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Simplified Novel Approach for Accurate Employee Churn Categorization using MCDM, De-Pareto Principle Approach, and Machine Learning
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Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date.  A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM scheme for categorizing employees. In 1st stage, analytic hierarchy process (AHP) has been utilized for assigning relative weights for employee accomplishment factors. In second stage, TOPSIS has been used for expressing significance of employees for performing employee categorization. A simple 20-30-50 rule in DE PARETO principle has been applied to categorize employees into three major groups namely enthusiastic, behavioral and distressed employees.  Random forest algorithm is then applied as baseline algorithm to the proposed employee churn framework to predict class-wise employee churn which is tested on standard dataset of the (HRIS), the obtained results are evaluated with other ML methods. The Random Forest ML algorithm in SNEC scheme has similar or slightly better overall accuracy and MCC with significant less time complexity compared with that of ECPR scheme using CATBOOST algorithm.

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Publication Date
Sun Jun 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
The role of the learning organization in the behavior of the work teams \ exploratory research in the Rasheed Bank
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This research aims to examine the relationship between learning organization and behavior of work teams. The variable of the learning organization took four dimensions depending on the study (sudhartna & Li, 2004): Common cultural values ​​, communication, knowledge transfer and the characteristics of workers. The behavior of teams was identified on the basis of realizing of the respondents of their organization to work as a team where the research relied concepts applied in the study (Hakim , 2005) , and chose to research the case of a service organization for the study and relied on four dimensions of coordination , cooperation , sharing of information , the performance of the team, and was a curriculum approach and des

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Publication Date
Mon May 22 2023
Journal Name
Journal Of Applied Business And Technology
Toxic Workplace, Mental Health and Employee Well-being, the Moderator Role of Paternalistic Leadership, an Empirical Study
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Based on previous research results that recognized the role of paternalistic leadership in promoting a positive work climate, this study explored the impact of a toxic work environment on the mental health and well-being of employees. We used the quantitative methodology to collect and analyze data. A sample of 108 participants from Iraqi internet service provider (ISPs) companies represented the purposive study sample. We targeted employees who experienced the COVID-19 pandemic. All data was collected through an electronic questionnaire (Google and Microsoft Forms). The research model was tested using structural equation modeling (SEM). The results showed a negative effect of the toxic workplace on the mental health of employees. T

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Publication Date
Wed Jun 01 2022
Journal Name
Iraqi Journal Of Physics
Theoretical Investigations of Electronic and Optical Properties of Vanadium Doped Wurtzite Zinc Oxide from First Principle Calculation Method
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In this study lattice parameters, band structure, and optical characteristics of pure and V-doped ZnO are examined by employing (USP) and (GGA) with the assistance of First-principles calculation (FPC) derived from (DFT). The measurements are performed in the supercell geometry that were optimized. GGA+U, the geometrical structures of all models, are utilized to compute the amount of energy after optimizing all parameters in the models. The volume of the doped system grows as the content of the dopant V is increased. Pure and V-doped ZnO are investigated for band structure and energy bandgaps using the Monkhorst–Pack scheme's k-point sampling techniques in the Brillouin zone (G-A-H-K-G-M-L-H). In the presence of high V content, the ban

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Publication Date
Fri Jan 07 2022
Journal Name
International Journal Of Early Childhood Special Education
Hierarchical learning and its effect on learning some basic skills in fencing for third stage students.
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MH Hamzah, AF Abbas, International Journal of Early Childhood Special Education, 2022

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Publication Date
Fri Oct 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Novel Approximate Solutions for Nonlinear Initial and Boundary Value Problems
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This paper investigates an effective computational method (ECM) based on the standard polynomials used to solve some nonlinear initial and boundary value problems appeared in engineering and applied sciences. Moreover, the effective computational methods in this paper were improved by suitable orthogonal base functions, especially the Chebyshev, Bernoulli, and Laguerre polynomials, to obtain novel approximate solutions for some nonlinear problems. These base functions enable the nonlinear problem to be effectively converted into a nonlinear algebraic system of equations, which are then solved using Mathematica®12. The improved effective computational methods (I-ECMs) have been implemented to solve three applications involving nonli

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Publication Date
Thu Feb 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Estimation of parameters of two-dimensional sinusoidal signal model by employing Deferential Evaluation algorithm and the use of Sequential approach in estimation
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Estimation the unknown parameters of a two-dimensional sinusoidal signal model is an important and a difficult problem , The importance of this model  in modeling Symmetric gray- scale texture image . In this paper, we propose employment Deferential Evaluation algorithm and the use of Sequential approach to estimate the unknown frequencies and amplitudes of the 2-D sinusoidal components when the signal is affected by noise. Numerical simulation are performed for different sample size, and various level of standard deviation to observe the performance of this method in estimate the parameters of 2-D sinusoidal signal model , This model was used for modeling  the Symmetric gray scale texture image and estimating by using

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Publication Date
Sun May 01 2016
Journal Name
Iraqi Journal Of Science
Efficient text in image hiding method based on LSB method principle
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The steganography (text in image hiding) methods still considered important issues to the researchers at the present time. The steganography methods were varied in its hiding styles from a simple to complex techniques that are resistant to potential attacks. In current research the attack on the host's secret text problem didn’t considered, but an improved text hiding within the image have highly confidential was proposed and implemented companied with a strong password method, so as to ensure no change will be made in the pixel values of the host image after text hiding. The phrase “highly confidential” denoted to the low suspicious it has been performed may be found in the covered image. The Experimental results show that the covere

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Publication Date
Fri May 03 2024
Journal Name
International Journal Of Economics And Finance Studies
THE CREDIT BUREAU SYSTEM'S ROLE IN ACHIEVING THE BANKING SOUNDNESS PRINCIPLE
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The regulatory authorities have implemented various standards to address the risks associated with credit facilities. One important aspect is the use of the Credit Bureau System (CBS), which plays a central role in ensuring banking soundness. Thus, the study seeks to explore the role of CBS in attaining banking soundness as a fundamental principle. The research sample consisted of three Iraqi banks spanning from 2010 to 2022. The research findings indicated that the implementation of CBS had a significant positive impact on achieving Banking Soundness (BS) rates in my bank. Furthermore, the asset quality index's value increased significantly, surpassing the standard value of 5%. It became evident that the banks needed to formulate a well-de

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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
The Exchange Rate of Iraqi Dinar between De facto Regime and De jure Regime in the Iraq during (2004-2012)
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         The understanding exchange rate policy is fundamental in order to identify the mechanism by which works out macroeconomic, And the vital for macroeconomic analysis and empirical work to differentiate between the de facto regimes and de jure regimes, Where the proved surveys and studies issued by the international monetary fund that there is divergence between the de facto regime (Regime of exchange applied by the country actually) and between the de jure regime (Regime de jure through the documents and formal writings of officials of the central bank), And launched studies on the de facto regime (Being a the basis of evaluating monetary policy) Stabilized (peg-like)arrangements or

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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Retrieving Encrypted Images Using Convolution Neural Network and Fully Homomorphic Encryption
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A content-based image retrieval (CBIR) is a technique used to retrieve images from an image database. However, the CBIR process suffers from less accuracy to retrieve images from an extensive image database and ensure the privacy of images. This paper aims to address the issues of accuracy utilizing deep learning techniques as the CNN method. Also, it provides the necessary privacy for images using fully homomorphic encryption methods by Cheon, Kim, Kim, and Song (CKKS). To achieve these aims, a system has been proposed, namely RCNN_CKKS, that includes two parts. The first part (offline processing) extracts automated high-level features based on a flatting layer in a convolutional neural network (CNN) and then stores these features in a

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