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The impact of wages and benefits systems on the performance of employees A field study in the General Company for Food Industries in the city of Baghdad
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The research aims to find out the impact of wages and benefits systems on the performance of employees, which included the research community on a sample of employees in the company, and the sample consisted of (50) employees and an employee, A questionnaire composed as prepared (23) paragraph, use the promised statistically methods in data collected by the questionnaire analysis. The research reached a number of results, the most prominent of which were: There is a correlation between wage systems, benefits and performance of employees, and the presence of the impact of the systems of wages and benefits to the performance of employees. The research was presented a set of recommendations including: increasing the effectiveness of the wage system in government institutions, and recommending to activate especially with regard to health insurance benefits systems.  

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Publication Date
Fri Oct 01 2010
Journal Name
2010 Ieee Symposium On Industrial Electronics And Applications (isiea)
Distributed t-way test suite data generation using exhaustive search method with map and reduce framework
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Publication Date
Tue Sep 14 2021
Journal Name
International Journal Of Advanced Biological And Biomedical Research
Candida Berkh. (1923) Species and Their Important Secreted Aspartyl Proteinases (SAP) Genes Isolated from Diabetic Patients
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Candida Berkh. (1923) occurs naturally in the body. But it becomes opportunistic fungi, meaning that it infects humans when there is any weakening of the immune system, such as exposure to chemotherapy, diabetes, or organ transplantation. Most species of Candida grow at a temperature between 20-40 °C and have a pH of 3-8. Human pathogens of Candida species include C. albicans, C. glabrata, C. lusitaniae, C. parapsilosis, C. tropicalis and C. utili. C. albicans has many virulence factors that facilitate injury process. Virulence factors are considered as a measure of pathogenicity, and it is in the form of fungal toxins, enzymes, or cell structures that facilitate infection, as well as pathogen resistance in different conditions. This study

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Publication Date
Tue Feb 16 2016
Journal Name
The Iraqi Journal Of Agricultural Sciences
MEASURING VIBRATION AT TRACTOR PLATFORM , STEERING WHEEL AND SEAT EFFECTIVE AMPLITUDE TRANSMISSIBILITY FACTOR DURING OPERATION TILLAGE
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Field experiment conducted to measure vibrations on three axes longitudinal X, lateral Y and vertical Z on steering wheel, platform tractor and vertical vibration in seat tractor and seat effective amplitude transmissibility (SEAT) factor during operation tillage in silt clay loam soil with depth 18 cm in Baghdad. Split – split plot design under randomized complete block design with three replications least significant design 5 % used. Three factor were used in this experiment included two types of plows included chisel and disc plows which represented main plot, three tires inflation pressure was second factor included 1.1 ,1.8 and 2.7 bar, and three forward speeds of the tillage was third factor included 2.35 , 4.25 and 6.50 km/hr. Resu

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Publication Date
Wed Feb 08 2023
Journal Name
Iraqi Journal Of Science
Subsurface 3D Prediction Porosity Model from Converted Seismic and Well Data Using Model Based Inversion Technique
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Seismic inversion technique is applied to 3D seismic data to predict porosity property for carbonate Yamama Formation (Early Cretaceous) in an area located in southern Iraq. A workflow is designed to guide the manual procedure of inversion process. The inversion use a Model Based Inversion technique to convert 3D seismic data into 3D acoustic impedance depending on low frequency model and well data is the first step in the inversion with statistical control for each inversion stage. Then, training the 3D acoustic impedance volume, seismic data and porosity wells data with multi attribute transforms to find the best statistical attribute that is suitable to invert the point direct measurement of porosity from well to 3D porosity distribut

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Publication Date
Wed Apr 25 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Using Approximation Non-Bayesian Computation with Fuzzy Data to Estimation Inverse Weibull Parameters and Reliability Function
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        In real situations all observations and measurements are not exact numbers but more or less non-exact, also called fuzzy. So, in this paper, we use approximate non-Bayesian computational methods to estimate inverse Weibull parameters and reliability function with fuzzy data. The maximum likelihood and moment estimations are obtained as non-Bayesian estimation. The maximum likelihood estimators have been derived numerically based on two iterative techniques namely “Newton-Raphson” and the “Expectation-Maximization” techniques. In addition, we provide compared numerically through Monte-Carlo simulation study to obtained estimates of the parameters and reliability function i

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Publication Date
Fri Jan 31 2025
Journal Name
Journal Mustansiriyah Of Sports Science
Self-Efficacy and its Relationship to Psychological Adjustment among Table Tennis Players with Disabilities Special Needs
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The introduction and importance of the research included that physical education and its various activities are important for the disabled. The exercise of physical activities by the disabled effectively contributes to raising their level of fitness and reducing diseases caused by lack of movement. Disabled people often suffer from psychological and social problems, and this feeling may be accompanied by a high level of anxiety, a lack of self-esteem and a loss of self-confidence. Psychological adaptation is one of the concepts of sports psychology interconnected with the psychological climate, as the process that the player seeks to meet his demands and needs. Adaptation includes the pursuit of emotional balance between the individual play

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Publication Date
Sat Jan 20 2024
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Enhanced Support Vector Machine Methods Using Stochastic Gradient Descent and Its Application to Heart Disease Dataset
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Support Vector Machines (SVMs) are supervised learning models used to examine data sets in order to classify or predict dependent variables. SVM is typically used for classification by determining the best hyperplane between two classes. However, working with huge datasets can lead to a number of problems, including time-consuming and inefficient solutions. This research updates the SVM by employing a stochastic gradient descent method. The new approach, the extended stochastic gradient descent SVM (ESGD-SVM), was tested on two simulation datasets. The proposed method was compared with other classification approaches such as logistic regression, naive model, K Nearest Neighbors and Random Forest. The results show that the ESGD-SVM has a

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Publication Date
Fri Oct 20 2023
Journal Name
Bmc Endocrine Disorders
Dietary caffeine intake is associated with favorable metabolic profile among apparently healthy overweight and obese individuals
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Abstract<sec> <title>Background

Recent studies have revealed some conflicting results about the health effects of caffeine. These studies are inconsistent in terms of design and population and source of consumed caffeine. In the current study, we aimed to evaluate the possible health effects of dietary caffeine intake among overweight and obese individuals.

Methods

In this cross-sectional study, 488 apparently healthy individuals with overweight and obesity were participated. Dietary intake was assessed by a Food Frequency Questionnaire (FFQ) and

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Publication Date
Sun May 01 2022
Journal Name
Optical Fiber Technology
Optical fiber sensor network integrating SAC-OCDMA and cladding modified optical fiber sensors coated with nanomaterial
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Publication Date
Thu Mar 01 2018
Journal Name
2018 International Conference On Computing Sciences And Engineering (iccse)
Comparison between Epsilon Normalized Least Means Square (ϵ-NLMS) and Recursive Least Squares (RLS) Adaptive Algorithms
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There is an evidence that channel estimation in communication systems plays a crucial issue in recovering the transmitted data. In recent years, there has been an increasing interest to solve problems due to channel estimation and equalization especially when the channel impulse response is fast time varying Rician fading distribution that means channel impulse response change rapidly. Therefore, there must be an optimal channel estimation and equalization to recover transmitted data. However. this paper attempt to compare epsilon normalized least mean square (ε-NLMS) and recursive least squares (RLS) algorithms by computing their performance ability to track multiple fast time varying Rician fading channel with different values of Doppler

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