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This article examines the concept of Generative Engine Optimization (GEO) in the context of the transformations enabled by the integration of generative artificial intelligence into contemporary information search an...

Abstract Generative artificial intelligence is reshaping how researchers discover protein-binding compounds and develop them into drug candidates. Unlike traditional methods that screen existing molecules, structure-base...

Line breeding programs of autogamous crops like barley and wheat are characterized by multiple crosses with high variability in cross means and segregation variances. From theory of order statistics, we derived formulas ...

Abstract In rural areas, unreasonable access of distributed photovoltaic (DPV) may pose a significant challenge to the safe operation of the power network. To address this, determining the maximum hosting capacity of net...

Endurance versus payload in UAVs is a direct trade-off governed by airframe mass and structural efficiency. Generative design (GD) and topology optimization (TO) are increasingly used to develop lightweight, high-perform...

Access to reliable and sustainable power generation in remote areas is a critical challenge faced by many regions worldwide. In such areas, hybrid energy systems integrating solar, wind, and battery components have emerg...

The integration of solar energy into modern power grids supports sustainability and energy efficiency but also introduces power quality (PQ) challenges such as harmonic distortion, voltage sag, swell, and fluctuations. I...

Due to the limitation of lacking elevation resolution, ground-based interferometric radar suffers from serious layover problem when applied to building deformation monitoring. Ground-based tomographic arc-scanning synthe...

In this paper, a near-field integrated sensing and communication (ISAC) using a multi-waveguide pinching antenna system (PASS) is proposed, where discrete radiating particles are flexibly clamped along multiple dielectri...

In this study, a new methodology is developed to optimize cold chain distribution routes of agricultural products with a view to reducing the costs of distribution. It develops a mathematical model that considers multipl...

Abstract Background Optimization of biotechnological processes is traditionally limited by time-consuming trial-and-error approaches and the complexity of simultaneously optimizing multiple, often conflicting objectives....

Electric Discharge Machining (EDM) is a non-traditional machining process that utilizes electric sparks between an electrode and a workpiece submerged in a dielectric fluid to ablate a material. It is commonly used in di...

Abstract Friction Stir Welding (FSW) is a reliable solid-state joining technique for aluminium alloys, where conventional fusion welding often causes porosity, solidification cracking, and excessive heat-affected softeni...

Introduction. Nowadays, the most widely used wind energy conversion system in wind farms is based on a doubly fed induction generator (DFIG); it has a large speed range and can function in multiple modes. Problem. Harmon...

Introduction. Metaheuristic algorithms are effective for solving complex power system optimization problems characterized by nonlinearity, multimodality, and high dimensionality. Nature-inspired strategies based on adapt...

Hypertension is a major chronic disease worldwide and in Iraq. Baghdad especially suffers from it due to rapid urbanization, dietary changes, and lifestyle shifts. We lack local data on hypertension factors in Baghdad co...

BackgroundLast-mile logistics accounts for approximately 28% of total logistics costs and is a major contributor to urban carbon emissions. The integration of drones with electric trucks offers a path toward more efficie...

To address the issues of low solution accuracy, premature convergence, and susceptibility to local optima in the Parrot Optimization (PO) algorithm, a Reinforced Multi-strategy Parrot Optimization (RMPO) algorithm has be...

Background: Deep learning has transformed medical imaging by enabling earlier and more accurate disease diagnosis. Lesion and tumor segmentation, essential for analyzing and tracking morphological changes, is commonly do...

The genetic algorithm (GA) is a widely recognized optimization technique for addressing complex and NP-hard problems; however, its effectiveness is often hampered by issues such as premature convergence and population di...

Abstract Feature selection is a critical step in machine learning, as it helps minimize redundant features, thereby enhancing model performance and interpretability. In practice, partially labeled datasets are common. Wh...

Implicit learning is a fundamental cognitive process whose identification is critical for understanding human cognition and developing innovative training methodologies. We propose a generalizable feature selection and s...

Abstract Grid-connected renewable energy systems with high penetration rates exacerbate frequency fluctuations in microgrids, making traditional control methods ill-suited for random source-load variations. This paper pr...

This paper proposes an innovative automated multiphysics Microelectromechanical systems (MEMS) co-optimization platform integrating the embedded reduced-order modeling offered by Coventor MEMS+ with MATLAB’s numerical ...