Browsing by Author "Sultana, Afrin"

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An Evaluation of the Training & Development Operations of Jamuna Bank Ltd.
(Daffodil International University, 2021-12-19) Sultana, Afrin
The modern banking system is the result of development due to changes in economic actions and existence. Its proposals the broadest range of fiscal services, particularly credit, investments and expense services, and achieves the broadest range of financial purposes of any commercial venture in the cheap. A bank, by meaning, gathers credits from money containers and capitalizes the accrued investments of investors in the form of credit and additional economic facilities for customers. On the one hand, the bank wages developed interest rates to borrowers to make a profit. So, we see that money acts as the entrance and exit of the banking sector. An important characteristic of a banking company is obtaining a good picture of the reliability in management investors' money. Jamuna Bank is one of the greatest famous banks in our country. Commercial banks are one of the chief participants in the economies of emerging countries. They performance as fiscal intermediaries, raising funds for one group and transferring them to another while creation a realistic profit after covering the costs of the assets. Bangladesh's banking sector follows a policy of branch growth and growth. The persons and the government itself are extremely dependent on the facilities of the 55 banks in the fiscal markets. To find out how well profitable banks really work. The banking repetition of conservative banking and Islamic banking is very dissimilar from the impression. The report starts with the Introduction chapter. Then this the report expressions the banking segment in Bangladesh. Then the report represents Jamuna Bank Ltd. The next chapter shows the establishment and development of the organization, creation, mission, vision, goals and shows the main body of the report on the establishment and progress of Jamuna Bank. The final chapter presents the results of the study, commendations, conclusion and references.
Analysis of Rectifier circuits with power factor correction
(BRAC University, 2014-01) Hassan, M. M. Emran; Sultana, Afrin; Akther, Sunjida; Abedin, Amina Hasan
Power Factor, the ratio between the real power and the apparent power forms a very essential parameter in power system. It is indicative of how effectively the real power of the system has been utilized. With rapid development in power semiconductor devices, the usage of power electronic systems has expanded to new and wide application range that include residential, commercial, aerospace and many others. Power electronic interfaces have proved to be superior. However, their non‐linear behavior puts a question mark on their high efficiency. The current drawn by the interfaces from the line is distorted resulting in a high Total Harmonic Distortion(THD) and low Power Factor(PF). Individually, a device with harmonic current does not pose much serious problem however when used on a massive scale the utility power supply condition could be deteriorated. Other adverse effects on the power system include increased magnitudes of neutral currents in three‐phase systems, overheating in transformers and induction motors etc. Hence, there is a continuous need for power factor improvement and reduction of line current harmonics. Development of new circuit topologies and control strategies for Power Factor Correction (PFC) and harmonic reduction has become essential. This project aims to develop a circuit for PFC using passive filters.
Estimation Of Fecundity And Gonadosomatic Index (Gsi) Of Paradise Threadfin, Polynemus Paradiseus (Linnaeus, 1758) From The Meghna River Estuary, Bangladesh
(Daffodil International University, 2013-07) Rahman, Md. Mofizur; Sultana, Afrin; Hasan, Mehedi Mahmudul; Sarker, Bhakta Supratim; Rahman, Mahabubur
The present investigation was conducted to assess the fecundity and gonadosomatic index of female Polynemus paradiseus (L.) of the Meghna river estuary during the spawning season. A total of 75 samples were collected from local fish markets Chairmanghat, Sonapur and Maijdee of Noakhali. Mean total length and mean body weight of the collected fish samples were 16.38 ± 0.29 cm and 25.01 ± 1.45g respectively. The mean total fecundity was found 11383.33 ± 343.35.Variation in fecundity, GSI, total length, body weight and gonad weight of the studied species was found across the spawning season (April- June). Gonadosomatic index was found higher in May-June than April. The relationships of fecundity with body length, body weight and gonad weight were found to be linear and correlation coefficient (r) values were 0.6861, 0.7823 and 0.8049 respectively. The linear relationship between body weight and fecundity was found more valid than the relationship between body length and fecundity. The present study revealed that the fecundity of P. paradiseus was comparatively low than other estuarine fish species. Basic information on the size at sexual maturity and fecundity of P. paradiseus will be helpful to evaluate reproductive potential of individual fish species in similar studies.
Understanding Climate Change Concern Using Machine Learning Technique
(Daffodil International University, 23-01-17) Sultana, Afrin
Climate transformation has been identified as the principal environmental crisis of the 21st century and become a matter of considerable debate. Nowadays, the significance of climate change is extensively argued through various papers, newspapers, websites, and blogs. But that writing may lack accuracy, while the severity of results in scientific articles may be too unclear for the public to understand. With the rapid evolution of the internet and communication technology today, more and more people are interested to express their thoughts via social media and debate there a lot. Utilize the welfare of social media in this study, a gigantic dataset of tweets containing particular keywords connecting to climate change is analyzed using volume analysis and text mining methods such as case modeling and sentiment analysis and how ML can be a strong tool to predict accurately people's concerns and help society adapt to a changing climate. This study provides an explanation as well as a solution by classifying the tweet's natural, man-made, and neutral opinion reviews using the Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbor, and Logistic Regression (LR). Among these algorithms, Support Vector Machine accuracy is the best accuracy and accuracy is 83.01%. The proposed model is made on Jupyter Notebook (a Python-based IDE) and trained on Kaggle's standard Twitter Climate Change Sentiment Dataset which has 43,743 records.