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Recurrent Stroke Prediction using Machine Learning Algorithms with Clinical Public Datasets: An Empirical Performance Evaluation
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Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning algorithms implementation in the recurrent stroke prediction models. This research aims to investigate and compare the performance of machine learning algorithms using recurrent stroke clinical public datasets. In this study, Artificial Neural Network (ANN), Support Vector Machine (SVM) and Bayesian Rule List (BRL) are used and compared their performance in the domain of recurrent stroke prediction model. The result of the empirical experiments shows that ANN scores the highest accuracy at 80.00%, follows by BRL with 75.91% and SVM with 60.45%.

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Publication Date
Tue Oct 08 2002
Journal Name
Iraqi Journal Of Laser
Laser Detection and Tracking System Using an Array of Photodiodes with Fuzzy Logic controller
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In this work laser detection and tracking system (LDTS) is designed and implemented using a fuzzy logic controller (FLC). A 5 mW He-Ne laser system and an array of nine PN photodiodes are used in the detection system. The FLC is simulated using MATLAB package and the result is stored in a lock up table to use it in the real time operation of the system. The results give a good system response in the target detection and tracking in the real time operation.

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Publication Date
Thu Nov 06 2025
Journal Name
Al–bahith Al–a'alami
PUBLIC RELATIONS AN ATTEMPT TO BUILD A DEFINITION
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This research deals with the most famous existing definitions of public relations, in an attempt to achieve a definition that will be added to the other existing and widespread definitions, especially that big developments have taken place in the concept of public relations and their idiomatic use.

In addition, many definitions of public relations have been restricted to some limited descriptions, therefore many of the descriptions given to the public relations are basically definitions as well as characteristics of the public relations.

This research aims at setting and formulating the definitions of public relations, it also deals with its credibility in achieving its significance in order to reach a new definition that

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Publication Date
Tue Mar 01 2022
Journal Name
Asian Journal Of Applied Sciences
Comparison between Expert Systems, Machine Learning, and Big Data: An Overview
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Today, the science of artificial intelligence has become one of the most important sciences in creating intelligent computer programs that simulate the human mind. The goal of artificial intelligence in the medical field is to assist doctors and health care workers in diagnosing diseases and clinical treatment, reducing the rate of medical error, and saving lives of citizens. The main and widely used technologies are expert systems, machine learning and big data. In the article, a brief overview of the three mentioned techniques will be provided to make it easier for readers to understand these techniques and their importance.

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Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Computer, Communication, Control And System Engineering
A Framework for Predicting Airfare Prices Using Machine Learning
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Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci

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Publication Date
Thu Sep 01 2022
Journal Name
Iraqi Journal Of Computers, Communications, Control And Systems Engineering
A Framework for Predicting Airfare Prices Using Machine Learning
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Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre

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Publication Date
Mon Dec 05 2022
Journal Name
Baghdad Science Journal
An Evaluation of the Activity of Prepared Zinc Nanoparticles with Extracted Alfalfa Plant in the Treatment of Heavy Metals
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The alfalfa plant, after harvesting, was washed, dried, and grinded to get fine powder used in water treatment. We used the alfalfa plant with ethanol to make the alcoholic extract characterized by using (GC-Mass, FTIR, and UV) spectroscopy to determine active compounds. Alcoholic extract was used to prepare zinc nanoparticles. We characterized Zinc nanoparticles using (FTIR, UV, SEM, EDX Zeta potential, XRD, AFM). Zinc nanoparticle with Alfalfa extract and alfalfa powder were used in the treatment of water polluted with inorganic elements such as Cr, Mn, Fe, Cu, Cd, Ag by (Batch processing). The batch process with using alfalfa powder gets treated with Pb (51.45%), which is the highest percentage of treatment. Mn (13.18%), which is the

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Publication Date
Wed Jun 01 2022
Journal Name
Baghdad Science Journal
Constructing a Software Tool for Detecting Face Mask-wearing by Machine Learning
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       In the pandemic era of COVID19, software engineering and artificial intelligence tools played a major role in monitoring, managing, and predicting the spread of the virus. According to reports released by the World Health Organization, all attempts to prevent any form of infection are highly recommended among people. One side of avoiding infection is requiring people to wear face masks. The problem is that some people do not incline to wear a face mask, and guiding them manually by police is not easy especially in a large or public area to avoid this infection. The purpose of this paper is to construct a software tool called Face Mask Detection (FMD) to detect any face that does not wear a mask in a specific

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Publication Date
Sat Jun 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
(Dynamic& Static) Forecast of surplus or Deficit of Public budget in Iraq for (2017،2018)
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 This research aims at forecasting the public budget of Iraq (surplus or deficit) for 2017 & 2018 through using two methods to forecast. First: forecast budget surplus or deficit by using IMF estimations average oil price per barrel adopted in the public federal budget amounted to USD 44 in 2017 & USD 46 in 2018; Second: forecast budget surplus or deficit by using MOO actual average oil price in global markets amounted to USD 66 in 2018 through applying Dynamic Model & Static Model. Then analyze the models to reach the best one. The research concluded that those estimations of dynamic forecasting model of budget surplus or deficit for 2017 & 2018 gives good reliable results for future periods when using the a

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Publication Date
Tue Mar 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
Performance evaluation criteria"Applied Study in the General Company for the manufacture of glass and ceramics"
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Contemporary management is interested in the process of performance assessment  because of its significance in the field of planning and controlling the multiactiveties to attain its goals and uncovering digression of virtual performance after comparing it with the plan or equitable performance.

Digression is analyzed to enable management control centers of authority.

Assessment process significance is closely related by setting definite categories to evaluate the economic activity to know the ability to achieves aims.

This study concentrated on the most important categories that used to evaluate  company understudy with ather categories suggested to complete assessment process.

This study is in

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Publication Date
Thu Nov 06 2025
Journal Name
Al–bahith Al–a'alami
Effectiveness of Dialogic Communication in Online Public Relations with an Audience : (Analytical Study of the Websites of Universities in UAE)
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The Study addressed the effectiveness of dialogic communication in online public relations with an audience of higher education institutions in the United Arab Emirates. The study aimed to know about the interest extent of higher education institutions through their websites with the elements of dialogic communication in online public relations to communicate with their audience. The researcher used survey methodology and content Analysis tool as an essential tool for collecting information. Some of the important results of the study are: The websites of higher education institutions in terms of indicators of ease of use; the main links on the websites are clearly available on the opening page, there is a map on the websites, reduce depe

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