Al-Khwarizmi Engineering Journal,
Vol.1, No. 2(2005)
Dr.A.barsoum, Entather Mahos
Fuzzy Wavenet (FWN) classifier for medical images
The combination of wavelet theory and neural networks has lead to the development of wavelet networks. Wavelet networks are feed-forward neural networks using wavelets as activation function. Wavelets networks have been used in classification and identification problems with some success.
In this work we proposed a fuzzy wavenet network (FWN), which learns by common back-propagation algorithm to classify medical images. The library of medical image has been analyzed, first. Second, Two experimental tables’ rules provide an excellent opportunity to test the ability of fuzzy wavenet network due to the high level of information variability often experienced with this type of images.
Dr. Tarik Zeyad
Human Face Recognition Using Wavelet Network
Dr. Walid A. Mahmoud
Dr. Mohammed N. Al-Turfi
FPGA Realization of Two-Dimensional Wavelet and Wavelet Packet Transform
The Field Programmable Gate Array (FPGA) approach is the most recent category, which takes the place in the implementation of most of the Digital Signal Processing (DSP) applications. It had proved the capability to handle such problems and supports all the necessary needs like scalability, speed, size, cost, and efficiency.
In this paper a new proposed circuit design is implemented for the evaluation of the coefficients of the two-dimensional Wavelet Transform (WT) and Wavelet Packet Transform (WPT) using FPGA is provided.
Dr.Nabil Hassan Hadi
Fuzzy control of mobile robot in slippery environment
Dr. Kamal K.M. Saify
Dr. Adnan N.J. Al-Temimy
Dr. Muhsin J.J
The Timoshenko Three-Beams Technique To EstimateThe Main Elastic Moduli Of Orthotropic Homogeneous Materials
Soroor K. Al-Khafaji
Dr. Nihad Al-Rahman
Dr. Zuhair I. Al- Dauod
Design of a Programmable System for Failure Modes
And Effect Analysis of Steam-Power Plant Based on the Fault Tree Analysis
In this paper, the system of the power plant has been investigated as a special type of industrial systems, which has a significant role in improving societies since the electrical energy has entered all kinds of industries, and it is considered as the artery of modern life.
The aim of this research is to construct a programming system, which could be used to identify the most important failure modes that are occur in a steam type of power plants. Also the effects and reasons of each failure mode could be analyzed through the usage of this programming system reaching to the basic events (main reasons) that causing each failure mode. The construction of this system for FMEA is depending on the logical relationships of the fault tree analysis for the systems that contained in the power station.
Dr: Hussain A.Dawood
Oday. I. Abdullah
Free Vibration Analysis for Dynamic Stiffness Degradation of Cracked Cantilever Plate
Mathematical Modeling for the Clarifier Units and Turbidity
Parameters in AL-KARAMA Treatment Plant
The high cost of chemical analysis of water has necessitated various researches into finding alternative method of determining portable water quality. This paper is aimed at modelling the turbidity value as a water quality parameter. Mathematical models for turbidity removal were developed based on the relationships between water turbidity and other water criteria. Results showed that the turbidity of water is the cumulative effect of the individual parameters/factors affecting the system. A model equation for the evaluation and prediction of a clarifier’s performance was developed:
Model: T = T0(-1.36729 + 0.037101∙10λpH + 0.048928t + 0.00741387∙alk)
The developed model will aid the predictive assessment of water treatment plant performance.
The limitations of the models are as a result of insufficient variable considered during the conceptualization.