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Kernel estimation of returns of retirement funds of employers based on monetary earnings (subscriptions and compensation) via regression discontinuity in Iraq
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Regression Discontinuity (RD) means a study that exposes a definite group to the effect of a treatment. The uniqueness of this design lies in classifying the study population into two groups based on a specific threshold limit or regression point, and this point is determined in advance according to the terms of the study and its requirements. Thus , thinking was focused on finding a solution to the issue of workers retirement and trying to propose a scenario to attract the idea of granting an end-of-service reward to fill the gap ( discontinuity point) if it had not been granted. The regression discontinuity method has been used to study and to estimate the effect of the end -service reward on the cutoff of insured workers as well as the increase in revenues resulting from that. The research has showed that this reward has a clear effect on increasing revenues due to the regularity of workers in their work and their work continuity . It has also found that using Local Linear Smother (LLS) by using three models of bandwidth selection. Its results after the analysis in the Regression program have been as follows: The CCT (Calonico, Cattaneo & Titiunik) beamwidth gives the best performance followed by the local linear regression using the LK (Lembens and kalyanman) beamwidth. The real data has been used in sample size 71 represented in compensation as a variable of effectiveness (illustrative) X and the revenue as a result or an approved variable Y, while the results of the traditional OLS estimation method have not been good enough.

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Publication Date
Tue Jan 10 2017
Journal Name
International Journal Of Dynamics And Control
On local approximation-based adaptive control with applications to robotic manipulators and biped robots
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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Breast Cancer MRI Classification Based on Fractional Entropy Image Enhancement and Deep Feature Extraction
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Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
Digital Data Encryption Using a Proposed W-Method Based on AES and DES Algorithms
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This paper proposes a new encryption method. It combines two cipher algorithms, i.e., DES and AES, to generate hybrid keys. This combination strengthens the proposed W-method by generating high randomized keys. Two points can represent the reliability of any encryption technique. Firstly, is the key generation; therefore, our approach merges 64 bits of DES with 64 bits of AES to produce 128 bits as a root key for all remaining keys that are 15. This complexity increases the level of the ciphering process. Moreover, it shifts the operation one bit only to the right. Secondly is the nature of the encryption process. It includes two keys and mixes one round of DES with one round of AES to reduce the performance time. The W-method deals with

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Publication Date
Thu Jun 01 2023
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Image encryption based on combined between linear feedback shift registers and 3D chaotic maps
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Protecting information sent through insecure internet channels is a significant challenge facing researchers. In this paper, we present a novel method for image data encryption that combines chaotic maps with linear feedback shift registers in two stages. In the first stage, the image is divided into two parts. Then, the locations of the pixels of each part are redistributed through the random numbers key, which is generated using linear feedback shift registers. The second stage includes segmenting the image into the three primary colors red, green, and blue (RGB); then, the data for each color is encrypted through one of three keys that are generated using three-dimensional chaotic maps. Many statistical tests (entropy, peak signa

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Publication Date
Thu Feb 09 2023
Journal Name
Artificial Intelligence Review
Community detection model for dynamic networks based on hidden Markov model and evolutionary algorithm
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Finding communities of connected individuals in complex networks is challenging, yet crucial for understanding different real-world societies and their interactions. Recently attention has turned to discover the dynamics of such communities. However, detecting accurate community structures that evolve over time adds additional challenges. Almost all the state-of-the-art algorithms are designed based on seemingly the same principle while treating the problem as a coupled optimization model to simultaneously identify community structures and their evolution over time. Unlike all these studies, the current work aims to individually consider this three measures, i.e. intra-community score, inter-community score, and evolution of community over

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Publication Date
Thu Oct 30 2025
Journal Name
Iraqi Journal Of Science
Postmortem Panoramic Dental Radiography: Human Identification Based on Convolution Neural Network and Contourlet Transform
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Human identification is crucial in forensics for the investigation of large-scale disasters such as fires, epidemics, earthquakes, and tsunamis. Even though biometric identification using panoramic dental radiography (PDR) has been the subject of several studies in the literature, further study remains a necessary and challenging issue. In this research, a human identification system was developed based on a convolutional neural network (CNN) and contour transform (CT). The proposed system was implemented on a total of 1540 PDR from 302 individuals. The preprocessing applied to PDRs for enhancing and taking the Region of Interest (ROI). The features were extracted using CT transform. These features were fused with features extracted

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Publication Date
Fri Oct 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Renewable energy between limited use and treatment of the electricity crisis in Iraq
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The electric energy is one of the most important renewable energies used in the world as it is the main source for sustainable development and economic development through its use in (production, transport and distribution), and in Iraq, the electric power sector has suffered from many problems and obstacles, as providing electric current is one of the most prominent difficulties and challenges That successive governments and residents have faced since the early nineties of the last century and are still ongoing, and that Iraq has all the climatic conditions for developing the work of the electricity system from renewable energies such as solar and hydroelectric energy, as well as gas fields that have become a Basic pillar of pow

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Publication Date
Wed Dec 19 2018
Journal Name
Indian Journal Of Natural Sciences
Genotyping of Cryptosporidium Spp. Isolated from Human and Cattle in Baghdad Province, Iraq
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Cryptosporidiosis is an intestinal protozoan parasitic disease that infects human and animals, caused by apicomplexan parasite belong to the genusof Cryptosporidium. The current study was done to record the infection rate of cryptosporidiosis in human and cattle, and genotype the clinical isolates of Cryptosporidium in Baghdad Province. A total of 265 stool sample were collected (150 from human and 115 from cattle) during the period from December 2016 to the May 2017. Cryptosporidial infection was detected using modified acid fast stain. DNA of the parasite was extracted from oocysts of positive fecal samples and nested PCR method was used for partial 60 kDa glycoprotein (gp60) gene amplification then sequence analysis for selected samples.

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Publication Date
Sun Oct 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
THE MACROECONOMIC ENVIRANMENT OF THE FOOD INDUSTRY IN IRAQ AND ITS FUTURE PROSPECTS
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Food industries are variety to include number of agricultural products (plantbotential and animal) which can be manufactured locally, thus, Iraqi market is full by different types of food products from neighbor countries, because of un equivalence and inability of competence, in away to cover (90%) average of local request need under commercial  opening.

In Iraq although its importance, this industry suffers from difficulties, the most important one is the rising  in  products costs, shortage in agricultural products, experience, and qualification, besides, the challenges , by flooding market in food products and what are contained of higher competitive features from quality and prices side

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Publication Date
Fri Jul 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Causality Analysis of the Nexus between Higher Education and Income Distribution in Iraq
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Abstract:

The achievement of economic and social welfare for individual is the main target to all policies that adopted by all countries worldwide either were economic, social, political or others. The obtaining of education by individuals and especially the higher education is one of the most important determinates in achieving the wellbeing and lasted economic development. This is because via the higher education new fields can be opened in front of individuals in order to get adequate jobs associated with their scientific specialization. This is allowing educated individuals gain higher income that can reduce the gap of income inequality.

Thus, this paper aims to analysis the n

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