Titlebook: New Trends in Disruptive Technologies, Tech Ethics and Artificial Intelligence; The DITTET 2023 Coll Daniel H. de la Iglesia,Juan F. de Paz

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Maryam Abbasi,Pedro Martinsut per capita in the sampled countries though its effect was small. However, institutional variables such as control for corruption and government effectiveness had a positive effect on growth though they were statistically insignificant. These findings agree with some of the studies conducted so fa

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Nikolaos Feloutzis,Georgios Lekakosl evidence on Ethiopia suggests that the trends in agricultural income tax and land use fee collection are highly inconsistent. Agricultural income tax and land use fee are not buoyant, indicating that the growth of the agricultural sector has no statistically significant impact on agricultural inco

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Comparing Supervised and Unsupervised Machine Learning Techniques to Decision Support Systems in Heapervised counterparts. Additionally, the application of unsupervised clustering preprocessing techniques did not lead to improved performance, although it did have a positive impact on overall results. In conclusion, this study highlights the superiority of supervised techniques over unsupervised te

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Machine Learning for Automatic Weather Stations: A Case Studycision agriculture, construction, and energy. With continuous advances in Machine Learning, these techniques are expected to be successfully applied in other areas of meteorology, bringing significant benefits to the scientific community.

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Synonym-Substitution Algorithms for Enriching the Agrovoc Vocabularyth cases, the newly learned names will be checked against the AGRIS database to eliminate any illogical candidates. To validate the results, the study generated sentences using both the keywords and new synonyms and utilized BERT for the Agricultural Domain to calculate vector encodings for each sen