Japanese researchers develop an adaptive robot motion system that enables human-like grasping using minimal training data.

Despite rapid robotic automation advancements, most systems struggle to adapt their pre-trained movements to dynamic ...

Discover how econometricians use math and statistics to analyze and predict economic trends, serving in finance and academia ...

Michael O. Lawanson, a Nigerian data scientist at the University of Arkansas, United States, is at the forefront of global ...

Choosing the right curve fit model is essential for revealing key data features, such as rate of change, asymptotes, and EC 50 /IC 50 values. The best model is the one that most faithfully reflects ...

Molecular circuits capable of autonomous learning could unlock novel applications in fields such as bioengineering and synthetic biology. To this end, existing chemical implementations of neural ...

Nature is marked not only by struggles for survival, but also by remarkable feats of cooperation. From microbes to insects to humans, organisms work together in a variety of ways to gather and share ...

This project implements a quadratic nonlinear regression model to estimate the real-world distance between a hand and a camera based on the relative positions of hand landmarks in 2D images. The ...

ABSTRACT: This paper applies the novel adaptive learning methodology to forecast agricultural and energy prices in Greece’s volatile, data-scarce markets. We combine traditional ordinary least squares ...

In order to improve bearing capacity and service life of marine structure using marine UHPC with coarse aggregate (UHPC-CA), it is necessary to reasonably predict the performance of UHPC-CA. The ...

Abstract: This paper proposes a nonlinear regression model of a microelectromechanical systems capacitive accelerometer, targeted to be used in tilt sensing and low-g motion-tracking applications. The ...