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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
Tue Jan 01 2013
Journal Name
Iraqi Journal Of Science
Effect of LPS Extracted from Campylobacter coli on Lymphocyte Transformation
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Publication Date
Tue Jan 30 2024
Journal Name
Iraqi Journal Of Science
Parallel Particle Swarm Optimization Algorithm for Identifying Complex Communities in Biological Networks
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    Identification of complex communities in biological networks is a critical and ongoing challenge since lots of network-related problems correspond to the subgraph isomorphism problem known in the literature as NP-hard. Several optimization algorithms have been dedicated and applied to solve this problem. The main challenge regarding the application of optimization algorithms, specifically to handle large-scale complex networks, is their relatively long execution time. Thus, this paper proposes a parallel extension of the PSO algorithm to detect communities in complex biological networks. The main contribution of this study is summarized in three- fold; Firstly, a modified PSO algorithm with a local search operator is proposed

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Publication Date
Tue Jan 30 2024
Journal Name
Iraqi Journal Of Science
Parallel Particle Swarm Optimization Algorithm for Identifying Complex Communities in Biological Networks
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    Identification of complex communities in biological networks is a critical and ongoing challenge since lots of network-related problems correspond to the subgraph isomorphism problem known in the literature as NP-hard. Several optimization algorithms have been dedicated and applied to solve this problem. The main challenge regarding the application of optimization algorithms, specifically to handle large-scale complex networks, is their relatively long execution time. Thus, this paper proposes a parallel extension of the PSO algorithm to detect communities in complex biological networks. The main contribution of this study is summarized in three- fold; Firstly, a modified PSO algorithm with a local search operator is proposed to d

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Publication Date
Tue Jan 01 2019
Journal Name
البحوث التربوية والنفسية
An educational design based on the models of the constructivist theory of chemistry and its impact on the life skills of second-year middle school female students
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Publication Date
Sat Dec 30 2023
Journal Name
Iraqi Journal Of Science
A Review for Arabic Sentiment Analysis Using Deep Learning
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     Sentiment Analysis is a research field that studies human opinion, sentiment, evaluation, and emotions towards entities such as products, services, organizations, events, topics, and their attributes. It is also a task of natural language processing. However, sentiment analysis research has mainly been carried out for the English language. Although the Arabic language is one of the most used languages on the Internet, only a few studies have focused on Arabic language sentiment analysis.

     In this paper, a review of the most important research works in the field of Arabic text sentiment analysis using deep learning algorithms is presented. This review illustrates the main steps used in these studies, which include

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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of the method of partial least squares and the algorithm of singular values decomposion to estimate the parameters of the logistic regression model in the case of the problem of linear multiplicity by using the simulation
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The logistic regression model is an important statistical model showing the relationship between the binary variable and the explanatory variables.                                                        The large number of explanations that are usually used to illustrate the response led to the emergence of the problem of linear multiplicity between the explanatory variables that make estimating the parameters of the model not accurate.    

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Publication Date
Mon Aug 26 2019
Journal Name
Iraqi Journal Of Science
Exact Methods for Solving Multi-Objective Problem on Single Machine Scheduling
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     In this paper, one of the Machine Scheduling Problems is studied, which is the problem of scheduling a number of products (n-jobs) on one (single) machine with the multi-criteria objective function. These functions are (completion time, the tardiness, the earliness, and the late work) which formulated as . The branch and bound (BAB) method are used as the main method for solving the problem, where four upper bounds and one lower bound are proposed and a number of dominance rules are considered to reduce the number of branches in the search tree. The genetic algorithm (GA) and the particle swarm optimization (PSO) are used to obtain two of the upper bounds. The computational results are calculated by coding (progr

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Publication Date
Tue Sep 25 2018
Journal Name
Iraqi Journal Of Science
Age Estimation Using Support Vector Machine
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Recently there has been an urgent need to identify the ages from their personal pictures and to be used in the field of security of personal and biometric, interaction between human and computer, security of information, law enforcement. However, in spite of advances in age estimation, it stills a difficult problem. This is because the face old age process is determined not only by radical factors, e.g. genetic factors, but also by external factors, e.g. lifestyle, expression, and environment. This paper utilized machine learning technique to intelligent age estimation from facial images using support vector machine (SVM) on FG_NET dataset. The proposed work consists of three phases: the first phase is image preprocessing include four st

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Publication Date
Fri Oct 28 2022
Journal Name
Political Sciences Journal
The protest movements in Sudan and their role in the political and social transformation
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This study investigates the factors that led to the outbreak of protest movements in Sudan, since Sudan’s independence in 1956 until December 2018. The study aims to identify the role of protests in bringing about political and social transformations in Sudan, besides identifying the factors that help in the success or failure of the governments that resulted from those protests, with special emphasis on the challenges of the government of the 2018 revolution. The main results of the study reveal that the December 2018 protests are the largest in term of numbers, and witness huge participation of youth and women, and the slogans raised were national and comprehensive. However, the challenges that the transitional government is going th

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Publication Date
Mon Dec 11 2006
Journal Name
Iraqi Journal Of Laser
In vivo N2 Laser Effect on Lymphocyte Transformation Capacity and Phagocytosis Activity in Mice
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The objective of this in vivo study is to investigate the effects of 337.1 nm pulsed N2 laser on cellular immune response represented by lymphocyte transformation capacity and phagocytosis activity in laboratory animals. The samples include 60 adult male BALB/c mice, were divided into control group and experimental groups. The experimental groups were divided into two main groups according to the time period after N2 laser irradiation. Each group was divided into 9 subgroups which exposed to N2 laser radiation at different values of pulse repetition rates and exposure times. The results of immunological tests demonstrated that the exposure to 180 J/cm2 of N2 laser radiation induce adverse effect to cellular immune response. The results o

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