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Holographic inspired high-performance circular polarized spoof surface plasmon polariton leaky-wave antenna excited by a novel launcher.
Sci Rep
January 2025
Department of Electrical Engineering, Iran University of Science and Technology, Tehran, 16846-1314, Iran.
The holographic technique is one of the simplest methods for designing antennas based on metasurface. This paper presents a spoof surface plasmon polariton (SSPP) leaky-wave antenna (LWA) based on the concept of impedance modulated metasurfaces by the anisotropic holographic technique. Instead of parasitic elements, anisotropic SSPP elements are exploited to achieve radiation with circular polarization.
View Article and Find Full Text PDFHybrid salp swarm maximum power point tracking algorithm for photovoltaic systems in highly fluctuating environmental conditions.
Sci Rep
January 2025
Department of Electrical Engineering, Imam Khomeini Naval Science University of Nowshahr, Nowshahr, Iran.
The maximum power delivered by a photovoltaic system is greatly influenced by atmospheric conditions such as irradiation and temperature and by surrounding objects like trees, raindrops, tall buildings, animal droppings, and clouds. The partial shading caused by these surrounding objects and the rapidly changing atmospheric parameters make maximum power point tracking (MPPT) challenging. This paper proposes a hybrid MPPT algorithm that combines the benefits of the salp swarm algorithm (SSA) and hill climbing (HC) techniques.
View Article and Find Full Text PDFOptimization of a two-stage emergency logistics system considering public psychological risk perception under earthquake disaster.
Sci Rep
December 2024
School of Management Science and Engineering, Shanxi University of Finance and Economics, Taiyuan, 030006, China.
To enhance the level of emergency supplies deployment during earthquake disaster, this study focuses on emergency logistics in China. An integrated two-stage optimization framework is adopted to incorporate demand and time satisfaction indicators into the supply allocation and route optimization models, respectively. Firstly, historical data and seismic monitoring information are used to estimate the number of people affected and to forecast the need for emergency supplies; Secondly, the concept of psychological risk perception and the degree of urgency of requirements are introduced.
View Article and Find Full Text PDFOptimizing VGG16 deep learning model with enhanced hunger games search for logo classification.
Sci Rep
December 2024
Department of Computer Science, Birzeit University, P.O. Box 14, Birzeit, West Bank, Palestine.
Accurate classification of logos is a challenging task in image recognition due to variations in logo size, orientation, and background complexity. Deep learning models, such as VGG16, have demonstrated promising results in handling such tasks. However, their performance is highly dependent on optimal hyperparameter settings, whose fine-tuning is both labor-intensive and time-consuming.
View Article and Find Full Text PDFA framework for modelling desert locust population dynamics and large-scale dispersal.
PLoS Comput Biol
December 2024
Epidemiology and Modelling Group, Department of Plant Sciences, University of Cambridge, Downing Street, Cambridge, United Kingdom.
Article Synopsis
- There is a critical need for mathematical models to enhance surveillance and management of transboundary pest invasions, specifically targeting desert locusts, which pose a significant threat to smallholder farmers.
- The proposed integrated modeling framework predicts locust populations by incorporating various life stages and their movement patterns in search of suitable environments for breeding and feeding.
- This framework combines epidemiological modeling, weather data, and atmospheric transport models, aiming to serve as a practical tool for predicting locust swarm movements during future upsurges.
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