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 implemented based on hybrid Crossoved Firefly Algorithm with Artificial Bee Colony (CFA-ABC) to tune the controller's parameters to achieve the optimal path. The performance of the hybrid optimization algorithm is verified by various benchmark functions. The simulation results show that the utilizing of CFA and (CFA-ABC ) are better than the original Firefly Algorithm. A simulation example is given to indicate the effectiveness of the proposed algorithm, the results have been done using MATLAB (R2013b), and all trajectory tracking results with two reference trajectories (circular and lemniscates ) are presented.
Metaheuristics under the swarm intelligence (SI) class have proven to be efficient and have become popular methods for solving different optimization problems. Based on the usage of memory, metaheuristics can be classified into algorithms with memory and without memory (memory-less). The absence of memory in some metaheuristics will lead to the loss of the information gained in previous iterations. The metaheuristics tend to divert from promising areas of solutions search spaces which will lead to non-optimal solutions. This paper aims to review memory usage and its effect on the performance of the main SI-based metaheuristics. Investigation has been performed on SI metaheuristics, memory usage and memory-less metaheuristics, memory char
... Show MoreThis paper deals with defining Burr-XII, and how to obtain its p.d.f., and CDF, since this distribution is one of failure distribution which is compound distribution from two failure models which are Gamma model and weibull model. Some equipment may have many important parts and the probability distributions representing which may be of different types, so found that Burr by its different compound formulas is the best model to be studied, and estimated its parameter to compute the mean time to failure rate. Here Burr-XII rather than other models is consider because it is used to model a wide variety of phenomena including crop prices, household income, option market price distributions, risk and travel time. It has two shape-parame
... Show MoreSilver/polyvinyl alcohol (Ag/PVA) nanocomposite films were synthesized via solution casting with varying concentrations of Ag nanoparticles (1–5 wt%). A comprehensive investigation was conducted to understand the influence of Ag content on the structural, optical, mechanical, thermal, electrical, and antibacterial properties of the composites. UV-Vis spectroscopy revealed a red shift in absorption peaks and a reduction in the optical band gap, which decreased from 3.78 eV for pure PVA to 3.37 eV for the 5 wt% Ag composite. FTIR and SEM analyses confirmed successful nanoparticle incorporation and morphological changes. The nanocomposites exhibited enhanced tensile strength, elongation at break, Young’s modulus, and hardness due t
... Show MoreSignal denoising is directly related to sample estimation of received signals, either by estimating the equation parameters for the target reflections or the surrounding noise and clutter accompanying the data of interest. Radar signals recorded using analogue or digital devices are not immune to noise. Random or white noise with no coherency is mainly produced in the form of random electrons, and caused by heat, environment, and stray circuitry loses. These factors influence the output signal voltage, thus creating detectable noise. Differential Evolution (DE) is an effectual, competent, and robust optimisation method used to solve different problems in the engineering and scientific domains, such as in signal processing. This paper looks
... Show MoreThis paper proposes a new method Object Detection in Skin Cancer Image, the minimum
spanning tree Detection descriptor (MST). This ObjectDetection descriptor builds on the
structure of the minimum spanning tree constructed on the targettraining set of Skin Cancer
Images only. The Skin Cancer Image Detection of test objects relies on their distances to the
closest edge of thattree. Our experimentsshow that the Minimum Spanning Tree (MST) performs
especially well in case of Fogginessimage problems and in highNoisespaces for Skin Cancer
Image.
The proposed method of Object Detection Skin Cancer Image wasimplemented and tested on
different Skin Cancer Images. We obtained very good results . The experiment showed that
The digital revolution had greatly affected the methods through which we communicate, starting from the basic concepts of the internet technology and the web content in addition to the important issues that concern the culture of the digital media, the internet governance and the variation in the digital age in general and the graphic and internal design in particular.
This research addresses an important topic that goes along with the scientific development in the field of the digital design, especially in the internal and graphic designs. This study consists of two sections: the first includes the problem of the study and the need for it. Starting from the problem of the research, there is no clear perception of the formal characte
The aim of this research is to apply the concept of total value management to improve the process design of producing the toothpaste in Al Mammon factory one of the in the general company of food industry. The concept of total value management is concerning with achieve more than one values which are important for the customers as these values are related to the customers satisfaction. The research problem is that the factory did not measure the effectiveness of process design as this company has weakness in analyzing this effectiveness in synchronies with total value management. On the other side, the company did not give more attention to the cost of products and selling prices within the value cost/ profit which is one of the
... Show MoreThis study proposed using color components as artificial intelligence (AI) input to predict milk moisture and fat contents. In this sense, an adaptive neuro‐fuzzy inference system (ANFIS) was applied to milk processed by moderate electrical field‐based non‐thermal (NP) and conventional pasteurization (CP). The differences between predicted and experimental data were not significant (