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Determination Optimum Inventory Level for Material Using Genetic Algorithm
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The integration of decision-making will lead to the robust of its decisions, and then determination optimum inventory level to the required materials to produce and reduce the total cost by the cooperation of purchasing department with inventory department and also with other company,s departments. Two models are suggested to determine Optimum Inventory Level (OIL), the first model (OIL-model 1) assumed that the inventory level for materials quantities equal to the required materials, while the second model (OIL-model 2) assumed that the inventory level for materials quantities more than the required materials for the next period.                                                    This study was applied in Wasit Company for Textile Manufacturing in the Textile Factory, where it produces five products, which are printed striped, plain, poplin, dyed poplin and Naba weave.  The products are made from cotton and they are passing through several stages to transfer to the final product. A genetic algorithm is used to determine the optimum quantity of the purchase a cotton and colors for each month and with minimum cost. Where the purchasing and transportation costs were either constant or variable with respect to purchased quantities while holding cost is kept constant. The results showed that the total cost of the first model is minimum than the second model because the holding cost for this model is less from the second model, while the purchasing and transportation costs from two models are equals. The percentage of purchasing cost for cotton is the biggest value, more 99% of purchasing cost for two models.

                        

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Publication Date
Fri Apr 01 2022
Journal Name
Journal Of Engineering
Prediction of Shear Strength Parameters of Gypseous Soil using Artificial Neural Networks
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The shear strength of soil is one of the most important soil properties that should be identified before any foundation design. The presence of gypseous soil exacerbates foundation problems. In this research, an approach to forecasting shear strength parameters of gypseous soils based on basic soil properties was created using Artificial Neural Networks. Two models were built to forecast the cohesion and the angle of internal friction. Nine basic soil properties were used as inputs to both models for they were considered to have the most significant impact on soil shear strength, namely: depth, gypsum content, passing sieve no.200, liquid limit, plastic limit, plasticity index, water content, dry unit weight, and initial

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Publication Date
Fri Apr 01 2022
Journal Name
Baghdad Science Journal
Numerical Solutions of Two-Dimensional Vorticity Transport Equation Using Crank-Nicolson Method
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This paper is concerned with the numerical solutions of the vorticity transport equation (VTE) in two-dimensional space with homogenous Dirichlet boundary conditions. Namely, for this problem, the Crank-Nicolson finite difference equation is derived.  In addition, the consistency and stability of the Crank-Nicolson method are studied. Moreover, a numerical experiment is considered to study the convergence of the Crank-Nicolson scheme and to visualize the discrete graphs for the vorticity and stream functions. The analytical result shows that the proposed scheme is consistent, whereas the numerical results show that the solutions are stable with small space-steps and at any time levels.

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Simulation and Modelling of Electricity Usage Control and Monitoring System using ThingSpeak
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Renewable energy technology is growing fast especially photovoltaic (PV) system to move the conventional electricity generation and distribution towards smart grid. However, similar to monthly electricity bill, the PV energy producers can only monitor their energy PV generation once a month. Any malfuntion in PV system components may reduce the performance of the system without notice. Thus, developing a real-time monitoring system of PV production is very crucial for early detection. In addition, electricity consumption is also important to be monitored more frequently to increase energy savings awareness among consumers. Hardware based Internet-of-Thing (IoT) monitoring and control system is widely used. However, the implementation of

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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network
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Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

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Publication Date
Wed Feb 14 2024
Journal Name
Aip Conference Proceedings
Segmentation Moon Images Using Different Segmentation Methods and Isolate the Lunar Craters
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Segmentation is the process of partition digital images into different parts depending on texture, color, or intensity, and can be used in different fields in order to segment and isolate the area to be partitioned. In this work images of the Moon obtained through observations in Astronomy and space dep. College of science university of Baghdad by ( Toward space telescopes and widespread used of a CCD camera) . Different segmentation methods were used to segment lunar craters. Different celestial objects cause craters when they crash into the surface of the Moon like asteroids and meteorites. Thousands of craters appears on the Moon's surface with ranges in size from meter to many kilometers, it provide insights into the age and ge

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Publication Date
Tue Oct 12 2021
Journal Name
Innovative Infrastructure Solutions
Facilitating claims settlement using building information modeling in the school building projects
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Publication Date
Wed Mar 18 2020
Journal Name
Baghdad Science Journal
On Light Mapping and Certain Concepts by Using m_X N-Open Sets
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The aim of this paper is to present a weak form of -light functions by using -open set which is -light function, and to offer new concepts of disconnected spaces and totally disconnected spaces. The relation between them have been studied. Also, a new form of -totally disconnected and inversely -totally disconnected function have been defined, some examples and facts was submitted.

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Publication Date
Wed May 01 2019
Journal Name
Iraqi Journal Of Science
In Vitro Regeneration of Pimpinella anisum L. Using Different Plant Growth Regulators
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Plant regeneration protocols were developed for medicinally important anise (Pimpinella anisum L.) that successfully achieved from seeds. Seeds were sterilized and inoculated on Murashige and Skoog (MS) medium with and without gibberellins (GA3) until full germination. The highest percentage of germination (100%) was recorded on MS medium treated with 2.0 mg/L GA3 after 7 days. For shoot proliferation, different concentrations of 6- benzyl adenine BA (1, 1.5, 2 mg/L) were used. To enhance shoot induction, 0.1 mg/L of naphthalene acetic acid (NAA) and 0.01 mg/L of thidiazuron (TDZ) were tested along with BA. Direct regenerated shoots were obtained on MS medium supplemented with BA alone (2mg/L) which gave (7shoot/explant), while the presence

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Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Using Fuzzy Clustering to Detect the Tumor Area in Stomach Medical Images
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Although the number of stomach tumor patients reduced obviously during last decades in western countries, but this illness is still one of the main causes of death in developing countries. The aim of this research is to detect the area of a tumor in a stomach images based on fuzzy clustering. The proposed methodology consists of three stages. The stomach images are divided into four quarters and then features elicited from each quarter in the first stage by utilizing seven moments invariant. Fuzzy C-Mean clustering (FCM) was employed in the second stage for each quarter to collect the features of each quarter into clusters. Manhattan distance was calculated in the third stage among all clusters' centers in all quarters to disclosure of t

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Publication Date
Tue May 01 2018
Journal Name
Journal Of Physics: Conference Series
Hiding Techniques for Dynamic Encryption Text based on Corner Point
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Hiding technique for dynamic encryption text using encoding table and symmetric encryption method (AES algorithm) is presented in this paper. The encoding table is generated dynamically from MSB of the cover image points that used as the first phase of encryption. The Harris corner point algorithm is applied on cover image to generate the corner points which are used to generate dynamic AES key to second phase of text encryption. The embedded process in the LSB for the image pixels except the Harris corner points for more robust. Experimental results have demonstrated that the proposed scheme have embedding quality, error-free text recovery, and high value in PSNR.

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