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An Integrated Grasshopper Optimization Algorithm with Artificial Neural Network for Trusted Nodes Classification Problem
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Wireless Body Area Network (WBAN) is a tool that improves real-time patient health observation in hospitals, asylums, especially at home. WBAN has grown popularity in recent years due to its critical role and vast range of medical applications. Due to the sensitive nature of the patient information being transmitted through the WBAN network, security is of paramount importance. To guarantee the safe movement of data between sensor nodes and various WBAN networks, a high level of security is required in a WBAN network. This research introduces a novel technique named Integrated Grasshopper Optimization Algorithm with Artificial Neural Network (IGO-ANN) for distinguishing between trusted nodes in WBAN networks by means of a classification approach, hence strengthening the safety of such networks. Feature extraction process is done by using Linear Regression-Based Principal Component Analysis (LR-PCA). The test results demonstrated that the proposed IGO-ANN method attains the greatest performance in terms of accuracy, end to end delay and packet delivery ratio regarding trusted WBAN nodes classification than certain existing methods.

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Publication Date
Fri Jun 28 2019
Journal Name
Journal Of The College Of Education For Women
The Effectiveness of an Educational Program For Early Intervention depending on Illustrative Pictures to Acquire some concepts For Children with Hearing impairment
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“Child of today is a man of the future" this slogan is one of the most popular logos of international organizations and institutions that dealing with human beings needs in general and children needs in particular, whether these needs are educational, health, social, or economic. Children require special care and extra legal protection, since the child-raising is not the Child’s own issue, but it's the issue of the society in which he/she would integrate.

As the education and language skillsacquisition primarily associated with hearing, because human being receives most of the skills and knowledge through the hearing; that imitate sounds and learn how to speak isacquired only by hearing, so therefore the hearing - impairedchi

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Publication Date
Wed Oct 07 2020
Journal Name
Journal Of Interdisciplinary Mathematics
Discrete an SIS model with immigrants and treatment
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In this paper, a discrete SIS epidemic model with immigrant and treatment effects is proposed. Stability analysis of the endemic equilibria and disease-free is presented. Numerical simulations are conformed the theoretical results, and it is illustrated how the immigrants, as well as treatment effects, change current model behavior

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Publication Date
Sun Dec 06 2015
Journal Name
Baghdad Science Journal
Solving Two-Points Singular Boundary Value Problem Using Hermite Interpolation
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In this paper, we have been used the Hermite interpolation method to solve second order regular boundary value problems for singular ordinary differential equations. The suggest method applied after divided the domain into many subdomains then used Hermite interpolation on each subdomain, the solution of the equation is equal to summation of the solution in each subdomain. Finally, we gave many examples to illustrate the suggested method and its efficiency.

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Publication Date
Sat Oct 20 2018
Journal Name
Journal Of Economics And Administrative Sciences
Solve the problem of assignment by using multi-Objective programming
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he assignment model represents a mathematical model that aims at expressing an important problem facing enterprises and companies in the public and private sectors, which are characterized by ensuring their activities, in order to take the appropriate decision to get the best allocation of tasks for machines or jobs or workers on the machines that he owns in order to increase profits or reduce costs and time As this model is called multi-objective assignment because it takes into account the factors of time and cost together and hence we have two goals for the assignment problem, so it is not possible to solve by the usual methods and has been resorted to the use of multiple programming The objectives were to solve the problem of

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Publication Date
Sun Jan 01 2023
Journal Name
Advances In The Theory Of Nonlinear Analysis And Its Application
Numerical identification of timewise dependent coefficient in Hyperbolic inverse problem
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Publication Date
Wed Oct 17 2018
Journal Name
Journal Of Economics And Administrative Sciences
Solve the fuzzy Assignment problem by using the Labeling method
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The Assignment model is a mathematical model that aims to express a real problem facing factories and companies which is characterized by the guarantee of its activity in order to make the appropriate decision to get the best allocation of machines or jobs or workers on machines in order to increase efficiency or profits to the highest possible level or reduce costs or time To the extent possible, and in this research has been using the method of labeling to solve the problem of the fuzzy assignment of real data has been approved by the tire factory Diwaniya, where the data included two factors are the factors of efficiency and cost, and was solved manually by a number of iterations until reaching the optimization solution,

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Publication Date
Thu Mar 31 2022
Journal Name
Iraqi Geological Journal
Development of Artificial Intelligence Models for Estimating Rate of Penetration in East Baghdad Field, Middle Iraq
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It is well known that the rate of penetration is a key function for drilling engineers since it is directly related to the final well cost, thus reducing the non-productive time is a target of interest for all oil companies by optimizing the drilling processes or drilling parameters. These drilling parameters include mechanical (RPM, WOB, flow rate, SPP, torque and hook load) and travel transit time. The big challenge prediction is the complex interconnection between the drilling parameters so artificial intelligence techniques have been conducted in this study to predict ROP using operational drilling parameters and formation characteristics. In the current study, three AI techniques have been used which are neural network, fuzzy i

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Publication Date
Fri Apr 20 2018
Journal Name
Iaes International Journal Of Artificial Intelligence (ij-ai)
Optimization of Digital Histopathology Image Quality
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One of the biomedical image problems is the appearance of the bubbles in the slide that could occur when air passes through the slide during the preparation process. These bubbles may complicate the process of analysing the histopathological images. The objective of this study is to remove the bubble noise from the histopathology images, and then predict the tissues that underlie it using the fuzzy controller in cases of remote pathological diagnosis. Fuzzy logic uses the linguistic definition to recognize the relationship between the input and the activity, rather than using difficult numerical equation. Mainly there are five parts, starting with accepting the image, passing through removing the bubbles, and ending with predict the tissues

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Publication Date
Thu Jan 01 2009
Journal Name
2009 Wri International Conference On Communications And Mobile Computing
Optimization of Cooperation Sensing Spectrum Performance
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Cooperation spectrum sensing in cognitive radio networks has an analogy to a distributed decision in wireless sensor networks, where each sensor make local decision and those decision result are reported to a fusion center to give the final decision according to some fusion rules. In this paper the performance of cooperative spectrum sensing examines using new optimization strategy to find optimal weight and threshold curves that enables each secondary user senses the spectrum environment independently according to a floating threshold with respect to his local environment. Our proposed approach depends on proving the convexity of the famous optimization problem in cooperative spectrum sensing that stated maximizing the probability of detec

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Publication Date
Mon Dec 01 2008
Journal Name
Journal Of Economics And Administrative Sciences
Neural Networks as a Discriminant Purposes
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Discriminant between groups is one of the common procedures because of its ability to analyze many practical phenomena, and there are several methods can be used for this purpose, such as linear and quadratic discriminant functions. recently, neural networks is used as a tool to distinguish between groups.

In this paper the simulation is used to compare neural networks and classical method for classify observations to group that is belong to, in case of some variables that don’t follow the normal distribution. we use the proportion of number of misclassification observations to the all observations as a criterion of comparison.  

 

 

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