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  • Pre-COVID-19 Knowledge, Attitude and Practice Among Nurses Towards Infection Prevention and Control in Bangladesh: A Hospital-Based Cross-Sectional Survey 
    Harun, Md. Golam Dostogir; Anwar, Md Mahabub Ul; Sumon, Shariful Amin; Abdullah-Al-Kafi, Md; Datta, Kusum; Haque, Md. Imdadul; Chowdhury, A. B. M. Alauddin; Sharmin, Sabrina; Islam, Md Saiful (Scopus, 22-12-01)
    Introduction Hospital-acquired infections endanger millions of lives around the world, and nurses play a vital role in the prevention of these infections. Knowledge of infection prevention and control (IPC) best practices ...
  • Predicting Absenteeism at Work Using Tree-based Learners 
    Wahid, Zaman; Satter, A. K. M. Zaidi; Imran, Abdullah Al; Bhuiyan, Touhid (ICMLSC 2019 the 3rd International Conference on Machine Learning and Soft Computing, ACM Digital Library, 2019-01-25)
    Absenteeism at workplace acts as a crucial role in demonstrating the productive and profitable capacity of a company. Thus the knowledge of absenteeism of employees' becomes the foundation for an organization in its multiple ...
  • Predicting and Classifying Potato Leaf Disease using K-means Segmentation Techniques and Deep Learning Networks 
    Nishada, Md. Ashiqur Rahaman; Mitua, Meherabin Akter; Jahan, Nusrat (Daffodil International University, 2023-12-20)
    Potato is one of the most cultivated crops. Worldwide potatoes have its own cultivation priority as a staple food. For a successful potato production, we can develop a strong food security system as it is the great source ...
  • Predicting and Staging Chronic Kidney Disease of Diabetes (Type-2) Patient Using Machine Learning Algorithms 
    Basak, Setu; Alam, Md. Mahbub; Rakshit, Aniruddha; Marouf, Ahmed Al; Majumder, Anup (International Journal of Innovative Technology and Exploring Engineering, Blue Eyes Intelligence Engineering & Sciences Publication, 2019-10-02)
    Mortality because of unending kidney disease increments essentially in recent years. Nowadays, about 422 million patients are suffering from diabetes among them around 30 percent of patients with Type 1 (adolescent beginning) ...
  • Predicting Career Using Data Mining 
    Arafath, Md. Yeasin; Saifuzzaman, Mohd.; Ahmed, Sumaiya; Hossain, Syed Akhter (2nd International Conference on Electrical, Computer and Communication Engineering, ECCE 2019, IEEE, 2019-03-28)
    Career goal specially choosing the appropriate career through monitoring of the scope and trends in computer science and engineering job dimension have been a prime need for all computer science undergraduate youngsters. ...
  • Predicting Chronic Kidney Disease of Diabetes Patients Using Ensemble Learning 
    Faruque, Md. Omar; Hossain, Sabbir; Al Marouf, Ahmed (6th International Conference on Communication and Electronics Systems (ICCES), IEEE, 2021-08-02)
    Chronic kidney disease is the reason for many deaths all over the world every year. Chronic kidney disease has troubled almost 753 million people all over the world in 2016, wherein 417 million are females and 336 million ...
  • Predicting Fertilizer Treatment of Maize Using Decision Tree Algorithm 
    Jahan, Nusrat; Shahariar, Rezvi (Scopus, 2020)
    Machine learning approaches are progressively successful in image based analysis such as different diseases prediction as well as level of risk assessment. In this paper, image based data analysis with machine learning ...
  • Predicting IMDb Rating of Movies by Machine Learning Techniques 
    Bristi, Warda Ruheen; Zaman, Zakia; Sultana, Nishat (10th International Conference on Computing, Communication and Networking Technologies, ICCCNT 2019, IEEE, 2019-12-30)
    Film Industry is not only a industry or a centre of entertainment, rather it is now a centre of global business. All over the world is now excited about a movie's box office success, popularity etc. A huge data is available ...
  • Predicting Innovation Capability through Knowledge Management in the Banking Sector 
    Edeh, Friday Ogbu; Zayed, Nurul Mohammad; Nitsenko, Vitalii; Yermolenko, Olha Brezhnieva-; Negovska, Julia; Shtan, Maryna (Daffodil International University, 2022-07-17)
    Purpose: The purpose of this study was to investigate the effects of knowledge management on innovation capability in the banking sector. Research methodology: Cross-sectional research design was employed in this study as ...
  • Predicting Insomnia Using Multilayer Stacked Ensemble Model 
    Zulfiker, Md. Sabab; Kabir, Nasrin; Biswas, Al Amin; Chakraborty, Partha (Scopus, 2021)
    Different forms of sleep disorders have become major health problems among people around the world, and insomnia is one of them. It is a physical condition in which a person faces difficulties to fall asleep at night. It ...
  • Predicting Performance Analysis of Garments Women Working Status in Bangladesh Using Machine Learning Approaches 
    Keya, Maria Sultana; Emon, Minhaz Uddin; Akter, Himu; Imran, Md. Al Mahmud; Hassan, Md. Kamrul; Mojumdar, Mayen Uddin (2021 6th International Conference on Inventive Computation Technologies (ICICT), IEEE, 2021-02-26)
    Maria Sultana Keya, Minhaz Uddin Emon, Himu Akter, Md. Al Mahmud Imran, Md. Kamrul Hassan, Mayen Uddin Mojumdar Abstract: In Bangladesh, the garment industry has played an important role in economically uplifting a ...
  • Predicting Satisfaction of Online Banking System in Bangladesh by Machine Learning 
    Shetu, Syeda Farjana; Jahan, Israt; Islam, Mohammad Monirul; Hossain, Refath Ara; Moon, Nazmun Nessa; Nur, Fernaz Narin (2021 International Conference on Artificial Intelligence and Computer Science Technology (ICAICST), IEEE, 2021-07-30)
    Online banking refers to using your smartphone, tablet, or another internet-connected computer to browse and access your bank account. It is quick and free, and it usually allows you to perform a variety of activities, ...
  • Predicting Students 
    Zulfiker, Md. Sabab; Kabir, Nasrin; Biswas, Al Amin; Chakraborty, Partha; Rahman, Md. Mahfujur (Scopus, 2020)
    Every year thousands of students get admitted into different universities in Bangladesh. Among them, a large number of students complete their graduation with low scoring results which affect their careers. By predicting ...
  • Predicting Students' Intention To Continue Business Courses on Online Platforms During the COVID-19 
    Unknown author (Scopus, 22-09-22)
    The objective of this study was to analyze the intention of a University's business department students to continue their studies on e-learning platforms during the ongoing COVID-19 pandemic. To this end, a questionnaire ...
  • Predicting the Appropriate Category of Bangla and English Books for Online Book Store Using Deep Learning 
    Islam, Md. Majedul; Khushbu, Sharun Akter; Islam, Md. Sanzidul (Scopus, 2021)
    At the era of this technology, we are seeking every stuff online first. Book was the best friend to us, still, it is. But this changed the way and medium by which we are being engaged with the book. Nowadays bookselling ...
  • Predicting the Appropriate Mode of Childbirth using Machine Learning Algorithm 
    Kowsher, Md.; Tahabilder, Anik; Prottasha, Nusrat Jahan; Rakib, Md. Abdur-; Alam, Md. Shameem; Habib, Kaiser (Scopus, 2021)
    —A woman's satisfaction with childbirth may have immediate and long-term effects on her health as well as on the relationship with her newborn child. The mode of baby delivery is genuinely vital to a delivery patient and ...
  • Predicting the Death of Road Accidents in Bangladesh Using Machine Learning Algorithms 
    Siddik, Md. Abu Bakkar; Arman, Md. Shohel; Hasan, Afia; Jahan, Mahmuda Rawnak; Islam, Majharul; Biplob, Khalid Been Badruzzaman (Scopus, 2021)
    Road accidents are now a common occurrence in our country. Every year thousands of people die in these accidents and thousands of people are crippled and cursed. Recently the level of road accidents has increased drastically. ...
  • Predicting the Enrollment and Dropout of Students in the Post-graduation Degree Using Machine Learning Classifier 
    Biswas, Al Amin; Majumder, Anup; Mia, Md. Jueal; Nowrin, Itisha; Ritu, Nadia Afrin (International Journal of Innovative Technology and Exploring Engineering, Blue Eyes Intelligence Engineering & Sciences Publication, 2019-09-08)
    Nowadays, In Bangladesh, the dropout rate at post-graduation level or incompletion of the post-graduation degree is considered as a serious problem in the education sector. This work can be used to support for identifying ...
  • Predicting the Intention and Adoption of Near Field Communication Mobile Payment 
    Malarvizhi, Chinnasamy Agamudainambi; Al Mamun, Abdullah; Jayashree, Sreenivasan; Naznen, Farzana; Abir, Tanvir (Daffodil International University, 2022-04-08)
    With the increasing use of mobile devices and new technologies, electronic payments, such as near field communication (NFC) mobile payments, are gaining traction and gradually replacing the currency-based cash payment ...
  • Predicting the Mental Health of Rural Bangladeshi Children in Coronavirus Disease 2019 
    Moon, Nazmun Nessa; Hossain, Refath Ara; Jahan, Israt; Shakil, Shahriar; Uddin, Shihab; Hassan, Mahmudul; Nu, Fernaz Narin (Daffodil International University, 22-06-18)
    The novel coronavirus disease 2019 (COVID-19) current pandemic is a worldwide health emergency like no other. It is not the only COVID-19 infection in infants, children, and adolescents that is causing concern among their ...

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