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Hybrid regimes: An Overview
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According to different types of democracy Indexes, hybrid regimes or those in the gray zone, make up the majority of regime transformations in the third wave of democracy. However, after nearly three decades, conceptual confusion about hybrid regimes persists and grows, while obstructing the accumulation of knowledge about the nature of hybrid regimes. This leads to significant political repercussions for democratization. This Paper attempts to provide a clearer view of different and overlapping concepts and classifications in this complex field, and sustain development in literature on democratic transformation. To achieve this, we followed an approach based on the classification of concepts and terms in three distinct categories, based on the different trends and successive stages in literature on hybrid regimes. This limits the conceptual stretching and intellectual bias. It also helps to extrapolate the elements of contrast and diversity to highlight the prospects for the transition to those regimes as much as possible. The Paper reached a number of results. The transition paradigm was the product of a previous stage during the strong early days of the third wave. Similarly, the subsequent facts have proven that this was not "the end of history." The hybrid regimes expressed these facts through their different patterns that were in multiple directions due to various cases and contexts. Therefore, the transition outcomes are also as accommodating towards the diversity in experiences of different democratic countries.

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Publication Date
Wed Jan 28 2026
Journal Name
F1000research
Enhancing Solar Power Forecasting Accuracy Using HMPCS and Machine Learning Techniques: An Applied Study
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Background Solar irradiance is a nonlinear and intermittent function, which makes accurate forecasting of solar power generation a challenge. The high variability of meteorological conditions is not well represented by conventional atmospheric models, thus hampering forecasting skill and model robustness. In this work, an advanced hybridization of multi-population cuckoo search (HMPCS) algorithm with machine learning (ML) methods is developed to enhance the prediction performance of photovoltaic (PV) power forecasting with more reliability. Methods In this study, a hybrid modeling framework is proposed, called HMPCS–ML framework which captures the global search capacity of HMPCS and predictive power of sophisti

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Publication Date
Wed Sep 01 2021
Journal Name
Computers And Concrete
Improving the seismic performance of reinforced concrete frames using an innovative metallic-shear damper
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Publication Date
Wed Jan 08 2020
Journal Name
International Journal Of Advanced Science And Technology
The local stability of an eco-epidemiological model involving a harvesting on predator population
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In this paper a prey - predator model with harvesting on predator species with infectious disease in prey population only has been proposed and analyzed. Further, in this model, Holling type-IV functional response for the predation of susceptible prey and Lotka-Volterra functional response for the predation of infected prey as well as linear incidence rate for describing the transition of disease are used. Our aim is to study the effect of harvesting and disease on the dynamics of this model.

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Publication Date
Wed Nov 01 2017
Journal Name
Biochemical Engineering Journal
Waste date seed oil extract as an alternative feedstock for Poly(3-hydroxybutyrate) synthesis
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Publication Date
Tue Nov 08 2022
Journal Name
Buildings
An Experimental Study of Granular Material Using Recycled Concrete Waste for Pavement Roadbed Construction
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Rapid worldwide urbanization and drastic population growth have increased the demand for new road construction, which will cause a substantial amount of natural resources such as aggregates to be consumed. The use of recycled concrete aggregate could be one of the possible ways to offset the aggregate shortage problem and reduce environmental pollution. This paper reports an experimental study of unbound granular material using recycled concrete aggregate for pavement subbase construction. Five percentages of recycled concrete aggregate obtained from two different sources with an originally designed compressive strength of 20–30 MPa as well as 31–40 MPa at three particle size levels, i.e., coarse, fine, and extra fine, were test

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
An Observation and Analysis the role of Convolutional Neural Network towards Lung Cancer Prediction
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Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c

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Publication Date
Tue Sep 15 2020
Journal Name
Arab World English Journal
A Cognitive-Semantic Analysis of Preposition on: An Experimental Study at University of Baghdad
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Publication Date
Sat Apr 20 2024
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
An Approximate Solution for a Second Order Elliptic Inverse Coefficient Problem with Nonlocal Integral
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This article studies the nonlocal inverse boundary value problem for a rectangular domain, a second-order, elliptic equation and a two-dimensional equation. The main objective of the article is to find the unidentified coefficient and provide a solution to the problem. The two-dimensional second-order, convection equation is solved directly using the finite difference method (FDM). However, the inverse problem was successfully solved the MATLAB subroutine lsqnonlin from the optimization toolbox after reformulating it as a nonlinear regularized least-square optimization problem with a simple bound on the unknown quantity. Considering that the problem under study is often ill-posed and that even a small error in the input data can hav

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Publication Date
Fri Apr 22 2022
Journal Name
Asian Journal Of Water, Environment And Pollution
An Ecological Comparison of Benthic Invertebrate Communities Between Sewage and Tigris River Water – Baghdad
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In the current study, two sites were selected from the city of Adhamiya, central Baghdad. The first site is the Adhamiya Corniche, which includes a sample of river water and the second includes domestic sewage in the same area. The total density of benthic invertebrates was 775 ind/m2, which is divided into 15 taxa. Biological indices were found, such as the stability index, the abundance index, the biodiversity index (Shannon’s index), the homogeneity index, and the invader’s guide. The result showed an increase in the density of benthic invertebrates, as well as an increase in the diversity of these organisms.

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Governance And Regulation
An empirical study to detect agency problems in listed corporations: The emerging market study
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The aim of this paper is to shed the light on the concepts of agency theory by measuring one of the problems that arise from it, which is represented by earnings management (EM) practices. The research problem is demonstrated by the failure of some Iraqi banks and their subsequent placement under the supervision of the Central Bank of Iraq, which was attributed, in part, to the inadequacy of the agency model in protecting stakeholders in shareholding institutions, as well as EM, pushed professional institutions to adopt the corporate governance model as a method to regulate the problem of accounting information asymmetry between the parties to the agency. We are using the Beneish M-score model and the financial analysis equations in

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