Explainable machine learning model for predicting compressive strength of CO2-cured concrete by Jia Chu, Bingbing Guo, Taotao Zhong, Qinghao Guan, Yan Wang, Ditao Niu

“…A comprehensive database comprising 198 datasets was collected from published experimental investigations, and four ML algorithms were employed, i.e., RF (random forest), SVR (support vector regression), GBRT (gradient boosting regression tree), and XGB (extreme gradient boosting). …”
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Imaging analysis using Artificial Intelligence to predict outcomes after endovascular aortic aneurysm repair: protocol for a retrospective cohort study by Athanasios Saratzis, Juliette Raffort, Robert J Hinchliffe, Jonathan Boyle, George A Antoniou, Arun Pherwani, Maarit Venermo, Fabien Lareyre, Stavros K Kakkos, Mario D’Oria, Bahaa Nasr, Matthias Trenner

“…Morphological changes following EVAR will be analysed and compared based on preoperative and postoperative CT angiography (CTA) images (within 1 to 12 months, and at the last follow-up) using the AI-based software PRAEVAorta 2 (Nurea). Deep learning algorithms will be applied to stratify the risk of postoperative outcomes into low or high-risk categories. …”
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Enhancing drinking water safety: Real-time prediction of trihalomethanes in a water distribution system using machine learning and multisensory technology by Antonio J. Aragón-Barroso, David Ribes, Francisco Osorio

“…In total, a total of two predictive models were built, based on data filtered by conductivity levels, with coefficients of determination (R2) of 0.64 and 0.47. The algorithms of these predictive models were integrated into the control center of the water company in the study area. …”
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Simulation of energy consumption processes at the metallurgical enterprises in the energy-saving projects implementation by Kiyko S. G., Druzhinin E. A., Prokhorov O. V., Haidabrus B. V.

“…The model likewise includes algorithms for transport equipment management that minimize disruptions in continuous casting machines’ operation and simulate emergencies. …”
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Artificial intelligence survival models for identifying relevant risk factors for incident diabetes in Azar cohort population by Neda Gilani, Mohammadhossein Somi, Farzaneh Hamidi, Pasqualina Santaguida, Elnaz Faramarzi, Reza Arabi Belaghi

“…Conclusion: RF machine learning algorithms and LASSO-Cox regression analyses consistently identified WC, hypertension, and MCHC as the main risk factors for developing diabetes. …”
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Simulating the Deterioration Behavior of Tunnel Elements Using Amalgamation of Regression Trees and State-of-the-Art Metaheuristics by Eslam Mohammed Abdelkader, Abobakr Al-Sakkaf, Moaaz Elkabalawy, Abdelhady Omar, Ghasan Alfalah

“…Leveraging metaheuristic algorithms’ strengths, the developed method jointly optimizes critical regression tree hyperparameters and identifies the most relevant features for deterioration prediction. …”
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Video Segmentation of Wire + Arc Additive Manufacturing (WAAM) Using Visual Large Model by Shuo Feng, James Wainwright, Chong Wang, Jun Wang, Goncalo Rodrigues Pardal, Jian Qin, Yi Yin, Shakirudeen Lasisi, Jialuo Ding, Stewart Williams

“…Additionally, conventional computer vision algorithms based on greyscale value and gradient lack flexibility and robustness in this scenario. …”
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Automated Overtake Assist System Using YOLOv4 and Mask R-CNN for Enhanced Autonomous Driving by Navya Thirumaleshwar Hegde, Kapileswar Rana, S. S. Barath, Florence Nishmitha, Vishnu G. Nair

“…This paper presents an Automated Overtake Assist (AOA) system that leverages state-of-the-art computer vision algorithms—YOLOv4 and Mask R-CNN—for lane and vehicle detection. …”
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Unmanned Aerial Vehicle Remote Sensing for Monitoring Fractional Vegetation Cover in Creeping Plants: A Case Study of <i>Thymus mongolicus</i> Ronniger by Hao Zheng, Wentao Mi, Kaiyan Cao, Weibo Ren, Yuan Chi, Feng Yuan, Yaling Liu

“…FVC estimation models were developed using four algorithms: multiple linear regression (MLR), random forest (RF), support vector regression (SVR), and artificial neural network (ANN). …”
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Multi-Level Depression Severity Detection with Deep Transformers and Enhanced Machine Learning Techniques by Nisar Hussain, Amna Qasim, Gull Mehak, Muhammad Zain, Grigori Sidorov, Alexander Gelbukh, Olga Kolesnikova

“…We take a dual approach using classical machine learning (ML) algorithms and recent Transformer-based architectures. …”
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Leaf area index-based phenotypic assessment of sweet potato varieties using UAV multispectral imagery and a hybrid retrieval approach by Philemon Tsele, Abel Ramoelo, Lucy Moleleki, Sunette Laurie, Whelma Mphela, Natasha Tshuma

“…Integrating radiative transfer models (RTMs), active learning algorithms and non-parametric regression methods using unmanned aerial vehicle (UAV) multispectral imagery have the potential for accurately estimating LAI across multiple crop varieties at varying growth stages. …”
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Structure-Texture Dual Preserving for Remote Sensing Image Super Resolution by Kanghui Zhao, Tao Lu, Yanduo Zhang, Junjun Jiang, Zhongyuan Wang, Zixiang Xiong

“…A large number of experimental results on Draper and NWPU-RESISC45 datasets show that our model is superior to several advanced SR algorithms in both objective and subjective image quality.…”
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Fatal pulmonary infection by trimethoprim-sulfamethoxazole resistant Nocardia otitidiscaviarum: report of two cases and review by Rushika Saksena, Dabet Rynga, Santosh Rajan, Rajni Gaind, Reetika Dawar, Raman Sardana, Manas Kamal Sen, Jagdish Chandra Suri

“…Mass spectrometry can become an integral part of diagnostic algorithms for nocardiosis. …”
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Automatic location and recognition of horse freezing brand using rotational YOLOv5 deep learning network by Zhixin Hua, Yitao Jiao, Tianyu Zhang, Zheng Wang, Yuying Shang, Huaibo Song

“…The experiment results showed that R-YOLOv5 outperformed other rotating target detection algorithms, and the AP (Average Accuracy) was 95.6 %, the FLOPs were 17.4 G, the detection speed was 14.3 fps. …”
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An experimental optimization environment for developing an intracycle pitch control in cross flow turbines by Stefan Hoerner, Roberto Leidhold, Shokoofeh Abbaszadeh, Karla Ruiz-Hussmann, Timo Bennecke, Zhao Zhao, Paul Joedecke, Christian-Thoralf Weber, Pierre-Luc Delafin, Cyrille Bonamy, Yves Delannoy

“…A superimposed governing system performs an experimental optimization process. Evolutionary algorithms are to be employed to solve two objectives: (1) maximizing the efficiency and (2) minimizing the structural loads. …”
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Implementation of a Smart Home Intruder Detection System using a Vibrometer and ESP 32 CAM by Samuel Owoeye, Folasade Durodola, Adekunle Oyelami, Racheal Oladejo, Samuel Obasuyi, Ademola Qasim, Joshua Ogundairo

“…The ATMega328P contributes to the system's intelligence by supporting motion detection algorithms, which, in turn, trigger automated alerts and activate lighting or alarm systems in response to detected movement. …”
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SSVEP Enhancement in Mixed Reality Environment for Brain&#x2013;Computer Interfaces by Jieyu Wu, Feng He, Xiaolin Xiao, Runyuan Gao, Lin Meng, Xiuyun Liu, Minpeng Xu, Dong Ming

“…The proposed SA-xTRCA significantly outperformed the other four traditional algorithms. The online average information transfer rate (ITR) achieved 57.58 &#x00B1; 5.31 bits/min. …”
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Improving Diagnostic Performance for Head and Neck Tumors with Simple Diffusion Kurtosis Imaging and Machine Learning Bi-Parameter Analysis by Suzuka Yoshida, Masahiro Kuroda, Yoshihide Nakamura, Yuka Fukumura, Yuki Nakamitsu, Wlla E. Al-Hammad, Kazuhiro Kuroda, Yudai Shimizu, Yoshinori Tanabe, Masataka Oita, Irfan Sugianto, Majd Barham, Nouha Tekiki, Nurul N. Kamaruddin, Miki Hisatomi, Yoshinobu Yanagi, Junichi Asaumi

“…MK and ADC values were extracted from pixels within the tumor area and used as explanatory variables. Five ML algorithms were used to create models for the prediction of tumor status (benign or malignant), which were evaluated through ROC analysis. …”
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Infrared dim tiny-sized target detection based on feature fusion by Peng Zhang, Yaman Jing, Guodong Liu, Ziyang Chen, Xiaoyan Wu, Osami Sasaki, Jixiong Pu

“…The comparison of the proposed network with other algorithms are performed on open-source dataset and experimentally generated infrared images. …”
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A Temporal Convolutional Network–Bidirectional Long Short-Term Memory (TCN-BiLSTM) Prediction Model for Temporal Faults in Industrial Equipment by Jinyin Bai, Wei Zhu, Shuhong Liu, Chenhao Ye, Peng Zheng, Xiangchen Wang

“…Traditional algorithms and single predictive models often face challenges such as limited prediction accuracy and insufficient modeling capabilities for complex time-series data in fault prediction tasks. …”
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