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Improving the Reliability of Evolutionary Algorithm for Complex Detection in Noisy Protein-Protein Interaction Networks
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Evolutionary algorithms are better than heuristic algorithms at finding protein complexes in protein-protein interaction networks (PPINs). Many of these algorithms depend on their standard frameworks, which are based on topology. Further, many of these algorithms have been exclusively examined on networks with only reliable interaction data. The main objective of this paper is to extend the design of the canonical and topological-based evolutionary algorithms suggested in the literature to cope with noisy PPINs. The design of the evolutionary algorithm is extended based on the functional domain of the proteins rather than on the topological domain of the PPIN. The gene ontology annotation in each molecular function, biological process, and cellular component is used to get the functional domain. The reliability of the proposed algorithm is examined against the algorithms proposed in the literature. To this end, a yeast protein-protein interaction dataset is used in the assessment of the final quality of the algorithms. To make fake negative controls of PPIs that are wrongly informed and are linked to the high-throughput interaction data, different noisy PPINs are created. The noisy PPINs are synthesized with a different and increasing percentage of misinformed PPIs. The results confirm the effectiveness of the extended evolutionary algorithm design to utilize the biological knowledge of the gene ontology. Feeding EA design with GO annotation data improves reliability and produces more accurate detection results than the counterpart algorithms.

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Publication Date
Sun Feb 28 2021
Journal Name
Journal Of Economics And Administrative Sciences
The use of the genetic algorithm to estimate the parameters function of the hypoexponential distribution by simulation
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In this research, the focus was placed on estimating the parameters of the Hypoexponential distribution function using the maximum likelihood method and genetic algorithm. More than one standard, including MSE, has been adopted for comparison by Using the simulation method

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Publication Date
Fri Jul 01 2016
Journal Name
Journal Of Engineering
An Adaptive Multi-Objective Particle Swarm Optimization Algorithm for Multi-Robot Path Planning
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This paper discusses an optimal path planning algorithm based on an Adaptive Multi-Objective Particle Swarm Optimization Algorithm (AMOPSO) for two case studies. First case, single robot wants to reach a goal in the static environment that contain two obstacles and two danger source. The second one, is improving the ability for five robots to reach the shortest way. The proposed algorithm solves the optimization problems for the first case by finding the minimum distance from initial to goal position and also ensuring that the generated path has a maximum distance from the danger zones. And for the second case, finding the shortest path for every robot and without any collision between them with the shortest time. In ord

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Publication Date
Thu Jun 01 2023
Journal Name
Bulletin Of Electrical Engineering And Informatics
A missing data imputation method based on salp swarm algorithm for diabetes disease
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Most of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B

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Publication Date
Sun Mar 01 2015
Journal Name
Journal Of Engineering
Multi-Sites Multi-Variables Forecasting Model for Hydrological Data using Genetic Algorithm Modeling
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A two time step stochastic multi-variables multi-sites hydrological data forecasting model was developed and verified using a case study. The philosophy of this model is to use the cross-variables correlations, cross-sites correlations and the two steps time lag correlations simultaneously, for estimating the parameters of the model which then are modified using the mutation process of the genetic algorithm optimization model. The objective function that to be minimized is the Akiake test value. The case study is of four variables and three sites. The variables are the monthly air temperature, humidity, precipitation, and evaporation; the sites are Sulaimania, Chwarta, and Penjwin, which are located north Iraq. The model performance was

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Publication Date
Sun Sep 07 2014
Journal Name
Baghdad Science Journal
An Algorithm for nth Order Intgro-Differential Equations by Using Hermite Wavelets Functions
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In this paper, the construction of Hermite wavelets functions and their operational matrix of integration is presented. The Hermite wavelets method is applied to solve nth order Volterra integro diferential equations (VIDE) by expanding the unknown functions, as series in terms of Hermite wavelets with unknown coefficients. Finally, two examples are given

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Publication Date
Sun Jun 01 2025
Journal Name
Medical Journal Of Babylon
Detection of Human Parvovirus (B19) in Beta Thalassemia Major Patients
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Abstract<sec> <title>Background:

Beta-thalassemia major (β-TM) is inheritable condition with many complications especially in children. The blood-borne viral infection was proposed as a risk factor due to recurrent blood transfusion regimen (hemotherapy).

Objectives:

This study aimed to investigate Human parvovirus B19 (PVB19) prevalence in β-TM patients by serological and molecular means.

Materials and Methods:

This is a cross-section

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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Engineering
Improving the Direction of Arrival Estimation Using the Parasitic Subspace Generated by Active-Parasitic Antenna (APA) Arrays
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The improvement in Direction of Arrival (DOA) estimation when the received signals impinge on Active-Parasitic Antenna (APA) arrays will be studied in this work. An APA array consists of several active antennas; others are parasitic antennas. The responses to the received signals are measured at the loaded terminals of the active element. The terminals of the parasitic element are shorted. The effect of the received signals on the parasites, i.e., the induced short-circuit current, is mutually coupled to the active elements. Eigen decomposition of the covariance matrix of the measurements of the APA array generates a third subspace in addition to the traditional signal and noise subspaces generated by the all-active ante

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Publication Date
Mon Apr 06 2020
Journal Name
Bmc Oral Health
The reliability of surgeons to avoid traumatic insertion of dental implants into high-risk regions: a panoramic radiograph study
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Abstract<sec> <title>Background

The posterior regions of the jaws usually represent a significant risk for implant surgery. A non-valid assessment of the available bone height may lead to either perforation of the maxillary sinus floor or encroachment of the inferior alveolar nerve and consequently to implant failure. This study aimed to evaluate the reliability of surgeon’s decision in appraising the appropriate implant length, in respect to vital anatomical structures, using panoramic radiographs.

Methods

Only implants that are inserted in relation to the maxillary sinus (MS) or the mandibular canal (MC) were enrolled

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Publication Date
Thu Jun 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
The Role of Strategic audit in detection of financial corruption cases in Iraq - Proposed Framework
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This research focuses on detecting the financial corruption cases in Iraq in light of adoption the strategic audit, the paper deals with the problem of the proliferation corruption cases particularly financial in Iraq and dramatically in the presence of audit and control devices as well as inspection and integrity devices, which indicates the existence of deficiencies and weaknesses in those devices in the implementation of audit and control functions in order to detect the corruption cases in the economic units in Iraq.

Stems objective of this research through the provision of approach of strategic audit concepts and indicate the extent importance of adopting of strategic audit as a means to detect the f

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Publication Date
Wed Dec 13 2017
Journal Name
Al-khwarizmi Engineering Journal
Design of a Kinematic Neural Controller for Mobile Robots based on Enhanced Hybrid Firefly-Artificial Bee Colony Algorithm
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The paper present design of a control structure that enables integration of a Kinematic neural controller for trajectory tracking of a nonholonomic differential two wheeled mobile robot, then  proposes a Kinematic neural controller to direct a National Instrument mobile robot (NI Mobile Robot). The controller is to make the actual velocity of the wheeled mobile robot close the required velocity by guarantees that the trajectory tracking mean squire error converges at minimum tracking error. The proposed tracking control system consists of two layers; The first layer is a multi-layer perceptron neural network system that controls the mobile robot to track the required path , The second layer is an optimization layer ,which is impleme

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