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Fuzzy Wavenet (FWN) classifier for medical images
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    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.

 We have known that the wavelet transformation is more accurate in small dimension problem. But image processing is large dimension problem then we used neural network. Results are presented on the application on the three layer fuzzy wavenet to vision system. They demonstrate a considerable improvement in performance by proposed two table’s rule for fuzzy and deterministic dilation and translation in wavelet transformation techniques.

    

 

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Publication Date
Sat Nov 01 2014
Journal Name
Al-khwarizmi Engineering Journal
Experimental and Theoretical Investigation of Impact Dynamic Plasticity for CK45
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This paper represents a study of the effect of the soil type, the drilling parameters and the drilling tool properties on the dynamic vibrational behavior of the drilling rig and its assessment in the drilling system. So first, an experimental drilling rig was designed and constructed to embrace the numerical work.

The experimental work included implementation of the drill-string in different types of soil with different properties according to the difference in the grains size, at different rotational speeds (RPM), and different weights on bit (WOB) (Thrust force), in a way that allows establishing the charts that correlate the vibration acceleration, the rate of penetration (ROP), and the power

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Publication Date
Fri Jun 01 2007
Journal Name
Journal Of Al-nahrain University Science
ON THE GREEDY RADIAL BASIS FUNCTION NEURAL NETWORKS FOR APPROXIMATION MULTIDIMENSIONAL FUNCTIONS
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The aim of this paper is to approximate multidimensional functions by using the type of Feedforward neural networks (FFNNs) which is called Greedy radial basis function neural networks (GRBFNNs). Also, we introduce a modification to the greedy algorithm which is used to train the greedy radial basis function neural networks. An error bound are introduced in Sobolev space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result is published in [16]).

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Publication Date
Sat Feb 25 2017
Journal Name
International Journal On Advanced Science, Engineering And Information Technology
A Novel DNA Sequence Approach for Network Intrusion Detection System Based on Cryptography Encoding Method
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A novel method for Network Intrusion Detection System (NIDS) has been proposed, based on the concept of how DNA sequence detects disease as both domains have similar conceptual method of detection. Three important steps have been proposed to apply DNA sequence for NIDS: convert the network traffic data into a form of DNA sequence using Cryptography encoding method; discover patterns of Short Tandem Repeats (STR) sequence for each network traffic attack using Teiresias algorithm; and conduct classification process depends upon STR sequence based on Horspool algorithm. 10% KDD Cup 1999 data set is used for training phase. Correct KDD Cup 1999 data set is used for testing phase to evaluate the proposed method. The current experiment results sh

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Publication Date
Sun Dec 30 2018
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of penetration Rate and cost with Artificial Neural Network for Alhafaya Oil Field
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Prediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs. This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process. This paper shows a new technique of rate of penetration prediction by using artificial neural network technique. A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field. These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT). Five data set represented five formations gathered

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Publication Date
Sun Dec 30 2018
Journal Name
Journal Of Engineering
A Cognition Path Planning with a Nonlinear Controller Design for Wheeled Mobile Robot Based on an Intelligent Algorithm
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This paper presents a cognition path planning with control algorithm design for a nonholonomic wheeled mobile robot based on Particle Swarm Optimization (PSO) algorithm. The aim of this work is to propose the circular roadmap (CRM) method to plan and generate optimal path with free navigation as well as to propose a nonlinear MIMO-PID-MENN controller in order to track the wheeled mobile robot on the reference path. The PSO is used to find an online tune the control parameters of the proposed controller to get the best torques actions for the wheeled mobile robot. The numerical simulation results based on the Matlab package show that the proposed structure has a precise and highly accurate distance of the generated refere

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Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Analytical Solutions for Advanced Functional Differential Equations with Discontinuous Forcing Terms and Studying Their Dynamical Properties
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This paper aims to find new analytical closed-forms to the  solutions of the nonhomogeneous functional differential equations of the nth order with finite and constants delays and various initial delay conditions in terms of elementary functions using Laplace transform method. As well as, the definition of dynamical systems for ordinary differential equations is used to introduce the definition of dynamical systems for delay differential equations which contain multiple delays with a discussion of their dynamical properties: The exponential stability and strong stability

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Publication Date
Thu Dec 28 2017
Journal Name
Al-khwarizmi Engineering Journal
Tuning PID Controller by Neural Network for Robot Manipulator Trajectory Tracking
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Ziegler and Nichols proposed the well-known Ziegler-Nichols method to tune the coefficients of PID controller. This tuning method is simple and gives fixed values for the coefficients which make PID controller have weak adaptabilities for the model parameters variation and changing in operating conditions. In order to achieve adaptive controller, the Neural Network (NN) self-tuning PID control is proposed in this paper which combines conventional PID controller and Neural Network learning capabilities. The proportional, integral and derivative (KP, KI, KD) gains are self tuned on-line by the NN output which is obtained due to the error value on the desired output of the system under control. The conventio

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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Green Synthesis of Silver Nanoparticles Using Aqueous Extract of Typha domingensis Pers. Pollen (qurraid) and Evaluate its Antibacterial Activity
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In this study, the aqueous extract of (Typha domingensis Pers.) pollen grain (qurraid) to know its ability to manufacture silver nanoparticles. Qurraid is a semi-solid yellow food substance, sold in Basra markets and eaten by the local population. It is made from the pollen of the T.  domingensis Pers. plant after being pressed and treated with water vapor. The Gas chromatography–mass spectrometry (GC-MS) reaction was done to identify the active compounds of qurraid aqueous extract. The ability of the aqueous extract of qurraid to manufacture silver nanoparticles was tested, and the construction of silver nanoparticles was inferred by the reaction mixture's color, which ranged from yellow to dark brown. The synthesi

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Publication Date
Sun Dec 17 2017
Journal Name
Al-khwarizmi Engineering Journal
Experimental and Prediction Using Artificial Neural Network of Bed Porosity and Solid Holdup in Viscous 3-Phase Inverse Fluidization
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In the present investigation, bed porosity and solid holdup in viscous three-phase inverse fluidized bed (TPIFB) are determined for aqueous solutions of carboxy methyl cellulose (CMC) system using polyethylene and polypropylene as  a particles with low-density and diameter (5 mm) in a (9.2 cm) inner diameter with height (200 cm) of vertical perspex column. The effectiveness of gas velocity Ug , liquid velocity UL, liquid viscosity μL, and particle density ρs on bed porosity BP and solid holdups εg were determined. The bed porosity increases with "increasing gas velocity", "liquid velocity", and "liquid viscosity". Solid holdup decreases with increasing gas, liquid

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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
" Forecasting Future Cash Flows Using the Metrics of Cash Flow and the Accounting Return "
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Providing useful information in estimating the amount and timing and the degree of uncertainty concerning the future cash flows is one of the three main objectives of the financial reporting system, which is done through the main financial statements. The interest on standard-setting bodies in the forecasting of future cash flows, especially Financial Accounting Standards Board (FASB) explain under Accounting Standard (1) of the year 1978 "Objectives of Financial Reporting by Business Enterprises", paragraph (37) thereof that accounting profits better than cash flows when forecasting future cash flows, In contrast, IAS (7) as amended in 1992 aims to compel economic units to prepare statement of c

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