Electrochemical–Thermal Modeling of Lithium-Ion Batteries: An Analysis of Thermal Runaway with Observation on Aging Effects by Milad Tulabi, Roberto Bubbico

“…Additionally, a machine learning algorithm (logistic regression) is employed to identify an internal resistance threshold, beyond which thermal runaway (TR) becomes highly probable, and to predict TR probability based on key battery parameters. …”
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Thermal Monitoring of an Internal Combustion Engine for Lightweight Fixed-Wing UAV Integrating PSO-Based Modelling with Condition-Based Extended Kalman Filter by Aleksander Suti, Gianpietro Di Rito, Giuseppe Mattei

“…The monitoring algorithm, being executable in real-time and capable of identifying incipient degradations of the thermal flow, demonstrates applicability for online diagnostics and predictive maintenance purposes.…”
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Integrated OVMD-BiGRU-SMAC Framework for Forecasting Construction Accidents in the Kingdom of Saudi Arabia by Badr T. Alsulami, Afaq Khattak

“…These IMFs are individually forecasted using Bidirectional Gated Recurrent Unit (BiGRU) models, which are capable of learning sequential patterns in both temporal directions. To enhance the predictive accuracy, the hyperparameters of each BiGRU model are optimized using the Sequential Model-based Algorithm Configuration (SMAC) technique. …”
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A Four‐Gene Autophagy‐Related Prognostic Model Signature and Its Association With Immune Phenotype in Lung Squamous Cell Carcinoma by Lumeng Luo, Jiaying Deng, Qiu Tang

“…ABSTRACT Background In the era of immunotherapy, there is a critical need for effective biomarkers to improve outcome prediction and guide treatment decisions for patients with lung squamous cell carcinoma (LUSC). …”
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Exploring the comprehensive integration of artificial intelligence in optimizing HVAC system operations: A review and future outlook by Shengze Lu, Shiyu Zhou, Yan Ding, Moon Keun Kim, Bin Yang, Zhe Tian, Jiying Liu

“…The main features of the AI technology are first introduced. The main algorithms of supervised learning, reinforcement learning, and deep learning are then analyzed in the fields of air conditioning operation optimization, energy consumption prediction and control, indoor environmental protection, and fault detection and diagnosis. …”
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Research on economic dispatching strategy for active distribution network considering high penetration of renewable energy source by ZHANG Yu, YUAN Bo, HUANG Shicheng, SHI Jinyue, AN Yichen

“…Finally, building upon the multi-agent deep deterministic policy gradient (MADDPG) algorithm, the bidirectional gated recurrent unit (BiGRU) is employed instead of fully connected layers for renewable energy output prediction, effectively mitigating the impact of renewable energy fluctuations. …”
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Advances in Federated Learning: Applications and Challenges in Smart Building Environments and Beyond by Mohamed Rafik Aymene Berkani, Ammar Chouchane, Yassine Himeur, Abdelmalik Ouamane, Sami Miniaoui, Shadi Atalla, Wathiq Mansoor, Hussain Al-Ahmad

“…This review paper explores the foundational concepts, and architectural variations of FL, prominent aggregation algorithms like FedAvg, FedProx, and FedMA, and diverse innovative applications in thermal comfort optimization, energy prediction, healthcare, and anomaly detection within smart buildings. …”
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Applications of machine learning-assisted extracellular vesicles analysis technology in tumor diagnosis by Liang Xu, Jing Li, Wei Gong

“…In recent years, machine learning (ML) technology in the medical field has gained momentum, which utilize various algorithms to analyze input data, identify potential patterns and trends, develop predictive models, and generate high-precision predictions of unknown data, demonstrating its clinical potential in disease diagnosis. …”
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Applied Artificial Intelligence in Materials Science and Material Design by Emigdio Chávez‐Angel, Martin Børstad Eriksen, Alejandro Castro‐Alvarez, Jose H. Garcia, Marc Botifoll, Oscar Avalos‐Ovando, Jordi Arbiol, Aitor Mugarza

“…By leveraging large datasets, AI algorithms can identify patterns, reduce noise, and predict material behavior with unprecedented accuracy. …”
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Artificial Intelligence in Numerical Modeling of Silver Nanoparticles Prepared in Montmorillonite Interlayer Space by Parvaneh Shabanzadeh, Norazak Senu, Kamyar Shameli, Maryam Mohaghegh Tabar

“…In this investigation, the accuracy of artificial neural network training algorithm was applied in studying the effects of different parameters on the particles, including the AgNO3 concentration, reaction temperature, UV-visible wavelength, and montmorillonite (MMT) d-spacing on the prediction of size of silver nanoparticles. …”
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Tri-manual interaction in hybrid BCI-VR systems: integrating gaze, EEG control for enhanced 3D object manipulation by Jian Teng, Jian Teng, Sukyoung Cho, Shaw-mung Lee

“…A soft maximum weighted arbitration algorithm resolves spatiotemporal conflicts between manual and virtual inputs with 92.4% success rate. …”
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Linear and Nonlinear Multivariate Classification of Iranian Bottled Mineral Waters According to Their Elemental Content Determined by ICP-OES by J.B. Ghasemi, E. Zolfonoun, R. Khosrokhavar

“…Hierarchical cluster analysis (HCA) and principal component analysis (PCA) showed differences in water samples according to the mineral composition. 120 samples (4 for each brand) were selected randomly for the calibration set, and 30 samples (1 for each brand) for the prediction set. PLS-DA, LS-SVM and SIMCA were implemented for calibration models. …”
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Measured spectrum environment map dataset with multi-radiation sources in urban scenariosMendeley Data by Haotian Zou, Qiuming Zhu, Qianhao Gao, Jie Wang, Zhipeng Lin, Yang Huang, Qihui Wu, Weizhi Zhong

“…Its applications include the verification of spectrum map completion algorithms, wireless channel modelling, deep learning-driven signal prediction, and the optimization of Wi-Fi/cellular networks.…”
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Deriving Overlapped Cloud Motion Vectors Based on Geostationary Satellite and Its Application on Monitoring Typhoon Mulan by Cuiping Liu, Wei Han, Feng Zhang, Jiaqi Jin, Qiong Wu, Wenwen Li, Chloe Yuchao Gao

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Forecast Model of TV Show Rating Based on Convolutional Neural Network by Lingfeng Wang

“…Therefore, this paper introduces the convolutional neural network structure to predict the TV program rating data. First, it briefly introduces artificial neural networks and deep learning methods and focuses on the algorithm principles of convolutional neural networks and support vector machines. …”
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Study on the Effect of Apple Size Difference on Soluble Solids Content Model Based on Near-Infrared (NIR) Spectroscopy by Xiaogang Jiang, Mingwang Zhu, Jinliang Yao, Yuxiang Zhang, Yande Liu

“…To better address the effects of apple size differences, data fusion techniques were used to perform an intermediate fusion of apple fruit diameter and spectra, firstly, the competitive adaptive reweighting algorithm (CARS) and the continuous projection algorithm (SPA) were used to select spectral variables and build their prediction models for apple SSC, respectively, and the results showed that the models built with 61 spectral variables selected by CARS had better performance, greatly reduced the amount of data involved in modeling, effectively simplified the model, and improved the stability of the model. …”
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Assessment and Modeling of Green Roof System Hydrological Effectiveness in Runoff Control: A Case Study in Dublin by Mehdi Gholamnia, Payam Sajadi, Salman Khan, Srikanta Sannigrahi, Saman Ghaffarian, Himan Shahabi, Francesco Pilla

“…The comprehensive dataset enabled detailed modeling of runoff hydrograph parameters using rainfall hyetographs, which were subsequently analyzed through sophisticated machine learning algorithms. This research introduces an innovative approach by identifying the optimal combination of variables for modeling key runoff characteristics, including Water Retention Amount (WRA), Total RUnoff Volume (TRUV), Peak Runoff Discharge (PRD), and Peak Flow Reduction (PFR). …”
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Digital Twin Based on CFD Modelling for Analysis of Two-Phase Flows During Pipeline Filling–Emptying Procedures by Duban A. Paternina-Verona, Oscar E. Coronado-Hernández, Vicente S. Fuertes-Miquel, Manuel Saba, Helena M. Ramos

“…These models effectively predict hazardous pressure peaks and vacuum conditions, confirming their reliability in optimising pipeline operations while significantly reducing computational time.…”
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Uncovering Hippo pathway-related biomarkers in acute myocardial infarction via scRNA-seq binding transcriptomics by Xingda Li, Xueqi He, Yu Zhang, Xinyuan Hao, Anqi Xiong, Jiayu Huang, Biying Jiang, Zaiyu Tong, Haiyan Huang, Lian Yi, Wenjia Chen

“…Notably, NAMPT, CXCL1, and GIMAP6 exhibited cell-type-specific expression in endothelial cells and macrophages. We further predicted 179 potential therapeutic agents targeting these biomarkers. …”
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Federated Learning-Based State of Charge Estimation in Electric Vehicles Using Federated Adaptive Client Momentum by Metin Yilmaz, Eyup Cinar, Ahmet Yazici

“…Traditional Battery Management System (BMS) algorithms can be inadequate for State of Charge (SoC) estimation due to incorrect measurements and unobservable battery characteristics. …”
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