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Stamps extraction using local adaptive k- means and ISODATA algorithms
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<span>One of the main difficulties facing the certified documents documentary archiving system is checking the stamps system, but, that stamps may be contains complex background and surrounded by unwanted data. Therefore, the main objective of this paper is to isolate background and to remove noise that may be surrounded stamp. Our proposed method comprises of four phases, firstly, we apply k-means algorithm for clustering stamp image into a number of clusters and merged them using ISODATA algorithm. Secondly, we compute mean and standard deviation for each remaining cluster to isolate background cluster from stamp cluster. Thirdly, a region growing algorithm is applied to segment the image and then choosing the connected region to produce a binary mask for the stamp area. Finally, the binary mask is combined with the original image to extract the stamp regions. The results indicate that the number of clusters can be determined dynamically and the largest cluster that has minimum standard deviation (i.e., always the largest cluster is the background cluster). Also, show that the binary mask can be established from more than one segment to cover are all stamp’s disconnected pieces and it can be useful to remove the noise appear with stamp region.</span>

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Publication Date
Tue Mar 30 2021
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Removal of Vanadium and Nickel Ions from Iraqi Atmospheric Residue by Using Solvent Extraction Method
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Iraqi crude Atmospheric residual fraction supplied from al-Dura refinery was treated to remove metals contaminants by solvent extraction method, with various hydrocarbon solvents and concentrations. The extraction method using three different type solvent (n-hexane, n-heptane, and light naphtha) were found to be effective for removal of oil-soluble metals from heavy atmospheric residual fraction. Different solvents with using three different hydrocarbon solvents (n-hexane, n-heptane, and light naphtha) .different variables were studied solvent/oil ratios (4/1, 8/1, 10/1, 12/1, and 15/1), different intervals of perceptual (15, 30-60, 90 and 120 min) and different temperature (30, 45, 60 and 90 °C) were used. The metals removal perce

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Publication Date
Mon Jun 01 2020
Journal Name
Colloids And Surfaces A: Physicochemical And Engineering Aspects
Removal of antibiotic tetracycline using nano-fluid emulsion liquid membrane: Breakage, extraction and stripping studies
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Publication Date
Sun Jun 21 2020
Journal Name
Baghdad Science Journal
Spectrophotometer Determination of Cefixime in pure form and pharmaceutical preparation by Using Cloud point Extraction
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Two simple methods spectrophotometric were suggested for the determination of Cefixime (CFX) in pure form and pharmaceutical preparation. The first method is based without cloud point (CPE) on diazotization of the Cefixime drug by sodium nitrite at 5Cº followed by coupling with ortho nitro phenol in basic medium to form orange colour. The product was stabilized and measured 400 nm. Beer’s law was obeyed in the concentration range of (10-160) μg∙mL-1 Sandell’s sensitivity was 0.0888μg∙cm-1, the detection limit was 0.07896μg∙mL-1, and the limit of Quantitation was 0.085389μg∙mL-1.The second method was cloud point extraction (CPE) with using  Trtion X-114 as surfactant. Beer

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Parallel Computing for Sorting Algorithms
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The expanding use of multi-processor supercomputers has made a significant impact on the speed and size of many problems. The adaptation of standard Message Passing Interface protocol (MPI) has enabled programmers to write portable and efficient codes across a wide variety of parallel architectures. Sorting is one of the most common operations performed by a computer. Because sorted data are easier to manipulate than randomly ordered data, many algorithms require sorted data. Sorting is of additional importance to parallel computing because of its close relation to the task of routing data among processes, which is an essential part of many parallel algorithms. In this paper, sequential sorting algorithms, the parallel implementation of man

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Publication Date
Mon Dec 01 2025
Journal Name
Case Studies In Construction Materials
Optimized stress-strain modeling of eco-friendly fiber-reinforced concrete members using meta-heuristic algorithms
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Eco-friendly concrete is produced using the waste of many industries. It reduces the fears concerning energy utilization, raw materials, and mass-produced cost of common concrete. Several stress-strain models documented in the literature can be utilized to estimate the ultimate strength of concrete components reinforced with fibers. Unfortunately, there is a lack of data on how non-metallic fibers, such as polypropylene (PP), affect the properties of concrete, especially eco-friendly concrete. This study presents a novel approach to modeling the stress-strain behavior of eco-friendly polypropylene fiber-reinforced concrete (PFRC) using meta-heuristic particle swarm optimization (PSO) employing 26 PFRC various mixtures. The cement was partia

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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Recurrent Stroke Prediction using Machine Learning Algorithms with Clinical Public Datasets: An Empirical Performance Evaluation
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Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al

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Publication Date
Sun Aug 25 2019
Journal Name
Civil Engineering Journal
Optimum Efficiency of PV Panel Using Genetic Algorithms to Touch Proximate Zero Energy House (NZEH)
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By optimizing the efficiency of a modular simulation model of the PV module structure by genetic algorithm, under several weather conditions, as a portion of recognizing the ideal plan of a Near Zero Energy Household (NZEH), an ideal life cycle cost can be performed. The optimum design from combinations of NZEH-variable designs, are construction positioning, window-to-wall proportion, and glazing categories, which will help maximize the energy created by photovoltaic panels. Comprehensive simulation technique and modeling are utilized in the solar module I-V and for P-V output power. Both of them are constructed on the famous five-parameter model.  In addition, the efficiency of the PV panel is established by the genetic algorithm

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Publication Date
Sat Sep 09 2017
Journal Name
International Journal Of Science And Research (ijsr)
Fingerprints Recognition Using the Local Energy Distribution over Haar Wavelet Subbands
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Fingerprints are commonly utilized as a key technique and for personal recognition and in identification systems for personal security affairs. The most widely used fingerprint systems utilizing the distribution of minutiae points for fingerprint matching and representation. These techniques become unsuccessful when partial fingerprint images are capture, or the finger ridges suffer from lot of cuts or injuries or skin sickness. This paper suggests a fingerprint recognition technique which utilizes the local features for fingerprint representation and matching. The adopted local features have determined using Haar wavelet subbands. The system was tested experimentally using FVC2004 databases, which consists of four datasets, each set holds

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Publication Date
Fri Nov 21 2025
Journal Name
Advances In Science And Technology Research Journal
Application of you only look once algorithms to crop production management using unmanned aerial vehicles and computer vision systems
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Global date palm production is steadily increasing and adopting technologies such as unmanned aerial vehicles (UAVs) and deep learning can reduce costs, save time, and improve productivity. To address this issue, the authors have proposed an innovative approach that uses UAVs for high-resolution aerial imaging. These images, collected by the Department of Computer Engineering at Al-Salam University in Baghdad and the Institute of Machine Design, Faculty of Mechanical Engineering, Poznan University of Technology, support improved orchard management, palm counting, and yield estimation. Precise spraying and pollination are also facilitated and accelerated, reducing overall cultivation costs. The proposed methodology involves processing captur

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Publication Date
Tue Dec 02 2025
Journal Name
International Journal Of Environmental Analytical Chemistry
Magnetic nanoparticle-based extraction and spectrophotometric determination of norepinephrine using Fe3O4@TTAB and Fe3O4@SiO2@TTAB adsorbents
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ABSTRACT This study presents an efficient approach for the separation and preconcentration of norepinephrine (NOR) from pharmaceutical formulations, environmental water, and human urine samples using a dispersive micro – solid phase extraction (DμSPE) technique employing magnetic nanoadsorbents. Two adsorbents, Fe3O4@TTAB and Fe3 O4@SiO2@TTAB, were prepared by functionalising iron oxide and silicacoated iron oxide nanoparticles with the cationic surfactant tetradecyltrimethylammonium bromide (TTAB). NOR was first converted into a sensitive diazonium dye via reaction with diazotised sulphamethazine and then extracted using mixed ademicelle – hemimicelle magnetic solid-phase extraction, followed by spectrophotometric quantification. Key

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