Daffodil International University

Congestion Propagation Identification and Prediction Using Self Attention–Based Diffusion Convolutional Approach

Abstract Traffic congestion frequently propagates among the interconnected road networks over time, driven by spatial and temporal factors. Identifying and predicting these patterns is crucial for effective public transport management and urban planning. Existing systems often fa...

Triple band Yagi antenna design and performance prediction for next generation (6G) wireless applications using supervised regression models

This study presents a high-performance Yagi antenna designed for sub-terahertz (sub-THz) and terahertz (THz) wireless communication applications, addressing the growing demands of emerging technologies such as high-resolution imaging, short-range secure communication, sensing, sp...

Detection of cardiovascular conditions using ECG image analysis: an evaluation of DenseNet121, InceptionV3, and a hybrid deep learning model

Cardiovascular diseases remain a leading cause of mortality worldwide, necessitating rapid and accurate diagnostic tools. Electrocardiogram (ECG) image analysis using deep learning offers a promising avenue for automated detection, yet model performance and generalizability requi...

Environmental Transparency Through Digital Transformation: Evidence on Carbon Disclosure Quality From China's Heavy‐Polluting Firms

ABSTRACT The rise of digital transformation (DT) has become an important driver of transparency in corporate environmental disclosure. Whether and how DT is related to the improvement of carbon information disclosure quality, particularly in heavily polluting firms that may have...

Quality by Design‐Guided Transethosomal Gel of Donepezil Hydrochloride and Quercetin for Potential Alzheimer's Management: Stability‐Indicating Eco‐Compatible RP‐HPLC Method

ABSTRACT Alzheimer's disease requires innovative therapeutic strategies that not only alleviate symptoms but also protect neurons. Donepezil hydrochloride, a cholinesterase inhibitor, and quercetin, a potent antioxidant, were co‐formulated into a transethosomal gel to enhance bra...

Integrated prognostic framework for survival status, Cancer stages and time estimation in hepatocellular carcinoma using machine learning approaches

Current medical limitations in assessing cancer survival status, stage, and duration necessitate advancements beyond physical indicators and conventional diagnostic techniques. Improving the quality of patient treatment is an ongoing objective of the medical community. Accurate p...

MDCV : Multimodal Deceptive Clickbait Video Detection Using Transformer‐Based Model in Bangla

The proliferation of internet usage has made people increasingly dependent on it. Some fraudulent content makers make the content in an intriguing way that engenders users' curiosity. However, after clicking, they are deceived, which wastes users' time and degrades the credibilit...

End-of-life planning and its governing policies: a comparison of New South Wales public health facility documents

OBJECTIVE: This desktop/scoping document review aimed to determine differences in availability, content, definitions, and terminology used in NSW Health policy documents that pertained to end-of-life planning. METHODS: A desktop/scoping comparative analysis of identified document...

Quad port MIMO antenna design for WLAN and N78 application using regression machine learning validation

This paper presents the design and analysis of a compact four-port MIMO antenna intended for 5G communication systems, specifically targeting the n78 band (3.5 GHz) and the WLAN band (5.25 GHz). The proposed antenna has dimensions of 88.2 mm × 88.2 mm (1.03λ 0 × 1.03λ 0 ). It ach...

Optimized Boosting machine learning approaches for tensile strength prediction and failure classification of mono, bi and tri fiber reinforced composites

Fiber reinforced composites (FRCs) are important to aerospace, automotive and marine industries because of their good strength-to-weight ratio and flexibility in design. However, their highly reliable design is defined by a complex interaction of numerous processing parameters wh...

AI-Driven Automated Phishing and Malware Detection Framework Using Deep Learning

With the rapid evolution of artificial intelligence and digital connectivity, cyber threats have grown increasingly sophisticated, presenting severe security challenges to individuals and enterprises alike. Traditional signature-based detection mechanisms often fail against zero-...

AI-Driven Automated Phishing and Malware Detection Framework Using Deep Learning

With the rapid evolution of artificial intelligence and digital connectivity, cyber threats have grown increasingly sophisticated, presenting severe security challenges to individuals and enterprises alike. Traditional signature-based detection mechanisms often fail against zero-...

Graph-Based Machine Learning for Predicting Drug–Drug Interactions: A Systematic Review

Background/Objectives: Drug–drug interactions (DDIs) are major medication-safety concerns, and experimental testing cannot cover the expanding number of drug pairs. This systematic review evaluates graph-based machine-learning methods for DDI prediction, focusing on machine-learn...

Digital device usage and psychological well-being in the post-COVID-19 era: insights from a cross-sectional survey

Abstract The COVID-19 pandemic accelerated digital technology adoption worldwide, yet limited evidence links post-pandemic multi-purpose online behavior with health outcomes and psychological well-being (PWB) in a single, integrated analysis. This study examines how digital devic...