A Secure and Robust Machine Learning Model for Intrusion Detection in Internet of Vehicles by Pradeep Kumar Tiwari, Shiv Prakash, Animesh Tripathi, Tiansheng Yang, Rajkumar Singh Rathore, Manish Aggarwal, Narendra Kumar Shukla

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Mathematical Validation of Proposed Machine Learning Classifier for Heterogeneous Traffic and Anomaly Detection by Azidine Guezzaz, Younes Asimi, Mourade Azrour, Ahmed Asimi

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On the Readiness of Scientific Data Papers for a Fair and Transparent Use in Machine Learning by Joan Giner-Miguelez, Abel Gómez, Jordi Cabot

“…Abstract To ensure the fairness and trustworthiness of machine learning (ML) systems, recent legislative initiatives and relevant research in the ML community have pointed out the need to document the data used to train ML models. …”
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Estimation of Acetic Acid Concentration from Biogas Samples Using Machine Learning by Lingga Aksara Putra, Bernhard Huber, Matthias Gaderer

“…The project aims to use NIR sensors and machine learning algorithms to estimate the acetic acid concentration in a biogas substrate based on the measured intensities of the substrate. …”
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Challenges and Prospects of Deploying AI and Machine Learning for Clinical Diagnosis in African Healthcare by Edmund Terem Ugar

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Improved cattle farm classification: leveraging machine learning and linked national datasets by Guy-Alain Schnidrig, Guy-Alain Schnidrig, Rahel Struchen, Sara Schärrer, Dagmar Heim, Daniela Hadorn, Gertraud Schüpbach-Regula, Giulia Paternoster

Subjects: “…machine learning…”
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Machine learning-driven solar irradiance prediction: advancing renewable energy in Rajasthan by Aayushi Tandon, Amit Awasthi, Kanhu Charan Pattnayak, Aditya Tandon, Tanupriya Choudhury, Ketan Kotecha

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Comment on “Early cancer detection by serum biomolecular fingerprinting spectroscopy with machine learning” by Ivan A. Bratchenko, Lyudmila A. Bratchenko

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Marigold: a machine learning-based web app for zebrafish pose tracking by Gregory Teicher, R. Madison Riffe, Wayne Barnaby, Gabrielle Martin, Benjamin E. Clayton, Josef G. Trapani, Gerald B. Downes

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Evaluation of Machine Learning and Ensemble Learning Models for Classification Using Delivery Data by İrem Karakaya

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Machine Learning-Based Detection of Anomalies, Intrusions, and Threats in Industrial Control Systems by Denis Benka, Dusan Horvath, Lukas Spendla, Gabriel Gaspar, Maximilian Stremy

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Machine learning analysis of rivaroxaban solubility in mixed solvents for application in pharmaceutical crystallization by Mohammed Alqarni, Ali Alqarni

Subjects: “…Machine learning…”
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Earthquake induced liquefaction hazard analysis for Chittagong City using machine learning by Md. Mehedi Hasan, Md. Zillur Rahman, Abul Kashem Faruki Fahim

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Classification of the optimal rebalancing frequency for pairs trading using machine learning techniques by Mahmut Bağcı, Pınar Kaya Soylu

“…This study proposes a machine learning (ML) approach to predict ORF ranges. To improve ML accuracy, pairs were categorized into three subgroups based on their correlation levels: positively, weakly, and negatively correlated. …”
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Forecasting CDS Term Structure Based on Nelson–Siegel Model and Machine Learning by Won Joong Kim, Gunho Jung, Sun-Yong Choi

“…Among the machine learning approaches, GMDH demonstrates the best performance in forecasting the CDS term structure. …”
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COVID-19 World Vaccination Progress Using Machine Learning Classification Algorithms by Nasiba M. Abdulkareem, Adnan Mohsin Abdulazeez, Diyar Qader Zeebaree, Dathar A. Hasan

Subjects: “…COVID-19 Vaccine, Machine learning, Classification algorithm, Dataset, weka…”
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A large synthetic dataset for machine learning applications in power transmission grids by Marc Gillioz, Guillaume Dubuis, Philippe Jacquod

“…Fast, essentially real-time computational approaches to evaluate their operational safety, stability and reliability are therefore highly desirable. Machine Learning methods have been advocated to solve this challenge, however they are heavy consumers of training and testing data, while historical operational data for real-world power grids are hard if not impossible to access. …”
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On Quantum Methods for Machine Learning Problems Part II: Quantum Classification Algorithms by Farid Ablayev, Marat Ablayev, Joshua Zhexue Huang, Kamil Khadiev, Nailya Salikhova, Dingming Wu

“…This second part of the review presents several classification problems in machine learning that can be accelerated with quantum subroutines. …”
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Novel models based on machine learning to predict the prognosis of metaplastic breast cancer by Yinghui Zhang, Wenxin An, Cong Wang, Xiaolei Liu, Qihong Zhang, Yue Zhang, Shaoqiang Cheng

“…We utilized prognostic factors to develop a novel machine learning model (CatBoost) for predicting patient survival rates. …”
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Prediction of the remaining useful life of a milling machine using machine learning by Abbas Al-Refaie, Majd Al-atrash, Natalija Lepkova

Subjects: “…Machine Learning…”
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