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The Shift towards the Results-Oriented Budget and Its Impact on Government Performance Information
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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
Sun Sep 01 2019
Journal Name
Journal Of Physics: Conference Series
Seed weight effect on germination properties and seedling growth of some cultivars of lupine
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A laboratory experiment was carried out and repeated at field of College of Agricultural Engineering Sciences, University of Baghdad in 2017. First factor was three cultivars of lupine 'Giza-1', 'Giza-2' and 'Hamburg'. Second factor was three seed weights (lower weight, medium weight and higher weight) which was following the cultivars factor. Nested design was used. Results showed supremacy of 'Giza-1' cultivar significantly and gave higher germination ratio, radical length, seedling dry weight, seedling vigour index, field emergence ratio, plant height and number of leaves per plant. The treatment ('Giza-1'×higher seed weight) was supremacy significantly and gave higher germination ratio, radical length, plumule length, and seedling vigo

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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 01 2020
Journal Name
Al-khwarizmi Engineering Journal
Pre-Processing and Surface Reconstruction of Points Cloud Based on Chord Angle Algorithm Technique
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Abstract

Although the rapid development in reverse engineering techniques, 3D laser scanners can be considered the modern technology used to digitize the 3D objects, but some troubles may be associate this process due to the environmental noises and limitation of the used scanners. So, in the present paper a data pre-processing algorithm has been proposed to obtain the necessary geometric features and mathematical representation of scanned object from its point cloud which obtained using 3D laser scanner (Matter and Form) through isolating the noised points. The proposed algorithm based on continuous calculations of chord angle between each adjacent pair of points in point cloud. A MATLAB program has been built t

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Publication Date
Mon Apr 29 2024
Journal Name
Euphrates Journal Of Agricultural Science
Effect foliar of some organic fertilizers on growth and yield of four potato cultivars
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Publication Date
Mon Feb 01 2021
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Comparative study of logistic regression and artificial neural networks on predicting breast cancer cytology
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<p>Currently, breast cancer is one of the most common cancers and a main reason of women death worldwide particularly in<strong> </strong>developing countries such as Iraq. our work aims to predict the type of tumor whether benign or malignant through models that were built using logistic regression and neural networks and we hope it will help doctors in detecting the type of breast tumor. Four models were set using binary logistic regression and two different types of artificial neural networks namely multilayer perceptron MLP and radial basis function RBF. Evaluation of validated and trained models was done using several performance metrics like accuracy, sensitivity, specificity, and AUC (area under receiver ope

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Publication Date
Tue Mar 01 2022
Journal Name
Iraqi Journal Of Physics
Effect of Copper on Tensile and Hardness of Al-Si Alloy in Automotive Application
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In current research Copper was employed for preparing a ternary system of Al–Si alloy in different (0.2–2.5 wt. %) the best was taken is (1.5%wt) of copper that circumstances of solidification for improving the mechanical performance of the available in aluminium alloy. Cast iron molds were prepared to obtain tensile strength testing specimens. Alloys were prepared by employing gas furnaces. The molten metal was poured into a preheated cast-iron mold. The obtained alloy structures were studied using an X-ray diffractometer and optical microscopy. The mechanical performance of the prepared alloys was examined under the influence of different hardening conditions in both heat and non-heat-treated conditions. The outcomes showed at the

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Publication Date
Wed Jan 01 2020
Journal Name
Biochemical And Cellular Archives
New derivative of chitosan based on epichlorohydrne, synthesis, characterization, antibacterial activity and swelling study
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A novel series of chitosan derivatives were synthesized via reaction of chitosan with carbonyl compounds and grafted it’s by with different amine compounds substituted hydrogen. The produced polymers were characterized by different analyses FTIR, 1HCNMR, XRD, DSC and TGA. Solubility in water as well as many solvent was investigated, antibacterial activity of chitosan and its derivatives against two types of bacteria E. coli and S. aureus was also investigated. The results showed that derivatives sort of have antibacterial activities against Esherichia coli (Gram negative) better than chitosan whilst compound IX has better antibacterial against Staphylococcus aureus (Gram positive). SEM analysis showed that increase of surface roughness wi

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Publication Date
Sat Aug 01 2015
Journal Name
Journal Of Engineering
A Real-Time Fuzzy Load Flow and Contingency Analysis Based on Gaussian Distribution System
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Fuzzy logic is used to solve the load flow and contingency analysis problems, so decreasing computing time and its the best selection instead of the traditional methods. The proposed  method is very accurate with outstanding computation time, which made the fuzzy load flow (FLF) suitable for real time application for small- as well as large-scale power systems. In addition that, the FLF efficiently able to solve load flow problem of ill-conditioned power systems and contingency analysis. The FLF method using Gaussian membership function requires less number of iterations and less computing time than that required in the FLF method using triangular membership function. Using sparsity technique for the input Ybus sparse matrix data gi

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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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