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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TR-Based Antenna Design with Forward FD: The Effects of Step Size on the Optimization Performancece of the final designs obtained using different FD setups may vary by as much as 18?dB (and by over 4?dB on average). At the same time, the . perturbations in a range between 1.5% and 3% (w.r.t. the initial design) seem to be suitable for maintaining (relatively) consistent and high-quality results.

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Assessing the?Stability of?Text-to-Text Models for?Keyword Generation Tasksmance, particularly with larger model sizes. Furthermore, they analyze the coherence within a family of models and propose novel approaches to assess the stability of the model. In general, the findings underscore the importance of considering experimental variability when evaluating and comparing text-to-text models for keyword generation tasks.

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Conference proceedings 2024place in Malaga, Spain, during July 2–4, 2024...The 155 full papers and 70 short papers included in these proceedings were carefully reviewed and selected from 430 submissions...They were organized in topical sections as follows:..Part I:. ICCS 2024 Main Track Full Papers;..Part II:.?ICCS 2024 Main

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Algebraic Analysis of Differential Equationsfficiency. We used four various real datasets in our experimental stage. Overall, we proceeded with almost twenty thousand experiments. The results prove that the clustering algorithm, the amount of input data, the method of cluster representation, and the subject of clustering significantly impact the inference efficiency.

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First-Order Ordinary Differential Equationsoundational element. By fusioning emotions and emotional dimension, arousal, and valence. This paper outlines the theoretical foundations, key components, and integration principles of the proposed framework, paving the way for future advancements in computational creativity and affective computing.

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Ernest G. Manes,Michael A. Arbib basic and its variant optimized by strip-mining vectorization) are based on OpenMP and OpenACC. Strip-mining gave clear enhancement in comparison to the basic version. The energy efficiency is much better on GPU than on CPU; and on CPU, the use of OpenMP is more energy-efficient; however, for GPU, OpenACC gives better results.