Comparative analysis of methods for predicting train-induced vibrations by Wei-Lun Hsu, Wei-Bin Chen, Meng-Ting Hsieh

“…The study compared measured and predicted vibration levels to assess the accuracy of the FTA’s detailed and general prediction methods. Results indicate that detailed assessments tend to overestimate vibration levels, while an optimized general vibration assessment curve offers a more precise estimate. …”
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Numerical solutions development for radiating flow of rheological nanoliquid invoking entropy optimization by Aqsa Razzaq, Tasawar Hayat, Sohail A. Khan, Aneeta Razaq

“…Entropy optimization with motile microorganism and chemical reaction is discussed. …”
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Hardware/Software Co-Design Optimization for Training Recurrent Neural Networks at the Edge by Yicheng Zhang, Bojian Yin, Manil Dev Gomony, Henk Corporaal, Carsten Trinitis, Federico Corradi

“…In this study, we propose a system for RNN training through sequence partitioning using the Forward Propagation Through Time (FPTT) training method, thereby enabling edge learning. Our optimized hardware/software co-design for FPTT represents a novel contribution in this domain. …”
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Alpine Wetlands Information Extraction Using Optimized Multifeatures and Random Forest Algorithm by Dongchuan Wang, Fei Yang, Shijie Jia, Zhiheng Wang, Chunhua Dong, Mingwei Lang, Kai Ye, Haotian Liu, Tingrong Li

“…Then, the RF algorithm is applied to optimize the filtered features. Finally, the RF classification model is used to refine wetland extraction based on this optimized feature set. …”
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Demand-Responsive Evaluation and Optimization of Fitness Facilities in Urban Park Green Spaces by Xiaohui Lv, Kangxing Li, Jiyu Cheng, Ziru Ren

“…Accurately identifying user demand provides a solid basis for optimizing the functional configuration of urban parks. (2) Methods: This study took the old city area of Zhengzhou, Henan Province, China, as a case study. …”
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Social Programs in the Structure of Expenditures of the Consolidated Budget of the Federa-tion Subject by A. S. Dmitriev, A. M. Stash

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Enhancing access to underutilized ground water potential for improving livelihoods and conflict reduction in Kagera Sub-Basin, Tanzania by Estella Mgala, Joel Nobert, Edmund B. Mabhuye, Brown Gwambene

“…The study employed a mixed-methods approach, utilizing key informant interviews, household questionnaires, focus group discussions, direct observations, and secondary data sources. …”
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Day-Ahead Scheduling of IES Containing Solar Thermal Power Generation Based on CNN-MI-BILSTM Considering Source-Load Uncertainty by Kun Ding, Yalu Sun, Boyang Chen, Jing Chen, Lixia Sun, Yingjun Wu, Yusheng Xia

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Dietary Sources and Nutrient Adequacy Potential of Local Foods among Children (6–23 Months) in Urban Slums of West Oromia (Ethiopia) by Wondu Garoma Berra

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Enhancing LiDAR Data Positioning Accuracy in National Forest Surveys through Multi-Source Point Cloud Matching in Terrasolid software by A. Shcherbacheva, A. Puttonen, A. Soininen

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LiDAR-Based Road Cracking Detection: Machine Learning Comparison, Intensity Normalization, and Open-Source WebGIS for Infrastructure Maintenance by Nicole Pascucci, Donatella Dominici, Ayman Habib

“…A key contribution of this work is the integration of geospatial analytics into an interactive, open-source WebGIS environment—developed using Blender, QGIS, and Lizmap—to support predictive maintenance planning. …”
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Multi-peak light sources can improve the physical and mechanical properties of a zirconia- and diatomite-based dental resin: an in vitro study by Jucivaldo Martins Gonçalves, Thalles Arievo Mota Sales, Cauã Santiago Figueiredo, Rafael Pinto de Mendonça, Jefferson Pires da Silva Júnior, Tânia Mara da Silva, Sérgio Eduardo de Paiva Gonçalves, Hércules Bezerra Dias

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Automated reinforcement learning for sequential ordering problem using hyperparameter optimization and metalearning by André Luiz Carvalho Ottoni

“…Therefore, this paper aims to present a new AutoRL approach for SOP. For this, two new methods are proposed using hyperparameter optimization and metalearning: AutoRL-SOP and AutoRL-SOP-MtL. …”
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Evolutionary adaptation of probiotics in the gut: selection pressures, optimization strategies, and regulatory challenges by Julia Leeflang, Josephine A. Wright, Daniel L. Worthley, M. Omar Din, Susan L. Woods

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Fairness-Oriented Charging Station Location Optimization Driven by Deep Reinforcement Learning by Siyue Yuan, Jiaying Fu, Xiaoyin Ma

“…Existing studies mostly rely on static data and traditional optimization methods, which are unable to adapt to the dynamic changes in the city, necessitating innovative strategies to improve both fairness and efficiency in location planning. …”
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Making JavaScript Render Decisions to Optimize Security-Oriented Crawler Process by Onur Aktas, Ahmet Burak Can

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Framework for the Multi-Objective Optimization of Hybrid Fuel Cell System Design and Operation by Luis M. Winkler, Alexander Kabza, Michael A. Danzer, Herbert Palm

“…The results, which can be transferred to other conflicting target variables and their simultaneous optimization, demonstrate the fundamental superiority of a Pareto-optimal system design and operational management over previous development methods.…”
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Statistical optimization characterizations and Eco- friendly synthesis of silica from sugarcane bagasse by Girma Assefa Habte, Tafere Aga Bullo, Yasin Ahmed

“…Abstract This research explores the synthesis and optimization of Silica have been effectively produced from sugarcane bagasse (SB) using the sol-gel methods. …”
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Optimization of The Budget of The Industrial Complex Transformation Strategy Based on Neural Network Modeling by A. G. Boev, A. G. Puzakov, Yu. P. Anisimov

“…Currently, Russian industry is developing mainly along an extensive path that does not provide a deep innovative transformation of business and the necessary increase in labor productivity.Materials and methods. The data source for the study is Rosstat materials on the development of industry in the Russian Federation, indicators of economic activity of industrial companies contained in SPARK-Interfax databases, as well as the results of monitoring activities of KPMG and the Agency for Strategic Initiatives. …”
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Predicting the Classification of Heart Failure Patients Using Optimized Machine Learning Algorithms by Marzia Ahmed, Mohd Herwan Sulaiman, Md Maruf Hassan, Touhid Bhuiyan

“…This study proposes an optimized machine learning approach using Gradient Boosting Machine (GBM) and Adaptive Inertia Weight Particle Swarm Optimization (AIW-PSO) to predict heart failure survival. …”
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