <entry>
    <title>Desaparición de Isaac Asimov</title>
    <link rel="alternate" href="https://hdl.handle.net/20.500.12008/56521" />
    <author>
      <name>Slomovitz, Daniel</name>
    </author>
    <id>https://hdl.handle.net/20.500.12008/56521</id>
    <updated>2026-09-03T14:38:02Z</updated>
    <published>1992-01-01T00:00:00Z</published>
    <summary type="text">Título: Desaparición de Isaac Asimov
Autor: Slomovitz, Daniel
Descripción: Boletin bimensual de Noticias del IEEE - Sección Uruguay</summary>
    <dc:date>1992-01-01T00:00:00Z</dc:date>
  </entry>
  <entry>
    <title>Optimal design of renewable generation mix for green hydrogen production</title>
    <link rel="alternate" href="https://hdl.handle.net/20.500.12008/56175" />
    <author>
      <name>Accinelli, Elvio</name>
    </author>
    <author>
      <name>Risso, Claudio</name>
    </author>
    <author>
      <name>Vignolo, Mario</name>
    </author>
    <author>
      <name>Nuñez, Facundo</name>
    </author>
    <id>https://hdl.handle.net/20.500.12008/56175</id>
    <updated>2026-07-21T11:19:14Z</updated>
    <published>2026-01-01T00:00:00Z</published>
    <summary type="text">Título: Optimal design of renewable generation mix for green hydrogen production
Autor: Accinelli, Elvio; Risso, Claudio; Vignolo, Mario; Nuñez, Facundo
Resumen: Green hydrogen is emerging as a key energy vector for the decarbonization of modern energy systems by enabling the storage and transport of renewable energy. It is produced through water electrolysis powered by renewable electricity, either on-site or supplied by a high-renewable grid. Its applications include hard-to-abate industrial sectors (e.g., steel and cement), long-distance transport, and as a feedstock for chemical synthesis, including clean synthetic fuels when combined with CO2 capture. In power systems with high shares of wind and solar generation, green hydrogen also plays a strategic role in managing surplus energy and reducing curtailment. This paper develops a quantitative framework to determine the optimal mix of renewable generation technologies for hydrogen production, incorporating generation variability, grid interactions, and long-term financial evaluation based on Net Present Value.</summary>
    <dc:date>2026-01-01T00:00:00Z</dc:date>
  </entry>
  <entry>
    <title>AI learns G-PON : Toward adaptive T-CONT configuration for fixed-mobile convergence</title>
    <link rel="alternate" href="https://hdl.handle.net/20.500.12008/55916" />
    <author>
      <name>Inglés, Lucas</name>
    </author>
    <author>
      <name>Anet Neto, Luiz</name>
    </author>
    <author>
      <name>Rattaro, Claudina</name>
    </author>
    <author>
      <name>Morvan, Michel</name>
    </author>
    <author>
      <name>Castro, Alberto</name>
    </author>
    <author>
      <name>Nuaymi, Loutfi</name>
    </author>
    <id>https://hdl.handle.net/20.500.12008/55916</id>
    <updated>2026-07-07T13:17:08Z</updated>
    <published>2026-01-01T00:00:00Z</published>
    <summary type="text">Título: AI learns G-PON : Toward adaptive T-CONT configuration for fixed-mobile convergence
Autor: Inglés, Lucas; Anet Neto, Luiz; Rattaro, Claudina; Morvan, Michel; Castro, Alberto; Nuaymi, Loutfi
Resumen: We demonstrate the use of a commercial G-PON as an AI-enhanced self-optimizing substrate. We refine the T-CONT configuration with deep reinforcement learning to optimize transmission latency and ensure stable and adaptive performances for fixed-mobile convergent scenarios.</summary>
    <dc:date>2026-01-01T00:00:00Z</dc:date>
  </entry>
  <entry>
    <title>Measurements of beamforming performance in commercial 5G deployments</title>
    <link rel="alternate" href="https://hdl.handle.net/20.500.12008/55913" />
    <author>
      <name>Benedetti, Bruno</name>
    </author>
    <author>
      <name>Rattaro, Claudina</name>
    </author>
    <author>
      <name>Rodríguez Díaz, Benigno</name>
    </author>
    <id>https://hdl.handle.net/20.500.12008/55913</id>
    <updated>2026-07-07T13:08:29Z</updated>
    <published>2026-01-01T00:00:00Z</published>
    <summary type="text">Título: Measurements of beamforming performance in commercial 5G deployments
Autor: Benedetti, Bruno; Rattaro, Claudina; Rodríguez Díaz, Benigno
Resumen: This paper presents field measurements of different beamforming mechanisms using a commercial 5 G network. Beamforming enhances signal quality and capacity through directional transmission, and its effectiveness depends on factors like user position and feedback. We analyze Sounding Reference Signal (SRS)-based and codebook-based beamforming under real-world conditions. Results show SRS-based beamforming excels in mid-cell areas, while codebook-based performs better at the cell edge.</summary>
    <dc:date>2026-01-01T00:00:00Z</dc:date>
  </entry>
</feed>

