The study deals with reactivity insertion linear and non linear and/or Ramp reactivity expressed as a polynomial in time in the presence of two Feedback mechanisms, using the neutronic-thermohydraulic coupling in order to predict the neutron behavior as a function of time in terms of reactor power. Also, a comparative study has been achieved in the case of the presence of the feedback mechanisms. Insertion of Ramp reactivities in terms of polynomial in time to study the behavior of power and reactivity as a function of time in the presence of two feedback mechanisms (fuel and coolant) has been carried out and the results are displayed as plots, and showed this results corresponding with international results. The present study shows t

The Next-generation networks, such as 5G and 6G, need capacity and requirements for low latency, and high dependability. According to experts, one of the most important features of (5 and 6) G networks is network slicing. To enhance the Quality of Service (QoS), network operators may now operate many instances on the same infrastructure due to configuring able slicing QoS. Each virtualized network resource, such as connection bandwidth, buffer size, and computing functions, may have a varied number of virtualized network resources. Because network resources are limited, virtual resources of the slices must be carefully coordinated to meet the different QoS requirements of users and services. These networks may be modifie

In this paper, SiO2 nanoparticles thin films were synthesised at different PH values of solution by sol gel method at fixed temperature (25oC) and molar ratio (R =H2O/precursor) of (Tetra Ethyl Ortho Silicate) TEOS as precursor at (R=1). The structure and optical properties of the thin films have been investigated. All thin films were tested by using X-RAY diffraction. All X-RAY spectrum can be indexed as monoclinic structure with strong crystalline (110) plane. The morphological properties of the prepared films were studied by SEM. The results indicate that all films are in nano scale and the particle size around (19-62) nm .The size of silica particles increases with increasing PH value of solution where both the rate of hydrolysis and

Human posture estimation is a crucial topic in the computer vision field and has become a hotspot for research in many human behaviors related work. Human pose estimation can be understood as the human key point recognition and connection problem. The paper presents an optimized symmetric spatial transformation network designed to connect with single-person pose estimation network to propose high-quality human target frames from inaccurate human bounding boxes, and introduces parametric pose non-maximal suppression to eliminate redundant pose estimation, and applies an elimination rule to eliminate similar pose to obtain unique human pose estimation results. The exploratory outcomes demonstrate the way that the proposed technique can pre

The increase globally fossil fuel consumption as it represents the main source of energy around the world, and the sources of heavy oil more than light, different techniques were used to reduce the viscosity and increase mobility of heavy crude oil. this study focusing on the experimental tests  and modeling with Back Feed Forward Artificial Neural Network (BFF-ANN) of the dilution technique to reduce a  heavy oil viscosity that was collected from the south- Iraq oil fields using organic solvents, organic diluents with different weight percentage  (5, 10 and  20 wt.% )  of  (n-heptane, toluene, and a mixture of  different ratio

 In this paper, the human robotic leg which can be represented mathematically by single input-single output (SISO) nonlinear differential model with one degree of freedom, is analyzed and then a simple hybrid neural fuzzy controller is designed to improve the performance of this human robotic leg model. This controller consists from SISO fuzzy proportional derivative (FPD) controller with nine rules summing with single node neural integral derivative (NID) controller with nonlinear function. The Matlab simulation results for nonlinear robotic leg model with the suggested controller showed that the efficiency of this controller when compared with the results of the leg model that is controlled by PI+2D, PD+NID, and F

Fluidization process is widely used by a great assortment of industries worldwide and represents a trillion dollar industry [6]. They are currently used in separation, classification, drying and mixing of particles, chemical reactions and regeneration processes; one of these processes is the mass transfer from an immersed surface to a gas fluidized bed

The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed

ABSTRACT: Ultimate bearing capacity of soft ground reinforced with stone column was recently predicted using various artificial intelligence technologies such as artificial neural network because of all the advantages that they can offer in minimizing time, effort and cost. As well as, most of applied theories or predicted formulas deduced analytically from previous studies were feasible only for a particular testing environment and do not match other field or laboratory datasets. However, the performance of such techniques depends largely on input parameters that really affect the target output and missing of any parameter can lead to inaccurate results and give a false indicator. In the current study, data were collected from previous rel