Completion of the Central Italy daily precipitation instrumental data series from 1951 to 2019 by Gamal AbdElNasser Allam Abouzied, Guoqiang Tang, Simon Michael Papalexiou, Martyn P. Clark, Eleonora Aruffo, Piero Di Carlo

“…Multi‐strategy merging strategy based on the Modified Kling‐Gupta efficiency (MS1) shows the highest performance as an individual precipitation gap‐filling strategy. However, the machine learning strategy using random forest (ML3) has the most outstanding share in the final estimates among all other strategies. …”
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Peningkatan Akurasi Klasifikasi Algoritma C 4.5 Menggunakan Teknik Bagging pada Diagnosis Penyakit Jantung by Erwin Prasetyo, Budi Prasetiyo

“…Data penyakit jantung diambil dari dataset UCI Machine Learning Repository. Tujuan dari penulis melakukan penelitian ini yaitu untuk mengetahui penerapan teknik bagging pada algoritma C4.5, mengetahui hasil akurasi dalam algoritma C4.5, dan membandingkan tingkat akurasi dari penerapan teknik bagging pada algoritma C4.5. …”
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The role of continuous monitoring in acute-care settings for predicting all-cause 30-day hospital readmission: A pilot study by Michael Joseph Pettinati, Kyriakos Vattis, Henry Mitchell, Nicole Alexis Rosario, David Michael Levine, Nandakumar Selvaraj

“…The influence of different data sources, including remotely monitored continuous vital signs and activity, on machine learning (ML) models’ performances is examined for predicting all-cause unplanned 30-day readmission. …”
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Supraglacial Lake Depth Retrieval from ICESat-2 and Multispectral Imagery Datasets by Quan Zhou, Qi Liang, Wanxin Xiao, Teng Li, Lei Zheng, Xiao Cheng

“…In this study, we present a machine learning-based method for estimating the depth of supraglacial lakes through the combination of ICESat-2 ATL03 data with multispectral imagery. …”
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Survey on Byzantine attacks and defenses in federated learning by ZHAO Xiaojie, SHI Jinqiao, HUANG Mei, KE Zhenhan, SHEN Liyan

“…Federated learning as an emerging distributed machine learning, can solve the problem of data islands. …”
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treeducken: An R package for simulating cophylogenetic systems by Wade Dismukes, Tracy A. Heath

“…This allows easier performance testing of methods and has potential applications in machine learning (ML) and approximate Bayesian computation (ABC) approaches.…”
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E-commerce Service Chatbot Application Design using KNN and Random Forest Methods by Fardan Zamakhsyari

“…In response to this need, the researcher has developed a chatbot application aimed at improving customer service, employing machine learning techniques with the KNN and Random Forest algorithms. …”
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Correlation Analysis between Exchange Rate Fluctuations and Oil Price Changes Based on Copula Function by Xiaodong Huang

“…Moreover, this paper improves some defects in the algorithm and combines some new learning frameworks in machine learning to generalize the copula function to a variety of learning models. …”
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Advances in Autism: a bibliometric analysis by Mehereen Chowdhury, Murdoc Gould, Latha Ganti

“…Institutions like Stanford University and McGill University demonstrate substantial research output, while authors such as Dennis Wall are prominent with contributions that make diagnosing Autism much more efficient with the use of AI. Keywords like "Machine learning", "Autism spectrum disorder", and “Children” dominate, reflecting ongoing efforts to leverage technology for ASD interventions. …”
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A systemic approach and multiscale data management. A ‘refrigerator’ case study by Paolo Marco Tamborrini, Eleonora Fiore

“…Many digital technologies, such as the Internet of Things, Artificial Intelligence and Machine Learning, could radically change the way of conceiving a design process, especially when they are used to retrieve essential information to define a problem, identify the requirements and support design decisions, all of which are typical of the pre-design phase. …”
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Sandy Soil Liquefaction Prediction Based on Clustering-Binary Tree Neural Network Algorithm Model by Yu Wang, Jiachen Wang

“…The neural network algorithm is a small sample machine learning method built on the statistical learning theory and the lowest structural risk principle. …”
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Implementation of the C4.5 Algorithm in Predicting the Interest of Prospective Students in Choosing Higher Education by Bambang Triraharjo, Prilian Ayu Minarni, Baskoro

“…In our contribution, we explain how Fuzzy c - means based machine learning can be used for oil data governance. This deep artificial intelligence concept, which we will use in addition to fuzzy logic, by applying Fuzzy c - means for good training can enable the decision-maker a better governance policy.…”
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Application of Intelligent Signal Reflection in the Communication Model of an Electronic Controller by Lan Lan

“…It combines the GAMP algorithm with machine learning, so it can achieve similar performance with much lower computational complexity than the traditional block sparse Bayesian learning algorithm. …”
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Use of Active Learning to Design Wind Tunnel Runs for Unsteady Cavity Pressure Measurements by Ankur Srivastava, Andrew J. Meade

“…In this work, the feasibility of an active machine learning technique to design wind tunnel runs using proxy data is tested. …”
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The Use of Big Data to Improve Human Health: How Experience From other Industries Will Shape the Future by Timothy E Hewett, Greg Olsen, Mark Atkinson

“…This commentary discusses what those differences are (Project vs Product Focus, Independent vs Integrated Efforts, Causality vs Prediction Driven, Statistical vs Machine Learning Centricity) why they exist, and the future convergence that we believe is on the horizon. …”
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Advancements, Trends and Future Prospects of Lower Limb Prosthesis by Muhammad Asif, Mohsin Islam Tiwana, Umar Shahbaz Khan, Waqar Shahid Qureshi, Javaid Iqbal, Nasir Rashid, Noman Naseer

“…This review presents for lower limb prosthesis; the study of lower limb amputation, design & development, control strategies & machine learning algorithms, the psycho-social impact of prosthetic users, and design trends in patents. …”
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A new and automated risk prediction of coronary artery disease using clinical endpoints and medical imaging-derived patient-specific insights: protocol for the retrospective GeoCAD... by Louisa Jorm, Daniel Moses, Dona Adikari, Ramtin Gharleghi, Shisheng Zhang, Arcot Sowmya, Sze-Yuan Ooi, Susann Beier

“…We propose a new risk prediction method predicated on CT coronary angiography (CTCA) data and state-of-the-art machine learning methods based on a better understanding of anatomical risk for CAD. …”
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Determination of the quantitative content of chlorophylls in leaves by reflection spectra using the random forest algorithm by E. A. Urbanovich, D. A. Afonnikov, S. V. Nikolaev

“…The article provides the analysis of the results, as well as recommendations for using this machine learning method to assess the quantitative content of chlorophylls in leaves.…”
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A Novel Convolutional Neural Network-Based Approach for Fault Classification in Photovoltaic Arrays by Farkhanda Aziz, Azhar Ul Haq, Shahzor Ahmad, Yousef Mahmoud, Marium Jalal, Usman Ali

“…An in-depth quantitative evaluation of the proposed approach is presented and compared with previous classification methods for PV array faults – both classical machine learning based and deep learning based. Unlike contemporary work, five different faulty cases (including faults in PS – on which no work has been done before in the machine learning domain) have been considered in our study, along with the incorporation of MPPT. …”
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Analysis and Recommendation of Outdoor Activities for Smart City Users Based on Real-Time Contextual Data by S. R. Mani Sekhar, D. M. Mushtaq Ahmed, G. M. Siddesh

“…This data are processed and interpreted using machine learning algorithms, which find correlations, trends, and patterns that affect outdoor activities. …”
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