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    The Impact of Depression and Stress on Preterm Births in First-Time Mothers:
    (Daffodil International University, 2024-02-03)
    This thesis looks at the relationship between stress, depression, and preterm births among first-time mothers in Bangladesh. Preterm births are defined as births that happen before 37 weeks of gestation, and they have a lot of health implications for both the mother and the baby. Stress and depression have been identified as potential risk factors for preterm births, but it is unclear how specifically they affect this issue in Bangladesh. The increased number of preterm births has raised concerns in recent years since it presents serious risks to the health of both the mother and the newborn. Preterm birth mechanisms continue to be complicated and multifactorial, despite international efforts to address this issue. The specific experiences of first-time mothers in Bangladesh are the main focus of this study, which also acknowledges the possible interactions between healthcare, cultural, and economic factors that may make this demographic more vulnerable to mental health issues during pregnancy. A mixed-methods strategy is used in the inquiry to collect thorough data, which combines quantitative surveys and qualitative interviews. First-time pregnant women's stress and depression levels are measured using standardized instruments as part of the quantitative component. Qualitative interviews, on the other hand, offer a more profound comprehension of the environmental and cultural elements that either exacerbate or lessen the effects of stress and depression on premature births. The results of this study may influence public health policy and focused interventions meant to enhance maternal mental health in Bangladesh. This study adds significant insights to the global conversation on maternal healthcare by highlighting the links between depression, stress, and preterm births in first-time mothers. It also highlights the importance of culturally appropriate methods for addressing mental health issues during pregnancy. In the end, the findings of this research might open the door to more practical approaches to lessen the incidence of preterm deliveries and enhance the general health of mothers and children in Bangladesh and other comparable settings
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    MIS Risk Management for Financial Organization during Pandemic
    (Daffodil International University, 2024-02-03) Rahman, Mohammad Maksudur
    The COVID-19 global health crisis, and the accompanying public health measures implemented by governments to reduce human-to-human transmissions, forced businesses around the world to adapt new work arrangements on a massive scale and at an unprecedented speed. People in Bangladesh are not accustomed to working in any other way than physically being there in the office. As a result, it is too risky for financial institutions such as banks, non-banks, and other fintech organizations to continue doing business. In this regard, the organization follows a few working concepts that reduce human health risks as well as IT risks for Fintech organizations. This study examined early data to discuss the significance of a new working model in financial organizations
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    Natural Disasters Visualization
    (Daffodil International University, 2024-02-03) Any, Tanjila Jahan
    This Research aims to create a system for visualizing the number of deaths caused by different types of pandemics worldwide. In order to achieve this, a number of existing technologies will be used. In particular, the programming language Python, Tkinter library, and SQLite database will be used for the development of the system. The Tkinter library is chosen as it is a popular, easy-to-use and cross-platform GUI (Graphical User Interface) library in Python, which can be used to create user-friendly GUI applications. The database used in this application is SQLite, as it is a reliable, free, and open-source database. Python is a powerful programming language and is widely used for developing software applications. It is also well-suited for data analysis and visualization, making it an ideal choice for this project. Additionally, Tkinter provides a range of functions which will be used to create the user interface of the program. Finally, SQLite is a lightweight, open-source database which will be used to store the data related to the pandemic. This system will have a number of advantages, including the ability to quickly visualize the rate of death caused by pandemics, understand the impact of these pandemics, and provide assistance to disaster-related research. Additionally, the program will be able to run without an internet connection, meaning it can be used in remote locations where internet access is not available. Finally, the system will be platform-independent, meaning that it can be used on Windows, Linux, and MacOS. This application can be beneficial to students and researchers all over the world, as it provides an easy and intuitive way to view the data and analyze the effects of pandemics on different countries. It is also useful for disaster relief organizations, which can use the data to plan and respond more effectively to pandemics
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    Prospect Of Digital Bank In The Context Of Bangladesh
    (Daffodil International University, 2024-07-06) Basak, Setu
    Digital banking has brought about a significant shift in the way that financial services are delivered and consumed in the modern day. The emergence of these organizations in Bangladesh can be attributed to the government's support of digital banking and the country's rising internet penetration. This is an attempt to examine the possibilities of digital banking in Bangladesh by providing a more comprehensive overview of the industry's current situation and weighing its advantages and disadvantages. There is a growing population of internet users and a proliferation of mobile financial services (MFS) providers such as bKash, Rocket, and NAGAD. These fintech businesses are now an integral part of the nation's financial ecosystems. The benefits of digital banking in Bangladesh are manifold, including enhanced customer satisfaction, economies of scale for both banks and clients relative to physical facilities, and better convenience and accessibility. Reaching the full potential of these advantages will require overcoming certain obstacles. Infrastructure barriers, such as those relating to biometrics, privacy concerns, and consumer trust difficulties; hazards linked with the internet, such as hacking and server vulnerabilities that might be exploited; and the desire for commerce to be legalized. The use of further cutting-edge technologies like big data analytics, block chain, and artificial intelligence is anticipated to advance the state of digital banking services as we move forward. Mobile financial services, expanding alliances between traditional banks and fintech companies, and more regulatory support will all support future expansion. The prospect of digital bank in Bangladesh is promising, with the potential to significantly contribute to the country's economic development and the broader goal of achieving a SMART Bangladesh.
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    Analyzing The Challenges Of Management Information System Implementation: A Case Study Of Healthcare Sector In Bangladesh
    (DAFFODIL INTERNATIONAL UNIVERSITY, 2024-02-04) Sakim, Md Abdus
    In the rapidly changing world of technology, this study delves into the complexities and challenges faced in the implementation of Management Information Systems (MIS) in the healthcare sector of Bangladesh. Recognizing the crucial role of technology in enhancing healthcare delivery, this research aims to provide an in-depth understanding of the specific barriers and difficulties encountered in the adoption and effective use of MIS in this vital sector. Through a comprehensive case study approach, the study meticulously examines various factors, including technological, human resource, financial, cultural, and policy-related challenges. It also considers the perspectives of multiple stakeholders, such as healthcare providers, managers, and IT professionals, to provide a holistic view of the MIS implementation landscape.
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    A Machine Learning Approach for Early Detection and Improved Decision-Making for Lung Cancer Diagnosis
    (DAFFODIL INTERNATIONAL UNIVERSITY, 2024-02-05) Hasan, Km. Zayedul
    Lung cancer is presently the leading cause of cancer-related mortalities worldwide. Environmental conditions, lifestyle habits, and genetics are the main causes of lung cancer. Early detection of lung cancer is pivotal in preventing its severe consequences. The integration of machine learning algorithms in the healthcare industry has led to significant advancements in disease diagnosis. These algorithms help medical professionals diagnose lung cancer accurately in the early stages. In this study, we propose using Quadratic Discriminant Analysis to improve the accuracy of lung cancer diagnosis by analyzing the symptoms of lung cancer patients. Our proposed technique is more suitable for diagnosing lung cancer with higher accuracy and precision compared to previous techniques. The methodology has demonstrated an impressive overall accuracy of 98% based on empirical results.
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    The Impact of Depression and Stress on Preterm Births in First-Time Mothers:
    (DAFFODIL INTERNATIONAL UNIVERSITY, 2024-02-10) Arif, Md. Rashid
    This thesis looks at the relationship between stress, depression, and preterm births among first-time mothers in Bangladesh. Preterm births are defined as births that happen before 37 weeks of gestation, and they have a lot of health implications for both the mother and the baby. Stress and depression have been identified as potential risk factors for preterm births, but it is unclear how specifically they affect this issue in Bangladesh. The increased number of preterm births has raised concerns in recent years since it presents serious risks to the health of both the mother and the newborn. Preterm birth mechanisms continue to be complicated and multifactorial, despite international efforts to address this issue. The specific experiences of first-time mothers in Bangladesh are the main focus of this study, which also acknowledges the possible interactions between healthcare, cultural, and economic factors that may make this demographic more vulnerable to mental health issues during pregnancy. A mixed-methods strategy is used in the inquiry to collect thorough data, which combines quantitative surveys and qualitative interviews. First-time pregnant women's stress and depression levels are measured using standardized instruments as part of the quantitative component. Qualitative interviews, on the other hand, offer a more profound comprehension of the environmental and cultural elements that either exacerbate or lessen the effects of stress and depression on premature births. The results of this study may influence public health policy and focused interventions meant to enhance maternal mental health in Bangladesh. This study adds significant insights to the global conversation on maternal healthcare by highlighting the links between depression, stress, and preterm births in first-time mothers. It also highlights the importance of culturally appropriate methods for addressing mental health issues during pregnancy. In the end, the findings of this research might open the door to more practical approaches to lessen the incidence of preterm deliveries and enhance the general health of mothers and children in Bangladesh and other comparable settings.
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    Comparison of Weighted Sum Model and Multi-Attribute Decision-Making Weighted Product Methods in Selecting the Best University in Bangladesh
    (DAFFODIL INTERNATIONAL UNIVERSITY, 2024-02-11) Biswas, Pronab
    selection of the best university plays a crucial role in shaping one's academic and professional career. This research paper focuses on comparing two prominent decisionmaking methods, namely the WSM and the MADM-WP method, to determine the best university in Bangladesh. The WSM method calculates the overall performance of universities by assigning weights to each attribute and summing the weighted scores. On the other hand, the MADM-WP method utilizes a product-based approach, multiplying attribute scores by their corresponding weights. The comparison between these two methods involves evaluating their effectiveness, accuracy, and suitability in selecting the best university. The findings of this study provide valuable insights for prospective students, educational institutions, and policymakers in Bangladesh.
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    Exploring the Impact of Social Media Marketing on E-commerce Sales and Brand Awareness
    (DAFFODIL INTERNATIONAL UNIVERSITY, 2024-07-11) Limon, Md Kamrul Islam
    This thesis investigates the impact of social media marketing strategies on e-commerce sales and brand awareness within the context of Bangladesh. By examining social media advertising, influencer marketing, and user-generated content, the study aims to understand their effectiveness in enhancing e-commerce performance and brand recognition. Data was collected through online surveys, interviews, and social media analytics from a diverse sample of e-commerce businesses in Bangladesh. The findings reveal that social media marketing significantly boosts e-commerce sales and brand awareness. Facebook and Instagram emerged as the most effective platforms due to their high user engagement rates. Influencer marketing was identified as particularly beneficial in reaching younger demographics and increasing brand credibility. Despite these benefits, businesses face challenges such as budget constraints, and navigating constantly changing social media algorithms. Environmental and ethical considerations were also examined. The rise in ecommerce has led to increased packaging waste and carbon emissions from delivery services. Ethical concerns, including consumer privacy and transparency in advertising, need to be addressed to maintain consumer trust and sustainability. The study concludes with recommendations for e-commerce businesses to adopt eco-friendly packaging, invest in green logistics, advocate for stronger data protection regulations, and establish guidelines for ethical marketing practices. It also suggests further research on longitudinal impacts, regional comparisons, advanced analytics, emerging platforms, sustainable practices, and digital literacy initiatives to build on the findings and enhance social media marketing strategies in Bangladesh and beyond.
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    Local Flower Detection Through Deep Learning Approach
    (DAFFODIL INTERNATIONAL UNIVERSITY, 2024-07-14) Sarkar, Tanu
    Flowers are some of the most beautiful creations of the Almighty. There are numerous seasonal flowers in Bangladesh. Each flower has its unique color, shape, and name. In our daily lives, we can see a variety of flowers when walking along highways, rail lines, and even in our gardens. However, the majority of our population is unaware of the significance of this beautiful creation. The identification and classification of local flower species using deep learning techniques has important implications for botanical research, biodiversity protection, and ecological monitoring. In this paper, we present an in-depth analysis of multiple deep learning models for detecting and classifying flowers from a dataset of 2400 photos of various flower species the tested models consist of VGG-16, MobileNet, M-1, and ResNet-50. Each model was selected based on its distinct architecture and established efficacy in image recognition tasks. The results of our study indicate that although all models work well, there are significant variations in their abilities. Specifically, the VGG16 model demonstrates great potential for real-time applications and achieving high accuracy of this dataset, with a rate of 97.73%.Six different kinds of flowers have been collected for our research. Our dataset consists of 2450 photos overall and 410 images per flower. We allocated 60% of the images to the training set in order to train the dataset. The validation set is assigned 20% of the total data, while another 20% is allocated to the test set for the purpose of testing. To improve the models' robustness and generalizability, we apply preprocessing techniques like resizing, normalization, and data augmentation. Six different kinds of flowers are used in this system. However, we plan to add more flowers in the future to make our system better.