Energy harvesting enhancement: A roadmap for systematically tuning controllers applied on synchronous generators of wind turbines by John Breno Santos Freitas, Felipe Augusto Silva Martins, Vinicius Foletto Montagner, Paulo Jefferson Dias de Oliveira Evald

“…Compared to the tenth algorithm in the rank, the ALO-based controller ensured a reduction of 96.78% and 90.27% of mean absolute error and root mean squared error, respectively. …”
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Optimization of the Backstepping Control Parameters of an Active Electrohydraulic Suspension to Improve Passenger Comfort and Road Handling by Rachid Fattah, Jean-Pierre Kenne, Khalid Benjelloun, Ahmed Chebak

“…Additionally, a comparison with Genetic Algorithm (GA)-based optimization highlights that PSO achieves superior convergence and performance. …”
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Forecasting Insurance Company Commitments with Long Short-Term Memory Models by Negar Tehraniyazdi, Reza Vaezi, Saeed Setayeshi, Iman Raeesi Vanani

“…A Long Short-Term Memory (LSTM) neural network algorithm is employed, recognized for its strong predictive capability in time series data. …”
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Bio-Inspired Compliant Joints and Economic MPC Co-Design for Energy-Efficient, High-Speed Locomotion in Snake-like Robots by Shuai Zhou, Gengbiao Chen, Mingyu Gong, Jing Liu, Peng Xu, Binshuo Liu, Nian Yin

“…The proposed predictive control strategy optimizes locomotion speed while minimizing energy consumption. …”
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Validation of Replicable Pipeline 3D Surface Reconstruction for Patient-Specific Abdominal Aortic Lumen Diagnostics by Edoardo Ugolini, Giorgio La Civita, Moad Al Aidroos, Samuele Salti, Giuseppe Lisanti, Emanuele Ghedini, Gianluca Faggioli, Mauro Gargiulo, Giovanni Rossi

“…<b>Conclusions:</b> The proposed algorithm can correctly reconstruct pathological vessels. …”
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Estimating genomic relationships of metafounders across and within breeds using maximum likelihood, pseudo-expectation–maximization maximum likelihood and increase of relationships... by Andres Legarra, Matias Bermann, Quanshun Mei, Ole F. Christensen

“…Approximating the first derivative by its first term results in a pseudo-EM algorithm that iteratively updates the estimate of $${\varvec{\Gamma}}$$ Γ by the corresponding block of the H-matrix. …”
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Conjecture Interaction Optimization Model for Intelligent Transportation Systems in Smart Cities Using Reciprocated Multi-Instance Learning for Road Traffic Management by Abdullah Faiz Al Asmari, Ahmed Almutairi, Fayez Alanazi, Tariq Alqubaysi, Ammar Armghan

“…The MIL algorithm integrates multi-instance learning into the interaction labelling process, enhancing the routing prediction by differentiating between reliable and erroneous data. …”
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SERLogic: A Logic-Integrated Framework for Enhancing Sequential Recommendations by Lihang Fan

“…Sequential recommendation models are used to predict users&#x2019; next top-K preferred items based on their historical interactions. …”
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Integrated single-cell and transcriptome sequencing to construct a prognostic model of M2 macrophage-related genes in prostate cancer by TANG Kairan, FENG Chengling, HAN Bangmin

“…The immune infiltration of TCGA samples was assessed using the CIBERSORTx algorithm. Differential genes in scRNA-seq data were identified using the FindMarkers function, and immune cell subtypes were characterized. …”
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Energy and exergy analysis of a modified air handling unit assisted by phase change material, heat recovery unit, and solar energy by Saman Faramarzi, Seyed Mohammad Mehdi Asadzadeh, Mohammad Reza Mohammad Hassani, Seyyed Amirreza Abdollahi, Reza Zarehzadeh, Mostafa Mafi

“…Through detailed energy and exergy analyses, the study evaluates the AHU’s performance and optimises the thickness and position of the PCM layer using genetic algorithm (GA) optimisation. Simulation of the proposed system was conducted using ASPEN Hysys and MATLAB software. …”
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Sleep Snoring Sound Recognition Based on Wavelet Packet Transform by Li Ding, Jianxin Peng, Xiaowen Zhang, Lijuan Song

“…An automatic snoring detection system based on the wavelet packet transform (WPT) with an eXtreme Gradient Boosting (XGBoost) classifier is proposed in the paper, which recognizes snoring sounds from the enhanced episodes by the generalization subspace noise reduction algorithm. The feature selection technology based on correlation analysis is applied to select the most discriminative WPT features. …”
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The Quest for the Best Explanation: Comparing Models and XAI Methods in Air Quality Modeling Tasks by Thomas Tasioulis, Evangelos Bagkis, Theodosios Kassandros, Kostas Karatzas

“…Moreover, the evaluation showed that models retained a substantial degree of predictive power (R² > 0.93) even in a reduced complexity size. …”
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Assessing the Risk of Natural and Socioeconomic Hazards Caused by Rainfall in the Middle Yellow River Basin by Yufeng Zhao, Shun Xiao, Xinshuang Wu, Shuitao Guo, Yingying Yao

“…In this study, we propose a comprehensive quantification framework and apply it to the Loess Plateau of northern China based on 40 years of climate data, streamflow measurements, and multiple spatial and geographical attribute datasets. A deep learning algorithm of long short-term memory (LSTM) was used to predict runoff, and the analytic hierarchy index was utilized to evaluate the comprehensive spatial risk considering natural and socioeconomic factors. …”
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Separating the albedo-reducing effect of different light-absorbing particles on snow using deep learning by L.-A. Chevrollier, A. Wehrlé, J. M. Cook, N. Pirk, L. G. Benning, A. M. Anesio, M. Tranter

“…Among these 180 surfaces, the albedo reduction due to light-absorbing particles was highly variable and reached up to 0.13, 0.21, and 0.25 for red algal blooms, mineral dust, and dark particles respectively. …”
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Structural Damping with Friction Beams by L. Gaul, J. Roseira, J. Becker

“…Numerical predictions and measurements of the double beam free vibration response are compared. …”
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Research review on improving the efficiency of multimodal transportation based on technological solutions by M. I. Malyshev

“…Based on the theory of controlled networks and integer linear programming methods, the experts developed mathematical models for the distribution of cargo flows, the choice of the most favorable transportation routes, ideal loading of rolling stock, and transportation of goods using the best forwarding algorithm. Methods are proposed for assessing the maximum capacity of the transport network and predicting the interference of weather conditions in the process of goods transportation, based on the Ford-Fulkerson theorem on the maximum flow and minimum cross section and the use of the mathematical apparatus of Markov chains. …”
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Machine learning-assisted quantitative metabolomics of West African patients with advanced breast cancer by Aboubacar Dit Tietie Bissan, Mathieu Michel, Xavier Dieu, Cinzia Bocca, Awo Emmanuela Hilda Amegonou, Fatoumata Matokoma Sidibe, Madani Ly, Bocary Sidi Koné, Nènè Oumou Kesso Barry, Kletigui Casimir Dembélé, Bakary Cissé, Bourèma Kouriba, Gilles Simard, Delphine Mirebeau-Prunier, Juan Manuel Chao de la Barca, Zahra Ouzzif, Pascal Reynier

“…The data were compared with those of 79 healthy controls using a combination of several machine learning approaches and statistical analyses. The predictive models obtained with the machine learning algorithms were comparable, with the best AUC of 0.878 obtained with ridge logistic regression using Boruta feature selection. …”
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Deep reinforcement learning agents for dynamic spectrum access in television whitespace cognitive radio networks by Udeme C. Ukpong, Olabode Idowu-Bismark, Emmanuel Adetiba, Jules R. Kala, Emmanuel Owolabi, Oluwadamilola Oshin, Abdultaofeek Abayomi, Oluwatobi E. Dare

“…Reinforcement Learning (RL) in CRs helps predict spectral changes and identify optimal transmission frequencies. …”
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A Tile with Nested Chain Abacus by Eman F. Mohammed

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Efficient and conservative estimation reliability analysis of strip footing on spatially variable c - ϕ soil using random finite element limit analysis by Szabowicz Hubert, Kawa Marek, Puła Wojciech

“…Additional use of adaptive meshing refinement algorithm leads to a significant reduction of the relative difference between statistical moments of obtained lower and upper bound results. …”
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