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Employing Neural Network and Naive Bayesian Classifier in Mining Data for Car Evaluation
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In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.

Publication Date
Tue Jun 15 2021
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Microneedle Array Patches: Characterization and in -vitro Evaluation
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 Patch in transdermal drug delivery(TDDS) used to overcome the hypodermic drawback, but these patch also have absorption limitation for hydrophilic and macromolecule like peptide and DNA. So that micronized projection have the ability for skin penetration developed named as microneedle.  Microneedle drug delivery system is a novel drug delivery to overcome the limitation of TDDS like skin barrier restriction for large molecule. Microneedle patch can penetrate through skin subcutaneous into epidermis, avoiding nerve fiber and blood vessel contact. There are many type of microneedle patch like solid, polymer, hallow, hydrogel forming microneedle and dissolving microneedle with different method of microfabrication

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Publication Date
Wed Jan 01 2025
Journal Name
Aip Conference Proceedings
Synthesis and evaluation of chalcone derivatives for antimicrobial and antioxidant activities using microwave-assisted methodology
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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
An improved neurogenetic model for recognition of 3D kinetic data of human extracted from the Vicon Robot system
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These days, it is crucial to discern between different types of human behavior, and artificial intelligence techniques play a big part in that.  The characteristics of the feedforward artificial neural network (FANN) algorithm and the genetic algorithm have been combined to create an important working mechanism that aids in this field. The proposed system can be used for essential tasks in life, such as analysis, automation, control, recognition, and other tasks. Crossover and mutation are the two primary mechanisms used by the genetic algorithm in the proposed system to replace the back propagation process in ANN. While the feedforward artificial neural network technique is focused on input processing, this should be based on the proce

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Publication Date
Tue Jan 01 2013
Journal Name
Communications And Network
Link and Cost Optimization of FTTH Network Implementation through GPON Technology
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Publication Date
Fri Jan 31 2020
Journal Name
Iraqi Geological Journal
ESTIMATION OF SHEAR WAVE VELOCITY FROM WIRELINE LOGS DATA FOR AMARA OILFIELD, MISHRIF FORMATION, SOUTHERN IRAQ
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Shear wave velocity is an important feature in the seismic exploration that could be utilized in reservoir development strategy and characterization. Its vital applications in petrophysics, seismic, and geomechanics to predict rock elastic and inelastic properties are essential elements of good stability and fracturing orientation, identification of matrix mineral and gas-bearing formations. However, the shear wave velocity that is usually obtained from core analysis which is an expensive and time-consuming process and dipole sonic imager tool is not commonly available in all wells. In this study, a statistical method is presented to predict shear wave velocity from wireline log data. The model concentrated to predict shear wave velocity fr

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Publication Date
Wed Feb 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
A comparison between the logistic regression model and Linear Discriminant analysis using Principal Component unemployment data for the province of Baghdad
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     The objective of the study is to demonstrate the predictive ability is better between the logistic regression model and Linear Discriminant function using the original data first and then the Home vehicles to reduce the dimensions of the variables for data and socio-economic survey of the family to the province of Baghdad in 2012 and included a sample of 615 observation with 13 variable, 12 of them is an explanatory variable and the depended variable is number of workers and the unemployed.

     Was conducted to compare the two methods above and it became clear by comparing the  logistic regression model best of a Linear Discriminant  function written

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Publication Date
Thu Dec 31 2020
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
QUALITY EVALUATION OF THE INTERNAL METALLIC COATING FOR SOME FOODS THAT AVAILABLE IN THE LOCAL MARKETS: QUALITY EVALUATION OF THE INTERNAL METALLIC COATING FOR SOME FOODS THAT AVAILABLE IN THE LOCAL MARKETS
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The study aimed to estimate the content of lead and determine the quality of the internal coating of metal cans through electrical conductivity as well as to determine the accuracy of the information card for some types of canned food that available in local markets. The information card test showed that all of these samples contained the name of the food, trade mark, country origin, weight, and components, as was indicated by the company producing in all of them except for the C12 sample which was otherwise, and the batch number was mentioned in all samples except for the C3 and C17 which was not clear and not mentioned in the C21, and the validity period was observed (produce and fini

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Publication Date
Fri Jun 01 2018
Journal Name
International Journal Of Computer Science Trends And Technology
Secure Video Data Deduplication in the Cloud Storage Using Compressive Sensing
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Cloud storage provides scalable and low cost resources featuring economies of scale based on cross-user architecture. As the amount of data outsourced grows explosively, data deduplication, a technique that eliminates data redundancy, becomes essential. The most important cloud service is data storage. In order to protect the privacy of data owner, data are stored in cloud in an encrypted form. However, encrypted data introduce new challenges for cloud data deduplication, which becomes crucial for data storage. Traditional deduplication schemes cannot work on encrypted data. Existing solutions of encrypted data deduplication suffer from security weakness. This paper proposes a combined compressive sensing and video deduplication to maximize

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Publication Date
Mon Dec 23 2019
Journal Name
Opcion
The Effect Of Employing The Strategy Of The TalkativeGroups On The Achievement And Attitudes Of ChemistryFor Fifth Grade Students Applied Scienc
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The study aimed to reveal the impact of employing the strategy of the talk-ative groups on the achievement and academic tendencies of chemistry forstudents of the fifth grade of applied science for the academic year (2018 -2019), and to achieve this goal the researcher used the experimental methodon the sample of the study consisting of (50) students, prepared achievementtest falls Under (60) paragraphs, and the scale of tendencies for chemistryfalls under (30) paragraphs, and after the researcher completed the researchexperiment according to what was planned:The superiority of the experimental group studied according to the strate-gy of the talkative groups was found in the post-application of the test ofachievement and attitudes of chemis

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Publication Date
Tue Dec 23 2025
Journal Name
Opción: Revista De Ciencias Humanas Y Sociales, Issn 1012-1587, Nº. 89, 2019
The effectiveness of employing the molecular representation strategy in the development of information Generation skills in the chemistry of second grade students in Intermediate School
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Autoría: Jehan Faris Yousif. Localización: Opción: Revista de Ciencias Humanas y Sociales. Nº. 89, 2019. Artículo de Revista en Dialnet.

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