Economic Dispatch Analysis of Risk Prevention and Control Based on Game Theory Equilibrium by Qixiang WANG, Zhentao HAN, Yi LIANG

“…In order to solve these problems, this paper first proposes an economic dispatch mathematical model for risk prevention and control of the power system considering green power generation and consumption and then puts forward a game theory equilibrium solution algorithm based on the optimal response method. Through case analysis, the game theory equilibrium situation of the economic dispatch problem under the generation and consumption of renewable energy is evaluated, and relevant suggestions are put forward for investment planning on the power generation side of the power system.…”
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The Adversarial Robust and Generalizable Stereo Matching for Infrared Binocular Based on Deep Learning by Bowen Liu, Jiawei Ji, Cancan Tao, Jujiu Li, Yingxun Wang

“…To compute the matching cost volume, we apply the multi-scale census transform to the input stereo images. …”
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Predicting biomarkers of progressive pulmonary fibrosis: morphological, cytokine profile, and clinical portrait by Nicol Bernardinello, Federica Pezzuto, Lauren D’Sa, Luca Vedovelli, Chiara Giraudo, Anamaria Chelu, Anamaria Chelu, Cecilia de Chellis, Francesca Lunardi, Francesco Fortarezza, Francesca Boscaro, Elisabetta Cocconcelli, Paolo Spagnolo, Elisabetta Balestro, Fiorella Calabrese

“…Lung specimens revealed a significant overexpression of IL9 in the PPF compared to the nPPF group (p=0.049). Boruta algorithm analysis showed that lymphoid aggregates and traction bronchiectasis at diagnosis are the most important variables in determining the PPF status.ConclusionsThe present results increase the understanding of the pathological mechanisms of PPF, offering potential avenues for improved prognostication and therapeutic intervention.…”
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Analysis of influencing factors and equity in hospitalization expense reimbursement for mobile populations based on random forest model: a cross-sectional study from China by Lisheng Shen, Xinan Lu, Yanyun Zhang, Lin Fei, Bo Dong

“…Factors contributing to hospitalization cost reimbursement probability inequity, listed in descending order of impact are education (42.3%), income (34.1%), health (12.4%), age (8.2%), and enrollment location (3.0%); factors contributing to the level of hospitalization reimbursement inequity, listed in descending order of impact are health (58.12%), mobility range (21.74%), total healthcare expenditures (9.35 %), type of healthcare coverage (9.28%), and illness (1.51%).ConclusionThere is still much room for improvement in the reimbursement rate of hospitalization expenses for the migrant population. …”
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SORA: Energy-Efficient Resource Allocation in Open Radio Access Network With Online Learning by Aerman Tuerxun, Akihiro Nakao

“…By integrating variational inference with Thompson Sampling, the framework efficiently balances exploration and exploitation, allowing dynamic adjustment of MCS and PRB allocations in response to changing network states. The proposed algorithm achieves sub-linear regret, ensuring convergence toward an optimal policy over time while maintaining robust adaptability. …”
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Enhancing Latent Defect Detection in Built-In Spindle Assembly Lines Through Vibration Data Analysis by Kuo-Hao Li, Chao-Nan Wang, Yao-Chi Tang

“…The integration of these advanced algorithms accurately identified defects and categorized them, thus optimizing manufacturing processes. …”
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The Analysis of the Possibility to Conduct Orbital Manoeuvres of Nanosatellites in the Context of the Maximisation of a Specific Operational Task by Magdalena Lewinska, Michal Kedzierski

“…For example, slight adjustments to the altitude of the orbit with the use of Hohmann transfer proved to be optimal in terms of fuel costs. On the other hand, changes in inclination, although they are definitely energy-consuming, may significantly improve the coverage of the defined area. …”
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Cerebral gray matter volume identifies healthy older drivers with a critical decline in driving safety performance using actual vehicles on a closed-circuit course by Handityo Aulia Putra, Kaechang Park, Kaechang Park, Fumio Yamashita

“…Feature selection and classification were performed using the Random Forest machine learning algorithm, optimized to identify the most predictive GM regions.ResultsOut of 114 GM regions, eleven were selected as optimal predictors: left angular gyrus, frontal operculum, occipital fusiform gyrus, parietal operculum, postcentral gyrus, planum polare, superior temporal gyrus, and right hippocampus, orbital part of the inferior frontal gyrus, posterior cingulate gyrus, and posterior orbital gyrus. …”
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A survey on resource allocation in backscatter communication networks by Yongjun XU, Haoke YANG, Yinghui YE, Qianbin CHEN, Guangyue LU

“…With the development of Internet of things (IoT) technology, wireless networks have the characteristics of massive user access, high power consumption, and high capacity requirements.In order to meet the transmission requirements and reduce energy consumption, backscatter communication technology was considered to be one of the most effective solutions to the above problems.In the fact of complex network scenarios, the improvement of spectrum efficiency, system capacity, and energy management has become an urgent problem of resource allocation areas in backscatter communications.For this problem, resource allocation algorithms in backscatter communications were surveyed.Firstly, the basic concept and different network architectures of backscatter communication were introduced.Then, resource allocation algorithms in backscatter communication networks were analyzed according to different network types, optimization objectives, and the number of antennas.Finally, the challenges and future research trends of resource allocation problems in backscatter communication networks were prospected.…”
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Smart CAR-T Nanosymbionts: archetypes and proto-models by Juan C. Baena, Juan C. Baena, Juan Sebastián Victoria, Juan Sebastián Victoria, Alejandro Toro-Pedroza, Alejandro Toro-Pedroza, Cristian C. Aragón, Cristian C. Aragón, Joshua Ortiz-Guzman, Joshua Ortiz-Guzman, Joshua Ortiz-Guzman, Juan Esteban Garcia-Robledo, Juan Esteban Garcia-Robledo, David Torres, Lady J. Rios-Serna, Lady J. Rios-Serna, Ludwig Albornoz, Joaquin D. Rosales, Joaquin D. Rosales, Carlos A. Cañas, Carlos A. Cañas, Carlos A. Cañas, Gustavo Adolfo Cruz-Suarez, Gustavo Adolfo Cruz-Suarez, Gustavo Adolfo Cruz-Suarez, Gustavo Adolfo Cruz-Suarez, Felipe Ocampo Osorio, Felipe Ocampo Osorio, Felipe Ocampo Osorio, Tania Fleitas, Ivan Laponogov, Alexandre Loukanov, Alexandre Loukanov, Alexandre Loukanov, Kirill Veselkov, Kirill Veselkov

“…At the same time, artificial intelligence (AI), with its powerful algorithms for data analysis and predictive modeling, is transforming how we design, evaluate, and monitor advanced therapies, including the optimization of manufacturing processes. …”
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Evaluation of Liver Fibrosis through Noninvasive Tests in Steatotic Liver Disease by Yuri Cho

“…Further research is needed to refine these diagnostic tools and improve accessibility.…”
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Development of a machine learning model for predicting renal damage in children with closed spinal dysraphism by Yu He, Wan-liang Guo, Ming-chang Zhang

“…The Shapley additive explanations (SHAP) algorithm and Local Interpretable Model-Agnostic Explanations (LIME) were used to interpret the optimal model. …”
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Parameterization of user functions in digital signal processing for obtaining angular superresolution by A. A. Shchukin, A. E. Pavlov

“…Objectives. One of the most important tasks in the development of goniometric systems is improving resolution in terms of angular coordinates. …”
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UAV-Based SAR-Imaging of Objects From Arbitrary Trajectories Using Weighted Backprojection by Alexander Grathwohl, Julian Kanz, Christina Bonfert, Christian Waldschmidt

“…Synthetic aperture radars (SARs) based on uncrewed aerial vehicles (UAVs) are advantageous in comparison to existing airborne systems. Apart from cost, their main advantage is the flexibility of their flight path. …”
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InvMOE: MOEs Based Invariant Representation Learning for Fault Detection in Converter Stations by Hao Sun, Shaosen Li, Hao Li, Jianxiang Huang, Zhuqiao Qiao, Jialei Wang, Xincui Tian

“…To overcome these issues, we propose InvMOE, a novel fault detection algorithm with two core components: (1) invariant representation learning, which captures task-relevant features and mitigates background noise interference, and (2) multi-task training using a mixture of experts (MOE) framework to adaptively optimize feature learning across tasks and address label sparsity. …”
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Normalised Diagnostic Contribution Index (NDCI) Integration to Multi Objective Sensor Optimisation Framework (MOSOF)—An Environmental Control System Case by Burak Suslu, Fakhre Ali, Ian K. Jennions

“…Building on previous work, the proposed approach leverages a multi-objective genetic algorithm to optimise key criteria, including performance, cost, reliability management, and compatibility. …”
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Gap-filling of land surface temperature in arid regions by combining Landsat 8 and 9 imageries by Fahime Arabi Aliabad, Ebrahim Ghaderpour, Ahmad Mazidi, Fatemeh Houshmandzade

“…The aims of this research are to determine the optimal parameters for the reconstruction of Landsat-LST images, required in many applications, by the harmonic analysis of time series algorithm (HANTS) and to investigate the possibility of improving LST reconstruction accuracy using Landsat 8 and 9 images simultaneously. …”
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The evaluation model of engineering practice teaching with complex network analytic hierarchy process based on deep learning by Xianlong Han, Xiaohui Chen

“…Abstract This study aims to effectively improve the quality evaluation system of engineering practice teaching in colleges and universities and enhance the efficiency of teaching management. …”
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Exploring Machine Learning Classification of Movement Phases in Hemiparetic Stroke Patients: A Controlled EEG-tDCS Study by Rishishankar E. Suresh, M S Zobaer, Matthew J. Triano, Brian F. Saway, Parneet Grewal, Nathan C. Rowland

“…Linear discriminant analysis was the most accurate (74.6%) algorithm with the shortest training time (0.9 s). …”
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Weighted Hybrid Random Forest Model for Significant Feature prediction in Alzheimer’s Disease Stages by M. Rohini, D. Surendran

“…Thus, the proposed Weighted Hybrid Random Forest algorithm (WHBM) utilized the 63 features that comprise the whole brain volume. …”
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