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Comparing Some of Robust the Non-Parametric Methods for Semi-Parametric Regression Models Estimation
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In this research, some robust non-parametric methods were used to estimate the semi-parametric regression model, and then  these methods were compared using the MSE comparison criterion, different sample sizes, levels of variance, pollution rates, and three different models were used. These methods are S-LLS S-Estimation -local smoothing, (M-LLS)M- Estimation -local smoothing, (S-NW) S-Estimation-NadaryaWatson Smoothing, and (M-NW) M-Estimation-Nadarya-Watson Smoothing.

The results in the first model proved that the (S-LLS) method was the best in the case of large sample sizes, and small sample sizes showed that the (M-LLS) method was the best, while the second model showed in general that the S-LLS method was the best in addition to the method M-LLS was the best in some cases of sample sizes and at different levels of variance. As for the third model, it was shown through the results that in most cases the S-LLS method was the best in addition to the M-LLS method which was better in some cases of sample sizes and at different levels of variance.

 

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Publication Date
Sun Jun 01 2014
Journal Name
University Of Baghdad
New Analytical Methods for Drugs Analysis A Comparative Study
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Four different spectrophotometric methods are used in this study for the determination of Sulfamethoxazole and sulfanilamide drugs in pharmaceutical compounds, synthetic samples, and in their pure forms. The work comprises four chapters which are shown in the following: Chapter One: Includes a brief for Ultraviolet-Visible (UV-VIS) Absorption spectroscopy, antibacterial drugs and sulfonamides with some methods for their determination. The chapter lists two methods for optimization; univariate method and multivariate method. The later includes different types, two of these were mentioned; simplex method and design of experiment method. Chapter Two: Includes reaction of the two studied drugs with sodium nitrite and hydrochloric acid for diazo

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Publication Date
Mon Nov 19 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Use of Logistic Regression Approach to Determine the Effective Factors Causing Renal Failure Disease
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    The main goal of this research is to determine the impact of some variables that we believe that they are important to cause renal failuredisease by using logistic regression approach.The study includes eight explanatory variables and the response variable represented by (Infected,uninfected).The statistical program SPSS is used to proform the required calculations

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Publication Date
Tue Dec 11 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Evaluation of Nursing staff Performance in Cardiac Care Units at Teaching and Non Teaching Hospitals in Kirkuk City: A Comparative Study
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Objective: The descriptive study was used to evaluate nursing staff performance in cardiac care units at teaching
and non teaching hospitals in kirkuk city: A comparative study.
Methodology: A descriptive study was used to evaluate nursing staff performance in cardiac care units. The study
was conducted from December 29th
, 2013 up to the 27th of Apr. 2014. A non-probability (purposive) sample of
(44) nurses who work in cardiac care unit at Azady teaching Hospital and Kirkuk general Hospital was evaluated by
a questionnaire which consisted of two parts; the first part is concerned with the demographic characteristics of
the nurses and the second part concerned Observation check list for evaluation nursing staff Perfo

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Publication Date
Wed Aug 31 2022
Journal Name
Al-kindy College Medical Journal
Health-Related Quality of Life in Diabetic Women with Comparing Obese & Normal weight
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Background: The prevalence of both obesity & diabetes are increasing all over the world & more in women.  They have a negative impact not only on morbidity & mortality but also on quality of life.

Objectives: To assess the HRQoL with a specific comparison between obese & normal weight among wo

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Publication Date
Sun Mar 17 2019
Journal Name
Baghdad Science Journal
The Potential of some Plant Extracts as Radical Scavengers and Dipeptidyl Peptidase-4 Inhibitors
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Seeds, beans, leaves, fruit peel and seeds of five plants (Ferula assa-foetida, Coffea robusta, Olea europaea, Punica granatum and Vitis vinifera, respectively) were extracted with four solvents (distilled water, 80% methanol, 80% acetone and a mixed solvent that included methanol, ethanol, acetone and n-butanol at proportions 7:1:1:1). Such manipulation yielded 20 extracts, which were phytochemically analyzed for total polyphenols (TP) and flavonoids (TF). The DPPH (2,2-diphenyl-1-picrylhydrazyl) radical scavenging activity (RSA) and DPP-4 (dipeptidyl peptidase-4) relative inhibition activity (RIA) were also assessed for each extract. The results revealed that mixed solvent extract of V.

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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
The Role of Talent Management on Strategic Performance Reinforcement A field research on some of Sumer's university colleges.
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In this research we have tackled the role of Talent management (as a private variable) within (the Talent attraction, the Talent management performance, Talent development and Talent retention) on strategic performance reinforcement ( accredited variable) within its dimensions ( financial perspective, costumer perspective, internal operations perspective and learning and development perspective). The research conducted on sample of some college teachers from two of Sumer's colleges. The research problem represented by the broad organization's competition as well as universities; which led these colleges to investigate it's skillful human staff to meet it's strategic performance. 

To meet the aims of

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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Antibacterial Activity of Three Algal Genera against some Pathogenic Bacteria
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In the current study, three types of algae namely Tetradesmus nygaardi (MZ801740), Scenedesmus quadricauda (MZ801741) and Coelastrella sp (MZ801742) were extracted by 95% ethanol and hexane against two types of gram positive and two types of gram negative bacteria by wells diffusion methods. Eleven concentrations from the extract of algae (2, 5, 10, 15, 20, 25, 30, 35, 40, 45 and 50 mg/ml) were utilized. It was noticed that ethanolic extraction was more effective than hexane in Scenedesmus quadricauda than the two other mentioned algal species against all pathogenic bacteria, Acintobacter baumanii (ATCC: 19606), Klebsiella pneumonia (ATCC: 13883) Enterococcus faecalis (ATCC: 29212) and Staphylococc

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
â- structure properties ofZn-Phthalocyanine organic semi-conductor
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The x-ray fluorescence (XRF) of Znpc molecule with (flow of Ar) and Znpc molecule with (grow in N2) showed two peaks at (8.5and 9.5 Kv) referring to orbital transition ) K?-shell & K?-shell) respectively. The study of x-ray diffraction (XRD) where it was observed good growth of the crystal structure as a needle by the sublimation technique with a ?-phase of (monoclinic structure ) . Using Bragg equation the value of the interdistance of the crystalline plane (d-value) were calculated. We noticed good similarity with like once in the American Standards for Testing Material (ASTM) .Powder Diffraction File (PDF) Program was used to ensure the information obtained from (ASTM) . The output of (PDF) was compared with celn program, where the val

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Publication Date
Sun Sep 01 2019
Journal Name
Journal Of Physics: Conference Series
Recovery of temporal coefficient for heat equation from non-local overdetermination conditions
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Abstract<p>Recovery of time-dependent thermal conductivity has been numerically investigated. The problem of identification in one-dimensional heat equation from Cauchy boundary data and mass/energy specification has been considered. The inverse problem recasted as a nonlinear optimization problem. The regularized least-squares functional is minimised through lsqnonlin routine from MATLAB to retrieve the unknown coefficient. We investigate the stability and accuracy for numerical solution for two examples with various noise level and regularization parameter.</p>
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Publication Date
Wed Oct 09 2024
Journal Name
Engineering, Technology &amp; Applied Science Research
Improving Pre-trained CNN-LSTM Models for Image Captioning with Hyper-Parameter Optimization
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The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

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