Abstract 

This paper presents an intelligent model reference adaptive control (MRAC) utilizing a self-recurrent wavelet neural network (SRWNN) to control nonlinear systems. The proposed SRWNN is an improved version of a previously reported wavelet neural network (WNN). In particular, this improvement was achieved by adopting two modifications to the original WNN structure. These modifications include, firstly, the utilization of a specific initialization phase to improve the convergence to the optimal weight values, and secondly, the inclusion of self-feedback weights to the wavelons of the wavelet layer. Furthermore, an on-line training procedure was proposed to enhance the control per

The human resources are considered to be the main pillar of the organizations , economic development and the foundation of moving wheels of individual growth. This is considered as the basic tasks for any productive and economic activity . The investment of the human resources is the economic pillar of production , but the most important element of the production . This research tried to access the method of resource investment and to identify the problems and training as key element in establishment of E –government . A questionnaire document have been distributed to the workers at different levels in the colleges and institutes. The research concluded the necessity of job description , continuous training of the workers , usi

This work presents an innovative approach to enhancing the performance of concrete with reclaimed asphalt pavement (RAP) aggregates using titanium dioxide (TiO2) nanoparticles. Traditional limestone coarse aggregates were partially replaced with 30% and 50% RAP aggregates; a subset of mixtures containing RAP aggregates was treated with TiO2 nanoparticles. The rheological, mechanical, and long-term properties of concrete, along with changes in its chemical composition following the addition of RAP and TiO2, were evaluated. Results revealed that using 30% and 50% RAP in concrete mixtures reduced their compressive strength by 18% and 27%, respectively. However, using TiO2 in those mixtures enhanced their compressive strength by 8.7% an

Many financial institutions invest their surplus funds in stocks, either to obtain dividends or for trading purposes and to obtain profits from the difference between the cost and the selling price, and investment in shares represents an important part of the financial position of financial institutions applying to the common accounting system of banks and insurance companies, in addition to their impact It is clear on the result of the activity of these institutions.The aim of the research is to define what the shares and their types are, and to indicate the accounting treatments needed to move towards the process of adopting the International Financial Reporting Standard No. (9) and its reflection on its financial statements. I

Corpus linguistics is a methodology in studying language through corpus-based research. It differs from a traditional approach in studying a language (prescriptive approach) in its insistence on the systematic study of authentic examples of language in use (descriptive approach).A “corpus” is a large body of machine-readable structurally collected naturally occurring linguistic data, either written texts or a transcription of recorded speech, which can be used as a starting-point of linguistic description or as a means of verifying hypotheses about a language.  In the past decade, interest has grown tremendously in the use of language corpora for language education. The ways in which corpora have been employed in language pedago

The process of controlling a Flexible Joint Robot Manipulator (FJRM) requires additional sensors for measuring the state variables of flexible joints. Therefore, taking the elasticity into account adds a lot of complexity as all the additional sensors must be taken into account during the control process. This paper proposes a nonlinear observer that controls FJRM, without requiring equipment sensors for measuring the states. The nonlinear state equations are derived in detail for the FJRM where nonlinearity, of order three, is considered. The Takagi–Sugeno Fuzzy Model (T-SFM) technique is applied to linearize the FJRM system. The Luenberger observer is designed to estimate the unmeasured states using error correction. The develop

Shadow removal is crucial for robot and machine vision as the accuracy of object detection is greatly influenced by the uncertainty and ambiguity of the visual scene. In this paper, we introduce a new algorithm for shadow detection and removal based on different shapes, orientations, and spatial extents of Gaussian equations. Here, the contrast information of the visual scene is utilized for shadow detection and removal through five consecutive processing stages. In the first stage, contrast filtering is performed to obtain the contrast information of the image. The second stage involves a normalization process that suppresses noise and generates a balanced intensity at a specific position compared to the neighboring intensit

<p>The directing of a wheeled robot in an unknown moving environment with physical barriers is a difficult proposition. In particular, having an optimal or near-optimal path that avoids obstacles is a major challenge. In this paper, a modified neuro-controller mechanism is proposed for controlling the movement of an indoor mobile robot. The proposed mechanism is based on the design of a modified Elman neural network (MENN) with an effective element aware gate (MEEG) as the neuro-controller. This controller is updated to overcome the rigid and dynamic barriers in the indoor area. The proposed controller is implemented with a mobile robot known as Khepera IV in a practical manner. The practical results demonstrate that the propo