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    Proposing a framework for body mass prediction with point clouds: A study applied in typical swine pen environments by Gabriel Pagin, Luciane Silva Martello, Rubens André Tabile, Rafael Vieira de Sousa

    Published 2025-12-01
    “…Challenges persist in implementing these techniques in pens with a large number of animals, especially in extracting physical body characteristics from images in a production environment. In this context, the main objective of this research is to investigate a novel framework comprising effective algorithms for feature extraction, attribute selection, hyperparameter optimization, and prediction modelling, using point clouds collected from production animals (growing and finishing pigs). …”
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    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Saad Ahmed Dheyab, Shaymaa Mohammed Abdulameer, Salama Mostafa

    Published 2022-12-01
    “…Subsequently, DDoS attack detection is performed based on random forest (RF) and decision tree (DT) algorithms. …”
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    Research on Ship Heave Motion Compensation Control Under Complex Sea State Environment Based on Improved Reinforcement Learning by ZHANG Qin, ZHOU Jingyi, WANG Xingyue, HU Xiong

    Published 2025-07-01
    “…In these diversified test scenarios, the improved TD3 algorithm exhibits remarkable adaptability and stability. …”
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    On precise path planning algorithm in wireless sensor network by Farhanda Javed, Samiullah Khan, Asfandyar Khan, Alweena Javed, Rohi Tariq, Matiullah, Faheem Khan

    Published 2018-07-01
    “…Simulation scenarios with three node densities are used in this research study such as sparse node density, medium node density, and dense node density. …”
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    Hybrid Weighted Random Forests Method for Prediction & Classification of Online Buying Customers by Umesh Kumar Lilhore, Sarita Simaiya, Devendra Prasad, Deepak Kumar Verma

    Published 2021-04-01
    “…This research article mainly proposed an extension of the Random Forest classifier named “Weighted Random Forests” (wRF), which incorporates tree-level weights to provide much more accurate trees throughout the calculation as well as an assessment of vector relevance. …”
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    Positioning Guselkumab in The Treatment Algorithm of Patients with Crohn’s Disease by D'Amico F, Bencardino S, Magro F, Dignass A, Gutiérrez Casbas A, Verstockt B, Hart A, Armuzzi A, Peyrin-Biroulet L, Danese S

    Published 2025-05-01
    “…Ferdinando D’Amico,1,* Sarah Bencardino,1,* Fernando Magro,2 Axel Dignass,3 Ana Gutiérrez Casbas,4 Bram Verstockt,5 Ailsa Hart,6 Alessandro Armuzzi,7,8 Laurent Peyrin-Biroulet,9 Silvio Danese1 1Gastroenterology and Endoscopy, IRCCS Ospedale San Raffaele and Vita-Salute San Raffaele University, Milan, Italy; 2CINTESIS@RISE, Faculty of Medicine of the University of Porto, Porto, Portugal; 3Department of Medicine I, Agaplesion Markus Hospital, Goethe University, Frankfurt/Main, Germany; 4Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Madrid, España; Hospital General Universitario de Alicante, Instituto de Investigación Sanitaria y Biomédica de Alicante (ISABIAL), Alicante, España; 5Department of Gastroenterology and Hepatology, University Hospitals Leuven, Leuven, KU, Belgium; 6Inflammatory Bowel Disease Unit, St Mark’s Hospital, LNWUH NHS Trust, Harrow, UK; 7IBD Unit, IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy; 8Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy; 9Department of Gastroenterology, INFINY Institute, INSERM NGERE, CHRU Nancy, Vandœuvre-lès-Nancy, F-54500, France*These authors contributed equally to this workCorrespondence: Silvio Danese, Gastroenterology and Endoscopy, IRCCS Ospedale San Raffaele and Vita-Salute San Raffaele University, Tel +390226432069, Fax +390282242591, Email sdanese@hotmail.comAbstract: Guselkumab, a selective interleukin-23 (IL-23) inhibitor, has emerged as a promising biologic therapy for the management of patients with moderate-to-severe Crohn’s disease (CD) and has been recently approved for its treatment. …”
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    ANALISIS JENIS BUDIDAYA TEBU MENGGUNAKAN ALGORITMA RANDOM FOREST (STUDI KASUS KECAMATAN TAJINAN, KABUPATEN MALANG) by Muhammad Nurhadi, Prima Widayani, Sandy Budi Wibowo

    Published 2025-07-01
    “…To address this issue, this research utilized the Random Forest (RF) algorithm on PlanetScope satellite imagery to classify the types of sugarcane cultivation, i.e. early planted sugarcane and pressed sugarcane. …”
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