Results 101 to 110 of about 1,298,041 (289)
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
Bayesian analysis of the 3-component mixture of an Exponential distribution under type-I right censoring scheme is considered in this paper. The Bayes estimators and posterior risks for the unknown parameters are derived under squared error loss function,
MUHAMMAD TAHIR, MUHAMMAD ASLAM
doaj +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
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
Forecasting adoption of ultra-low-emission vehicles using Bayes estimates of a multinomial probit model and the GHK simulator [PDF]
In this paper we use Bayes estimates of a multinomial probit model with fully flexible substitution patterns to forecast consumer response to ultra-low-emission vehicles.
Achtnicht, Martin, Daziano, Ricardo
core +3 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
This study enables the simultaneous estimations of the unknown parameters of two inverted Nadarajah–Haghighi populations. The estimations are conducted using data collected from joint progressively type-II censored samples from the populations of ...
Ohud A. Alqasem +3 more
doaj +1 more source
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
Bayes and pseudo-Bayes estimates of conditional probabilities and their reliability [PDF]
Various ways of estimating probabilities, mainly within the Bayesian framework, are discussed. Their relevance and application to machine learning is given, and their relative performance empirically evaluated. A method of accounting for noisy data is given and also applied.
openaire +3 more sources
Neural Fields for Highly Accelerated 2D Cine Phase Contrast MRI
ABSTRACT 2D cine phase contrast (CPC) MRI provides quantitative information on blood velocity and flow within the human vasculature. However, data acquisition is time‐consuming, motivating the reconstruction of the velocity field from undersampled measurements to reduce scan times. In this work, neural fields are proposed as a continuous spatiotemporal
Pablo Arratia +7 more
wiley +1 more source

