Browsing by Author "Khan, Shahidul Islam"

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    Development of national health data warehouse framework for Bangladesh
    (International Islamic University Chittagong, 2022-07) Khan, Shahidul Islam
    Data Warehouse (DW) integrates data from two or more sources into a repository for reporting, analysis, and knowledge discovery. This technology can be used in healthcare to develop National Health Data Warehouse (NHDW) that combines patient information from clinics, hospitals, laboratories, diagnostic centers, etc. In this research, we propose a framework for NHDW based on studying different global frameworks and conducting surveys among the potential stakeholders of the framework. Here, patient data will be collected in two phases: physical data collection and data collection over the internet. We did surveys on different healthcare organizations among patients, medical staff, and doctors. The survey questionnaire was divided into four sections: personal information, information privacy and security, performance, and usability to know the requirement of the stakeholders. As healthcare data is very sensitive and can be misused, providing privacy for these patients' information is properly addressed in this framework. The NHDW framework may significantly improve our healthcare services in Bangladesh.
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    Face and Hand Gesture Recognition Based Person Identification System using Convolutional Neural Network
    (International Journal of Intelligent Systems and Applications in Engineering, 2022-02-07) Kabisha, Mysha Sarin; Rahim, Kazi Anisa; Khaliluzzaman, Md.; Khan, Shahidul Islam
    Person identification system is now become the most hyped system for security purpose. It’s also gaining a lot of attention in the field of computer vision. For verification of human, facial recognition and hand gesture recognition are the most common topics of research. In the current days, various researchers focused on facial and hand gesture recognition using various shallow techniques and Deep Convolutional Neural Network (DCNN). However, using one feature of human for person identification is the most researched topic till now. In this paper, we proposed a Convolutional Neural Network (CNN) based system which will identify a person using two traits i.e., face and hand gesture of number sign of that person. For feature extraction and recognition Neural Network have shown immense good result. This proposed system works on two models, one is a VGG16 architecture model for face recognition and another model is for hand gesture which is based on simple CNN with two convolutional layers. With two customized dataset our face model gained 98.00% accuracy and hand gesture (number sign) model gained an accuracy of 98.33%.