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An Evolutionary Algorithm for Solving Academic Courses Timetable Scheduling Problem
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Scheduling Timetables for courses in the big departments in the universities is a very hard problem and is often be solved by many previous works although results are partially optimal. This work implements the principle of an evolutionary algorithm by using genetic theories to solve the timetabling problem to get a random and full optimal timetable with the ability to generate a multi-solution timetable for each stage in the collage. The major idea is to generate course timetables automatically while discovering the area of constraints to get an optimal and flexible schedule with no redundancy through the change of a viable course timetable. The main contribution in this work is indicated by increasing the flexibility of generating optimal timetable schedules with different copies by increasing the probability of giving the best schedule for each stage in the campus with the ability to replace the timetable when needed. The Evolutionary Algorithm (EA) utilized in this paper is the Genetic Algorithm (GA) which is a common multi-solution metaheuristic search based on the evolutionary population that can be applied to solve complex combinatorial problems like timetabling problems. In this work, all inputs: courses, teachers, and time acted by one array to achieve local search and combined this acting of the timetable by using the heuristic crossover to ensure that the essential conditions are not broken. The result of this work is a flexible scheduling system, which shows the diversity of all possible timetables that can be created depending on user conditions and needs.

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Publication Date
Sat Sep 27 2014
Journal Name
Soft Computing
Multi-objective evolutionary routing protocol for efficient coverage in mobile sensor networks
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Publication Date
Thu Dec 01 2011
Journal Name
Swarm And Evolutionary Computation
Energy-aware evolutionary routing protocol for dynamic clustering of wireless sensor networks
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Publication Date
Sun Jul 01 2012
Journal Name
Applied Soft Computing
A new evolutionary based routing protocol for clustered heterogeneous wireless sensor networks
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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Computational Intelligence Systems
Evolutionary Feature Optimization for Plant Leaf Disease Detection by Deep Neural Networks
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Publication Date
Sat Sep 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
New Approach for Solving Multi – Objective Problems
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  There are many researches deals with constructing an efficient solutions for real problem having Multi - objective confronted with each others. In this paper we construct a decision for Multi – objectives based on building a mathematical model formulating a unique objective function by combining the confronted objectives functions. Also we are presented some theories concerning this problem. Areal application problem has been presented to show the efficiency of the performance of our model and the method. Finally we obtained some results by randomly generating some problems.

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Publication Date
Sun Dec 07 2014
Journal Name
Baghdad Science Journal
New Iterative Method for Solving Nonlinear Equations
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The aim of this paper is to propose an efficient three steps iterative method for finding the zeros of the nonlinear equation f(x)=0 . Starting with a suitably chosen , the method generates a sequence of iterates converging to the root. The convergence analysis is proved to establish its five order of convergence. Several examples are given to illustrate the efficiency of the proposed new method and its comparison with other methods.

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Publication Date
Mon Mar 02 2026
Journal Name
Psychiatry International
Patterns of Substance Use in Medical Students: Evidence from an Iraqi Academic Setting
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Background: Medical students often face substantial psychological stress, which can increase the risk of substance use, professional detriment, and insufficient patient care. However, substance use in medical students remains understudied in Iraq. This study highlights the prevalence, patterns, risk factors, and negative effects of substance use among medical students at the University of Baghdad. A cross-sectional study involving 414 medical students at the University of Baghdad was conducted. The questionnaire included sociodemographic variables and the Alcohol, Smoking, and Substance Involvement Screening Test to screen for psychoactive substance use. The lifetime prevalence of substance use was 38.9%. Among substance users, 42.8

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Publication Date
Tue Sep 23 2025
Journal Name
مجلة اكليل للدراسات الانسانية
The educational counselor in the school and his role in guidance and problem solving: a field study in the city of Baghdad
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Summary: The study focused on the role of the educational counselor in schools, as an integral part of the educational system that faces multiple challenges and difficulties. In this context, the counselor’s role becomes crucial in attempting to reduce or eliminate such difficulties, in addition to guiding students in an appropriate manner. Methodes: The study employed a descriptive field approach, using interviews and direct observation as tools to examine the actual role performed by school counselors. Results: The study concluded with several key findings, most notably the numerous challenges faced by counselors, including students’ negative behaviors, school dropouts, and the limited administrative support for counselors’ work. Fu

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Publication Date
Sun Apr 13 2025
Journal Name
Scientific Reports
Optimized image segmentation using an improved reptile search algorithm with Gbest operator for multi-level thresholding
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Abstract<p>Image segmentation using bi-level thresholds works well for straightforward scenarios; however, dealing with complex images that contain multiple objects or colors presents considerable computational difficulties. Multi-level thresholding is crucial for these situations, but it also introduces a challenging optimization problem. This paper presents an improved Reptile Search Algorithm (RSA) that includes a Gbest operator to enhance its performance. The proposed method determines optimal threshold values for both grayscale and color images, utilizing entropy-based objective functions derived from the Otsu and Kapur techniques. Experiments were carried out on 16 benchmark images, which inclu</p> ... Show More
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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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