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bsj-1122
Pre-Test Single and Double Stage Shrunken Estimators for the Mean of Normal Distribution with Known Variance
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This paper is concerned with pre-test single and double stage shrunken estimators for the mean (?) of normal distribution when a prior estimate (?0) of the actule value (?) is available, using specifying shrinkage weight factors ?(?) as well as pre-test region (R). Expressions for the Bias [B(?)], mean squared error [MSE(?)], Efficiency [EFF(?)] and Expected sample size [E(n/?)] of proposed estimators are derived. Numerical results and conclusions are drawn about selection different constants included in these expressions. Comparisons between suggested estimators, with respect to classical estimators in the sense of Bias and Relative Efficiency, are given. Furthermore, comparisons with the earlier existing works are drawn.

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Publication Date
Sun Jul 07 2013
Journal Name
Journal Of Educational And Psychological Researches
Measurement of double-thinking among university students
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Current search targeted to:
  1 - Measurement of double-thinking among university students.
  2 - Identify the significant differences in the degrees of double-thinking members of the sample according to the variables of sex (male - female), specialty (I know - a human).
      To achieve the objectives of the research chose researcher samples from the community of the first search for statistical analysis, has reached 400 students, and the second sample of the application of the final, has reached (480) students were selected randomly with simple check of equal value, and the researcher building a search tool double think, After the completion of the scale-building measures think

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Publication Date
Tue Jan 01 2019
Journal Name
Biochemical & Cellular Archives
Assessment of uric acid in patients of end-stage renal disease with hypertension and diabetic nephropathy and the risk of cardiovascular diseases
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The relationship of hyperuricemia to kidney disease, diabetes, hypertension and the risk of cardiovascular diseases remain controversial. The aim of this study is to evaluate the use of uric acid (UA) levels to find the higher risk of cardiovascular disease (CVD) in patients with end stage renal disease that have diabetic nephropathy (DN), nephropathy with hypertension (NH) and patients with both diabetic nephropathy with hypertension (DNH). This study deals with 115 patients with end-stage renal disease under hemodialysis sub-grouped into 35 patients with (DN), 40 patients with (NH), and 40 patients with (DNH). Some biochemical parameters were determined in the serum of all participants such as HbA1c, fasting blood glucose (FBG), UA, urea,

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Publication Date
Thu Feb 02 2012
Journal Name
Education College Journal/al-mustansiriyah University
On Significance Testimator in Pareto Distribution Via Shrinkage Technique
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In this paper, preliminary test Shrinkage estimator have been considered for estimating the shape parameter α of pareto distribution when the scale parameter equal to the smallest loss and when a prior estimate α0 of α is available as initial value from the past experiences or from quaintance cases. The proposed estimator is shown to have a smaller mean squared error in a region around α0 when comparison with usual and existing estimators.

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Publication Date
Thu Jan 06 2022
Journal Name
Kuwait Journal Of Science
AVO analysis for high amplitude anomalies using 2D pre-stack seismic data
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Amplitude variation with offset (AVO) analysis is an 1 efficient tool for hydrocarbon detection and identification of elastic rock properties and fluid types. It has been applied in the present study using reprocessed pre-stack 2D seismic data (1992, Caulerpa) from north-west of the Bonaparte Basin, Australia. The AVO response along the 2D pre-stack seismic data in the Laminaria High NW shelf of Australia was also investigated. Three hypotheses were suggested to investigate the AVO behaviour of the amplitude anomalies in which three different factors; fluid substitution, porosity and thickness (Wedge model) were tested. The AVO models with the synthetic gathers were analysed using log information to find which of these is the

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Publication Date
Sun Oct 01 2017
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Pre-operative serum TSH level estimation for predicting malignant nodular thyroid disease
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Publication Date
Sun May 01 2011
Journal Name
Information Sciences
Design and implementation of a t-way test data generation strategy with automated execution tool support
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Publication Date
Wed Feb 08 2023
Journal Name
Eneurologicalsci
Double encephalocele with an excellent outcome postoperatively: A case report from Iraq
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HTH Ali Tarik Abdulwahid , Ahmed Dheyaa Al-Obaidi , Mustafa Najah Al-Obaidi, eNeurologicalSci, 2023

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Publication Date
Sun Feb 03 2019
Journal Name
Iraqi Journal Of Physics
Study of charge density distributions, elastic charge form factors and root-mean square radii for 4He, 12C and 16O nuclei using Woods- Saxon and harmonic-oscillator potentials
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The nuclear charge density distributions, form factors and
corresponding proton, charge, neutron, and matter root mean square
radii for stable 4He, 12C, and 16O nuclei have been calculated using
single-particle radial wave functions of Woods-Saxon potential and
harmonic-oscillator potential for comparison. The calculations for the
ground charge density distributions using the Woods-Saxon potential
show good agreement with experimental data for 4He nucleus while
the results for 12C and 16O nuclei are better in harmonic-oscillator
potential. The calculated elastic charge form factors in Woods-Saxon
potential are better than the results of harmonic-oscillator potential.
Finally, the calculated root mean square

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Publication Date
Tue Apr 02 2019
Journal Name
Artificial Intelligence Research
A three-stage learning algorithm for deep multilayer perceptron with effective weight initialisation based on sparse auto-encoder
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A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an

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Publication Date
Tue Feb 17 2026
Journal Name
Sustainable Engineering And Innovation
Morlet wavelet–based olfactory-evoked EEG features for random forest classification of normal, aMCI, and Alzheimer’s disease
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Olfactory impairment and abnormal frontal EEG oscillations are recognized as early markers of Alzheimer’s disease (AD). Using a publicly available olfactory EEG dataset of 35 subjects spanning normal cognition, amnestic mild cognitive impairment (aMCI), and AD, each with MMSE scores and demographics, stimulus-locked epochs from four electrodes (Fp1, Fz, Cz, Pz) were processed with wavelet-based time–frequency analysis. Band-limited power ratios (delta, theta, alpha, beta) were computed as log-transformed post-odor/baseline values and aggregated to subject-level features. Statistical analyses revealed graded attenuation of odor-evoked frontal (Fp1) band-power ratios across groups, with significant differences in several band–od

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