A Swarm-Based Multi-Objective Framework for Lightweight and Real-Time IoT Intrusion Detection by Hessah A. Alsalamah, Walaa N. Ismail

“…However, the high dimensionality, class imbalance, and complexity of network traffic—combined with the dynamic nature of sensor networks—pose substantial challenges to the development of efficient and effective detection algorithms. …”
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Advancing pavement preservation: Comprehensive analysis and optimization of microsurfacing mixtures with stabilizers, bitumen types, emulsifiers, and fiber impacts by Ali Latifi, Parham Hayati, Ahmad Goli

“…These insights emphasize the criticality of precise additive selection in optimizing microsurfacing efficiency and provide effective guidelines for the optimal design of microsurfacing mixtures.…”
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Inverse-design topology optimization of magnonic devices using level-set method by Andrey A. Voronov, Marcos Cuervo Santos, Florian Bruckner, Dieter Suess, Andrii V. Chumak, Claas Abert

“…While promising for analog, Boolean, and neuromorphic computing, current implementations face memory limitations that hinder the design of complex systems. This study presents a level-set parameterization method for topology optimization, combined with an adjoint-state approach for memory-efficient simulation of magnetization dynamics. …”
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Soil Organic Matter (SOM) Mapping in Subtropical Coastal Mountainous Areas Using Multi-Temporal Remote Sensing and the FOI-XGB Model by Hao Zhang, Xiaomei Li, Jinming Sha, Jiangning Ouyang, Zhipeng Fan

“…Current remote sensing inversion of SOM faces challenges, including the underutilization of temporal information and low feature selection efficiency. To address these limitations, this study developed an integrated framework combining multi-temporal Landsat imagery, field-measured SOM data, intelligent feature optimization, and machine learning. …”
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Decision support systems for waste-to-energy technologies: A systematic literature review of methods and future directions for sustainable implementation in Ghana by Theophilus Frimpong Adu, Lena Dzifa Mensah, Mizpah Ama Dziedzorm Rockson, Francis Kemausuor

“…These tools have demonstrated their effectiveness in handling the complex, multi-faceted nature of WtE technology selection and implementation, addressing issues ranging from site selection to technology ranking based on multiple criteria. …”
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Optimization of Bolted Steel T-Stub Connection Based on Nonlinear Finite Element Analysis Using Genetic Algorithm by Péter Grubits, Tamás Balogh, Majid Movahedi Rad

“…To enhance the simulation efficiency and reduce the computational time without significantly compromising accuracy, the study introduces a simplified modeling methodology. …”
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A Proposal for a New Python Library Implementing Stepwise Procedure by Luiz Paulo Fávero, Helder Prado Santos, Patrícia Belfiore, Alexandre Duarte, Igor Pinheiro de Araújo Costa, Adilson Vilarinho Terra, Miguel Ângelo Lellis Moreira, Wilson Tarantin Junior, Marcos dos Santos

“…Carefully selecting variables in problems with large volumes of data are extremely important, as it reduces the complexity of the model, improves the interpretation of the results, and increases computational efficiency, ensuring more accurate and relevant analyses. …”
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MATHEMATICAL MODELS OF DECISION SUPPORT IN THE PROBLEMS OF LOGISTICS NETWORKS OPTIMIZATION by Володимир Валентинович Безкоровайний, Оксана Михайлівна Драз

“…The practical use of the proposed models and procedures will reduce the time and capacity complexity of decision support technologies, and through the use of the proposed selection procedures - to improve their quality across a variety of functional and cost indicators.…”
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Innovative computational model for optimal deep coal mining under large-scale crustal stress conditions by Shuanhu Li, Chi Li, De Yao, Yuanhao Xing

“…Abstract Understanding and controlling the ground stress in deep coalfield mining is crucial for ensuring mine safety and efficiency. This study aims to address two unresolved scientific issues in ground stress research: the selection of optimal excavation plans and the large-scale rapid acquisition of ground stress data. …”
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Uncertainty‐aware nuclear power turbine vibration fault diagnosis method integrating machine learning and heuristic algorithm by Ruirui Zhong, Yixiong Feng, Puyan Li, Xuanyu Wu, Ao Guo, Ansi Zhang, Chuanjiang Li

“…The numerous state parameters in the operation and maintenance of nuclear power turbines are collected, forming a complex high‐dimensional feature space. These high‐dimensional feature spaces contain redundant information, which increases the training cost and reduces the recognition accuracy and efficiency of the fault diagnosis model. …”
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Human autonomy teaming-based safety-aware navigation through bio-inspired and graph-based algorithms by Timothy Sellers, Tingjun Lei, Chaomin Luo, Zhuming Bi, Gene Eu Jan

“…Human Autonomy Teaming (HAT) is crucial for promoting safe and efficient human–robot collaboration in dynamic indoor environments. …”
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A novel wind speed prediction model based on neural networks, wavelet transformation, mutual information, and coot optimization algorithm by Faezeh Amirteimoury, Farshid Keynia, Elaheh Amirteimoury, Gholamreza Memarzadeh, Hanieh Shabanian

“…To evaluate the efficiency of the proposed model, its performance was measured using error metrics such as mean squared error, mean absolute error, mean absolute percentage error, coefficient of determination ( $$R^2$$ ), and median absolute error. …”
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Identification of digital clinical decision support systems for supporting diagnosis and triage of patients with shoulder disorders: A scoping review protocol. by Cheyenne R Schamerhorn, Nathaniel M Peñas, Jared R Fletcher, Richard Hayman, Breda H F Eubank

“…Primary care decision-making is complex and has the potential to influence quality of care provided and patient outcomes. …”
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CAMP: Counterexamples, Abstraction, MDPs, and Policy Refinement for Enhancing Safety, Stability, and Rewards in Reinforcement Learning by Ryeonggu Kwon, Gihwon Kwon

“…The proposed method enhances computational efficiency in complex state spaces through state abstraction and strengthens policy safety by employing the PRISM model checker to quantitatively analyze transitions to failure states. …”
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Key frame extraction algorithm for surveillance videos using an evolutionary approach by Manjusha Rajan, Latha Parameswaran

“…Furthermore, the computational complexity of the GA is intricately compared to that of DE and DL-based approaches, highlighting the distinct efficiencies and performance features.…”
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Methodology for assessing the social effectiveness of exhibition activity by Yu. V. Vorontsova, D. S. Garbuz

“…The article presents the methodology developed by the authors for the quantitative assessment of social efficiency, which is complex and also includes the calculation of the selected elements’ sensitivity of social efficiency to different changes. …”
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Identification of SSR marker linked to gynoecious loci in cucumber (Cucumis sativus L.) by ZHOU Shengjun, ZHANG Peng, ZHU Yuqiang, CHEN Xinjuan, CHEN Liping

“…The use of molecular markers for indirect selection of important agronomic characters, or marker-assisted selection (MAS) can improve the efficiency of traditional breeding. …”
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Hierarchical Reinforcement Learning with Automatic Curriculum Generation for Unmanned Combat Aerial Vehicle Tactical Decision-Making in Autonomous Air Combat by Yang Li, Wenhan Dong, Pin Zhang, Hengang Zhai, Guangqi Li

“…Additionally, the visual analysis of UCAVs’ flight logs validates the learned hierarchical decision-making process, showcasing the interplay between tactical selection and manoeuvring execution. This research provides novel methodologies combining hierarchical reinforcement learning with tactical domain knowledge for the autonomous decision-making of UCAVs in complex air combat scenarios.…”
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Evaluating the effect of digital elevation model resolution in lahar hazard simulations: insights from the 1877 Cotopaxi scenario, Ecuador by Francisco J. Vasconez, Francisco J. Vasconez, Jeremy C. Phillips, S. Daniel Andrade, Mark J. Woodhouse

“…This work provides a quantitative framework to guide DEM selection, balancing computational efficiency with predictive fidelity in lahar hazard assessment.…”
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Enhancing biometric identification using 12-lead ECG signals and graph convolutional networks by Maram Al Alfi, Pedro Peris-Lopez, Carmen Camara

“…The GCN model is trained on this graph, enabling it to learn complex patterns for user identification efficiently.ResultsExperimental results demonstrate that the proposed GCN-MI model achieves 100% accuracy with a 5-layer architecture at a k-fold of 75, outperforming conventional approaches that require less training data.DiscussionThis work introduces several innovations: the integration of MI indices enhances feature selection, improving model robustness and efficiency; the graph-based learning framework effectively captures both spatial and statistical relationships within ECG data, leading to higher classification accuracy; the proposed approach offers a scalable and real-time biometric authentication system suitable for applications in finance, healthcare, and personal device access. …”
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