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Fish Assemblage and Impact of Oscillation Between Drowning and Drought on Fish Size-Spectrum in the Al-Chibyaish Marsh, Southern Iraq
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The present study was implemented in the period from January to December 2017, to assess the assemblage of fish, with the effects of some environmental factors and knowledge the impacts of annual periodic fluctuations between drowning and drought on the abundance and size-spectrum on the fish community in Al-Cibyaish marsh. Water temperature ranged between 13 ͦ C in January to 35 ͦ C in July, salinity from 2.90 PSU (Practical salinity unite) in February to 4.14 PSU in August. Hydrogen ion ranged between 7.60 in July to 8.30 in February. The present study appears contribution of environmental variables in the distribution, widespread and occurrence of fish assemblage in the Al-Chibyaish marsh. A total of 3294 specimens were collected represented 15 fish species affiliated to 15 genera, six families and five orders. Three fish species in present area were formed 72.38% of the total number of species in the marsh. Planiliza abu was the most abundant species formed 35.43%, Alburnus mossulensis, 19.22% and Oreochromis aureus, 17.73%. The ecological indices were within the range of previous studies and described as poor for diversity index ranged between1.38 in June to 1.96 in November. Richness index fluctuated from 0.96 in May and July to 1.96 in April and can express as half integrated. The evenness index values ranged from 0.68 in September to 0.85 in November and December indicate to semi-balanced or slightly balanced. Fish size revealed dominance of the small size due to high mortality in the dry season. The present study affirms prevalence and dominates of historical small native species P. abu and some of the small invasive species, which possess various functional characteristics, enable it to inhabit the marsh.

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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Breast Cancer MRI Classification Based on Fractional Entropy Image Enhancement and Deep Feature Extraction
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Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

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Publication Date
Wed Mar 30 2022
Journal Name
Iraqi Journal Of Science
Involutive Gamma Derivations on n-Gamma Lie Algebra and 3- Pre Gamma -Lie Algebra
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     In this paper, the structure of  and  have  been introduced and studied. We also obtain that a is  of a  if and only if there exists an  on such that . In addition, we obtain  that  of if and only if there is an   on  such that  , where  are subspaces of  with eigenvalues 1 and  −1, respectively. We also find  t that the existence of  on  implies that there exists a compatible  under appropriate condition.

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Intelligent Systems
A study on predicting crime rates through machine learning and data mining using text
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Abstract<p>Crime is a threat to any nation’s security administration and jurisdiction. Therefore, crime analysis becomes increasingly important because it assigns the time and place based on the collected spatial and temporal data. However, old techniques, such as paperwork, investigative judges, and statistical analysis, are not efficient enough to predict the accurate time and location where the crime had taken place. But when machine learning and data mining methods were deployed in crime analysis, crime analysis and predication accuracy increased dramatically. In this study, various types of criminal analysis and prediction using several machine learning and data mining techniques, based o</p> ... Show More
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Publication Date
Tue Aug 01 2023
Journal Name
Journal Of Engineering
An Extensive Literature Review on Risk Assessment Models (Techniques and Methodology) for Construction Industry
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This study looks into the many methods that are used in the risk assessment procedure that is used in the construction industry nowadays. As a result of the slow adoption of novel assessment methods, professionals frequently resort to strategies that have previously been validated as being successful. When it comes to risk assessment, having a precise analytical tool that uses the cost of risk as a measurement and draws on the knowledge of professionals could potentially assist bridge the gap between theory and practice. This step will examine relevant literature, sort articles according to their published year, and identify domains and qualities. Consequently, the most significant findings have been presented in a manne

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Publication Date
Tue Sep 25 2018
Journal Name
Iraqi Journal Of Science
Generating dynamic S-BOX based on Particle Swarm Optimization and Chaos Theory for AES
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Data security is a significant requirement in our time. As a result of the rapid development of unsecured computer networks, the personal data should be protected from unauthorized persons and as a result of exposure AES algorithm is subjected to theoretical attacks such as linear attacks, differential attacks, and practical attacks such as brute force attack these types of attacks are mainly directed at the S-BOX and since the S-BOX table in the algorithm is static and no dynamic so this is a major weakness for the S-BOX table, the algorithm should be improved to be impervious to future dialects that attempt to analyse and break the algorithm  in order to remove these weakness points, Will be generated dynamic substitution box (S-B

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Publication Date
Thu Feb 28 2019
Journal Name
Iraqi Journal Of Science
Arabic Handwriting Word Recognition Based on Scale Invariant Feature Transform and Support Vector Machine
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Offline Arabic handwritten recognition lies in a major field of challenge due to the changing styles of writing from one individual to another. It is difficult to recognize the Arabic handwritten because of the same appearance of the different characters.  In this paper a proposed method for Offline Arabic handwritten recognition. The   proposed method for recognition hand-written Arabic word without segmentation to sub letters based on feature extraction scale invariant feature transform (SIFT) and   support vector machines (SVMs) to enhance the recognition accuracy. The proposed method  experimented using (AHDB) database. The experiment result  show  (99.08) recognition  rate.

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Publication Date
Tue Jan 04 2022
Journal Name
Iraqi Journal Of Science
Proposed Handwriting Arabic Words classification Based On Discrete Wavelet Transform and Support Vector Machine
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A proposed feature extraction algorithm for handwriting Arabic words. The proposed method uses a 4 levels discrete wavelet transform (DWT) on binary image. sliding window on wavelet space and computes the stander derivation for each window. The extracted features were classified with multiple Support Vector Machine (SVM) classifiers. The proposed method simulated with a proposed data set from different writers. The experimental results of the simulation show 94.44% recognition rate.

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Publication Date
Fri Feb 01 2019
Journal Name
Journal Of The College Of Education For Women
The Video effect on Youths Value
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The Video effect on Youths Value

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Publication Date
Wed Jun 01 2005
Journal Name
Journal Of The College Of Languages (jcl)
NEW PERSPECTIVES ON SHAKESPEAR'S "THE TEMPEST"
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This paper is mainly concerned with the study of the moral aspects that prompts William Shakespeare to attempt a romance in which he has embedded the epitome of his thought, experience, and philosophy concerning certain significant aspects of human life whose absence or negligence may threaten human existence, peace, and stability. From the beginning of history man realizes the importance of prosperity on the many and various levels that touch and address his needs and desires—natural, material, and spiritual. The Tempest, due to the dramatist's awareness of the aforementioned values, reflects the dramatist's duty as to projecting and unfolding these important aspects, reconciliation and forgiveness, that promote prosperity which is th

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Publication Date
Thu Dec 29 2016
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
On The Modified Divergence Information Criterion
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In this work (paper), we investigate about the robustness of the modified divergence Information Criterion (MDIC), which proposed by Mantalos, Mattheou and Karagrigoriou (2008), to determine the probability of the Criterion picking up the true lag for Autoregressive process, when the error term of this process is normally and Non normally distributed. We obtained the results for different sample sizes by using simulation.

 

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