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ijs-3169
Development of a Job Applicants E-government System Based on Web Mining Classification Methods
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     Governmental establishments are maintaining historical data for job applicants for future analysis of predication, improvement of benefits, profits, and development of organizations and institutions. In e-government, a decision can be made about job seekers after mining in their information that will lead to a beneficial insight. This paper proposes the development and implementation of an applicant's appropriate job prediction system to suit his or her skills using web content classification algorithms (Logit Boost, j48, PART, Hoeffding Tree, Naive Bayes). Furthermore, the results of the classification algorithms are compared based on data sets called "job classification data" sets. Experimental results indicated that the algorithm j48 had the highest precision (94.80%) compared to other algorithms for the aforementioned dataset.

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Publication Date
Sun Apr 28 2024
Journal Name
International Journal Of Sustainable Development And Planning
The Role of Environmental Auditing in Achieving Sustainable Development: Management Systems as a Mediator
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The present study tackles the complex issue of the urgent need for Environmental Auditing (EA) in Iraq in the absence of laws that support environmental management and in the light of the high rates of cancerous diseases in Iraq, which coincided significantly with the increase in oil production, according to the numbers indicated in the Iraqi Ministry of Health. The study aimed to investigate the mediating role of Management Systems (MS) related to the role of EA supporting sustainability reports concerning the reduction of the negative effects of gas emissions from oil companies. We adopted the descriptive approach which relies on studying relationships through a questionnaire that was distributed to a group of workers at Doura Refinery in

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Publication Date
Wed Jan 01 2020
Journal Name
Journal Of Mechanical Engineering Research And Developments
Development of natural convection heat transfer in heat sink using a new fin design
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Publication Date
Wed Jun 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
A Comparison between robust methods in canonical correlation by using empirical influence function
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       Canonical correlation analysis is one of the common methods for analyzing data and know the relationship between two sets of variables under study, as it depends on the process of analyzing the variance matrix or the correlation matrix. Researchers resort to the use of many methods to estimate canonical correlation (CC); some are biased for outliers, and others are resistant to those values; in addition, there are standards that check the efficiency of estimation methods.

In our research, we dealt with robust estimation methods that depend on the correlation matrix in the analysis process to obtain a robust canonical correlation coefficient, which is the method of Biwe

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Publication Date
Sat Aug 13 2022
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The impact of e-marketing on the quality of the insurance service: Applied research in the National Insurance Company
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This research aims to introduce the importance of electronic marketing and the extent of its impact on the quality of the insurance service in general, and the national insurance company in particular, and the advantages it can achieve, an increase in its competitiveness, as well as contributing to increasing the efficiency of the performance of the insurance company.

The research relied on the questionnaire form as a main tool for obtaining data and information by the 70 questionnaire questionnaires required for the field side of the research, as they were distributed and retrieved in full, and all of them are suitable for analysis. The sample .The questionnaire was designed with three axes, the first wa

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Publication Date
Tue Sep 29 2020
Journal Name
Iraqi Journal Of Science
An Automated Classification of Mammals and Reptiles Animal Classes Using Deep Learning
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Detection and classification of animals is a major challenge that is facing the researchers. There are five classes of vertebrate animals, namely the Mammals, Amphibians, Reptiles, Birds, and Fish, and each type includes many thousands of different animals. In this paper, we propose a new model based on the training of deep convolutional neural networks (CNN) to detect and classify two classes of vertebrate animals (Mammals and Reptiles). Deep CNNs are the state of the art in image recognition and are known for their high learning capacity, accuracy, and robustness to typical object recognition challenges. The dataset of this system contains 6000 images, including 4800 images for training. The proposed algorithm was tested by using 1200

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Publication Date
Tue Feb 01 2022
Journal Name
Int. J. Nonlinear Anal. Appl.
Computer-based plagiarism detection techniques: A comparative study
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Plagiarism is becoming more of a problem in academics. It’s made worse by the ease with which a wide range of resources can be found on the internet, as well as the ease with which they can be copied and pasted. It is academic theft since the perpetrator has ”taken” and presented the work of others as his or her own. Manual detection of plagiarism by a human being is difficult, imprecise, and time-consuming because it is difficult for anyone to compare their work to current data. Plagiarism is a big problem in higher education, and it can happen on any topic. Plagiarism detection has been studied in many scientific articles, and methods for recognition have been created utilizing the Plagiarism analysis, Authorship identification, and

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Publication Date
Sun Oct 01 2017
Journal Name
2017 47th European Microwave Conference (eumc)
A semiconductor based millimeter-wave waveguide junction circulator
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Publication Date
Tue Sep 01 2020
Journal Name
Microprocessors And Microsystems
Design considerations for a microprocessor-based Doppler radar
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Publication Date
Sat Oct 01 2022
Journal Name
Therapeutic Delivery
Particles-based Medicated Wound Dressings: A Comprehensive Review
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Publication Date
Tue Jan 25 2022
Journal Name
Iraqi Journal Of Science
A Modified Segmentation Approach for Real World Images Based on Edge Density Associated with Image Contrast Stretching
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Segmentation of real world images considered as one of the most challenging tasks in the computer vision field due to several issues that associated with this kind of images such as high interference between object foreground and background, complicated objects and the pixels intensities of the object and background are almost similar in some cases. This research has introduced a modified adaptive segmentation process with image contrast stretching namely Gamma Stretching to improve the segmentation problem. The iterative segmentation process based on the proposed criteria has given the flexibility to the segmentation process in finding the suitable region of interest. As well as, the using of Gamma stretching will help in separating the

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