scholarly journals Modeling of stochastic brain function in artificial intelligence

2019 ◽  
Vol 4 (3) ◽  
pp. 8-14
Author(s):  
Andrei N. Volobuev ◽  
Vasiliy F. Pyatin ◽  
Natalya P. Romanchuk ◽  
Petr I. Romanchuk ◽  
Svetlana V. Bulgakova
Keyword(s):  
Mathematical Modeling ◽  
Artificial Intelligence ◽  
Brain Function ◽  
Brain Activity ◽  
Necessary Condition ◽  
Alpha Wave ◽  
Brain Functioning ◽  
One Dimensional ◽  
The One ◽  
Stochastic Mode

Objectives -research of stochastic brain function in respect to creation of artificial intelligence. Material and methods. Mathematical modeling principles were used for simulation of brain functioning in a stochastic mode. Results. Two types of brain activity were considered: determinated type, usually modeled using the perceptron, and stochastic type. It is shown, that stochastic brain function modeling is the necessary condition for AI to become capable of creativity, generation of new knowledge. Mathematical modeling of a neural network of the cerebral cortex, consisting of the set of the cyclic neuronal circuits (memory units), was performed for the stochastic mode of brain functioning. Models of "two-dimensional" and "one-dimensional" brain were analyzed. The pattern of excitation in memory units was calculated in the "one-dimensional" brain model. Conclusion. Relying on the knowledge of the stochastic mode of brain function, a way of creation of AI can be offered. а-rhythm of a patient is a recommended focus of the therapist's attention in diagnostics and treatment of brain disorders. It was noted, that the alpha wave amplitude and frequency could indicate the cognitive, creative and intuitive abilities of a person.

THE FINITE-DIFFERENCE METHOD OF ONE-DIMENSIONAL NONLINEAR SYSTEMS ANALYSIS

Fractals ◽  
2000 ◽  
Vol 08 (01) ◽  
pp. 49-65 ◽  
Author(s):  
A. YU. SHAHVERDIAN
Keyword(s):  
Time Series ◽  
Systems Analysis ◽  
Computational Study ◽  
Brain Activity ◽  
Logistic Map ◽  
Cantor Sets ◽  
Point Of View ◽  
One Dimensional ◽  
Time Flow ◽  
The One

The paper introduces one-dimensional analogy of Poincare "section" method. It reduces the one-dimensional nonlinear system orbit's study to consideration of some special conjugate orbit's "asymptotical" intersections with a thin arithmetical space of zero Lebesgue measure. The application of this approach to analysis of the logistic map orbits, earthquake time-series, and the sequences of fractional parts, is considered. Through computational study of these time-series, the existence of some Cantor sets, to which the conjugate orbits are attracted, is established. A fractal dynamical system, describing these different systems from a unified point of view, is introduced. The inner differential Cantorian structure of brain activity and time flow is discussed.

scholarly journals Mathematical Modeling of a Class of Symmetrical Islamic Design

Symmetry ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 517
Author(s):  
Mostafa ZAHRI
Keyword(s):  
Mathematical Modeling ◽  
Unit Circle ◽  
Convergence Properties ◽  
Periodic Sequences ◽  
New Model ◽  
One Dimensional ◽  
Geometric Patterns ◽  
Interesting Class ◽  
The One

In this paper, we present a new model for simulating an interesting class of Islamic design. Based on periodic sequences on the one-dimensional manifolds, and from emerging numbers, we construct closed graphs with edges on the unit circle. These graphs build very nice shapes and lead to a symmetrical class of geometric patterns of so-called Islamic design. Moreover, we mathematically characterize and analyze some convergence properties of the used up-down sequences. Finally, four planar type of patterns are simulated.

Modeling of washout of a well-killing liquid after launching of an oil well

2020 ◽  
Vol 15 (3-4) ◽  
pp. 167-175
Author(s):  
A.S. Topolnikov
Keyword(s):  
Mathematical Modeling ◽  
Multicomponent Mixture ◽  
Variable Density ◽  
Oil Well ◽  
One Dimensional ◽  
Reservoir Fluid ◽  
Pump Head ◽  
Measuring Field ◽  
The One ◽  
Bottomhole Pressure

The paper presents the results of mathematical modeling of the process of launching and output to the mode of an oil well, which was uploaded by a well-killing liquid at the stage of repairs. After the launching of the electric submergible pump the drop of the bottomhole pressure occurs and the inflow of reservoir fluid begins. As a result the multicomponent mixture is generated inside the well, which consists of oil, associated water, well-killing liquid and free gas, originated from the oil during degassing, and this mixture is pumped out towards wellhead. As soon as the pump characteristics are changed, when the liquid with variable density is pumped out, it is necessary to control the speed of a shaft of the pump for providing the stable pump regime. This problem is solved in the paper for different ratios of densities of well-killing liquid and reservoir fluid by the mathematical modeling of multiphase flow in the well elements and inside the pump. As a mathematical model the one-dimensional quasi-stationary model in approach of drift for description of relative motion of the components is applied, which proved itself well for modeling of non-stationary processes lasting for several days. The comparison of calculated and measuring field parameters is presented. It is shown that the speed of washout of the well-killing liquid from the oil well and the probability of the pump stop due to its head failure depend on the ration of densities of the well-killing liquid and reservoir fluid. It is stated that the monitoring of change of parameters of the pump in time through the mathematical modeling can help to optimize the output to the mode of the well. This allows to avoid stops due to the pump head failure and to diminish the electricity costs.

Methods of mathematical modeling of non-Gaussian random variables quantities and processes

2019 ◽  
pp. 15-21
Author(s):  
V. M. Artyushenko ◽  
V. I. Volovach
Keyword(s):  
Mathematical Modeling ◽  
Gaussian Noise ◽  
Random Variables ◽  
Random Processes ◽  
Mathematical Methods ◽  
Gaussian Random Variables ◽  
One Dimensional ◽  
The One ◽  
Non Gaussian ◽  
Stationary Random Processes

Mathematical methods allowing to model non-Gaussian random variables and processes are considered. The models and description of non-Gaussian correlated processes in the form of generated Gaussian noise are analyzed, as well as the methods of formation of stationary random processes defined by the one-dimensional density distribution of Vero -abilities and the autocorrelation function. Examples of formation of non-Gaussian random variables and processes are given.

scholarly journals Fuzzy String Matching Using a Prefix Table

2020 ◽  
pp. 116-121
Author(s):  
Armen Kostanyan
Keyword(s):  
Artificial Intelligence ◽  
Finite State Machine ◽  
String Matching ◽  
Two Dimensional ◽  
Matching Problem ◽  
Machine Method ◽  
One Dimensional ◽  
Finite State ◽  
Fuzzy Pattern ◽  
The One

The string matching problem (that is, the problem of finding all occurrences of a pattern in the text) is one of the well-known problems in symbolic computations with applications in many areas of artificial intelligence. The most famous algorithms for solving it are the finite state machine method and the Knuth-Morris-Pratt algorithm (KMP). In this paper, we consider the problem of finding all occurrences of a fuzzy pattern in the text. Such a pattern is defined as a sequence of fuzzy properties of text characters. To construct a solution to this problem, we introduce a two-dimensional prefix table, which is a generalization of the one-dimensional prefix array used in the KMP algorithm.

Exploring the Multidimensional Facets of Authoritarianism: Authoritarian Aggression and Social Dominance Orientation

2008 ◽  
Vol 67 (1) ◽  
pp. 51-60 ◽  
Author(s):  
Stefano Passini
Keyword(s):  
Social Dominance ◽  
Factor Model ◽  
Three Dimensional ◽  
Social Dominance Orientation ◽  
Model Fit ◽  
Regression Analyses ◽  
One Dimensional ◽  
Confirmatory Factor ◽  
The One ◽  
Better Than

The relation between authoritarianism and social dominance orientation was analyzed, with authoritarianism measured using a three-dimensional scale. The implicit multidimensional structure (authoritarian submission, conventionalism, authoritarian aggression) of Altemeyer’s (1981, 1988) conceptualization of authoritarianism is inconsistent with its one-dimensional methodological operationalization. The dimensionality of authoritarianism was investigated using confirmatory factor analysis in a sample of 713 university students. As hypothesized, the three-factor model fit the data significantly better than the one-factor model. Regression analyses revealed that only authoritarian aggression was related to social dominance orientation. That is, only intolerance of deviance was related to high social dominance, whereas submissiveness was not.

Skipping Breakfast Affects the Early Steps of Cognitive Processing

2019 ◽  
Vol 33 (2) ◽  
pp. 109-118
Author(s):  
Andrés Antonio González-Garrido ◽  
Jacobo José Brofman-Epelbaum ◽  
Fabiola Reveca Gómez-Velázquez ◽  
Sebastián Agustín Balart-Sánchez ◽  
Julieta Ramos-Loyo
Keyword(s):  
Working Memory ◽  
Cognitive Processing ◽  
Task Difficulty ◽  
Brain Activity ◽  
Reaction Times ◽  
Brain Potentials ◽  
Brain Functioning ◽  
Attentional Processes ◽  
Electrical Brain Activity ◽  
Skipping Breakfast

Abstract. It has been generally accepted that skipping breakfast adversely affects cognition, mainly disturbing the attentional processes. However, the effects of short-term fasting upon brain functioning are still unclear. We aimed to evaluate the effect of skipping breakfast on cognitive processing by studying the electrical brain activity of young healthy individuals while performing several working memory tasks. Accordingly, the behavioral results and event-related brain potentials (ERPs) of 20 healthy university students (10 males) were obtained and compared through analysis of variances (ANOVAs), during the performance of three n-back working memory (WM) tasks in two morning sessions on both normal (after breakfast) and 12-hour fasting conditions. Significantly fewer correct responses were achieved during fasting, mainly affecting the higher WM load task. In addition, there were prolonged reaction times with increased task difficulty, regardless of breakfast intake. ERP showed a significant voltage decrement for N200 and P300 during fasting, while the amplitude of P200 notably increased. The results suggest skipping breakfast disturbs earlier cognitive processing steps, particularly attention allocation, early decoding in working memory, and stimulus evaluation, and this effect increases with task difficulty.

Sign in / Sign up

Export Citation Format

Share Document