In modern centrifugal pump machines (CPM), a data acquisition system encompassing software- hardware interfacing is essential for parameter recording. The quality of recorded data plays a crucial role and directly influences the data transformation p...
The application of deep learning for semantic segmentation has revolutionized image analysis, particularly in the geospatial and medical fields. UNet, an encoder-decoder architecture, has been suggested to be particularly effective. However, limitati...
Enhancement prediction of load demand is crucial for effective energy management and resource allocation in modern power systems and especially in medical segment. Proposed method leverages strengths of ANFIS in learning complex nonlinear relationshi...
Advanced Persistent Threat (APT) malware attacks, characterized by their stealth, persistence, and high destructiveness, have become a critical focus in cybersecurity defense for large organizations. Verifying and identifying the sources and affiliat...
OBJECTIVE: Accurate evaluation of thyroid nodules is crucial for effective management; however, methods such as ultrasonography and Fine Needle Aspiration Cytology (FNAC) can be subjective and operator-dependent. Indeterminate thyroid nodules (ITNs) ...
Understanding the behavior of microbial consortia is crucial for predicting metabolite production by microorganisms. Genome-scale network reconstructions enable the computation of metabolic interactions and specific associations within microbial cons...
BACKGROUND: While liver transplantation saves lives from irreversible liver damage, it poses challenges such as graft dysfunction due to factors like ischemia-reperfusion (IR) injury, which can lead to significant cellular damage and systemic complic...
Deep learning has revolutionized the classification of land cover objects in hyperspectral images (HSIs), particularly by managing the complex 3D cube structure inherent in HSI data. Despite these advances, challenges such as data redundancy, computa...
Mathematical optimization is fundamental across many scientific and engineering applications. While data-driven models like gradient boosting and random forests excel at prediction tasks, they often lack mathematical regularity, being non-differentia...
In recent years, the number of telecom frauds has increased significantly, causing substantial losses to people's daily lives. With technological advancements, telecom fraud methods have also become more sophisticated, making fraudsters harder to det...
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