Network intrusion detection model using wrapper based feature selection and multi head attention transformers by Muhammad Umer, Muhammad Tahir, Muhammad Sardaraz, Muhammad Sharif, Hela Elmannai, Abeer D. Algarni

“…The model uses a wrapper-based feature selection technique using machine learning algorithms to select the best features, which are then combined and fed into a Multi-Head Attention-based transformer for getting the predictions. …”
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Honeybee Colony Growth Period Recognition Based on Multivariate Temperature Feature Extraction and Machine Learning by Chuanqi Lu, Lin Li, Denghua Li, Qiuying Huang, Wei Hong

“…The results demonstrate that the proposed features can effectively characterize the growth period of bee colonies, and the BP method performs best in predicting growth period categories, with an MAE of only 1.45%. …”
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Open-Loop Control System for High Precision Extrusion-Based Bioprinting Through Machine Learning Modeling by Javier Arduengo, Nicolas Hascoet, Francisco Chinesta, Jean-Yves Hascoet

“…Thus, the control system offers predictability and adaptability capabilities to ensure the consistent production of high-quality bioprinted structures. …”
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Dim and Small Target Detection Based on Improved Bilateral Filtering and Gaussian Motion Probability Estimation by Fan Xiangsuo, Qin Wenlin, Feng Gaoshan, Huang Qingnan, Min Lei

“…Six scenes and eleven comparison algorithms are selected for experiments, experimental results show the effectiveness and robustness of the proposed algorithm.…”
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Symmetry-Based Data Augmentation Method for Deep Learning-Based Structural Damage Identification by Long Li, Xiaoming Tao, Hui Song, Xiaolong Li, Zhilong Ye, Yao Jin, Qiuyu He, Shiyin Wei, Wenli Chen

“…Finally, a probabilistic generative model based on a deep belief network (DBN) is developed to predict damage locations and degrees. The proposed methods are validated using vibration data from a numerical three-span continuous bridge subjected to random vehicle excitations. …”
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Hypothesis: the generation of T cells directed against neoepitopes employing immune-mediating agents other than neoepitope vaccines by Renee N Donahue, Jeffrey Schlom, James L Gulley, James W Hodge, Claudia Palena, Duane H Hamilton, Sofia R Gameiro

“…As with all cancer therapy modalities, neoepitope vaccine development and delivery also has some drawbacks, including the level of effort to develop a patient-specific product, accuracy of algorithms to predict neoepitopes, and with the exception of melanoma and some other tumor types, biopsies of metastatic lesions of solid tumors are often not available. …”
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Improved Electrochemical–Mechanical Parameter Estimation Technique for Lithium-Ion Battery Models by Salvatore Scalzo, Davide Clerici, Francesca Pistorio, Aurelio Somà

“…Accurate and predictive models of lithium-ion batteries are essential for optimizing performance, extending lifespan, and ensuring safety. …”
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Design and Assessment of an Austenitic Stainless Alloy for Laser Powder Bed Additive Manufacturing by Mariam Assi, Julien Favre, Marcin Brykala, Franck Tancret, Anna Fraczkiewicz

“…This method integrates a suite of predictive tools, including machine learning, calculation of phase diagrams (CALPHAD) and physical models, all piloted by a multi-objective genetic algorithm. …”
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Advancing Agricultural Machinery Maintenance: Deep Learning-Enabled Motor Fault Diagnosis by Xusong Bai, Qian Chen, Xiangjin Song, Weihang Hong

“…These technologies offer reliable and efficient solutions for predictive maintenance in agricultural machinery, enabling proactive intervention in the early stages of catastrophic failures. …”
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Shape Penalized Decision Forests for Imbalanced Data Classification by Rahul Goswami, Aindrila Garai, Payel Sadhukhan, Palash Ghosh, Tanujit Chakraborty

“…The proposed approach enhances predictive performance and generalization by leveraging ensemble learning strategies such as bagging and adaptive boosting. …”
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Understanding students’ sentiment from feedback with a new feature selection and semantics networks by Tran Anh Tuan, Dao Thi Thanh Loan, Nichnan Kittiphattanabawon

“… Sentiment analysis of students’ feedback using machine learning algorithms has emerged as a valuable tool for understanding students’ sentiments and improving educational outcomes. …”
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Modelling and simulation of the block pouring construction system considering spatial–temporal conflict of construction machinery in arch dams by Zhipeng Liang, Jiayao Peng, Chunju Zhao, Huawei Zhou, Dongfeng Li, Yihong Zhou, Quan Liu, Xiaodong Li, Cheng Zhang, Fang Wang

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Cluster-based RSU deployment strategy for vehicular ad hoc networks with integration of communication, sensing and computing by Xinrui Gu, Shengfeng Wang, Zhiqing Wei, Zhiyong Feng

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An ensemble learning strategy for multi‐source hydrogen embrittlement data by introducing missing information by Xujie Gong, Ruichao Lei, Ruize Sun, Xue Jiang, Yanjing Su, Yu Yan

“…Abstract Accurately and quickly predicting hydrogen embrittlement performance is critical for the service of metal materials. …”
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Collaborative Forecasting of Multiple Energy Loads in Integrated Energy Systems Based on Feature Extraction and Deep Learning by Zhe Wang, Jiali Duan, Fengzhang Luo, Xiaoyu Qiu

“…However, directly applying single models to predict coupled cooling, heating, and electric loads under complex influencing factors often yields unsatisfactory results. …”
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MALDI-TOF mass spectrometry discriminates drug-susceptible and -resistant strains in Mycobacterium abscessus. by Tran Duong Thai, Nut Nithimongkolchai, Benjawan Kaewseekhao, Janejira Samarnjit, Chutipapa Sukkasem, Lumyai Wonglakorn, Auttawit Sirichoat, Arnone Nithichanon, Kiatichai Faksri

“…With the aid of machine learning, particularly the decision-tree algorithm, predictive models demonstrated excellent performance with 100% sensitivity and specificity. …”
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Application of Markov processes for analysis and control of aircraft maintainability by Yu. M. Chinyuchin, A. S. Solov'ev

“…The given approbation of the analysis methods and maintainability control using Markov processes for an object under control allowed to build a predictive-controlled model in which the expected costs for its maintenance and repair are calculated as well as the required number of spare parts for each specified operating time interval. …”
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Equivalence Between Optical Flow, the Unrest Index, and Walking Distance to Estimate the Welfare of Broiler Chickens by Danilo Florentino Pereira, Irenilza de Alencar Nääs, Saman Abdanan Mehdizadeh

“…This study supports the integration of Optical Flow and Unrest Index technologies into precision livestock systems, offering a foundation for predictive welfare management at scale.…”
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Artificial Intelligence in Medicine: Transforming The Future of Healthcare by Tashfeen Alam Jan, Shumaila Naz

“…AI showcased tremendous promise in a plethora of applications, such as the accurate analysis of medical imagery, the personalization of therapies through the tailor-made dosing of medicines, predictive analysis in forecasting the course of the disease, and the assistance of patients and clinicians by deploying virtual health tools. …”
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Addressing water scarcity challenges through rainwater harvesting: A comprehensive analysis of potential zones and model performance in arid and semi-arid regions–A case study on P... by Subhra Halder, Suddhasil Bose

“…Approximately 2% of the area is unsuitable, 8% is poorly suitable, 33% is moderately suitable, 45% is highly suitable, and the remaining 12% is extremely suitable in Purulia. Two predictive models were developed, with the RF algorithm demonstrating nearly 99% accuracy. …”
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