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Proposed Entropy Loss function and application to find Bayesian estimator for Exponential distribution parameter
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The aim of this paper to find Bayes estimator under new loss function assemble between symmetric and asymmetric loss functions, namely, proposed entropy loss function, where this function that merge between entropy loss function and the squared Log error Loss function, which is quite asymmetric in nature. then comparison a the Bayes estimators of exponential distribution under the proposed function, whoever, loss functions ingredient for the proposed function the using a standard mean square error (MSE) and Bias quantity (Mbias), where the generation of the random data using the simulation for estimate exponential distribution parameters different sample sizes (n=10,50,100) and (N=1000), taking initial values for the parameters  and initial value b, to get to estimator balanced add between two loss function ,moreover, the optimal sample size determination under proposed entropy loss function.

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Publication Date
Sun Jan 01 2017
Journal Name
International Journal Of Advanced Computer Science And Applications
A Proposed Framework to Investigate the User Acceptance of Personal Health Records in Malaysia using UTAUT2 and PMT
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Publication Date
Tue Feb 01 2022
Journal Name
Baghdad Science Journal
Application of Groebner Bases to Study a Communication System
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This paper introduces a relationship between the independence of polynomials associated with the links of the network, and the Jacobian determinant of these polynomials. Also, it presents a way to simplify a given communication network through an algorithm that splits the network into subnets and reintegrates them into a network that is a general representation or model of the studied network. This model is also represented through a combination of polynomial equations and uses Groebner bases to reach a new simplified network equivalent to the given network, which may make studying the ability to solve the problem of network coding less expensive and much easier.

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Publication Date
Tue Dec 01 2009
Journal Name
Iraqi Journal Of Physics
Laplacian Operator as Speaker Identification Parameter
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New speaker identification test’s feature, extracted from the differentiated form of the wave file, is presented. Differentiation operation is performed by an operator similar to the Laplacian operator. From the differentiated record’s, two parametric measures have been extracted and used as identifiers for the speaker; i.e. mean-value and number of zero-crossing points.

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Publication Date
Mon Jan 01 2024
Journal Name
Fusion: Practice And Applications
Proposed Framework for Semantic Segmentation of Aerial Hyperspectral Images Using Deep Learning and SVM Approach
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Publication Date
Wed Feb 01 2012
Journal Name
Ibn Al-haytham Journal For Pure And Applied Science
Using Restricted Least Squares Method to Estimate and Analyze the Cobb-Douglas Production Function with Applicatio
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Publication Date
Sat Apr 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Application the generalized estimating equation Method (GEE) to estimate of conditional logistic regression model for repeated measurements
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Conditional logistic regression is often used to study the relationship between event outcomes and specific prognostic factors in order to application of logistic regression and utilizing its predictive capabilities into environmental studies. This research seeks to demonstrate a novel approach of implementing conditional logistic regression in environmental research through inference methods predicated on longitudinal data. Thus, statistical analysis of longitudinal data requires methods that can properly take into account the interdependence within-subjects for the response measurements. If this correlation ignored then inferences such as statistical tests and confidence intervals can be invalid largely.

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Publication Date
Sun Sep 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
Compared Methods of Generating Both Gamma Distribution and Beta Distribution
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Beta Distribution

Abstract

             Gamma and Beta Distributions has very important in practice in various areas of statistical and applications reliability and quality control of production. and There are a number of methods to generate data behave on according to these distribution. and These methods bassic primarily on the shape parameters of each distribution and the relationship between these distributions and their relationship with some other probability distributions.    &nb

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Publication Date
Thu Dec 28 2017
Journal Name
Al-khwarizmi Engineering Journal
An Autocorrelative Approach for EMG Time-Frequency Analysis
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As they are the smallest functional parts of the muscle, motor units (MUs) are considered as the basic building blocks of the neuromuscular system. Monitoring MU recruitment, de-recruitment, and firing rate (by either invasive or surface techniques) leads to the understanding of motor control strategies and of their pathological alterations. EMG signal decomposition is the process of identification and classification of individual motor unit action potentials (MUAPs) in the interference pattern detected with either intramuscular or surface electrodes. Signal processing techniques were used in EMG signal decomposition to understand fundamental and physiological issues. Many techniques have been developed to decompose intramuscularly detec

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Publication Date
Mon Nov 24 2025
Journal Name
2025 13th International Conference On Control, Mechatronics And Automation (iccma)
Modeling Twisting and Coiling Actuators with Regression-Based Learning: Application to Neck Rehabilitation
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Twisting and coiling actuators (TCAs) are lightweight artificial muscles that can produce large linear contractions while lifting heavy loads with low power. A TCA consists of two or more strings connected to a rotational motor and a load. When activated, the strings twist and coil, causing contraction. This study presents a data-driven framework for modeling TCA behavior using experimental data. Polynomial regression, Support Vector Regression (SVR), and symbolic regression were applied using the motor angle and payload weight as inputs. The models were evaluated under various loads and implemented in a neck-rehabilitation prototype. SVR showed the highest accuracy (RMSE: 6.17 mm upward, 4.98 mm downward); however, it lacks a closed-form e

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Publication Date
Thu Jan 01 2026
Journal Name
International Journal Of Energy Research
Mobility of Hydrophilic and Hydrophobic Nanoparticles in Carbonate Reservoirs: Application to Subsurface Projects
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Nanoparticles (NPs) have been suggested for subsurface projects, including enhanced oil recovery (EOR), carbon capture and storage (CCS), and hydrogen storage, due to their small size, high surface energy, controlled surface properties, and significant effects on the underground formation properties. Silica is an excellent NP that efficiently modifies the surface properties of subsurface formations for incremental oil recovery and to derisk carbon and hydrogen leaks. However, the retention of injected NPs in a narrow area near the injection inlet can limit a project’s feasibility. In the present study, hydrophobic (hybrid) NPs were produced via silanization of silica NPs, and the mobility behavior of bare (hydrophilic) and hybrid

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