Results 101 to 110 of about 1,723,352 (285)
Muscle Control of an Extra Robotic Digit
This study compares muscle‐ and movement‐based control for operating a supernumerary robotic thumb. While movement control performs better in the proposed tasks, muscle‐based (EMG) control promotes broader motor learning. The results highlight the promise and challenges of using biosignals for human augmentation, offering new insights into intuitive ...
Julien Russ +7 more
wiley +1 more source
Comparisons of Methods of Estimation for a New Pareto-type Distribution
Bourguignon et al. (2016) introduced a new Pareto-type distribution to model income and reliability data. The aim of this paper is to estimate the parameters of this distribution from both frequentist and Bayesian view points.
Ali Saadati Nik +2 more
doaj +1 more source
Mutual Adaptation and Influence: Review of Latent Dynamics Models in Human–Robot Interaction
Robots are becoming better teammates by learning hidden patterns in how people act. This review covers how state‐of‐the‐art approaches leverage these patterns to help robots not only react but also anticipate and guide cooperation. Here, we synthesize a unifying framework for these approaches, classify and review existing works, and highlight key ...
Mason O. Smith +4 more
wiley +1 more source
STEM-Based Bayesian Computational Learning Model-BCLM for Effective Learning of Bayesian Statistics
This work contributes to the comprehension of Bayes’ theorem inclusive Bayesian probabilities and Bayesian inferencing within the framework of STEM (Science, Technology, Engineering, Arts, and Mathematics) and cognitive learning w.r.t Bloom’
Ikram E. Khuda +2 more
doaj +1 more source
This review maps the methods to monitor robots’ health by fusing vibration, sound, control signals, vision, force, and oil information with artificial intelligence. It identifies deep learning, transfer learning, digital twins, and physics‐informed models as key methodological pathways enabling earlier diagnosis, safer human–robot collaboration, and ...
Yuting Qiao +6 more
wiley +1 more source
On the Stability of Bayes Estimators for Gaussian Processes. [PDF]
Consider a Gaussian signal process \(X=(X_ t)\) observed in the presence of an additive Gaussian noise process \(N=(N_ t)\) for t in [0,T]. The paper is concerned with the behaviour of the Bayes estimator \(\delta_ 0\) under departures from Gaussian law by the prior or noise processes. The problem of choosing a suitable contamination model is discussed.
openaire +2 more sources
Learning‐Based Soft Robotic Grasping: Recent Progress and Remaining Challenges
This review analyzes learning‐based soft robotic grasping from a pipeline‐oriented perspective, encompassing soft gripper design, multimodal sensing, and learning‐based planning and control. It surveys key neural network architectures and benchmark datasets and identifies critical challenges such as sim‐to‐real transfer, generalization, and continual ...
Arnab Majumder +3 more
wiley +1 more source
AN EMPIRICAL BAYES APPROACH TO MODELING DROUGHT [PDF]
This paper illustrates an alternative approach to estimating the occurrence of drought. The empirical Bayes methodology was developed because of deficiencies in time-series and regression analysis with respect to prediction of drought. This manuscript is
Chamberlain, P.J.
core
The sea cucumber Holothuria leucospilota detects blue and adjacent wavelengths of light via an r‐opsin with a maximum absorption at 459 nm. In the oral tentacles, papillae, and tube feet, distinct light‐sensing structures with specialized morphologies are formed, constituting a unique pentaradial and bilateral combined photoreception system.
Jiasheng Huang +20 more
wiley +1 more source
In this study, the variance compounds parameters of the mixed bi-division variance analysis sample are estimated. This estimation is obtained, by Bayes quadratic unbiased estimator. The second way to estimate variance compounds parameters of a suggested
Shaymaa Riyadh Thanoon
doaj +2 more sources

