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Mobile Ad-Hoc Networks (MANET) is a type of ad-hoc networks which use less infrastructure, that means the nodes in this network forward the massages without the need of infrastructure such as routers, switches etc. One o...

This work primarily focuses on diagnosis of heart disease before explicit visit to the expert doctor. Machine learning based systems have been found useful in medical diagnosis applications because of their ability to le...

Abstract The accurate prediction of the deterioration of Continuously Reinforced Concrete Pavement (CRCP) is essential for the effective management of pavements and the maintenance of infrastructure. In this study, a co...

Climate change presents significant challenges to ecosystems, economies, and societies globally. In Malaysia, a tropical country highly dependent on its natural resources, the impacts are evident in altered rainfall patt...

The COVID-19 pandemic has placed enormous strain on providing health care services internationally while reinforcing the argument for the need to strengthen forecasting techniques. Existing forecasting methods have drawb...

Financial institutions worldwide face significant challenges in detecting and preventing illicit financial activities, such as money laundering and terrorism financing. Traditional rule-based methods often generate high ...

Abstract Proposed research presents a data-driven framework for forecasting municipal solid waste (MSW) generation and emission dynamics in Erode City, India, by employing supervised machine learning algorithms. Leveragi...

Car classification is important in daily life because there are many distinct types of automobiles made by various manufacturers. Although there are numerous methods for classifying autos, machine learning technologies h...

Mobile Legends: Bang Bang (MLBB) has become a significant phenomenon within the global e-sports landscape, attracting millions of active players and fans. This study presents a comprehensive sentiment analysis and topic ...

ObjectiveTo develop an accurate and efficient binary classification model for predicting the binding capacity of endocrine-disrupting chemicals （EDCs） to the G protein-coupled estrogen receptor （GPER）.MethodsGPER...

This study examines the relationship between Sustainable Development Goals (SDGs) compliance and financial performance in Malaysian banks from 2013 to 2022. Using advanced machine learning techniques, including Support V...

Understanding how consumers behave in e-commerce is essential for businesses, especially in today’s digital world where people rely heavily on online shopping platforms. A key part of this understanding comes from sent...

Abstract High-throughput analysis of EEG data has significantly contributed to understanding neural dynamics in Alzheimer’s disease diagnosis. However, the complexity and high dimensionality of EEG signals pose challen...

"Falls pose a significant health risk to older adults, often resulting in serious injuries and reduced independence. This study explored two machine learning approaches for detecting falls using data from wearable sensor...

"La predicción del contenido de carbono orgánico total (COT) es un indicador crucial para evaluar las características geoquímicas de las rocas madre. Aunque los enfoques basados en regresión múltiple y la clasifica...