Constitutive Model for Hot Deformation Behavior of Fe-Mn-Cr-Based Alloys: Physical Model, ANN Model, Model Optimization, Parameter Evaluation and Calibration by Jie Xu, Chaoyang Sun, Huijun Liang, Lingyun Qian, Chunhui Wang

“…The parameters and architecture of the ANN model are then systematically optimized using optimization algorithms to enhance training efficiency and prediction accuracy. …”
Get full text

From motion to meaning: understanding students’ seating preferences in libraries through PIR-enabled machine learning and explainable AI by Gizem Izmir Tunahan, Goksu Tuysuzoglu, Hector Altamirano

“…Drawing on over 1.3 million ten-minute passive infrared (PIR) sensor observations collected throughout 2023 at the UCL Bartlett Library, we modeled seat-level occupancy using 24 spatial, environmental, and temporal features through advanced machine learning algorithms. Among the models tested, Categorical Boosting (CatBoost) demonstrated the highest predictive performance, achieving a classification accuracy of 72.5%, with interpretability enhanced through SHAP (Shapley Additive exPlanations) analysis. …”
Get full text

Implications of artificial intelligence in periodontal treatment maintenance: a scoping review by Raafat Musief Sarakbi, Sudhir Rama Varma, Sudhir Rama Varma, Lovely Muthiah Annamma, Vinay Sivaswamy, Vinay Sivaswamy

“…Additionally, AI facilitated predictive analytics for disease progression and personalized treatment strategies. …”
Get full text

Enhancing emergency response efficiency through advanced urban logistics: The role of driver psychophysiology and vehicle dynamics in mitigating socio-economic impacts by Yurii Davidich, Dávid Földes, Andrii Galkin

“…Utilising regression models and physiological assessments, we developed predictive models that link these factors to emergency response times. …”
Get full text

Anomalous Behavior in Weather Forecast Uncertainty: Implications for Ship Weather Routing by Marijana Marjanović, Jasna Prpić-Oršić, Anton Turk, Marko Valčić

“…This allows uncertainty to be quantified not as a static estimate, but as a function sensitive to both variable type and prediction horizon. When integrated into routing algorithms, such representations allow for route planning strategies that are not only more reflective of real-world meteorological limitations but also more robust to evolving weather conditions, demonstrated by a 3–7% increase in travel time in exchange for improved safety margins across eight test cases.…”
Get full text

Overview of Startups Developing Artificial Intelligence for the Energy Sector by Naiyer Mohammadi Lanbaran, Darius Naujokaitis, Gediminas Kairaitis, Gabrielė Jenciūtė, Neringa Radziukynienė

“…Startup companies in this revolution use AI technologies like Machine Learning (ML), predictive analytics, and optimization algorithms to improve energy efficiency, optimize grid management, and incorporate renewable energy sources. …”
Get full text

Advancing malware imagery classification with explainable deep learning: A state-of-the-art approach using SHAP, LIME and Grad-CAM. by Sadia Nazim, Muhammad Mansoor Alam, Syed Safdar Rizvi, Jawahir Che Mustapha, Syed Shujaa Hussain, Mazliham Mohd Suud

“…There has been relatively little study on explainability, especially when dealing with malware imagery data, irrespective of the fact that DL/ML algorithms have revolutionized malware detection. Explainability techniques such as SHAP, LIME, and Grad-CAM approaches are employed to present a complete comprehension of feature significance and local or global predictive behavior of the model over various malware categories. …”
Get full text

Decoding circRNA translation: challenges and advances in computational method development by Jingjing Zhang, Jingjing Zhang, Rui Zhou, Rui Zhou, Huiling Zhang, Yin Peng, Jintao Meng, Wenhui Xi, Yanjie Wei

“…Subsequently, we provide a systematic introduction to existing circRNA translation analysis tools and their underlying algorithms, with emphasis on benchmarking the performance of sequence-based methods using a unified dataset. …”
Get full text

Multimodal machine learning-based model for differentiating nontuberculous mycobacteria from mycobacterium tuberculosis by Hong-ling Li, Ri-zeng Zhi, Hua-sheng Liu, Mei Wang, Si-jie Yu

“…The multimodal model contained age, IL-6, and the 2 radiomics features, and the optimal model was from LightGBM algorithm. The optimal multimodal model had the highest AUC value, accuracy, sensitivity, and negative predictive value compared with the optimal clinical or radiomics models, and its’ favorable performance was also verified in the external test dataset (accuracy = 0.745, sensitivity = 0.900). …”
Get full text

Comparative Analysis of Control Strategies for Microgrid Energy Management with a Focus on Reinforcement Learning by Parisa Mohammadi, Razieh Darshi, Saeed Shamaghdari, Pierluigi Siano

“…Traditional methods, including classical, metaheuristic, model predictive, stochastic, and robust control techniques, have been extensively studied. …”
Get full text

The future of 3D printing in instrumented implantable polymer meta-stents by C. Brosseau, G. Nocchiero, J. Ville

“…Thirdly, virtual replica digital twin technology can facilitate personalized stent design based on individual patient characteristics, medical history, and real-time physiological data. This new predictive analysis in healthcare systems relies largely on the use of deep learning algorithms, appropriate for managing massive data integration. …”
Get full text

An enhanced CNN-Bi-transformer based framework for detection of neurological illnesses through neurocardiac data fusion by Kavita Rawat, Trapti Sharma

“…The model achieved promising results with high accuracy (98.54%) and sensitivity (97.77%) in predicting mental problems, including neurological and psychiatric conditions. …”
Get full text

Forecast of hydrocarbon losses in deposits during the development of gas condensate fields by R. K. Dobrolyubova, E. I. Inyakina, I. I. Krasnov, V. V. Inyakin, A. F. Semenenko

“…To create such a model, a technique based on equations of state and an algorithm for modeling vapor-liquid transitions of hydrocarbon mixtures is used. …”
Get full text

The Advanced Actuarial Data Science Based AI-Driven Solutions for Automated Loss Reserving Under IFRS 17 in Non-Life Insurance by Brighton Mahohoho, Charles Chimedza, Florance Matarise, Sheunesu Munyira

“…Among eight evaluated machine learning algorithms, the Random Forest (RANGER) outperformed others for estimating Aggregate Comprehensive Automated Actuarial Loss Reserves (ACAALR). …”
Get full text

Artificial Intelligence-Based Surface Roughness Estimation Modelling for Milling of AA6061 Alloy by Aykut Eser, Elmas Aşkar Ayyıldız, Mustafa Ayyıldız, Fuat Kara

“…This study introduces the improvement of mathematical and predictive models of surface roughness parameter (Ra) in milling AA6061 alloy using carbide cutting tools coated with CVD-TiCN in dry condition. …”
Get full text

Older people and the smart city – Developing inclusive practices to protect and serve a vulnerable population by Aaro Tupasela, Juanita Devis Clavijo, Marjut Salokannel, Christoph Fink

“…In this article, we report on the main challenges encountered during the implementation of the URBANAGE project, and the development of the components for big data analytics, visualisations, predictive algorithms and simulation. Using examples from three European locations – Helsinki, Flanders and Santander – we describe and discuss how we can gather personal data related to the daily lives of older people in terms of the existing privacy and data protection laws in the EU. …”
Get full text

Adaptive Differential Privacy Cox-MLP Model Based on Federated Learning by Jie Niu, Runqi He, Qiyao Zhou, Wenjing Li, Ruxian Jiang, Huimin Li, Dan Chen

“…Experimental results on simulated and clinical datasets demonstrate improved predictive performance and robust privacy protection.…”
Get full text

Current Topics on the Integration of Artificial Intelligence in the Histopathological and Molecular Diagnosis of Uveal Melanoma by Serena Salzano, Giuseppe Broggi, Andrea Russo, Teresio Avitabile, Antonio Longo, Rosario Caltabiano, Manuel Mazzucchelli

“…Particular focus is placed on its role in histopathological assessments of UM, where algorithms facilitate the analysis of whole-slide images (WSIs). …”
Get full text

Optimization of Adaptive Observation Strategies for Multi-AUVs in Complex Marine Environments Using Deep Reinforcement Learning by Jingjing Zhang, Weidong Zhou, Xiong Deng, Shuo Yang, Chunwang Yang, Hongliang Yin

“…Additionally, experiments with three, five, and seven AUVs reveal that while increasing platform numbers enhances predictive accuracy, the benefits diminish with additional units.…”
Get full text

Air pressure forecasting for the Mutriku oscillating‐water‐column wave power plant: Review and case study by Jorge Marques Silva, Susana M. Vieira, Duarte Valério, João C. C. Henriques, Paul D. Sclavounos

“…A Least Squares Support Vector Machine (LS‐SVM) algorithm was developed to predict the air chamber pressure and compare it to the real signal. …”
Get full text