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iqjmc-1713
Optimizing Linear Models via Sinusoidal Transformation for Boosted Machine Learning in Medicine: Sinusoidal Optimization of Linear Models
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Background: Machine learning relies on a hybrid of analytics, including regression analyses. There have been no attempts to deploy a sinusoidal transformation of data to enhance linear regression models.
Objectives:
We aim to optimize linear models by implementing sinusoidal transformation to minimize the sum of squared error.
Methods:
We implemented non-Bayesian statistics using SPSS and MatLab. We used Excel to generate 30 trials of linear regression models, and each has 1,000 observations. We utilized SPSS linear regression, Wilcoxon signed-rank test, and Cronbach’s alpha statistics to evaluate the performance of the optimization model. Results: The sinusoidal transformation succeeded by significantly reducing the sum of squared errors (P-value<0.001). Inter-item reliability testing confirmed the robust internal consistency of the model (Cronbach’s alpha=0.999). Conclusion: Our optimization model is valuable for high-impact research based on linear regression. It can reduce the computational processing demands for powerful real-time and predictive analytics of big data.

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Publication Date
Mon May 15 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Developing a Real Time Method for the Arabic Heterogonous DBMS Transformation
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   A common problem facing many Application models is to extract and combine information from multiple, heterogeneous sources and to derive information of a new quality or abstraction level. New approaches for managing consistency, uncertainty or quality of Arabic data and enabling e-client analysis of distributed, heterogeneous sources are still required. This paper presents a new method by combining two algorithms (the partitioning and Grouping) that will be used to transform information in a real time heterogeneous Arabic database environment

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Publication Date
Fri May 15 2009
Journal Name
Journal Of Planner And Development
Preservation of heritage markets within an integrated framework to preserve the urban heritage in the historical centers of cities (selected models and experiments)
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This research discusses the rehabilitation of heritage markets in the historical centers of Islamic Arab cities and their use in the field of cultural tourism as one of the most important tourist attractions and the subsequent revival of the national economy in addition to preserving the urban heritage as these markets part of the historical centers of cities. The research also discusses the preservation of the continuity of heritage markets as a product of cultural heritage value within an integrated framework to preserve the urban heritage in the historic centers of cities. The study then reviews a number of experiences of Arab and Islamic countries in the field of preserving and rehabilitating heritage markets, which qualify them to b

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Publication Date
Mon Nov 01 2021
Journal Name
International Journal Of Hydrogen Energy
Experimental study on combustion stability and performance of hydrogen-enriched compressed natural gas of a free-piston linear generator
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Publication Date
Sat Apr 30 2022
Journal Name
Revue D'intelligence Artificielle
Performance Evaluation of SDN DDoS Attack Detection and Mitigation Based Random Forest and K-Nearest Neighbors Machine Learning Algorithms
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

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Publication Date
Sun Nov 01 2009
Journal Name
Tencon 2009 - 2009 Ieee Region 10 Conference
Optimizing the MPLS support for real time IPv6-Flows using MPLS-PHS approach
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Publication Date
Sat Dec 30 2023
Journal Name
Traitement Du Signal
Optimizing Acoustic Feature Selection for Estimating Speaker Traits: A Novel Threshold-Based Approach
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Publication Date
Sun Dec 01 2019
Journal Name
Academic Medicine
Academic medicine and science diplomacy: medical education in Iraq
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Physicians are infrequently selected to serve in the yearlong role of Jefferson Science Fellow (JSF) as senior science advisor for the US Department of State or the United States Agency for International Development. The authors discuss the role of a JSF in promoting “science diplomacy” from the perspective of one alumnus, who sites examples of ongoing, long-term collaborative projects including one focusing on medical education reform in Iraq that would not have been possible without the JSF program. More than 3 decades of political and social unrest, terrorism, the internal displacement of millions of Iraqi citizens, the arrival of Syrian refugees, international sanctions, and the effect of fluctuating oil prices that fund education i

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Publication Date
Tue Apr 26 2011
Journal Name
Evolutionary Algorithms
Variants of Hybrid Genetic Algorithms for Optimizing Likelihood ARMA Model Function and Many of Problems
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Publication Date
Thu Dec 23 2021
Journal Name
Iraqi Journal Of Science
Optimizing the Radius of Curvature of Black Silicon Peaks for Solar Cell Using Matlab Simulations
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    As part of our research on efficiency improvement of PERC (Passivated Emitter Rear Solar Cell), achieving very low reflectivity values of solar cell surface is a must. One of the most advance technologies to do so is the use of advanced texturing for the front surface of the cells. This texture, also known as Black Silicon, consists of peaks and valleys of nano metric dimensions and capable of dramatically reducing the reflectance of the front surface. A reflectance around 5%  was reached ,using simulation, when using a Black-Silicon texturing with height of 50nm with peak rounding of 5nm. Even though this texturing may affect other parameters such as series resistance or surface recombination, as a starting point

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Publication Date
Mon Jul 05 2010
Journal Name
Evolutionary Algorithms
Variants of Hybrid Genetic Algorithms for Optimizing Likelihood ARMA Model Function and Many of Problems
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Optimization is essentially the art, science and mathematics of choosing the best among a given set of finite or infinite alternatives. Though currently optimization is an interdisciplinary subject cutting through the boundaries of mathematics, economics, engineering, natural sciences, and many other fields of human Endeavour it had its root in antiquity. In modern day language the problem mathematically is as follows - Among all closed curves of a given length find the one that closes maximum area. This is called the Isoperimetric problem. This problem is now mentioned in a regular fashion in any course in the Calculus of Variations. However, most problems of antiquity came from geometry and since there were no general methods to solve suc

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