Gear fault detection, diagnosis, and classification are critical yet challenging
tasks due to the similarity in spectral features among various gear fault types.
This study presents an automated approach for detecting, ...
Deep neural networks (DNNs) have grown increasingly large
and complex, which requires effective optimization techniques to improve
efficiency and scalability. Sparsity has emerged as a primary and widely adopted
optimization ...
This paper presents a novel approach for determining the optimal placement
and sizing of photovoltaic (PV) systems in power distribution networks. The
proposed methodology employs Particle Swarm Optimization (PSO) to ...
New public health issue (COVID-19) was beginning to emerge in the latter part
of 2019 with a risk that specifically affected diabetics. The use of algorithm-
based methods and artificial intelligence to help clinical ...
Integrating Artificial Intelligence (AI) in English as a Foreign Language (EFL)
education fundamentally reshapes traditional pedagogical frameworks, offering
new avenues for enhancing language acquisition and improving ...
This article examines how artificial intelligence (AI) is becoming an integral part
of modern industries, revolutionizing and improving existing processes. By
automating key tasks and leveraging vast amounts of data, AI ...
The expansion of the Internet of Things (IoT) has introduced transformative
possibilities by connecting diverse devices, from small-scale sensors to complex
systems. However, this connectivity also brings substantial ...
Early and accurate brain tumor detection is critical for effective treatment
planning and improving patient outcomes. Traditional diagnostic methods, such
as biopsies, are invasive and can delay timely intervention. This ...
This study addresses the need for rapid and accurate COVID-19 diagnosis by
utilizing Convolutional Neural Networks (CNNs) on CT chest images. Given the
limitations of traditional RT-PCR testing, CT imaging has emerged ...
Weather prediction is a crucial tool for a wide range of applications, including
ag-riculture, transportation, and disaster preparedness and response. It remains
one of the most complex scientific and technological ...
Arrhythmias, defined as irregular heartbeats, play a vital
role in the early detection of heart disorders using Electrocardiogram (ECG)
signals, which capture the heart’s electrical activity and offer valuable insights
into ...
Skin cancer, one of the fastest-growing cancer types globally, includes both
benign and malignant forms. Recent advances in artificial intelligence have
enabled the early detection of various diseases with high accuracy, ...
This study addresses the forecasting of Key Performance Indicators (KPIs) in
LTE net-works through a comparative analysis of advanced machine learning
and statistical models, specifically the Gated Recurrent Unit (GRU) ...
he exponential development of digital technology exposes systems to
increasingly high security risks, making intrusion detection a major issue in this
context. In this study, the authors present a two-step approach. ...
Lung cancer remains a leading cause of cancer mortality, emphasizing the
importance of early and accurate diagnosis. This study proposes an attention-
based CNN model to enhance lung cancer classification from CT scans. ...
Recent studies have focused on leveraging artificial neural networks (ANNs) to
optimize the formulation of pharmaceutical drug micro-emulsions, specif-ically
targeting the ideal composition of surfactants, co-surfactants, ...
Healthcare fraud remains a major financial burden, requir-
ing precise and efficient detection methods. Traditional machine learning
(ML) models often face limitations due to redundant features and dataset
imbalance, ...