Articles: Recent submissions

  • Pollution Status and Ecological Risks of Metals in Surface Water of a Coastal Estuary and Health Risk Assessment for Recreational Users 
    Real, Md. Khalid Hassan; Varol, Memet; Rahman, M. Safiur; Islam, Abu Reza Md. Towfiqul (Elsevier, 2024-01-15)
    Since the areas close to the Sundarbans mangrove estuary, which is one of the most dynamic and productive ecosystems in the world, are very suitable for urban and industrial activities, the coastal areas of this ecosystem ...
  • Polycystic Ovary Syndrome (PCOS) Disease Prediction Using Traditional Machine Learning and Deep Learning Algorithms 
    Mridul, Aunik Hasan; Ahsan, Nowreen; Alam, Syeda Sadia; Afrose, Sonia; Sultana, Zakia; kafi, Md. Tanvir Mahmud (Cerebration Science Publishing, 2024-07-10)
    In recent years, there has been a noticeable rise in the prevalence of Polycystic Ovary Syndrome (PCOS), a complex endocrine disorder that affects a significant portion of the population, particularly women of reproductive ...
  • Polyphenols as Therapeutics in Respiratory Diseases: Moving from Preclinical Evidence to Potential Clinical Applications 
    Emran, Talha Bin; Eva, Taslima Akter; Zehrav, Mehrukh; Islam, Fahadul; Khan, Jishan; Kareemulla, Shaik; Arjun, Uppuluri Varuna Naga Venkata; Balakrishnan, Anitha; Taru, Poonam Popatrao; Nainu, Firzan; Salim, Emil; Rab, Safia Obaidur; Nafady; Wilairatana, Polrat; Park, Moon Nyeo; Kim, Bonglee (Ivyspring International Publisher, 2024-06-03)
    Respiratory diseases are the most common and severe health complication and a leading cause of death worldwide. Despite breakthroughs in diagnosis and treatment, few safe and effective therapeutics have been reported. ...
  • Polyphenols in Wound Healing: Unlocking Prospects with Clinical Applications 
    Utpal, Biswajit Kumar; Sutradhar, Baishakhi; Zehravi, Mehrukh; Sweilam, Sherouk Hussein; Panigrahy, Uttam Prasad; Urs, Deepadarshan; Fatima, Ayesha Farhath; Nallasivan, Kumar; Chhabra, Gurmeet Singh; Sayeed, Mohammed; Alshehri, Mohammed Ali; Rab, Safia Obaidur; Khan, Sharuk L.; Emran, Talha Bin (Springer Nature, 2024-10-15)
    Wound healing is a multifaceted, complex process that factors like aging, metabolic diseases, and infections may influence. The potentiality of polyphenols, natural compounds, has shown anti-inflammatory and antimicrobial ...
  • Potential Inhibitors from Natural Compounds against SARS-CoV-2 Main Protease: A Systematic Molecular Modelling Approach 
    Raman, Kannan; Kalirajan, Rajagopal; Islam, Fahadul; Zehravi, Mehrukh; Singh, Laliteshwar Pratap; Murugesan, Sankaranarayanan; Jupudi, Srikanth; Akash, Shopnil; Rana, Ritesh; Byran, Gowramma; Nainu, Firzan; Emran, Talha Bin; Dawoud, Turki M.; Bourhia, Mohammed; Barua, Rashu (John Wiley & Sons, 2024-02-12)
    The COVID-19 outbreak poses a significant threat to the world‘s human population in 2020. Finding new drugs rapidly during this pandemic is quite challenging. Thus, in silico drug screening experiments may provide effective ...
  • Potential Smart Grid Vulnerabilities to Cyber Attacks 
    Paul, Bishowjit; Sarker, Auvizit; Abhi, Sarafat Hussain; Das, Sajal Kumar; Ali, Md. Firoj; Islam, Md Manirul; Islam, Md. Robiul; Moyeen, Sumaya Ishrat; Badal, Md. Faisal Rahman; Ahamed, Md. Hafiz; Sarker, Subrata Kumar; Das, Prangon; Hasan, Md. Mehedi; Saqib, Nazmus (Elsevier, 2024-09-16)
    A novel concept in the realm of conventional electricity grids, known as the “smart grid,” has emerged to explore the most effective methods for integrating green and renewable energy sources. By leveraging existing ...
  • Precision Management of Complex Coronary Lesions: Drug-Coated Balloons and Computational Cardiology at the Forefront of Nanotechnology 
    Padda, Inderbir; Sebastian, Sneha Annie; Moinuddin, Arsalan; Emran, Talha Bin; Goel, Sunny; Johal, Gurpreet (John Wiley & Sons, 2024-10-22)
    Complex coronary lesions present formidable challenges in interventional cardiology, necessitating innovative approaches for effective management. From myocardial bridging (MB) to ostial lesions and bifurcations, each poses ...
  • Predicting Diabetes in Women through Machine Learning 
    Hasan, Rakib; Islam, Muksitul; Hosen, Md. Mamun; Abdullah-Al-Kafi, Md; Radhakrishnan, Niranchana (IEEE, 2024-04-18)
    Diabetes, a predominant non-communicable illness, presents a significant worldwide open well-being concern with rising incidence rates and noteworthy mortality around the world. Timely determination is essential in moderating ...
  • Predicting Electric Vehicles Adoption 
    Choo, Seen Yee; Vafaei-Zadeh, Ali; Hanifah, Haniruzila; Thurasamy, Ramayah (Elsevier, 2024-10-25)
    The increasing popularity of electric vehicles (EVs) as an alternative mode of transportation aims to reduce greenhouse gas emissions and energy expenditures, playing a crucial role in the evolution of emerging mobility ...
  • Predicting Groundwater Phosphate Levels in Coastal Multi-aquifers: A Geostatistical and Data-driven Approach 
    Abdullah-Al Mamun, Md.; Islam, Abu Reza Md Towfiqul; Aktar, Mst.Nazneen; Uddin, Md Nashir; Islam, Md. Saiful; Pal, Subodh Chandra; Islam, Aznarul; Bari, A.B.M. Mainul; Idris, Abubakr M.; Senapathi, Venkatramanan (Elsevier, 2024-11-25)
    The groundwater (GW) resource plays a central role in securing water supply in the coastal region of Bangladesh and therefore the future sustainability of this valuable resource is crucial for the area. However, there is ...
  • Predicting Groundwater Phosphate Levels in Coastal Multi-aquifers A Geostatistical and Data-driven Approach 
    Abdullah-Al Mamun, Md.; Islam, Abu Reza Md Towfiqul; Aktar, Mst. Nazneen; Uddin, Md Nashir; Islam, Md. Saiful; Pal, Subodh Chandra; Islam, Aznarul; Bari, A.B.M. Mainul; Idris, Abubakr M.; Senapathi, Venkatramanan (Elsevier, 2024-11-15)
    Even if you want to make a profit from cryptocurrency, you are worried that you will lose money, and it is difficult to afford it. There are a vast number of papers that study such unpredictable price fluctuations of ...
  • Predicting High Volatility Cryptocurrency Prices using Deep Learning 
    Ito, Tsutomu; Hasebe, Kodai; Hamakawa, Fumito; Biki, Bidesh Biswas; Ikeda, Satoshi; Takei, Amane; Sakamoto, Makoto; Riajuliislam, Md; Shital, Sabrina Bari; Ito, Takao (Elsevier, 2024-01-15)
    Even if you want to make a profit from cryptocurrency, you are worried that you will lose money, and it is difficult to afford it. There are a vast number of papers that study such unpredictable price fluctuations of ...
  • Predicting Pre-Owned Bike Values with Machine Learning Techniques in Bangladesh 
    Ferdous, Kazi Hassanul; Arman, Md.Shohel; Ahmed, Kazi Rifat; Tasnim, Nusrat; Mahmud, Imran; Revathi, P. (IEEE, 2024-10-01)
    As the importance of sustainable practices in the automobile sector grows, it's critical to anticipate motorcycle prices and offerings. With so many variables to consider when buying a secondhand motorcycle-condition, ...
  • Predicting Public Willingness to Use Autonomous Shuttles: Evidence from an Emerging Economy 
    Liew, Ying Wei; Vafaei-Zadeh, Ali; Teoh, Ai Ping; Ramayah, Thurasamy (Sage Publications, 2024-08-28)
    The purpose of this paper is to investigate the public’s willingness to adopt autonomous shuttles for public transport. This study proposes a research framework to explain people’s adoption intentions. Therefore, this study ...
  • Predicting Student Dropout: A Machine Learning Approach 
    Deb, Sreedham; Sammy, Mst. Sakira Rezowana; Tusher, Abdur Nur; Sakib, Md. Rabbi Salehin; Hasan, Md. Firoz; Aunik, Ajharul Islam (IEEE, 2024-11-04)
    Student dropout is a pervasive problem in the education system, with a significant number of students failing to complete their studies due to various reasons such as academic difficulties, financial issues, personal ...
  • Predicting Team Success in the Indian Premier League Cricket 2024 Season Using Random Forest Analysis 
    Sanjaykumar, Swamynathan; Natarajan, Subhashree; Lakshmi, Ponnusamy Yoga; Boby, Farjana Akter (OVS LLC, 2024-04-30)
    Background. Random Forest is a popular machine learning algorithm used for classification and regression tasks. The study purpose is to investigate the use of Random Forest machine learning to predict the winning chances ...
  • Predicting Public Willingness to Use Autonomous Shuttles: Evidence from an Emerging Economy 
    Liew, Ying Wei; Vafaei-Zadeh, Ali; Teoh, Ai Ping; Ramayah, Thurasamy (National Academy of Sciences, 2024-01-15)
    The purpose of this paper is to investigate the public’s willingness to adopt autonomous shuttles for public transport. This study proposes a research framework to explain people’s adoption intentions. Therefore, this study ...
  • Predicting the Effects of Microcredit on Women’s Empowerment in Rural Bangladesh: Using Machine Learning Algorithms 
    Polin, Johora Akter; Sarker, Md.Fouad Hossain; Khanom, Mst Dilruba (Institute of Advanced Engineering and Science (IAES), 2024-08-15)
    This study aimed to predict the impact of microcredit on women’s empowerment in Bangladesh using machine learning (ML) algorithms. In rural Bangladesh, where microcredit programs are not significantly employed, data for ...
  • Prediction of Bangladeshi Urban Children’s Mental Health for the Effect of Mobile Gaming Using Machine Learning 
    Hasan, Tanveer; Bonny, Moushumi Zaman; Das, Rajesh Kumar; Sultanaa, Salma; Islam, Md. Touhidul; Sattar, Abdus (Wolters Kluwer Health, Inc., 2024-06-30)
    The popularity of mobile gaming is increasing globally, fueled by technological advancements, high-quality smartphones with gaming features, and widespread internet access. A large number of young people and also children ...
  • Predictive Modeling for Breast Cancer Classification in the Context of Bangladeshi Patients by Use of Machine Learning Approach with Explainable Ai 
    Islam, Taminul; Sheakh, Md. Alif; Tahosin, Mst. Sazia; Hena, Most. Hasna; Akash, Shopnil; Jardan, Yousef A. Bin; Wondmie, Gezahign Fentahun; Nafidi, Hiba‑Allah; Bourhia, Mohammed (Springer Nature, 2024-04-11)
    Breast cancer has rapidly increased in prevalence in recent years, making it one of the leading causes of mortality worldwide. Among all cancers, it is by far the most common. Diagnosing this illness manually requires ...

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