Browsing by Author "Biswas, Sourav"

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Corruption plays an important role to economic growth in Bangladesh.
(Uttara University, 2020-08-30) Biswas, Sourav
This study investigates the relationship between corruption and economic growth in Bangladesh, highlighting the detrimental effects of corruption on national development. With Bangladesh consistently ranking among the most corrupt countries, as reported by the Global Corruption Perception Index 2019, this research aims to analyze the current status of corruption and its impact on economic growth. The findings will provide valuable insights for future researchers in Economics and Finance and raise awareness about the pervasive issue of corruption in various sectors. Ultimately, this study seeks to contribute to societal understanding and assist the government in formulating strategies to mitigate corruption, thereby fostering a healthier economic environment.
Impact of economic crisis on the financial performance of Blue Ocean Footwear Ltd.
(BRAC University, 2023-09) Biswas, Sourav; Mahi, Abu Saad Md. Masnun Al
This report examines the financial performance of Blue Ocean Footwear Ltd. and its impact on the economy during the Covid-19 pandemic, dollar crisis, de-dollarization, and Ukraine & Russia war. The company generated 7.68% profit from net sales in 2015 and increased by 0.59% to 8.27% in 2015. However, in 2016, the company faced losses, leading to a negative profit margin ratio. In 2017, the company recovered its loss to 6.99%, but from 2018 to 2021, the net profit margin fluctuated, indicating a lack of steady revenue growth and risk for shareholders. The decline in net profitability can be attributed to the Covid-19 pandemic and the dollar crisis due to the Russia and Ukraine war. The study found a negative relationship between the financial performance of Blue Ocean Footwear Ltd. and economic crisis situations, such as the dollar crisis or global impacts of the Russia and Ukraine war. The calculated value of F was 5.94, which is greater than the tabulated value of F at 4.74 with alpha 0.05. The study supports that there is a negative relationship between a company's financial performance and economic crisis situations, particularly in the fiscal years 2019-2020 and 2021-2022. The Covid-19 pandemic in 2029-2020 and the dollar crisis in 2021-2022 were significant economic crises, while the Ukraine & Russia war in 2022 further impacted the company's financial condition. The structural break in financial data indicates that the company's financial condition is not stable, and it is essential to conduct further research and analysis to better understand the company's financial situation.
Internship Report On “Student–Teacher Interaction and Its Impact on Learning: Insights from Nowapara Government Primary School”
(Daffodil International University, 2025-12-08) Biswas, Sourav
This report emphasizes the significance of the student-teacher relationship at Noapara Government Primary School. It states that building positive student-teacher relationships is essential to creating a supportive and confidence-building learning environment for young learners. The report, through classroom observations and teaching experience, shows how this relationship has a consistently positive impact on the overall emotional development of primary school students. It is clear that when a student is properly understood and encouraged, they perform better academically and are more motivated to learn. However, some constraints such as large classrooms and lack of adequate individual attention can affect the formation of relationships. The report emphasizes the importance of strong student-teacher engagement in primary education and suggests effective approaches to improve the performance of young learners.
Performance comparison of transformer-based models for multi-reasoning in machine reading comprehension
(Brac University, 2024-06) Sayma, Sadika; Tonima, Fariha Hasan; Biswas, Sourav; Ferdos, Jannatul; Haque, Tasnuva; Choudhury, Najeefa Nikhat
Machine Reading Comprehension (MRC) is an artificial intelligence task that ex amines a given passage or text and answers queries regarding it. The objective is to make an intelligent support system that has the ability to understand the contex tual information of the passage and give correct answers for multi-reasoning ques tions, commonsense based questions and multiple-choice questions, etc. One of the main challenges faced by MRC models in commonsense based and multi-reasoning questions is the need for understanding and reasoning beyond explicit textual infor mation. To enhance the capabilities of MRC systems in these areas, the research focuses on the comparative analysis of state-of-the-art transformer-based models in cluding BERT, ALBERT, RoBERTa, DistilBERT, MobileBERT, and ELECTRA. Our investigation specifically targets the enhancement of commonsense reasoning within MRC frameworks. In regards to this, we have used a binary decision mak ing approach in our algorithm, in order to achieve a better outcome from these transformer-based models. To evaluate the performance, the experiments were con ducted using CosmosQA dataset, which consists of narrative-driven questions that necessitate commonsense understanding to resolve.
Robotic Car for Cockroach Detection
(Daffodil International University, 2019-04-07) Ahamed, Nafiz; Hossain, MD. Nazmul; Biswas, Sourav; Hasan, MD. Minul
Efficient and accurate object detection has been an important topic in the advancement of computer vision systems. With the advent of deep learning techniques, the accuracy for object detection has increased drastically. The project aims to incorporate neural networks technique for object detection with the goal of achieving high accuracy with a real-time performance. Robotic vision continues to be treated including different methods for processing, analyzing, and understanding. All these methods produce information that is translated into decisions for robots. From start to capture images and to the final decision of the robot, a wide range of technologies and algorithms are used like a committee of filtering and decisions. This report aims to design and implement the object detection and machine interfacing for cockroach detection. Here the working procedure has been divided into two parts hardware and software. In order for the system to be operational, Tensor flow, Arduino and Raspberry Pi microcontroller as well as camera module has been used. The projected algorithm has been used to train neural network model to detect cockroach from picture and real time image which is captured by camera module as input for finding accuracy. Finally, it is found that our project provides faster image detection process.