Strength prediction of ECC-CES columns under eccentric compression using adaptive sampling and ML techniques by Khaled Megahed

“…Based on evaluation metrics, the Gaussian Process Regression (GPR), CatBoost (CATB), and LightGBM (LGBM) models emerged as the most accurate and reliable, with over 97% of the finite element (FE) samples falling within a 10% error range. …”
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Trustworthy Load Prediction for Cantilever Roadheader Robot Without Imputation by Pengjiang Wang, Yuxin Li, Yunwang Li, Yang Shen, Weixiong Zheng, Shigen Fu

“…Furthermore, we utilize boosting techniques to enhance the prediction performance of the base predictor by incorporating cutting safety–trust constraints during the prediction process. …”
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Applying Syntax-Prosody Mapping Hypothesis and Boundary-Driven Theory to Neural Sequence-to-Sequence Speech Synthesis by Kei Furukawa, Takeshi Kishiyama, Satoshi Nakamura, Sakriani Sakti

“…Additionally, the model demonstrates a unique proficiency in reproducing the rhythmic boost phenomenon, despite rhythmic boost being absent in the training data. …”
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Predicting fine-scale downstream migratory movement of Atlantic salmon smolt (Salmo salar) in front of a hydropower plant by Kim M. Bærum, Ana T. Silva, Henrik Baktoft, Karl Ø. Gjelland, Finn Økland, Torbjørn Forseth

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Machine Learning for Predicting Required Cross-Sectional Dimensions of Circular Concrete-Filled Steel Tubular Columns by Anton Chepurnenko, Samir Al-Zgul, Vasilina Tyurina

“…The main focus is on automating the design process of CFST columns using the CatBoost algorithm and artificial neural networks. …”
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K-Gen PhishGuard: an Ensemble Approach for Phishing Detection with K-Means and Genetic Algorithm by Ali Al-Hafiz, Adnan Jabir, Shamala Subramaniam

“…In the second phase, the best set of features in each group is identified through the Genetic algorithm to enhance the classification process. Finally, a voting ensemble technique is applied, in which the Support Vector Machine (SVM), Random Forest (RF), Extreme Gradient Boosting (XGBoost) and Adaptive boosting (AdaBoost) models are combined. …”
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Enhanced efficiency and stability in indoor organic photovoltaics with spray-deposited, liquid-processable MoS₂ and WS₂ hole transport layers by Marinos Tountas, Katerina Anagnostou, Christos Polyzoidis, Evangelos Sotiropoulos, Emmanuel Kymakis

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Machine-learning-driven prediction of flow curves and development of processing maps for hot-deformed Ni–Cu–Co–Ti–Ta alloy by Reliance Jain, Sandeep Jain, Sheetal Kumar Dewangan, M.R. Rahul, Sumanta Samal, Eunhyo Song, Younggeon Lee, Yongho Jeon, Krishanu Biswas, Gandham Phanikumar, Byungmin Ahn

“…To reduce experimental efforts and enhance prediction accuracy, five machine learning (ML) models random Forest (RF), XGBoost (XGB), decision tree (DT), K-Nearest neighbor (KNN), and gradient boosting (GB) were applied to predict the flow stress–strain response and construct processing maps. …”
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Thermal performance estimation and optimisation of a shallow geothermal compound heat pumping system for combined process heating and cooling by J.E. De León-Ruiz, R. Beltrán-Chacón, I. Carvajal-Mariscal, M. Venegas, A. Ponsich

“…Finally, the complementary economic assessment showed that this setup, on average, resulted in a 10.5 % gross energy cost reduction, based on doubling the batch processing rate. Based on this information, the presented compound system, is capable of boosting available source capacity, whilst simultaneously producing serviceable heating, cooling and residual outputs. …”
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Effects of <i>Amphidinium carterae</i> Phytocompounds on Proliferation and the Epithelial–Mesenchymal Transition Process in T98G Glioblastoma Cells by Julia Oyón Díaz de Cerio, Giulia Venneri, Ida Orefice, Martina Forestiero, Carlos Roman Baena, Gianluca Bruno Tassone, Isabella Percopo, Angela Sardo, Maria Luisa Panno, Francesca Giordano, Valeria Di Dato

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Predicting Endpoint Temperature of Molten Steel in VD Furnace Refining Process Using Metallurgical Mechanism and Bayesian Optimization XGBoost by Ji XU, Zicheng XIN, Mo LAN, Wenhui LIN, Bo ZHANG, Qing LIU

“…Unlike other furnaces, the VD furnace lacks a heating function, leading to a significant drop in the temperature of molten steel during the refining process. If the refining endpoint temperature of molten steel is excessively high, it results in energy waste and can even disrupt the continuous casting process. …”
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Prediction of ultimate tensile strength of Al‐Si alloys based on multimodal fusion learning by Longfei Zhu, Qun Luo, Qiaochuan Chen, Yu Zhang, Lijun Zhang, Bin Hu, Yuexing Han, Qian Li

“…Finally, four machine‐learning models (i.e., decision tree, random forest, adaptive boosting, and extreme gradient boosting [XGBoost]) are used to predict the UTS of Al‐Si alloys. …”
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Mopane worm (Gonimbrasia belina)—An exclusive African edible insect as human food—A comprehensive review by Shahida Anusha Siddiqui, Deepak Kumar Mahanta, Tanmaya Kumar Bhoi, Ali Ahmad, Ito Fernando

“…Mass rearing, gathering, processing, and storage practices that are effective and sustainable can guarantee the safety and quality of products while boosting consumer demand and producer prospects for profit. …”
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Multiple entropy fusion predicts driver fatigue using forehead EEG by Renyu Yang, Ling Zhang, Renhuan Yang, Lixing Hou, Donglong Zhu, Boming Zhong

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Decoding Depression from Different Brain Regions Using Hybrid Machine Learning Methods by Qi Sang, Chen Chen, Zeguo Shao

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A robot process automation based mobile application for early prediction of chronic kidney disease using machine learning by Md. Hasan Imam Bijoy, Md. Jueal Mia, Md. Mahbubur Rahman, Mohammad Shamsul Arefin, Pranab Kumar Dhar, Tetsuya Shimamura

“…The proposed models were trained on five pre-processed CKD datasets using four robust feature selection techniques, including Lasso, Fisher score, Information Gain, and Relief. …”
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Using optimized dimensionality reduction and machine learning to explain driving processes of phytoplankton community assembly in large mountain rivers by Jingxu Ye, Daikui Li, Qi Liu, Jianying Song, Jiawei Song, Zhigang Zu, Yujun Yi

“…Currently, the elucidation of aquatic community assembly processes is primarily achieved by integrating multiple factors. …”
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Novel transfer learning based bone fracture detection using radiographic images by Aneeza Alam, Ahmad Sami Al-Shamayleh, Nisrean Thalji, Ali Raza, Edgar Anibal Morales Barajas, Ernesto Bautista Thompson, Isabel de la Torre Diez, Imran Ashraf

“…Fractures are primarily caused by injuries and accidents, affecting millions of people worldwide. The healing process for a fracture can take anywhere from one month to one year, leading to significant economic and psychological challenges for patients. …”
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Improved reconstruction of highly boosted $$\tau $$ τ -lepton pairs in the $$\tau \tau \rightarrow (\mu \nu _{\mu }\nu _{\tau })(\text {hadrons}+\nu _{\tau })$$ τ τ → ( μ ν μ ν τ )... by ATLAS Collaboration

“…Abstract This paper presents a new $$\tau $$ τ -lepton reconstruction and identification procedure at the ATLAS detector at the Large Hadron Collider, which leads to significantly improved performance in the case of physics processes where a highly boosted pair of $$\tau $$ τ -leptons is produced and one $$\tau $$ τ -lepton decays into a muon and two neutrinos ( $$\tau _\mathrm {\mu }$$ τ μ ), and the other decays into hadrons and one neutrino ( $$\tau _\textrm{had}$$ τ had ). …”
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Perception-Based H.264/AVC Video Coding for Resource-Constrained and Low-Bit-Rate Applications by Lih-Jen Kau, Chin-Kun Tseng, Ming-Xian Lee

“…To this end, macroblocks (MBs) containing human faces are detected using the Viola–Jones algorithm, which leverages AdaBoost for feature selection and a cascade of classifiers for fast and accurate detection. …”
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