The Performance of an ML-Based Weigh-in-Motion System in the Context of a Network Arch Bridge Structural Specificity by Dawid Piotrowski, Marcin Jasiński, Artur Nowoświat, Piotr Łaziński, Stefan Pradelok

“…In civil and bridge engineering, they can facilitate the identification of specific patterns through the analysis of data acquired from structural health monitoring (SHM) systems. To evaluate the prediction capabilities of ML, this study examines the performance of several ML algorithms in estimating the total weight and location of vehicles on a bridge using strain sensing. …”
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A Review of Computer Vision Technology for Football Videos by Fucheng Zheng, Duaa Zuhair Al-Hamid, Peter Han Joo Chong, Cheng Yang, Xue Jun Li

“…In the era of digital advancement, the integration of Deep Learning (DL) algorithms is revolutionizing performance monitoring in football. …”
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Systematic review of AI/ML applications in multi-domain robotic rehabilitation: trends, gaps, and future directions by Giovanna Nicora, Samuele Pe, Gabriele Santangelo, Lucia Billeci, Irene Giovanna Aprile, Marco Germanotta, Riccardo Bellazzi, Enea Parimbelli, Silvana Quaglini

“…After article retrieval, a tagging phase was carried out to devise a comprehensive and easily-interpretable taxonomy: its categories include the aim of the AI/ML within the rehabilitation system, the type of algorithms used, and the location of robots and sensors. …”
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Optimized Wireless Sensor Network Architecture for AI-Based Wildfire Detection in Remote Areas by Safiah Almarri, Hur Al Safwan, Shahd Al Qisoom, Soufien Gdaim, Abdelkrim Zitouni

“…The system also integrates artificial intelligence (AI) algorithms (multiclass logistic regression) to process sensor data and predict fire risk levels with 99.97% accuracy, enabling proactive wildfire mitigation. …”
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Review of Urban Rail Transit Ticket Clearing Methods by WANG Yao, LI Jiming, GAO Shen, LIU Guangjie, XU Zhongquan

“…［Method］Through an introduction to urban rail transit ticket clearing schemes in both domestic and foreign cities, the ticket clearing methods for multi-line travel in major Chinese cities are analyzed and compared, and the applicable ticket clearing method is selected through analyzing the advantages and disadvantages of the clearing models and algorithms. ［Result & Conclusion］The one-ticket transfer model commonly used in China relies only on OD (origin and destination) for checking records, making it difficult to fairly and reasonably distribute the fare to multiple operating entities that may be involved. …”
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Assessing CO2 separation performances of IL/ZIF-8 composites using molecular features of ILs by Hasan Can Gulbalkan, Alper Uzun, Seda Keskin

“…The accurate prediction power of these ML models was shown by comparing their estimates with the experimental and simulation data. …”
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Micro hole drilling and multi criteria optimization of soda lime glass via ultrasonic assisted rotary electrochemical discharge drilling by Sahil Grover, Viveksheel Rajput, Sanjay Kumar Mangal, Sarbjit Singh, Sandeep Singh, Shubham Sharma, Ehab El Sayed Massoud, Dražan Kozak, Jasmina Lozanovic

“…Machine learning-based algorithms are also used to predict the responses using Random Forest and Gradient Boost approaches. …”
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MFGC-Net: Bridging and Fusing Multiscale Features and Global Contexts for Multitask Sea Ice Fine Segmentation by Tianen Ma, Xinwei Chen, Linlin Xu, Pengfei Ma, Peilin Yu

“…Sea ice segmentation from synthetic aperture radar (SAR) imagery is a key task in polar sea ice monitoring, which is crucial for global climate prediction and polar route planning. However, the existing sea ice segmentation algorithms for SAR images often fail to consider long-range contextual dependencies when capturing multiscale features, resulting in an inability to fully exploit multiscale global contextual information. …”
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A Review of Recent Advances in Roll Stability Control in On-Road and Off-Road Vehicles by Jie Chen, Ruochen Wang, Wei Liu, Dong Sun, Yu Jiang, Renkai Ding

“…Furthermore, the integration of machine learning and advanced predictive algorithms promises to enhance the intelligence and versatility of roll stability control systems.…”
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Establishment and validation of an immune-related nomogram for the prognosis of pancreatic adenocarcinoma by Kan Wang, Yunkun Lu, Yanfei Cao, Ping Feng, Qiu Wu, Peng Xiao, Yimin Ding

“…This study aims to improve prognosis prediction to guide therapeutic decision-making, and to identify novel targets for immunotherapy of PDAC. …”
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The Use of General Inverse Problem Platform (GRIPP) as a Robust Backtracking Solution by Nikolas Gomes Silveira de Souza, Jader Lugon, Alexandre Macedo Fernandes, Ramiro Joaquim de Jesus Neves, Antônio José da Silva Neto

“…An approach is presented employing the General Inverse Problem Platform (GRIPP) coupled with a General Simulated Annealing (GenSA) algorithm for robust backtracking. This methodology was applied to a hypothetical case study in Guanabara Bay, Brazil, using the MOHID Water platform for hydrodynamic and Lagrangian simulations. …”
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Intelligent design of mixture proportions of manufactured sand concrete from environmental, economical and mechanical perspectives by Junfei Zhang, Changhai Xu, Lei Zhang, Ling Wang

“…This study proposes a multi-objective optimization (MOO) method based on machine learning (ML) and the non-dominated sorting genetic algorithm II (NSGA-II) to optimize MSC mixtures. The results indicate that the extremely randomized trees (ERT) model exhibits the best predictive performance for UCS, with an R value of 0.988 on the test set. …”
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Miniaturized Near-Infrared Analyzer for Quantitative Detection of Trace Water in Ethylene Glycol by Qunling Luo, Zhiqiang Guo, Danping Lin, Boxue Chang, Yinlan Ruan

“…The modeling performances of three algorithms including Support Vector Machine Regression (SVMR), Principal Component Regression (PCR), and Partial Least Squares Regression (PLSR) were systematically evaluated, with PLSR identified as the optimal algorithm. …”
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Thermal-Hydraulic Network Model for steady-state thermal analysis and design of power transformer magnetic cores by L.H. Medeiros, M.M. Oliveira, C.E.G. Falcão, V.C. Bender, T.B. Marchesan

“…Based on the constructive and operational data, the model determines the complete oil flow and temperature distributions over the columns, yokes, and joints by iteratively solving an algorithm composed of hydraulic and thermal resistance networks. …”
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Machine Learning Analysis of Umbilic Defect Annihilation in Nematic Liquid Crystals in the Presence of Nanoparticles by Ingo Dierking, Adam Moyle, Gabriele Maria Cepparulo, Katherine Skingle, Laura Hernández, Juhan Raidal

“…A machine learning methodology based on a YOLO algorithm is trained and optimized to identify defects of strength s = ±1 and determine their trajectories during the annihilation process of umbilics of opposite sign. …”
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Establishing an AI-based diagnostic framework for pulmonary nodules in computed tomography by Ruiting Jia, Baozhi Liu, Mohsin Ali

“…The diagnostic accuracy was 90.58%, with an overall positive predictive value of 89% and an overall negative predictive value of 86%. …”
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Critical Review and Benchmark Proposal on FE Modeling for Patch Loading Resistance of Slender Steel Plate Girders in Launched Bridges by Marck Anthony Mora Quispe

“…It provides a comprehensive description of an FE model that accurately predicts both the load–displacement behavior and the patch loading resistance. …”
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LoD2 Building Reconstruction from Stereo Satellite Imagery using Deep Learning and Model-Driven Approach by Rojgar Qarani Ismael, Haval Sadeq

“…The suggested methodology is tested on the GeoEye-1 satellite imagery dataset for Erbil City, which is validated with ground truth data. The proposed algorithm presented promising results, it is shown that the model can predict building heights for ridge and eave to a mean absolute error of 0.70 m, and in the occluded area was approximately 1.0 m. …”
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Time series forecasting of infant mortality rate in India using Bayesian ARIMA models by Anuj Singh, Tripti Tripathi, Rakesh Ranjan, Abhay K. Tiwari

“…A Random Walk Metropolis algorithm has been used to deal with analytically intractable posterior results from the ARIMA model. …”
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From Tables to Computer Vision: Transforming HPDC Process Data into Images for CNN-Based Deep Learning by A. Burzyńska

“…The approach assists in predicting key values of the dependent variable associated with defect occurrence, enabling foundries to enhance product quality, reduce waste, and augment overall production process efficiency. …”
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