NSU INSTITUTIONAL REPOSITORY
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Recent Submissions
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Open Access
PERFORMANCE EVALUATION OF US MUTUAL FUNDS – A LOOK AT ‘GROWTH FUNDS’, ‘GROWTH AND INCOME FUNDS’ AND ‘INCOME FUNDS’
(North South University, 2020-06) Shahran Abu Sayeed; Jashim Uddin Ahmed, PhD
This study evaluates the performances of domestic equity mutual funds in the US. Three performance measurement models act as tools in measuring the performances. Using monthly data from January 1993 to December 2012, it is found that funds, on average, underperform the benchmark across the entire period. Moreover, it is also shown that amongst the three style categories of funds, ‘Growth Funds’ report the lowest average abnormal performance as compared to ‘Growth and Income Funds’ and ‘Income Funds’.
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Open Access
Implementation of Cellphone Detector with Signal Jammer
(North South University, 2022) Asif Hasan Akash; Tamzidul Haque Riaz; Shibly Ahmed; Md. Mahedi Hasan; Md. Eliush Molla; Dihan Md. Nuruddin Hasan; 1731261043; 1731703643; 1731489043; 1731343043; 1731041043
This research have been done to restrict the use of cellphones in restricted areas and to increase security. Sometimes people go to the extent of using mobiles in prohibited areas, due to such acts the security policies of those places are hindered and the effects might be hazardous. Therefore to find an answer to that problem with the help of this study a solution can be derived. A device can be set up which will consist of a cell phone detector with signal jammer. In the current market, basically these are two separate devices i.e., a cell phone detector and a signal jammer but they don’t serve the purpose completely as the detector can only detect signals but they can’t block them whereas the jammer can only jam the signals but they cannot detect it, and we cannot let the jammer turned on continuously as it may harm the environment. But if we combine these two devices and make it a single handy device then our purpose can be served.
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Open Access
10th int’l business genius Bangladesh held at NSU
(New Age, 2025-08-10) New Age
University Grants Commission of Bangladesh member Professor Tanzim Uddin was chief guest at the opening ceremony. Guest of honour of the ceremony was Professor Abdul Hannan Chowdhury, vice-chancellor, North South University, and AKM Zabed, COO, Dekko Foods Ltd. Special Guests of the ceremony was Khandker Md Nahin Mamun, chairperson and assistant professor, department of marketing and international business, North South University. Associate Professor M Abdullah Al Mamun, chief adviser, Business Genius Bangladesh, was the chair of the ceremony. The event’s event management partner was the Federation of Hospitality, Tourism and Event Management while the debate management partner was Bangladesh Debate Warriors.
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Open Access
Krishi House An IoT based smart greenhouse
(North South University, 2021) Moumita Ferdoushi; Shorony Mehtaz Ahmed; Ashfia Binte Habib; 1631125045; 1331066045
In Bangladesh, one of the main economic activities lies in the agricultural sector. Although the good presence of resources does not produce results equal to the availability. The cause of scarcity and incompetent use of technology, deficiency of knowledge and awareness among the agrarians, methods which are time-consuming, hard labor, and more expensive in the long run. A Greenhouse is a technical approach in which farmers in rural areas will be benefitted by automatic monitoring and control of the greenhouse environment. The project focuses on the use of IoT in the greenhouse for environment monitoring and control by implementing low-cost, space, and effort strategies. A system that is efficient in terms of power and water usage while keeping the system architecture and design modest. Krishi House is semi-automated making human supervision redundant. With the help of a temperature sensor, soil moisture, pH and humidity sensor, light sensor the system will take inputs from the sensors to the microcontroller and microprocessor of the greenhouse where the algorithm will give desired output in form of irrigation, growth light, and system alert along with sending data wirelessly to the user. Power efficiency is attained by the use of solar energy when acquired; cost and space efficiency is achieved with a meticulous selection of components, materials, and horticulture technique. The goal is to have a competent semiautomated eco-system that supports different types of vegetation which will provide a better yield than the traditional farming method without the hard labor keeping cost and power use at least. The data collected throughout the experiment by the microcontroller and the microprocessor are attained wirelessly in a cloud database and can also be seen by a mobile app at the user’s convenience. The goal is to achieve a High-tech greenhouse with automation without the extra cost. The use of IoT and technological advancement will improve the agricultural prospect drastically in Bangladesh which shall be economically accommodating.
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Open Access
Innovative System for Mask Detection & Distance Maintainer
(North South University, 2021) Md. Nasir Uddin; Sheikh Imam Hossain; Md. Mahfuzur Rahman Shakil; Atiqur Rahman; 1811274642; 1812617643; 1812918642
Covid-19 is a novel virus that has never been seen in humans before. This disease was first detected in December 2019 in Wuhan, China, and has been spreading since worldwide. The virus can easily pass from person to person through breathing & making physical contact, which is why it is spreading rapidly. To stop the transmission of Covid-19, wearing face mask and maintaining social distance are crucial disciplines to follow. But these disciplines are not being followed properly because of the lack of monitoring system that could enforce such disciplines among people especially in places of social gathering. As a result, lockdowns are being enforced & many work places, industries, garments, educational institutions are being shut down in order to stop the spread. Which is damaging our economy & productivity to a great extent. In order to prevent further damage & to recover the losses due to pandemic, we have come up with a project plan that deals with ensuring a system which is capable of detecting faces with & without masks and also capable of measuring distance between person to person & displaying the information in details on big screen for monitoring. The project is AI and deep learning-based. Various types of electronic devices & components are required to make this system. The system we are developing is productive, feasible & can be easily implemented. And for being cost efficient, it can be mass produced as well. By implementing such system in places of social gathering can prevent the transmission of the virus. As the system enforces people to wear masks & maintain certain distance from each other at gathering places, it significantly reduces the possibility of transmission. And because of the implementation of the system, lockdowns will no longer be necessary & people can continue working in their respective work places. Productivity & progress will continue, even during the pandemic. This project can bring forth significant changes in economic progress & development of the country and can assist in recovering the productive losses due to the pandemic.
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Open Access
Real Estate Company Beater Price Prediction Using Machine Learning
(North South University, 2021) Md. Nur-E-Azam; Md. Reaz Islam; Hridoy Saha; Shazzad Hosain; 1512268042; 1520663042; 1611520042
The below document presents the implementation of price prediction project for the real estate markets and housing. Many algorithms are used here to effectively increase the accuracy percentage, various researchers have done this project and implemented the algorithms like hedonic regression, artificial neural networks which is considered as the best models in the price prediction. These are considered as the base models and by the help of advanced data analysis tools algorithms like a random forest, gradient boosted trees, multi layer perceptron and ensemble machine learning models are used and prediction accuracy is attained in a higher rate. The results and evaluation of these models using the machine learning and advanced data analysis tools like pandas will have the more influence in the price prediction.
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Open Access
Breast Cancer prediction using Machine Learning and Implementation with Web Application
(North South University, 2022) Md. Amith Hasan Omee; Minhaz Mahmud; Md.Sharun Tasin; Syed Latiful Akhter; Shahnewaz Siddique; 1620352042; 171263042; 1712338042; 1712334042
Breast Cancer is one of the common cases for women. A significant number of women around the world are facing it. About 43000 women die in a year from this cancer. The main reason for the death of cancer is the lack of human knowledge about it. The main target of this project is to detect breast cancer at an early stage. If any woman can detect her breast cancer at an early stage, then she should take proper treatment at the very beginning and she could save her life. Each and every life is important for the country. For this early detection we use Machine learning because Machine learning techniques are highly preferable for use in the medical field because of their high accuracy.
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Open Access
HOW DO BANGLADESHI INVESTORS TAKE DECISIONS? AN ETHNOGRAPHIC DECISION TREE MODEL OF STOCK SELECTION
(North South University, 2020-06) Ashiqul Haq Chowdhurya; Asad Karim Khan Priyob; Jashim Uddin Ahmed, PhD
The study explores the decision making process of Bangladeshi stock market investors. We interview 31 investors currently holding stock portfolio in the Dhaka Stock Exchange (DSE) to understand their choices and decision making process. Based on the findings, we develop an Ethnographic Decision Tree Model (EDTM) of Stock Selection. We find that a stock usually comes to an investor’s attention through news/ rumors or suggestions received from family/ friends/ broker or on the basis of past experience. Information use often depends on trust and the necessity to act on it immediately. In an active search process, ‘filter’ criteria are used to reduce the choice set of stocks for further evaluation. The nature of evaluation depends on whether investors look to invest for the long or the short term. Finally, stock selection depends on whether investors perceive the stock to be undervalued and whether the stock fits her/ his investment strategy. We also find that collective intelligence affects an individual’s investment decision and trustworthiness of the information source is a key factor in determining her/ his investment behavior.
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Open Access
Global Spell Bee 2025 National final concludes at NSU
(The Daily Star, 2025-07-17) The Daily Star
The Bangladesh National segment of the Global Spell Bee 2025 came to its conclusion at North South University on 12 July 2025. Finalists showcased their English language skills, analytical thinking, and academic excellence. Organized by EduPro Concepts BD Ltd., in association with GateKeepr and Help the Future, and hosted by North South University Debate Club. Professor Abdul Hannan Chowdhury, Vice-Chancellor of North South University and Chairman of Grameen Bank, was present as the Chief Guest. Mohammad Inzamul Haque, Assistant Personal Secretary to the Education Adviser at the Ministry of Education, highlighted the broader value of such competitions, noting, Nabiha Tahseen Nubah from Sunny Dale School emerged as the champion in the Senior Category, while Ibnat Namira Ahmed from Summerfield International School claimed the top spot in the Junior Category.
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Open Access
Analysis of glucose concentration in a non-invasive way using NIR spectra through linear regression model
(North-south University, 2018-06-30) Mahbubur Rhaman Mishal; Tanvir Tazul Islam; Shahadat Hossain Antor; Dr. Tanzilur Rahman; 1410385042; 1420392042; 1420918042
World Health Organization (WHO) stated that 2.2 million people died in 2012 for high blood glucose and diabetes will be the 7th cause of death by 2030. To improve this situation, a continuous monitoring system of glucose level in blood is extremely necessary for the diabetes patients. The purpose of this study is to propose a signal processing model for the detection of glucose concentration with high accuracy in a non-invasive way. The study includes correction of NIR spectra collected from a mixture of components (glucose, urea, triacetin) through different preprocessing techniques, classify the preprocessed data through linear regression models and performance analysis of the applied techniques on the prediction of glucose concentration. The objective of the study is to identify the best model with optimum result. Baseline correction techniques such as Standard Normal Variate (SNV), Mean Scatter Correction (MSC), Asymmetric Least Square (ALS) and Savitzky-Golay Transformation (SGT) have been applied to remove the scatter from the collected NIR spectra. ALS along with SGT gives the best result in this case. Different filtering techniques have also been applied to remove the noise those came along with the NIR spectra. Chebyshev filter on the ALS+SGT corrected data has the best performance in noise removal. Different linear regression model like PLS, PCR are applied separately on the preprocessed spectra to bring out the targeted result. Several derivative order of PLS also applied and the 3rd order works well than the 2nd order here. The model that applies Chebyshev filter on baseline corrected data by ALS+SGT and do regression through PLS have given the most accurate and clinically acceptable result to isolate the glucose data from the NIR spectra and predict the glucose concentration level. Since this combination among different techniques that are found through this study is able to isolate the glucose data and predict the concentration level from a mixture of different components with high accuracy, we hope that the study will be valuable in realizing a continuous monitoring system of glucose level in noninvasive way in the near future.