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Plain, Edge, and Texture Detection Based on Orthogonal Moment
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Image pattern classification is considered a significant step for image and video processing. Although various image pattern algorithms have been proposed so far that achieved adequate classification, achieving higher accuracy while reducing the computation time remains challenging to date. A robust image pattern classification method is essential to obtain the desired accuracy. This method can be accurately classify image blocks into plain, edge, and texture (PET) using an efficient feature extraction mechanism. Moreover, to date, most of the existing studies are focused on evaluating their methods based on specific orthogonal moments, which limits the understanding of their potential application to various Discrete Orthogonal Moments (DOMs). Therefore, finding a fast PET classification method that accurately classify image pattern is crucial. To this end, this paper proposes a new scheme for accurate and fast image pattern classification using an efficient DOM. To reduce the computational complexity of feature extraction, an election mechanism is proposed to reduce the number of processed block patterns. In addition, support vector machine is used to classify the extracted features for different block patterns. The proposed scheme is evaluated by comparing the accuracy of the proposed method with the accuracy achieved by state-of-the-art methods. In addition, we compare the performance of the proposed method based on different DOMs to get the robust one. The results show that the proposed method achieves the highest classification accuracy compared with the existing methods in all the scenarios considered.

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Publication Date
Fri Mar 01 2024
Journal Name
Al-khwarizmi Engineering Journal
Modification, Characterization of Tea Residue-derived Activated Carbon, and Ciprofloxacin Adsorption
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تقدم هذه الدراسة وصفا للطريقة المستخدمة في تحضير الكربون المنشط  (AC)من بقايا الشاي. تم دراسة الخواص الفيزيائية والكيميائية وكفاءة الامتزاز للكربون المنشط المحضر. تم إنتاج الكربون المنشط (AC) على مرحلتين: الاولى التنشيط باستخدام حامض الفوسفوريك (H3PO4) والثانية الكربنة عند درجة حرارة 450 درجة مئوية. استخدم الكربون المنشط لغرض امتصاص العقار الدوائي السيبروفلوكساسين(CIP) . تمت  دراسة عدة عوامل تشغيلية  بدرجة حرار

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Publication Date
Fri Jul 29 2022
Journal Name
Research Journal Of Pharmacy And Technology
Characterization and Testing the properties of PEKK- Strontium- hydroxyapatite composite material
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Polymers, being one of the most important materials in dentistry, offer great physical and mechanical qualities, as well as good biocompatibility. Aim of this study was done to evaluate the Polyetherketoneketone and Polyetherketoneketone polymer composite material used as dental implant through tensile strength, Fourier Transform Infrared analysis FTIR, and wettability). Polyetherketoneketone composites (Polyetherketoneketone and Strontium-containing hydroxyapatite) with selected weight percentage ratios of (0, 10%, 20%, 30%), were fabricated using a compression molding technique”, The study involved Samples preparation (sheets) shaped and form into the desired shape according to standard for tests which included tensile strength,

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Publication Date
Sun Mar 26 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Formulation and Evaluation of Nystatin Microparticles as a Sustained Release System
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Nystatin is the drug of choice for treatment of cutaneous fungal infections with main disadvantage that is the need for multiple applications to achieve complete eradication which may reduce patient compliance. Microparticles offer a solution for such issue as they are one of sustained release preparations that achieve slow release of drug over an extended period of time. The objectives of this study were to fabricate nystatin-loaded chitosan microparticles with the ultimate goal of prolonging drug release and to analyze the influence of polymer concentration on various properties of microparticles. Microparticles were prepared by chemical cross-linking method using glutaraldehyde as cross-linking agent. Five formulas, namely N1C1, N1C2,

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Publication Date
Thu Nov 17 2022
Journal Name
Journal Of Interdisciplinary Mathematics
The existence and uniqueness of common fixed points in expanded spaces
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Publication Date
Sat Sep 01 2018
Journal Name
Saudi Medical Journal
Relationship between human leukocyte antigen DRB1 and psoriasis in Iraqi patients
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Publication Date
Mon Jul 01 2019
Journal Name
Journal Of Physics: Conference Series
Fusion Power Density and Radiation Losses Characteristics for Tritium Fusion Reactions
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A new data for Fusion power density has been obtained for T-3He and T-T fusion reactions, power density is a substantial term in the researches related to the fusion energy generation and ignition calculations of magnetic confined systems. In the current work, thermal nuclear reactivities, power densities of a fusion reactors and the ignition condition inquiry are achieved by using a new and accurate formula of cross section, the maximum values of fusion power density for T-3He and TT reaction are 1.1×107 W/m3 at T=700 KeV and 4.7×106 W/m3 at T=500 KeV respectively, While Zeff suggested to be 1.44 for the two reactions. Bremsstrahlung radiation has also been determined to reaching self- sustaining reactors, Bremsstrahlung values are 4.5×

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Publication Date
Mon Mar 11 2019
Journal Name
Baghdad Science Journal
Determination of Nicotine Extracted from Eggplant and Green Pepper by HPLC
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Nicotine was separated from eggplant and green pepper seeds (Solanaceous) by High Performance Liquid Chromatography (HPLC).The concentration of nicotine in the eggplant extract (0.871-0.877 μg/ml) was determined by injecting standard material with 0.5 and 1.5 μg/ml, while the concentrations of nicotine in green pepper extract (0.613-0.618 μg/ml) was determined when the standard material was injected with 0.5 and 1.5 μg/ml. The qualitative chemical data was calculated from derivations of the standard material. Nicotine concentration was measured qualitatively in both extracts through the calibration curve and method of the standard addition. This technique has high accuracy and compatibility, bringing the proportion of relati

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Publication Date
Thu Jun 01 2023
Journal Name
Baghdad Science Journal
Comparison of Faster R-CNN and YOLOv5 for Overlapping Objects Recognition
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Classifying an overlapping object is one of the main challenges faced by researchers who work in object detection and recognition. Most of the available algorithms that have been developed are only able to classify or recognize objects which are either individually separated from each other or a single object in a scene(s), but not overlapping kitchen utensil objects. In this project, Faster R-CNN and YOLOv5 algorithms were proposed to detect and classify an overlapping object in a kitchen area.  The YOLOv5 and Faster R-CNN were applied to overlapping objects where the filter or kernel that are expected to be able to separate the overlapping object in the dedicated layer of applying models. A kitchen utensil benchmark image database and

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Publication Date
Tue Feb 27 2024
Journal Name
Tem Journal
Supervised Classification Accuracy Assessment Using Remote Sensing and Geographic Information System
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Assessing the accuracy of classification algorithms is paramount as it provides insights into reliability and effectiveness in solving real-world problems. Accuracy examination is essential in any remote sensing-based classification practice, given that classification maps consistently include misclassified pixels and classification misconceptions. In this study, two imaginary satellites for Duhok province, Iraq, were captured at regular intervals, and the photos were analyzed using spatial analysis tools to provide supervised classifications. Some processes were conducted to enhance the categorization, like smoothing. The classification results indicate that Duhok province is divided into four classes: vegetation cover, buildings,

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Publication Date
Sun Aug 01 2021
Journal Name
Bulletin Of Electrical Engineering And Informatics
Robust speaker verification by combining MFCC and entrocy in noisy conditions
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Automatic speaker recognition may achieve remarkable performance in matched training and test conditions. Conversely, results drop significantly in incompatible noisy conditions. Furthermore, feature extraction significantly affects performance. Mel-frequency cepstral coefficients MFCCs are most commonly used in this field of study. The literature has reported that the conditions for training and testing are highly correlated. Taken together, these facts support strong recommendations for using MFCC features in similar environmental conditions (train/test) for speaker recognition. However, with noise and reverberation present, MFCC performance is not reliable. To address this, we propose a new feature 'entrocy' for accurate and robu

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