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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
Fri Jun 16 2023
Journal Name
Acta Scientiarum Polonorum Administratio Locorum
An analysis of Baghdad’s masterplans based on the development of green areas
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Motives: Baghdad is the capital city and an important political, administrative, social, cultural and economic centre of Iraq. Baghdad’s growth and development has been significantly influenced by efforts to accommodate various needs of its steadily growing population. Uncontrolled population and urban growth have exerted negative effects in numerous dimensions, including environmental sustainability because urban expansion occurred in green spaces within the city and the surrounding areas.Aim: The aim of this study was to examine the planning solutions in Baghdad’s green areas in the past and at present, and to identify the key changes in the city’s green areas, including changes in the ratio of green urban spaces to the tota

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Publication Date
Mon Sep 12 2022
Journal Name
Biomedicine
An assessment of serum interleukin - 39 in rheumatoid arthritis patients from Iraq
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Introduction and Aim: The pro-inflammatory cytokine IL-39, a member of the IL-12 family plays a key role in the inflammatory response by modulating immune cell activity and inflammation. A literature search shows no study undertaken for the effect of IL-39's on arthritis so far. Hence, the purpose of this study was to investigate the role of IL-39 in rheumatoid arthritis. Materials and Methods: This study involved 80 patients with rheumatoid arthritis registered at the Rheumatology Clinic at Baghdad teaching hospital. The patients were divided into three groups based on treatments received. Group 1 included patients who were not on any treatment for arthritis, Group 2 with patients on hydroxychloroquine and or prednisone treatment,

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of The Mechanical Behavior Of Materials
Evaluation of a fire safety risk prediction model for an existing building
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Abstract<p>Fire is one of the most critical risks devastating to human life and property. Therefore, humans make different efforts to deal with fire hazards. Many techniques have been developed to assess fire safety risks. One of these methods is to predict the outbreak of a fire in buildings, and although it is hard to predict when a fire will start, it is critical to do so to safeguard human life and property. This research deals with evaluating the safety risks of the existing building in the city of Samawah/Iraq and determining the appropriateness of these buildings in terms of safety from fire hazards. Twelve parameters are certified based on the National Fire Protection Association (NFPA20</p> ... Show More
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Publication Date
Sat Jul 01 2023
Journal Name
International Journal Of Intelligent Engineering And Systems
An Efficient Cryptosystem for Image Using 1D and 2D Logistic Chaotic Maps
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Publication Date
Sat Jan 01 2022
Journal Name
Computers, Materials &amp; Continua
An Optimal Method for Supply Chain Logistics Management Based on Neural Network
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Publication Date
Thu Aug 31 2023
Journal Name
Journal Européen Des Systèmes Automatisés​
An IoT and Machine Learning-Based Predictive Maintenance System for Electrical Motors
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The rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com

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Publication Date
Tue Feb 01 2022
Journal Name
Baghdad Science Journal
An Efficient Algorithm for Fuzzy Linear Fractional Programming Problems via Ranking Function
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In many applications such as production, planning, the decision maker is important in optimizing an objective function that has fuzzy ratio two functions which can be handed using fuzzy fractional programming problem technique. A special class of optimization technique named fuzzy fractional programming problem is considered in this work when the coefficients of objective function are fuzzy. New ranking function is proposed and used to convert the data of the fuzzy fractional programming problem from fuzzy number to crisp number so that the shortcoming when treating the original fuzzy problem can be avoided. Here a novel ranking function approach of ordinary fuzzy numbers is adopted for ranking of triangular fuzzy numbers with simpler an

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Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Engineering
An Investigation to the Abrasive Wear in Pipes Used for Oil Industry
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The work reported in this study focusing on the abrasive wear behavior for three types of pipes used in oil industries (Carbone steel, Alloy steel and Stainless steel) using a wear apparatus for dry and wet tests, manufactured according to ASTM G65. Silica sand with
hardness (1000-1100) HV was used as abrasive material. The abrasive wear of these pipes has been measured experimentally by measuring the wear rate for each case under different sliding speeds, applied loads, and sand conditions (dry or wet). All tests have been conducted using sand of particle size (200-425) µm, ambient temperature of 34.5 °C and humidity 22% (Lab conditions).
The results show that the material loss due to abrasive wear increased monotonically with

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Publication Date
Thu Apr 27 2023
Journal Name
Al-rafidain Journal Of Medical Sciences ( Issn: 2789-3219 )
Anticancer Activities of Some Heterocyclic Compounds Containing an Oxygen Atom: A Review
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The purpose of this study is to underline the progression and development of research regarding oxygen-containing heterocycles as well as the contribution that some oxygen-containing heterocycles have made as anticancer medicines. A series of publications about the antitumor effects of derivatives of heterocyclic compounds containing an oxygen atom, such as furan, benzofuran, oxazole, benzoxazole, and oxadiazole, were evaluated, and their anticancer activities showed encouraging results when compared to those of established standard treatments.

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Publication Date
Thu Apr 20 2023
Journal Name
Fire
An Efficient Wildfire Detection System for AI-Embedded Applications Using Satellite Imagery
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Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

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