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Solution for Multi-Objective Optimisation Master Production Scheduling Problems Based on Swarm Intelligence Algorithms
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The emphasis of Master Production Scheduling (MPS) or tactic planning is on time and spatial disintegration of the cumulative planning targets and forecasts, along with the provision and forecast of the required resources. This procedure eventually becomes considerably difficult and slow as the number of resources, products and periods considered increases. A number of studies have been carried out to understand these impediments and formulate algorithms to optimise the production planning problem, or more specifically the master production scheduling (MPS) problem. These algorithms include an Evolutionary Algorithm called Genetic Algorithm, a Swarm Intelligence methodology called Gravitational Search Algorithm (GSA), Bat Algorithm (BAT), Teaching Learning Based Algorithm and Harmony Search Algorithm (GA, TLBO and HS). This segment of the research constitutes of two parts the first emphasises on the outcome of the five simulation algorithms and then identifies the best, while the second part is about comparing the best with the search algorithm work in 2009, the applicability of BAT Algorithm and Gravitational Search Algorithm (GSABAT) to planning problems, the technique used for calculating master production scheduling, and the very important results and recommendations for future studies

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Publication Date
Tue Nov 30 2021
Journal Name
Iraqi Journal Of Science
Measurement of Pollution Level with Particulate Matter in Babylon Concrete Plant and Evaluation of Oxidative Stress and Hematological Profile of Plant Workers
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The impact of exposure to different sizes of particulate matter (PM1, PM2.5, PM7, and PM10) was evaluated in  Babylon concrete plant workers who had been exposed to concrete dust for at least 10 years.  The effects of  these particles on the hematological parameters, malondialdehyde (MDA) levels, and  antioxidant enzymes (catalase and glutathione peroxidase ) were examined. The results exhibited that the levels of PM2.5 and PM10 were higher than the acceptable limits approved by the National Ambient Air Quality Standards (NAAQS). The blood parameters, namely white blood cells (WBC), red blood cell (RBC) and platelets counts, demonstrated non-significant differences between w

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Publication Date
Wed Jul 20 2022
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
A Scoping Review of Machine Learning Techniques and Their Utilisation in Predicting Heart Diseases
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Heart diseases are diverse, common, and dangerous diseases that affect the heart's function. They appear as a result of genetic factors or unhealthy practices. Furthermore, they are the leading cause of mortalities in the world. Cardiovascular diseases seriously concern the health and activity of the heart by narrowing the arteries and reducing the amount of blood received by the heart, which leads to high blood pressure and high cholesterol. In addition, healthcare workers and physicians need intelligent technologies that help them analyze and predict based on patients’ data for early detection of heart diseases to find the appropriate treatment for them because these diseases appear on the patient without pain or noticeable symptoms,

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
Processing of Polymers Stress Relaxation Curves Using Machine Learning Methods
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Currently, one of the topical areas of application of machine learning methods is the prediction of material characteristics. The aim of this work is to develop machine learning models for determining the rheological properties of polymers from experimental stress relaxation curves. The paper presents an overview of the main directions of metaheuristic approaches (local search, evolutionary algorithms) to solving combinatorial optimization problems. Metaheuristic algorithms for solving some important combinatorial optimization problems are described, with special emphasis on the construction of decision trees. A comparative analysis of algorithms for solving the regression problem in CatBoost Regressor has been carried out. The object of

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Publication Date
Thu Oct 20 2022
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Producing Hydrogen Energy Using Cr2O3-TiO2 Nanocomposite with Animal (Chitosan) Extract via Photocatalaysis
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      In this study, an efficient photocatalyst for water splitting was developed. The Cr2O3 and TiO2 nanoparticles (Cr2O3-TNPs) nanocomposite with (Chitosan extract) was created using ecologically friendly methods, such as the impregnation technique as TiO2 exhibits nano spherical (TNPs) shape structure. According to the researchers, this nanocomposite material enhanced its ability to absorb ultraviolet light while also speeding up the recombination of photogenerated electrons and holes. The TNPs and prepared Cr2O3-TNPs were characterized by X-ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM), energy dispersive x-ray sp

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Publication Date
Fri Jan 26 2024
Journal Name
Iraqi Journal Of Science
Isolation, Identification and Detection of Some Virulence Factors of Staphylococci in milk and cheese in Baghdad
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During 2011; 300 milk and white cheese samples were collected from Baghdad markets. Out of 200 staphylococcal isolates isolated from milk and white cheese samples, the predominant species was Staphylococcus aureus 97 isolates (48%), followed by S.chromogenes 82 (41%) and 21 (11%) S.epidermidis isolates. S. aureus isolates were DNase, coagulase, protease, urease, lipase, gelatinase and slime layer producers, other species were variable in the production of such virulence factors. S. chromogenes was the most prevalent isolated staphylococcal species from milk samples; while cheese samples contaminated mainly by S. aureus.

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Publication Date
Fri Apr 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
The Local Food Crisis in Iraq Between Thoughts of the Malthusian Theory and the Agricultural Section Regression Reality
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Most countries in the world particularly developing countries, including Iraq,  facing  extremely dangerous problem with social and political dimensions, which is the emergence of the food crisis  problem ,the decrease in domestic food production in Iraq isn't meet the needs of its population food, due to the fact that the agricultural sector suffers from multiple natural ,economic  and human   problems .It is still below the level required to meet the needs of the population  of  food ,since food  at the forefront of priorities needed by the human . This represents indispensable  basic  necessity , so the responsibility of its availability permanently  in appropriate&nb

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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Journal Of Science
Wind Resource Estimation and Mapping at Ali Al-Gharby Site (East-South of Iraq) Using WAsP Model
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The wind atlas analysis and application program, WAsP, is used to assess wind
energy potential، wind climate from geostrophic winds of a given area. In this paper,
metrological data from Ali Algharby station was used to predict the wind resource
and wind turbine energy production at Ali Algharby site.
Data from metrological station was used to draw up observed wind climates at the
anemometer site. Site contour map was digitized using WAsP Map Editortool.
Observed wind climate, digitized contour map, terrain roughness length, obstacle
groups and their porosity were used as input to the WAsP model. Vestas V182, 1.65
MW turbine was used. Weibull probability distribution graph of wind speed, power
density were dra

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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Modeling and Control of Fuel Cell Using Artificial Neural Networks
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This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback

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Publication Date
Sat Sep 30 2023
Journal Name
Iraqi Journal Of Science
Performance Improvement of Generative Adversarial Networks to Generate Digital Color Images of Skin Diseases
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     The main task of creating new digital images of different skin diseases is to increase the resolution of the specific textures and colors of each skin disease. In this paper, the performance of generative adversarial networks has been optimized to generate multicolor and histological color digital images of a variety of skin diseases (melanoma, birthmarks, and basal cell carcinomas). Two architectures for generative adversarial networks were built using two models: the first is a model for generating new images of dermatology through training processes, and the second is a discrimination model whose main task is to identify the generated digital images as either real or fake. The gray wolf swarm algorithm and the whale swarm alg

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
Modeling Jar Test Results Using Gene Expression to Determine the Optimal Alum Dose in Drinking Water Treatment Plants
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Coagulation is the most important process in drinking water treatment. Alum coagulant increases the aluminum residuals, which have been linked in many studies to Alzheimer's disease. Therefore, it is very important to use it with the very optimal dose. In this paper, four sets of experiments were done to determine the relationship between raw water characteristics: turbidity, pH, alkalinity, temperature, and optimum doses of alum [   .14 O] to form a mathematical equation that could replace the need for jar test experiments. The experiments were performed under different conditions and under different seasonal circumstances. The optimal dose in every set was determined, and used to build a gene expression model (GEP). The models were co

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