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An efficient artificial fish swarm algorithm with harmony search for scheduling in flexible job-shop problem
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Flexible job-shop scheduling problem (FJSP) is one of the instances in flexible manufacturing systems. It is considered as a very complex to control. Hence generating a control system for this problem domain is difficult. FJSP inherits the job-shop scheduling problem characteristics. It has an additional decision level to the sequencing one which allows the operations to be processed on any machine among a set of available machines at a facility. In this article, we present Artificial Fish Swarm Algorithm with Harmony Search for solving the flexible job shop scheduling problem. It is based on the new harmony improvised from results obtained by artificial fish swarm algorithm. This improvised solution is sent to comparison to an overall best solution. When it is the better one, it replaces with the artificial fish swarm solution from which this solution was improvised. Meanwhile the best improvised solutions are carried over to the Harmony Memory. The objective is to minimize a total completion time (makespan) and to make the proposed approach as a portion of the expert and the intelligent scheduling system for remanufacturing decision support. Harmony search algorithm has demonstrated to be efficient, simple and strong optimization algorithm. The ability of exploration in any optimization algorithm is one of the key points. The obtained optimization results show that the proposed algorithm provides better exploitation ability and enjoys fast convergence to the optimum solution. As well, comparisons with the original artificial fish swarm algorithm demonstrate improved efficiency.

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Publication Date
Wed Oct 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
THE ROLE OF ORGANIZATIONAL CULTURE IN ORGANIZATIONAL CITIZENSHIP BEHAVIOR (Search in the Integrity Commission)
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This research sought to detect the level of organizational culture prevailing in the Integrity Commission as well as the level of the organizational citizenship behavior of staff of the Commission and the impact of organizational culture in these behaviors. To achieve the objectives of the research and test the validity of hypotheses have been used questionnaire derived from measurements ready modern researchers foreigners have been adapted to suit the Iraqi environment, have been distributed  (189) questionnaire on the number of employees from the Integrity Commission, which represented the research sample where the research community has a number is (1365) employees in the Baghdad was the use of a number of statistical met

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Publication Date
Wed Jan 01 2025
Journal Name
Journal Of Advanced Veterinary And Animal Research
Investigation and genetic confirmation of the Cryptosporidium species in fish handlers in Baghdad city
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Objective: The present study aims to investigate molecular confirmation for <i>Cryptosporidium</i> species in fish handlers in Baghdad City, central Iraq. Materials and Methods: Sixty stool samples were collected between early November 2023 and late April 2024. All samples were examined phenotypically using a modified Ziehl-Neelsen stain and genotypically (nested polymerase chain reaction technique) based on a partial sequence of 18S rRNA genes with sequencing and phylogenetic tree analysis. Results: The total molecular results identified <i>Cryptosporidium parvum</i> with an infection rate of 45% (27/60). A higher infection rate of 51.9% (14/27) was found in the age group between 15 and 35 years, and male

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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
Tue Jul 15 2025
Journal Name
Smart Innovation, Systems And Technologies
The Role of Artificial Intelligence in Enhancing Translation and Cultural Diversity with Reference English and Arabic Translation
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With the spread of globalization, the need for translators and scholars has grown, as translation is the only process that helps bridge linguistic gaps. Following the emergence of artificial intelligence (AI), a strong competitor has arisen to the translators, sweeping through all scientific and professional fields, including translation sector, with a set of tools that aid in the translation process. The current study aims to investigate the capability of AI tools in translating texts rich in cultural variety from one language to another, specifically focusing on English-Arabic translations, through qualitative analysis to uncover cultural elements in the target language and determine the ability of AI tools to preserve, lose, or alter the

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Publication Date
Thu Oct 22 2020
Journal Name
2020 4th International Symposium On Multidisciplinary Studies And Innovative Technologies (ismsit)
Artificial Intelligence in Smart Agriculture: Modified Evolutionary Optimization Approach for Plant Disease Identification
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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
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
Three Weighted Residuals Methods for Solving the Nonlinear Thin Film Flow Problem
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Abstract<p>In this paper, the methods of weighted residuals: Collocation Method (CM), Least Squares Method (LSM) and Galerkin Method (GM) are used to solve the thin film flow (TFF) equation. The weighted residual methods were implemented to get an approximate solution to the TFF equation. The accuracy of the obtained results is checked by calculating the maximum error remainder functions (MER). Moreover, the outcomes were examined in comparison with the 4<sup>th</sup>-order Runge-Kutta method (RK4) and good agreements have been achieved. All the evaluations have been successfully implemented by using the computer system Mathematica®10.</p>
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Publication Date
Fri Jun 30 2023
Journal Name
Iraqi National Journal Of Nursing Specialties
Impact of Physical Work Environment upon Nurses’ Job performance in Al-Nassiryah City Hospitals
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AbstractObjectives: The work environment has an impact on the performance of nurses, as well as to determine the relationship between the work environment and the performance of nurses.Research methodology: A descriptive analytical study was designed for the impact of the work environment on the performance of nurses' jobs in the hospitals of the city of Nasiriyah. The study began in the period from May 15, 2022 to 1 November, 2022. The non-probability (purposive) sample consisted of (410) nurses working in the city center hospitals. Nasiriyah, they were chosen based on the study criteria, and after obtaining approval from them. The data was collected using the questionnaire, which consi

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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
The Role of Information Technology on job Performance analytical study to sample of private Iraqi banking managers answers and relationships with their personal characters The Role of information technology on job performance
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Abstract:

Purpose\The researcher paper aims to determine the impact of information technology on the job performance, for Iraq private ban as through the use of technology dimensions of job performance.

The aim of this research: this study aims to discuss the importance of information technology and its role in achieving job performance and its impact on the Iraq banking sector design/ methodology/ approach used entrance design/methodology/approach- pilot, the questionnaire was used to collect data in order to develop a model to measure reliably and correctly to the variables of information technology and job performance, and hypotheses were tested through the use of some statisti

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Publication Date
Tue Jun 03 2025
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Comparison of some artificial neural networks for graduate students
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Artificial Neural Networks (ANN) is one of the important statistical methods that are widely used in a range of applications in various fields, which simulates the work of the human brain in terms of receiving a signal, processing data in a human cell and sending to the next cell. It is a system consisting of a number of modules (layers) linked together (input, hidden, output). A comparison was made between three types of neural networks (Feed Forward Neural Network (FFNN), Back propagation network (BPL), Recurrent Neural Network (RNN). he study found that the lowest false prediction rate was for the recurrentt network architecture and using the Data on graduate students at the College of Administration and Economics, Univer

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