Optimal design and performance prediction of stepped honeycomb labyrinth seal using CFD and ANN by Geunseo Park, Min Seok Hur, Tong Seop Kim

“…An ANN-based performance prediction metamodel was developed, and a genetic algorithm was applied to the metamodel to optimize seal geometry, achieving a 12.34% improvement in leakage performance over the reference seal. …”
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An Efficient Evolutionary Task Scheduling/Binding Framework for Reconfigurable Systems by A. Al-Wattar, S. Areibi, G. Grewal

“…The proposed Island Based GA framework achieves on average 55.2% improvement over a single-GA implementation and an 80.7% improvement over a baseline random allocation and binding approach.…”
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High Precision Navigation and Positioning for Multisource Sensors Based on Bibliometric and Contextual Analysis by Jiayi Wei, Min Song, Yunbin Yuan

“…The study concludes by summarizing existing research findings and identifying gaps, with future research focusing on optimizing multisensor fusion algorithms, enhancing system adaptability, improving error models, and enhancing sensor performance in adverse environmental conditions.…”
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Assessing the Risk of Artificial Intelligence Impact on Decision-Making Automation in Digital Businesses by Mioara Chirita, George Chirita

“…While AI-enabled automation has many benefits, such as improved scalability, accuracy, and efficiency, it also brings new hazards that businesses need to be aware of. …”
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Research on the Operation Optimization of Public Building Systems in Extremely Cold Areas Based on Flexible Loads by Chuan Tian, Shunli Jiang, Shuai Li, Guohui Feng, Bin Yu

“…Flexible loads can actively participate in controlling the operation of the power grid, improving the energy utilization and the economy of the system. …”
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Equilibrium Analysis of Electricity Market with Multi-Agents Considering Uncertainty by Zhonghai Sun, Runyi Pi, Junjie Yang, Chao Yang, Xin Chen

“…A hybrid solution methodology integrating nonlinear complementarity formulations with genetic algorithm-based optimization was developed. Extensive numerical case studies validate the methodological efficacy, demonstrating improvements in solution optimality and computational efficiency compared to conventional approaches.…”
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Inverse Dynamic Parameter Identification for Remote Sensing of Soil Moisture From SMAP Satellite Observations by Runze Zhang, Adam Watts, Mohamad Alipour

“…In the soil moisture active passive (SMAP) mission&#x0027;s soil moisture retrieval algorithms, the effects of surface roughness and vegetation scattering on the brightness temperature are conventionally modeled using time-invariant parameters: roughness intensity (<italic>h</italic>) and effective scattering albedo (&#x03C9;). …”
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Adaptive gradient scaling: integrating Adam and landscape modification for protein structure prediction by Vitalii Kapitan, Michael Choi

“…Despite their success, machine learning methods face fundamental limitations in optimizing complex high-dimensional energy landscapes, which motivates research into new methods to improve the robustness and performance of optimization algorithms. …”
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Identification of biomarkers for the diagnosis of type 2 diabetes mellitus with metabolic associated fatty liver disease by bioinformatics analysis and experimental validation by Guiling Wu, Guiling Wu, Sihui Wu, Sihui Wu, Tian Xiong, Tian Xiong, Tian Xiong, You Yao, You Yao, Yu Qiu, Yu Qiu, Yu Qiu, Liheng Meng, Cuihong Chen, Xi Yang, Xi Yang, Xi Yang, Xinghuan Liang, Yingfen Qin

“…Candidate biomarkers were screened using machine learning algorithms combined with 12 cytoHubba algorithms, and a diagnostic model for T2DM-related MAFLD was constructed and evaluated.The CIBERSORT method was used to investigate immune cell infiltration in MAFLD and the immunological significance of central genes. …”
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A Stabilized Incompressible SPH Method by Relaxing the Density Invariance Condition by Mitsuteru Asai, Abdelraheem M. Aly, Yoshimi Sonoda, Yuzuru Sakai

“…In order to overcome this problem, there are several improvements. One is small compressibility approach, and the other is introduction of two kinds of pressure Poisson equation related to velocity divergence-free and density invariance conditions, respectively. …”
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An Intelligent Path Planning System for Urban Airspace Monitoring: From Infrastructure Assessment to Strategic Optimization by Qianyu Liu, Wei Dai, Zichun Yan, Claudio J. Tessone

“…Extensive simulations demonstrate that the proposed approach significantly improves path success rates, reduces traversal through poorly monitored regions, and maintains high navigation efficiency. …”
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Building Equi-Width Histograms on Homomorphically Encrypted Data by Dragoș Lazea, Anca Hangan, Tudor Cioara

“…Histograms are widely used for summarizing data distributions, detecting anomalies, and improving machine learning models’ accuracy. However, traditional histogram-based methods require access to raw data, raising privacy concerns, particularly in sensitive IoT applications. …”
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Intelligent Counterforce Allocation Method Using Multi-Agent Reinforcement Learning for Ground Operations by Kiwoong Park, Sangheun Shim

“…Compared to rule-based approaches, ICAGO demonstrates lower performance variance and significantly improves doctrinal metrics, including up to a 30% increase in win rate and enhanced protection of critical friendly zones, even under uncertainty and diverse operational scenarios. …”
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Synergistic Effects of Energy Storage Systems and Demand-Side Management in Optimizing Zero-Carbon Smart Grid Systems by Zeyad A. Almutairi, Ali M. Eltamaly

“…An advanced load and weather-forecasting strategy is introduced for improving grid planning and management. An advanced optimization algorithm enhances grid stability and efficiency. …”
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Impacts of Spatial Expansion of Urban and Rural Construction on Typhoon-Directed Economic Losses: Should Land Use Data Be Included in the Assessment? by Siyi Zhou, Zikai Zhao, Jiayue Hu, Fengbao Liu, Kunyuan Zheng

“…Results demonstrate three key findings: (1) By introducing prototype learning, a meta-learning approach, to guide model updates, we achieved precise assessments with small training samples, attaining an MAE of 1.02, representing 58.5–76.1% error reduction compared to conventional machine learning algorithms. …”
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Syn-MolOpt: a synthesis planning-driven molecular optimization method using data-derived functional reaction templates by Xiaodan Yin, Xiaorui Wang, Zhenxing Wu, Qin Li, Yu Kang, Yafeng Deng, Pei Luo, Huanxiang Liu, Guqin Shi, Zheng Wang, Xiaojun Yao, Chang-Yu Hsieh, Tingjun Hou

“…Abstract Molecular optimization is a crucial step in drug development, involving structural modifications to improve the desired properties of drug candidates. …”
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Breast lesion classification via colorized mammograms and transfer learning in a novel CAD framework by Abbas Ali Hussein, Morteza Valizadeh, Mehdi Chehel Amirani, Sedighe Mirbolouk

“…In a subsequent step, Machine Learning (ML) algorithms are employed to classify these tumors as malign or benign cases. …”
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Artificial Intelligence for Predicting Delivery Modes: A Systematic Review of Applications, Challenges, and Future Directions by Yu Zhou, Jing Li, Xiaomei Hou, Zhen Li, Yanan Xu, Yan Wang, Mingze Sun, Fumin Zheng, Enhui Guo, Jun Zhou

“…Conclusions: Future research should prioritize data standardization and sharing, enhance the generalizability of prediction models, address ethical considerations, and ensure the fairness and transparency of AI algorithms to improve clinical trust and applicability. …”
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DIP-UP: Deep Image Prior for Unwrapping Phase by Xuanyu Zhu, Yang Gao, Zhuang Xiong, Wei Jiang, Feng Liu, Hongfu Sun

“…We compared the DIP-refined models to their original versions, as well as to the conventional PRELUDE algorithm from FSL, using both simulated and in vivo brain data. …”
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Asymptotic Approximation of the Stationary Solution with Internal Layer for FitzHugh–Nagumo System by A. A. Melnikova, R. L. Argun

“…The application of contrast structures theory to the study of active media models can be used for analytical studies of other such systems, improving existing models and increasing the efficiency of the numerical calculations.…”
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