In this paper, a cognitive system based on a nonlinear neural controller and intelligent algorithm that will guide an autonomous mobile robot during continuous path-tracking and navigate over solid obstacles with avoidance was proposed. The goal of the proposed structure is to plan and track the reference path equation for the autonomous mobile robot in the mining environment to avoid the obstacles and reach to the target position by using intelligent optimization algorithms. Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) Algorithms are used to finding the solutions of the mobile robot navigation problems in the mine by searching the optimal paths and finding the reference path equation of the optimal

n this research, some thermophysical properties of ethylene glycol with water (H2O) and two solvent mixtures dimethylformamide/ water (DMF + H2O) were studied. The densities (ρ) and viscosities (η) of ethylene glycol in water and a mixed solvent dimethylformamide (DMF + H2O) were determined at 298.15 K, t and a range of concentrations from 0.1 to1.0 molar. The ρ and η values were subsequently used to calculate the thermodynamics of mixing including the apparent molar volume (ϕv), partial molar volume (ϕvo) at infinite dilution. The solute-solute interaction is presented by Sv results from the equation ∅_v=ϕ_v^o+S_v √m. The values of viscosity (B) coefficients and Falkenhagen coefficient(A) of the Jone-Dole equation and Gibbs free

A simple, sensitive and rapid method was used for the estimate of: Propranolol with Bi (III) to prove the efficiency, reliability and repeatability of the long distance chasing photometer (NAG-ADF-300-2) using continuous flow injection analysis. The method is based on a reaction between propranolol and Bi (III) in an aqueous medium to obtain a yellow precipitate. Optimum parameters were studied to increase the sensitivity for the developed method. A linear range for calibration graph was 0.1-25 mmol/L for cell A and 1-40 mmol/L for cell B, and LOD 51.8698 ng/200 µL and 363.0886 ng /200 µL , respectively to cell A and cell B with correlation coefficient (r) 0.9975 for cell A, 0.9966 for cell B, RSD% was lower than 1%, (n = 8) for the

The radial wave functions of the Bear–Hodgson potential have been used to study the ground state features such as the proton, neutron and matter densities and the as- sociated rms radii of two neutrons halo 6He, 11Li, 14Be and 17B nuclei. These halo nuclei are treated as a three-body system composed of core and outer two-neutron (Core + n + n). The radial wave functions of the Bear–Hodgson potential are used to describe the core and halo density distributions. The interaction of core-neutron takes the Bear–Hodgson potential form. The outer two neutrons of 6He and 11Li interact by the realistic interaction REWIL whereas those of 14Be and 17B interact by the realistic interaction of HASP. The obtained results show that this model succee

Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c

A total of 48 experiments were conducted to investigate the impact of slit weir dimensions and locations on the maximum scour depth and scour area created upstream. The slit weir model was a 110 mm slit opening, and it was installed at the end of the working section in a laboratory flume. The flume was 10.0 m long, 30 cm wide, 30 cm deep, and almost middle. It includes a 2 m working section with a mobile bed with 110 mm in thickness. In the mobile bed, two types of nonuniform sand (with a geometric standard deviation of 1.58 and 1.6) were tested separately. The weir dimensions and location were changed with flow rates. Then dimensions of the slit weir were changed from 60 x 110 mm to 60 x 70 mm (width x height), while th

Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration

This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number

Survival analysis is widely applied to data that described by the length of time until the occurrence of an event under interest such as death or other important events. The purpose of this paper is to use the dynamic methodology which provides a flexible method, especially in the analysis of discrete survival time, to estimate the effect of covariate variables through time in the survival analysis on dialysis patients with kidney failure until death occurs. Where the estimations process is completely based on the Bayes approach by using two estimation methods: the maximum A Posterior (MAP) involved with Iteratively Weighted Kalman Filter Smoothing (IWKFS) and in combination with the Expectation Maximization (EM) algorithm. While the other

   The region of Kirkuk and its surrounding areas, including (Baba, Jambour, Qara Chuq, Qaiyarah, Demir Dagh, Bai Hassan, Taq Taq, Makhul, Gilabat as well as southern Mosul and the cities of Erbil and Sulymania, are known as one of the oldest discovered oil fields in northern Iraq. This area presents a significant opportunity for further organic geochemical analysis to describe maturation zones and estimate economically generated hydrocarbons with particular reference to the Sargelu formation, to enhance hydrocarbons productivity. To assess the potential of these oil fields, it is essential to perform correlation, comparisons, and geochemical analyses of the data collected from exploration wells in the surrounding area. This appro