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Some Robust methods for Estimates the power Spectrum in ARMA Models Simulation Study
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Abstract:

Robust statistics Known as, resistance to errors caused by deviation from the stability hypotheses of the statistical operations (Reasonable, Approximately Met, Asymptotically Unbiased, Reasonably Small Bias, Efficient ) in the data selected in a wide range of probability distributions whether they follow a normal distribution or a mixture of other distributions deviations different standard .

power spectrum function lead to, President role in the analysis of Stationary random processes, form stable random variables organized according to time, may be discrete random variables or continuous. It can be described by measuring its total capacity as function in frequency.

 As supposed distribution of the data mistakes in accordance with the normal or approach to the normal distribution ،Share estimation methods fortified with the concept of nonparametric in the absence of a clear model parameters (Free distribution) as the contamination is unknown model has distributed part of it in accordance with the normal distribution, while the other part is unknown distribution, and thus became the distribution of tainted its parameters unknown, so it can be considered the highest level in grades nonparametric methods are based on the conversion calculable test to a standard degree held by the convergence class standard process.

The aim of the Search: compared to some of the Robust estimation methods and non-parametric, So find the best estimator of Power spectrum With the mixed ARMA model for time series follow a Normal distribution, Then,  applied the most accurate on realistic data About the diagnosis of the factors that reflect the sources of change in time series of the electrical reference (ECG - Electrocardiogram) in normal state (unsatisfactory), through the analysis of the power spectrum. By finding the best estimator of the ability of spectrum according to the mixed spectrum for Series follow a particular dist. & applied to Real data(ECG), The method adopted other Parameters to get realistic results are related to the behavior of the real System reference (ECG)the Capabilities of ability Normal dist. Increase with the size of the Section ,and the highest at Section 200 in a manner Tokey

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Publication Date
Sat Jul 31 2021
Journal Name
Brain Sciences
Robust EEG Based Biomarkers to Detect Alzheimer’s Disease
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Biomarkers to detect Alzheimer’s disease (AD) would enable patients to gain access to appropriate services and may facilitate the development of new therapies. Given the large numbers of people affected by AD, there is a need for a low-cost, easy to use method to detect AD patients. Potentially, the electroencephalogram (EEG) can play a valuable role in this, but at present no single EEG biomarker is robust enough for use in practice. This study aims to provide a methodological framework for the development of robust EEG biomarkers to detect AD with a clinically acceptable performance by exploiting the combined strengths of key biomarkers. A large number of existing and novel EEG biomarkers associated with slowing of EEG, reductio

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Publication Date
Fri Dec 01 2023
Journal Name
Political Sciences Journal
¬The Role of the European Union in Conflicts Resolution in the Eastern Neighborhood: Selected Models
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The launch of the EU’s Eastern Partnership in 2009 intended to signal a new, elevated level of EU engagement with its Eastern neighborhood. Yet there remain several long-simmering and potentially destabilizing conflicts in the region, with which EU engagement thus far has been sporadic at best. The Union’s use of its Common Security and Defense Policy (CSDP) in the region and to help solve these disputes has been particularly ad hoc and inconsistent, wracked by inter-institutional incoherence and undermined by Member States’ inability to agree on a broad strategic vision for engagement with the area.

The three CSDP missions deployed to the region thus far have all suffered from this incoherence to various extents. In particu

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Publication Date
Wed Oct 31 2018
Journal Name
Heat Transfer-asian Research
Comparative study on heat transfer enhancement of nanofluids flow in ribs tube using CFD simulation
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Publication Date
Tue Jun 13 2023
Journal Name
Journal Of Survey In Fisheries Sciences
Spectrum Analyzing X-ray Data Image (FITS) Using Ds9 Program
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n this study, data or X-ray images Fixable Image Transport System (FITS) of objects were analyzed, where energy was collected from the body by several sensors; each sensor receives energy within a specific range, and when energy was collected from all sensors, the image was formed carrying information about that body. The images can be transferred and stored easily. The images were analyzed using the DS9 program to obtain a spectrum for each object,an energy corresponding to the photons collected per second. This study analyzed images for two types of objects (globular and open clusters). The results showed that the five open star clusters contain roughly t

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Publication Date
Tue Jan 08 2019
Journal Name
Iraqi Journal Of Physics
Simulation and experimental study of Pin-Plate DC discharge plasma technique
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The present work intends to study of dc glow discharge were generated between pin (cathode) and a plate (anode) in Ar gas is performed using COMSOL were used to study electric field distribution along the axis of the discharge and also the distribution of electron density and electron temperature at constant pressure (P=.0.0mbar) and inter electrode distance (d=4 cm) at different applied voltage for both pin cathode system and plate anode and comparison with experimental results.

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Publication Date
Wed Apr 01 2009
Journal Name
2009 Ieee Wireless Communications And Networking Conference
Power Efficiency Maximization in Cognitive Radio Networks
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Cognitive radio technology is used to improve spectrum efficiency by having the cognitive radios act as secondary users to access primary frequency bands when they are not currently being used. In general conditions, cognitive secondary users are mobile nodes powered by battery and consuming power is one of the most important problem that facing cognitive networks; therefore, the power consumption is considered as a main constraint. In this paper, we study the performance of cognitive radio networks considering the sensing parameters as well as power constraint. The power constraint is integrated into the objective function named power efficiency which is a combination of the main system parameters of the cognitive network. We prove the exi

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Publication Date
Wed Aug 30 2023
Journal Name
Mathematical Modelling Of Engineering Problems
Dynamic Low Power Clustering Strategy in MWSN
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Publication Date
Sat Mar 26 2022
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Dual use of Altman financial failure prediction analysis and stress tests to achieve integration in banking risk management : Analytical study of the National Bank of Iraq
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The research aims to demonstrate the dual use of analysis to predict financial failure according to the Altman model and stress tests to achieve integration in banking risk management. On the bank’s ability to withstand crises, especially in light of its low rating according to the Altman model, and the possibility of its failure in the future, thus proving or denying the research hypothesis, the research reached a set of conclusions, the most important of which (the bank, according to the Altman model, is threatened with failure in the near future, as it is located within the red zone according to the model’s description, and will incur losses if it is exposed to crises in the future according to the analysis of stress tests

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Publication Date
Mon Oct 02 2023
Journal Name
Journal Of Engineering
Skull Stripping Based on the Segmentation Models
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Skull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither non-brain tissues nor

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Publication Date
Mon Oct 02 2023
Journal Name
Journal Of Engineering
Skull Stripping Based on the Segmentation Models
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Skull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither no

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