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Profil bibliographique

Guillem Duran

Informations fournies par OpenAlex. Research Africa ne déduit ni nationalité, ni poste, ni coordonnées personnelles.

8Publications signalées
44Citations signalées
1Affiliations récentes

Les institutions déclarées

Les domaines associés

Network Traffic and Congestion ControlNetwork Security and Intrusion DetectionAdvanced Queuing Theory AnalysisOptical Network TechnologiesPeer-to-Peer Network Technologies

Les publications récentes

Accès ouvert 2024 conference-abstract OpenAlex

Clustering in \({}^{11,12,13}\)C

L. Palada, Neven Soić, Luis Acosta, Sam Bailey et autres

Characterization of the excited states of 11C, 12C, 13C isotopes was performed using experimental data collected at the INFN-LNL in Italy. The study employed a 95 MeV 14N beam on 10B targets to probe clustering phenomena in carbon isotopes. The experimental setup …

dk (code pays fourni par la source)

1 citation Acta Physica Polonica B Proceedings Supplement
Accès ouvert 2021 article OpenAlex

Modeling a New AQM Model for Internet Chaotic Behavior Using Petri Nets

José M. Amigó, Guillem Duran, Ángel Giménez, José Valero et autres

Formal modeling is considered one of the fundamental phases in the design of network algorithms, including Active Queue Management (AQM) schemes. This article focuses on modeling with Petri nets (PNs) a new scheme of AQM. This innovative AQM is based on a …

es (code pays fourni par la source)

7 citations Applied Sciences
2017 conference-paper OpenAlex

Happiness, an inside job?

Jose Oriol Lopez Berengueres, Guillem Duran, Dani Castro

In this paper, we describe how to rank employees for risk of turnover by using data obtained from a happiness self-reporting app. Two data sources are used: daily happiness and social interactions. The data spans 2.5 years and 4,356 employees of 34 …

ae (code pays fourni par la source)

5 citations
Accès ouvert 2017 preprint OpenAlex

General Algorithmic Search

Sergio Hernández, Guillem Duran, José M. Amigó

In this paper we present a metaheuristic for global optimization called General Algorithmic Search (GAS). Specifically, GAS is a stochastic, single-objective method that evolves a swarm of agents in search of a global extremum. Numerical simulations with a sample of 31 test …

4 citations arXiv (Cornell University)

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