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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
Sun Feb 03 2019
Journal Name
Journal Of The College Of Education For Women
Logical thinking and its relation with problem Solving among female instructors in the university
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problems with its unobvious effect on scientific creativity and information. Problem solving is one of main goals of researchers because it develops their right logical thinking methods. The present study aims at measuring logical thinking among female it structures in the university mea swing problem solving among them ,identifying statically differences significance in logical thinking among female instructors in the university according to (Specialization Variable), identifying differences significance in problem Solving among female instructions in the university according to ( Specialization Variable) and identifying the Correlation between logical thinking and problem solving among female instructors in the university. The sample c

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Publication Date
Sat Mar 01 2025
Journal Name
Coed
Engaging High School Teachers with Artificial Intelligence Concepts, Applications, and Developments
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This work analyzes the effectiveness of an artificial intelligence (AI) community- building workshop designed for high school teachers and it focuses on contemporary issues related to AI concepts and applications. A group of high school teachers from local education districts attended a one-day AI hands-on workshop at our university. The workshop included several AI-related topics and hands-on examples and exercises aiming to introduce AI concepts and tools relevant to pre-college education. The participating teachers were expected to become a part of a collaborative network created to design, develop, and implement novel AI learning modules for high school students. Initial and a post-training surveys have been used to measure the

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Publication Date
Thu Oct 01 2020
Journal Name
Alexandria Engineering Journal
Biodegradation of reactive dyes by some bacteria using response surface methodology as an optimization technique
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Water pollution as a result of contamination with dye-contaminating effluents is a severe issue for water reservoirs, which instigated the study of biodegradation of Reactive Red 195 and Reactive Blue dyes by E. coli and Bacillus sp. The effects of occupation time, solution pH, initial dyes concentrations, biomass loading, and temperature were investigated via batch-system experiments by using the Design of Experiment (DOE) for 2 levels and 5 factors response surface methodology (RSM). The operational conditions used for these factors were optimized using quadratic techniques by reducing the number of experiments. The results revealed that the two types of bacteria had a powerful effect on biodegradable dyes. The regression analysis reveale

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Publication Date
Tue Apr 02 2019
Journal Name
Artificial Intelligence Research
A three-stage learning algorithm for deep multilayer perceptron with effective weight initialisation based on sparse auto-encoder
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A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an

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Publication Date
Sun Sep 01 2019
Journal Name
Baghdad Science Journal
Symmetric and Positive Definite Broyden Update for Unconstrained Optimization
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Broyden update is one of the one-rank updates which solves the unconstrained optimization problem but this update does not guarantee the positive definite and the symmetric property of Hessian matrix.

In this paper the guarantee of positive definite and symmetric property for the Hessian matrix will be established by updating the vector  which represents the difference between the next gradient and the current gradient of the objective function assumed to be twice continuous and differentiable .Numerical results are reported to compare the proposed method with the Broyden method under standard problems.

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Publication Date
Wed Mar 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
The Role of the Auditor in Confirming the Integrated Reports - An Exploratory Study on a Sample of External Auditors in Iraq-
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  The aim of the research is to identify the extent of the ability to ensure the integrated reports by the auditor in verifying the credibility of these reports, and their implications for the benefit of all parties dealing with the economic unit, as well as measuring the impact of the assurance procedures followed by the auditors and their role in confirming these reports.

  The research methodology was designed after studying the previous literature related to the research variables, and then the relationship between these variables was tested, through the use of a questionnaire list. A questionnaire targeting the community of auditors in the local environment, and the results of the study wer

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Publication Date
Fri Aug 01 2008
Journal Name
2008 First International Conference On The Applications Of Digital Information And Web Technologies (icadiwt)
Hybrid canonical genetic algorithm and steepest descent algorithm for optimizing likelihood estimators of ARMA (1, 1) model
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This paper presents a hybrid genetic algorithm (hGA) for optimizing the maximum likelihood function ln(L(phi(1),theta(1)))of the mixed model ARMA(1,1). The presented hybrid genetic algorithm (hGA) couples two processes: the canonical genetic algorithm (cGA) composed of three main steps: selection, local recombination and mutation, with the local search algorithm represent by steepest descent algorithm (sDA) which is defined by three basic parameters: frequency, probability, and number of local search iterations. The experimental design is based on simulating the cGA, hGA, and sDA algorithms with different values of model parameters, and sample size(n). The study contains comparison among these algorithms depending on MSE value. One can conc

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Publication Date
Fri Dec 01 2023
Journal Name
Bulletin Of Electrical Engineering And Informatics
A comparative study of Gaussian mixture algorithm and K-means algorithm for efficient energy clustering in MWSN
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Wireless sensor networks (WSNs) represent one of the key technologies in internet of things (IoTs) networks. Since WSNs have finite energy sources, there is ongoing research work to develop new strategies for minimizing power consumption or enhancing traditional techniques. In this paper, a novel Gaussian mixture models (GMMs) algorithm is proposed for mobile wireless sensor networks (MWSNs) for energy saving. Performance evaluation of the clustering process with the GMM algorithm shows a remarkable energy saving in the network of up to 92%. In addition, a comparison with another clustering strategy that uses the K-means algorithm has been made, and the developed method has outperformed K-means with superior performance, saving ener

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Publication Date
Sat Jun 01 2024
Journal Name
Case Studies In Chemical And Environmental Engineering
Optimization of photocatalytic process with SnO2 catalyst for COD reduction from petroleum refinery wastewater using a slurry bubble photoreactor
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Publication Date
Fri Jun 05 2015
Journal Name
International Journal Of Science And Research
The Effect of Growth Medium and Nodes Number on the Acclimatization Success of Tissue Propagated Potatoes Seedlings Solanum tuberasum
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The experiment was conducted at the period from 20th Dec. 2015 to 30th Mar. 2016 to know the effect of growth medium and nodes number on the acclimatization success of tissue propagated potatoes seedlings (Burrin class) and study some plant physiological properties. The first experiment involved testing growth media: loam, peat moss, and perlite with different portions (1:1) to plant tissue propagated potato tubers, while the second experiment involved testing the nodes number where 9, 8, 7, 6, and 5 plant nodes were chosen. Results of the first experiment showed the superiority of the culture media of peat moss + perlite to other culture media by giving the higher values of shoot system studied properties: plant height, branches number, le

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