BioPipeline Creator—a user-friendly Java-based GUI for managing and customizing biological data pipelines by Cléo Maia Cordeiro, Gislenne da Silva Moia, Mônica Silva de Oliveira, Lucas da Silva e Silva, Maria Paula Cruz Schneider, Sávio S. Costa, Rafael Azevedo Baraúna, Diego Assis das Graças, Artur Silva, Adonney Allan de Oliveira Veras

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Railway traffic characterisation data based on weigh-in-motion and machine learning: A case study in PortugalZenodo by Idilson A. Nhamage, Cláudio S. Horas, José A. Campos e Matos, João Poças Martins

“…However, identifying train types in these data is often a manual and laborious task, with this information being crucial not only for structural assessment, such as fatigue analysis, but also for broader considerations within the railway sector, including economic and social impacts. …”
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Blockchain Enabled Secure Medical Data Transmission and Diagnosis Using Golden Jackal Optimization Algorithm with Deep Learning by Kiruthikadevi Kulandaivelu, Sivaraj Rajappan, Vijayakumar Murugasamy

“…Abstract The incorporation of deep learning (DL) and blockchain (BC) technologies in healthcare revolutionizes disease diagnoses and improves data security. The tamper-resistant and decentralized nature of BC safeguards the integrity and confidentiality of medical records, alleviating the risk of any unauthorized access. …”
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Forest Fire Hazard Assessment using Remote Sensing Data and Machine Learning, Case Study of Jijel, Algeria by Matougui Zakaria, Zouidi Mohamed

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Limited data based kinetic modeling and optimization of propionic acid synthesis over supported Rh/C catalyst by László Balogh, Jenő Bódis, Botond Szilágyi, Ágnes Bárkányi, Attila Egedy

“…The data were not primarily measured for modeling, but for parametric reactor analysis. …”
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Characterization of Power System Oscillation Modes Using Synchrophasor Data and a Modified Variational Decomposition Mode Algorithm by José Oscullo Lala, Nathaly Orozco Garzón, Henry Carvajal Mora, Diego Echeverria, José Vega-Sánchez, Takaaki Ohishi

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Data driven fuel consumption prediction model for green aviation using radial basis function neural network by Yuandi Zhao, Zhongyi Wang, Xiaohui Wang, Ye Song, Yuzhe Han

“…The model provides a lightweight and computationally efficient solution for high-dimensional, nonlinear flight data, ensuring accuracy with lower computational burdens. …”
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Deep Learning‐Based 3D Microseismic Event Direct Location Using Simultaneous Surface and Borehole Data by Yuanyuan Yang, Omar M. Saad, Tariq Alkhalifah

“…It is also able to effectively model the complicated dynamics from the moveout patterns of microseismic energy to responsible source locations, and the concerted interactions of these moveout signatures across various sensor layouts. The statistical analysis on results from synthetic passive seismic data demonstrates the efficacy of the method. …”
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THE RESULTS OF SURGICAL TREATMENT OF PATIENTS WITH MULTIPLE PRIMARY LUNG CANCERS ACCORDING TO ORENBURG REGIONAL ONCOLOGICAL CLINIC DATA by E. A. Kalinin, M. A. Senchukova, M. N. Vasukov, P. V. Samoilov, S. O. Mitryakov, S. V. Pinchuk

“…Clinical and morphological data, results of instrumental studies, immediate and long-term treatment results were analyzed. …”
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Developing a Prediction Model for Real-Time Incident Detection Leveraging User-Oriented Participatory Sensing Data by Md Tufajjal Hossain, Joyoung Lee, Dejan Besenski, Branislav Dimitrijevic, Lazar Spasovic

“…Traditional methods relying on stationary technologies are often costly and provide limited coverage, prompting the exploration of crowdsourced data such as Waze. While Waze offers extensive coverage, its data can be unverified and unreliable. …”
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An Improved Processing Method for Low-Frequency Spaceborne Full-Polarimetric SAR Data Affected by Ionospheric Faraday Rotation by Xun Wang, Yunhua Zhang, Dong Li

“…This article develops an improved processing method for low-frequency spaceborne FP SAR data affected by FR in the presence of additive noise to generate the 3 × 3 coherency matrix (CM) used for polarimetric analysis. …”
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Normative and Equated Data of the Original and Basic Versions of the Montreal Cognitive Assessment among Community Dwelling Saudi Arabians by Taim A. Muayqil, Nada K. Alamri, Awyshah M. Alqahtani, Sarah S. Julaidan, Raya Alsuhaibani, Ibrahim Nafisah, Walid A. Alkeridy, Bandar N. Aljafen, Mohammed H. Alanazy

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XGBoost-based machine learning model combining clinical and ultrasound data for personalized prediction of thyroid nodule malignancy by Wenhan Li, Wenhan Li, Yajing Zhou, Ziyu Luo, Ziyu Luo, Miao Tan, Miao Tan, Rui Yin, Jianhui Li, Jianhui Li

“…Furthermore, six ML models (KNN, Logistic Regression, RF, Classification Tree, SVM, and XGBoost) were developed and validated via 10-fold cross-validation, evaluating performance using area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, calibration curves, and decision curve analysis (DCA).Results17 variables were influential factors for diagnosing TNs. …”
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Catheter‐Based Renal Denervation for Resistant Arterial Hypertension: 10‐Year Real‐World Follow‐Up Data by Sofie Brouwers, Giulia Botti, Matthias Verbesselt, Lucio Addeo, Marta Belmonte, Kostas Bermpeis, Dario Tino Bertolone, Chiara Valeriano, Michele Mattia Viscusi, Eric Wyffels

“…ABSTRACT This analysis of real‐world data examines the efficacy, safety, and long‐term outcomes of renal denervation in hypertensive patients for up to 10 years. …”
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Machine learning approaches for predicting frailty base on multimorbidities in US adults using NHANES data (1999–2018) by Teng Li, Xueke Li, Haoran XU, Yanyan Wang, Jingyu Ren, Shixiang Jing, Zichen Jin, Gang chen, Youyou Zhai, Zeyu Wu, Ge Zhang, Yuying Wang

“…Methods: This cross-sectional study utilized data from the National Health and Nutrition Examination Survey (1999–2018). …”
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Predictive model for sarcopenia in chronic kidney disease: a nomogram and machine learning approach using CHARLS data by Renjie Lu, Shiyun Wang, Pinghua Chen, Fangfang Li, Fangfang Li, Pan Li, Qian Chen, Xuefei Li, Fangyu Li, Suxia Guo, Jinlin Zhang, Jinlin Zhang, Dan Liu, Zhijun Hu

“…Model accuracy was evaluated using calibration curves, while predictive performance was assessed through receiver operating characteristic (ROC) and decision curve analysis (DCA). …”
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Advancing digital soil mapping with multi-year crop cover data: Impacts on model accuracy and soil interpretation by Babak Kasraei, Margaret G. Schmidt, Daniel D. Saurette, Chuck E. Bulmer, Jin Zhang, Travis Pennell, Kingsley John, Brandon Heung

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Analysis of Water Loss Management Performance of Water Utilities and Development of Basic Performance Indicator Analysis Tool by Mahmut Fırat, Cansu Orhan, Salih Yılmaz, Özgür Özdemir

“…The details of this tool were detailed, its advantages were discussed by analyzing of sample data set. It is believed that this analysis tool developed in this study will provide significant contributions to the analysis and monitoring of the performance of the Utilities in terms of water loss management and its components, and to evaluate the process performance for active leakage control activities…”
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Design of a novel noise resilient algorithm for fault detection in wind turbines on supervisory control and data acquisition system by Muhammad Irfan, Nabeel Ahmed Khan, Muhammad Abubakar, Zohaib Mushtaq, Tomasz Jakubowski, Paweł Sokołowski, Grzegorz Nawalany, Saifur Rahman

“…The following study explores the application of Supervisory Control and Data Acquisition (SCADA) data for fault detection and diagnosing different operational states in wind turbines by focusing on environmental and operational factors which affect the performance. …”
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Racio analysis of companies in the textile industry of Serbia: Comparison of financial results with online and offline scope of work by Đalić Tamara, Vesić Anđela, Cvetković Dragan

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