Advancing Marine Surveillance: A Hybrid Approach of Physics Infused Neural Network for Enhanced Vessel Tracking Using Automatic Identification System Data by Tasmiah Haque, Md Asif Bin Syed, Srinjoy Das, Imtiaz Ahmed

“…Recognizing the strengths and limitations of the LSTM model, we propose a hybrid machine-learning algorithm that integrates LSTM with a physics-based model. …”
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Enhancing Supply Chain Efficiency Resilience Using Predictive Analytics and Computational Intelligence Techniques by Lixing Bo, Jie Xu

“…Results from the study indicate significant improvements. The Transformer model achieved a reduction in Mean Absolute Error (MAE) from 15.8 to 8.2 and Root Mean Squared Error (RMSE) from 22.3 to 11.5, demonstrating enhanced forecasting accuracy. …”
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Automatic 3D Reconstruction: Mesh Extraction Based on Gaussian Splatting from Romanesque–Mudéjar Churches by Nelson Montas-Laracuente, Emilio Delgado Martos, Carlos Pesqueira-Calvo, Giovanni Intra Sidola, Ana Maitín, Alberto Nogales, Álvaro José García-Tejedor

“…It reviews recent advancements in machine learning and deep learning—particularly neural radiance fields (NeRFs) and its successor, Gaussian splatting (GS)—as state-of-the-art techniques in the domain. …”
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Uncovering Key Factors That Drive the Impressions of Online Emerging Technology Narratives by Lowri Williams, Eirini Anthi, Pete Burnap

“…Additionally, the sentiment associated with specific technologies also played a crucial role; positive sentiments linked to beneficial technologies like data science or machine learning significantly boosted impressions, while similar sentiments towards negatively viewed technologies like cyber threats reduced them. …”
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Adaptive neuro-fuzzy inference system optimization of natural rubber latex modified concrete’s mechanical Properties by Efiok Etim Nyah, David Ogbonna Onwuka, Joan Ijeoma Arimanwa, George Uwadiegwu Alaneme, G. Nakkeeran, Ulari Sylvia Onwuka, Chinenye Elizabeth Okere

“…Traditional laboratory testing for concrete properties is often time-consuming, costly, and prone to variability due to environmental and procedural inconsistencies. Machine learning techniques, such as ANFIS, offer a robust alternative by effectively modelling complex, nonlinear relationships in material behavior based on experimental data. …”
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Exploring the integration of medical and preventive chronic disease health management in the context of big data by Yueyang Wang, Yueyang Wang, Ruigang Deng, Xinyu Geng

“…Through synthesizing existing research, we propose a novel framework that includes the development of machine learning models and interoperable health information platforms for real—time data sharing. …”
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Physics-Informed Neural Networks for Enhanced State Estimation in Unbalanced Distribution Power Systems by Petros Iliadis, Stefanos Petridis, Angelos Skembris, Dimitrios Rakopoulos, Elias Kosmatopoulos

“…Physics-Informed Neural Networks (PINNs) offer a compelling solution by integrating machine learning with the physical laws that govern power system behavior. …”
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Accelerating multi-objective optimization of concrete thin shell structures using graph-constrained GANs and NSGA-II by Zhichun Fang, Xiuhong Wang, Yuyong Sun, M. A. Adibhashimi

“…The implementation of the system in a concrete thin shell structure at the Shenzhen Qianhai Smart Community resulted in significant performance improvements: a 33.3% reduction in total weight, a 50% decrease in maximum deflection, and a 20% reduction in strain energy compared to baseline models. …”
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Spectral Entropic Radiomics Feature Extraction (SERFE): an adaptive approach for glioblastoma disease classification by V. L. Sowmya, A. Bharathi Malakreddy, Santhi Natarajan, N. Prathik, I. S. Rajesh

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Dynamic Monitoring and Precision Fertilization Decision System for Agricultural Soil Nutrients Using UAV Remote Sensing and GIS by Xiaolong Chen, Hongfeng Zhang, Cora Un In Wong

“…The integration of UAV remote sensing, dynamic modeling, and machine learning distinguishes this work from conventional static systems, offering a scalable and adaptive framework for sustainable farming practices.…”
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Embedded feature selection using dual-network architecture by Abderrahim Abbassi, Arved Dörpinghaus, Niklas Römgens, Tanja Grießmann, Raimund Rolfes

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Bitcoin price direction prediction using on-chain data and feature selection by Ritwik Dubey, David Enke

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Graph2Mat: universal graph to matrix conversion for electron density prediction by Pol Febrer, Peter Bjørn Jørgensen, Miguel Pruneda, Alberto García, Pablo Ordejón, Arghya Bhowmik

“…As a prediction target for machine learning (ML) models, electron density is often represented on a dense real space grid, which is data heavy, or through density fitting approximations. …”
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A Review of Finite Element Studies on Laser-Based Acoustic Applications in Solid Media by Evaggelos Kaselouris, Vasilis Dimitriou

“…In biomedical applications, the FEM aids in tissue characterization and disease detection, while in engineering, its integration with laser-based methods contributes to noise reduction and vibration control. Furthermore, this review provides a comprehensive synthesis of FEM simulations and experimental validation while also highlighting the emerging role of artificial intelligence and machine learning in optimizing FEM models and improving computational efficiency, which has not been addressed in previous studies. …”
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Increasing 3D Printing Accuracy Through Convolutional Neural Network-Based Compensation for Geometric Deviations by Moustapha Jadayel, Farbod Khameneifar

“…This study proposes a machine learning-based approach to enhance the geometric accuracy of 3D printed parts produced by Fused Filament Fabrication (FFF), a widely used material extrusion process in which thermoplastic filament is heated and deposited layer by layer to form a part. …”
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Supply Chains Problem During Crises: A Data-Driven Approach by Farima Salamian, Amirmohammad Paksaz, Behrooz Khalil Loo, Mobina Mousapour Mamoudan, Mohammad Aghsami, Amir Aghsami

“…This study addresses these challenges by proposing a novel bi-objective optimization framework. The model integrates a Mixed-Integer Linear Programming (MILP) approach with advanced machine learning techniques to simultaneously minimize total costs and maximize patient satisfaction. …”
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Multimodal Collaborative Perception for Dynamic Channel Prediction in 6G V2X Networks by Ghazi Gharsallah, Georges Kaddoum

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A New Hyperspectral Image Identification Method Based on LSDA and OSELM by Chengjiang Zhou, Mingli Yang, Sasa Duan, Lu Shao, Zhilin Zhang, Yunfei Liu

“…To solve the problems of information loss and nonlinear transformation of hyperspectral image dimensionality reduction methods and the problem that recognition methods are sensitive to noise and cannot be trained online, a new hyperspectral image identification method based on locality sensitive discriminant analysis (LSDA) and online sequential extreme learning machine (OSELM) is proposed. …”
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Reducing bias in coronary heart disease prediction using Smote-ENN and PCA. by Xinyi Wei, Boyu Shi

“…This indicates that combining data balancing and feature dimensionality reduction techniques significantly improves model accuracy and makes the random forest model the best model. …”
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Comparative life cycle assessments of laboratory and Pilot-scale Mechanochemical processes for producing carbonated mineral products as cement substitutes by Mohamed Katish, Xinyuan Ke, Phil Renforth

“…Life cycle assessments consistently revealed GWP reductions for OPC-BFA mixtures, with additional emissions reductions when incorporating flow sheet modelling and machine learning data. …”
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