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Intelligence framework dust forecasting using regression algorithms models
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<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, comes in second place with a gross ratio of 91%. Furthermore, Bayesian ridge (BR), linear regressor (LR), and stochastic gradient descent (SGD), with mean square error and with accuracy ratios of 84.365%, 84.363%, and 79%. As a result, the performance precision of these regression models yields. The interaction framework was designed to be a straightforward tool for working with this paradigm. This model is a valuable tool for establishing strategies to counter the swiftness of climate change in the area under study.</span>

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Publication Date
Thu Mar 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
Nadaraya-Watson Estimator a Smoothing Technique for Estimating Regression Function
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    The using of the parametric models and the subsequent estimation methods require the presence of many of the primary conditions to be met by those models to represent the population under study adequately, these prompting researchers to search for more flexible models of parametric models and these models were nonparametric models.

    In this manuscript were compared to the so-called Nadaraya-Watson estimator in two cases (use of fixed bandwidth and variable) through simulation with different models and samples sizes.  Through simulation experiments and the results showed that for the first and second models preferred NW with fixed bandwidth fo

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Publication Date
Fri Sep 18 2020
Journal Name
Hal Open Science
Adaptive Approximation Control of Robotic Manipulators: Centralized and Decentralized Control Algorithms
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The regressor-based adaptive control is useful for controlling robotic systems with uncertain parameters but with known structure of robot dynamics. Unmodeled dynamics could lead to instability problems unless modification of control law is used. In addition, exact calculation of regressor for robots with more than 6 degrees of freedom is hard to be calculated, and the task could be more complex for robots. Whereas the adaptive approximation control is a powerful tool for controlling robotic systems with unmodeled dynamics. The local (partitioned) approximation-based adaptive control includes representation of the uncertain matrices and vectors in the robot model as finite combinations of basis functions. Update laws for the weighting matri

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Publication Date
Fri Aug 01 2014
Journal Name
International Journal Of Engineering And Innovative Technology (ijeit)
New Predictive Block Matching Searching Algorithms and Hybrid Predictive Search System
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In this paper, two new simple, fast and efficient block matching algorithms are introduced, both methods begins blocks matching process from the image center block and moves across the blocks toward image boundaries. With each block, its motion vector is initialized using linear prediction that depending on the motion vectors of its neighbor blocks that are already scanned and their motion vectors are assessed. Also, a hybrid mechanism is introduced, it depends on mixing the proposed two predictive mechanisms with Exhaustive Search (ES) mechanism in order to gain matching accuracy near or similar to ES but with Search Time ST less than 80% of the ES. Also, it offers more control capability to reduce the search errors. The experimental tests

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Publication Date
Wed Jun 27 2018
Journal Name
Wireless Communications And Mobile Computing
Developing a Video Buffer Framework for Video Streaming in Cellular Networks
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This work proposes a new video buffer framework (VBF) to acquire a favorable quality of experience (QoE) for video streaming in cellular networks. The proposed framework consists of three main parts: client selection algorithm, categorization method, and distribution mechanism. The client selection algorithm was named independent client selection algorithm (ICSA), which is proposed to select the best clients who have less interfering effects on video quality and recognize the clients’ urgency based on buffer occupancy level. In the categorization method, each frame in the video buffer is given a specific number for better estimation of the playout outage probability, so it can efficiently handle so many frames from different video

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Publication Date
Sat Aug 01 2015
Journal Name
Journal Of Economics And Administrative Sciences
A conceptual Framework For the Relationship between Human and Social Capital
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Purpose: The research seeks to develop the implications of intellectual human capital, and social capital in business organizations, and will be accomplished on three levels, the first level (the level of description) to identify, diagnose and display content philosophical Strategic Human Resource Management at the thought of modern administrative represented by human capital and Ras social capital. The second level (level of analysis) and the analysis of the extent of the impact of alignment between human capital, and social capital in the organizational strength of the organizations. The third level (Level predict) the formulation of a plan to strengthen the organizational strength in business organizations and to develop speci

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Publication Date
Fri Jan 01 2021
Journal Name
Journal Of Intelligent Systems
An online COVID-19 self-assessment framework supported by IoMT technology
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Abstract<p>As COVID-19 pandemic continued to propagate, millions of lives are currently at risk especially elderly, people with chronic conditions and pregnant women. Iraq is one of the countries affected by the COVID-19 pandemic. Currently, in Iraq, there is a need for a self-assessment tool to be available in hand for people with COVID-19 concerns. Such a tool would guide people, after an automated assessment, to the right decision such as seeking medical advice, self-isolate, or testing for COVID-19. This study proposes an online COVID-19 self-assessment tool supported by the internet of medical things (IoMT) technology as a means to fight this pandemic and mitigate the burden on our nation</p> ... Show More
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Publication Date
Thu Jan 31 2019
Journal Name
Journal Of The College Of Education For Women
Iraqi-US relations in the light of the strategic framework agreement
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The United States has stood by Iraq and supported militarily and morally, but the relationship did not quickly be strained again before August 1990, when the oldest former political system in Iraq after Iraqi troops entered the territory of Kuwait, the United States stood beside Kuwait because the two parties link military ties opted States United to support the Kuwaiti side relying on the resolutions passed by the UN security Council, the United States and found in this issue right opportunity to execute the mechanics of meddling in Iraqi affairs and the various means of political, economic, military, and methods for dealing with Iraq, especially after finding the impediment standing in front of the implementation of its goals The strat

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Publication Date
Mon Jul 05 2021
Journal Name
Revue Française D’allergologie
Indoor house dust-borne fungi and risk of allergic respiratory diseases in Baghdad city
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Publication Date
Wed Apr 01 2015
Journal Name
Journal Of Economics And Administrative Sciences
Multi-level model of the factors that affect the escalation of dust in Iraq
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In this research The study of Multi-level  model (partial pooling model) we consider The partial pooling model which is one Multi-level  models and one of  the Most important models and extensive use and application in the analysis of the data .This Model characterized by the fact that the treatments take hierarchical or structural Form, in this partial pooling models, Full Maximum likelihood FML was used to estimated parameters of partial pooling models (fixed and random ), comparison between the preference of these Models, The application was on the Suspended Dust data in Iraq, The data were for four and a half years .Eight stations were selected randomly  among the stations in Iraq. We use Akaik′s Informa

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Publication Date
Sun May 01 2022
Journal Name
Revue Française D'allergologie
Indoor house dust-borne fungi and risk of allergic respiratory diseases in Baghdad city
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