Laser-Induced Breakdown Spectroscopy vs. Fluorescence Spectroscopy for Olive Oil Authentication by Marios Bekogianni, Theodoros Stamatoukos, Eleni Nanou, Stelios Couris

“…The acquired spectroscopic data were analyzed by several machine learning algorithms, and the constructed predictive models are evaluated thoroughly for their reliability and robustness. …”
Get full text

Design of Gain-Scheduled Lateral Controllers for Autonomous Vehicles by Ákos Bokor, Ádám Szabó, Szilárd Aradi, László Palkovics

“…This study evaluates their effectiveness in real-time navigation scenarios within a simulated environment by applying gain-scheduled linear quadratic regulators and model predictive control. The results show that while traditional controllers, such as Pure Pursuit, perform adequately under constant speed conditions, adaptive model-based algorithms significantly enhance the performance, especially in dynamic driving situations involving speed variations.…”
Get full text

Deep Ocean Learning of Small Scale Turbulence by Ali Mashayek, Nick Reynard, Fangming Zhai, Kaushik Srinivasan, Adam Jelley, Alberto Naveira Garabato, Colm‐cille P. Caulfield

“…Here, we show that supervised machine learning algorithms can be trained on the existing turbulence data to develop skillful predictions of the key properties of turbulence from T, S, Z, and topographic data. …”
Get full text

Application of neural network technology for public opinion analysis by Kyrylo Perevoznyk, Yurii Parzhyn

Get full text

Pediatric anaphylaxis in the emergency department: Performances of dynamic tryptase measurement by Constance Gonzalez, MD, Meng Sun, MSc, Aurélie Morand, MD, PhD, Philippe Minodier, MD, Marc Leone, MD, PhD, Jean-Christophe Dubus, MD, PhD, Joana Vitte, MD, PhD, Moïse Michel, PharmD, PhD

“…A cutoff for sAT/sBT ratio of >1.74 yielded 66.7% sensitivity, 90.0% specificity, 96.8% positive predictive value, and 24.3% negative predictive value. …”
Get full text

Multigoal-oriented a posteriori error control for heated material processing using a generalized Boussinesq model by Beuchler, Sven, Endtmayer, Bernhard, Lankeit, Johannes, Wick, Thomas

“…Therein, error reductions and effectivity indices are consulted to establish the robustness and efficiency of our framework.…”
Get full text

Does Artificial Intelligence Bring New Insights in Diagnosing Phlebological Diseases?—A Systematic Review by Sergiu-Ciprian Matei, Sorin Olariu, Ana-Maria Ungureanu, Daniel Malita, Flavia Medana Petrașcu

“…The future of AI in venous diagnostics is promising, and several areas of development were noted, including AI algorithms embedding directly into ultrasound devices to provide instantaneous diagnostic insights during patient evaluations; combining AI-processed Doppler data with other imaging modalities, such as computed tomography or MRI, for comprehensive assessments; AI usage in order to predict disease progression and tailor treatment strategies based on individual patient profiles; and constructing large-scale, multicenter datasets to improve the robustness and generalizability of AI algorithms.…”
Get full text

Towards Machine Learning Interpretability for Tabular Data with Mixed Data Types by Prativa Pokhrel, Alina Lazar

“…Gradient Boosting (GB) algorithms have been proposed for a variety of automated predictions and classification tasks with applications in many domains. …”
Get full text

Using A One-Class SVM To Optimize Transit Detection by Jakob Roche

“…As machine learning algorithms become increasingly accessible, a growing number of organizations and researchers are using these technologies to automate the process of exoplanet detection. …”
Get full text

A genetic association study of serum acute-phase C-reactive protein levels in rheumatoid arthritis: implications for clinical interpretation. by Benjamin Rhodes, Marilyn E Merriman, Andrew Harrison, Michael J Nissen, Malcolm Smith, Lisa Stamp, Sophia Steer, Tony R Merriman, Timothy J Vyse

“…CRP is increasingly being incorporated into clinical algorithms to compare disease activity between patients and to predict future clinical events: our findings impact on the use of these algorithms. …”
Get full text

Pedotransfer functions for estimating the van Genuchten model parameters in the Cerrado biome by Mariana F. Veloso, Lineu N. Rodrigues, Elpídio I. Fernandes Filho, Carolina F. Veloso, Bruna N. Rezende

“…Multiple Linear Regression (MLR) and four machine learning (ML) algorithms were used to develop the PTFs. The ML algorithms were the Multivariate Adaptive Regression Splines (MARS), Random Forest (RF), Support Vector Regression (SVR), and K Nearest Neighbors (KNN). …”
Get full text

Recent Results on the Use of Artificial Intelligence Techniques Applied to Wireless Power Transfer Systems by Federico Amadei, Michele Quercio, Francesco Riganti Fulginei

“…We explore how ML can optimize the geometric and structural design of WPT coils, predict the optimal parameters for inductive couplers, and enhance coupling efficiency under varying conditions. …”
Get full text

Error Data Analytics on RSS Range-Based Localization by Shuhui Yang, Zimu Yuan, Wei Li

“…The significance of our discovery has two folds: First, we present a general expression for localization error data analytics, which can explain and predict the accuracy of range-based localization algorithms; second, the further study on the general analytics expression and its minimum can be used to optimize current localization algorithms.…”
Get full text

Comparison of tone mapping methods during images processing on liquid crystal displays by A. V. Sycev, A. A. Stepanov, A. G. Smirnov, K. .. Blankenbach

Get full text

Geographical Peer Matching for P2P Energy Sharing by Romaric Duvignau, Vincenzo Gulisano, Marina Papatriantafilou, Ralf Klasing

“…Significant cost reductions attract ever more households to invest in small-scale renewable electricity generation and storage. …”
Get full text

Complex Therapy for Intraoperative Blood Loss during Pelvic Bone Repair by Z. G. Marutyan, Yu. V Nikiforov, A. B. Kazantsev, A. A. Ter-Grigoryan

“…Objective: to introduce blood saving technologies and to develop algorithms for management of patients with pelvic fractures. …”
Get full text

Improved Key Microbial Biomarker Discovery Using Ensemble Statistical Methods by Walter Pirovano, Yashjit Gangopadhyay, Mirna Lilian Baak, Christiaan Arie de Leeuw, Radhika Bongoni, Eline Suzanne Klaassens

“…However, advanced biostatistical analysis is required to properly combine microbiome taxonomic abundance data with phenotypical metadata and reliably predict disease states. While differential abundance analysis and machine-learning techniques are widely used to perform such analyses, selecting the best method is not trivial due to the complexity and specific characteristics of both the data and the algorithms. …”
Get full text

Mathematical Modelling and Optimisation of Operating Parameters for Enhanced Energy Generation in Gas Turbine Power Plant with Intercooler by Anthony O. Onokwai, Udochukwu B. Akuru, Dawood A. Desai

“…The study demonstrated the potential of extending metaheuristic algorithms to provide sustainable solutions to energy system problems and reduced emissions through gas turbine power plant (GTPP) optimisation.…”
Get full text

Tracking Secondary Raw Material Operational Framework—DataOps Case Study by Gabriel Pestana, Marisa Almeida, Nelson Martins

“…It enhances supply chain transparency through digital traceability, promotes predictive material sourcing, and streamlines logistics via algorithmic optimization. …”
Get full text

Web Application for Mathematical Modeling of Unsteady Oil Flow in Porous Medium by A. A. Mazitov

“…The analysis and interpretation of hydrodynamic research data are based on theoretical models and computational algorithms. Despite the demand for this topic, numerous issues related to unsteady fluid flows in oil reservoirs still require solutions. …”
Get full text