Optimizing mRNA Vaccine Degradation Prediction via Penalized Dropout Approaches by Hwai Ing Soon, Azian Azamimi Abdullah, Hiromitsu Nishizaki, Latifah Munirah Kamarudin

“…To further optimize model performance, two advanced hyperparameter optimization (HPO) techniques—Dropout-Enhanced Technique (DEet) and Hyperparameter Optimization Algorithm Penalizer (HOPeR)—are proposed to mitigate overfitting, address inefficiencies in conventional HPO algorithms (HPOAs), and accelerate model convergence. …”
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Mortality prediction of inpatients with NSTEMI in a premier hospital in China based on stacking model. by Li Wang, Yu Zhang, Feng Li, Caiyun Li, Hongzeng Xu

“…Finally, a unique double-layer stacking model is designed to improve the performance of the algorithm. Seven classical artificial intelligence methods of Logistic Regression (LR), Decision Tree (DT), Support Vector Machine (SVM), Random Forest (RF), Adaptive Boosting (ADB), Extra Tree (ET), and Gradient Boosting Decision Tree (GBDT) were selected as candidate models for the base model of the first layer of the model, and extreme gradient enhancement (XGBOOST) was selected as the meta-model for the second layer.…”
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Research and application of a novel grey multivariable model in port scale prediction under the impact of Free Trade Zone by Yuyu Sun, Yuchen Zhang, Zhiguo Zhao

“…Second, the heuristic grey wolf optimization (GWO) algorithm is used to determine the optimal nonlinear parameters. …”
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Novel nocturnal insect pest monitoring for sustainable crop protection using ensemble augmented deep learning classification by Hui Zhao, Bo Fu, Fernando Auat Cheein, Matthew Butler, W. Edwin Harris, Tom W. Pope, Joe M. Roberts

“…This may be addressed by developing an identification algorithm for adult weevils. Here we present results that show improved machine learning models can identify adult vine weevils under laboratory and semi-field conditions. …”
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Crop row centerline extraction method based on regional feature point clustering by Baofeng Ji, Hang Wang, Chunhong Dong, Song Chen, Hongtao Chen, Fazhan Tao, Ji Zhang, Huitao Fan

“…First, the 2G-R-B feature factor and an optimal adaptive threshold segmentation method are used to segment crops and background. …”
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Conflict-based model predictive control for multi-agent path finding experimentally validated on a magnetic planar drive system by Kai Janning, Abdalsalam Housin, Christopher Schulte, Frederik Erkens, Luca Frenken, Laura Herbst, Bastian Nießing, Robert H. Schmitt, Robert H. Schmitt

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Early breast cancer detection via infrared thermography using a CNN enhanced with particle swarm optimization by Riyadh M. Alzahrani, Mohamed Yacin Sikkandar, S. Sabarunisha Begum, Ahmed Farag Salem Babetat, Maryam Alhashim, Abdulrahman Alduraywish, N. B. Prakash, Eddie Y. K. Ng

“…Infrared thermography, by contrast, offers a non-invasive and economical alternative; however, its clinical adoption has been limited, largely due to difficulties in accurate thermal image interpretation and the suboptimal tuning of machine learning algorithms. To overcome these limitations, this study proposes an automated classification framework that employs convolutional neural networks (CNNs) for distinguishing between malignant and benign thermographic breast images. …”
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Golden eagle optimized CONV-LSTM and non-negativity-constrained autoencoder to support spatial and temporal features in cancer drug response prediction by Wesam Ibrahim Hajim, Suhaila Zainudin, Kauthar Mohd Daud, Khattab Alheeti

“…Advanced machine learning (ML) and deep learning (DL) methods have recently been utilized in Drug Response Prediction (DRP), and these models use the details from genomic profiles, such as extensive drug screening data and cell line data, to predict the response of drugs. …”
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Advances in Numerical Modeling for Heat Transfer and Thermal Management: A Review of Computational Approaches and Environmental Impacts by Łukasz Łach, Dmytro Svyetlichnyy

“…This review explores key methods like Computational Fluid Dynamics (CFD), the Finite Element Method (FEM), the Finite Volume Method (FVM), and multiphysics modeling, alongside emerging strategies such as Adaptive Mesh Refinement (AMR), machine learning (ML), reduced-order modeling (ROM), and high-performance computing (HPC). …”
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Advanced Credit Card Fraud Detection: An Ensemble Learning Using Random Under Sampling and Two-Stage Thresholding by Ibrahim Almubark

“…We employed synthetic over-sampling and under-sampling techniques in certain machine learning algorithms to tackle the same issue. …”
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The Three Laws of Artificial Intelligence: Re-Evaluating Human-AI Agency and Interaction in a Time of the Generative and Agentic AI Ren[ai]ssance by Aras Bozkurt

“…This prime directive is not for the AI, but for its creators, designed to prevent a system from invisibly reshaping humanity and to stop humanity from thoughtlessly obeying the machine. In all, the article advocates for a shift from Asimov’s robot-centric rules to adaptive, human-centric governance frameworks that prioritize transparency, accountability, and the preservation of human agency within an “algorithmic panopticon.” …”
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Smart diabetes management: remote monitoring and predictive health insights by K.S. Smelyakov, I.A. Lurin, K.V. Misiura, A.S. Chupryna, T.V. Tyzhnenko, O.D. Dolhanenko, V.M. Repikhov

“…GluComp integrates CGM systems with personalized machine learning models to deliver real-time alerts, predictive insights, and adaptive care. …”
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I-MPN: inductive message passing network for efficient human-in-the-loop annotation of mobile eye tracking data by Hoang H. Le, Duy M. H. Nguyen, Omair Shahzad Bhatti, László Kopácsi, Thinh P. Ngo, Binh T. Nguyen, Michael Barz, Daniel Sonntag

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Sperm swarm optimization for many objective power flow problems with enhanced performance evaluation in power systems by Wulfran Fendzi Mbasso, Ambe Harrison, Pradeep Jangir, Idriss Dagal, Hossam Kotb, Njimboh Henry Alombah, Raman Kumar, Aseel Smerat, Emmanuel Fendzi Donfack, Saad F. Al-Gahtani, Z. M. S. Elbarbary

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Towards a Sustainable Disruptive Growth Model: Integrating Foresight, Wild Cards and Weak Signals Analysis by Rafael Popper, Yuli Villarroel, Raimund Popper

“…This model also explores AI, machine learning, and explainable AI (XAI) in labor market dynamics, where predictive algorithms can identify trends and mitigate systemic risks. …”
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Dynamic Spectrum Coexistence of NR-V2X and Wi-Fi 6E Using Deep Reinforcement Learning by Kashish D. Shah, Dhaval K. Patel, Brijesh Soni, Siddhartan Govindasamy, Mehul S. Raval, Mukesh Zaveri

“…Most existing works on coexistence rely on rule-based approaches or classical machine learning algorithms. These approaches may fall short in real-time environments where adaptive decision-making is required. …”
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Emerging Technologies Driving Zero Trust Maturity Across Industries by Hrishikesh Joshi

“…Furthermore, the integration of AI and machine learning in Zero Trust frameworks raises questions about data privacy, algorithmic bias, and the need for explainable security decisions. …”
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A Systematic Mapping Study on State Estimation Techniques for Lithium-Ion Batteries in Electric Vehicles by Carolina Tripp-Barba, José Alfonso Aguilar-Calderón, Luis Urquiza-Aguiar, Aníbal Zaldívar-Colado, Alan Ramírez-Noriega

“…RUL prediction sees advancements through deep learning techniques, especially LSTM and gated recurrent units (GRUs), improved using algorithms such as Harris Hawks Optimization (HHO) and Adaptive Levy Flight (ALF). …”
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Modeling of Distorted Degradation Data Based on Oil Analysis by Yue Chen, Jian Shi

“…Second, we developed a three-step explosion search algorithm for robust parameter estimation. Notably, though our methodology was initially developed for wear degradation analysis, this data-driven framework demonstrates adaptability to broader degradation scenarios. …”
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Artificial Intelligence in Orthopedic Medical Education: A Comprehensive Review of Emerging Technologies and Their Applications by Kyle Sporn, Rahul Kumar, Phani Paladugu, Joshua Ong, Tejas Sekhar, Swapna Vaja, Tamer Hage, Ethan Waisberg, Chirag Gowda, Ram Jagadeesan, Nasif Zaman, Alireza Tavakkoli

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