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

The paper present design of a control structure that enables integration of a Kinematic neural controller for trajectory tracking of a nonholonomic differential two wheeled mobile robot, then  proposes a Kinematic neural controller to direct a National Instrument mobile robot (NI Mobile Robot). The controller is to make the actual velocity of the wheeled mobile robot close the required velocity by guarantees that the trajectory tracking mean squire error converges at minimum tracking error. The proposed tracking control system consists of two layers; The first layer is a multi-layer perceptron neural network system that controls the mobile robot to track the required path , The second layer is an optimization layer ,which is impleme

One of the most important elements of achieving food security is livestock, which is an essential element in the agricultural sector, and is one of the state support sectors. Animal production (sheep) ranked an important position in this sector due to the economic advantages that are available when rearing. Moreover, the success and development of sheep breeding depend on several factors, including financial return and achieving profitability. The study aims to identify the phenomenon size of random slaughter as a problem, which spread in Baghdad and its causes and the factors that influencing its development. As well as, the possibility of applying the idea of a​​mobile slaughterhouse to reduce this phenomen

A program in Visual Basic language was designed to predict the type of radio storm that emitted from Jupiter at specific Local Time (LT) from two different Iraqi locations (Baghdad and Basra), such storms result from the Central Meridian Longitude (CML) of system ??? for Jupiter and phase of Io’s satellite (?Io). Some of these storms are related to position of Io (Io- A,B,C,D) and others are unrelated (non-Io-A,B,C,D) to its position. The input parameters for this program were user specified by determining the observer’s location (longitude), year, month and day. The output program results in form of tables provides the observer with information about the date and the LT of beginning and end of each type of emitted storm. Two Io-storm r

Sensibly highlighting the hidden structures of many real-world networks has attracted growing interest and triggered a vast array of techniques on what is called nowadays community detection (CD) problem. Non-deterministic metaheuristics are proved to competitively transcending the limits of the counterpart deterministic heuristics in solving community detection problem. Despite the increasing interest, most of the existing metaheuristic based community detection (MCD) algorithms reflect one traditional language. Generally, they tend to explicitly project some features of real communities into different definitions of single or multi-objective optimization functions. The design of other operators, however, remains canonical lacking any inte

Localization is an essential demand in wireless sensor networks (WSNs). It relies on several types of measurements. This paper focuses on positioning in 3-D space using time-of-arrival- (TOA-) based distance measurements between the target node and a number of anchor nodes. Central localization is assumed and either RF, acoustic or UWB signals are used for distance measurements. This problem is treated by using iterative gradient descent (GD), and an iterative GD-based algorithm for localization of moving sensors in a WSN has been proposed. To localize a node in 3-D space, at least four anchors are needed. In this work, however, five anchors are used to get better accuracy. In GD localization of a moving sensor, the algo

Internet paths sharing the same congested link can be identified using several shared congestion detection techniques. The new detection technique which is proposed in this paper depends on the previous novel technique (delay correlation with wavelet denoising (DCW) with new denoising method called Discrete Multiwavelet Transform (DMWT) as signal denoising to separate between queuing delay caused by network congestion and delay caused by various other delay variations. The new detection technique provides faster convergence (3 to 5 seconds less than previous novel technique) while using fewer probe packets approximately half numbers than the previous novel technique, so it will reduce the overload on the network caused by probe packets.