Intelligent fault diagnosis and operation condition monitoring of transformer based on multi-source data fusion and mining by Jingping Cui, Wei Kuang, Kai Geng, Pihua Jiao

“…Furthermore, Apriori correlation analysis is performed on the transformer load rate and upper oil layer, winding temperature, and fusion indices of gas components by support and confidence levels to achieve a predictive assessment of the transformer state. Finally, the validity of the algorithm is verified by applying actual data from a power system monitoring platform. …”
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A Cell Component-Related Prognostic Signature for Head and Neck Squamous Cell Carcinoma Based on the Tumor Microenvironment by Siyu Li, Yajun Gu, Junguo Wang, Dengbin Ma, Xiaoyun Qian, Xia Gao

“…The tumor microenvironment (TME) is composed of numerous noncancerous cells that contribute to tumorigenesis and prediction of therapeutic effects. In this study, we aimed to develop a cell component-related prognostic model based on TME. …”
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Molecular function validation and prognostic value analysis of the cuproptosis-related gene ferredoxin 1 in papillary thyroid carcinoma by Shiyue He, Wenzhong Peng, Xinyue Hu, Yong Chen

“…Based on six selected cuproptosis-related genes a predictive prognosis model was established and CRRS displayed a good prediction accuracy. …”
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Advanced hybrid computational analysis of febuxostat solubility using machine learning in supercritical processing method by Turki Al Hagbani, Rami M. Alzhrani, Majed Ahmed Algarni

“…As an innovative aspect of this research, in addition to the Voting model, the HHO algorithm has been used to tune the hyper-parameters of the models. …”
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The role of artificial intelligence in enhancing disaster preparedness and trauma care by Mohamad Sorani

“…Furthermore, ethical considerations such as data privacy, algorithmic bias, and equitable access are crucial to ensuring that AI-driven solutions are implemented responsibly and inclusively.This review also explores future directions for AI, including the development of sophisticated predictive models, autonomous systems for high-risk tasks, immersive training programs utilizing virtual and augmented reality, and global collaboration aimed at standardizing AI tools and practices. …”
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Variable Selection for Multivariate Failure Time Data via Regularized Sparse-Input Neural Network by Bin Luo, Susan Halabi

“…Both methods are optimized using a composite gradient descent algorithm combining standard gradient steps with proximal updates. …”
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An Optical Sensor for Measuring In-Plane Linear and Rotational Displacement by Suhana Jamil Ahamed, Michael Aaron McGeehan, Keat Ghee Ong

“…Variations in reflected R, G, B and C light intensities, caused by displacements, were used to predict linear and rotational motion via a polynomial regression algorithm. …”
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Between Two Worlds: Investigating the Intersection of Human Expertise and Machine Learning in the Case of Coronary Artery Disease Diagnosis by Ioannis D. Apostolopoulos, Nikolaos I. Papandrianos, Dimitrios J. Apostolopoulos, Elpiniki Papageorgiou

“…These results highlight a potential synergistic relationship between human expertise and advanced algorithmic predictions, suggesting a hybrid approach as a promising direction for enhancing CAD diagnostics.…”
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Development of a battery free, solar powered, and energy aware fixed wing unmanned aerial vehicle by Jackson Liller, Rishabh Goel, Abdul Aziz, Josiah Hester, Phuc Nguyen

“…We also derive the Greedy Energy-Aware Control (GEAC) and Predictive Energy-Aware Control (PEAC) solar control algorithm that overcomes power system brownouts and total-loss-of-thrust events, enabling the prototype to perform maneuvers without a battery. …”
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Combination treatment optimization using a pan-cancer pathway model. by Robin Schmucker, Gabriele Farina, James Faeder, Fabian Fröhlich, Ali Sinan Saglam, Tuomas Sandholm

“…In recent years, sophisticated mechanistic, ordinary differential equation-based pathways models that can predict treatment responses at a molecular level have been developed. …”
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Location allocation approach based on influence of points of dispensing by Nusaybah Alghanmi, Reem Alotaibi, Sultanah Alshammari, Arif Mahmood

“…It also obtained the closest results to the case study in terms of number, location and predictive performance.…”
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Privacy, ethics, transparency, and accountability in AI systems for wearable devices by Petar Radanliev, Petar Radanliev

“…The integration of artificial intelligence (AI) and machine learning (ML) into wearable sensor technologies has substantially advanced health data science, enabling continuous monitoring, personalised interventions, and predictive analytics. However, the fast advancement of these technologies has raised critical ethical and regulatory concerns, particularly around data privacy, algorithmic bias, informed consent, and the opacity of automated decision-making. …”
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Enhancing Power Allocation in DAS: A Hybrid Machine Learning and Reinforcement Learning Model by S. Gnanasekar, K. C. Sriharipriya

“…The proposed method combines Machine Learning (ML) for predictive modeling with Multi-Agent Reinforcement Learning (MARL) for real-time coordination among RAUs. …”
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A Distributed Energy Optimized Routing Using Virtual Potential Field in Wireless Sensor Networks by Haifeng Jiang, Yanjing Sun, Renke Sun, Wei Chen, Shanshan Ma, Jing Gao

“…Simulation results show that the algorithm effectively extends the network lifetime, has good performance on energy balance of sensors, and decreases the average hop of data transmission with the increase of the number of sinks, compared with similar algorithms.…”
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Deep learning method for cucumber disease detection in complex environments for new agricultural productivity by Jun Liu, Xuewei Wang, Qian Chen, Peng Yan, Xin Liu

“…This study proposes YOLO-Cucumber, an improved lightweight detection algorithm based on YOLOv11n, incorporating four key innovations: (1) Deformable Convolutional Networks (DCN) for enhanced feature extraction of irregular targets, (2) a P2 prediction layer for fine-grained detection of early-stage lesions, (3) a Target-aware Loss (TAL) function addressing class imbalance, and (4) Channel Pruning via Batch Normalization (CPBN) for model compression. …”
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3D Volumetric Strain Distribution of the Cerro Prieto Geothermal Field Inferred From Inverse Modeling of InSAR and Leveling Data by Luis A. Gallardo, Olga Sarychikhina, Ewa Glowacka, Braulio Robles

“…We present and release a conjugate‐gradient inversion code that searches for the three‐dimensional distribution of the volumetric strain that predicts simultaneously any observed InSAR, leveling and GPS surface displacement. …”
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VAMP-Based Kalman Filtering Under Non-Gaussian Process Noise by Tiancheng Gao, Mohamed Akrout, Faouzi Bellili, Amine Mezghani

“…For the sake of theoretical performance prediction, we conduct a state evolution (SE) analysis of the proposed algorithm and show its consistency with the asymptotic empirical mean-squared error (MSE). …”
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Advancing sepsis diagnosis and immunotherapy machine learning-driven identification of stable molecular biomarkers and therapeutic targets by Weichuan Xiong, Yian Zhan, Rui Xiao, Fangpeng Liu

“…Prediction models were constructed and validated using six machine learning algorithms, achieving high accuracy (AUC > 0.75). …”
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Large‐scale identification of genetic design strategies using local search by Desmond S Lun, Graham Rockwell, Nicholas J Guido, Michael Baym, Jonathan A Kelner, Bonnie Berger, James E Galagan, George M Church

“…Methods based on flux–balance analysis (FBA) and bi‐level optimization have been used to great effect in aiding metabolic engineering. These methods predict the result of genetic manipulations and allow for the best set of manipulations to be found computationally. …”
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Calibration and surrogate model-based sensitivity analysis of crystal plasticity finite element models by Hugh Dorward, David M. Knowles, Eralp Demir, Mahmoud Mostafavi, Matthew J. Peel

“…Crystal plasticity models are powerful tools for predicting the deformation behaviour of polycrystalline materials accounting for underlying grain morphology and texture. …”
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