Browsing by Author "Islam, Sumaya"

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Human resource management plan failures and outcomes in Maxces Trims Limited with proposed solutions
(BRAC University, 2020-01) Islam, Sumaya; Ahsan, Feihan
This research summarizes the internship program experience at Maxces Trims Ltd. as a course of the BBA program. It describes all the learnings, outcomes, and experience of the internship program while working in the organization. There is an overview of general activities, the process of various departments and some brief about the collaborative nature and clients of the organization. The main objective is of the report to find out determine the shortcomings of HR Plans in Maxces Trims Ltd. and how they managed to overcome them with some proposed solutions. In the first phase, there is a description of their recruitment plans and issues they have faced during recruitment along with the details of their financial deficit back in the fiscal year of 2011-2012. Furthermore, a detail analysis of their lack of performance review and incentive programs have also been duly highlighted. In findings, there is an analysis the various shortcomings faced by Maxces Trims Ltd. over the years and their perspective towards overcoming these problems. Further, how the steps they have taken have affected them in the short run as well as how they are helping them at present. Overall, the Covid-19 pandemic has changed their views on their internal environment and recruitment plans which are paving the way for future developmental plans.
Image based bird detection and classification through deep learning
(Daffodil International University, 2024-01-25) Islam, Sumaya
Birds, as a diverse and integral component of our natural world, play a pivotal role in maintaining the balance and health of ecosystems. Their presence influences not only the environment but also various aspects of human life, making the accurate identification and understanding of birds crucial. Bird detection and classification from images is a challenging task with diverse applications, ranging from wildlife conservation and ecological studies to urban planning and agriculture. This research paper aims to explore the use of deep learning techniques for accurately detecting and classifying birds in images. Deep learning is used in many fields [1], like speech, image recognition, drug discovery and toxicology, customer management, recommendation systems, bioinformatics, NLP etc. In our paper delve into various state-of-the-art deep learning architectures, including EfficientNetB7, MobileNetV3, ResNet101. The research involves the preparation of a comprehensive dataset of bird images and evaluates the performance of different models based on various metrics, such as precision, recall, and F1-score. By enhancing our capacity to identify and comprehend birds, we strengthen our ability to protect and conserve the intricate web of life on our planet. Furthermore, we discussed the challenges encountered during the process and proposed potential avenues for future research to enhance bird detection capabilities in real-world scenarios.
Intensive nutrition education with or without supplementary feeding improves the nutritional status of moderately-malnourished children in Bangladesh
(2005-12) Roy, S.K.; Fuchs, G.J.; Mahmud, Zeba; Ara, Gulshan; Islam, Sumaya; Shafique, Sohana; Akter, Syeda Sharmin
Bangladesh Integrated Nutrition Project (BINP); World Bank (WB).