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The shift from conventional irrigation methods to sprinkler systems is intended to improve accuracy and efficiency; however, it requires thorough validation of the uniformity of water distribution. This research focuses ...

Abstract As an integrated application of modern information technologies and artificial intelligence, Prognostic and Health Management (PHM) is important for machine health monitoring. Prediction of tool wear is one of t...

Extensive research has demonstrated that music enhances cognitive functions, such as learning, reasoning, and memory. This study investigated the influence of music on short- and long-term memory while learning through t...

Abstract A good wireless network design depends on technical and financial viability and a number of other criteria that must be met. Following the emergence of new technologies and services, such as 5G transmission and ...

Oil spill monitoring in port and maritime environments is essential for environmental protection and emergency response. However, precise segmentation from UAV-captured optical imagery is still difficult due to specular ...

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...

Abstract The precise forecasting of the Remaining Useful Life (RUL, expressed in hours) of aircraft engine-like systems using a synthetic dataset designed to mimic real engine degradation patterns is a key factor in sett...

Digital health increasingly relies on artificial intelligence for clinical decision-making, patient management, and distributed learning, yet two persistent challenges remain: the computational complexity of optimization...

Robot Operating System (ROS) is a middleware widely used in robotics development. ROS simplifies communication between nodes within a network so that robot developers are able to simply develop robot applications. Howeve...

Camera rigs for Advanced Driver Assistance Systems (ADAS) are subject to design choices of each vehicle variant; therefore, ADAS algorithms should be rig-invariant or tunable with limited additional data. Recently, the A...

Question-answering (QA) has been a crucial NLP (Natural Language Processing) task for a long time. As an umbrella term, QA has multiple sub-tasks under its hood. Question classification (QC) is one of the most important ...

Arid and semi-arid lands (ASALs) like Marsabit and Isiolo Counties in Kenya face significant water scarcity, necessitating accurate mapping of surface water resources. Even with mostly dry and arid conditions in these re...

Time series analysis is essential for finance, transportation, energy, healthcare, and climate research. While time-frequency domain representation underpins effective time series modeling, its holistic utilization and i...

Convolutional neural networks (CNNs) and visual Transformers have become the dominant approaches for hyperspectral image (HSI) classification due to their powerful feature representation capabilities. However, CNNs are l...

Abstract Visualization of three-dimensional image stacks from serial sectioned histology or from other modalities poses a challenge, and solutions are often limited to projections or to rotated views of the 3D stacks. He...

Gold mining plays a central role in Ghana’s national economy. However, conventional exploration approaches, particularly within artisanal and small‑scale mining sectors, often rely on trial‑and‑error methods ...

Salinity distribution is a critical determinant in the management of water resources and the protection of ecological integrity in coastal regions, drawing particular concerns in the context of increasing saltwater intru...

Road traffic crashes are among the leading causes of death and injury worldwide. While urban planning and design are known to influence road safety, it is not clear how features of the built environment contribute to tra...

Abstract Accurate and reliable wind power forecasting models are essential for the optimal dispatch of power systems. However, existing methods still face several challenges, including ineffective signal decomposition, l...

Feature selection is an important problem for pattern classification systems. We study how to select good features according to the maximal statistical dependency criterion based on mutual information. Because of the dif...

A major assumption in many machine learning and data mining algorithms is that the training and future data must be in the same feature space and have the same distribution. However, in many real-world applications, this...

Since the classical molecular dynamics simulator LAMMPS was released as an open source code in 2004, it has become a widely-used tool for particle-based modeling of materials at length scales ranging from atomic to mesos...

BACKGROUND: Synthesis of multiple randomized controlled trials (RCTs) in a systematic review can summarize the effects of individual outcomes and provide numerical answers about the effectiveness of interventions. Filter...