Browsing by Author "Hossain, Arafat"

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Accurate analysis of mood detection using eye-images rather than facial expression recognition (FER)
(BRAC University, 6/5/2022) Hossain, Arafat; Chakraborty, Akash; Syara, Syeda Rifa; Rahman, Saadman; Tanmoy, Fahad Muntasir; Rahman, Tanvir; Shakil, Arif
There are several works on mood detection by machine learning from physical and neuro- physical data of people, along with works on emotion recognition using eye-tracking. We want to show that a person’s mood can be detected using their eye images only. The mood is reflected through one’s eyes. The goal is to establish a connection between an individual’s mood and one’s eye images. The machine learning algorithm that we are going to use is Convolutional Neural Network (CNN) because it does not require external feature extraction. They system learns to extract the features by itself. In this paper, we developed two CNN models and used FER- 2013 as our dataset from which we used only the eye images for each of the six emotions: happy, fear, sad, angry, neutral and surprise to create our own dataset. We trained and tested our models with both FER-2013 dataset as well as our own dataset and compared the results. For FER-2013 dataset, our final accuracy score for model 1 was 83.78% with a validation accuracy score of 65.35%. It was seen that our model 1 showed the final accuracy score of 69.19% with a validation accuracy of 72.08% whereas for model 2, the final accuracy was 66.55% with a validation accuracy of 72.36% when trained and tested with our own dataset. The low accuracy for our dataset is due to the limitations that we faced for insufficient training and testing images. The accuracy can be improved with a better dataset for training our models.
An analysis of communication and branding strategies of Dhaka bank ltd.
(Daffodil International University, 2018-05) Hossain, Arafat
After 90s Bangladesh economies has been achieving a rapid growth action that’s the reason Bangladesh is a developing country, many sectors play an important role with the economic and others development of the country. And banking secretors has huge contribution of this economic development. We can easily consider that banking system of a country as a barometer of an economic development. In this modern era well-developed banking system is much more needed for every type of trade and commerce. Day by day we are involving economical activities, as a result we are depending on banking sectors. In this reason our country has been promoting our financial sectors. Now days we can experience different type of Bank service like national and international. In our country banking system has divided in different ways like state owned, privet and foreign commercial bank. And In our country Bangladesh Bank play a vital role as guardian of all Banks who are providing financial or non-financial service in Bangladesh. Now this analyze has mention some name of the Bank who is providing financial service in our country, Sonali Bank Ltd.Rupali Bank Ltd.Janata Bank Ltd.Bangladesh Development Bank Limited. Basic Bank Limited. Bangladesh, AB Bank Limited, IFIC Bank Limited, Modhumoti Bank Limited, Mutual Trust Bank Limited, NRB Bank Limited, NRB Commercial Bank Limited, NRB Global Bank Limited, One Bank Limited, Premier Bank Limited, Prime Bank Limited, Pubali Bank Limited,Shimanto Bank Ltd,South Bangla Agriculture & Commerce Bank Limited, Standard Bank Limited, Limited, Limited, Trust , Uttara Bank Limited and others. All those banks are using different types of communication and branding strategies but this study will analyze the communication and branding strategies of Dhaka Bank LDT. So this study has been focused on the process of communication of Dhaka bank limited. And how to maintain their communication channels with daily basis of routine work. And which strategies they have followed for their branding. And also followed their positioning strategies in the competitive market
Anti-Viral Drug Discovery Against Monkeypox and Smallpox Infection by Natural Curcumin Derivatives
(Bentham Science Publishers Ltd., 2023-03-22) Akash, Shopnil; Hossain, Arafat; Hossain, Md. Sarowar; Rahman, Md. Mominur; Ahmed, Mohammad Z.; Ali, Nemat; Valis, Martin; Kuca, Kamil; Sharma, Rohit
"Background: In the last couple of years, viral infections have been leading the globe, considered one of the most widespread and extremely damaging health problems and one of the leading causes of mortality in the modern period. Although several viral infections are discovered, such as SARS CoV-2, Langya Henipavirus, there have only been a limited number of discoveries of possible antiviral drug, and vaccine that have even received authorization for the protection of human health. Recently, another virial infection is infecting worldwide (Monkeypox, and Smallpox), which concerns pharmacists, biochemists, doctors, and healthcare providers about another epidemic. Also, currently no specific treatment is available against Monkeypox. This research gap encouraged us to develop a new molecule to fight against monkeypox and smallpox disease. So, firstly, fifty different curcumin derivatives were collected from natural sources, which are available in the PubChem database, to determine antiviral capabilities against Monkeypox and Smallpox. Material and method: Preliminarily, the molecular docking experiment of fifty different curcumin derivatives were conducted, and the majority of the substances produced the expected binding affinities. Then, twelve curcumin derivatives were picked up for further analysis based on the maximum docking score. After that, the density functional theory (DFT) was used to determine chemical characterizations such as the highest occupied molecular orbital (HOMO), lowest unoccupied molecular orbital (LUMO), softness, and hardness, etc. Results: The mentioned derivatives demonstrated docking scores greater than 6.80 kcal/mol, and the most significant binding affinity was at -8.90 kcal/mol, even though 12 molecules had higher binding scores (-8.00 kcal/mol to -8.9 kcal/mol), and better than the standard medications. The molecular dynamic simulation is described by root mean square deviation (RMSD) and root-mean-square fluctuation (RMSF), demonstrating that all the compounds might be stable in the physiological system. Conclusion: In conclusion, each derivative of curcumin has outstanding absorption, distribution, metabolism, excretion, and toxicity (ADMET) characteristics. Hence, we recommended the aforementioned curcumin derivatives as potential antiviral agents for the treatment of Monkeypox and Smallpox virus, and more in vivo investigations are warranted to substantiate our findings."
Comparison of Calcium level in Blood Serum of cattle in late pregnancy and postpartal period
(Chattogram Veterinary & Animal |Sciences University, 2009-02) Hossain, Arafat
The study was carried out in Chittagong district to find out the calcium levels in the blood serum in late pregnant and post partum cow. The study revealed that the levels of calcium in blood serum to the late pregnant cows were 8.45±0.16 mg/dl and post partum cows were 7.95±0.56 mg/dl. The serum calcium level is slightly higher in late pregnant cow than in post partum cow
Corrigendum: Anti-Viral Drug Discovery Against Monkeypox and Smallpox Infection by Natural Curcumin Derivatives
(Frontiers, 2023-03-22) Akash, Shopnil; Hossain, Arafat; Hossain, Md. Sarowar; Rahman, Md. Mominur; Ahmed, Mohammad Z.; Ali, Nemat; Valis, Martin; Kuca, Kamil; Sharma, Rohit
"Background: In the last couple of years, viral infections have been leading the globe, considered one of the most widespread and extremely damaging health problems and one of the leading causes of mortality in the modern period. Although several viral infections are discovered, such as SARS CoV-2, Langya Henipavirus, there have only been a limited number of discoveries of possible antiviral drug, and vaccine that have even received authorization for the protection of human health. Recently, another virial infection is infecting worldwide (Monkeypox, and Smallpox), which concerns pharmacists, biochemists, doctors, and healthcare providers about another epidemic. Also, currently no specific treatment is available against Monkeypox. This research gap encouraged us to develop a new molecule to fight against monkeypox and smallpox disease. So, firstly, fifty different curcumin derivatives were collected from natural sources, which are available in the PubChem database, to determine antiviral capabilities against Monkeypox and Smallpox. Material and method: Preliminarily, the molecular docking experiment of fifty different curcumin derivatives were conducted, and the majority of the substances produced the expected binding affinities. Then, twelve curcumin derivatives were picked up for further analysis based on the maximum docking score. After that, the density functional theory (DFT) was used to determine chemical characterizations such as the highest occupied molecular orbital (HOMO), lowest unoccupied molecular orbital (LUMO), softness, and hardness, etc. Results: The mentioned derivatives demonstrated docking scores greater than 6.80 kcal/mol, and the most significant binding affinity was at -8.90 kcal/mol, even though 12 molecules had higher binding scores (-8.00 kcal/mol to -8.9 kcal/mol), and better than the standard medications. The molecular dynamic simulation is described by root mean square deviation (RMSD) and root-mean-square fluctuation (RMSF), demonstrating that all the compounds might be stable in the physiological system. Conclusion: In conclusion, each derivative of curcumin has outstanding absorption, distribution, metabolism, excretion, and toxicity (ADMET) characteristics. Hence, we recommended the aforementioned curcumin derivatives as potential antiviral agents for the treatment of Monkeypox and Smallpox virus, and more in vivo investigations are warranted to substantiate our findings."
Detection of acute Lymphocytic Leukemia (ALL) and its type by image processing and machine learning
(BRAC University, 2018-12) Chowdhury, Himadri; Banik, Shounak; Hossain, Arafat; Khaled, Md. Imran; Chakrabarty, Amitabha
Cancer starts when cells of body begin to grow rapidly. Cells in nearly any part of the body can become cancer and can spread to other areas of the body. The origin of Chronic Lymphocytic Leukemia (CLL) in the bone marrow and causes the random growth of a large number of unnatural cells. The leukemia cells start in the bone marrow. By the time, access into the blood cells and cause fatal disease. Mainly, there exist 4 types of leukemia which are Acute Lymphoblastic Leukemia (ALL), Acute Myeloid Leukemia (AML), Chronic Lymphocytic Leukemia (CLL) and Chronic Myeloid Leukemia (CML). In this paper, we proposed to build a methodology to detect the Leukemia (Cancer) by the help of image processing and machine learning. We are using the two stage otsu-optimization approach algorithm, Lab color space algorithm and wrapper method. For image preprocessing to be fit in the classifiers Image to Feature Vector method and Label Encoding methods have been applied on the dataset. Furthermore, we applied various machine learning algorithms, Logistic Regression, Decision Tree, Gaussian Naive Bayes, K-Nearest Neighbor (KNN) and from neural network algorithm Convolutional Neural Network (CNN) has been applied. We made an effort to build a comprehensive comparison among machine learning algorithms. Though it has been done in past research papers but in this paper we collected few image data from Dhaka Medical College and preprocessed it with another public image data set named ADL to attain at least a promising test accuracy. Moreover, in this research paper we tried to break a superstition of recent age which is Convolutional Neural Network (CNN) is the only appropriate model to train an image dataset. We implemented AdaBoost Classifier which has given 87% of test accuracy with a glimpse of high cross validation accuracy of 90%. We also brought Voting Classifier in process, mixing AdaBoost, Gaussian Naive Bayes, K-Nearest Neighbor (KNN) classifiers together has given 89% of test accuracy as much as like Convolutional Neural Network (CNN) 90%. Thus, we can conclude the debate that image dataset can be trained for pattern recognition with simple machine learning algorithm with the minimum computational cost with higher accuracy.
Modified Coptisine Derivatives as an Inhibitor Against Pathogenic Rhizomucor miehei, Mycolicibacterium smegmatis (Black Fungus), Monkeypox, and Marburg Virus by Molecular Docking and Molecular Dynamics Simulation-Based Drug Design Approach
(Frontier Scientific Publishing, 2023-04-19) Akash, Shopnil; Hossain, Arafat; Mukerjee, Nobendu; Sarker, Md. Moklesur Rahman; Khan, Mohammad Firoz; Hossain, Md. Jamal; Rashid, Mohammad A.; Kumer, Ajoy; Ghosh, Arabinda; León-Figueroa, Darwin A.; Barboza, Joshuan J.; Padhi, Bijaya Kumar; Sah, Ranjit
"During the second phase of SARS-CoV-2, an unknown fungal infection, identified as black fungus, was transmitted to numerous people among the hospitalized COVID-19 patients and increased the death rate. The black fungus is associated with the Mycolicibacterium smegmatis, Mucor lusitanicus, and Rhizomucor miehei microorganisms. At the same time, other pathogenic diseases, such as the Monkeypox virus and Marburg virus, impacted global health. Policymakers are concerned about these pathogens due to their severe pathogenic capabilities and rapid spread. However, no standard therapies are available to manage and treat those conditions. Since the coptisine has significant antimicrobial, antiviral, and antifungal properties; therefore, the current investigation has been designed by modifying coptisine to identify an effective drug molecule against Black fungus, Monkeypox, and Marburg virus. After designing the derivatives of coptisine, they have been optimized to get a stable molecular structure. These ligands were then subjected to molecular docking study against two vital proteins obtained from black fungal pathogens: Rhizomucor miehei (PDB ID: 4WTP) and Mycolicibacterium smegmatis (PDB ID 7D6X), and proteins found in Monkeypox virus (PDB ID: 4QWO) and Marburg virus (PDB ID 4OR8). Following molecular docking, other computational investigations, such as ADMET, QSAR, drug-likeness, quantum calculation and molecular dynamics, were also performed to determine their potentiality as antifungal and antiviral inhibitors. The docking score reported that they have strong affinities against Black fungus, Monkeypox virus, and Marburg virus. Then, the molecular dynamic simulation was conducted to determine their stability and durability in the physiological system with water at 100 ns, which documented that the mentioned drugs were stable over the simulated time. Thus, our in silico investigation provides a preliminary report that coptisine derivatives are safe and potentially effective against Black fungus, Monkeypox virus, and Marburg virus. Hence, coptisine derivatives may be a prospective candidate for developing drugs against Black fungus, Monkeypox and Marburg viruses."