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Preferential flow in soils is key to the development of nebkhas in water limited regions
Published 2025-02-01“…Higher soil organic matter content, total porosity, and thickness of the soil crust in LN all significantly contributed to the development of preferential flow in nebkhas especially under low precipitation conditions. We conclude that a higher degree of preferential flow in nebkhas may enhance their rainwater infiltration capacity and that represents a very important strategy in nebkha adaptation to extremely arid environments.…”
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Detection of UAV GPS Spoofing Attacks Using a Stacked Ensemble Method
Published 2024-12-01“…To address this issue, we propose a detection method based on stacked ensemble learning that combines convolutional neural network (CNN) and extreme gradient boosting (XGBoost) to detect spoofing signals in the GPS data received by UAVs. …”
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Diameter problems for univalent functions with quasiconformal extension
Published 1993-01-01“…This paper utilizes the method of extremal length to study several diameter problems for functions conformal outside of a disc centered at the origin, with a standard normalization, which possess a quasiconformal extension to a ring subdomain of this disc. …”
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MONITORING OF RIVERBANKS AS A PART OF STATE MONITORING OF WATER BODIES: CURRENT STATE AND DEVELOPMENT PROSPECTS
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An analysis of observed and predicted extreme heat and precipitation trends across four pulse producing regions in North America: North Dakota, Montana, Saskatchewan, and Northeast...
Published 2025-01-01“…In this paper, we study two climate-related stressors for pulse production in North America: extreme heat and excess moisture during harvest. Pulses must be dried on the plant before harvest, requiring a 7 day dry spell before harvest or the use of Roundup (glyphosate) to kill the plants quickly. …”
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Pengembangan Auto-AI Model Generatif Analisis Kompleksitas Waktu Algoritma Untuk Data Multi-Sensor IoT Pada Node-RED Menggunakan Extreme Learning Machine
Published 2022-12-01“…The steps in the study are utilized to create a generative model based on the Extreme Learning Machine (ELM) algorithm according to the recording of computational time values on several tests to automate the determination of time complexity equation model of the algorithm in general including the search of best cases, worst cases, and average cases for non-recursive, and base cases and recurrent cases for recursive, as well as algorithms that contain both. …”
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Changement climatique et viticulture en Champagne : du constat actuel aux prévisions du modèle ARPEGE-Climat sur l’évolution des températures pour le XXIe siècle
Published 2010-12-01“…In the aim to find responses concerning temperature evolution (means and daily extremes) in a context of greenhouse concentration rise, daily temperature data calculated by ARPEGE-Climate model (Météo-France) are validated by comparison to Reims-Courcy station on period control from 1950 to 2000. …”
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New data on the distribution of Amaranthus retroflexus and Brassica juncea in Mongolia
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Towards Quantifying the Uncertainty in Estimating Observed Scaling Rates
Published 2022-06-01“…Abstract Short‐duration precipitation extremes (PE) increase at a rate of around 7%/K explained by the Clausius‐Clapeyron relationship. …”
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Effect of bending load on electrical conductivity of carbon/epoxy composites filled with nanoparticles using design of experiment and artificial neural networks
Published 2025-03-01“…Additionally, we determine the bending strength of the specimens using a three-point bending method. We examine the distribution pattern of nanoparticles in the samples through scanning electron microscope images. …”
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