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Function Approximation Technique (FAT)-Based Adaptive Feedback Linearization Control for Nonlinear Aeroelastic Wing Models Considering Different Actuation Scenarios
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Publication Date
Thu Dec 28 2023
Journal Name
Journal Européen Des Systèmes Automatisés
Design of a Hybrid Adaptive Controller for Series Elastic Actuators of Robots
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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
An Adaptive Harmony Search Part-of-Speech tagger for Square Hmong Corpus
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Data-driven models perform poorly on part-of-speech tagging problems with the square Hmong language, a low-resource corpus. This paper designs a weight evaluation function to reduce the influence of unknown words. It proposes an improved harmony search algorithm utilizing the roulette and local evaluation strategies for handling the square Hmong part-of-speech tagging problem. The experiment shows that the average accuracy of the proposed model is 6%, 8% more than HMM and BiLSTM-CRF models, respectively. Meanwhile, the average F1 of the proposed model is also 6%, 3% more than HMM and BiLSTM-CRF models, respectively.

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Publication Date
Sun Oct 05 2025
Journal Name
Mesopotamian Journal Of Computer Science
DGEN: A Dynamic Generative Encryption Network for Adaptive and Secure Image Processing
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Cyber-attacks keep growing. Because of that, we need stronger ways to protect pictures. This paper talks about DGEN, a Dynamic Generative Encryption Network. It mixes Generative Adversarial Networks with a key system that can change with context. The method may potentially mean it can adjust itself when new threats appear, instead of a fixed lock like AES. It tries to block brute‑force, statistical tricks, or quantum attacks. The design adds randomness, uses learning, and makes keys that depend on each image. That should give very good security, some flexibility, and keep compute cost low. Tests still ran on several public image sets. Results show DGEN beats AES, chaos tricks, and other GAN ideas. Entropy reached 7.99 bits per pix

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Publication Date
Mon Apr 01 2024
Journal Name
Heliyon
Ground effect of an inverted double element wing diffuser on a sedan car
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Publication Date
Sat Jun 01 2024
Journal Name
International Journal Of Advanced And Applied Sciences
High-accuracy models for iris recognition with merging features
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Due to advancements in computer science and technology, impersonation has become more common. Today, biometrics technology is widely used in various aspects of people's lives. Iris recognition, known for its high accuracy and speed, is a significant and challenging field of study. As a result, iris recognition technology and biometric systems are utilized for security in numerous applications, including human-computer interaction and surveillance systems. It is crucial to develop advanced models to combat impersonation crimes. This study proposes sophisticated artificial intelligence models with high accuracy and speed to eliminate these crimes. The models use linear discriminant analysis (LDA) for feature extraction and mutual info

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Publication Date
Wed Mar 29 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
A Review on Models for Evaluating Rock Petrophysical Properties
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The evaluation of subsurface formations as applied to oil well drilling started around 50 years ago. Generally, the curent review articule includes all methods for coring, logging, testing, and sampling. Also the methods for deciphering logs and laboratory tests that are relevant to assessing formations beneath the surface, including a look at the fluids they contain are discussed. Casing is occasionally set in order to more precisely evaluate the formations; as a result, this procedure is also taken into account while evaluating the formations. The petrophysics of reservoir rocks is the branch of science interested in studying chemical and physical properties of permeable media and the components of reservoir rocks which are associated

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Publication Date
Fri Mar 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
Robust Two-Step Estimation and Approximation Local Polynomial Kernel For Time-Varying Coefficient Model With Balance Longitudinal Data
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      In this research, the nonparametric technique has been presented to estimate the time-varying coefficients functions for the longitudinal balanced data that characterized by observations obtained through (n) from the independent subjects, each one of them is measured repeatedly by group of  specific time points (m). Although the measurements are independent among the different subjects; they are mostly connected within each subject and the applied techniques is the Local Linear kernel LLPK technique. To avoid the problems of dimensionality, and thick computation, the two-steps method has been used to estimate the coefficients functions by using the two former technique. Since, the two-

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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Bayesian Tobit Quantile Regression Model Using Double Adaptive elastic net and Adaptive Ridge Regression
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     Recently Tobit  Quantile Regression(TQR) has emerged as an important tool in statistical analysis . in order to improve the parameter estimation in (TQR) we proposed Bayesian hierarchical model with double adaptive elastic net technique  and Bayesian hierarchical model with adaptive ridge regression technique .

 in double adaptive elastic net technique we assume  different penalization parameters  for penalization different regression coefficients in both parameters λ1and  λ, also in adaptive ridge regression technique we assume different  penalization parameters for penalization different regression coefficients i

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Publication Date
Mon May 02 2022
Journal Name
Journal Of Research In Medical And Dental Science
Compression study of Irisin, Vitamin D and Kidney Function Parameters Between Iraqi Fracture Patients with and Without DM2 and Healthy Control
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Compression study of Irisin, Vitamin D and Kidney Function Parameters Between Iraqi Fracture Patients with and Without DM2 and Healthy Control, Omar Yousif Majnun*, Altaie AF

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Publication Date
Fri Apr 21 2023
Journal Name
Aip Conference Proceedings
Efficient computational methods for solving the nonlinear initial and boundary value problems
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In this paper, three approximate methods namely the Bernoulli, the Bernstein, and the shifted Legendre polynomials operational matrices are presented to solve two important nonlinear ordinary differential equations that appeared in engineering and applied science. The Riccati and the Darcy-Brinkman-Forchheimer moment equations are solved and the approximate solutions are obtained. The methods are summarized by converting the nonlinear differential equations into a nonlinear system of algebraic equations that is solved using Mathematica®12. The efficiency of these methods was investigated by calculating the root mean square error (RMS) and the maximum error remainder (𝑀𝐸𝑅n) and it was found that the accuracy increases with increasi

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