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Molecular Identification of Aspergillus fumigatus Using ISSR and RAPD Markers
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The aim of this stud to isolate and identified of A. fumigatus from different sources and study the genetic diversity among these isolates by using RAPD and ISSR markers.Collected 20 samples from 7samples were isolated A. fumigatusisolates were characterized depending on its morphological, then extracted DNA from its.RAPD markersrandomly bandingwith sitesof genome more than ISSR markers where the primer OPN-07 achieved discriminative power (19.1) and 43 bands, while ISSR6 achieved discriminative power (17.1) with 32 bands.ISSR were more efficiency in specific binding then RAPD, ISSR primers has great a binding to production unique band, when 9 primers from 01 primers, ISSR9 was produce (5) unique bands, while RAPD markers was low ability to production unique bands, 3primers from 9 primers were produced unique bands.The dendrogram of RAPD was reverted than isolates number 5 and 7 had the great genetic diversity 0.33361 while the isolates number 5 and 6 had the lowest genetic similarity 0.98521 in contrast with ISSR markers was show isolates number1 and 2 greats genetic diversity 0.97826whilethe isolates number 5 and 7 had the lowest genetic similarity 0.10253.

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Publication Date
Wed Oct 01 2025
Journal Name
Chinese Journal Of Analytical Chemistry
Synthesis, characterization, antioxidant and bioactivity assessment, and thermodynamic analysis of metal ion complexes using a novel azo dye
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In this study, the new azo dye,5,5-[1,2-phenylenebis(2,1-biazenediyl)] bis[8-quinolino], was used to synthesize complexes with Co2+, Ni2+, Cu2+, Zn2+, and Cd2+ ions. The compounds were characterized using 1H and 13C nuclear magnetic resonance (NMR) spectroscopy, Fourier transform infrared (FT-IR) spectroscopy, ultraviolet-visible (UV-Vis) spectroscopy, mass spectrometry, thermo gravimetric analysis (TGA), diffevential scanning calovimltry (DSC), CHN analysis. Further, conductivity, magnetic susceptibility, and metal and chlorine content analysis using FT-IR spectroscopy revealed that the ligand chelates as a bidentate (OH) phenol group and a bidentate (C=N) ring group. The ligand exhibited tetradentate behavior, forming tetrahedral complexe

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Publication Date
Wed Oct 01 2025
Journal Name
Chinese Journal Of Analytical Chemistry
Synthesis, characterization, antioxidant and bioactivity assessment, and thermodynamic analysis of metal ion complexes using a novel azo dye
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Publication Date
Mon Aug 01 2011
Journal Name
Journal Of Engineering
DYE REMOVAL FROM TEXTILE WASTEWATER BY COAGULATION USING ALUM AND PAC
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Removal of solar brown and direct black dyes by coagulation with two aluminum based
coagulants was conducted. The main objective is to examine the efficiency of these
coagulants in the treatment of dye polluted water discharged from Al-Kadhymia Textile
Company (Baghdad-Iraq). The performance of these coagulants was investigated through
jar test by comparing dye percent removal at different wastewater pH, coagulant dose,
and initial dye concentration. Results show that alum works better than PAC under acidic
media (5-6) and PAC works better under basic media (7-8) in the removal of both solar
brown and direct black dyes. Higher doses of PAC were required to achieve the
maximum removal efficiency under optimum pH co

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Publication Date
Tue Jan 17 2012
Journal Name
Journal Of The College Of Basic Education
Image Retrieval Using DCT/KWT and D4/KWT in Distributed System
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This paper presents a proposed method for (CBIR) from using Discrete Cosine Transform with Kekre Wavelet Transform (DCT/KWT), and Daubechies Wavelet Transform with Kekre Wavelet Transform (D4/KWT) to extract features for Distributed Database system where clients/server as a Star topology, client send the query image and server (which has the database) make all the work and then send the retrieval images to the client. A comparison between these two approaches: first DCT compare with DCT/KWT and second D4 compare with D4/KWT are made. The work experimented over the image database of 200 images of 4 categories and the performance of image retrieval with respect to two similarity measures namely Euclidian distance (ED) and sum of absolute diff

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Publication Date
Sat Sep 06 2025
Journal Name
Mesopotamian Journal Of Cybersecurity
Multilevel Text Protection System Using AES and DWT-DCT-SVD Techniques
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In the digital age, protecting intellectual property and sensitive information against unauthorized access is of paramount importance. While encryption helps keep data private and steganography hides the fact that data are present, using both together makes the security much stronger. This paper introduces a new way to hide encrypted text inside color images by integrating discrete wavelet transform (DWT), discrete cosine transform (DCT), and singular value decomposition (SVD), along with AES-GCM encryption, to guarantee data integrity and authenticity. The proposed method operates in the YCbCr color space, targeting the luminance (Y) channel to preserve perceptual quality. Embedding is performed within the HL subband obtained from DWT deco

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Publication Date
Fri Mar 31 2017
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Investigation Desulfurization Method Using Air and Zinc Oxide/Activated Carbon Composite
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In present work examined the oxidation desulfurization in batch system for model fuels with 2250 ppm sulfur content using air as the oxidant and ZnO/AC composite prepared by thermal co-precipitation method. Different factors were studied such as composite loading 1, 1.5 and 2.5 g, temperature 25 oC, 30 oC and 40 oC and reaction time 30, 45 and 60 minutes. The optimum condition is obtained by using Tauguchi experiential design for oxidation desulfurization of model fuel. the highest percent sulfur removal is about 33 at optimum conditions. The kinetic and effect of internal mass transfer were studied for oxidation desulfurization of model fuel, also an empirical kinetic model was calculated for model fuels

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Publication Date
Wed Jun 24 2015
Journal Name
Chinese Journal Of Biomedical Engineering
Single Channel Fetal ECG Detection Using LMS and RLS Adaptive Filters
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ECG is an important tool for the primary diagnosis of heart diseases, which shows the electrophysiology of the heart. In our method, a single maternal abdominal ECG signal is taken as an input signal and the maternal P-QRS-T complexes of original signal is averaged and repeated and taken as a reference signal. LMS and RLS adaptive filters algorithms are applied. The results showed that the fetal ECGs have been successfully detected. The accuracy of Daisy database was up to 84% of LMS and 88% of RLS while PhysioNet was up to 98% and 96% for LMS and RLS respectively.

Publication Date
Mon Dec 14 2020
Journal Name
2020 13th International Conference On Developments In Esystems Engineering (dese)
Anomaly Based Intrusion Detection System Using Hierarchical Classification and Clustering Techniques
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With the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect

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Publication Date
Fri Jan 01 2016
Journal Name
Journal Of Computer And Communications
Pathfinding in Strategy Games and Maze Solving Using A* Search Algorithm
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Publication Date
Wed Nov 30 2022
Journal Name
Iraqi Journal Of Science
Breast Cancer Detection using Decision Tree and K-Nearest Neighbour Classifiers
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      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu

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