Search results for "PROX"
showing 10 items of 1411 documents
SHEAR COMPLIANCE AND SELF WEIGHT EFFECTS ON TRACTION BELT MECHANICS
2007
The transverse elastic deflection of a traction belt along the free span depends mainly on the flexural stiffness, but may be significantly influenced by the distributed weight and the shear compliance, which affect together the width of the arc of contact. In particular, the shear compliance yields a virtual decrease of the flexural stiffness, flattens the free span and increases the wound regions, to the advantage of the transmissible torque. Moreover, the tensioning of a given belt may be somewhat larger, in comparison with the ideal circular-straight path with the same centre distance, because of the increased length of the deflected belt trajectory due to gravity. The present paper ad…
Regularized LMS methods for baseline wandering removal in wearable ECG devices
2016
The acquisition of electrocardiogram (ECG) signals by means of light and reduced size devices can be usefully exploited in several health-care applications, e.g., in remote monitoring of patients. ECG signals, however, are affected by several artifacts due to noise and other disturbances. One of the major ECG degradation is represented by the baseline wandering (BW), a slowly varying change of the signal trend. Several BW removal algorithms have been proposed into the literature, even though their complexity often hinders their implementation into wearable devices characterized by limited computational and memory resources. In this study, we formalize the BW removal problem as a mean-square…
A survey on handling computationally expensive multiobjective optimization problems with evolutionary algorithms
2017
Evolutionary algorithms are widely used for solving multiobjective optimization problems but are often criticized because of a large number of function evaluations needed. Approximations, especially function approximations, also referred to as surrogates or metamodels are commonly used in the literature to reduce the computation time. This paper presents a survey of 45 different recent algorithms proposed in the literature between 2008 and 2016 to handle computationally expensive multiobjective optimization problems. Several algorithms are discussed based on what kind of an approximation such as problem, function or fitness approximation they use. Most emphasis is given to function approxim…
Higher Degree F-transforms Based on B-splines of Two Variables
2016
The paper deals with the higher degree fuzzy transforms (F-transforms with polynomial components) for functions of two variables in the case when two-dimensional generalized fuzzy partition is given by B-splines of two variables. We investigate properties of the direct and inverse F-transform in this case and prove that using B-splines as basic functions of fuzzy partition allows us to improve the quality of approximation.
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…
Crowd-Averse Robust Mean-Field Games: Approximation via State Space Extension
2016
We consider a population of dynamic agents, also referred to as players. The state of each player evolves according to a linear stochastic differential equation driven by a Brownian motion and under the influence of a control and an adversarial disturbance. Every player minimizes a cost functional which involves quadratic terms on state and control plus a cross-coupling mean-field term measuring the congestion resulting from the collective behavior, which motivates the term “crowd-averse.” Motivations for this model are analyzed and discussed in three main contexts: a stock market application, a production engineering example, and a dynamic demand management problem in power systems. For th…
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 note on best proximity point theory using proximal contractions
2018
In this paper, a reduction technique is used to show that some recent results on the existence of best proximity points for various classes of proximal contractions can be concluded from the corresponding results in fixed point theory.
Best proximity point theorems for proximal cyclic contractions
2017
The purpose of this article is to compute a global minimizer of the function $$x\longrightarrow d(x, Tx)$$ , where T is a proximal cyclic contraction in the framework of a best proximally complete space, thereby ensuring the existence of an optimal approximate solution, called a best proximity point, to the equation $$Tx=x$$ when T is not necessarily a self-mapping.
Assessing the Histone Deacetylase Activity of SIRT6 in Primary Murine Hepatocytes via Proximity Ligation Assay
2016
Generation of primary cell culture of hepatocytes by mouse liver perfusion (MLP) combines the advantages of in vivo and in vitro models. It provides hepatocytes that grow under physiological conditions in mice, with the genotype of the whole organism or a specific gene knockout. In contrast to immortalized cell cultures, primary murine hepatocytes (pmHep) are non-cancerous cells with a limited lifespan but still amenable to classical in vitro methods such as treatment with drugs, small molecule inhibitors, and agonistic/antagonistic antibodies of surface receptors as well as transfection. One technique, which has gained popularity recently, is the analysis of protein-protein interactions by…