Combining machine learning and single-cell sequencing to identify key immune genes in sepsis by Hao Wang, Linghan Len, Li Hu, Yingchun Hu

“…Next, a Biological association network was constructed, and five key hub genes (CD4, HLA-DOB, HLA-DRB1, HLA-DRA, AHNAK) were identified using a combination of three topological analysis algorithms (MCC, Closeness, and MNC) and four machine learning algorithms (Random Forest, LASSO regression, SVM, and XGBoost). immune cell distribution showed that the key genes correlated with multiple immune cell infiltrations. …”
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THE DIAGNOSIS TECHNIQUE OF ABNORMAL HEATING OF POWER CAPACITORS by D. I. Zalizny

“…The algorithms have been developed heuristically. The final formation of the algorithms is possible only after the long-term operation of the proposed diagnosis system on real objects. …”
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Assessment of Machine Learning Methods for Concrete Compressive Strength Prediction by Oluwafemi Omotayo, Chinwuba Arum, Catherine Ikumapayi

“…The study considered a wide range of literature data and examined the efficiency of boosted algorithms in predicting the strength of ordinary Portland cement concrete. …”
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Hybrid quantum neural networks show strongly reduced need for free parameters in entity matching by Lukas Bischof, Stefan Teodoropol, Rudolf M. Füchslin, Kurt Stockinger

“…In this paper, we evaluate quantum machine learning algorithms for entity matching on a hand-crafted data set and compare them to similar classical algorithms. …”
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Assessing the potential of a Bayesian ranking as an alternative to consensus meetings for decision making in research funding: A case study of Marie Skłodowska-Curie actions. by Rachel Heyard, David G Pina, Ivan Buljan, Ana Marušić

“…The best agreement between the final funding ranking can be observed in the case of funding schemes with very low success rates. While we set out to understand if algorithmic approaches, with the aim of summarising individual evaluation scores, could replace consensus meetings, we concluded that currently individual scores assigned prior to the consensus meetings are not useful to predict the final funding outcomes of the proposals. …”
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Two Methods for Superposing the Structures of Like-Molecule Assemblies: Application to Peptide and Protein Oligomers and Aggregates by Adam Liwo, Mateusz Leśniewski

“…Two algorithms are proposed for the superposition of assemblies of like molecules (e.g., peptide and proteins homooligomers and homoaggregates), which do not require examining all permutations of the molecules. …”
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Applications of Machine Learning in Human Factors and Ergonomics: A Comprehensive Review of Research From the Past Decade by Erman Cakit, Waldemar Karwowski

“…For instance, ANN models for Electroencephalography (EEG)-based MWLA achieved up to 94% accuracy, while SVM classifiers reached up to 97.94% in posture classification. …”
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A Strategy-Driven Semantic Framework for Precision Decision Support in Targeted Medical Fields by Sivan Albagli-Kim, Dizza Beimel

“…Strategies integrate domain-specific knowledge and algorithms, refining decision making while maintaining the iterative nature of expert–patient interactions. …”
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Enhanced‐Resolution Learning‐Based Direction of Arrival Estimation by Programmable Metasurface by Nawel Meftah, Badreddine Ratni, Mohammed Nabil El Korso, Shah Nawaz Burokur

“…Abstract Due to its growing importance and wide range of applications, direction‐of‐arrival (DOA) estimation has become a major research topic, particularly in the field of communication systems. While traditional DOA estimation methods rely on antenna arrays and complex algorithms, recent progress achieved in the design and implementation of metasurfaces has proved their effectiveness as promising alternatives. …”
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An elliptically symmetric fisher distribution and its application in statistics of discontinuities in rock mass by Shuang Wang, Jun Sun, Yi Cheng, Fumin Shu, Cunjia Qiu

“…Serving as a general form of the Fisher distribution, the model retains the simplicity, interpretability, and ease of calculation of the Fisher distribution while expanding its applicability. Parameter estimation and data simulation algorithms for the model are presented, demonstrating its efficiency and versatility. …”
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A fault diagnosis method for rolling bearing based on gram matrix and multiscale convolutional neural network by Xinyan Zhang, Shaobin Cai, Wanchen Cai, Yuchang Mo, Liansuo Wei

“…In the last few years, there have been significant advances in the algorithms for intelligent fault diagnosis of bearings. …”
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Simplified LSL-Net Architecture for Unmanned Aerial Vehicle Detection in Real-Time by Francisco David Camacho-Gonzalez, Nestor Andres Garcia-Rojas, José Francisco Martínez-Trinidad, Jesús Ariel Carrasco-Ochoa

“…The literature has addressed this problem by applying traditional computer vision algorithms and, more recently, deep learning architectures, which, while proven more effective than previous ones, are computationally more expensive. …”
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Performance Analysis of a Semiactive Suspension System with Particle Swarm Optimization and Fuzzy Logic Control by Abroon Jamal Qazi, Clarence W. de Silva, Afzal Khan, Muhammad Tahir Khan

“…Particle swarm optimization (PSO) is applied to determine the optimal gain parameters for the fuzzy logic controller, while maintaining within the normalized ranges of the controller inputs and output. …”
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New Design of Smooth PSO-IPF Navigator With Kinematic Constraints by Mahsa Mohaghegh, Hedieh Jafarpourdavatgar, Samaneh-Alsadat Saeedinia

“…In addition, while PSO efficiently explores solution spaces, it generates long paths and has limited global search. …”
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The classification method of donkey breeds based on SNPs data and machine learning by Dekui Li, Dekui Li, Xiaolong Hu, Yongdong Peng

“…For instance, chromosome Chr2 showed the highest classification accuracy with KNN, while chromosome Chr19 performed best with SVM and RF models. …”
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Artificial intelligence in soil science: Where do we go now? by Jose Pablo Castro, Caley K. Gasch, Paulo Flores

“…Abstract Recognizing the fast advancement of artificial intelligence (AI) in soil science, the main objective of this commentary paper is to discuss how this technology is being incorporated into the discipline, focusing on the most common algorithms and their applications. Employing a discursive and reflective methodology, the article draws insights from the authors' expertise and opinions. …”
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Facial Skin Analysis in Malaysians using YOLOv5: A Deep Learning Perspective by Ying Huey Gan, Shih Yin Ooi, Ying Han Pang, Yi Hong Tay, Quan Fong Yeo

“…The beauty sector market is increasing, and more skin type readers are being created to help people determine their skin type. While various skin type readers are in the market, each is invented and tested abroad. …”
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A Review of Non-Fully Supervised Deep Learning for Medical Image Segmentation by Xinyue Zhang, Jianfeng Wang, Jinqiao Wei, Xinyu Yuan, Ming Wu

“…We delve into the theoretical foundations, core advantages, typical application scenarios, and representative algorithmic implementations associated with each paradigm. …”
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E-scooter crash severity in the United Kingdom: A comparative analysis using machine learning techniques and random parameters logit with heterogeneity in means and variances by Ali Agheli, Kayvan Aghabayk, Matin Sadeghi, Subasish Das

“…We employed a random parameters logit model and investigated several machine learning algorithms, with XGBoost performing best. Analysis reveals that severe injuries are more likely in crashes involving senior riders, at night with lighting, and at T, staggered, or crossroad junctions. …”
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Impact of Public Space in Primary and Secondary Schools Based on Natural Visibility Ratio by Feng Liu, Hao Zhou, Jiangtao Xie, Yue Tang, Shuyu Liu

“…This study utilizes algorithmic simulations, spatial analysis, and statistical methods to examine the relationships between the layouts of buildings, public space morphology, and campus safety. …”
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