Human Performance in Deepfake Detection: A Systematic Review by Klaire Somoray, Dan J. Miller, Mary Holmes

“…Deepfakes refer to a wide range of computer-generated synthetic media, in which a person’s appearance or likeness is altered to resemble that of another. …”
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Cost-efficient behavioral modeling of antennas by means of global sensitivity analysis and dimensionality reduction by Slawomir Koziel, Anna Pietrenko-Dabrowska

“…Abstract Computational tools, particularly electromagnetic (EM) solvers, are now commonplace in antenna design. …”
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Reliability-Based Geotechnical Design Method Using the Gaussian Process Regression–Based Differential Evolution Algorithm by Kai Wen, Zemin Kuang, Wei Zeng, Sanyou Zeng, Yue Qiu

“…We demonstrate the efficacy of our proposed GPR–based DE algorithm through a case study of the Sau Mau Ping rock slope in Hong Kong, highlighting the method’s ability to achieve superior accuracy and substantial computational savings.…”
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A Pipeline for Multivariate Time Series Forecasting of Gas Consumption in Pelletization Process by Thadeu Pezzin Melo, Jefferson Andrade, Karin Satie Komati

“…Although AutoML did not outperform the statistical model in terms of RMSE values, regarding training time, AutoML models were significantly more efficient than the statistical approach, optimizing computational resource usage and enabling faster model adjustments. …”
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Modelo para simulação da dinâmica de nitrato em colunas verticais de solo não saturado A simulation model of nitrate displacement in vertical columns in a non-saturated soil by Jarbas H. de Miranda, Sergio N. Duarte

“…In this connection, the present study had the objective of developing and evaluating a computational model for solute displacement simulation in the soil based on numerical solutions of differential equations describing this displacement. …”
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Does a Greater Hamstring Muscle Thickness Mean a Greater Aponeurosis Thickness? by Chrysostomos Sahinis, Eleftherios Kellis

“…Superficial and deep aponeurosis and muscle thickness were evaluated across the entire length of the ST and BFlh using a computational image segmentation approach, which generated approximately ~360 data points per participant. …”
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Fast, smart, and adaptive: using machine learning to optimize mental health assessment and monitor change over time by Daiana Colledani, Claudio Barbaranelli, Pasquale Anselmi

“…In particular, Machine Learning-based CAT (MT-based CATs) enables adaptive, rapid, and accurate evaluations that are more easily implementable than traditional methods. …”
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Covariant analysis of electromagnetic current on the light cone: exposition with scalar Yukawa theory by Wenyu Zhang, Yang Li, James P. Vary

“…Instead of adopting the conventional Drell-Yan frame ζ = 0, we evaluate the form factor in general frames, and use the frame dependence to quantitatively gauge the loss of the Lorentz covariance. …”
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Advanced Phishing Detection: Leveraging t-SNE Feature Extraction and Machine Learning on a Comprehensive URL Dataset by Taha Etem, Mustafa Teke

“…The proposed method offers substantial benefits in terms of computational efficiency. The feature-extracted dataset requires less processing power; thus, it is well-suited for systems with limited resources. …”
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Adaptive BBU Migration Based on Deep Q-Learning for Cloud Radio Access Network by Sura F. Ismail, Dheyaa Jasim Kadhim

“…The proposed method determines whether to initiate a migration by evaluating resource usage on each compute node and identifies the target node for migration if required. …”
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Tooth size discrepancy in different malocclusion groups in Libya: a pilot study by F Elsheikhi, I Bugaighis, T Hamed

“…Background: Orthodontists need to evaluate intermaxillary tooth size discrepancy (TSD) prior to initiating treatment in order to achieve a stable treatment. …”
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Survey on Image-Based Vehicle Detection Methods by Mortda A. A. Adam, Jules R. Tapamo

“…We analyze widely adopted performance metrics from recent studies, evaluate characteristics and limitations of popular vehicle detection datasets, and explicitly discuss technical challenges, including domain generalization, environmental variability, computational constraints, and annotation quality. …”
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Reliable Process Tracking Under Incomplete Event Logs Using Timed Genetic-Inductive Process Mining by Yutika Amelia Effendi, Minsoo Kim

“…Moreover, the TGIPM algorithm exhibits lower computational cost and more effectively captures parallelism, making it particularly suitable for large and incomplete datasets. …”
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Does improving sleep lead to better mental health? A protocol for a meta-analytic review of randomised controlled trials by Georgina Rowse, Alexander J Scott, Thomas L Webb

“…Hedges’ g and associated 95% CIs will be computed from means and SDs where possible. Following this, meta-analysis will be used to synthesise the effect sizes from the primary studies and investigate the impact of variables that could potentially moderate the effects. …”
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Comparison of human cadaver and blue phantom for teaching ultrasound-guided regional anesthesia to novice postgraduate students of anesthesiology: A randomized controlled trial by Deepanshu Dang, Manoj Kamal, Mritunjay Kumar, Bharat Paliwal, Ashish Nayyar, Pradeep Bhatia, Geeta Singariya

“…Various studies have evaluated different simulation models for training of regional anesthesia (RA). …”
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Time Series Forecasting Based on Temporal Networks Evolution and Dynamic Constraints by Yunlong Peng, Han Li, Xu Han

“…A loss function is constructed by integrating the ability of weighted temporal networks to reconstruct the original time series data and visibility-based constraint features, enabling the computation of predicted values for next time step. …”
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Active Liver Bleed Caught During FAST Exam from Spontaneous Hemangioma Rupture: A Case Report by Raul Rodriguez, Nicole Aviles

“…Introduction: This case highlights the advances that have been made when skilled sonographers using point-of-care ultrasound (POCUS) are able to evaluate for more than free fluid on the focused assessment with sonography in trauma (FAST) exam. …”
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Area integrity index with random rearrangement (AIIRR): A new concept for quantifying disruptive colorations by Masahiko Tanahashi, Min‐Chen Lin, Chung‐Ping Lin

“…The basic AIIRR method successfully evaluated the difference in the strength of the area separation in Metapocyrtus and Pachyrhynchus weevils. …”
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Detection and diagnosis of air compressor faults using weightless neural networks by Anubhab Bhattacharyya, Naveen Venkatesh Sridharan, Aravinth Sivakumar, Sugumaran Vaithiyanathan

“…Following this, the features were divided into separate sets to evaluate the validation, training, and testing accuracies of the WNNs using the WiSARD classifier. …”
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Automating areas of interest analysis in mobile eye tracking experiments based on machine learning by Julian Wolf, Stephan Hess, David Bachmann, Quentin Lohmeyer, Mirko Meboldt

“…We introduce a new machine learning-based algorithm, the computational Gaze-Object Mapping (cGOM), that automatically maps gaze data onto respective AOIs. cGOM extends state-of-the-art object detection and segmentation by mask R-CNN with a gaze mapping feature. …”
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