Evolutionary Computation Paradigm to Determine Deep Neural Networks Architectures

Image classification is usually done using deep learning algorithms. Deep learning architectures are set deterministically. The aim of this paper is to propose an evolutionary computation paradigm that optimises a deep learning neural network’s architecture. A set of chromosomes are randomly generated, after which selection, recombination, and mutation are applied. At each generation the fittest chromosomes are kept. The best chromosome from the last generation determines the deep learning architecture. We have tested our method on a second trimester fetal morphology database. The proposed model is statistically compared with DenseNet201 and ResNet50, proving its competitiveness

Alantolactona în tulpina, frunzele şi inflorescenţele de Tagetes Erecta

The genus Tagetes (Asteraceae) comprises species with a wide arrays of uses. Previous studies have been focused on the distribution of flavonoids in the genus but little has been done on the identification of the sesquiterpenlactones in the medicinal, cosmetic and aromatic species. The significance of the distribution and accumulation of this compound thorough the plant is not yet clear. In the current study, the alantolactone content of aerial parts of Tagetes erecta was investigated, during budding and full flowering stages. The TLC and HPLC methods confirmed the presence of alantolactones, greater in budding stage sampes than in full flowering ones (0.2309 μg % in buds, 0.5097 μg % in leaves). The fertilized plant inflorescences contain greater amounts of studied metabolites than unfertilized plants. The leaves content is not influenced by fertilization. The presence of this metabolite alerts to the allergenic potential of plant, especially in budding stag

Boundary Control by Boundary Observer for Hyper-redundant Robots

The control problem of a class of hyper-redundant arms with continuum elements, with boundary measuring and control is discussed. First, the dynamic model of the continuum arm is presented. The measuring systems are based on the film sensors that are placed at the terminal sub-regions of the arm. The observers are proposed in order to reconstruct the full state of the arm. A back-stepping method is used to design a boundary control algorithm. Numerical simulations of the arm motion toward an imposed position are presented. An experimental platform shows the effectiveness of the proposed methods

Exoskeleton Hand Control by Fractional Order Models

This paper deals with the fractional order control for the complex systems, hand exoskeleton and sensors, that monitor and control the human behavior. The control laws based on physical significance variables, for fractional order models, with delays or without delays, are proposed and discussed. Lyapunov techniques and the methods that derive from Yakubovici-Kalman-Popov lemma are used and the frequency criterions that ensure asymptotic stability of the closed loop system are inferred. An observer control is proposed for the complex models, exoskeleton and sensors. The asymptotic stability of the system, exoskeleton hand-observer, is studied for sector control laws. Numerical simulations for an intelligent haptic robot-glove are presented. Several examples regarding these models, with delays or without delays, by using sector control laws or an observer control, are analyzed. The experimental platform is presented

UNCONSTRAINED AND CONSTRAINED CONTROL FOR A TENTACLE MANIPULATOR

ABSTRACT The control problem of the spatial tentacle manipulator is presented. In order to avoid the difficulties generated by the complexity of the nonlinear integral -differential model, the control problem is based by the artificial potential method. It is shown that the control of a tentacle robot to a desired position it is possible if the artificial potential is a potential functional whose point of minimum is attractor of this dissipative controlled system. Then, the method is used for constrained motion in an environment with obstacles. Numerical simulations for spatial and planar tentacle models are presented in order to illustrate the efficiency of the method. Keywords: potential, control, hyper-redundant system, distributed parameter system. INTRODUCTION A tentacle manipulator is a hyper-redundant or hyperdegree-of-freedom manipulator and there has been a rapidly expanding interest in their study and construction lately. The control of these systems is very complex and a great number of researchers have tried to offer solutions for this difficult problem. In [1] it was analysed the control by cables or tendons meant to transmit forces to the elements of the arm in order to closely approximate the arm as a truly continuous backbone. In In other papers The difficulty of the dynamic control is determined by integral-partial-differential models with high nonliniarities that characterise the dynamic of these systems