Browsing by Author "Islam, Shahedul"

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    Al Muslim group overview of five major departments
    (BRAC University, 2025-11) Islam, Shahedul; Aziz, Syeda Salina
    The summary is the reflection of my Industrial Training at Al Muslim Group. I have been working here as an Assistant Merchandiser for the last two years. I was working on my industrial training for the last three months and I acknowledged everything in detail. I got an opportunity to practice and experience my learnings and skills in an efficient way by implementing the knowledge which I have been learning over the last 9 months at PGD-KIM, Brac University. This PGD-KIM course is the projection of the development of the knitwear industry by BKMEA in association with SICIP. Knitwear has a large contribution to the RMG industry for the improvement of our country. Bangladesh has a great impact and also opportunities in this industry. This course made my knowledge vaster about the knitwear industry. So, the projection of this report is practical knowledge and experience in the knitwear industry. I have made the report with detailed and efficient information. This experience is a great help for my future career. This report is on achieving practical knowledge and experience which will help me in my future career. And I have prepared this report with all the necessary information and data and related steps of industrial training.
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    An Expert System to Detect Polycystic Ovary Syndrome under Uncertainty
    (Journal of Pharmacy and Biological Sciences (IOSR-JPBS), 2016-08) Khaliluzzaman, Md.; Islam, Shahedul; Karim, Rezaul
    This paper describes a prototype of clinical expert system for risk stratification of patients with polycystic ovary syndrome (PCOS). Polycystic ovary syndrome (PCOS) is the most common hormonal disorder among women of reproductive age. It is a heterogeneous disorder of uncertain causes. Since the symptoms of PCOS are seemingly unrelated to one another the condition is often overlooked and undiagnosed. The determination of accurate degree or intensity of PCOS signs is difficult for the physician. Hence, the accuracy of diagnostic process is difficult to achieve. The signs and symptoms of PCOS are usually expressed in qualitative and quantitative ways. Since the qualitative factors can not measured in a quantitative way, various types of uncertainties may occurs such as incompleteness, vagueness, and imprecision. For that, it is necessary to address the issue of uncertainty by using appropriate methodology. However, no existing system is able to address this issue of uncertainty. Therefore, this paper demonstrates the application of a novel method, named belief rule-based inference methodology -RIMER; this prototype can deal with uncertainties in both clinical domain knowledge and clinical data. This paper reports the development of a Belief Rule Based Expert System (BRBES) using RIMER approach, which is capable of detect the PCOS by taking account of signs and symptoms.