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A Survey of Teachers’ Status in Mental Health Education Management Based on Big Data Analysis
Published 2022-01-01Get full text
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A big data dynamic approach for adaptive music instruction with deep neural fuzzy logic control
Published 2025-01-01Get full text
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Personalized Travel Route Recommendation Model of Intelligent Service Robot Using Deep Learning in Big Data Environment
Published 2022-01-01“…Finally, the processed data is input into the trained recommendation model to generate a personalized tourism route recommendation scheme. …”
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NeuralACT: Accounting Analytics Using Neural Network for Real-Time Decision Making From Big Data
Published 2025-01-01“…This paper presents a deep neural network (DNN)-based accounting analytics, NeuralACT, to support the decision-making process using real-time predictions made from big data. It uses a Bidirectional Long Short-Term Memory (BiLSTM) network trained with Visegrad Group Companies (VGC) dataset customized and improved for accounting features prediction. …”
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Privacy-preserving approach for IoT networks using statistical learning with optimization algorithm on high-dimensional big data environment
Published 2025-01-01“…Privacy-preserving machine learning (ML) training in the development of aggregation permits a demander to firmly train ML techniques with the delicate data of IoT collected from IoT devices. …”
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Assessing the effects of therapeutic combinations on SARS-CoV-2 infected patient outcomes: A big data approach.
Published 2023-01-01“…<h4>Methods</h4>Gradient Boosted Decision Tree, Deep and Convolutional Neural Network classifiers were implemented and trained on the National COVID Cohort Collaborative (N3C) data repository to predict the patients' outcome of death or discharge. …”
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From awareness to action: investigating the impact of big-five teamwork model awareness on rationing of nursing care and patient-centered care
Published 2025-02-01“…Aim This study aimed to assess the impact of the Big Five Teamwork Awareness Sessions (Big 5TWAS) on the rationing of nursing care and patient-centered care. …”
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Dynamic Prediction Research of Silicon Content in Hot Metal Driven by Big Data in Blast Furnace Smelting Process under Hadoop Cloud Platform
Published 2018-01-01“…In order to explore a dynamic prediction model with good generalization performance of the content of [Si] in molten iron, an improved SVM algorithm is proposed to enhance its practicability in the big data sample set of the smelting process. Firstly, we propose a parallelization scheme to design an SVM solution algorithm based on the MapReduce model under a Hadoop platform to improve the solution speed of the SVM on big data sample sets. …”
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The Modern World Landscape of Data Science Online Education
Published 2022-04-01Get full text
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Spatiotemporal Variability of Channel Roughness and its Substantial Impacts on Flood Modeling Errors
Published 2024-07-01Get full text
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Harnessing Big Heterogeneous Data to Evaluate the Potential Impact of HIV Responses Among Key Populations in Sub-Saharan Africa: Protocol for the Boloka Data Repository Initiative
Published 2025-01-01“…ObjectiveThis study aimed to leverage and harness big heterogeneous data on HIV among KPs and harmonize and analyze it to inform a targeted HIV response for greater impact in Sub-Saharan Africa. …”
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Multi-view Clustering: A Survey
Published 2018-06-01“…In the big data era, the data are generated from different sources or observed from different views. …”
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Two-centers machine learning analysis for predicting acid-fast bacilli results in tuberculosis sputum tests
Published 2025-02-01Get full text
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Machine learning of swimming data via wisdom of crowd and regression analysis
Published 2017-03-01Get full text
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Digital Horizons in Teacher Education Development
Published 2020-07-01Subjects: Get full text
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Social exclusion as a side effect of machine learning mechanisms
Published 2023-02-01“…Neurotraining understood as the principles of any neural networks’ training. Social exclusion and the resulting discrimination in decisions made by artificial intelligence is considered as a consequence of the big data processing principles. …”
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Understanding the reliability of citizen science observational data using item response models
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