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A Hybrid DVS Scheduling Approach for Hard Real-Time Systems., , , , , и . SMC, стр. 2848-2853. IEEE, (2009)AMALGHMA -An environment for measuring execution time and energy consumption in embedded systems., , , , , , и . SMC, стр. 3364-3369. IEEE, (2014)Model-driven software synthesis for hard real-time applications with energy constraints., , , , , , , и . Des. Autom. Embed. Syst., 14 (4): 327-366 (2010)Multi-View Fine-Grained Vehicle Classification with Multi-Loss Learning., , и . ICARSC, стр. 209-214. IEEE, (2021)GPT-4 as an Agronomist Assistant? Answering Agriculture Exams Using Large Language Models., , , , и . CoRR, (2023)Marginal agricultural land identification in the Lower Mississippi Alluvial Valley based on remote sensing and machine learning model., , , , , и . Int. J. Appl. Earth Obs. Geoinformation, (декабря 2023)ASTRO: A tool for dependability evaluation of Data Center infrastructures., , , , , , , , , и 2 other автор(ы). SMC, стр. 783-790. IEEE, (2010)Subjective Evaluation of Haptic Feedback Technologies for Interactive Multimedia., , , , и . EUROCON, стр. 1-6. IEEE, (2019)The Mercury Environment: A Modeling Tool for Performance and Dependability Evaluation., , , , , , , , , и . Intelligent Environments (Workshops), том 29 из Ambient Intelligence and Smart Environments, стр. 16-25. IOS Press, (2021)Reduzindo a Variabilidade das Decisões de Roteamento em Redes em Malha Sem Fio., , и . SBRC, стр. 1047-1060. (2018)