Amer Almahdawi

@uobaghdad.edu.iq

Amer Almahdawi

Amer Almahdawi


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6

Scopus Publications

Scopus Publications

  • Iraqi Stock Market Structure Analysis Based on Minimum Spanning Tree
    Baidaa Saleh Mahdi, Amer Almahdwi, Jalal Hattem
    Aip Conference Proceedings, 2023
    Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Twitter Facebook Reddit LinkedIn Tools Icon Tools Reprints and Permissions Cite Icon Cite Search Site Citation Baidaa Saleh Mahdi, Amer Almahdwi, Jalal Hattem; Iraqi stock market structure analysis based on minimum spanning tree. AIP Conf. Proc. 13 February 2023; 2414 (1): 040083. https://doi.org/10.1063/5.0114925 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAIP Publishing PortfolioAIP Conference Proceedings Search Advanced Search |Citation Search
  • Diabetes Prediction Using Machine Learning
    Amer Almahdawi, Zaid S. Naama, Ahmed Al-Taie
    3rd Information Technology to Enhance E Learning and Other Application IT Ela 2022, 2022
    Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five attributes of the training process. The results of the second experiment showed improvement in the performance of the KNN and the Multilayer Perceptron. The results of the second experiment showed a slight decrease in the performance of the Random Forest with 97.5% accuracy.
  • Minimum spanning tree application in Covid-19 network structure analysis in the countries of the Middle East
    Baidaa Saleh Mahdi, Jalal Hatem Hussein Al-Bayati, Amer J. Al-Mahdawi
    Journal of Discrete Mathematical Sciences and Cryptography, 2022
    Coronavirus disease (Covid-19) has threatened human life, so it has become necessary to study this disease from many aspects. This study aims to identify the nature of the effect of interdependence between these countries and the impact of each other on each other by designating these countries as heads for the proposed graph and measuring the distance between them using the ultrametric spanning tree. In this paper, a network of countries in the Middle East is described using the tools of graph theory.
  • A New Arabic Dataset for Emotion Recognition
    Amer J. Almahdawi, William J. Teahan
    Advances in Intelligent Systems and Computing, 2019
  • Automatically recognizing emotions in text using prediction by partial matching (PPM) text compression method
    Amer Almahdawi, William John Teahan
    Communications in Computer and Information Science, 2018
  • Emotion recognition in text using ppm
    Amer Almahdawi, William John Teahan
    Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2017