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Minimum Spanning Tree Algorithm for Skin Cancer Image Object Detection
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This paper proposes a new method Object Detection in Skin Cancer Image, the minimum
spanning tree Detection descriptor (MST). This ObjectDetection descriptor builds on the
structure of the minimum spanning tree constructed on the targettraining set of Skin Cancer
Images only. The Skin Cancer Image Detection of test objects relies on their distances to the
closest edge of thattree. Our experimentsshow that the Minimum Spanning Tree (MST) performs
especially well in case of Fogginessimage problems and in highNoisespaces for Skin Cancer
Image.
The proposed method of Object Detection Skin Cancer Image wasimplemented and tested on
different Skin Cancer Images. We obtained very good results . The experiment showed that the
proposedmethod obtained very good results but it requires more testing on different types of Skin
Cancer Images.

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Publication Date
Sun Nov 01 2020
Journal Name
Journal Of Materials Research And Technology
Immobilization of l-asparaginase on gold nanoparticles for novel drug delivery approach as anti-cancer agent against human breast carcinoma cells
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Publication Date
Tue Dec 01 2009
Journal Name
Al-khwarizmi Engineering Journal
Adsorption of Cd(II) and Pb(II) Ions from Aqueous Solution by Activated Carbon
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Heavy metal consider as major environmental pollutants. Many of industrial wastewater effluents contain a wide range of these heavy metals. The adsorption of Cd2+ and Pb2+ metal ions from aqueous solution by activated carbon was studied. The results showed that maximum adsorption capacity occurred at 486.9×10-3 mg/kg for Pb2+ ion and 548.8×10-3 mg/kg for Cd2+ ion. The adsorption in a mixture of the metal ions had a balancing effect on the adsorption capacity of the activated carbon. The adsorption capacity of each metal ion was affected by the presence of other metal ions rather than its presence individually. The study showed the presence of other heavy metals attribute to the reduction in the activated carbon capacity, and the adsorp

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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Classification of Arabic Alphabets Using a Combination of a Convolutional Neural Network and the Morphological Gradient Method
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The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet

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Publication Date
Wed Jun 01 2022
Journal Name
Baghdad Science Journal
Kinetic, Isotherm and Thermodynamic Studies on the Ciprofloxacin Adsorption from Aqueous Solution Using Aleppo bentonite
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          Aleppo bentonite was investigated to remove ciprofloxacin hydrochloride from aqueous solution. Batch adsorption experiments were conducted to study the several factors affecting the removal process, including contact time, pH of solution, bentonite dosage, ion strength, and temperature. The optimum contact time, pH of solution and bentonite dosage were determined to be 60 minutes, 6 and 0.15 g/50 ml, respectively. The bentonite efficiency in removing CIP decreased from 89.9% to 53.21% with increasing Ionic strength from 0 to 500mM, and it increased from 89% to 96.9% when the temperature increased from 298 to 318 K. Kinetic studies showed that the pseudo second-order model was the best in describing  the adsorption sys

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
Offline Signature Biometric Verification with Length Normalization using Convolution Neural Network
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Offline handwritten signature is a type of behavioral biometric-based on an image. Its problem is the accuracy of the verification because once an individual signs, he/she seldom signs the same signature. This is referred to as intra-user variability. This research aims to improve the recognition accuracy of the offline signature. The proposed method is presented by using both signature length normalization and histogram orientation gradient (HOG) for the reason of accuracy improving. In terms of verification, a deep-learning technique using a convolution neural network (CNN) is exploited for building the reference model for a future prediction. Experiments are conducted by utilizing 4,000 genuine as well as 2,000 skilled forged signatu

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Publication Date
Sat Mar 01 2014
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Strategic Performance Evaluation Using Benchmarking Technique: Applied Research In The Sample Of Offices Of Inspectors General
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In light of the rapid changes in the business environment and the entry of administrative leaders in the challenges of the atheist and twenty- increasing competition between sectors and the desire to acquire the skills, the traditional methods are no longer viable, which requires doing evaluates performance according to a more holistic, rather than limiting the performance evaluation on the financial hub that has not longer enough alone, as well as benchmarking method that has proven successful in developed countries as a way to develop and improve products and services.

I've touched your search to the development of indicators evaluating the performance and preparation of a mechanism for making comparisons of reference between o

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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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Publication Date
Tue Sep 01 2020
Journal Name
Baghdad Science Journal
Diversity and Geographical Distribution of Sand Flies Phlebotomus papatasi (Diptera: Phlebotominae) by using Geometric Morphometric Technique from two Iraqi Provinces
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            The variation in wing morphological features was investigated using geometric morphometric technique of the Sand Fly from two Iraqi provinces Babylon and Diyala . We distributed eleven landmarks on the wings of Sand Fly species. By using the centroid size and shape together, all species were clearly distinguished.  It is clear from these results that the wing analysis is an essential method for future geometric morphometry studies to distinguish the species of Sand Flies in Iraq.

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Publication Date
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
On Comparison Study between Double Sumudu and Elzaki Linear Transforms Method for Solving Fractional Partial Differential Equations
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        In this paper, double Sumudu and double Elzaki transforms methods are used to compute the numerical solutions for some types of fractional order partial differential equations with constant coefficients and explaining the efficiently of the method by illustrating some numerical examples that are computed by using  Mathcad 15.and graphic in Matlab R2015a.

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Publication Date
Sun Sep 01 2019
Journal Name
Baghdad Science Journal
Detection a New Antiseptic Resistant Variant of qac Gene in Some Multi Drug Resistant Staphylococcus aureus Isolated from Different Clinical Sources
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The increasing use of antiseptic compounds creates selective pressure cause emergence of antiseptic resistance among Staphylococcus aureus .Resistance mechanism of antiseptic is driven mainly by multi drug resistant (MDR) efflux protein.Sixty five isolates of S.aureuswere collected from different clinical sources and subjected to 11 antibiotics most of them are recognized by efflux systems as extruded substrates. Range of efflux activity was estimated using cartwheel method. Simultaneous discrimination of antiseptic coding genes (qacA/B, smr and norA)as well as nuc and mecA genes among multidrug resistantS.aureus(MRSA) isolates was preformed using multiplex PCR assay

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