25 documents found, page 1 of 3

Optimized design and analysis of cable-based parallel manipulators for enhanced...

The subsea exploration of complex and challenging areas has increased the need for advanced robotic frameworks, such as cable-based parallel manipulators (CPMs). Known for their flexibility and precision, CPMs are essential for performing detailed tasks underwater. In submarine environments, handling external underwater forces presents a significant challenge, necessitating the optimization of cable tension for...

Addressing a decision problem through a bipolar Pythagorean fuzzy approach: A n...

Decision-making in real-world scenarios often faces the challenge of uncertainty. Traditionally, fuzzy theory has been a means to represent and navigate such uncertainty. In this study, we propose a pioneering approach that incorporates a bipolarity analysis into multi-criteria decision-making processes, with a focus on its application in digital marketing. The proposal allows the analysis to be more encompassi...

An epidemiological analysis for assessing and evaluating COVID-19 based on data...

In this research, we investigate the COVID-19 spread in Latin American countries using time-series and epidemic models. We highlight the diverse outbreak patterns and the crucial role of the reproduction number in modeling pandemic scenarios. Our findings underscore the need for ongoing epidemic surveillance and accurate data handling.

Robust semi-parametric inference for two-stage production models: a beta regres...

The data envelopment analysis is related to a non-parametric mathematical tool used to assess the relative efficiency of productive units. In different studies on productive efficiency, it is common to employ semi-parametric procedures in two stages to determine whether any exogenous factors of interest affect the performance of productive units. However, some of these procedures, particularly those based on co...

On the use of machine learning techniques and non-invasive indicators for class...

This research aims to enhance the classification and prediction of ischemic heart diseases using machine learning techniques, with a focus on resource efficiency and clinical applicability. Specifically, we introduce novel non-invasive indicators known as Campello de Souza features, which require only a tensiometer and a clock for data collection. These features were evaluated using a comprehensive dataset of h...

Similarity-based predictive models: Sensitivity analysis and a biological appli...

Predictive models based on empirical similarity are instrumental in biology and data science, where the premise is to measure the likeness of one observation with others in the same dataset. Biological datasets often encompass data that can be categorized. When using empirical similarity-based predictive models, two strategies for handling categorical covariates exist. The first strategy retains categorical cov...

Fractional transformation-based decentralized robust control of a coupled-tank ...

Petrochemical and dairy industries, waste management, and paper manufacturing fall under the category of process industries where flow and liquid control are essential. Even when liquids are mixed or chemically treated in interconnected tanks, the fluid and flow should constantly be observed and controlled, especially when dealing with nonlinearity and imperfect plant models. In this study, we propose a nonline...

Para alem do binário: Lógica Fuzzy na modelação de problemas complexos

Advanced mathematical approaches in psycholinguistic data analysis: a methodolo...

In the evolving landscape of psycholinguistic research, this study addresses the inherent complexities of data through advanced analytical methodologies, including permutation tests, bootstrap confidence intervals, and fractile or quantile regression. The methodology and philosophy of our approach deeply resonate with fractal and fractional concepts. Responding to the skewed distributions of data, which are obs...

Geoscientists’ views about science communication: predicting willingness to com...

The main barriers to science communication are common in different fields and they are widely identified in the literature. Studies focused on specific scientific communities framed science communication as an activity with the specificities of each context and field. In this study, we analysed geoscientists’ representations and attitudes about communication to understand which factors can have significant impa...