Search results for "feed"
showing 10 items of 1675 documents
A new approach to simulate coating thickness in cold spray
2020
Abstract In the process of cold spray on complex components, the coating thickness is an important indicator to monitor and control. Current methods such as destructive tests or direct mechanical measurements can only be performed after spraying. Besides, these methods lead to production shutdown and additional costs . This article presents a novel approach predicting coating thickness for components with complex curved surfaces, especially in the case of shadow effects. Firstly, a three-dimensional geometric model of the coating profile based on Gaussian distribution was developed. In addition, the relative deposition efficiency (RDE) resulting from the different robot kinematic parameters…
Improved Active Disturbance Rejection Control for Trajectory Tracking Control of Lower Limb Robotic Rehabilitation Exoskeleton.
2020
Neurological disorders such as cerebral paralysis, spinal cord injuries[acronym](SCI), and strokes, result in the impairment of motor control and induce functional difficulties to human beings like walking, standing, etc. Physical injuries due to accidents and muscular weaknesses caused by aging [english]affectsaffect people and can cause them to lose their ability to perform daily routine functions. In order to help people recover or improve their dysfunctional activities and quality of life after accidents or strokes, assistive devices like exoskeletons and orthoses are developed. Control strategies for control of exoskeletons are developed with the desired intention of improving the qual…
Vibration control strategy for large-scale structures with incomplete multi-actuator system and neighbouring state information
2016
The synthesis of optimal controllers for vibrational protection of large-scale structures with multiple actuation devices and partial state information is a challenging problem. In this study, the authors present a design strategy that allows computing this kind of controllers by using standard linear matrix inequality optimisation tools. To illustrate the main elements of the new approach, a five-story structure equipped with two interstory actuation devices and subjected to a seismic disturbance is considered. For this control setup, three different controllers are designed: an ideal state-feedback H 8 controller with full access to the complete state information and two static output-fee…
Extreme Learning Machines for Data Classification Tuning by Improved Bat Algorithm
2018
Single hidden layer feed forward neural networks are widely used for various practical problems. However, the training process for determining synaptic weights of such neural networks can be computationally very expensive. In this paper we propose a new learning algorithm for learning the synaptic weights of the single hidden layer feedforward neural networks in order to reduce the learning time. We propose combining the upgraded bat algorithm with the extreme learning machine. The proposed approach reduces the number of evaluations needed to train a neural network and efficiently finds optimal input weights and the hidden biases. The proposed algorithm was tested on standard benchmark clas…
Comparison of KVP and RSI for Controlling KUKA Robots Over ROS
2020
In this work, an open-source ROS interface based on KUKAVARPROXY for control of KUKA robots is compared to the commercial closed-source Robot Sensor Interface available from KUKA. This comparison looks at the difference in how these two approaches communicate with the KUKA robot controller, the response time and tracking delay one can expect with the different interfaces, and the difference in use cases for the two interfaces. The investigations showed that the KR16 with KRC2 has a 50 ms response time, and RSI has a 120 ms tracking delay, with negligible delay caused by the ROS communication stack. The results highlight that the commercial inferface is more reliable for feedback control tas…
Do Randomized Algorithms Improve the Efficiency of Minimal Learning Machine?
2020
Minimal Learning Machine (MLM) is a recently popularized supervised learning method, which is composed of distance-regression and multilateration steps. The computational complexity of MLM is dominated by the solution of an ordinary least-squares problem. Several different solvers can be applied to the resulting linear problem. In this paper, a thorough comparison of possible and recently proposed, especially randomized, algorithms is carried out for this problem with a representative set of regression datasets. In addition, we compare MLM with shallow and deep feedforward neural network models and study the effects of the number of observations and the number of features with a special dat…
A Critical View of Neurofeedback Experimental Designs: Sham and Control as Necessary Conditions
2016
C l i n M e d International Library Citation: Alino M, Gadea M, Espert R (2016) A Critical View of Neurofeedback Experimental Designs: Sham and Control as Necessary Conditions. Int J Neurol Neurother 3:041 Received: January 29, 2016: Accepted: February 25, 2016: Published: February 27, 2016 Copyright: © 2016 Alino M, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. ISSN: 2378-3001 Volume 3 | Issue 1 Alino et al. Int J Neurol Neurother 2016, 3:041
Roles for RpoS in survival of Escherichia coli during protozoan predation and in reduced moisture conditions highlight its importance in soil environ…
2017
The soil is a complex ecosystem where interactions between biotic and abiotic factors determine the survival and fate of microbial inhabitants of the system. Having previously shown that Escherichia coli requires the general stress response regulator, RpoS, to survive long term in soil, it was important to determine what specific conditions in this environment necessitate a functional RpoS. This study investigated the susceptibility of soil-persistent E. coli to predation by the single-celled eukaryotes Acanthamoeba polyphaga and Tetrahymena pyriformis, and the role RpoS plays in resisting this predation. Strain-specific differences were observed in the predation of E. coli strains, with so…
What are the determinants of adherence to the mediterranean diet?
2021
Current evidence suggests that adherence to traditional dietary patterns are slowly disappearing in favour of a globalised market, in which higher availability of processed, ready-to-use, energy-dense foods undermines the consumption of fresh, locally produced goods ... When exploring the nutritional quality of processed foods, excess content in added free sugars, saturated and hydrogenated fats, together with scarcity in fibre and vitamins, ...
Association between parental feeding practices and shared family meals. The Food4toddlers study
2020
Background Parental feeding practices and family meals are important determinants for infants' diet and health. Still, there is no previous research of the association between feeding practices and family meals in infants. Objective Explore potential associations between feeding practices and family meals among infants. Design We present cross-sectional results (baseline) from the Food4toddlers study. In total 298 parents of 1-year-olds, recruited from all over Norway, filled in a questionnaire regarding frequency of shared family meals (breakfast, lunch, dinner) and feeding practices using the validated instrument Comprehensive Feeding Practices Questionnaire. Logistic regression was used …