Titlebook: Computational Science – ICCS 2024; 24th International C Leonardo Franco,Clélia de Mulatier,Peter M. A. Slo Conference proceedings 2024 The

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PGAS Data Structure for Unbalanced Tree-Based Algorithms at Scalerkload distribution mechanisms in a productive and scalable way. In this paper, we propose a PGAS data structure along with a Work-Stealing mechanism for the class of parallel tree-based algorithms that explore unbalanced trees using the depth-first search strategy. The contribution has been impleme

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Assessing the Stability of Text-to-Text Models for Keyword Generation Tasksperimental variations such as the seed used to shuffle fine-tuning data. The authors advocate for incorporating error bars and standard deviations when reporting results to account for this variability, which is common practice in other domains of data science, but not common in keyphrase generation

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A Dictionary-Based with Stacked Ensemble Learning to Time Series Classificationve for time series data that have different lengths. Our contribution involves introducing the integration of a dictionary-based technique with stacked ensemble learning. This study is unique since it combines the symbolic aggregate approximation (SAX) with stacking gated recurrent units (GRU) and a

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Agent Based Simulation as an Efficient Way for HPC I/O System Tuningttings. This paper proposes to use agent-based modeling and simulation (ABMS) to evaluate the performance of the I/O software stack to allow researchers to choose the best possible configuration without testing the real system. Testing configurations in a simulated environment minimizes the risk of

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