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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Counselling Career with Artificial Intelligence: A Systematic Review by Rifqi Muhammad, Patriana Patriana, Yusrain Yusrain, Astaman Astaman, Manja Manja

“…Objectives: career prediction, career matching with companies, career selection, career guidance, and career decision-making. …”
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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

“…To leverage the strengths of these individual models, three ensemble methods are explored, that includes supervised ensembling with XGBoost, unsupervised ensembling with the DBSCAN algorithm, and mathematical aggregation using weighted averaging. …”
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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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Automatic detection of pupil reactions in cataract surgery videos. by Natalia Sokolova, Klaus Schoeffmann, Mario Taschwer, Stephanie Sarny, Doris Putzgruber-Adamitsch, Yosuf El-Shabrawi

“…We employ a Mask R-CNN architecture as a segmentation algorithm to segment the pupil and iris with pixel-based accuracy and then track their sizes across the entire video. …”
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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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Quasi-preview control: A novel method for active structural vibration control subject to seismic disturbances using adaptive filters and multiple remote seismic observations by Shinya FUJIMURA, Tomohiro WATANABE, Kazuhiko HIRAMOTO

“…The performance index involves the one-step-ahead prediction of the structural response obtained by the model of the structural system and the control input candidate to perform the switching action. …”
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An integrated bioinformatic investigation of succinic acid metabolism related genes in ccRCC followed by preliminary validation of SLC25A4 in tumorigenesis by Dong Yue, Fengyun Dong, Sen Wang, Miao Zheng

“…Our study reveals that succinate metabolism-related biomarkers can provide a basis for exploring the prediction of prognosis in ccRCC.…”
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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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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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Deep Learning to Estimate Model Biases in an Operational NWP Assimilation System by Patrick Laloyaux, Thorsten Kurth, Peter Dominik Dueben, David Hall

“…Abstract Model bias is one of the main obstacles to improved accuracy and reliability in numerical weather prediction conducted with state‐of‐the‐art atmospheric models. …”
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Machine Learning Advancements in Urban Traffic Simulation: A Comprehensive Survey by Harshit Maheshwari, Li Yang, Richard W. Pazzi

“…Urban traffic simulation is useful in many ways to understand, manage, and predict the growing complexities of traffic dynamics within a city. …”
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A Case Study on Integrating an AI System into the Fuel Blending Process in a Chemical Refinery by Abdul Gani Abdul Jameel

“…This work discusses a case study of a hybrid artificial intelligence (AI)-based method for gasoline blending based on a genetic algorithm (GA) combined with an artificial neural network (ANN). …”
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