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Intelligent reflective surfaces in 5G and beyond: optimizing uplink satellite connectivity for IoT
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Research on somatic interactive exhibition design of lacquer artwork based on multi-source data analysis
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183
A Voice-Based Personal Assistant for Mental Health in Kreol Morisien
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184
From Binding-Induced Dynamic Effects in SH3 Structures to Evolutionary Conserved Sectors.
Published 2016-05-01“…Prior experimental NMR work on the SH3 domain of Src showed that ligand binding induces long-range dynamic changes consistent with an induced fit mechanism. …”
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Unsupervised learning analysis on the proteomes of Zika virus
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Variation-resilient spike-timing-dependent plasticity in memristors using bursting neuron circuit
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ChatGMP: A case of AI chatbots in chemical engineering education towards the automation of repetitive tasks
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The impact of generative AI on essay revisions and student engagement
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191
Assessing Urban functional area delineation: POI data and kde analysis in pekanbaru
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192
Estimating behavioural relaxation induced by COVID-19 vaccines in the first months of their rollout.
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193
Multiple-Feature Construction for Image Segmentation Based on Genetic Programming
Published 2025-05-01“…However, performing accurate segmentation is difficult due to image variations. In this way, this work proposes an automated multiple-feature construction approach for image segmentation, working with magnetic resonance images, computed tomography, and RGB digital images. …”
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A new approach to Health Benefits Package design: an application of the Thanzi La Onse model in Malawi.
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Machine learning approaches for imputing missing meteorological data in Senegal
Published 2025-09-01“…In contrast, DT performance declined sharply with increased data loss, and OK was constrained by the sparse spatial distribution of meteorological stations, notably impairing its ability to impute precipitation (PRCP) and wind speed (WDSP).This work contributes a multivariable imputation framework specifically adapted to West African climatic and infrastructural realities. …”
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A Data-Driven Approach Based on Deep Neural Network Regression for Predicting the Compressive Strength of Steel Fiber Reinforced Concrete
Published 2025-04-01“…A dataset, consisting of 303 samples and 12 predictor variables, is used to train the deep learning approach. Notably, the current work has carried out a comparative study to identify the suitable regularization strategy for establishing a robust SFRC strength estimation model. …”
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