Now showing items 1-6 of 6

    • A Federated Learning Approach for Type-2 Diabetes Detection Using a Naive Bayes Classifier 

      Rahman, M. M.; Islam, Ashraful; Pasha, Syed Tangim; Islam, M. Usama; Alam, Md Zahangir (, The International Diabetes Federation (IDF), 2023, 2023-10)
      Federated learning (FL) is a new way of training machine learning models across decentralized devices without exchanging the raw data. This approach preserves privacy and promotes the development of more personalized models ...
    • Genre Classification of Bangla Poem Using Machine Learning and Deep Learning Techniques 

      Pasha, Syed Tangim; Islam, Ashraful; Rahman, Mohammed Masudur; Ahmed, Eshtiak; Foysal, Md. Ferdouse Ahmed; Alam, Md Zahangir (Independent University, Bangladesh, 2023-05)
      The computational analysis of the Bangla poems is a challenging task due to the diverse linguistic, stylistic, and semantic features of the Bangla language. In this work, we prepared a dataset of 1311 Bangla poems of two ...
    • Low-cost relay selection in multihop cooperative networks 

      Rahman, Suryaia; Alam, Md Zahangir; Islam, Ashraful; Habib, Md. Tarek; AHMED, ESHTIAK; Hasan, Mahady; Ahmed, Tarem (Journal of King Saud University - Computer and Information Sciences, Q1, 2023-09)
      A best relay selection algorithm for a cooperative multi-hop cross-layer single-input single-output (SISO) amplify-and-forward (AF) wireless relay network is analyzed in this work, with the application where exact channel ...
    • Multi-agent best routing in high mobility digital-twin-driven internet of vehicles 

      Alam, Md Zahangir; S. Khan, Komal; Jamalipour, Abbas (IEEE IoT Journal, Rank Q1, 2023-10)
      Low-delay high-gain optimal multi-hop routing path is crucial to guarantee both the latency and reliability require- ments for infotainment services in the high mobility internet of vehicles (IoVs) subject to queue stability. ...
    • SMOTE Oversampling and Near Miss Undersampling Based Diabetes Diagnosis from Imbalanced Dataset with XAI Visualization 

      Nayan, Nasim Mahmud; Islam, Ashraful; Islam, Muhammad Usama; Ahmed, Eshtiak; Hossain, Mohammad Mobarak; Alam, Md Zahangir (Independent University, Bangladesh, 2023-05)
      This study investigated the predictive ability of ten different machine learning (ML) models for diabetes using a dataset that was not evenly distributed. Additionally, the study evaluated the effectiveness of two oversampling ...
    • Using an Ensemble Machine Learning Model with Explainable AI (XAI) to Diagnose Gestational Diabetes Mellitus 

      Pasha, Syed Tangim; Islam, Ashraful; Sikder, Sanker; Habib, Md Tarek; Alam, Md Zahangir; Amin, M Ashraful (The International Diabetes Federation (IDF), 2023, 2023-10)
      The emergence of gestational diabetes mellitus (GDM) in pregnant women is a serious health concern and an alarming issue. According to the most recent data from the International Diabetes Federation (IDF), in 2021, 16.7 ...

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