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Reducing False Notification in Identifying Malicious Application Programming Interface (API) to Detect Malwares Using Artificial Neural Network with Discriminant Analysis
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Publication Date
Sun Sep 21 2025
Journal Name
Journal Of University Of Babylon
Reduction Vehicle Speed Using GPS Android Smart Phone Programming
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Publication Date
Mon Mar 13 2017
Journal Name
Journal Of Baghdad College Of Dentistry
Assessment of Different Techniques to Detect Recurrent Carious Lesion Around Amalgam Filling
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Abstract Background: This in-vitro study was to evaluated bitewing radiograph and tactile examination for detection secondary caries adjacent to amalgam restorations. Material and method: Sixty primary extracted molars with class I and class II amalgam restorations were selected from children, and examined by bitewing radiographs were taken by using film holders and interpreted on a backlit screen without magnification. Then, we used tactile examination with blunt probe. Result: The result of this study showed that the best cut-off points for the sample were found by a Receiver Operator Characteristic (ROC) analysis, and the area under the ROC curve and the sensitivity, specificity and accuracy of the techniques were calculated for enamel (

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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
Fri Mar 30 2007
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Drop Interface Coalescence in Liquid-Liquid System
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This investigation is a study of the length of time where drops can exist at an oil-water interface before coalescence take place with a bulk of the same phase as the drops. Many factors affecting the time of coalescence were studied in is investigation which included: dispersed phase flow rate, continuous phase height, hole size in distributor, density difference between phases, and viscosity ratio of oil/water systems, employing three liquid/liquid systems; kerosene/water, gasoil/water, and hexane/water. Higher value of coalescence time was 8.26 s at 0.7ml/ s flow rate, 30cm height and 7mm diameter of hole for gas oil/water system, and lower value was 0.5s at 0.3ml/s flow rate, 10 cm height and 3mm diameter of hole for  hexane

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Publication Date
Thu Dec 30 2004
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Drop Interface Coalescence in Liquid-Liquid System
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Publication Date
Wed Mar 31 2021
Journal Name
Electronics
Adaptive Robust Controller Design-Based RBF Neural Network for Aerial Robot Arm Model
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Aerial Robot Arms (ARAs) enable aerial drones to interact and influence objects in various environments. Traditional ARA controllers need the availability of a high-precision model to avoid high control chattering. Furthermore, in practical applications of aerial object manipulation, the payloads that ARAs can handle vary, depending on the nature of the task. The high uncertainties due to modeling errors and an unknown payload are inversely proportional to the stability of ARAs. To address the issue of stability, a new adaptive robust controller, based on the Radial Basis Function (RBF) neural network, is proposed. A three-tier approach is also followed. Firstly, a detailed new model for the ARA is derived using the Lagrange–d’A

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Scopus (38)
Crossref (34)
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Publication Date
Sat Jun 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Use multi-goal fuzzy programming to find the critical path
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The exploitation of all available resources and benefiting from them is one of the most important problems facing the decision makers at the present time. In order to exploit these resources, it is necessary to organize the conflicting objectives, which is the main work in the project management, which enables the development of a plan that decision makers can use to shorten the total completion time and reduce the total cost of the project. Through the use of modern scientific techniques, and therefore the researcher using the critical path method using the technology of programming goals to find more efficient ways to make appropriate decisions where the researcher worked to solve the problems in the construction of the Departm

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Publication Date
Thu Dec 31 2020
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Application of data content analysis (DEA) technology to evaluate performance efficiency: applied research in the General Tax Authority
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The aim of the research is to use the data content analysis technique (DEA) in evaluating the efficiency of the performance of the eight branches of the General Tax Authority, located in Baghdad, represented by Karrada, Karkh parties, Karkh Center, Dora, Bayaa, Kadhimiya, New Baghdad, Rusafa according to the determination of the inputs represented by the number of non-accountable taxpayers and according to the categories professions and commercial business, deduction, transfer of property ownership, real estate and tenders, In addition to determining the outputs according to the checklist that contains nine dimensions to assess the efficiency of the performance of the investigated branches by investing their available resources T

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Publication Date
Sun Sep 21 2025
Journal Name
Journal Of Administration And Economics
Bayesian Method in Classification Regression Tree to estimate nonparametric additive model compared with Logistic Model with Application
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The use of Bayesian approach has the promise of features indicative of regression analysis model classification tree to take advantage of the above information by, and ensemble trees for explanatory variables are all together and at every stage on the other. In addition to obtaining the subsequent information at each node in the construction of these classification tree. Although bayesian estimates is generally accurate, but it seems that the logistic model is still a good competitor in the field of binary responses through its flexibility and mathematical representation. So is the use of three research methods data processing is carried out, namely: logistic model, and model classification regression tree, and bayesian regression tree mode

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Publication Date
Sun Jan 14 2024
Journal Name
Journal Of Al-rafidain University College For Sciences ( Print Issn: 1681-6870 ,online Issn: 2790-2293 )
Using Nonparametric Procedure to Develop an OCMT Estimator for Big Data Linear Regression Model with Application Chemical Pollution in the Tigris River
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Chemical pollution is a very important issue that people suffer from and it often affects the nature of health of society and the future of the health of future generations. Consequently, it must be considered in order to discover suitable models and find descriptions to predict the performance of it in the forthcoming years. Chemical pollution data in Iraq take a great scope and manifold sources and kinds, which brands it as Big Data that need to be studied using novel statistical methods. The research object on using Proposed Nonparametric Procedure NP Method to develop an (OCMT) test procedure to estimate parameters of linear regression model with large size of data (Big Data) which comprises many indicators associated with chemi

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