Analysis of Two-Grid Characteristic Finite Element Methods for Convection-Diffusion Equations by Keyan Wang, Boxia Hu

“…We present an optimal error estimate in Lp-norm for the characteristic finite element method unconditionally, while all previous works require certain time-step restrictions. …”
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Analysis of Blockchain-Technology by Danylo Dvorchuk, Iryna Shpinareva

“…The study explores the comparative advantages and limitations of different blockchain architectures and evaluates emerging optimization techniques such as hybrid consensus algorithms and artificial intelligence-based enhancements. …”
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Turning Energy-Aware Route Planning With an Extended TSP and Double-Layer State Graph: Experimental Evaluation With a Crawler Mobile Robot by Namihei Adachi, Hisashi Date

“…The routes that minimized energy consumption showed an average 17 % reduction in energy consumption, while the routes that minimized travel time achieved an average 5 % reduction in travel time compared to the standard TSP algorithm.…”
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Research on Unmanned Aerial Vehicle Path Planning for Carbon Emission Monitoring of Land-Side Heavy Vehicles in Ports by Xincong Wu, Zhanzhu Li, Xiaohua Cao

“…In the simulation experiment results, the proposed algorithm outperforms A*, ACO, and IEA algorithms in optimizing path length, reducing collision points to ensure path safety, and robustness. …”
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Differentiable architecture search-based automatic modulation recognition for multi-carrier signals by LI Jie, LI Jing, LYU Lu, GONG Fengkui

“…Simulation results demonstrate that the proposed algorithm improves accuracy in urban multipath channels, especially at low SNR, while simultaneously providing better robustness to modulation parameter variations and small-sample scenarios.…”
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Retrieval of water quality parameters based on IOA-ML models and their response to short-term hydrometeorological factors by Wentong Hu, Donghao Miao, Chi Zhang, Zixian He, Wenquan Gu, Dongguo Shao

“…The best IOA-ML model for total phosphorus (TP), total nitrogen (TN), and permanganate index (CODMn) was extreme gradient boosting optimized by genetic algorithm (GA-XGB), while that for dissolved oxygen (DO) and turbidity was categorical boosting regression optimized by GA (GA-CBR). …”
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Artificial Intelligence-Based Techniques for Fouling Resistance Estimation of Shell and Tube Heat Exchanger: Cascaded Forward and Recurrent Models by Ikram Kouidri, Abdennasser Dahmani, Furizal Furizal, Alfian Ma’arif, Ahmed A. Mostfa, Abdeltif Amrane, Lotfi Mouni, Abdel-Nasser Sharkawy

“…The training process is optimized using the Levenberg–Marquardt (LM) algorithm, ensuring rapid convergence and high accuracy. …”
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A real-time 3D modeling method for buildings driven by IMU and RGB-D fusion by Yuhan Gao, Chao Dang, Jun Zhu, Yakun Xie, Ya Hu, Chunli Yan, Kun Yi, Chuan Yi, Xue Li

“…The method incorporates an adaptive sampling strategy for RGB-D cameras based on IMU data calibration, introduces a pose estimation optimization algorithm that combines dynamic feature point cluster centroid prediction with bias detection, establishes a progressive 3D modeling approach constrained by structural features, and develops a prototype system for in-depth case study analysis. …”
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Machine learning enables legal risk assessment in internet healthcare using HIPAA data by Shixian Liu, Hailing Liu, Siyu Fan, Leming Song, Zeyu Wang

“…Each algorithm has its strengths and limitations depending on the specific legal risk assessment task. …”
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Modify a dual ridge horn antenna for drone jamming applications by Alaa Hussein Hilal, Ahmed Hameed Reja, Mohammed J. Mohammed

“…This work presents a DRHA developed utilizing CST Studio and optimized by using genetic algorithm optimization (GA) that has been employed to improve parameters that enhance selected frequencies. …”
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A Robust Game Approach for On Spot Price Cloud Markets in Microservice-Based Applications by Hamta Sedghani, Mauro Passacantando, Riccardo Lancellotti, Mina Zolfy Lighvan, Danilo Ardagna

“…Furthermore, we propose a best-reply algorithm to identify a robust GNE, ensuring that the solution remains feasible even under the worst-case scenarios of uncertain parameters. …”
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Huffman coding-based data reduction and quadristego logic for secure image steganography by Irsyad Fikriansyah Ramadhan, Ntivuguruzwa Jean De La Croix, Tohari Ahmad, Andre Uzamurengera

“…To address these challenges, this study proposes a novel steganographic algorithm integrating two key innovations: (1) Enhancement of stego image quality via stego image’s segmentation into four images, reducing concentration-induced distortions, and (2) optimization of data embedding through Huffman coding through a lossless compression minimizing the embedding-induced distortions while maximizing payload capacity. …”
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Multiplicity and stability of solutions in transport phenomena of non-Newtonian Carreau nanofluid with nonlinear Rosseland thermal approximations and neural prediction by Puneet Rana, Xinyi Zhu, Ioan Pop

“…The optimal number of neurons in a single hidden layer is determined and compared using metrics R2 and RMSE for each algorithm. …”
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Experimental Study on Evaluation of Organization Collaboration in Prefabricated Building Construction by Dingjing Bao, Yuan Chen, Shuai Wan, Jinlai Lian, Ying Lei, Kaizhe Chen

“…The knowledge-driven part of this evaluation system used an evaluation model based on the analytic hierarchy process (AHP), while the data-driven part used a prediction model based on the BO-XGBoost algorithm to verify the validity of the AHP-based model. …”
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Analyzing the impact of non-Newtonian nanofluid flow on pollutant discharge concentration in wastewater management using an artificial computing approach by Sidra Jubair, Jie Yang, Bilal Ali, Bandar Bin-Mohsin, Hamiden Abd El-Wahed Khalifa

“…These equations (ODEs) are solved using the Levenberg Marquardt back-propagation optimization algorithm (LMBOA) of the artificial neural network (ANN). …”
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Predicting weather-related power outages in large scale distribution grids with deep learning ensembles by L. Prieto-Godino, C. Peláez-Rodríguez, J. Pérez-Aracil, J. Pastor-Soriano, S. Salcedo-Sanz

“…This paper focuses on predicting daily reported incidences in electrical grids within specific regions, leveraging weather conditions as specific predictive variables. An optimization-based feature selection approach has been considered for selecting the optimal Reanalysis node locations used as predictors. …”
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Machine Learning to Select Experiments Driven by Fundamental Science and Applications for Targeted Nuclear Data Improvement by D. Neudecker, T. E. Cutler, M. Devlin, P. Brain, N. Gibson, M. J. Grosskopf, M. W. Herman, J. Hutchinson, T. Kawano, A. Khatiwada, N. Kleedtke, E. Leal-Cidoncha, R. C. Little, A. E. Lovell, A. Stamatopoulos, E. C. Thompson, S. A. Vander Wiel, E. Williamson

“…We chose as differential measurements those that investigate ^{63}Cu and ^{239}Pu total cross sections, based on D-optimality rank and feasibility constraints. Two integral (criticality) experiments were selected: An experiment with Al_{2}O_{3} and graphite interleaved with Pu and a thick Cu reflector explores 1–30 keV, while we target the 30–600 keV range with an experiment that swaps boron in place of graphite with a different geometry.…”
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Multi-time Scale Voltage-Reactive Power Control for Distribution Network with Distributed Generation by LIU Haotian, ZHENG Chuyu, LENG Yang, LI Qin, ZHANG Hua, CHEN Shidu, LI Jiayong

“…And for the voltage regulation, it can optimize the regulation target according to the voltage sensitivity and the regulation costs of each DG, and thus has better economic performance while adjusting voltages.…”
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SQNR Improvement Enabled by Nonuniform DAC Output Levels for IM-DD OFDM Systems by Jizong Peng, Lei Han, Qingming Zhu, Ciyuan Qiu, Yong Zhang, Christine Tremblay, Yikai Su

“…Our scheme enables transmission of such signals with no further optimization with ∼−25-dBm receiver sensitivity, while it is impossible using a conventional way. …”
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AI-driven modeling for predicting compressive strength of recycled aggregate concrete under thermal conditions for sustainable construction by Morteza Ghodratnama, Amir R. Masoodi, Amir H. Gandomi

“…A detailed comparative analysis revealed that ANN models outperformed GEP in terms of predictive accuracy, while GEP models offered interpretable equations for practical engineering use. …”
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