DIU Institutional Repository: Recent submissions

  • Massilia agrisoli sp. nov., Isolated From Rhizospheric Soil of Banana 
    Huq, Md. Amdadul; Ma, Juncai; Srinivasan, Sathiyaraj; Parvez, Md. Anowar Khasru; Rahman, M. Mizanur; Naserkheil6​, Masoumeh; Abuhena, Md.; Maitra, Pulak; Islam, Fahadul; NAM, Kihong; Park, Jong-Hyun; Akter, Shahina (The ICSP and the BAM division of the IUMS., 2023-01-15)
    A Gram-stain-negative, aerobic, short rod-shaped and motile novel bacterial strain, designated MAHUQ-52T, was isolated from the rhizospheric soil of a banana plant. Colonies grew at 10–35 °C (optimum, 28 °C), pH 6.0–9.5 ...
  • Local bird species classification using advanced deep learning architecture 
    Sourov, Md. Abugalib (Daffodil International University, 2024-01-01)
    The goal of this research is to create a reliable system for classifying local bird species using modern deep learning architectures. The dataset forms the basis for this study and consists of 1,179 photos covering seven ...
  • A proposed deep learning approach for Bangla handwritten character recognition 
    Mahmud, Shadhin (Daffodil International University, 2024-01-24)
    The present research on Bangla Handwritten Character Identification investigated a wide range of deep learning architectures, including DenseNet201, VGG19, MobileNetV2, ResNet101, CNN01, and CNN02, and evaluated their ...
  • Bangladeshi Rice & Tea Leaf Disease Detection Using Machine Learning 
    Rakib, Md. (Daffodil International University, 2024-01-01)
    Bangladesh's economy is based primarily on agriculture, with the production of tea and rice being essential to maintaining livelihoods and food security. The persistent risk of illnesses in rice and tea plants, however, ...
  • Network management & security system of Globaltech 
    Khatun, Mst. Aklima (Daffodil International University, 2024-01-26)
    This Internship on “Network Management & Security System of Globaltech”, Today's computer networks have gone from typically being a small local area network to wide area networks. With continuous growth of the networking, ...
  • Mapping Out the Vulnerabilities of Migrant Women in the Informal Sector: A Qualitative Investigation in Dhaka City 
    Sifullah, Md. Khaled; Sohel, Md. Salman; Sarker, Md. Fouad Hossain; Islam, Muhaiminul; Ahmad, Maruf; Rahman, Md Motiur (Elsevier, 2023-10-12)
    The current study seeks to explore the vulnerabilities typically encountered by female migrants in the informal sector in Dhaka city. It used a qualitative research approach, purposively selecting four areas from Dhaka ...
  • Managing the Invisible Threat of Microplastics in Marine Ecosystems: Lessons From Coast of the Bay of Bengal 
    Mubin, Al-Nure; Arefin, Shahoriar; Mia, Md. Sonir; Islam, Abu Reza Md. Towfiqul; Bari, A.B.M. Mainul; Islam, Md. Saiful; Ali, Mir Mohammad; Siddique, Md. Abu Bakar; Rahman, M. Safiur; Senapathi, Venkatramanan; Idris, Abubakr M.; Malafaia, Guilherme (IEEE, 2023-09-01)
    Invisible microplastics (MP) have become a significant problem worldwide in recent years. Although many studies have highlighted the sources, effects, and fate of MPs pollution on various ecosystems in developed countries, ...
  • Machine Learning-Based Technique for Resonance and Directivity Prediction of UMTS LTE Band Quasi Yagi Antenna 
    Haque, Md. Ashraful; Saha, Dipon; Al-Bawri, Samir Salem; Paul, Liton Chandra; Rahman, Md Afzalur; Alshanketi, Faisal; Alhazmi, Ali; Rambe, Ali Hanafiah; Zakariya, M.A.; Hashwan, Saeed S. Ba (Elsevier, 2023-09-01)
    In this study, we have presented our findings on the deployment of a machine learning (ML) technique to enhance the performance of LTE applications employing quasi-Yagi-Uda antennas at 2100 MHz UMTS band. A number of ...
  • Machine Learning-Based Technique for Gain and Resonance Prediction of Mid Band 5G Yagi Antenna 
    Haque, Md. Ashraful; Rahman, Md Afzalur; Al‑Bawri, Samir Salem; Yusoff, Zubaida; Sharker, Adiba Haque; Abdulkawi, Wazie M.; Saha, Dipon; Paul, Liton Chandra; Zakariya, M. A. (Springer, 2023-08-03)
    In this study, we present our findings from investigating the use of a machine learning (ML) technique to improve the performance of Quasi-Yagi–Uda antennas operating in the n78 band for 5G applications. This research study ...
  • Machine Learning Technique Based Fake News Detection 
    Sutradhar, Biplob Kumar; Zonaid, Md.; Ria, Nushrat Jahan; Noori, Sheak Rashed Haider (IEEE, 2023-01-15)
    False news has received attention from both the general public and the scholarly world. Such false information has the ability to affect public perception, giving nefarious groups the chance to influence the results of ...
  • Machine Learning Modeling for Reconditioned Car Selling Price Prediction 
    Abdullah, Fatema; Rahman, Md. Ataur; Shidujaman, Mohammad; Hasan, Mahady; Habib, Md. Tarek (SPIE Publications, 2023-09-19)
    Almost 80% of the vehicles required for Bangladesh's road transportation industry are supplied by reconditioned cars. Using machine learning (ML) to predict car prices refers to using ML algorithms and techniques to make ...
  • Machine Learning-Based Model to Predict Heart Disease in Early Stage Employing Different Feature Selection Techniques 
    Biswas, Niloy; Ali, Md Mamun; Rahaman, Md Abdur; Islam, Minhajul; Mia, Md. Rajib; Azam, Sami; Ahmed, Kawsar; Bui, Francis M.; Al-Zahrani, Fahad Ahmed; Moni, Mohammad Ali (Hindawi Publications, 2023-05-02)
    Almost 17.9 million people are losing their lives due to cardiovascular disease, which is 32% of total death throughout the world. It is a global concern nowadays. However, it is a matter of joy that the mortality rate due ...
  • Machine Learning-Based Depression Detection 
    Biswas, Saikat; Islam, Md.Mozahidul; Sarker, Utpaul; Hridoy, Rashidul Hasan; Habib, Md. Tarek (Springer Nature, 2023-04-14)
    Depression is an extremely serious illness of humans which causes constant mood swings and feelings of sadness. Nowadays, it is considered to be a deadly disorder in the world. At present, everyone from young to old is ...
  • Machine Learning-Based Approach for Predicting Diabetes Employing Socio-Demographic Characteristics 
    Rahman, Md. Ashikur; Abdulrazak, Lway Faisal; Ali, Md. Mamun; Mahmud, Imran; Ahmed, Kawsar; Bui, Francis M. (MDPI Publications, 2023-10-29)
    Diabetes is one of the fatal diseases that play a vital role in the growth of other diseases in the human body. From a clinical perspective, the most significant approach to mitigating the effects of diabetes is early-stage ...
  • Machine Learning Approach on Multiclass Classification of Internet Firewall Log Files 
    Rahman, Md Habibur; Islam, Taminul; Rana, Md Masum; Tasnim, Rehnuma; Mona, Tanzina Rahman; Sakib, Md. Mamun (IEEE, 2023-01-15)
    "Firewalls are critical components in securing communication networks by screening all incoming (and occasionally exiting) data packets. Filtering is carried out by comparing incoming data packets to a set of rules ...
  • MRIAD: A Pre-clinical Prevalence Study on Alzheimer’s Disease Prediction Through Machine Learning Classifiers 
    Loba, Jannatul; Mia, Md. Rajib; Mahmud, Imran; Mahi, Md. Julkar Nayeen; Whaiduzzaman, Md.; Ahmed, Kawsar (Springer Nature, 2023-08-31)
    Alzheimer’s disease (AD) is a neurological illness that worsens with time. The aged population has expanded in recent years, as has the prevalence of geriatric illnesses. There is no cure, but early detection and proper ...
  • MRI-Based Brain Tumor Classification Using Various Deep Learning Convolutional Networks and CNN 
    Saiful, Md.; Haider, Sakib; Rahman, S. M. Arafat; Reza, Nahid; Reza, Ahmed Wasif; Arefin, Mohammad Shamsul (Springer Nature, 2023-11-11)
    "Yearly, brain tumors cause many fatalities and a significant portion of these victims come from rural regions. However, beginning brain tumor diagnosis technology is not as effective as anticipated. We thus set out to ...
  • MEDIC: A Multi-Task Learning Dataset for Disaster Image Classification 
    Alam, Firoj; Alam, Tanvirul; Hasan, Md. Arid; Hasnat, Abul; Imran, Muhammad; Ofli, Ferda (Springer Nature, 2022-09-03)
    Recent research in disaster informatics demonstrates a practical and important use case of artificial intelligence to save human lives and suffering during natural disasters based on social media contents (text and images). ...
  • MCNN-LSTM: Combining CNN and LSTM to Classify Multi-Class Text in Imbalanced News Data 
    Hasib, Khan Md.; Azam, Sami; Karim, Asif; Marouf, Ahmed Al; Shamrat, F M Javed Mehedi; Montaha, Sidratul; Yeo, Kheng Cher; Jonkman, Mirjam (IEEE, 2023-08-29)
    "Searching, retrieving, and arranging text in ever-larger document collections necessitate more efficient information processing algorithms. Document categorization is a crucial component of various information ...
  • Lupenone, a Wonder Chemical Obtained From Euphorbia segetalis To Boost Affinity for the Transcriptional Factor Escalating Drought-Tolerance in Solanum lycopersicum 
    Debnath, Sandip; Alqahtan, Taha; Alqahtan, Ali; Alharb, Hanan M.; Akash, Shopnil (PLOS ONE Publications, 2023-11-08)
    Drought is the single greatest abiotic factor influencing crop yield worldwide. Plants remain in one area for extended periods, making them vulnerable to natural and man-made influences. Understanding plant drought responses ...

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