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jeasiq-317
Compared of estimating two methods for nonparametric function to cluster data for the white blood cells to leukemia patients
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   We can notice cluster data in social, health and behavioral sciences, so this type of data have a link between its observations and we can express these clusters through the relationship between measurements on units within the same group.

    In this research, I estimate the reliability function of cluster function by using the seemingly unrelated Kernel Estimators method and the Generalized Least Squares Smoothing Spline Estimators method, and I applied these two methods on Leukemia patients and made a comparison between the two methods by using MSE and MAE comparison standard, the empirical results showed the efficiency of the Generalized Least Squares Smoothing Spline Estimators method.

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Publication Date
Mon Jan 01 2024
Journal Name
Pharmaceutical Sciences Asia
Effect of sub-minimum inhibitory concentrations of ceftriaxone on the Pseudomonas aeruginosa adhesion to human oral mucosal epithelial cells and biofilm formation to polystyrene in vitro
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Publication Date
Fri Dec 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
مقارنة بين طريقتي مقدرات لابلاس وهوبر الحصين لتقدير معلمات أنموذج الانحدار اللوجستي
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يعد أنموذج الانحدار اللوجستي من نماذج الانحدار المهمة، حيث يلقى اهتماماً واضحاً في معظم الدراسات التي تأخذ طابعاً اكثر تقدماً في عملية التحليل الاحصائي. أن طرائق التقدير الاعتيادية تفشل في التعامل مع البيانات التي تتضمن وجود القيم الشاذة حيث أن لها تأثير غير مرغوب على النتائج. سنستعرض في هذا البحث طرائق لتقدير معلمات انموذج الانحدار اللوجستي وهذه الطرائق هي: طريقة مقدر لابلاس (Laplace estimator) (LP-) وطريقة مقدر هوب

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Publication Date
Tue Nov 10 2020
Journal Name
International Journal Of Psychosocial Rehabilitation
Hybridization Methodology of ARMA-FIGARCH Model to Examine Gasoline Data in Iraq
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Publication Date
Fri Dec 30 2011
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Improved Method to Correlate and Predict Isothermal VLE Data of Binary Mixtures
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Accurate predictive tools for VLE calculation are always needed. A new method is introduced for VLE calculation which is very simple to apply with very good results compared with previously used methods. It does not need any physical property except each binary system need tow constants only. Also, this method can be applied to calculate VLE data for any binary system at any polarity or from any group family. But the system binary should not confirm an azeotrope. This new method is expanding in application to cover a range of temperature. This expansion does not need anything except the application of the new proposed form with the system of two constants. This method with its development is applied to 56 binary mixtures with 1120 equili

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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
THE IMPACT OF LISTEN TO THE VOICE OF THE CUSTOMER IN ACHIEVING COMPETITIVE SUPERIORITY
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The subject of the listen to the voice of the customer of topics relatively new in management thought, as it won the attention of many organizations of different types, because it is important to achieve success and to continue and superiority to them, so there is a need to study this term in the Iraqi organizations and try to diagnose the implementation of the study sample to listen voice of the Customer and its

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Publication Date
Mon Jun 30 2008
Journal Name
Iraqi Journal Of Science
On the Greedy Ridge Function Neural Networks for Approximation Multidimensional Functions
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The aim of this paper is to approximate multidimensional functions f∈C(R^s) by developing a new type of Feedforward neural networks (FFNS) which we called it Greedy ridge function neural networks (GRGFNNS). Also, we introduce a modification to the greedy algorithm which is used to train the greedy ridge function neural networks. An error bound are introduced in Sobolov space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result in [1]).

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Publication Date
Wed Feb 10 2016
Journal Name
ألمؤتمر الدولي العلمي الخامس للاحصائيين العرب/ القاهرة
Proposition of Modified Genetic Algorithm to Estimate Additive Model by using Simulation
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Often phenomena suffer from disturbances in their data as well as the difficulty of formulation, especially with a lack of clarity in the response, or the large number of essential differences plaguing the experimental units that have been taking this data from them. Thus emerged the need to include an estimation method implicit rating of these experimental units using the method of discrimination or create blocks for each item of these experimental units in the hope of controlling their responses and make it more homogeneous. Because of the development in the field of computers and taking the principle of the integration of sciences it has been found that modern algorithms used in the field of Computer Science genetic algorithm or ant colo

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Publication Date
Sat May 01 2021
Journal Name
Key Engineering Materials
Synthesis and Characterization of the Thin Films NiSe2/Si Heterojunction for Solar Cells
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Thin film solar cells are preferable to the researchers and in applications due to the minimum material usage and to the rising of their efficiencies. In particular, thin film solar cells, which are designed based one transition metal chalcogenide materials, paly an essential role in solar energy conversion market. In this paper, transition metals with chalcogenide Nickel selenide termed as (NiSe2/Si) are synthesized. To this end, polycrystalline NiSe2 thin films are deposited through the use of vacuum evaporation technique under vacuum of 2.1x10-5 mbar, which are supplied to different annealing temperatures. The results show that under an annealed temperature of 525 K,

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Publication Date
Sat Mar 01 2014
Journal Name
Renewable And Sustainable Energy Reviews
Review on the development of natural dye photosensitizer for dye-sensitized solar cells
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Publication Date
Mon Apr 01 2019
Journal Name
2019 International Conference On Automation, Computational And Technology Management (icactm)
Multi-Resolution Hierarchical Structure for Efficient Data Aggregation and Mining of Big Data
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Big data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining an

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