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Proposed Hybrid Sparse Adaptive Algorithms for System Identification
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Abstract 

For sparse system identification,recent suggested algorithms are  -norm Least Mean Square (  -LMS), Zero-Attracting LMS (ZA-LMS), Reweighted Zero-Attracting LMS (RZA-LMS), and p-norm LMS (p-LMS) algorithms, that have modified the cost function of the conventional LMS algorithm by adding a constraint of coefficients sparsity. And so, the proposed algorithms are named  -ZA-LMS,  -RZA-LMS, p-ZA-LMS and p-RZA-LMS that are designed by merging twoconstraints from previous algorithms to improve theconvergence rate and steady state of MSD for sparse system. In this paper, a complete analysis was done for the theoretical operation of proposed algorithms by exited white Gaussian sequence for input signal. The discussion of mean square deviation (MSD) with regard to parameters of algorithms and system sparsity was observed. In addition, in this paper, the correlation between proposed algorithms and the last recent algorithms were presented and the necessary conditions of these proposed algorithms were planned to improve convergence rate. Finally, the results of simulations are compared with theoretical study (?), which is presented to match closely by a wide-range of parameters..

Keywords: Adaptive filter,  -LMS, zero-attracting, p-LMS, mean square deviation, Sparse system identification.

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Publication Date
Wed Jun 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Proposed method to estimate missing values in Non - Parametric multiple regression model
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In this paper, we will provide a proposed method to estimate missing values for the Explanatory variables for Non-Parametric Multiple Regression Model and compare it with the Imputation Arithmetic mean Method, The basis of the idea of this method was based on how to employ the causal relationship between the variables in finding an efficient estimate of the missing value, we rely on the use of the Kernel estimate by Nadaraya – Watson Estimator , and on Least Squared Cross Validation (LSCV) to estimate the Bandwidth, and we use the simulation study to compare between the two methods.

 

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Publication Date
Thu Dec 01 2022
Journal Name
Iop Conference Series: Earth And Environmental Science
Velocity Patterns inside the Proposed Makhool Dam Reservoir with Different Operation Plans
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Abstract<p>The Makhoul Dam project proposed to be established is considered one of the strategic projects in Iraq as it works to insurance large quantity of water spare in flood seasons, increase the storage capacity of the dams in Iraq, as well as increase food security. The Makhool Dam is located on Tigris River in Salah al-Din Governorate, and 8 km south of the meeting point of the Tigris River with the Lower Zab River. The lake area is about 256 km2. In this research, a mathematical model was prepared by using HEC-RAS Two Dimension Software to analyze the velocity patterns and water depths inside makhool dam reservoir at the highest operational water elevation, based on the designs prepared </p> ... Show More
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Publication Date
Sun Jun 30 2013
Journal Name
Al-kindy College Medical Journal
Rapid and Reliable Method for Identification of V. Cholera O1 and V. Cholera O139 Serotypes in Diarrheal Cases in Baghdad.
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Backgrround:: Cholera is gastroenteritis caused by enterotoxin producing Vibrio cholera. Cholera is predominantly a waterborne disease especially in countries with inadequate sanitation. Several rapid methods have been developed and used to detect V. cholerae serotypes directly from stools.
Objjecttiives:: to evaluate a rapid and accurate method for the diagnosis of cholera caused by V. cholerae O1 and O139 serogroups d to find the incidence of sporadic cases of cholera in Baghdad.
Metthods:: Sixty four stool samples were collected from four hospitals in Baghdad. The age of patients ranging from two months to 12 years, 26 were females and 38 males. Immunochromatographic visual test for qualitative detection of O1 and /or O139 serog

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Publication Date
Thu May 29 2025
Journal Name
Indonesian Journal Of Chemistry
Synthesis, Spectral Identification, Thermal Studies, Antioxidant Properties, and Biological Effects for Some Metal Ion Complexes with New Schiff Base Ligand
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The tetradentate N2O2 Schiff base ligand, which is produced via the condensation reaction of 2-hydroxynaphthaldehyde with phthalohydrazide, is prepared in this work with a fair yield. The prepared ligand was characterized using a microanalysis technique (C.H.N), UV-vis, FTIR, 1H-,13C-NMR, mass spectrometry, and thermal gravimetric analysis (TGA). New complexes were synthesized by a reaction between ligand (N'1E,N'2Z)-N'1,N'2-bis((1-hydroxynaphthalen-2yl)methylene)phthalohydrazide and metal chloride of Co+2, Ni+2, and Zn+2 ions in absolute ethanol. The present complexes are also characterized by techniques such as C.H.N, UV-vis, FTIR, TGA, molar conductivity, atomic absorption, and magnetic moment measurements. The in vitro antimicro

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Publication Date
Fri Mar 29 2024
Journal Name
Iraqi Journal Of Science
Biological versus Topological Domains in Improving the Reliability of Evolutionary-Based Protein Complex Detection Algorithms
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     By definition, the detection of protein complexes that form protein-protein interaction networks (PPINs) is an NP-hard problem. Evolutionary algorithms (EAs), as global search methods, are proven in the literature to be more successful than greedy methods in detecting protein complexes. However, the design of most of these EA-based approaches relies on the topological information of the proteins in the PPIN. Biological information, as a key resource for molecular profiles, on the other hand, acquired a little interest in the design of the components in these EA-based methods. The main aim of this paper is to redesign two operators in the EA based on the functional domain rather than the graph topological domain. The perturb

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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Recurrent Stroke Prediction using Machine Learning Algorithms with Clinical Public Datasets: An Empirical Performance Evaluation
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Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al

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Publication Date
Sun Aug 25 2019
Journal Name
Civil Engineering Journal
Optimum Efficiency of PV Panel Using Genetic Algorithms to Touch Proximate Zero Energy House (NZEH)
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By optimizing the efficiency of a modular simulation model of the PV module structure by genetic algorithm, under several weather conditions, as a portion of recognizing the ideal plan of a Near Zero Energy Household (NZEH), an ideal life cycle cost can be performed. The optimum design from combinations of NZEH-variable designs, are construction positioning, window-to-wall proportion, and glazing categories, which will help maximize the energy created by photovoltaic panels. Comprehensive simulation technique and modeling are utilized in the solar module I-V and for P-V output power. Both of them are constructed on the famous five-parameter model.  In addition, the efficiency of the PV panel is established by the genetic algorithm

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Publication Date
Mon Dec 01 2025
Journal Name
Case Studies In Construction Materials
Optimized stress-strain modeling of eco-friendly fiber-reinforced concrete members using meta-heuristic algorithms
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Eco-friendly concrete is produced using the waste of many industries. It reduces the fears concerning energy utilization, raw materials, and mass-produced cost of common concrete. Several stress-strain models documented in the literature can be utilized to estimate the ultimate strength of concrete components reinforced with fibers. Unfortunately, there is a lack of data on how non-metallic fibers, such as polypropylene (PP), affect the properties of concrete, especially eco-friendly concrete. This study presents a novel approach to modeling the stress-strain behavior of eco-friendly polypropylene fiber-reinforced concrete (PFRC) using meta-heuristic particle swarm optimization (PSO) employing 26 PFRC various mixtures. The cement was partia

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Publication Date
Wed Sep 15 2021
Journal Name
2021 International Conference On Computing And Communications Applications And Technologies (i3cat)
Parallel Hybrid String Matching Algorithm Using CUDA API Function
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Publication Date
Mon Sep 01 2025
Journal Name
Journal Of Information Hiding And Multimedia Signal Processing
Steganography Based on Image Compression Using a Hybrid Technique
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Information security is a crucial factor when communicating sensitive information between two parties. Steganography is one of the most techniques used for this purpose. This paper aims to enhance the capacity and robustness of hiding information by compressing image data to a small size while maintaining high quality so that the secret information remains invisible and only the sender and recipient can recognize the transmission. Three techniques are employed to conceal color and gray images, the Wavelet Color Process Technique (WCPT), Wavelet Gray Process Technique (WGPT), and Hybrid Gray Process Technique (HGPT). A comparison between the first and second techniques according to quality metrics, Root-Mean-Square Error (RMSE), Compression-

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