Comparison of machine learning models for coronavirus prediction by B. K. Amos, I. V. Smirnov, M. M. Hermann

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Comparison of 7 artificial intelligence models in predicting venous thromboembolism in COVID-19 patients by Indika Rajakaruna, Mohammad Hossein Amirhosseini, Mike Makris, Mike Laffan, Yang Li, Deepa J. Arachchillage

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Distribution of age at natural menopause, age at menarche, menstrual cycle length, height and BMI in BRCA1 and BRCA2 pathogenic variant carriers and non-carriers: results from EMBR... by Nasim Mavaddat, Debra Frost, Emily Zhao, Daniel R. Barnes, Munaza Ahmed, Julian Barwell, Angela F. Brady, Paul Brennan, Hector Conti, Jackie Cook, Harriet Copeland, Rosemarie Davidson, Alan Donaldson, Emma Douglas, David Gallagher, Rachel Hart, Louise Izatt, Zoe Kemp, Fiona Lalloo, Zosia Miedzybrodzka, Patrick J. Morrison, Jennie E. Murray, Alex Murray, Hannah Musgrave, Claire Searle, Lucy Side, Katie Snape, Vishakha Tripathi, Lisa Walker, Stephanie Archer, D. Gareth Evans, Marc Tischkowitz, Antonis C. Antoniou, Douglas F. Easton

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Interpersonal counselling for adolescent depression delivered by youth mental health workers without core professional training: the ICALM feasibility RCT by Jon Wilson, Viktoria Cestaro, Eirini Charami-Roupa, Timothy Clarke, Aoife Dunne, Brioney Gee, Sharon Jarrett, Thando Katangwe-Chigamba, Andrew Laphan, Susie McIvor, Richard Meiser-Stedman, Jamie Murdoch, Thomas Rhodes, Carys Seeley, Lee Shepstone, David Turner, Paul Wilkinson

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The coverage method of unmanned aerial vehicle mounted base station sensor network based on relative distance by Taifei Zhao, Hua Wang, Qianwen Ma

“…The simulation results show that the coverage of the proposed algorithm is 22.4% higher than that of random deployment, and it is 9.9%, 4.7% and 2.1% higher than similar virtual force-oriented node, circular binary segmentation and hybrid local virtual force algorithms.…”
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Rapid and accurate multi-phenotype imputation for millions of individuals by Lin-Lin Gu, Hong-Shan Wu, Tian-Yi Liu, Yong-Jie Zhang, Jing-Cheng He, Xiao-Lei Liu, Zhi-Yong Wang, Guo-Bo Chen, Dan Jiang, Ming Fang

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Characteristics and Rapid Prediction of Seismic Subsidence of Saturated Seabed Foundation with Interbedded Soft Clay–Sand by Liuyuan Zhao, Miaojun Sun, Jianhong Ye, Fuqin Yang, Kunpeng He

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Importance Analysis of Causative Nodes for Accident Chains of Railway Locomotive Operation Based on STPA-PageRank Method by Ping WAN, Wei-Lun YANG, Jie-Wen LUO, Xiao-Feng MA

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Improved mapping of highland bamboo forests using Sentinel-2 time series and machine learning in Google Earth Engine by Dagnew Yebeyen, Binyam Tesfaw Hailu, Worku Zewdie, Temesgen Abera, Gudeta W. Sileshi, Melaku Getachew, Sileshi Nemomissa

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Post-hoc Evaluation of Sample Size in a Regional Digital Soil Mapping Project by Daniel D. Saurette, Richard J. Heck, Adam W. Gillespie, Aaron A. Berg, Asim Biswas

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Wetland Gain and Loss in the Mississippi River Bird‐Foot Delta by Jiangjie Yang, Zhijun Dai, Xuefei Mei, Yaying Lou, Sergio Fagherazzi

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Enhancing Software Defect Prediction Using Ensemble Techniques and Diverse Machine Learning Paradigms by Ayesha Siddika, Momotaz Begum, Fahmid Al Farid, Jia Uddin, Hezerul Abdul Karim

“…The prediction of software defects is a crucial element in maintaining the stability and reliability of software systems. This research addresses this need by combining advanced techniques (ensemble techniques) with seventeen machine learning algorithms for predicting software defects, categorised into three types: semi-supervised, self-supervised, and supervised. …”
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RAPO: An Automated Performance Optimization Tool for Redis Clusters in Distributed Storage Metadata Management by Yunkai Zhu, Tian Xia, Te Zhu, Zhoujie Zhao, Kexin Li, Xingbo Hu

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Improving Attack Detection in IoV with Class Balancing and Feature Selection by Thierry Widyatama, Ifan Rizqa, Fauzi Adi Rafrastara

“…The ensemble algorithms evaluated in this research comprise Random Forest, Gradient Boosting, and XGBoost. …”
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Advancing malware imagery classification with explainable deep learning: A state-of-the-art approach using SHAP, LIME and Grad-CAM. by Sadia Nazim, Muhammad Mansoor Alam, Syed Safdar Rizvi, Jawahir Che Mustapha, Syed Shujaa Hussain, Mazliham Mohd Suud

“…The trust of users in the models used for cybersecurity would be undermined by the ambiguous and indefinable nature of existing AI-based methods, specifically in light of the more complicated and diverse nature of cyberattacks in modern times. The present research addresses the comparative analysis of an ensemble deep neural network (DNNW) with different ensemble techniques like RUSBoost, Random Forest, Subspace, AdaBoost, and BagTree for the best prediction against imagery malware data. …”
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Integrating Handcrafted Features with Machine Learning for Hate Speech Detection in Albanian Social Media by Fetahi Endrit, Hamiti Mentor, Susuri Arsim, Zenuni Xhemal, Ajdari Jaumin

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AN INTELLIGENT POSTOPERATIVE CHRONIC PAIN PREDICTION SYSTEM (I-POCPP) by Elif Kartal, Fatma Önay Koçoğlu, Zeki Özen, İlkim Ecem Emre, Gürcan Güngör, Pervin Sutaş Bozkurt

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Wavelet-Based ensembled intelligent technique for a better quality of fault detection and classification in AC microgrids by Nityananda Giri, Pravati Nayak, Ranjan Kumar Mallick, Sairam Mishra, Aymen Flah, Habib Kraiem, Lukas Prokop, Mohammad Kanan

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Modeling Flood Susceptibility Utilizing Advanced Ensemble Machine Learning Techniques in the Marand Plain by Ali Asghar Rostami, Mohammad Taghi Sattari, Halit Apaydin, Adam Milewski

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Combined L-Band Polarimetric SAR and GPR Data to Develop Models for Leak Detection in the Water Pipeline Networks by Yuyao Zhang, Hongliang Guan, Fuzhou Duan

“…The model features are selected with the Boruta wrapper algorithm based on the SAOCOM-1A images after pre-processing, and the SSRDC values at sampling locations within the research area are calculated with the reflected wave method based on the GPR data. …”
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