High-Performance Thin PTFE-Ni Metamaterial Absorber for Ultra-Broadband Applications by Camilla C. Moro Carmo, Ursula C. Resende, Silvia C. Albuquerque, Mauricio D. Almeida

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Small Defects Detection of Galvanized Strip Steel via Schatten-<i>p</i> Norm-Based Low-Rank Tensor Decomposition by Shiyang Zhou, Xuguo Yan, Huaiguang Liu, Caiyun Gong

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Optimization and analysis of interior permanent magnet drive motor with unequal thickness magnetic poles for electric vehicle by Shilun MA, Yongyi WU, Changwei LI, Keqi CHEN

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Variable Speed Limit Strategies Based on the Macro Hierarchical Control Traffic Flow Model by Shubin Li, Tao Wang, Hualing Ren, Baiying Shi, Xiangke Kong, Jianyong Chai, Xuejuan Wang

“…A solution algorithm is further developed to find the optimal parameters of VSL by minimizing the total travel time and delay. …”
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Classification of Precipitation Types and Investigation of Their Physical Characteristics Using Three-Dimensional S-Band Dual-Polarization Radar Data by Choeng-Lyong Lee, Wonbae Bang, Chia-Lun Tsai, GyuWon Lee

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Application of Image Processing Technology in Aerobics Injury Diagnosis by Duo Zhang, Yan Tian

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Machine learning applied to the design and optimization of polymeric materials: A review by Sudarsan M. Pai, Karim A. Shah, Sruthi Sunder, Rodrigo Q. Albuquerque, Christian Brütting, Holger Ruckdäschel

“…Machine learning (ML) offers a promising solution to this issue. By leveraging ML algorithms, researchers can accelerate the design process, predict material properties more rapidly, and optimize formulations. …”
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An implementation of smoothed particle hydrodynamic methods for fluids problems by Nguyen Hoai Son, Nguyen Duy Hung

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Evaluating the level of digitalization of the innovation process with artificial intelligence approach in the digital transformation of knowledge-based companies by ali Bagheri, reza radfar, sepehr ghazinoory

“…As a subset of artificial intelligence, machine learning algorithms create a mathematical model based on sample data or "training data" in order to predict or make decisions without overt planning (Du et al., 2019). …”
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Comprehensive Fault Diagnosis of Three-Phase Induction Motors Using Synchronized Multi-Sensor Data Collection by Kevin Thomas, Ahasanur Rahman, Wesam Rohouma, Md. Faysal Ahamed, Fariya Bintay Shafi, Md. Nahiduzzaman, Amith Khandakar

“…The dataset, organized into ten distinct CSV files covering various operational states, provides a rich resource for developing and testing fault detection algorithms. A Random Forest classifier trained on this dataset achieved an accuracy of 99.82%, demonstrating its suitability for real-time fault diagnosis and predictive maintenance applications. …”
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Microgrid Resilience Enhancement with Sensor Network-Based Monitoring and Risk Assessment Involving Uncertain Data by Tangxiao Yuan, Kossigan Roland Assilevi, Kondo Hloindo Adjallah, Ayité Sénah A. Ajavon, Huifen Wang

“…Both decision processes skillfully utilize Monte Carlo simulation and multi-objective genetic algorithms to effectively manage the uncertainty risks in the decision-making process, thereby significantly enhancing the overall resilience of the microgrid.…”
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Statistical assessment of interrelationship of marriage and divorces to fertility by A. B. Sinelnikov, O. A. Zolotareva, M. D. Khabib

“…A number of indicators complement the traditional methodology of marriage and divorce tables calculation. The algorithms for obtaining the indicators proposed for implementation (in particular, the cumulative marriage rate of divorcees, the level of divorces compensation by legal remarriages, etc.) have been prescribed, and their estimations have been made, which substantiates the scientific significance of the study. …”
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The Gut Microbiota and Colorectal Cancer: Understanding the Link and Exploring Therapeutic Interventions by Imen Zalila-Kolsi, Dhoha Dhieb, Hussam A. Osman, Hadjer Mekideche

“…The study of intratumoral microbiota offers new diagnostic and prognostic tools that, combined with artificial intelligence algorithms, could predict treatment responses and assess the risk of adverse effects. …”
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A Novel Mutation of the CYP11B2 in a Saudi Infant with Primary Hypoaldosteronism by Lama Alfaraidi, Abrar Alfaifi, Rawan Alquaiz, Faten Almijmaj, Horia Mawlawi

“…Given the position of the transition at a highly conserved nucleotide and the predictions of different bioinformatic algorithms, it is likely that the mutation is the pathogenic cause of this condition. …”
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Advancing nearshore and onshore tsunami hazard approximation with machine learning surrogates by N. Ragu Ramalingam, K. Johnson, M. Pagani, M. Pagani, M. L. V. Martina

“…The ML model serves as a surrogate, predicting the tsunami waveform on the coast and the maximum inundation depths onshore at the different test sites. …”
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Research on the WSN Node Localization Based on TOA by Qing-hui Wang, Ting-ting Lu, Meng-long Liu, Li-feng Wei

“…Simulation results show that the proposed algorithm renders satisfactory performance in terms of average delay reduction from end to end, packet loss rate, and routing overhead. …”
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Performance Optimization of a Formula Student Racing Car Using the IPG CarMaker, Part 1: Lap Time Convergence and Sensitivity Analysis by Dominik Takács, Ambrus Zelei

“…The IPG CarMaker uses a multibody vehicle model and a learning algorithm for the virtual driver. The goal is to discover the behavior of the learning algorithm from the point of view of reliability and convergence. …”
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Method of unknown protocol classification based on autoencoder by Chunxiang GU, Weisen WU, Ya’nan SHI, Guangsong LI

“…Aiming at the problem that a large number of unknown protocols exist in the Internet,which makes it very difficult to manage and maintain the network security,a classification and identification method of unknown protocols was proposed.Combined with the autoencoder technology and the improved K-means clustering technology,the unknown protocol was classified and identified for the network traffic.The autoencoder was used to reduce dimensionality and select features of network traffic,clustering technology was used to classify the dimensionality reduction data unsupervised,and finally unsupervised recognition and classification of network traffic were realized.Experimental results show that the classification effect is better than the traditional K-means,DBSCAN,GMM algorithm,and has higher efficiency.…”
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Raman Spectra Classification of Pharmaceutical Compounds: A Benchmark of Machine Learning Models with SHAP-Based Explainability by Dimitris Kalatzis, Alkmini Nega, Yiannis Kiouvrekis

“…In addition to strong predictive performance, SHAP (SHapley Additive exPlanations) analysis was employed to interpret model decisions. …”
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Analysis of space solar array arc images based on deep learning techniques by Afaf M. Abd El-Hameed, Ahmed S. Farahat, Khaled Y. Youssef, M. Elfarran, I. M. Selim

“…Furthermore, algorithms and image processing tools, such as Python and Maxim-DL, are employed to examine variations in intensities and spatial variation in the arced region. …”
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