Application of Machine Learning for Radiowave Propagation Modeling Below 6 GHz by Mohammud Z. Bocus, Afzal Lodhi

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An interpretable and transparent machine learning framework for appendicitis detection in pediatric patients by Krishnaraj Chadaga, Varada Khanna, Srikanth Prabhu, Niranjana Sampathila, Rajagopala Chadaga, Shashikiran Umakanth, Devadas Bhat, K. S. Swathi, Radhika Kamath

“…In recent times, Artificial Intelligence and machine learning have been a boon for medicine. Hence, several supervised learning techniques have been utilized in this research to diagnose appendicitis in pediatric patients. …”
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Fruit size prediction of tomato cultivars using machine learning algorithms by Masaaki Takahashi, Yasushi Kawasaki, Hiroki Naito, Hiroki Naito, Unseok Lee, Koichi Yoshi

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Machine Learning Algorithm for Estimating Surface PM2.5 in Thailand by Pawan Gupta, Shanshan Zhan, Vikalp Mishra, Aekkapol Aekakkararungroj, Amanda Markert, Sarawut Paibong, Farrukh Chishtie

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Predicted Mean Vote of Subway Car Environment Based on Machine Learning by Kangkang Huang, Shihua Lu, Xinjun Li, Ke Feng, Weiwei Chen, Yi Xia

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IDMPF: intelligent diabetes mellitus prediction framework using machine learning by Leila Ismail, Huned Materwala

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Machine learning-assisted development of polypyrrole-grafted yarns for e-textiles by Matteo Iannacchero, Joakim Löfgren, Mithila Mohan, Patrick Rinke, Jaana Vapaavuori

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Research and Application of Heart Disease Prediction Model Based on Machine Learning by Bao Yongli

“…This study aims to improve the accuracy and efficiency of heart disease prediction through Machine learning (ML) methods to help medical diagnosis. …”
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Advances in machine learning applications to resource technology for organic solid waste by Hongzhi MA, Yichan LIU, Jihua ZHAO, Fan FEI, Ming GAO, Qunhui WANG

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Optimization of Depth Map Intra Coding Algorithms Based on Machine Learning by Wenjun Song, Jiaying Yang, Qiuwen Zhang

“…We focus specifically on the depth maps in 3D video content and introduce an extreme forest model from machine learning to optimize intra-frame coding. This paper proposes a novel CU partitioning strategy implemented through a two-stage extreme forest model. …”
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Holographic reconstruction of black hole spacetime: machine learning and entanglement entropy by Byoungjoon Ahn, Hyun-Sik Jeong, Keun-Young Kim, Kwan Yun

“…To validate our approach, we first apply our machine learning algorithm to holographic entanglement entropy data derived from the Gubser-Rocha and superconductor models, which serve as representative models of strongly coupled matters in holography. …”
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MARPUF: physical unclonable function with improved machine learning attack resistance by Somanath Tripathy, Vikash Kumar Rai, Jimson Mathew

“…Although PUF is very useful in the area of hardware security, it is vulnerable to machine learning modelling attacks (ML‐MA) by modelling the challenge‐response pairs (CRPs) behaviour. …”
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An Overview of Application of Machine Learning Models in Urban Flood Simulation and Forecasting by CHEN Zeming, FANG Xuhong, LI Jiaye, WANG Mengyao, CHEN Aifang, YIN Ling

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Integrating Machine Learning and Material Feeding Systems for Competitive Advantage in Manufacturing by Müge Sinem Çağlayan, Aslı Aksoy

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Persistent Homology Combined with Machine Learning for Social Network Activity Analysis by Zhijian Zhang, Yuqing Sun, Yayun Liu, Lin Jiang, Zhengmi Li

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An Overview of Application of Machine Learning Models in Urban Flood Simulation and Forecasting by CHEN Zeming, FANG Xuhong, LI Jiaye, WANG Mengyao, CHEN Aifang, YIN Ling

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MASC: Wearable Design for Infectious Disease Detection Through Machine Learning by Sumaiya Afroz Mila, Bhagawat Baanav Yedla Ravi, Md Rafiul Kabir, Sandip Ray

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Classification of ductile cast iron specimens: a machine learning approach by A. De Santis, D. Iacoviello, V. Di Cocco, F. Iacoviello

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On the use of adversarial validation for quantifying dissimilarity in geospatial machine learning prediction by Yanwen Wang, Mahdi Khodadadzadeh, Raúl Zurita-Milla

Subjects: “…Machine learning…”
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Quantum machine learning with Adaptive Boson Sampling via post-selection by Francesco Hoch, Eugenio Caruccio, Giovanni Rodari, Tommaso Francalanci, Alessia Suprano, Taira Giordani, Gonzalo Carvacho, Nicolò Spagnolo, Seid Koudia, Massimiliano Proietti, Carlo Liorni, Filippo Cerocchi, Riccardo Albiero, Niki Di Giano, Marco Gardina, Francesco Ceccarelli, Giacomo Corrielli, Ulysse Chabaud, Roberto Osellame, Massimiliano Dispenza, Fabio Sciarrino

“…Our experimental results demonstrate that Adaptive Boson Sampling is a viable route towards dimension-enhanced quantum machine learning with linear optical devices.…”
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