First-order theory refinement using neural networks is still an open problem. Towards a solution to this problem, we define a First-Order extension of the Cascade ARTMAP (FOCA) system, using Inductive Logic Programming techniques. To present such a first-order extension of Cascade ARTMAP, we: a) modify the network structure to handle first-order objects; b) define firstorder versions of the mai...

HYPOTHESIS Light at certain wavelengths, can cross the cell, tissue sections and organ tissues for in-vitro studies, but can also be used for in-vivo studies. The ability to guide the growth of neural extensions was proven by laser. Synapses produced with laser have the instability as main disadvantage, in the absence of high densities of neurons. The main mechanism of synapse formation is the ...

Web traffic has continued to increase at a significant rate and is resulting in considerable strain on web servers and bandwidth providers, such as Internet Service Providers (ISPs). Proxy caches are often used to reduce this burden. In this research, a novel approach to web proxy cache replacement is developed. Unlike previous approaches, this research utilizes neural networks for replacement ...

The synchronization of neural signals has been proposed as a tem poral coding scheme in distributed cortical networks Theoretical studies in that direction mainly focused on the synchronization of cou pled oscillatory subsystems In the present work we show that several complex types of synchronization previously described for graded re sponse neurons appear similarly also in biologically realis...

While deeper and wider neural networks are actively pushing the performance limits of various computer vision and machine learning tasks, they often require large sets of labeled data for effective training and suffer from extremely high computational complexity. In this paper, we will develop a new framework for training deep neural networks on datasets with limited labeled samples using cross...

Mechanisms for the induction of motor learning in the vestibulo-ocular reflex (VOR) were evaluated by recording the patterns of neural activity elicited in the cerebellum by a range of stimuli that induce learning. Patterns of climbing-fiber, vestibular, and Purkinje cell simple-spike signals were examined during sinusoidal head movement paired with visual image movement at stimulus frequencies...

The analysis of the outgrowth pattern of spinal axons in the chick embryo has shown that somites are polarized into anterior and posterior halves. This polarity dictates the segmental development of the peripheral nervous system: migrating neural crest cells and outgrowing spinal axons traverse exclusively the anterior halves of the somite-derived sclerotomes, ensuring a proper register between...

While deeper and wider neural networks are actively pushing the performance limits of various computer vision and machine learning tasks, they often require large sets of labeled data for effective training and suffer from extremely high computational complexity. In this paper, we will develop a new framework for training deep neural networks on datasets with limited labeled samples using cross...

Data mining technology is applied to extract the water supply operation rules in this study. Five characteristic attributes—reservoir storage water, operation period number, water demand, runoff, and hydrological year—are chosen as the dataset, and these characteristic attributes are applied to build a mapping relation with the optimal operation mode calculated by dynamic programming (DP). A Le...

This paper proposes an adaptive neural predictive nonlinear controller to guide a nonholonomic wheeled mobile robot during continuous and non-continuous gradients trajectory tracking. The structure of the controller consists of two models that describe the kinematics and dynamics of the mobile robot system and a feedforward neural controller. The models are modified Elman neural network and fee...