Investigating Brain Lobe Biomarkers to Enhance Dementia Detection Using EEG Data

Information Science, Artificial Intelligence, Medicine, Neurology, Medical Imaging,
Electroencephalogram   Dementia   Alzheimer's Disease   Frontotemporal Dementia   Short-Time Fourier Transform   Convolutional Neural Networks  

Background Introduction Dementia is a global health issue that significantly impacts patients’ quality of life and places a substantial burden on healthcare systems. Alzheimer’s Disease (AD) and Frontotemporal Dementia (FTD) are two common types of dementia, and their overlapping symptoms make accurate diagnosis and targeted treatment development p...

A Multi-Scale Feature Fusion Network Focusing on Small Objects in UAV-View

Information Science, Computer Science, Artificial Intelligence,
Unmanned Aerial Vehicle   Small Object Detection   Feature Fusion   Attention Module   Intersection over Union  

Background Introduction With the rapid development of unmanned aerial vehicle (UAV) technology, low-altitude remote sensing images captured by UAVs have been widely used in tasks such as disaster management, search and rescue. However, small object detection in UAV images remains a challenging problem. Due to the fact that small objects occupy only...

Single-Valued Neutrosophic Distance Measure-Based Merec-Rancom-Wisp for Solving Sustainable Energy Storage Technology Problem

Engineering, Energy Engineering, Information Science, Computer Science, Artificial Intelligence,
Single-Valued Neutrosophic Set   Energy Storage Technology   Distance Measure   Merec Method   Rancom Method   Wisp Method   Multi-Criteria Decision Making  

Academic Background With the continuous growth of global energy demand, Energy Storage Technology (EST) plays a crucial role in mitigating environmental impacts and reducing carbon footprints. EST is not only an essential component of renewable energy but also a key factor in decarbonizing the global energy structure. However, selecting the appropr...

t-norms and t-conorms of symmetrical linear orthopair fuzzy sets and their cognitive applications in multiple-criteria decision-making

Mathematics, Information Science, Artificial Intelligence,
orthopair fuzzy sets   symmetrical linear orthopair fuzzy sets   intuitionistic fuzzy sets   t-norms and t-conorms   addition and scalar multiplication   multiple-criteria decision-making  

Academic Background and Problem Statement In the field of fuzzy sets (Fuzzy Sets, FSs), handling uncertainty is one of the core challenges. Fuzzy sets were first introduced by Zadeh in 1965 and quickly became a hot topic in theoretical and applied research. With the deepening of research, an extended form of fuzzy sets—Orthopair Fuzzy Sets (OFSs)—e...

MediVision: Empowering Colorectal Cancer Diagnosis and Tumor Localization through Supervised Learning Classifications and Grad-CAM Visualization of Medical Colonoscopy Images

Information Science, Artificial Intelligence, Medicine, Medical Imaging, Oncology,
Colorectal Cancer   Colonoscopy   Convolutional Neural Networks   Malignant Tumors   Integrated CNN   Grad-CAM  

Academic Background Colorectal Cancer (CRC) is one of the most common cancers worldwide, particularly among individuals over the age of 50. Early detection and accurate diagnosis are crucial for improving patient survival rates. However, traditional CRC screening methods, such as colonoscopy, rely heavily on the experience and visual judgment of ph...

Comparative Analysis of Hybrid and Ensemble Machine Learning Approaches in Predicting Football Player Transfer Values

Information Science, Computer Science, Artificial Intelligence,
market valuation   international reputation index   football superstars   filtering feature selection   boosting tree regression   metaheuristic optimization algorithms  

Academic Background In modern football economics, a player’s transfer market value is not only determined by their on-field performance but also influenced by factors such as their popularity and social media presence. With the globalization of the football industry, clubs are increasingly relying on data-driven analysis for decision-making in the ...