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bsj-4593
Detection of Nutrients and Major Ions at Al Muthanna Storage Site Soil
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In the early 90s military operations and United Nations Special Commission “UNSCOM” teams have been destroyed the past Iraqi chemical program. Both operations led an extensive number of scattered remnants of contaminated areas. The quantities of hazardous materials, incomplete destructed materials, and toxic chemicals were sealed in two bunkers. Deficiency of appropriate destruction technology led to spreading the contamination around the storage site. This paper aims to introduce the environmental detection of the contamination in the storage site area using geospatial analysis technique. The environmental contamination level of nutrients and major ions such as sulphate (SO4), potassium (K), sodium (Na), magnesium (Mg), calcium (Ca), chlorine (Cl), phosphate (PO4) and nitrate (NO3) were detected and analyzed. The grid soil samples on the site and surrounding areas have been investigated, analyzed, and compared to the background points. The storage area grid was divided into 30 major sectors and all samples were evaluated from acquires 10 samples from each sector. The detection results have indicated that SO4 level was exceeded the permitted level by 25 times, K level also exceeded the permitted level but by 460, Na ions were 85 times greater the permitted level. Mg level was 180 times higher than that of permitted content. Activity level of Ca in the soil samples of the study area has also exhibited variability with nine times over the permitted level near the bunkers. However, very high contamination spot activity of Cl was found in destruction zone about which 44 times over the background level was found while PO4 level exceeded the permitted level by 35 times over the permitted level and there was no activity detected for the nitrate in the storage area site.

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Publication Date
Sun Mar 01 2020
Journal Name
Baghdad Science Journal
The Spatial Analysis for Bassia eriophora (Schrad.) Asch. Plant Distributed in all IRAQ by Using RS & GIS Techniques
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        Most vegetation’s are Land cover (LC) for the globe, and there is an increased attention to plants since they represent an element of balance to natural ecology and maintain the natural balance of rapid changes due to systematic and random human uses, including the subject of the current study (Bassia eriophora ) Which represent an essential part of the United Nations system for land cover classification (LCCS), developed by the World Food Organization (FAO) and the world Organization for environmental program (UNEP), to observe basic environmental elements with modern techniques. Although this plant is distributed all over Iraq, we found that this plant exists primarily in the middle

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Publication Date
Thu May 18 2023
Journal Name
College Of Islamic Sciences
The jurisprudential approach Imam Al-Qurtubi through his interpretation Verses of rulings
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There are great figures in our nation, who are famous for their encyclopedia in their sciences, and their fame spreads across the horizons for what they presented to their religion and nation.
So they became torches of guidance, advocates of goodness, and treasuries of knowledge until God inherits the earth and those on it.
Among these imams is Imam al-Qurtubi, who died in the year (671 AH), after whom he left a great legacy of valuable books, including this one, which is the subject of my research, his valuable interpretation (Al-Jami’ Li Ahkam Al-Qur’an). Taking from him and his approach in interpreting the verses of judgment, following the method of extrapolation, investigation and deduction to know his style, which he used

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Publication Date
Sun Jan 01 2012
Journal Name
Iraqi Journal Of Physics
Using remote sensing techniques to monitoring and evaluate the water cover in AL_Razzaza lake: Iraq at deferent periods
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Multi-spectral satellite images of the Landsat satellite by the tow sensitive Thematic Mapper (TM) and Thematic Mapper Enhancement (ETM+), which covered the study area located south east of Iraq. In this research; used the sixth thermal spectral band (Thermal Band) for study the water cover in the AlRazzaza Lake located within the province of Karbala. We intended to study the cover a case of the study area, used satellite images showing the status of region during the period from 1990 to 2001 and 2007. From this study we conclude that cover the water of the study area change in sequence case to decrease during these years.

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Publication Date
Tue May 01 2012
Journal Name
Iraqi Journal Of Physics
Using remote sensing techniques to monitoring and evaluate the water cover in AL_Razzaza lake: Iraq at deferent periods
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Multi-spectral satellite images of the Landsat satellite by the tow sensitive Thematic Mapper (TM) and Thematic Mapper Enhancement (ETM+), which covered the study area located south east of Iraq. In this research; used the sixth thermal spectral band (Thermal Band) for study the water cover in the Al-Razzaza Lake located within the province of Karbala. We intended to study the cover a case of the study area, used satellite images showing the status of region during the period from 1990 to 2001 and 2007. From this study we conclude that cover the water of the study area change in sequence case to decrease during these years.

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Publication Date
Fri Mar 29 2024
Journal Name
Iraqi Journal Of Science
Biological versus Topological Domains in Improving the Reliability of Evolutionary-Based Protein Complex Detection Algorithms
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     By definition, the detection of protein complexes that form protein-protein interaction networks (PPINs) is an NP-hard problem. Evolutionary algorithms (EAs), as global search methods, are proven in the literature to be more successful than greedy methods in detecting protein complexes. However, the design of most of these EA-based approaches relies on the topological information of the proteins in the PPIN. Biological information, as a key resource for molecular profiles, on the other hand, acquired a little interest in the design of the components in these EA-based methods. The main aim of this paper is to redesign two operators in the EA based on the functional domain rather than the graph topological domain. The perturb

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Publication Date
Thu Jan 30 2025
Journal Name
Iraqi Journal Of Science
Improving the Reliability of Evolutionary Algorithm for Complex Detection in Noisy Protein-Protein Interaction Networks
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Evolutionary algorithms are better than heuristic algorithms at finding protein complexes in protein-protein interaction networks (PPINs). Many of these algorithms depend on their standard frameworks, which are based on topology. Further, many of these algorithms have been exclusively examined on networks with only reliable interaction data. The main objective of this paper is to extend the design of the canonical and topological-based evolutionary algorithms suggested in the literature to cope with noisy PPINs. The design of the evolutionary algorithm is extended based on the functional domain of the proteins rather than on the topological domain of the PPIN. The gene ontology annotation in each molecular function, biological proce

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Publication Date
Mon Aug 01 2011
Journal Name
International Journal Of Research And Reviews In Computer Science
Detection of the photon number splitting attack by using decoy states quantum key distribution system
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The goal of this work is to check the presence of PNS (photon number splitting) attack in quantum cryptography system based on BB84 protocol, and to get a maximum secure key length as possible. This was achieved by randomly interleaving decoy states with mean photon numbers of 5.38, 1.588 and 0.48 between the signal states with mean photon numbers of 2.69, 0.794 and 0.24. The average length for a secure key obtained from our system discarding the cases with Eavesdropping was equal to 125 with 20 % decoy states and 82 with 50% decoy states for mean photon number of 0.794 for signal states and 1.588 for decoy states.

Publication Date
Sat Jan 01 2022
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science (ijeecs)
Increasing validation accuracy of a face mask detection by new deep learning model-based classification
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During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

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Publication Date
Sun Mar 02 2014
Journal Name
Baghdad Science Journal
Rapid Detection of Aspergillus flavus isolates producing aflatoxin using UV light on different culture media
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This study included the isolation and identification of Aspergillus flavus isolates associated with imported American rice grains and local corn grains which collected from local markets, using UV light with 365 nm wave length and different media (PDA, YEA, COA, and CDA ). One hundred and seven fungal isolates were identified in rice and 147 isolates in corn.4 genera and 7 species were associated with grains, the genera were Aspergillus ,Fusarium ,Neurospora ,Penicillium . Aspergillus was dominant with occurrence of 0.47% and frequency of 11.75% in rice grains whereas in corn grains the genus Neurospora was dominant with occurrence of 1.09% and frequency 27.25% ,results revealed that 20 isolates out of 50 A. flavus isolates were able

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Publication Date
Tue May 01 2012
Journal Name
Iraqi Journal Of Physics
Early detection of breast cancer mass lesions by mammogram segmentation images based on texture features
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Mammography is at present one of the available method for early detection of masses or abnormalities which is related to breast cancer. The most common abnormalities that may indicate breast cancer are masses and calcifications. The challenge lies in early and accurate detection to overcome the development of breast cancer that affects more and more women throughout the world. Breast cancer is diagnosed at advanced stages with the help of the digital mammogram images. Masses appear in a mammogram as fine, granular clusters, which are often difficult to identify in a raw mammogram. The incidence of breast cancer in women has increased significantly in recent years.
This paper proposes a computer aided diagnostic system for the extracti

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