Noise correlations and neuronal diversity may limit the utility of winner-take-all readout in a pop out visual search task. by Ori Hendler, Ronen Segev, Maoz Shamir

“…The analysis identifies specific response statistics that require further empirical characterization to accurately predict WTA performance in biologically plausible models of visual pop out detection.…”
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Modeling Lane Changes at Freeway On-Ramps With a Novel Car-Following Model Based on Desired Time Headways by Moritz Berghaus, Markus Oeser

“…The model also includes components to predict the lane change start time based on surrogate safety measures and to describe the lateral behavior during the lane change. …”
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3D-Printed PLA Hollow Microneedles Loaded with Chitosan Nanoparticles for Colorimetric Glucose Detection in Sweat Using Machine Learning by Anastasia Skonta, Myrto G. Bellou, Haralambos Stamatis

“…The Random Sample Consensus algorithm was used to train a simple linear regression model to predict glucose concentrations in unknown samples. …”
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Identifying novel risk factors for aneurysmal subarachnoid haemorrhage using machine learning by Jos P. Kanning, Junfeng Wang, Shahab Abtahi, Mirjam I. Geerlings, Ynte M. Ruigrok

“…Using the UK Biobank, we identified aSAH cases via hospital-based ICD codes and analysed 618 baseline variables covering demographics, lifestyle, medical history, and physical measurements. The CatBoost ML algorithm and Shapley Additive Explanations (SHAP) identified the top 25 variables most influential in predicting aSAH. …”
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Use of electrochemical energy storage systems in autonomous power supply systems to reduce fuel consumption of power installations by A. I. Fedotov, E. A. Fedotov, A. F. Abdullazyanov

“…The technique is valid for convex consumption characteristics of power plants. In the context of predicted changes in power profiles (work / weekend days), optimal control scenarios are calculated individually. …”
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The nonlinear impact of cycling environment on bicycle distance: A perspective combining objective and perceptual dimensions by Yantang Zhang, Xiaowei Hu

“…This study uses 2019 cycling data from Shenzhen, China, employing the XGBoost algorithm to uncover the relative importance and thresholds of objective and perceived factors in the cycling environment. …”
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Collaborative optimization of signals and ecological driving speed guidance for buses without dedicated bus lanes in the connected environment by Hui Li, Yunfei Ge, Yuzhou Duan, Xu Zhang

“…Initially, an Extended Kalman Filter is employed to predict the arrival time of buses at intersections and the signal status. …”
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Ensemble learning methods with single and multi-model deep learning approaches for cephalometric landmark annotation by S. Rashmi, S. Srinath, R. Rakshitha, B. V. Poornima

“…The methodology is strategically designed to address the complexities and variations in cephalometric images through a dual learning process: building base learners using end-to-end regression approaches and then constructing a meta-learner that ensembles the output of the base models to obtain collective predictions. Two primary approaches are followed to design base learners: an end-to-end single model and a multi-model strategy for localizing landmarks. …”
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Identification of global main cable line shape parameters of suspension bridges based on local 3D point cloud by Yurui Li, Danhui Dan, Ruiyang Pan

“…Given the strong design prior information available during suspension bridge construction, Bayesian theory is applied to predict and adjust the global line shape of the main cable. …”
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Enhancing depression recognition through a mixed expert model by integrating speaker-related and emotion-related features by Weitong Guo, Qian He, Ziyu Lin, Xiaolong Bu, Ziyang Wang, Dong Li, Hongwu Yang

“…Abstract The World Health Organization predicts that by 2030, depression will be the most common mental disorder, significantly affecting individuals, families, and society. …”
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Shear Capacity of Masonry Walls Externally Strengthened via Reinforced Khorasan Jacketing by Cagri Mollamahmutoglu, Mehdi Ozturk, Mehmet Ozan Yilmaz

“…The Horasan mortar was represented using an elastoplastic Mohr-Coulomb model with a custom softening law (parabolic-to-exponential), calibrated via inverse parameter fitting using the Nelder-Mead algorithm. The numerical predictions closely matched the experimental data. …”
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Modelling Red-Crowned Parrot (Psittaciformes: Amazona viridigenalis [Cassin, 1853]) distributions in the Rio Grande Valley of Texas using elevation and vegetation indices and their... by Elise Varaela Voltura, James L Tracy, J Jill Heatley, Simon Kiacz, Donald J Brightsmith, Anthony M Filippi, Jesús G Franco, Robert Coulson

“…Our ensemble models accurately predicted the three distributions of interest ([Formula: see text] Area Under the Curve [AUC] = 0.904-0.969). …”
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Integration of smart insoles for gait assessment in exoskeleton assisted rehabilitation by Luigi D’Arco, Haiying Wang, Huiru Zheng

“…Gait phases were identified using a Finite State Machine, with transitions guided by predictions from a fuzzy c-means clustering algorithm. …”
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Geoinformatics-based prioritisation of natural resources rich regions at disaggregated levels for sustainable management by T. V. Ramachandra, Paras Negi

“…Landscape dynamics is assessed by classifying temporal remote sensing data using the supervised machine learning (ML) technique based on the Random Forest (RF) algorithm. Additionally, predicting likely land use changes in ecologically fragile areas would help formulate appropriate location-specific mitigation measures. …”
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Power Adaptation for Optimizing Secrecy Energy Efficiency in NOMA-Enabled Underlay Cognitive Radio Networks and DNN-Based Evaluation by P. P. Hema, A. V. Babu

“…Finally, a deep neural network (DNN) framework is developed as an innovative approach to accurately and quickly predict the JOTPA values that meet the desired objectives.…”
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The use of ridge regression for estimating the severity of acute pancreatitis by D. V. Cherdantsev, A. V. Stroev, E. S. Mangalova, N. V. Kononova, O. V. Chubarova

“…Ridge regression was used in combination with an algorithm for sequential reduction of attribute space.Results. …”
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Convolution neural network–based Alzheimer's disease classification using hybrid enhanced independent component analysis based segmented gray matter of T2 weighted magnetic resonan... by Shaik Basheera, M Satya Sai Ram

“…Abstract In recent times, accurate and early diagnosis of Alzheimer's disease (AD) plays a vital role in patient care and further treatment. Predicting AD from mild cognitive impairment (MCI) and cognitive normal (CN) has become popular. …”
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Machine Learning Forecasting of Commercial Buildings’ Energy Consumption Using Euclidian Distance Matrices by Connor Scott, Alhussein Albarbar

“…A Euclidian distance matrix, akin to a K-nearest neighbour algorithm, determines the appropriate neural network(s) to utilise. …”
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Crowdsourced data leaking user's privacy while using anonymization technique by Naadiya Mirbahar Mirbahar, Kamlesh Kumar, Asif Ali Laghari, Mansoor Ahmed Khuhro

“…Five supervised standard learning algorithm classifiers have been utilized to predict the user identity i.e., Extra Tree, Bagging, Decision Tree, Nearest Neighbor (KNN), and Random Forest Tree classifiers. …”
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Multi-fidelity modelling of a high bypass ratio turbofan engine with variable area nozzle by Andrea Magrini, Ernesto Benini

“…By adopting a novel algorithm to match the cycle conditions to the CFD solutions, the propulsive performance of the turbofan is analysed in a reference aircraft mission. …”
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